Karya
Judul/Title Topography Variable to Downscale GPM Satellite Precipitation Data Using Geographically Weighted Regression
Penulis/Author IRFAN ZAKI IRAWAN (1) ; Drs. Sudaryatno, M.Si. (2); Josaphat Tetuko Srisumantyo (3)
Tanggal/Date 2021
Kata Kunci/Keyword
Abstrak/Abstract GPM is a satellite that capture global precipitation data, using radar, microwave, and infrared sensor. The data has a rough spatial resolution, so it is necessary to detail the spatial resolution so that it can be used in a more local area. Geographically Weighted Regression (GWR) is a regression-based method that can be used to detail spatial resolution by utilizing the relationship of an independent variable, in this case precipitation, with a predictor variable that has a strong correlation. Topography is a biophysical element that is closely related to precipitation, for example, local type of rainfall or orographic type of rain. ALOS PALSAR is a radar sensor satellite that records the altitude of the earth's surface.
Level Internasional
Status
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