text:
Blackpool detective dies after valiant three-year fight with motor neurone disease
Morecambe charity Unique Kidz and Co raise over £11,000 at first fundraiser held for two years due to the Covid pandemic
Morecambe charity for disabled children Unique Kidz and Co held their annual charity ball at The Villa Levens and raised £11,472.31 on the night.
By Michelle Blade
Monday, 1st November 2021, 12:47 pm
Updated Monday, 1st November 2021, 12:48 pm
Guests at the Unique Kidz and Co charity ball enjoying entertainment by Amber Sax. Picture by Nick Hellier Photography.
The event was attended by over 140 guests and was sponsored by Lid Assist, a local company providing wheelie bin lid solutions and recently seen on BBC's The Customer is Always Right.
Jordan Halpin, head of fundraising said: "Once again we were blown away by the generosity shown from our local community and businesses who supported us.
"After a long two years with no fundraising events, it was lovely to be back celebrating what we do at Unique Kidz and Co and raising lots of money and awareness that will help us to continue providing our vital services for disabled children and young adults."
Young adults from Unique Kidz and Co and their parents. Left to right Kathryn, Rebecca, Jared, Samantha. Picture by Nick Hellier Photography.
"We would like to say a huge thank you to all our guests for joining us and making the evening one we will never forget."
Guests enjoyed a drinks reception, sponsored by Lid Assist, a three course meal, entertainment by Amber Sax and PC Roadshows, photos by Nick Hellier Photography and stunning decorations by Poppins Parties and Events.
Guests were also treated to a sign and dance performance by some of the young adults who used the charity's services.
The charity was founded in 2009 by Jane Halpin from Bolton-le-Sands and Denise Armer from Warton; two mums who had struggled for years to find any childcare that was suitable for their disabled children.
The Taylor Family at the Unique Kidz and Co charity ball. Picture by Nick Hellier Photography.
Nine years later, the charity now runs from its own building in Morecambe and supports more than 130 children and young adults.
In addition to its original services of the specialist afterschool and holiday clubs, the charity now also runs '4Ever Unique', a daytime support service
for young adults aged 16-25 with disabilities, Stay and Play, a group that meets twice a week and supports children under the age of 5, and a Siblings Group that runs twice a month.
The money raised will go towards continuing the vital work that the charity provides.
Denise Armer, co-founder of Unique Kidz and Co said: "After purchasing our building this year, it was brilliant to get together and celebrate. It means so much to have such amazing support and we are looking forward to lots more fundraising events coming up soon!"
A massive thank you from all at Unique Kidz and Co to everyone who attended and supported the event helping to make the evening such a success!
If you would like to support Unique Kidz and Co, please email [email protected]
MorecambeBBC


WHAT'S UP IN WILMYWOOD – 05/30/2013 – Homicide Investigation points finger at Dan Aykroyd.
A Homicide Investigation points a finger at Dan Aykroyd. A landfill worker uncovered film of Dan Aykroyd standing over a bloody corpse. The man in Canada turned it in to police, thinking he stumbled upon murder evidence caught on film. Turns out it was a scene was from the 1990 flick, "Loose Cannons." Aykroyd was last seen Wednesday at the Blue Post signing his Crystal Head Vodka. His cast members of Tammy are getting a late start shooting into the very late hours in Shallotte at "The Grille" on Main St. today.
Back in 1989, Wilmywood was the home for the movie, Dream a Little Dream, starring the "Coreys." Corey Feldman had a say about wardrobe and used his own, very expensive black jacket. Well, that jacket was stolen. Now over 20 years later, it was finally recovered at a Boston Flea Market and was returned to Corey. Feldman said it's worth $100,000. Some of the locations used in Dream a Little Dream include: New Hanover High, Thalian Hall, the old Roy's Riverboat Landing, the house at 1705 Princess St.
We have yet another reason to be grateful for NBC's Revolution shooting its first season in Wilmywood. The series brought in over $50 million to the state. The Wilmington Regional Film Commission says an estimated $56 million was spent – wages earned/taxed in NC along with goods and services bought and taxed. Don't forget the season finale is Monday at 10:00pm EST.
Under the Dome is getting a late morning start in Currie NC. Our own sports star, baseball player Trot Nixon will be inducted into Wilmington Walk of Fame today.


text:
100 Years Devoted to Fresh Louisiana Pecans
Horace Joseph Bergeron began his career as a merchant and carried on the family tradition of planting and farming. In 1910, He purchased a small "shotgun" house for the locals to come trade or hand crack pecans in exchange for merchandise and food items. 5 cents a pound was the going rate. This process all changed in 1941 when Bergeron's sons saw the need to modernize the process.
H.J. Bergeron Pecan Shelling Plant in New Roads, Louisiana
A Modest Beginning
Born in 1890 near New Roads, Horace Joseph Bergeron was of early French ancestry and raised in the heart of Louisiana. Beginning his career as a merchant, Horace opened a small country merchandise store along False River in 1909. He soon began profiting from pecans and purchased a small house for local families to sell or trade their pecans in exchange for merchandise in his store. The company flourished as HJ Bergeron's two sons grew the business alongside their father.
A Need for Expansion
In 1941, Horace's sons opened a premium pecan shelling plant equipped with the best machinery available. HJ Bergeron Pecan Shelling Plant soon became firmly established on a national level as shellers and packers of quality pecans. However, it wasn't until after WWII that the company really came into full bloom in marketing one of Louisiana's most popular commodities.
Continued Growth
Over time, the company added modern equipment, expansions, and other improvements to earn their shelling plant the title of Highest Quality Pecans from the United States Pecan Shelling Association. Today, the company processes 5 - 7 million pounds of in-shell pecans a year. Currently led by the third generation of Bergerons, our company continues to support the community by purchasing our pecans from local growers and farmers.
Dedication to the Future
HJ Bergeron Pecan Company's longevity is due to the devotion of our workforce and their passion for the company. Many people and families have worked for us for decades. HJ Bergeron Pecan Company owes its success to these dedicated employees. Families such as the Swindlers, Ladmairaults, and Aguillards all play an important role in the high quality of pecans that our company is able to consistently provide. With dedicated people like these standing behind us, HJ Bergeron Pecan Company will continue to grow in its achievements and success.

redpajama_set_name: RedPajamaCommonCrawl


text:
In order to optimize our website for you and to continuously improve it, we use cookies. By continuing to use the website, you consent to the use of cookies. For more information on cookies, please refer to our Privacy Policy.
Topics & Ideas
Strategie & Transformation New Work & Collaboration Cybersecurity & Compliance Data & Business Analytics Customer Experience HR & Employee Experience Logistik & Supply Chain IoT & Machine Learning Intelligentes ERP & SAP S/4HANA Managed Cloud Services
About us Management Corporate & Investor Relations News & Press Partners International Engagement Locations Integrity Line
Strategie & Transformation Strategy and transformation projects for companies and teams looking to become agile, curious organisations.
New Work & Collaboration A world of work, where productivity, teamwork and agility is unleashed and that is attractive to employees and talent.
Cybersecurity & Compliance Maintain compliance requirements and protect the data - and reputation - of your company.
Data & Business Analytics Navigation instruments for efficient management processes based on your data and, increasingly, with a help from AI.
Customer Experience Design ideal customer experiences, attract customers and promote lasting customer loyalty to a digital world.
HR & Employee Experience The employees you need are creative and ready for innovation. It is HR's job to recruit, retain and develop these people.
Logistik & Supply Chain Leverage new technologies to plan, manage and optimise your supply chain and how you can enhance your supplier and customer network.
IoT & Machine Learning Use new technologies to improve or automate processes - or tap into new business models.
Intelligentes ERP & SAP S/4HANA A high-performance ERP is at the digital heart of every networked, intelligent company with smart processes.
Managed Cloud Services Your IT organisation is focussed on providing services for your specialist departments. We take over your resource-intensive IT operations.
Corporate & Investor Relations
Startpage Company News & Press Half-Year Financial Report as at 31 March 2014 / All for One Steeb
Half-Year Financial Report as at 31 March 2014 / All for One Steeb
Dear Shareholders, Ladies and Gentlemen: We successfully finished the first 6 months of the financial year 2013/14 with a growth in revenues of 24% to EUR 109.1 million and a 49% increase in EBIT to EUR 7.4 million. The EBIT margin for the period of October 2013 to March 2014 improved from 5.6% to 6.8%. Whereas in the first half-year 2012/13 we reported a decline of 9% in what are by their very nature volatile licensing sales, we were able to increase these by 67% in the current reporting period and post licensing revenues in the amount of EUR 17.9 million.
Filderstadt, 15 May 2014 – »The customer comes first, second and third« is a principle that our employees also fully accept and support. As »the company for people who want to get things done«, we have built a strong employer brand with a distinctive identity, unmistakable culture and values that are faithfully put into practise. »We'll celebrate our 1,000th employee with 1,000 litres of free beer at the next garden party, college graduation gala, or farewell get-together at his or her former employer« was the theme of our recruitment campaign that on 28 February 2014 helped us achieve the milestone of bringing our thousandth employee (including apprentices and trainees) on board. The small-business magazine Markt + Mittelstand acclaimed this campaign as the »Idea of the Month«. Our employees voted us one of Germany's »Best Employers in ICT 2014« as part of the respected Great Place to Work Institute's survey. The news magazine FOCUS also ranked All for One Steeb one of the »Best Employers in Germany« from among the 800 companies from 22 industries surveyed (FOCUS Spezial, February 2014).
We supplement our vigorous organic growth with a buy & build strategy designed to further strengthen our business model. Following the acquisition and integration of Steeb (2011/12), OSC, selected assets of ORGA, WEBMAXX (2012/13) and the enlargement of our shareholdings in KWP (2013/14), we see in the acquisition of avantum consult AG, Düsseldorf, the opportunity of also taking a top spot in the overall market for enterprise performance management and business analytics. Shareholders also benefit from such good developments, as witnessed by the annual general meeting of 27 March 2014 approving a dividend of 50 euro cents per share (prior year: 15 euro cents per share). Despite this strong first half-year, we remain committed to our existing forecast for the financial year 2013/14.
We regularly release information about new developments in the company in the intervals between our quarterly reports. Shall we send this information directly to you? If so, you can sign up to receive such news in the Investor Relations section of our website www.all-for-one.com.
Lars Landwehrkamp, CEO
Stefan Land, CFO
info@all-for-one.com +49 711 788 07-0
COPYRIGHT © 2019 ALL FOR ONE GROUP ALL RIGHTS RESERVED
Imprint Privacy policy Legal information Compliance


We will be offering up exciting live demos on an 85" screen by our CEO Jason Briggs featuring FIN Stack, FIN Mobile, and all of their new features.
In addition to these demos we'll be introducing a new FIN Certified embedded server.
You'll be able to participate in a training simulator panel and check out some of the members of our FIN Community like Intellastar, KMC, Contemporary Controls, and EasyIO.
See you there! Watch the video below to see what you're in for when you come visit our booth.


text:
The following is a list of the oldest hospitals in the United States, containing extant hospitals in the United States established prior to the year 1900. The dates refer to the foundation or the earliest documented contemporary reference to the hospital.

