TOWARD A FULLY AND ABSOLUTELY RASTER-BASED EROSION MODELING BY USING RS AND GIS
Bambang Sulistyo(1*), Totok Gunawan(2), Hartono .(3), Projo Danoedoro(4)
(1) 
(2) 
(3) 
(4) 
(*) Corresponding Author
Abstract
The erosion map data is one of important data used in planning
conservation of degraded land. Generally, erosion data is predicted using a model
because to gain actual erosion requires much resource (timely, costly and labour
intensive). USLE (Universal Soil Loss Equation) is one of existing erosion models
applied worlwide, including Indonesia. Nevertheless, erosion analysis conducted is
based on analysis using vector-based maps. This method involves simplification,
either algorithms or procedures, and subject to subjectivity, so the result has high
uncertainty. This article deals with the idea to build a fully raster-based erosion
modeling. Steps required to obtain raster-based data was highlighted as from the
beginning up to the model validation to get an absolute model. The integration of
remote sensing and GIS was inevitably usedfor the analysis.
conservation of degraded land. Generally, erosion data is predicted using a model
because to gain actual erosion requires much resource (timely, costly and labour
intensive). USLE (Universal Soil Loss Equation) is one of existing erosion models
applied worlwide, including Indonesia. Nevertheless, erosion analysis conducted is
based on analysis using vector-based maps. This method involves simplification,
either algorithms or procedures, and subject to subjectivity, so the result has high
uncertainty. This article deals with the idea to build a fully raster-based erosion
modeling. Steps required to obtain raster-based data was highlighted as from the
beginning up to the model validation to get an absolute model. The integration of
remote sensing and GIS was inevitably usedfor the analysis.
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PDFDOI: https://doi.org/10.22146/ijg.2269
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Accredited Journal, Based on Decree of the Minister of Research, Technology and Higher Education, Republic of Indonesia Number 225/E/KPT/2022, Vol 54 No 1 the Year 2022 - Vol 58 No 2 the Year 2026 (accreditation certificate download)
ISSN 2354-9114 (online), ISSN 0024-9521 (print)
IJG STATISTIC