Please use this identifier to cite or link to this item:
Title: Geostatistical approaches to conflation of continental snow data
Authors: Zhang, Jingxiong 
Kyriakidis, Phaedon 
Kelly, Richard 
Keywords: Hydrological systems;Effective water resources management;Ground-measured;Microwave remotely sensed snow data
Category: Environmental Engineering
Field: Engineering and Technology
Issue Date: Sep-2009
Publisher: Taylor & Francis, Ltd
Source: International Journal of Remote Sensing, 2009, Volume 30, Issue 20, pages 5441-5451
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.
ISSN: 0143-1161
1366-5901 (Online)
DOI: 10.1080/01431160903130960
Rights: © Informa UK Limited, an Informa Group Company
Type: Article
Appears in Collections:Άρθρα/Articles

Show full item record

Citations 20

checked on Dec 8, 2018

Citations 10

Last Week
Last month
checked on Dec 4, 2018

Page view(s)

Last Week
Last month
checked on Dec 9, 2018

Google ScholarTM



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.