Hospitals

Eighteenth century

Nineteenth century

See also
History of medicine in the United States

References

Oldest
History of medicine in the United States

redpajama_set_name: RedPajamaWikipedia


Zhongxin machine, let the machine change the future!
Note lubrication equipment, since the adhesive wear between river gravel vertical shaft impact crusher making machine parts, abrasive wear, surface fatigue wear and corrosion wear, etc., and lubrication conditions. The oil was added in the lubricant extreme pressure and anti-wear additives, can effectively reduce the surface adhesive wear and fatigue wear.
Regular river gravel vertical shaft impact crusher making machine to make adequate downtime, and to regularly observe the internal wear of the crusher, the central feed tube, cone cap on the impeller, obscene Road liner circumference shield, wear block the degree of wear, if worn should be replaced or repaired should be replaced at the same time replace wearable pieces, wearable pieces to ensure that the same weight. Note also that the crusher normal course of their work is never open to observe in order to avoid the risk of accidents.
If the river gravel vertical shaft impact crusher making machine parts inside loose, resulting in unstable operation of the device. If parts falling off in the crushing cavity, impact crusher will cause abnormal noise and vibration at work. So we have to regularly check each part is loose, if found to be loose fastening timely.
write down your requirement and contact details in the following form to get the latest price of this product within one day!
Subscribe now,you will receive monthly valuable information.


text:
Capital Link's Blog
Natalie Handy
New Rural FQHC Resources
Capital Link has just released three new resources that focus specifically on Federally Qualified Health Centers (FQHCs) that serve rural communities. Located in all 50 states and territories, rural FQHCs are the healthcare safety net in many parts of the rural US. They provide comprehensive primary care and other critical health services including dental, prenatal care, and mental and behavioral health to rural residents, including immigrants and communities of color. Rural FQHCs also often serve as major employers in their communities.
Financial Impact of COVID-19 on Rural Federally Qualified Health Centers
A new report from Capital Link illustrates how the pandemic has financially impacted health centers that serve rural communities. Results show that the nation's more than 608 rural Federally Qualified Health Centers (FQHCs) have experienced a 25% decline in patient visits between April and December 2020, as patients complied with stay-at-home orders. After taking into account federal relief funding, rural FQHCs experienced net losses of $1.1 billion. Without additional support to cover the identified shortfall through June 2021, many health centers sites will remain closed, 7,121 staff may be laid off or furloughed, and 35% of FQHCs may drain cash reserves to dangerous levels. VIEW REPORT >
FQHC Roles and Opportunities Related to Rural Hospital Distress and Closure
This publication provides a high-level examination of the lived experiences of FQHCs that serve rural communities, particularly in the context of rural hospital financial distress and closure. Utilizing a recently conducted national assessment of rural FQHCs, it seeks to document health centers' experiences with hospital distress and closure over the past five years and to evaluate the extent to which these centers have and can play an instrumental role in preserving access to care under these difficult circumstances. VIEW PUBLICATION >
Rural Federally Qualified Health Centers Financial and Operational Performance Analysis 2016-2019
This report provides an aggregate financial and operational profile of rural Federally Qualified Health Centers. It offers a framework for identifying the financial strengths, challenges, and benchmarks that support opportunities for rural FQHC performance improvement through an examination of multi-year trends and median results. The report also provides comparisons between rural, urban, and national performance, as well as recommended benchmarks, where available. VIEW ANALYSIS >


