Land Cover/Use Classification at Landsat 8 with Random Forest and Support Vector Machine Algorithm in Sumedang Regency, West Java
DOI:
https://doi.org/10.29244/jitl.27.1.24-31Keywords:
national strategic project, reflectance pattern, machine learningAbstract
Sumedang Regency is one of the selected regencies in the national strategic project, in the form of the construction of the Jatigede Reservoir and the Cisumdawu Toll Road. This development has a negative impact on the agricultural sector because it causes a change in the function of agricultural land, so that measurable monitoring of land cover/use is needed. This study aims to identify the pattern of reflectance values for each land cover/use and compare the RF and SVM approaches in the classification of land cover/use in Sumedang Regency in 2023. The pattern of reflectance values for each land cover/use is unique, but the use of rice fields and fields/dry fields has a similar pattern and is more susceptible to misclassification. The RF and SVM approaches produce high classification accuracy, which is 93.6% for RF and 98% for SVM. The difference in RF and SVM classification results is 34.64%. This difference occurs due to differences in the way the classification works.
Keywords : national strategic project, reflectance pattern, machine learning
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Department of Soil Science and Land Resources Departemen Ilmu Tanah dan Sumberdaya Lahan, Faculty of Agriculture Fakultas Pertanian, IPB University
