| dc.description.abstract | Rainfall is the accumulation of rainwater in a uniform rain
measurement that is flat and does not absorb, drip, or flow. The rain
occurs on a wide scale and spreads out, but in Indonesia, the
measurements are only conducted at a few points, so it is hard to
describe the rainfall temporally or spatially. When predicting rainfall
information on a regional or global scale, alternative data is needed,
namely remote sensing in the form of Integrated Multi-satellite
Retrievals for GPM (IMERG) with large-scale spatial resolution.
Furthermore, IMERG needs validated downscaling to be used as
alternative data. IMERG downscaling uses the support vector machine
(SVM) regression method and is validated using the R-squared (R2),
root mean square (RMSE), and bias methods. IMERG downscaling
data is validated using rainfall data taken with a rain gauge. The results
of the downscaled and calibrated IMERG validation show relatively
high R2 and bias values, namely 0.901 and 0.2, respectively. However,
the model exhibits a relatively small prediction error for rainfall, as
evidenced by the average error value of 2.227 mm/day each year. Based
on these validation results, this method holds great promise for
utilization in areas with limited spacing between rainfall stations, as
the model is capable of predicting rainfall data accurately in regions
without rainfall stations. Further research is highly needed for the
upcoming years. | en_US |