text:
A Combined Satellite-Derived Drought Indicator to Support Humanitarian Aid Organizations
Tropical Forest Fire Susceptibility Mapping at the Cat Ba National Park Area, Hai Phong City, Vietnam, Using GIS-Based Kernel Logistic Regression
10.3390/rs8040348
Academic Editors
Richard Gloaguen
Prasad S. Thenkabail
Nagler, T.
Rott, H.
Ripper, E.
Bippus, G.
Hetzenecker, M.
Advancements for Snowmelt Monitoring by Means of Sentinel-1 SAR
Thomas Nagler
Helmut Rott
Elisabeth Ripper
Gabriele Bippus
Markus Hetzenecker
ENVEO IT GmbH, Technikerstrasse 21a, A-6020 Innsbruck, Austria
Institute of Atmospheric and Cryospheric Sciences, University of Innsbruck, A-6020 Innsbruck, Austria
Remote Sens. 2016, 8(4), 348; https://doi.org/10.3390/rs8040348
Received: 24 February 2016 / Revised: 6 April 2016 / Accepted: 11 April 2016 / Published: 20 April 2016
The Sentinel satellite constellation series, developed and operated by the European Space Agency, represents the dedicated space component of the European Copernicus program, committed to long-term operational services in environment, climate and security. We developed, tested and evaluated an algorithm for generating maps of snowmelt area from C-band synthetic aperture radar (SAR) data of the Sentinel-1 mission. For snowmelt classification, a change detection method is applied, using multitemporal dual-polarized SAR data acquired in Interferometric Wide swath (IW) mode, the basic operation mode over land surfaces. Of particular benefit for wet snow retrievals are the high instrument stability, the high spatial resolution across the 250 km wide swath, and the short revisit time. In order to study the impact of polarization, we generated maps of melting snow using data of the VV-polarized channel, the VH-polarized channel and a combined VV- and VH-based channel using a weighting function that accounts for effects of the local incidence angle. Comparisons are performed with snow maps derived from Landsat images over study areas in the Alps and in Iceland. The pixel-by-pixel comparisons show good agreement between the snow products of the two sensors, with the best performance for retrievals based on the combined (VV and VH) channel and a minor decline for the VH-based product. The VV-based snowmelt extent product shows a drop-off in quality over areas with steep terrain because of the decreasing backscatter contrast of snow-covered versus snow-free surfaces on fore-slopes. The investigations demonstrate the excellent capability of the Sentinel-1 mission for operational monitoring of snowmelt areas.
Sentinel-1; SAR; snow extent; snowmelt; Alps; Iceland
The Sentinel satellite constellation series represents the dedicated space component of the European Earth observation program Copernicus, previously known as GMES (Global Monitoring for Environment and Security) [1]. Copernicus, coordinated and managed by the European Commission, provides global, timely and easily accessible information and services in application domains such as land, marine, atmosphere, emergency management, climate change and security [2]. In the final deployment stage, each of the six Sentinel missions that were developed and operated by the European Space Agency (ESA), comprises two satellites in order to fulfill the revisit and coverage requirements for a wide range of operational applications.
Sentinel-1A, the first dedicated satellite of the Copernicus program, was launched on 3 April 2014. The Sentinel-1 (S1) satellites are equipped with a C-band synthetic aperture radar (SAR) [3]. The Sentinel-1 mission objectives include land monitoring of forests, water, soil and agriculture, marine monitoring (sea state, sea ice, icebergs, oils spills, vessel detection), monitoring of ice sheets, glaciers, snow cover, lake and river ice, emergency response applications (floods, geohazards, terrain deformation), and climate change monitoring [3,4]. In order to meet the observation requirements for this breadth of applications, the Sentinel-1 SAR instrument supports four operational imaging modes providing different spatial resolution and coverage: the Interferometric Wide swath (IW) mode, the Extra Wide swath (EW) mode, the Strip-Map (SM) mode, and the Wave (WV) mode [3,4]. In the field of cryosphere applications, the capabilities of the Sentinel-1 SAR EW data for operational sea-ice and iceberg monitoring have already been demonstrated [5], and the feasibility and performance of ice sheet wide surface velocity mapping with IW mode data has been shown for Greenland [6].
In the cryosphere domain, C-band SAR is also a main tool for mapping and monitoring the extent of wet snow areas. We developed, tested and validated an algorithm for retrieving snowmelt areas from S1 IW mode data, which is the nominal operation mode for land areas [7]. Monitoring of the snowmelt area has been identified as an important S1 application over land areas [4,8]. Previously, C-band SAR data of the European satellites ERS-1, ERS-2 and Envisat, and of the Canadian RADARSAT missions have been applied for mapping and monitoring snowmelt area for scientific studies and for hydrological applications at regional scale, e.g., [9,10,11,12,13,14,15]. The Sentinel-1 mission, with its systematic and long-term acquisition strategy and high duty cycle of the SAR sensor, enables high resolution operational snow cover monitoring over large areas at short revisit intervals. Here, we describe the method and workflow for generating maps of snowmelt area from S1 SAR data and present examples for the European Alps and Iceland. This work paves the way for an operational snow cover monitoring service within the Copernicus program, a precursor of which has been implemented within the project CryoLand of the 7th Framework Programme for Research and Technological Development of the European Union [16].
2. Data Characteristics
Observational requirements for satellite-based snowmelt area products for operational hydrology and climate research range from 100 m to 500 m spatial resolution and one day to five day revisit time, depending on the application [8,17]. The data requirements in terms of spatial and temporal resolution can be fulfilled by S1 SAR operating in IW mode. The main characteristics of S1 IW mode data are summarized in Table 1.
The Sentinel-1 spacecraft, operating in near polar sun-synchronous orbit at 693 km height, provides highly accurate pointing knowledge and real time orbit determination, resulting in very high geolocation accuracy of the SAR products [3,18]. The orbit repeat cycle is 12 days. Sentinel-1B will have the same reference orbit as Sentinel-1A with a 180-degree orbital phasing difference. Six day exact repeat pass observation will be achieved with the two-satellite constellation. The repeat coverage in mid-latitudes will be two to three days using adjoining swaths.
The S1 SAR operates at a center frequency of 5.4 GHz. IW mode data over Europe, used for this study, were acquired in dual polarization (VV and VH). The IW mode is operated as TOPS (Terrain Observation with Progressive Scans in azimuth) mode, providing a swath width of 250 km at a nominal ground resolution of 5 m × 20 m for single look data and offering enhanced image performance compared to the conventional ScanSAR mode [3]. Each image swath in IW mode is composed of three sub-swaths. Individual swaths are subdivided into slices of about 350 km length along track. The evaluation of signals from corner reflectors and transponders yields, for IW mode SLC data, a spatial resolution of 22 m in azimuth and of 2.84 m, 3.10 m, and 3.50 m in LOS for sub-swath IW1, IW2, and IW3, respectively [18].
Level-1 data (swath-based SAR images) are available in two main categories: Single Look Complex imagery (SLC) and Ground Range Detected imagery (GRD). GRD products consist of focused SAR data that have been detected, multi-looked and projected to ground range using an Earth ellipsoid model [19]. We use SLC images for generating the snow cover product, in order to exploit the original backscatter statistics for speckle filtering and classification, and to perform terrain-corrected geocoding using high resolution digital elevation models (DEMs). The geolocation accuracy of IW SLC products is 1.5 m in LOS and 2.5 m in azimuth [20].
The analysis of S1A products indicates better radiometric performance than the threshold values specified in the mission requirements [21]. The noise equivalent sigma-0 ( N E S Z ) values for the cross-polarized channels range from −24 dB to −30 dB, depending on the antenna off-boresight angle. The standard deviation of the radar cross section measured over transponders and corner reflectors ranges from 0.34 to 0.56 dB.
For comparisons and evaluation of the S1 snow products, we derived snow maps from terrain corrected images of the Landsat-7 and Landsat-8 [22] missions using the visible and shortwave infrared channels with 30 m pixel size. The Landsat data were downloaded from USGS as L1T data being radiometrically calibrated and rectified in UTM projection. The absolute geolocation error of the terrain corrected Landsat-8 data is 18 m [23].
The reduced backscattering coefficient ( σ 0 ) of wet snow compared to surfaces that are snow-free or covered by dry snow provides the basis for mapping snowmelt areas [9,10,11,12,13,14,15]. Due to the high dielectric losses of water, σ 0 of snow decreases with increasing liquid water content [24,25,26]. The typical C-band one-way penetration depth of dry seasonal snow is about 20 m, whereas for wet snow with liquid water content of 5% by volume, it is only 3 cm [25]. Whereas for wet snow the radar signal at C- and X-band frequencies is reflected and scattered at the surface and within the uppermost centimeters of the snowpack, in the case of dry seasonal snow, a main part of the observed signal is contributed by the snow/ground interface. Consequently, the contrast in backscatter intensity of dry snow areas and snow-free surfaces is small and not suitable for reliable mapping of dry snow. The combined use of optical sensors and SAR enables the mapping of total snow area and the monitoring of the temporal dynamics of snowmelt [14].
The backscatter intensity of wet snow packs is subject to temporal variations, which may affect the snow retrievals. Refreezing of the surface layer, for example during a cloudless night, causes an increase in σ 0 due to the high scattering albedo of the frozen layer [27,28]. This results in a decrease in the contrast of snow versus snow-free surfaces. Backscatter theory and experimental data show that this effect is less pronounced at C-band than at X-band because of the smaller scattering efficiency and the better penetration through the frozen layer at the longer wavelength [28].
Another issue that plays a role for snow retrievals is the angular dependence of backscatter. The backscatter contrast between melting snow and snow-free surfaces changes with the local incidence angle of the radar beam, which refers to the normal surface. For co-polarized backscatter, the contrast in σ 0 decreases significantly towards low incidence angles because of a comparatively strong rise of the backscatter signal of wet snow surfaces [25,29]. Cross-polarized backscatter shows less angular dependence, maintaining a clear difference between wet snow and snow-free surfaces also at low incidence angles. On the other hand, at high incidence angles cross-polarized backscatter may approach the noise floor. For these reasons, it is advisable to use both the co- and the cross-polarized channel for snow retrievals if available.
3.1. Classification Algorithm
Change detection procedures are commonly applied for retrieving snowmelt areas from SAR backscatter images [9,10,11,12,13,14]. This is an efficient means for reducing the impact of topography. The ratio of backscatter intensity of the SAR image with melting snow ( σ s n o w 0 ) versus a reference image ( σ r e f 0 ) of the same satellite track is computed for detecting the reduced backscatter signal of melting snow areas. Threshold-based segmentation is applied to separate snow-covered and snow-free surfaces. Preferably, the reference image is the average of multiple SAR images from dates with surfaces that are snow-free and/or covered by dry snow. Stacking multiple images reduces speckle and helps to suppress the impact of temporal variations in backscatter in the reference scenes.
As a first step in the processing line, the snow image and reference images in radar geometry (Figure 1) are calibrated to radar brightness [18] and precisely co-registered to a pre-selected master image of the same track, using the orbit data and a DEM [30]. Due to the high accuracy of the S1 orbit data, geolocation at sub-pixel accuracy is achieved [20]. In the next step, the speckle-related uncertainty is reduced by applying a multichannel SAR intensity filter [31]. This filter optimally reduces speckle while preserving the intensity and spatial resolution of the individual channels. In the filtering process, M new images J k are produced by linearly combining M co-registered intensity images I i , with 1 ≤ i ≤ M . For intensity images with the same number of looks, L , the following formulation for the filter is valid [31]:
J k = σ k M ∑ i = 1 M I i σ i , 1 ≤ k ≤ M
where σ k is the intensity in channel k of the filtered image, and σ i is the mean intensity in the channel i of the unfiltered image. The mean intensity in the filtered images is unbiased while the loss in spatial detail is minimal. An estimate of the local mean intensity is obtained by averaging the intensity values in a local window around each pixel. We apply the filter over windows of 7 × 7 pixels, using the stack of multi-temporal SLC images in the two polarizations. If all pixels in a window with N pixels are spatially uncorrelated, the resulting equivalent number of looks, E N L , in the filtered image is:
E N L = M N L M + N − 1
Taking into account the difference in spatial resolution of the IW mode data in LOS and azimuth, we perform block averaging over 16 × 4 (LOS × azimuth) pixels of the SLC images before applying the multichannel filter. The averaged pixels have a size of about 55 m in azimuth and 58 m in ground range at 40° incidence angle. We estimated the equivalent number of looks by extracting the mean and variance of intensity over distributed targets with uniform surface properties extending over several hundred pixels. For the 16 × 4 block averaged pixels, the E N L is 26. Applying the multichannel intensity filter increases E N L significantly while maintaining the pixel size. Using one snow image and one reference image (dual channel each) we obtain after filtering E N L = 106 , and, using three reference images, E N L = 202 . For the reference images, further speckle reduction is achieved by using averages compiled from backscatter images of multiple dates.
The σ 0 -ratio of the snow image versus the reference image is computed separately for the VV and VH channels and transformed to a logarithmic scale (dB). The statistical analysis shows a comparatively high degree of correlation between the VV and VH ratio images, with typical values of the correlation coefficient ( ρ ) of 0.85 ≤ ρ ≤ 0.90 for different study areas. This suggests that the two-dimensional feature space, spanned by the VV and VH ratio channels, can be reduced to a one-dimensional ratio image before performing the segmentation. For fusion of the two channels, we use the weighted average of the VV and VH ratio. Experimental backscatter data and theory show reduced separability of the two classes for co-polarized backscatter at low local incidence angles (below about 30°) [25,29]. The separability in cross-polarized backscatter data, on the other hand, decreases only slightly towards low incidence angles.
