Evaluating remotely sensed rainfall estimates using nonlinear mixed models and geographically weighted regression

Y. Kamarianakis; H. Feidas; G. Kokolatos; N. Chrysoulakis; V. Karatzias

doi:10.1016/j.envsoft.2008.04.007

Evaluating remotely sensed rainfall estimates using nonlinear mixed models and geographically weighted regression

Y. Kamarianakis, H. Feidas, G. Kokolatos, N. Chrysoulakis, V. Karatzias

Arizona State University

Research output: Contribution to journal › Article › peer-review

33 Scopus citations

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	https://doi.org/10.1016/j.envsoft.2008.04.007
State	Published - Dec 1 2008

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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10.1016/j.envsoft.2008.04.007

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AU - Karatzias, V.

PY - 2008/12/1

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Evaluating remotely sensed rainfall estimates using nonlinear mixed models and geographically weighted regression

Abstract

Keywords

ASJC Scopus subject areas

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