Analisis Ketelitian Dem Aster Gdem, Srtm, Dan Lidar Untuk Identifikasi Area Pertanian Tebu Berdasarkan Parameter Kelerengan (Studi Kasus : Distrik Tubang, Kabupaten Merauke, Provinsi Papua)

Abstract

Slopes are the earth\u27s surface that has a sloping uniform. Slope is the ratio between the height difference and distance. One of information USAges of slope is in the field of sugarcane plantations especially for the determination of the planting area. The mapping process of thousands acres of area is certainly not efficient when using directly survey mapping survey method. One of alternative methods that usually applied is by using the elevation data of DEM SRTM and ASTER which are considered as a high ground area. However, many other literatures explain that the elevation of DEM (Digital Elevation Model) is actually a level of land cover elevation above ground. This condition triggers the present method of LIDAR (Light Detection and Ranging) that is considered better than the previous methods, due to the laser beam based which possibly measures the height of terrain. This study analyzed relationship and differences in the classification slope DEM SRTM and ASTER data with the classification slope LiDAR data. Area examined in this research is the sugarcane plantations area with the vast of ± 7,370 hectares in Tubang, Merauke, Papua.Map making slope is cited from SOP (Standard Operating Procedures) issued by BIG (Badan Informasi Geospasial) in 2012 related to the data processing for mapping slope number 03.01.11.02. Whereas, the outline of the data processing stages are including gridding, definition of projection system, slope classification, clustering, smoothing, and generalization. While, the distribution of slope classification types following the rules made by Puslittanak (Pusat Penelitian Tanah dan Agroklimat), it is due to this study relates to the condition of agricultural land. This study is resulting three slope maps with a scale of 1:30,000 of LiDAR, SRTM and ASTER data.After the testing of height data towards the BM control point and RBI maps, revealed that LiDAR data has the best difference with a standard deviation of ± 1.387 m, then SRTM ± 4.339 m, and ASTER ± 7.979 m. However, the manual calculations indicated that the three data produced the same slope analysis with the RBI, differentiation and standard deviations are less than ± 0.4 m. Then the results of correlation and significance of the slope broad classification show a 49.6% direct relationship between SRTM and LIDAR (considered to be enough), whereas a 57.8% indirect relationship between LIDAR and ASTER (considered to be strong). And the value difference between LiDAR and SRTM is 3,382,840 m², while the between LiDAR and ASTER is 5,547,200 m². The result of recapitulating sugarcane planting area which based of DEM/DTM has explained that the more resemble is between LiDAR and SRTM with the value difference is 1,380,356.127 m², while the between LiDAR and ASTER is 9,952,798.232 m². Then the equality of arable area which resemble with the result of LiDAR is ASTER, it has equation a 85.18%, whereas SRTM a 73.76%