Angular trends of multitemporal backscatter ratios for Sentinel-1 data are shown in Figure 2 for wet snow areas and snow-free surfaces in three study areas. Snow masks derived from Landsat images were used to extract the VV-polarized ( R v v ) and VH-polarized ( R v h ) backscatter ratios for the two classes. Details on the data sets and the procedures for this analysis are presented in Section 3.2 and Section 3.3. The ratios of snow-free surfaces show small angular variations, whereas the wet snow ratios change significantly. The differences between snow/snow-free classes decrease for both R v v and R v h from mid-range angles towards large angles. The separability between the two classes decreases significantly towards lower local incidence angles for R v v , and less for R v h . Taking into account this angular behavior, we apply the following relation for merging R v v and R v h ratios in order to create a combined single channel, R c :
R c = W R v h + ( 1 − W ) R v v .
The weight ( W ) varies with the local incidence angle ( θ ) applying the following rule:
I F ( θ < θ 1 ) → { W = 1.0 } , I F ( θ 1 ≤ θ ≤ θ 2 ) → { W = k [ 1 + ( θ 2 − θ ) ( θ 2 − θ 1 ) ] } , I F ( θ > θ 2 ) → { W = k } .
For the data sets in this study, we use k = 0.5 , θ 1 = 20 ° , θ 2 = 45 ° . This means that R v v and R v h have the same weight for θ ≥ 45 ° . For θ < 45 ° , the weight of R v v decreases gradually, vanishing at θ = 20 ° . We limit the local incidence angles for snow mapping to the range 15 ° ≤ θ ≤ 75 ° . At lower angles, the surface resolution in range decreases significantly. At higher local incidence angles, the signal-to-noise ratio for targets with low reflectivity such as wet snow is quite small. Furthermore, for steep fore-slopes and near-grazing incidence, possible errors in the DEM used for geocoding become critical.
Terrain corrected geocoding is performed for the ratio image using precise orbit data. In addition, maps of the local incidence angle and masks of layover and radar shadow are generated by SAR image simulation using orbit and imaging parameters and a Digital Elevation Model as input. For the data presented in this paper we use the Digital Elevation Model over Europe (EU-DEM), which is a 3D raster data set with elevations captured at 1 arc second postings, corresponding to about 30 m [32]. For the standard snow product we are resampling the R c ratio image to a 100 m grid in UTM projection. The segmentation rule ( R c < T H R ) for discriminating wet snow versus dry snow and snow-free areas is applied to the geocoded R c ratio image, using a threshold of T H R = − 2 d B . The selection of this threshold value is based on histograms of the ratio values for the two classes.
Post-processing includes the application of a 3 × 3 median filter to eliminate single outlier pixels, and the use of land cover maps to exclude dense forests and water surfaces. Forest cover and water bodies are extracted from the digital Landsat based maps of Hansen et al. [33] with 30 m resolution. In addition, we use the SRTM Water Body Data Set [34] for complementing the water mask by adding the river courses.
3.2. Landsat Maps of Snow Extent
In order to assess the quality of S1 based snow maps, we generated maps of snow extent from Landsat data over study areas in the Alps and in Iceland. Due to widespread cloudiness in these regions during the snowmelt seasons, the choice of suitable Landsat images for comparison with S1 snow maps is rather limited. The acquisition time, geographic location and solar elevation of the used Landsat scenes are specified in Table 2.
The images cover the Tröllaskagi Peninsula in northern Iceland and two subareas of the Alps. The Iceland image is cloud-free. The image of the Swiss Alps contains a few small cumulus clouds. The image of the Ötztal Alps shows a substantial number of scattered cumulus clouds, mainly over snow-free mountain slopes. Clouds of this type can be well detected by means of visible and short-wave infrared reflectance. We use thresholds in Landsat-7 bands 3 and 5 for cloud screening. Cloud shadows are identified visually by mapping dark pixels in the neighborhood of the clouds, taking into account the direction of solar illumination. The resulting cloud masks include the clouds and the cloud shadows.
Landsat-7 images are impaired by data gaps due to failure of the SLC. In order to minimize the impact of the SLC failure, we restrict the analysis to the central parts of the images, which are only slightly affected by this failure and, exclude the missing lines for the statistical comparison.
For generating the Landsat snow maps, we apply a binary algorithm with threshold-based segmentation in normalized difference snow index ( N D S I ) images, using as threshold value of N D S I = 0.4 , as applied for generating Landsat climate data records on snow extent [35]. The N D S I is computed from top-of-atmosphere reflectances:
N D S I = R ( V I S ) − R ( S W I R ) R ( V I S ) + R ( S W I R )
For the Landsat-7 Enhanced Thematic Mapper (ETM+) we use the visible (VIS) band 2 (0.52–0.60 μm) and the shortwave infrared (SWIR) band 5 (1.55–1.75 μm), for the Landsat-8 Operational Land Imager (OLI), the band 3 (0.53–0.59 μm) and the band 6 (1.57–1.65 μm). The binary snow map is posted at 30 m pixel size in UTM projection, corresponding to the pixel size of the Landsat images.
3.3. Comparison of Sentinel-1 and Landsat Snow Maps
For discussing the performance of S1 snow classification, we use the Landsat snow maps as reference. Landsat snow maps are frequently used as benchmarks for cross-sensor snow map validation [36] so that the S1 snow maps can be evaluated in relation to common snow-products.
The three study areas for comparison of Landsat and S1 snow maps cover mountainous terrain. The two Alpine areas extend over an elevation range of about 3500 m, more than twice the range at the Tröllaskagi Peninsula where the highest peak reaches 1538 m in elevation. In the Alpine study areas, the snowline on the selected dates was located above the tree line. The Iceland area lacks a forest cover.
Dates in late spring were selected for the intercomparison when the snow cover was melting up to the highest elevations. Suitable Landsat images are not available on exactly the same day as the S1 images. For the Iceland area (A1), the time difference is only one day, whereas for the Alpine areas the Landsat images were acquired 3 days later (A2), and 4 days earlier (A3), respectively, than the S1 image (Table 2 and Table 3). For the area A1, the impact of the time difference is probably very small, as the good agreement between the Landsat and S1 snow maps shows (Figure 3).
Figure 3, Figure 4 and Figure 5 show the binary Landsat and S1 snow maps at 100 m pixel size. In order to match the grid size of the S1 maps for the statistical comparison, the binary 30 m Landsat snow pixels are aggregated into pixels of 100 m size. This provides an estimate of fractional snow cover at 100 m scale, representing an upper estimate because the N D S I threshold value of 0.4, used for the binary snow classification, corresponds to a cut-off value of about 50% snow cover [35,36]. For the statistical comparison (Table 4), we generate a binary Landsat snow map with 100 m pixel size by assigning all pixels with fractional snow extent ≥ 75 % to the snow class. This map is also used for defining snow/snow-free areas to extract the S1 backscatter ratios for Figure 2. Areas with clouds in Landsat images and areas with layover, foreshortening (S1 local incidence angle θ < 15 ° ), backslopes with θ > 75 ° , and dense forests in S1 images are masked out.
For compiling the confusion matrix between Landsat and S1 snow classification (Table 4), the total pixel number is normalized according to the Landsat-based classification result, assigning the value 100 to each class. This normalization enables a direct comparison of the performance for the different study areas and for the different ratio images. The overall agreement rate ( 0.0 ≤ A R ≤ 1.0 ) shows for areas A1 and A2 the best agreement for the combined ratio ( R c ) and a small decline for R v h . For A3, the performance of R c and R v h is the same. The drop-off in the A R of R v v is significant for the areas A2 and A3. We tested the application of different threshold values for segmentation in the R v v images, but this does not result in improvements. The lower performance of R v v for snow detection is in accordance with the smaller difference between the ratios of snow-covered and snow-free areas, in particular at lower incidence angles (Figure 2).
Tröllaskagi Peninsula has the highest overall agreement rate (0.97), followed by Ötztal Alps (0.96) and Swiss Alps (0.95). The time difference of three (Ötztal), respectively four (Swiss Alps) days, between the Landsat and S1 snow maps may play a role. Moreover, the two Alpine areas have steeper topography than the Tröllaskagi Peninsula, as is obvious from the higher fractions of layover and foreshortening in Figure 4 and Figure 5 versus Figure 3. The impact of topography seems to be substantial for the R v v based classification, as indicated by the lower AR values for Ötztal and the Swiss areas.
4. Sentinel-1 Snow Maps of Iceland and European Alps
Figure 6 and Figure 7 show snowmelt maps over large areas on different dates. The pixel size is 100 m, providing better spatial resolution than the snow maps derived from medium resolution optical sensors (e.g., MODIS [36]). In case of overlapping tracks, we select the pixel with the local incidence angle closest to θ = 45 ° , in order to fetch the angle with the better separability between the snow and snow-free classes.
For Iceland (Figure 6), snow maps posted in 100 m UTM were compiled for two epochs: (1) based on S1 IW images of 17 May (track 118), 19 May (track 147), 22 May 2015 (track 016); (2) based on S1 IW images of 10 June, 12 June and 15 June 2015 (same tracks as in May). Between the two epochs, the snowline ascended from about 600 m to 800 m in elevation. Above about 1600 m altitude, the accumulation areas on the ice caps Vatnajökull and Hofsjökull were still dry in the June images. The dry snow areas show little temporal variability in backscatter and therefore can be well identified in the ratio images.
Snow maps over the Alps (Figure 7) are shown for three epochs based on S1 IW images of: (1) 20, 21, 22 and 23 April 2015; (2) 14, 15, 16 and 17 May 2015; (3) 1, 2, 3 and 4 July 2015. The track numbers are 66, 88, 95 and 117. The digital radar-based map, displayed in Figure 7, comprises 43 million pixels of about 100 m size in geographic map projection. The SLC database used for compiling the snow map of a single track comprises about 20 GB, for the time series including reference images about 100 GB. On date 1 (20–23 April), melting snow surfaces extended up to 3000 m altitude, and on date 2, (14–17 May), to 3500 altitude. In the combined snow map, the dry snow areas are superposed by melting snow areas of later dates.
The investigations demonstrate the excellent capability of the Sentinel-1 mission for operational monitoring of snowmelt areas. The proposed algorithm, based on change detection in multitemporal SAR images, represents an extension to previously applied procedures for wet snow mapping. It exploits the advanced technical features of the S1 SAR sensor. Of particular benefit for the quality of the snowmelt area maps are the high instrument stability and the high spatial resolution across the comparatively wide swath of the IW mode [21]. The electronic azimuth scanning by means of the TOPSAR operation, harmonizing the performance in along-track direction and reducing scalloping effects, offers significant improvements in terms of radiometric quality compared to the conventional ScanSAR operation mode [3]. Due to the high spatial resolution of S1 SAR and the application of multichannel filtering in the snow mapping algorithm, the speckle-related uncertainty for the multi-temporal ratio images is very low.
Another beneficial feature for snow mapping is the regular acquisition of dual polarization (VV-VH) IW mode data, being used as standard operation scenario over many land areas [37]. Co-polarized channel data are the preferred option for interferometric applications, a main application field of the S1 mission. On the other hand, for retrieving snowmelt areas, the added value of cross-polarized data is significant, in particular in regions with steep topography. Thanks to the moderate angular dependence of backscatter, cross-polarized data offer good separability of wet snow and snow-free surfaces also on fore-slopes. For co-polarized data, the separability decreases significantly towards low incidence angles.
For assessing the accuracy of the S1 snow maps, we performed pixel-wise comparisons with Landsat-based snow maps. The results cannot be exactly translated into error numbers for the S1 snow maps because Landsat snow maps also show sensor specific features [35], and the dates of the Landsat and S1 snow maps differ by up to four days. Even so, the overall agreement rate between the Landsat and S1 classifications ranges from 0.95 to 0.97 for the various test sites (Table 4), confirming the good quality of both products that are derived from independent data sources. These numbers indicate significant improvements for SAR snow mapping by Sentinel-1 compared to previous snow cover products that are based on co-polarized SAR data of various satellite missions [11,12,13,14].
The comparison with Landsat snow maps reveals a slight trend for underestimation of snow extent for S1. This refers mainly to pixels with patchy snow cover where the signal contribution of snow-free surface dominates in SAR images, whereas the NDSI-based binary classifier separates the two classes at about 50% fractional snow cover [35,36].
For dense coniferous forest, common in the European Alps, reliable snow mapping with C-band SAR is not feasible because the radar signal is largely dominated by scattering in the canopy [38]. Therefore, we apply a land cover mask to exclude forested areas for snow retrievals over the Alps. Forests in Nordic areas are less dense, which offers the possibility to detect melting snow in open forests [39]. This could be a topic for further studies on the application of S1 for snow mapping.
The Sentinel satellite missions are dedicated to long-term routine observations for operational services in a wide range of applications. The data are also of great benefit to the Earth science community. Each Sentinel mission is based on a constellation of two identical satellites. By now, the first satellites of the Sentinel-1, -2, and -3 missions are in orbit. In this paper, we report on the features and performance of an algorithm for generating maps of snowmelt area based on radar images of the Sentinel-1 mission.
The nominal operation mode of the S1 SAR sensor for land areas is the Interferometric Wide swath (IW) mode, which offers high radiometric accuracy and high spatial resolution and covers a swath of 250 km width. These are important attributes for snow retrievals that are based on backscatter signals. Of benefit for snowmelt retrievals, in particular in regions with steep topography, is also the acquisition of cross-polarized data, helping to compensate for the reduced sensitivity of co-polarized data for detection of wet snow on fore-slopes. The comparison with snow maps derived from high resolution optical sensors confirms the high quality of the S1 snow cover maps. In particular, during the snowmelt period, when the snow extent is subject to rapid changes, the high temporal revisit of the S1 mission is of great value for hydrology, water management, flood forecasting and support of land surface process modeling. The revisit time of a single S1 satellite operating in IW mode is about four days in mid-latitudes and about two days in high latitudes. After deployment of the Sentinel-1B satellite, scheduled for launch on 22 April 2016, the revisit time will improve by a factor of two.
