Open AccessDeveloping land capability to reduce land degradation and disaster incident in Bendo Watershed, Banyuwangi
Author(s) -
Syamsul Bachri,
Sumarmi Sumarmi,
Listyo Yudha Irawan,
Mohammad Naufal Fathoni,
Ahmad Mufti Fawaid,
Sismi Gusty Nuraini,
Kresno Sastro Bangun Utomo,
Yulius Eka Aldianto
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 - 10.1088/1755-1315/630/1/012004
Subject(s) - watershed , land degradation , landform , land use , watershed area , environmental science , landslide , unit (ring theory) , hydrology (agriculture) , geography , water resource management , environmental resource management , computer science , civil engineering , cartography , geology , engineering , geomorphology , mathematics , machine learning , mathematics education , geotechnical engineering
Land degradation have caused decline in land productivity and triggering landslide incident in Bendo Watershed. This area has been selected as study area which represent characteristic upland area of the region. The research examines land capability analysis in order to reduce land degradation and disaster incidents and for sustainable use of land resources. The geomorphology approach was used along with sixteen of landform unit as unit sample. Further, artificial neural network models were used to classify land capabilities. Network architecture 10-8-1 was used on classification process due to the lowest error value factors. The findings of the study present that 20, 46% of Bendo watershed are prone to land degradation. Physical characteristic within area are contributing increasing land degradation. The capability classes of Bendo watershed ranges from class II to class VII. The upstream areas have erosion and intensive landslides as its limited factors, hence tend to have poor land capability classes. While the middle to downstream areas of Bendo watershed have better land capability classes with more diverse land use recommendations.