You are presented with multiple paper abstracts, alongside the associated literature review and chapter titles. Given the provided information, you are going to do a literature review. Please generate a coherent literature review that synthesizes the content, draws connections between different works, highlights major findings, and identifies any gaps in the existing research.

Literature Review Title: A Review of Wetland Remote Sensing 
Chapter Title:  Review of Medium Spatial Resolution Data for Wetland Studies 
1. Abstract of Cited Paper (BIB001):  A method has been developed, based on spectral mixture analysis, to estimate the concentration of suspended sediment in surface waters of the Amazon River wetlands from Landsat MSS and TM images. Endmembers were derived from laboratory reflectance measurements of water-sediment mixtures with a range of sediment concentrations. Using these reference spectra, we applied a linear mixture analysis to multispectral images after accounting for instrument and atmosphere gains and offsets. Sediment concentrations were estimated for individual pixels from the mixture analysis results based on a nonlinear calibration curve relating laboratory sediment concentrations and reflectance to endmember fractions. The uncertainty in the sediment concentrations derived from this analysis for three Amazon images is predicted to be within ±20 mg/L, and the concentrations fall within a range of concentrations of suspended sediment that were measured at several times and places in the field over the past 15 years. The emphasis of our work is to use the patterns of sediment concentrations to compute the approximate volumes of sediment that are transferred between the main channel and floodplain of the Amazon River. However, the methodology can be applied universally if the optical properties of water and sediment at the site are known, and it is, therefore, useful for the study of suspended sediment concentrations in surface waters of wetlands elsewhere. 
2. Abstract of Cited Paper (BIB002):  This study aimed to develop simple remote-sensing techniques suitable for mapping and monitoring wetlands, using Landsat TM imagery of inland wetland sites in Victoria and New South Wales. A range of classification methods was examined in attempts to map the location and extent of wetlands and their vegetation types. Multi-temporal imagery (winter/spring and summer) was used to display seasonal variability in water regime and vegetation status. Simple density slicing of the mid-infrared band (TM5) from imagery taken during wet conditions was useful for mapping the location and extent of inundated areas. None of the classification methods tested reproduced field maps of dominant vegetation species; however, density slicing of multi-temporal imagery produced classes based on seasonal variation in water regime and vegetation status that are useful for reconnaissance mapping and for examining variability in previously mapped units. Satellite imagery is unlikely to replace aerial photography for detailed mapping of wetland vegetation types, particularly where ecological gradients are steep, as in many riverine systems. However, it has much to offer in monitoring changes in water regime and in reconnaissance mapping at regional scales. 
3. Abstract of Cited Paper (BIB003):  Mangrove forests provide important ecosystem goods and services for human society. Extensive coastal development in many developing countries has converted mangrove forests to other land uses without regard to their ecosystem service values; thus, the ecosystem state of mangrove forests is critical for officials to evaluate sustainable coastal management strategies. The objective of this study is to investigate the multidecadal change in mangrove forests in Ca Mau peninsula, South Vietnam, based on Landsat data from 1979 to 2013. The data were processed through four main steps: 1) data preprocessing; 2) image processing using the object-based image analysis (OBIA); 3) accuracy assessment; and 4) multitemporal change detection and spatial analysis of mangrove forests. The classification maps compared with the ground reference data showed the satisfactory agreement with the overall accuracy higher than 82%. From 1979 to 2013, the area of mangrove forests in the study region had decreased by 74%, mainly due to the boom of local aquaculture industry in the study region. Given that mangrove reforestation and afforestation only contributed about 13.2% during the last three decades, advanced mangrove management strategies are in an acute need for promoting environmental sustainability in the future.

Literature Review:
In this research, medium spatial resolution refers to the spatial resolution within the range of 4-30 m. In this paper, medium-resolution data mainly includes Landsat TM/Enhanced Thematic Mapper Plus (ETM+), Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), China & Brazil Earth Resource Satellite (CBERS), Systeme Probatoire D'Observation De La Terre (SPOT 1-4) and Advanced Land Observing Satellite (ALOS) Advanced visible and near infrared radiometer type 2 (AVNIR-2). Landsat data were used the most in wetland studies. Of the 5719 wetland research papers, 1259 papers used Landsat data. This research reviewed 95 papers of those 1259 papers based on six study themes (Table 2) . Landsat Multispectral Scanner (MSS) has been sparsely used in wetland studies because of its coarse resolution (80 m, recent distribution is resampled to 60 m); in many cases, MSS images were used together with TM and other sensors to prolong the time scale of wetland change detection BIB001 BIB004 BIB002 . Studies using TM data usually have higher accuracy of wetland mapping than MSS because of the improved spatial resolution and the increased number of optical bands BIB003 . Because of the recent launch (2013), Landsat 8 Operational Land Imager (OLI) data have not been used for many wetland studies. Figure 2 shows the Landsat images of Zhalong Nature Reserve in Qiqihar city of China. (Table 2) . Landsat Multispectral Scanner (MSS) has been sparsely used in wetland studies because of its coarse resolution (80 m, recent distribution is resampled to 60 m); in many cases, MSS images were used together with TM and other sensors to prolong the time scale of wetland change detection BIB001 BIB004 BIB002 . Studies using TM data usually have higher accuracy of wetland mapping than MSS because of the improved spatial resolution and the increased number of optical bands BIB003 . Because of the recent launch (2013), Landsat 8 Operational Land Imager (OLI) data have not been used for many wetland studies. Figure 2 shows the Landsat images of Zhalong Nature Reserve in Qiqihar city of China. Table 2 . Wetland studies using Landsat data for seven study themes.