Open AccessSpatial Evapotranspiration Modeling Assisted With Landsat 8 Image Using Sebal And Geographically Weighted Regression Methods In Magelang District
Author(s) -
AF Nugraha,
BS Hadi
Publication year - 2021
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/884/1/012026
Subject(s) - evapotranspiration , environmental science , albedo (alchemy) , normalized difference vegetation index , scale (ratio) , regression analysis , vegetation (pathology) , geographically weighted regression , geographic information system , spatial analysis , agriculture , remote sensing , geography , cartography , mathematics , statistics , climate change , geology , medicine , art , ecology , oceanography , archaeology , pathology , performance art , biology , art history
Information about evapotranspiration is very important in relation to vegetation because it can be used for planning both in urban planning and agriculture. Magelang Regency has a lot of vegetated green land, both agricultural and non-agricultural and has no information about evapotranspiration. The calculation of evapotranspiration uses the SEBAL (Surface Energy Balance Algorithm for Land) method and modeling uses the GWR (Geographiccaly Weighted Regression) model. Calculation and modeling assisted by QGIS 2.14, QGIS 3.6, SPSS 20, and GWR 4.09 applications. The results showed that (1) GWR evapotranspiration model with significance (sig.) 5% is divided into 3 sub-district groups according to the significant variables in the sub-district (2) NDVI and Surface Albedo variables have a small effect on a global scale and have a large effect on a local scale.