Pemetaan Padang Lamun dengan Citra ALOS dan Citra ASTER di Pulau Pari, Kabupaten Administratif Kepulauan Seribu
Shofa, Moh Ikhwanush
Natih, Nyoman Metta N.
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One of the utilization of remote sensing technology is in the seagrass observations. Utilization of satellite imagery for mapping seagrass has been done before in Pari Island in 2008. Tobe able to see the changes therefore seagrass monitoring still needs to be done. The purpose of this study is to map the distribution of seagrass in Pari Island using ALOS and ASTER imagery as well as know the value of the accuracy of the seagrass distribution maps. Image processing for image sharpening using composite and Lizenga algorithm. Image classification was conducted using unsupervised classification and supervised classification. Type of seagrass found in the waters of Pari Island in general is Enhalus accoroides, Thalassia hemprichii, and Cymodocea rotundata. Extensive seagrass beds mapped with unsupervised classification method on ALOS imagery is 1.641 km2 with an accuracy of 71.01 % and the ASTER image of 1794 km2 with an accuracy of 68.11 %. Mapping the supervised classification methods known seagrass mapped area of 1.373 km2 is the ALOS images with an accuracy of 62.32 % and the ASTER image of 1.389 km2 with an accuracy of 60.87 %. Seagrass mapping with ALOS imagery has higher accuracy value of mapping using ASTER imagery.