Open AccessAPPLICATION METHOD OF DIGITAL CLASSIFICATION TO MAKE LAND RESOURCES MAP
Author(s) -
Teguh Hariyanto,
Regita Faridatunisa Wijayanti,
Cherie Bhekti Pribadi
Publication year - 2021
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.179
H-Index - 26
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/731/1/012012
Subject(s) - scale (ratio) , segmentation , remote sensing , satellite imagery , computer science , geography , cartography , artificial intelligence
The Lumajang Urban Area (BWP) is the center of government and the economy in Lumajang Regency. The growth and development of cities in BWP Lumajang every year results in significant land changes. Thus, a map of land resources in Lumajang BWP is needed to determine the level of land use in the area. This research was conducted to make the Lumajang BWP Land Resource Map of Lumajang Regency using Geographic Information Systems (GIS). This study uses data processing methods with Object-Based Classification (OBIA). The data used for this study are the results of the Pleiades 1-A High-Resolution Satellite Image (CSRT) segmentation in 2016. The data used as an initial reserve (asset) is the 2009 RBI map. The data used for resource utilization (liability) is the result segmentation of Pleiades 1-A HighResolution Satellite Imagery (CSRT) in 2016. In processing OBIA using scale, shape, and compactness parameters. In this study, it can be seen that the scale parameters have the greatest role in the formation of OBIA segmentation. The smaller the scale value is given results in more accurate segmentation. The results of this study are that at a higher level of accuracy is the method of image segmentation method of 89,041% and the land cover that has the largest decrease in area is irrigated rice fields and the largest increase is a plantation.