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https://hdl.handle.net/20.500.14279/8670
Τίτλος: | Geostatistical approaches to conflation of continental snow data | Συγγραφείς: | Zhang, Jingxiong Kyriakidis, Phaedon Kelly, Richard |
Major Field of Science: | Engineering and Technology | Field Category: | Environmental Engineering | Λέξεις-κλειδιά: | Hydrological systems;Effective water resources management;Ground-measured;Microwave remotely sensed snow data | Ημερομηνία Έκδοσης: | Σεπ-2009 | Πηγή: | International Journal of Remote Sensing, 2009, vol. 30, no. 20, pp. 5441-5451 | Volume: | 30 | Issue: | 20 | Start page: | 5441 | End page: | 5451 | Περιοδικό: | International Journal of Remote Sensing | Περίληψη: | 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: | https://hdl.handle.net/20.500.14279/8670 | ISSN: | 13665901 | DOI: | 10.1080/01431160903130960 | Rights: | © Taylor & Francis | Type: | Article | Affiliation: | Wuhan University University of California University of Waterloo |
Publication Type: | Peer Reviewed |
Εμφανίζεται στις συλλογές: | Άρθρα/Articles |
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