Please use this identifier to cite or link to this item: https://ktisis.cut.ac.cy/handle/10488/8670
Title: Geostatistical approaches to conflation of continental snow data
Authors: Zhang, Jingxiong 
Kyriakidis, Phaedon 
Kelly, Richard 
Major Field of Science: Engineering and Technology
Field Category: Environmental Engineering
Keywords: Hydrological systems;Effective water resources management;Ground-measured;Microwave remotely sensed snow data
Issue Date: Sep-2009
Source: International Journal of Remote Sensing, 2009, vol. 30, no. 20, pp. 5441-5451
Volume: 30
Issue: 20
Start page: 5441
End page: 5451
Journal: International Journal of Remote Sensing 
Abstract: Information on snow cover extent and mass is important for characterization of hydrological systems at different spatial and temporal scales, and for effective water resources management. This paper explores geostatistics for conflation of ground-measured and passive microwave remotely sensed snow data, here referred to as primary and secondary data, respectively. A modification to conventional cokriging is proposed, which first estimates differenced local means between sparsely distributed primary data and densely sampled secondary data by cokriging, followed by a best linear estimation of the primary variable based on the primary data and bias-corrected secondary data, with variogram models revised in the light of corrections made to the original secondary data. An experiment was carried out with snow depth (SD) data derived from the Advanced Microwave Scanning Radiometer for EOS (AMSR-E) instrument and the World Meteorological Organization (WMO) SD measurement, confirming the effectiveness of the proposed methodology.
URI: http://ktisis.cut.ac.cy/handle/10488/8670
ISSN: 1366-5901
DOI: 10.1080/01431160903130960
Rights: © Taylor & Francis
Type: Article
Affiliation : Wuhan University 
University of California 
University of Waterloo 
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