globalchange  > 气候变化事实与影响
DOI: 10.1016/j.jag.2015.09.011
Scopus记录号: 2-s2.0-85015947834
论文题名:
Varying applicability of four different satellite-derived soil moisture products to global gridded crop model evaluation
作者: Sakai T; , Iizumi T; , Okada M; , Nishimori M; , Grünwald T; , Prueger J; , Cescatti A; , Korres W; , Schmidt M; , Carrara A; , Loubet B; , Ceschia E
刊名: International Journal of Applied Earth Observation and Geoinformation
ISSN: 15698432
出版年: 2016
卷: 48
起始页码: 51
结束页码: 60
语种: 英语
英文关键词: Cropland ; Flux tower observation ; Intercomparison ; Satellite remote sensing ; Soil moisture
Scopus关键词: AMSR-E ; crop plant ; reliability analysis ; remote sensing ; satellite data ; soil moisture ; Glycine max ; Triticum aestivum ; Zea mays
英文摘要: Satellite-derived daily surface soil moisture products have been increasingly available, but their applicability to global gridded crop model (GGCM) evaluation is unclear. This study compares four different soil moisture products with the flux tower site observation at 18 cropland sites across the world where either of maize, soybean, rice and wheat is grown. These products include the first and second versions of Climate Change Initiative Soil Moisture (CCISM-1 and CCISM-2) datasets distributed by the European Space Agency and two different AMSR-E (Advanced Microwave Scanning Radiometer–Earth Observing System)-derived soil moisture datasets, separately provided by the Japan Aerospace Exploration Agency (AMSRE-J) and U.S. National Aeronautics and Space Administration (AMSRE-N). The comparison demonstrates varying reliability of these products in representing major characteristics of temporal pattern of cropland soil moisture by product and crop. Possible reasons for the varying reliability include the differences in sensors, algorithms, bands and criteria used when estimating soil moisture. Both the CCISM-1 and CCISM-2 products appear the most reliable for soybean- and wheat-growing area. However, the percentage of valid data of these products is always lower than other products due to relatively strict criteria when merging data derived from multiple sources, although the CCISM-2 product has much more data with valid retrievals than the CCISM-1 product. The reliability of the AMSRE-J product is the highest for maize- and rice-growing areas and comparable to or slightly lower than the CCISM products for soybean- and wheat-growing areas. The AMSRE-N is the least reliable in most location-crop combinations. The reliability of the products for rice-growing area is far lower than that of other upland crops likely due to the extensive use of irrigation and patch distribution of rice paddy in the area examined here. We conclude that the CCISM-1, CCISM-2 and AMSRE-J products are applicable to GGCM evaluation, while the AMSRE-N product is not. However, we encourage users to integrate these products with in situ soil moisture data especially when GGCMs simulations for rice are evaluated. © 2015 Elsevier B.V.
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/80083
Appears in Collections:气候变化事实与影响

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作者单位: Agro-Meteorology Division, National Institute for Agro-Environmental Sciences, 3-1-3 Kannondai, Tsukuba, Ibaraki, Japan; Technische Universität Dresden, Institute of Hydrology and Meteorology, Chair of Meteorology, Dresden, Germany; The National Laboratory for Agriculture and the Environment (USDA-ARS-NLAE), 2110 University Blvd, Ames, IA, United States; European Commission, Joint Research Centre, Institute for Environment and Sustainability, Ispra, Italy; Institute of Geography, University of Cologne, Cologne, Germany; Agrosphere Institute (IBG-3), Institute of Bio- and Geosciences, Jülich, Germany; Fundación Centro de Estudios Ambientales del Mediterráneo (CEAM), 14, Parque Tecnológico, Paterna, Spain; INRA, UMR INRA-AgroParisTech ECOSYS, Thiverval-Grignon, France; CESBIO (CNES/CNRS/UPS/IRD), 18, Avenue Edouard Belin, Toulouse Cedex, France

Recommended Citation:
Sakai T,, Iizumi T,, Okada M,et al. Varying applicability of four different satellite-derived soil moisture products to global gridded crop model evaluation[J]. International Journal of Applied Earth Observation and Geoinformation,2016-01-01,48
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