Whereas a main advantage of C-band SAR for snow mapping is the feasibility to penetrate clouds, the sensitivity to dry snow cover is rather limited. Therefore, the synergy with optical sensors is needed for a comprehensive observing system on snow extent. The Sentinel-2 and Sentinel-3 missions of the Copernicus program offer excellent capabilities for this task. Sentinel-2 is a polar-orbiting, multispectral imaging mission with 13 spectral bands (from 443 nm to 2190 nm wavelength) and spatial resolution of 10 m, 20 m and 60 m in the various channels, covering a swath of 290 km width [40]. With two satellites, the coverage by repeat orbits will be five days, disregarding cloud cover. The Sentinel-3 mission is equipped with a dual frequency synthetic aperture radar altimeter and two medium-resolution optical sensors: an imaging spectrometer, the Ocean Land Color Instrument (OLCI), and a dual-view multispectral radiometer, the Sea Land Surface Temperature Radiometer (SLSTR) [41]. After full deployment, the Sentinel-3 mission offers daily complete coverage in mid and high latitudes. Whereas the optical observation sequences for dynamic phenomena, such as seasonal snow, are strongly impaired by cloud cover, Sentinel-1 provides regular revisits at high temporal sequence, well-matched for capturing rapid changes due to snowmelt. The investigations reported here highlight the great potential of S1 for operational monitoring of snowmelt areas and for supporting multi-sensor snow cover mapping.
The work was supported by the Austrian Research Promotion Agency (FFG) Austrian Space Application Programme (Contract Nr. 847998), and the EU FP7 Project SEN3APP (Grant Agreement 607052). Sentinel-1 data were made available through ESA Sentinel Scientific Data Hub. Landsat data were obtained through GLOVIS USGS.
Thomas Nagler and Helmut Rott performed the scientific analysis and prepared the manuscript. Thomas Nagler developed SAR snow mapping tools and carried out SAR data processing. Elisabeth Ripper carried out the processing and analysis of optical snow maps and SAR data. Gabriele Bippus contributed to processing and interpretation of optical snow maps. Markus Hetzenecker contributed to the development of SAR processing tools. All authors contributed to editing the manuscript.
The following abbreviations are used in this manuscript:
DEM Digital Elevation Model
ENL Effective Number of Looks
ESA European Space Agency:
ETM+ Enhanced Thematic Mapper
EW Extra Wide swath mode
FFG Austrian Research Promotion Agency
GB Giga Byte
GLOVIS Global Visualization Viewer
GMES Global Monitoring for Environment and Security
GRD Ground Range Detected
IW Interferometric Wide swath mode
LOS Line Of Sight
MODIS Moderate-resolution Imaging Spectroradiometer
NESZ Noise Equivalent Sigma-0
OLCI Ocean Land Color Instrument
OLI Operational Land Imager
S1 Sentinel-1
SAR Synthetic Aperture Radar
SLC Single Look Complex
SLSTR Sea Land Surface Temperature Radiometer
SM Stripmap mode
SRTM Shuttle Radar Topography Mission
TOPS Terrain Observation with Progressive Scans
TOPSAR Terrain Observation with Progressive Scans SAR
USGS United States Geological Survey
UTM Universal Transverse Mercator
VH Vertical polarisation transmit and Horizontal polarisation receive
VV Vertical polarisation transmit and Vertical polarisation receive
WV Wave mode
Aschbacher, J.; Milagro-Peréz, M.P. The European Earth monitoring (GMES) programme: Status and perspectives. Remote Sens. Environ. 2012, 120, 3–8. [Google Scholar] [CrossRef]
Copernicus—Application Domains. Available online: http://www.copernicus.eu/main/application-domains (accessed on 20 February 2016).
Torres, R.; Snoeij, P.; Geudtner, D.; Bibby, D.; Davidson, M.; Attema, E.; Potin, P.; Rommen, B.; Floury, N.; Brown, M.; et al. GMES Sentinel-1 mission. Remote Sens. Environ. 2012, 120, 9–24. [Google Scholar] [CrossRef]
Fletcher, K. Sentinel-1: ESA's Radar Observatory Mission for GMES Operational Services; ESA SP-1322/1; ESA-ESTEC: Noordwijk, The Netherlands, 2012; p. 83. [Google Scholar]
Pedersen, L.T.; Saldo, R.; Fenger-Nielsen, R. Sentinel-1 results: Sea ice operational monitoring. In Proceedings of the IEEE IGARSS, Milan, Italy, 26–31 July 2015; pp. 2828–2831.
Nagler, T.; Rott, H.; Hetzenecker, M.; Wuite, J.; Potin, P. The Sentinel-1 Mission: New opportunities for ice sheet observations. Remote Sens. 2015, 7, 9371–9389. [Google Scholar] [CrossRef]
Potin, P.; Rosich, B.; Roeder, J.; Bargellini, P. Sentinel-1 mission operations concept. In Proceedings of the IEEE IGARSS, Québec, QC, Canada, 13–18 July 2014; pp. 1465–1468.
Malenovský, Z.; Rott, H.; Cihlar, J.; Schaepman, M.E.; García-Santos, G.; Fernandes, R.; Berger, M. Sentinels for Science: Potential of Sentinel-1, -2, and -3 missions for scientific observations of ocean, cryosphere and land. Remote Sens. Environ. 2012, 120, 91–101. [Google Scholar] [CrossRef]
Baghdadi, N.; Gauthier, Y.; Bernier, M. Capability of multitemporal ERS-1 SAR data for wet snow mapping. Remote Sens. Environ. 1997, 60, 174–186. [Google Scholar] [CrossRef]
Baghdadi, N.; Gauthier, Y.; Bernier, M.; Fortin, J.P. Potential and limitations of RADARSAT SAR data for wet snow monitoring. IEEE Trans. Geosci. Remote Sens. 2000, 38, 316–320. [Google Scholar] [CrossRef]
Nagler, T.; Rott, H. Retrieval of wet snow by means of multitemporal SAR data. IEEE Trans. Geosci. Remote Sens. 2000, 38, 754–765. [Google Scholar] [CrossRef]
Nagler, T.; Rott, H.; Glendinning, G. Snowmelt runoff modelling by means of RADARSAT and ERS SAR. Can. J. Remote Sens. 2000, 26, 512–520. [Google Scholar] [CrossRef]
Luojus, K.P.; Pulliainen, J.; Metsamaki, S.; Hallikainen, M. Snow-covered area estimation using satellite radar wide-swath images. IEEE Trans. Geosci. Remote Sens. 2007, 45, 978–989. [Google Scholar] [CrossRef]
Nagler, T.; Rott, H.; Malcher, P.; Müller, F. Assimilation of meteorological and remote sensing data for snowmelt runoff forecasting. Remote Sens. Environ. 2008, 112, 1408–1420. [Google Scholar] [CrossRef]
Longepe, N.; Allain, S.; Ferro-Famil, L.; Pottier, E.; Durand, Y. Snowpack characterization in mountainous regions using C-Band SAR data and a meteorological model. IEEE Trans. Geosci. Remote Sens. 2009, 47, 406–418. [Google Scholar] [CrossRef]
CryoLand-Copernicus Service Snow and Land Ice. Available online: http://www.cryoland.eu (accessed on 14 April 2016).
Key, J.; Drinkwater, M.; Ukita, J. (Eds.) IGOS Cryosphere Theme Report; WMO/TD-1405; WMO: Geneva, Switzerland, 2007; p. 124.
Miranda, N.; Meadows, P.J. Radiometric Calibration of S-1 Level-1 Products Generated by the S-1 IPF; ESA-EOPG-CSCOP-TN-0002; Technical Note. European Space Agency: Frascati, Italy, 2015; p. 13. Available online: https://sentinel.esa.int/documents/247904/685163/S1-Radiometric-Calibration-V1.0.pdf (accessed on 14 April 2016).
Sentinel-1 Team. Sentinel-1 User Handbook; GMES-S1OP-EOPG-TN-13-0001. European Space Agency: Frascati, Italy, 2013; p. 80. Available online: https://sentinel.esa.int/documents/247904/ 685163/Sentinel-1_User_Handbook (accessed on 14 April 2016).
Miranda, N.; Palumbo, G. Sentinel-1 Instrument and Product Performance Status. In Proceddings of the FRINGE 2015 Workshop, ESA-ESRIN, Frascati, Italy, 23–27 March 2015; Available online: http://seom.esa.int/fringe2015/files/presentation359.pdf (accessed on 18 February 2016).
Miranda, N.; Meadows, P.; Hajduch, G.; Pilgrim, A.; Piantanida, R.; Giudici, D.; Small, D.; Schubert, A.; Husson, R.; Vincent, P.; et al. The Sentinel-1A instrument and operational product performance status. In Proceedings of the IEEE IGARSS, Milan, Italy, 26–31 July 2015; pp. 2824–2827.
Knight, E.J.; Kvaran, G. Landsat-8 Operational Land Imager design, characterization, and performance. Remote Sens. 2014, 6, 10286–10305. [Google Scholar] [CrossRef]
Storey, J.; Choate, M.; Lee, K. Landsat 8 Operational Land Imager on-orbit geometric calibration and performance. Remote Sens. 2014, 6, 11127–11152. [Google Scholar] [CrossRef]
Shi, J.; Dozier, J. Inferring snow wetness using C-band data from SIR-C's polarimetric synthetic aperture radar. IEEE Trans. Geosci. Remote Sens. 1995, 33, 905–914. [Google Scholar]
Mätzler, C. Applications of the interaction of microwaves with the natural snow cover. Remote Sens. Rev. 1987, 2, 259–387. [Google Scholar] [CrossRef]
Ulaby, F.T.; Long, D. Microwave Radar and Radiometric Remote Sensing; University of Michigan Press: Ann Arbor, MI, USA, 2014; p. 1016. [Google Scholar]
Reber, B.; Mätzler, C.; Schanda, E. Microwave signatures of snow crusts. Modeling and measurements. Int. J. Remote Sens. 1987, 8, 1649–1665. [Google Scholar] [CrossRef]
Floricioiu, D.; Rott, H. Seasonal and short-term variability of multifrequency, polarimetric radar backscatter of alpine terrain from SIR-C/X-SAR and AIRSAR data. IEEE Trans. Geosc. Rem. Sens. 2001, 39, 2634–2648. [Google Scholar] [CrossRef]
Strozzi, T.; Wiesman, A.; Mätzler, C. Active microwave signatures of snow covers at 5.3 and 35 GHz. Radio Sci. 1997, 32, 479–495. [Google Scholar] [CrossRef]
Sansosti, E.; Berardino, P.; Manunta, M.; Serafino, F.; Fornaro, G. Geometrical SAR image registration. IEEE Trans. Geosci. Remote Sens. 2006, 44, 2861–2870. [Google Scholar] [CrossRef]
Quegan, S.; Yu, J.J. Filtering of multichannel SAR data. IEEE Trans. Geosc. Rem. Sens. 2001, 39, 2373–2379. [Google Scholar] [CrossRef]
European Environment Agency. Digital Elevation Model over Europe (EU-DEM). Available online: http://www.eea.europa.eu/data-and-maps/data/eu-dem (accessed on 12 February 2016).
Hansen, M.C.; Potapov, P.V.; Moore, R.; Hancher, M.; Turubanova, S.A.; Tyukavina, A.; Thau, D.; Stehman, S.V.; Goetz, S.J.; Loveland, T.R.; et al. High-Resolution Global Maps of 21st-Century Forest Cover Change. Science 2013, 342, 850–853. [Google Scholar] [CrossRef] [PubMed]
SRTM Water Body Dataset. Available online: https://lta.cr.usgs.gov/srtm_water_body_dataset (accessed on 12 February 2016).
Crawford, C.J.; Manson, S.M.; Bauer, M.E.; Hall, D.K. Multitemporal snow cover mapping in mountainous terrain for Landsat climate data record development. Remote Sens. Environ. 2013, 135, 224–233. [Google Scholar] [CrossRef]
Crawford, C.J. MODIS Terra Collection 6 fractional snow cover validation in mountainous terrain during spring snowmelt using Landsat TM and ETM+. Hydrol. Process. 2015, 29, 128–138. [Google Scholar] [CrossRef]
Potin, P.; Rosich, B.; Miranda, N.; Grimont, P.; Bargellini, P.; Monjoux, E.; Martin, J.; Desnos, Y.-L.; Roeder, J.; Shurmer, I. Sentinel-1 mission status. In Proceedings of the IEEE IGARSS, Milan, Italy, 26–31 July 2015; pp. 2820–2823.
Karam, M.A.; Amar, F.; Fung, A.K.; Mougin, E.; Lopes, A.; Vine, D.M.L.; Beaudoin, A. A microwave polarimetric scattering model for forest canopies based on vector radiative transfer theory. Remote Sens. Environ. 1995, 53, 16–30. [Google Scholar] [CrossRef]
Koskinen, J.T.; Pulliainen, J.T.; Luojus, K.P.; Takala, M. Monitoring of snow cover properties during the spring melting period in forested areas. IEEE Trans. Geosci. Remote Sens. 2010, 48, 50–58. [Google Scholar] [CrossRef]
Drusch, M.; Del Bello, U.; Carlier, S.; Colin, O.; Fernandez, V.; Gascon, F.; Hoersch, B.; Isola, C.; Laberinti, P.; Martimort, P.; et al. Sentinel-2: ESA's Optical High-Resolution Mission for GMES Operational Services. Remote Sens. Environ. 2012, 120, 25–36. [Google Scholar] [CrossRef]
Donlon, C.; Berruti, B.; Buongiorno, A.; Ferreira, M.-H.; Féménias, P.; Frerick, J.; Goryl, P.; Klein, U.; Laur, H.; Mavrocordatos, C.; et al. The Global Monitoring for Environment and Security (GMES) Sentinel-3 Mission. Remote Sens. Environ. 2012, 120, 37–57. [Google Scholar] [CrossRef]
Figure 1. Flow chart of the algorithm for retrieval of snowmelt area from Sentinel-1 Interferometric Wide swath mode data.
Figure 2. Backscatter ratio (median, Mdn, 1st and 3rd quartile) for S1 VV- and VH- polarized channels in dependence of the local incidence angle, θ , for areas classified as snow-free and snow-covered in Landsat images (see Section 3.2): (a) test site A1: Tröllaskagi; (b) test site A2: Ötztal Alps; (c) test site A3: Swiss Alps.
Figure 3. Snow map of Tröllaskagi Peninsula, Iceland. (Left) Snow extent (blue) derived from Landsat-8 image of 27 June 2015; white: water; background: Landsat-8 OLI bands 6, 5, 4. (Right) Wet snow extent (blue) derived from Sentinel-1 image of 26 June 2015; background: S1 amplitude image, VV-channel; orange: mask for layover and foreshortening.
Figure 4. Snow map of the Ötztal mountain region, Eastern Alps of Austria and Italy. (Left) Snow extent (blue) derived from Landsat-7 image of 5 June 2015; yellow: clouds; white: water; background: Landsat-7 ETM+ bands 5, 4, 3. (Right) Wet snow extent (blue) derived from Sentinel-1 image of 2 June 2015; background: S1 amplitude image, VV-channel; orange: mask for layover and foreshortening.
Figure 5. Snow map of Swiss Alps (Berne, Valais). (Top) Snow extent (blue) derived from Landsat-7 image of 3 June 2015; background: Landsat ETM+ bands 5, 4, 3; yellow: clouds; white: water. (Bottom) Snow extent (blue) derived from Sentinel-1 image of 7 June 2015; background: amplitude image, VV-channel; orange: mask for layover and foreshortening.
Figure 6. Map of snowmelt area extent in Iceland, derived from Sentinel-1 data of 17, 19 and 22 May 2015 (Date 1) and 10, 12, and 15 June 2015 (Date 2). Light blue: decrease of snow extent between Date 1 and Date 2. Dark blue: snowmelt area on Date 2. Light grey: dry snow on ice caps; white: water surfaces; orange: mask of layover and foreshortening. Background: S1 SAR amplitude image, VV polarizations.
Figure 7. Map of snowmelt area extent over the Alps, derived from Sentinel-1 data of 20 to 23 April 2015 (Date 1), 14 to 17 May 2015 (Date 2), 1 to 4 July 2015 (Date 3). Light blue: decrease of snow extent between Date 1 and Date 2. Dark blue: decrease of snow extent between Date 2 and Date 3; Purple: snowmelt area on Date 3. Black: water surfaces; orange: mask of layover and foreshortening. Background: S1 SAR amplitude image, VV polarizations.
Table 1. Main characteristics of Sentinel-1 SAR data in Interferometric Wide swath (IW) mode [3]. Nominal spatial resolution for single look complex (SLC) data. GR: Ground range; AZ: azimuth. LOS: line-of sight. NESZ: noise equivalent sigma-0.
Centre Frequency
Swath Width
Incidence Angle
Nominal Resolution GR × AZ
Pixel Spacing LOS × AZ
Maximum NESZ
Radiom. Stability (3σ)
Radiom. Accuracy (3σ)
5.407 GHz 250 km 31°–46° 5 m × 20 m 2.4 m × 13.9 m −22 dB 0.5 dB 1.0 dB
Table 2. Information on the Landsat scenes used for comparison with S1 snow maps. Latitude, longitude and sun elevation refer to the scene center.
Date & Time (UTC)
Lat/Lon
Sun Elev.
A1, Tröllaskagi, Iceland Landsat-8 27 June 2015 12:45 65.59° N/19.98° W 47.3°
A2, Ötztal Alps, Austria Landsat-7 5 June 2015 10:03 47.45° N/11.02° E 61.4°
A3, Swiss Alps Landsat-7 3 June 2015 10:16 46.03° N/7.39° E 62.1°
Table 3. Information on Sentinel-1 images used for comparison with Landsat snow maps. The incidence angle, θ , refers to a horizontal surface in the center of each area.
Date & Time UTC
Orbit Heading
Track Nr.
A1, Tröllaskagi, Iceland 26 June 2015 07:41 Descending 9 40°
A2, Ötztal Alps, Austria 2 June 2015 05:26 Descending 168 37°
A3, Swiss Alps 7 June 2015 05:35 Descending 66 42°
Table 4. Confusion matrix for the classes snow (S) and snow-free (F) in the 3 study areas, for snow classification based on Landsat (LS) and Sentinel-1 (S1) data. S1 results are shown for snow maps based on the ratios R v v , R v h , and R c . AR —overall agreement rate ( 0.0 ≤ A R ≤ 1.0 ).
Rvv
Rvh
S1-S
S1-F
A1 LS-S 92.8 7.2 92.6 7.4 94.6 5.4
LS-F 2.0 98.0 0.2 99.8 0.2 99.8
0.954 0.962 0.972
A2 LS-S 80.7 19.3 94.5 6.4 94.7 5.3
Nagler, T.; Rott, H.; Ripper, E.; Bippus, G.; Hetzenecker, M. Advancements for Snowmelt Monitoring by Means of Sentinel-1 SAR. Remote Sens. 2016, 8, 348. https://doi.org/10.3390/rs8040348
Nagler T, Rott H, Ripper E, Bippus G, Hetzenecker M. Advancements for Snowmelt Monitoring by Means of Sentinel-1 SAR. Remote Sensing. 2016; 8(4):348. https://doi.org/10.3390/rs8040348
Nagler, Thomas, Helmut Rott, Elisabeth Ripper, Gabriele Bippus, and Markus Hetzenecker. 2016. "Advancements for Snowmelt Monitoring by Means of Sentinel-1 SAR" Remote Sensing 8, no. 4: 348. https://doi.org/10.3390/rs8040348
Remote Sens., EISSN 2072-4292, Published by MDPI


