标题：The Impact of Local Acquisition Time on the Accuracy of Microwave Surface Soil Moisture Retrievals over the Contiguous United States作者：Lei, Fangni; Crow, Wade T.; Shen, Huanfeng; Parinussa, Robert M.;Holmes, Thomas R. H.

来源出版物：Remote Sensing 卷：7 期：10 页：13448-13465 DOI：10.3390/rs71013448 出版年：OCT 2015

摘要：Satellite-derived soil moisture products have become an important data source for the study of land surface processes and related applications. For satellites with sun-synchronous orbits, these products are typically derived separately for ascending and descending overpasses with different local acquisition times. Moreover, diurnal variations in land surface conditions, and the extent to which they are accurately characterized in retrieval algorithms, lead to distinct systematic and random error characteristics in ascending versus descending soil moisture products. Here, we apply two independent evaluation techniques (triple collocation and direct comparison against sparse ground-based observations) to quantify (correlation-based) accuracy differences in satellite-derived surface soil moisture acquired at different local acquisition times. The orbits from different satellites are separated into two overpass categories: AM (12:00 a.m. to 11:59 a.m. Local Solar Time) and PM (12:00 p.m. to 11:59 p.m. Local Solar Time). Results demonstrate how patterns in the accuracy of AM versus PM retrieval products obtained from a variety of active and passive microwave satellite sensors vary according to land cover and across satellite products with different local acquisition times.

入藏号：WOS:000364328600040

文献类型：Article

语种：English

作者关键词：remote sensing, soil moisture, acquisition time, retrieval algorithm, data merging

扩展关键词：TRIPLE COLLOCATION; GLOBAL-SCALE; L-BAND; AMSR-E; SMOS; ERRORS; LAND; TEMPERATURE; VEGETATION; GRASS

通讯作者地址：Lei, Fangni; Wuhan Univ, Sch Resource & Environm Sci, Wuhan 430072, Peoples R China.

电子邮件地址：leifangni@whu.edu.cn; Wade.Crow@ars.usda.gov; shenhf@whu.edu.cn; r.parinussa@unsw.edu.au; Thomas.Holmes@ars.usda.gov

地址：

[Lei, Fangni; Shen, Huanfeng]Wuhan Univ, Sch Resource & Environm Sci, Wuhan 430072, Peoples R China.

[Lei, Fangni; Crow, Wade T.; Holmes, Thomas R. H.] USDA ARS, Hydrol & Remote Sensing Lab, Beltsville, MD 20705 USA.

[Parinussa, Robert M.] Univ New S Wales, Sch Civil & Environm Engn, Water Res Ctr, Sydney, NSW 2052, Australia.

[Holmes, Thomas R. H.] Sci Syst & Applicat Inc, Greenbelt, MD 20705 USA.

研究方向：Remote Sensing

ISSN：2072-4292

影响因子（2014）：3.180