Publikasi Penelitian

Pemanfaatan Citra dari Google Earth dan DEM Aster yang Bebas Diunduh untuk Mendapatkan Beberapa Parameter Lahan


Abstrak (Indonesia):
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Abstract (English) :
Land cover and slope are essential biophysical parameters for monitoring and evaluating of watershed condition. Those informations can be extracted from remotely sensed data. The data are commonly expensive, while monitoring and evaluation (monev) of watershed condition should be conducted in every year. Therefore, utilization of free access of remotely sensed data is an effort to reduce cost of monev. This study is intended to evaluate the utilization of DEM ASTER and image from Google Earth in providing information on slope and land cover. These parameters were then used to predict erosion based on USLE (Universal Soil Loss Equation) method and land capability classes. The study was conducted in Samin Sub-Watershed, Central Java. The results suggest that open access of imageries provide reasonable results for slope and land cover classifications. For slope classification, DEM ASTER provides an overall accuracy of 79.5% with Kappa agreement of 0.67, while land cover classification using image from Google Earth produces an average accuracy of 70.3% with Kappa agreement of 0.60. Prediction of soil erosion shows that severe soil erosion is also found in forest area because of its very steep slope. Land capability classification shows that the study area is dominated by class IV with slope as a restriction. It is found that some of the area in class VII is still used for settlement and dryland cultivation with minimum soil conservation practices. The use of free access remotely sensed data reduce the cost of monitoring in term of slope and land cover classification, with reasonable result. The limitation using the image is land cover classification must be conducted based on visual interpretation.
Media Publikasi :
Prosiding Seminar Nasional Hasil Penelitian Teknologi Pengelolaan DAS
Penulis :
Tyas Mutiara Basuki, Dr., Ir., M.Sc., Nining Wahyuningrum, Ir., M.Sc.
Ukuran Berkas :
1.6 MB

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