Pastor Marvin Winans for years has reached fans through his music and by preaching the word of God. At his church he continues to create events that allow for teachable moments.
Moreover this upcoming weekend Winans is having a 'Power of Unity' conference where it will focus on men and women working together. Winans believes there aren't any roles that a man can do or woman can do better.
Winans also mentioned that at this time we're in a era of a feminist movement and woman are taking upon roles that people denied them of for a long time. People must recognize that we need each other and recognize that the power of unity is an amazing thing.
Lastly, Erica Campbell asked him about the importance of showing married couple in church. Winans believes it's very important because it's an added blessing when it comes to unity. It shows two people working together in a relationship and is a great example to people in the church.
Make sure you see 12 gospel artists who are also pastors below!


text:
Niemienice – wieś w Polsce położona w województwie lubelskim, w powiecie krasnostawskim, w gminie Krasnystaw.

W latach 1975–1998 miejscowość położona była w województwie chełmskim.

Przez miejscowość przepływa rzeka Żółkiewka, dopływ Wieprza.
W 2011 roku w Niemienicach oddano do użytku Wiejski Dom Kultury w którym siedzibę posiadają: filia Biblioteki Gminnej, Koło Gospodyń wiejskich oraz Wiejski Dom Kultury z salą konferencyjną.

Z Niemienicami graniczy Rezerwat przyrody Wodny Dół z unikatową w skali kraju roślinnością. Przez wieś przebiega również trasa rowerowa, która prowadzi przez okolice pobliskiego miasta Krasnystaw.

W czasie II wojny światowej we wsi Niemienice działał partyzancki oddział Batalionów Chłopskich, który we wrześniu 1943 roku wymaszerował właśnie z Niemienic na Krasnostawskie więzienie. Słynna akcja oswobodzenia więzienia bez oddania ani jednego strzału. Mieszkańców Niemienic poległych w walkach podczas II wojny światowej upamiętnia pomnik przy przebiegającej przez wieś drodze wojewódzkiej nr. 842.

Wieś stanowi sołectwo gminy Krasnystaw. Według Narodowego Spisu Powszechnego (III 2011 r.) wieś liczyła 354 mieszkańców.

Historia
Wieś występuje w dokumentach źródłowych w roku 1448 jako Niemienycze. Według lustracji z 1628 roku wchodziła w skład starostwa krasnostawskiego (zobacz t.IV, 643-1).

Słownik geograficzny Królestwa Polskiego z roku 1886 wymienia Niemienice jako wieś w powiecie krasnostawskim, gminie i parafii Krasnystaw. Wieś posiadała wówczas szkołę początkową ogólną.
Według spisu z 1827 roku było tu 21 domów i 195 mieszkańców.

Odznaczenia
 Order Krzyża Grunwaldu III klasy (1985)

Przypisy

Bibliografia
 .

Wsie starostwa krasnostawskiego
Niemienice (województwo lubelskie)


