Open AccessAccuracy Assessment of Land Use Change Analysis Using Google Earth in Sadar Watershed Mojokerto Regency
Author(s) -
F A Islami,
Suria Tarigan,
Enni Dwi Wahjunie,
Bambang Dwi Dasanto
Publication year - 2022
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/950/1/012091
Subject(s) - cohen's kappa , watershed , java , land use , land cover , remote sensing , settlement (finance) , agriculture , agricultural land , geography , population , environmental science , forestry , hydrology (agriculture) , cartography , computer science , statistics , mathematics , geology , engineering , civil engineering , machine learning , demography , archaeology , geotechnical engineering , sociology , world wide web , payment , programming language
Mojokerto Regency is one of the regencies in East Java with a high population growth rate of around 0.96%, thus encouraging significant land use changes on built-up areas. Classifying remote sensing imageries to obtain reliable and accurate land use and land cover (LULC) information remains a challenge that depends on many factors such as complexity of the landscape, the remote sensing data selected, image processing, and classification methods. This study examined the accuracy assessment of LULC classification using Google Earth in Sadar Watershed, Mojokerto, East Java Indonesia for the years 2010, 2015, and 2020. The land use was classified into five categories; those are agriculture land (paddy field, field, and plantation), non-agriculture land (forest land, bushland, grazing land), bare land, settlement land, and water bodies. Around 85 random points were generated in ArcGIS and verified with Google Earth. The results showed that the Overall Accuracy of LULCC for 2010 was 80.2% and Kappa Coefficient was 0.74; for 2015, the Overall Accuracy was 85.3% and Kappa Coefficient was 0.8, and for 2020, the Overall Accuracy was 84.0%, and Kappa Coefficient was 0.79. All accuracy is considered as good categorized and acceptable in both overall accuracy and Kappa Coefficient.