农业工程学报2011，Vol.27Issue(12)：161-167,7.DOI:10.3969/j.issn.1002-6819.2011.12.031
基于NDVI优化选择的土壤水分数据同化
Soil moisture data assimilation based on NDVI optimization
摘要
Abstract
Soil moisture could be better estimated through assimilation at various observations into ecosystem models to use all sources of information well. However, different assimilation results could be got from different observations. And the results might have big differences. Three different remote sensed surface soil moisture derived from MODIS red-, near infrared and shortwave infrared bands was assimilated to initialize the soil moisture in BEPS(boreal ecosystem production simulator) in May to July in 2008, taking Guguan city in Ningxia as a case. Three different drought indexes PDI (perpendicular drought index)-, SPSI (shortwave infrared perpendicular water stress index)and MPDI (modify perpendicular drought index)to derive the surface soil moisture were chose based on the time-series NDVI (normalized difference vegetation index) threshold. An Ensemble Kalman Filter was used to perform the data assimilation. The in-situ sites' observations were used to verify the assimilation results which were got from three different remote sensed results. It was demonstrated that the method of remote sensed soil moisture assimilation could help to improve the results in BEPS model. And the assimilation using accurate remote sensed result as observation in different time series could help to improve the soil moisture results.关键词
土壤水分/遥感/优化/集合数据同化/NDVI/BEPS模型Key words
soil moisture/ remote sensing/ optimization/ ensemble data assimilation/ NDVI/ BEPS分类
信息技术与安全科学引用本文复制引用
王金梁,秦其明,刘明超,朱琳..基于NDVI优化选择的土壤水分数据同化[J].农业工程学报,2011,27(12):161-167,7.基金项目
国家自然科学基金(项目编号:41071221)、国家高技术研究发展计划(863计划)(项目编号:2008AA121806)、国家气象局公益性行业专项(项目编号:GYHY200806022)、中国博士后科学基金(20110490197) （项目编号:41071221）
