Please use this identifier to cite or link to this item: https://ktisis.cut.ac.cy/handle/10488/10089
Title: Geostatistical Integration of Coarse Resolution Satellite Precipitation Products and Rain Gauge Data to Map Precipitation at Fine Spatial Resolutions
Authors: Park, No-Wook 
Kyriakidis, Phaedon 
Hong, Sungwook 
Major Field of Science: Engineering and Technology
Field Category: Civil Engineering
Keywords: Downscaling;Multivariate kriging;Tropical Rainfall Measuring Mission (TRMM)
Issue Date: 1-Mar-2017
Source: Remote Sensing, 2017, vol. 9, no. 3
Volume: 9
Issue: 3
Journal: Remote Sensing 
Abstract: This paper investigates the benefits of integrating coarse resolution satellite-derived precipitation estimates with quasi-point rain gauge data for generating a fine spatial resolution precipitation map product. To integrate the two precipitation data sources, a geostatistical downscaling and integration approach is presented that can account for the differences in spatial resolution between data from different supports and adjusts inherent errors in the coarse resolution precipitation estimates. First, coarse resolution precipitation estimates are downscaled at a fine spatial resolution via area-to-point kriging to allow direct comparison with rain gauge data. Second, the downscaled precipitation estimates are integrated with the rain gauge data by multivariate kriging. In particular, errors in the coarse resolution precipitation estimates are adjusted against rain gauge data during this second stage. In this study, simple kriging with local means (SKLM) and kriging with an external drift (KED) are used as multivariate kriging algorithms. For comparative purposes, conditional merging (CM), a frequently-applied method for integrating rain gauge data and radar precipitation, is also employed. From a case study with Tropical Rainfall Measuring Mission (TRMM) 3B43 monthly precipitation products acquired in South Korea from May-October in 2013, we found that the incorporation of TRMM data with rain gauge data did not improve prediction performance when the number of rain gauge data was relatively large. However, the benefit of integrating TRMM and rain gauge data was most striking, regardless of multivariate kriging algorithms, when a small number of rain gauge data was used. These results indicate that the coarse resolution satellite-derived precipitation product would be a useful source for mapping precipitation at a fine spatial resolution if the geostatistical integration approach is applied to areas with sparse rain gauges.
ISSN: 2072-4292
DOI: 10.3390/rs9030255
Rights: © by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license.
Type: Article
Affiliation : Inha Univeristy 
Cyprus University of Technology 
Sejong University 
Appears in Collections:Άρθρα/Articles

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