Abstract
This article evaluates an infrared-based satellite algorithm for rainfall estimation, the Convective Stratiform technique, over Mediterranean. Unlike a large number of works that evaluate remotely sensed estimates concentrating on global measures of accuracy, this work examines the relationship between ground truth and satellit0e derived data in a local scale. Hence, we examine the fit of ground truth and remotely sensed data on a widely adopted probability distribution for rainfall totals - the mixed lognormal distribution - per measurement location. Moreover, we test for spatial nonstationarity in the relationship between in situ observed and satellite-estimated rainfall totals. The former investigation takes place via using recent algorithms that estimate nonlinear mixed models whereas the latter uses geographically weighted regression.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 1438-1447 |
| Number of pages | 10 |
| Journal | Environmental Modelling and Software |
| Volume | 23 |
| Issue number | 12 |
| DOIs | |
| State | Published - Dec 2008 |
| Externally published | Yes |
Keywords
- Geographically weighted regression
- Nonlinear mixed models
- Rainfall estimation
- Remotely sensed estimations
- Zero inflated lognormal distribution
ASJC Scopus subject areas
- Software
- Environmental Engineering
- Ecological Modeling
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