text:
'They wrote to each other frequently, exchanged intellectual banter, confided in each other'—Siphiwo Mahala chats about his new play, Bloke and His American Bantu
February 17, 2022 February 17, 2022 Jennifer MalecLeave a Comment on 'They wrote to each other frequently, exchanged intellectual banter, confided in each other'—Siphiwo Mahala chats about his new play, Bloke and His American Bantu
The JRB presents an interview with Siphiwo Mahala about his new play, Bloke and His American Bantu.
Bloke and His American Bantu is produced by The University of Johannesburg in association with the Sello Maake kaNcube Foundation, directed by the internationally acclaimed Sello Maake kaNcube, and stars Anele Nene as Bloke Modisane and Josias Dos Moleele as Langston Hughes.
Bloke and His American Bantu will be on stage at the UJ Arts Centre in Johannesburg from 16 to 26 February 2022 at 7 p.m. every day, except Sunday and Monday.
The JRB: Congratulations on the production of Bloke and His American Bantu, Siphiwo. Tell us a little about the inception of this play. Where did the idea come from?
Siphiwo Mahala: Having read quite extensively about the Harlem Renaissance, and knowing that Langston Hughes had corresponded with Es'kia Mphahlele, I was always interested to see the original letters. When I visited the United States for the first time in 2012, I went to the Schomburg Center for Research in Black Culture in Harlem, New York, where Hughes's ashes are buried. The next day I went to the Beinecke Rare Book and Manuscript Library in Connecticut, where Hughes's archives are kept. Here, I found the correspondence with Mphahlele, but more than that, I realised that there was reference to Bloke Modisane in almost every second letter. When I asked for the Modisane files, I realised that Hughes had a much more intimate relationship with Modisane compared to many other people he corresponded with throughout the world. They wrote to each other frequently, exchanged intellectual banter, confided in each other, and at times wrote to each other for the sheer joy derived from the art of letter writing. I could visualise their lives unfolding right before me as I was going through the letters. A play was born.
The JRB: The play is set in the nineteen-sixties, during, as you say 'one of the darkest hours in the history of South Africa'. Why do you think this is an important story to tell in South Africa in 2022?
Siphiwo Mahala: It's an important story to tell, first of all, because it's a uniquely South African-American story. In other words, South Africa has staged many American plays to which we can relate and from which we can model our lives. This play is about our joint heritage. It is not an American story put in the context of South Africa. It is a story that illustrates the ties that bind South Africa and the United States of America. It shows the role of cultural workers and intellectuals in the fight against apartheid. It demonstrates how important the cultural sector was in mobilising international solidarity against apartheid. Most importantly, it shows us that artists have the agency to build relations between nations beyond what diplomats can ever dream of. Following the Sharpeville Massacre, the world's eyes were on South Africa. Modisane, who had writing credits alongside Lewis Nkosi for Come Back, Africa, a film that came out in 1959 and gave Miriam Makeba international exposure, used his cultural agency to conscientise the world about the sociopolitical condition in South Africa.
The JRB: This is a story of solidarity across borders, one that highlights the value of these kinds of relationships between artists and intellectuals. What do you think the two learnt from each other intellectually during their conversations?
Siphiwo Mahala: Bloke Modisane had been following Hughes's work for years, and being published by him in An African Treasury in nineteen-sixty was a major breakthrough for Modisane into international markets. Similarly, until Hughes was introduced to the Drum writers like Henry Nxumalo, Can Themba and Modisane, the only South African writers he had read were Alan Paton, Nadine Gordimer and Peter Abrahams. Publishing the book gave him exposure to the work and thought processes of a kaleidoscope of African writers.
Hughes came from a mixed family background, and was deliberate about reclaiming his black identity. However, apart from a number of short visits, he had not lived on the continent. Through the exchange of letters and gifts, including cultural garments, as well as learning some isiZulu and Sepedi words, he was learning the tenets of blackness from Modisane. Similarly, Modisane delivered over twenty lectures across the US, in which he shared the living experience of black South Africans in a country where they were an oppressed majority. His lectures in the US were not just political, he taught African rhythms in music and dance, among other subjects. In a sense, through Modisane, Hughes learnt what it meant to be a black South African banished from your ancestral land.
The JRB: What personal aspects of the letters between Modisane and Hughes were you keen to bring out in this work? In other words, what about their relationship and camaraderie touched you and inspired you to share this story?
Siphiwo Mahala: What struck me at first was witnessing the evolution of their friendship, to see them addressing each other innocuously, and then getting to know each other, becoming nonchalant, giving each other affectionate names and exchanging banter. I also found it amazing that at some point in the nineteen-sixties, they sent each other several letters within a space of a week. It came naturally that, when one was in trouble, they knew whom to call and the empathy was palpable even though they were separated by the Pacific Ocean. When Modisane was destitute—unemployed and homeless in London, and even contemplating going back to South Africa where at least he 'was alive', it was Hughes who lent an ear. Similarly, when excited over something, they wanted to tell each other about their fortune and celebrate together.
The JRB: The conversation between these two men highlights the differences and similarities that connect the South African liberation struggle with that of Black America. What struck you about this connection as you were reading and writing?
Siphiwo Mahala: The similarities have been written about—being that black people were oppressed and discriminated against in both countries. Parallels have been drawn between what are popularly known as the Harlem Renaissance and Sophiatown Renaissance; similarly, connections have been drawn between the Black Power movement in the US, and the Black Consciousness movement in South Africa. Black people in these two countries fought similar struggles. However, there are two major differences: the first being that apartheid was legislated in South Africa whereas discrimination was not necessarily an official government policy in the US; the second is that black people in South Africa, unlike the US, were the oppressed majority. These are some of the scenarios that are explored in the play, and I think more than the historical facts, there is a special emotional connection that the peoples from these two nations share, and this comes strongly in the play.
The JRB: What approach did you use to get into the mind of these two men, who lived at a very different time to you?
Siphiwo Mahala: I read over fifty letters exchanged between the two, and there was no way I wouldn't get to understand who they were, their anxieties and ecstasies. Furthermore, I spent nine years reading further on them, watching documentaries and reading their work. I visited New York at least four times in the past ten years. I spent a lot of time researching before I could sit down and write. This helped me a great deal in portraying their characters. I was fortunate that Sello Maake kaNcube, the director of the play, immersed himself in the work and helped the actors understand and feel the story as opposed to just memorising the words. The two actors in the show, Anele Nene and Josias Dos Moleele, do great justice to the characters.
The JRB: Do you have a favourite piece of Modisane's writing? What about a favourite Hughes poem?
Siphiwo Mahala: After going through all their writing as a researcher, I find it hard to decide on a single piece of writing as my favourite. What stands out for me in terms of significance is the opening lecture Modisane delivered at the American Society of African Culture (AMSAC) authors' dinner in March 1963, titled 'Short Story Writing in Black South Africa'. It set the tone for his US tour, but it's also about short stories, which is my area of specialty. Similarly, I think with Hughes 'The Negro Speaks of Rivers' holds a special place for me because it's a poem that ushered him into superstardom when he was only seventeen years of age.
The JRB: Thank you for your time ahead of the play's premiere.
Drama / Interviews / South AfricaAlan Paton American Society of African Culture An African Treasury Anele Nene Apartheid Beinecke Rare Book and Manuscript Library Black Consciousness Black Power movement Bloke Modisane Can Themba Come Back Africa Drama Drum magazine Es'kia Mphahlele Harlem Harlem Renaissance Henry Nxumalo isiZulu Josias Dos Moleele Langston Hughes Lewis Nkosi London Miriam Makeba Nadine Gordimer New York Pacific Ocean Peter Abrahams Schomburg Center for Research in Black Culture Sello Maake kaNcube Sepedi Sharpeville Massacre Siphiwo Mahala Sophiatown Renaissance United States
Previous Post Previous post: New flash fiction: The Burning Fruit by Abbey Khambule
Next Post Next post: [Sponsored] Cover reveal! Vivian de Klerk's shocking, poignant and funny new novel Serpent Crescent
The party has a purpose—Carey Baraka considers…
November 15, 2022 No Comment
'No meaningful change can come from those…
'I was an identity-less person at the…
'There was a heated discussion about me…


text:
Q: Appending only a subset of a dataframe with another one For two dataframes like
import pandas as pd
df1 = pd.DataFrame({'A' : [1,5,6] , 'B' : [3,8,9]})
df2 = pd.DataFrame({'A' : [1,7,6] , 'B' : [31,81,91]})

how could we append (or other combining technique) df2 to df1 but consider only those rows of df2 which have common A with df1? and get
pd.DataFrame({'A' : [1,5,6,1,6], 'B' : [3,8,9,31,91]})

and how could we consider only those rows of df2 which don't have common A with df1? and get
pd.DataFrame({'A' : [1,5,6,7], 'B' : [3,8,9,81]})

A: Use isin to find the common values and concat to join the DataFrames:
mask = df2['A'].isin(df1['A'])
intersection = pd.concat((df1, df2[mask]))
print(intersection)

Output (intersection)
   A   B
0  1   3
1  5   8
2  6   9
0  1  31
2  6  91

Now the second part, use the negation of the mask:
mask = df2['A'].isin(df1['A'])
difference = pd.concat((df1, df2[~mask]))
print(difference)

Output (difference)
   A   B
0  1   3
1  5   8
2  6   9
1  7  81

redpajama_set_name: RedPajamaStackExchange


Saj and Grill present a unique food experience from South Bank, serving modern Lebanese food while maintaining traditional culinary methods of cooking. Indulge in a variety of Middle Eastern handcrafted and traditional cuisine that suits all tastes, from vegetarian needs to meaty hungers. Take time to enjoy morning coffees with LaVazza, lebanese wraps for lunch, or dine on mediterranean salads, kaftas and the signature Saj flatbread - handmade and cooked in the same ways of five thousand years ago. Finish this Middle Eastern spread by looking through a variety of delicious Lebanese sweets that are homemade and traditional.


text:
Eastminster Presbyterian Church East Lansing, MI
An open and welcoming church serving East Lansing and the MSU campus community
Sunday Worship 10:00 a.m. 1315 Abbot Rd., East Lansing, MI | 517-337-0893
Eastminster Presbyterian Church History
Eastminster Architecture
Theological Underpinnings
Alden Dow Design Philosophy
Eastminster Design Phases
Pulpit, Pews, and Cross
Building Pictures
Eastminster Gardens
Eastminster Garden
Prayer Path
About the Organbuilder
Organ Contributors
Advent House
Community English Classes
Haven House
Mission Collections
Super Bowl of Caring
Crop Walk
Presbyterian Special Offerings
After Worship Fellowship
UKirk Campus Ministry
Cultured Purls Knitting
20s and 30s Group
Sunday Morning/MORE
Youth and Adults
Mid-Week Education
Weekly E-Voice
You are here: Home / Deacons
The primary role of the Deacons at Eastminster is to provide hospitality, member care, and ministries of compassion to our members in cooperation with the pastor. Deacons are elected to a three year term. The moderator of the Deacons is Linda Hardenbergh.
Class of 2020 Class of 2020 Class of 2021
Barbara Dalzell
Heather Heitman
Cindy Mackay
Sherri Blanchard
Linda Hardenbergh
Suzanne Hunt
Beverly Bonning
Sulin Campbell
Judy Dickinson
Sulin has been a member of Eastminster Presbyterian Church since 1999. She is serving her second term as a Deacon. Sulin enjoys singing in the Chancel Choir and sharing her music with the congregation at EPC. She has taught at the MSU Community Music School, and has also maintained an independent piano studio in her home in Okemos, for 25 years. Sulin and her husband Bruce have four children–now grown. (Bruce passed away in 2011. He had served as the Music Director and Organist at Eastminster for 17 years.) Sulin is happily looking forward to the arrival of their first grandchild in January 2020!
Barb Dalzell
BARB DALZELL will be the Card Ministry Coordinator for the Deacons. Barb has been a Deacon several times, a Sunday School teacher, Superintendent and Chancel Coordinator. She worked on the Prayer Path and enjoys knitting with the Cultured Purls. She raised two daughters at EPC and has three grandchildren. She values the support and friendship of our EPC family.
Linda Hardenbergh is a deacon and a member of the Finance and Administration Committee and the Worship and Music Committee. In the past, she's been an elder and served on the personnel committee. Linda values the friendly people here at Eastminster and hopes that it will continue to be an open and welcoming community.
HEATHER HEITMAN is a Deacon leading the Welcome Table for greeting visitors and guests to Eastminster services. She also a member of the Memorial Fund Committee and has assisted with children's worship. I still remember my first service at Eastminster like it was just yesterday. I was so impressed with how friendly and welcoming everyone was. Now that I am a Deacon running the Welcome Table, I am hoping to create that same welcoming feeling that I received on my first visit.
A new deacon at Eastminster, Suzanne is a native of Philadelphia, Pennsylvania and a twenty-five year resident of Princeton, New Jersey. She moved to East Lansing, Michigan three years ago. Suzanne is the wife of Reverend Chase S.Hunt, who served in churches in New York City and Ferndale Michigan and on the staff of Princeton Theological Seminary. Suzanne was a learning Consultant for many years in the public school system in New Jersey. She has been painting in the medium of watercolor for over thirty years and has a small business, Suzanne Hunt Watercolors. Her art is exhibited at the Shiawssee Art Center in Owosso, Michigan and with The Mid-Michigan Art Guild.
Cindy Mackay joined Eastmnister in 1989. She and her husband, Norm had to relocate in 1996. But in 2012, they returned to mid-Michigan and rejoined Eastminster. Having been recently ordained as a deacon, Cindy is still learning on the job. Her mantra is "just tell me what to do and I'll do it". Away from church she enjoys her daily workout during trips to the gym. Twice a month, Cindy and Norm support their daughter Jessica at ConnectUs, a community-based service organization for disabled adults.
Estelle McGroarty
Estelle McGroarty initially joined Eastminster in the early 1970's but left in the mid-1980's when she and her family moved to Holt. They rejoined in 2003 when they moved to Dewitt. In the past she has served as an elder, Sunday school teacher and member of the Pastor Nominating Committee. Currently, in addition to serving as a deacon, she is a member of the mission committee. She is a retired faculty member and administrator at Michigan State University, and has 2 children and 6 grandchildren. Over the years, Eastminster has been a strong spiritual support for our family.
Welcome to Eastminster
With open hearts and minds, increasing our faith in service of our community. Welcome to Eastminster Presbyterian Church, a diverse and dynamic congregation in the heart of the greater Lansing region. We are a church family who comes together to praise our Lord, learn and grow in the image of Jesus Christ, and serve the community, nation, and World through our missions. Located just minutes from the campus of Michigan State University and the Michigan Capitol, we offer a wide array of educational programs, service opportunities, and ministries and fellowship for all ages. Please join us, to feel the warmth, love, and acceptance that Jesus Christ has taught us all to embody.
Support Eastminster and UKirk
We, the members of Eastminster Presbyterian Church,
celebrate the grace of God and the redeeming love of Jesus Christ.
1315 Abbot Road
East Lansing. MI 48823
Email: office@eastminsterchurch.org
Office Hours: 9-3; Monday – Thursday


