Abstract:
Distribution and density of unfamiliar observation post network, the lack of data and non-continuous data
becomes problem in conducting analysis and making information of climate classification in South
Kalimantan. One technique to obtain rainfall data today is by using satellite data. one of the rainfall
prediction techniques using satellite data is GSMaP. Utilization of GSMaP data is an alternative data that
needs to be studied to overcome the limitations of surface observation data. Data validation is done using
statistical method by analizing the correlation value (r) and RMSE (Root Mean Square Error). Climation
zonation based on climate classification Schmidt Ferguson. Schmidt Ferguson climate clas sification
calculation from GSMaP data mapped spatially using Arc GIS software 10.2. GSMaP satellite rainfall data
validation and surface rainfall showed a high correlation value for monthly average with correlation value
0,89 and RMSE 41,8mm/month (1,66mm/day). Schmidt Ferguson climate zoning based on GSMaP satellite
data in southern Kalimantan is divided into 3 climate zones, namely type A, B and C.