Das Maurerhäusl mit gemütlichen Ferienwohnungen liegt außerhalb von Hochfilzen am ruhig und idyllisch gelegenen Wiesense..
Our campsite is very natural and idyllic, situated close to the lake of Walchsee (5 min. by walk), possibility for swimm..
Camping Ötztal is suitable for families with children, for those who enjoy hiking and mountains, and for those who want ..
Faak am See, Seeufer Landesstraße 45, A-..
Camp-site Sandbank is situated on the most southern part of Austria, on the foothill of mountain Mittagskogel. It is sur..


Our historically listed Inn consists of five guest rooms and one double room family-suite. "The Heart of Alem" offers you the chance to experience "the intimate atmosphere of the old days" in its recently renovated interior.
In and around Alem you are able to wander or cycle along old historic routes that follow the course of the rivers "Maas en Waal". Typical small dutch ferries allow for a unique way to traverse the rivers and enjoy the countryside from the water.
For lunch and dinner we can provide you with recommendations for various restaurants close by. In Alem itself, opposite "The Heart of Alem", you will find a small marina which boasts a restaurant with a traditional dutch "Old Inn" ambience. As well as great food, the marina offers slow motorboats for rent. This gives you the opportunity to explore the rivers and experience the beauty of our country from the waters at your own pace.
The historical cities of Zaltbommel and 's-Hertogenbosch are a few kilometers away, whether you are interested in the host of bars, restaurants or culture, you will not be dissapointed. From enjoying a drink on the terrace overlooking the market in Zaltbommel, to spending a relaxing afternoon of shopping in 's-Hertogenbosch, there is plenty to do.
For the more active, in only 5 minutes from Alem, you can enjoy "De Dorpswaard", a 9 hole golf course in the heart of "De Bommelerwaard".
After a good night sleep the daily breakfast is pure luxury with fresh fruit, orange juice, biological bread and croissants. For a more hearty start to the day the kitchen chef will prepare bacon and eggs or an omelet on special request.
A true holiday-feeling is guaranteed!


text:
Sunrise Adds iPad App And Week View In Its Quest To Build The Best Calendar Platform
Romain Dillet	@romaindillet / 8 years
Calendar app Sunrise released a major update today, completing two missing pieces of the complicated calendar puzzle — you can now use Sunrise on your iPad with a new design tailored for bigger screens, and there is a much-requested week view to get a better picture of what your schedule looks like. Finally, the company added background updates so that your calendar is always up to date when you open the app.
"We realized that mobile is an even bigger paradigm shift than we originally thought," co-founder and CEO Pierre Valade told me. "Every other day, I don't even use a computer anymore — I consider the iPad as a mobile device. People want to feel productive anywhere, and work from their iPad. So that's why we built Sunrise for the iPad."
The iPad app is what you would expect if you are an existing Sunrise user. You get a bigger perspective on your calendar with a more detailed month view — you can actually see your events from the month view. Events work exactly the same way, with information pulled from Facebook, LinkedIn and other platforms. The infinite feed is slightly deemphasized with the full screen month view, but there is now this new week view. In fact, the week view makes more sense on the iPad than on the iPhone.
Most of the time, when you open your calendar, you want the answer to a simple question — what's next? That's why Sunrise's feed has always been one of its key features — you open the app and you get a scrollable list of all your next events. But sometimes, you want to schedule a call or a meeting and you need to see more easily when you are available.
That's where the week view kicks in. If you have a busy schedule with only a few empty zones, or want to see how your week looks at-a-glance, just press the new week view button at the top, and the screen will switch to a very readable week calendar.
Like the month grid, it relies a lot on scrolling, not on tiny text. Sunrise remains clean yet easy to understand. With a finger swipe, you can move around your day feed, week view or month grid. The overall design is very fluid.
[gallery ids="938746,938747,938748,938749,938750"]
When it comes to calendar apps, most of the time you have to fight with your calendar to add information and see what you want. But it's the opposite with Sunrise. Contrarily to competitor Fantastical which relies heavily on natural language input ("Lunch with Fred at 1pm"), Sunrise now tries to minimize keyboard interactions.
Sunrise was also heavily influenced by popular consumer apps like Snapchat and Frontback — reducing the number of taps is one of the team's top priorities. That's why the week view is an important tool as well. Instead of having a traditional and cumbersome iOS time picker, you can now switch to the week view and tap on the right time. It will only save a few seconds, but it greatly contributes to creating a finely tuned user experience. These little details explain why Sunrise is one of TechCrunch's top apps of 2013.
Reducing the number of taps is one of the team's top priorities.
Sunrise is only available on iOS for now, and works with Google and iCloud calendars. The company doesn't hide on its Twitter account that it is working on an Android version and Exchange support. It has raised $2.2 million so far.
The next goal for Sunrise is probably to create a ubiquitous calendar platform. While the app relies heavily on calendar APIs, everything happens on Sunrise's servers. For example, once you connect your Google calendar, Sunrise only has to interact and sync with its own servers. Choosing a server-side infrastructure will allow the company to easily recreate the same Sunrise experience on multiple operating systems. Sunrise is slowly but surely evolving from a neat iPhone app to a full-fledged calendar platform.
But the company doesn't forget to polish its original product. One update at a time, Sunrise removes each and every roadblock so that you don't have any reason left to hold back. Hundreds of thousands of users now use the app. "We think we now have the best calendar on iOS," Valade said. Yet, apart from new platform support, the same recurring question is also true for Sunrise: what's next?


WWE Royal Rumble 2019 Results: Becky Lynch, Seth Rollins reign as winners: The most awaited WWE Royal Rumble event finally came to an end by giving Seth Rollins as the winner of men's Royal Rumble match. WWE fans were very much excited for this Royal Rumble match which was finally held on 27th January 2019, Sunday with a kick-off event show at 5 p.m. ET.
Previously, the first name which was considered for the men's Royal Rumble match was Seth Rollins only following him other names was also considered as the Royal Rumble champion such as John Cena, Drew McIntyre, Mustafa Ali and Bobby Lashley.
Rollins first smash Strowman with a stomp to his back of the head which eventually send him out of the ring.
WWE through its official twitter accout tweeted, "#TheArchitect @WWERollins just STOMPED his way to @WrestleMania!!! #RoyalRumble".
Various other events also held in the Royal Rumble match such as Nia Jax entered the ring of men's Royal Rumble. In WWE Universal official twitter account, they also mentioned it by tweeting, "ATTENTION: @NiaJaxWWE is IN the Men's #RoyalRumble Match, and she just ELIMINATED @MustafaAliWWE! #RoyalRumble".
She becomes the fourth woman in history of WWE to enter men's Royal Rumble. Soon after coming third in the women's Royal Rumble, Nia Jax set free a surprise attack on R-Truth, the last competitor into the contest. Jax continued to go into the ring and remove Mustafa Ali, one of the top 5 anticipated possible winners of the event.
Previously also other women wrestlers has entered the ring like this and Jax is the fourth women to contend in the men's Rumble match, subsequent in the footsteps of the late Chyna, Beth Phoenix and Kharma.
On the other hand Bobby Lashley, WWE Intercontinental champion was eradicated minutes after entering the Royal Rumble match, and then he took all his frustration out on Seth Rollins. Lashley dragged Rollins out of the ring from beneath the ropes and banged him over an announce table, leaving Rollins knocked out. But somehow Rollins took over his attack and make a brave comeback late in the match, making him the ultimate champion.
WWE Network through its twitter account tweeted, "#TheAllMighty @fightbobby got eliminated in a HURRY, and that means BAD THINGS for @WWERollins as the Men's #RoyalRumble Match continues!".


I've been really fortunate to play some roles that really resonated with women. The first one was Thelma and Louise, where i had no idea the reaction was going to be what it was. I had become used to women recognizing me in the supermarket sometimes, and they'd say, "oh I like Beetle Juice maybe." Or, "I like the The Fly." But I was completely unprepared for the reaction after Thelma and Louise came out. It was 21 years ago now, I think. But there was a big cultural nerve that got struck. It was in editorials. It was in magazines everywhere. "Oh my God! Now the women have guns." It was really fascinating to be a part of that and what changed when people might recognize me from that movie was they were so passionate about it. And they wanted to share their thoughts and ideas. And "my friend and I call each other Thelma and Louise." It really brought home for me how few opportunities we give women to feel like that about the female characters in a movie. So I decided I'm going to keep this in mind and see if I can pick characters that women will appreciate on some level. And it happened that my very next part was in A League of Their Own, which was all about women, women working together. Suddenly I had the same reaction, but with 13-year-old girls, saying, "oh my God! I play sports because of that movie." Fortunately, later, I also got to play the first female President of the United States, briefly. And all of these experiences have impacted my life in a big way. It's fair to say that Thelma and Louise changed my life because it focused me so acutely on how women are portrayed in Hollywood, which has subsequently led me to be interested in how women and girls are portrayed in what kids see.