Global S&T Development Trend Analysis Platform of Resources and Environment
DOI | 10.1029/2019WR025055 |
Ecohydrologic Error Models for Improved Bayesian Inference in Remotely Sensed Catchments | |
Tang, Yating1; Marshall, Lucy1; Sharma, Ashish1; Ajami, Hoori2; Nott, David J.3 | |
2019-06-01 | |
发表期刊 | WATER RESOURCES RESEARCH |
ISSN | 0043-1397 |
EISSN | 1944-7973 |
出版年 | 2019 |
卷号 | 55期号:6页码:4533-4549 |
文章类型 | Article |
语种 | 英语 |
国家 | Australia; USA; Singapore |
英文摘要 | Leaf area index (LAI) is an important vegetation indicator widely used for simulating vegetation dynamics and quantifying biomass production. Spatial and temporal variability of LAI are often characterized using satellite remote sensing products. However, these types of satellite products often have relatively low quality when compared to in situ measurements. This work presents an approach for characterizing Moderate Resolution Imaging Spectroradiometer LAI observation errors in a Bayesian ecohydrological modeling framework using Moderate Resolution Imaging Spectroradiometer quality flags data. We introduce a novel ecohydrologic error model, which partitions observation and model residual error according to the estimated retrieval uncertainty of LAI and the quality flags for each pixel. We examine our approach in two study catchments in Australia with varying degrees of good and poor quality satellite LAI data. Results show improved LAI predictions and less model residual error for both catchments when accounting for satellite observational uncertainties in a Bayesian framework. |
英文关键词 | ecohydrological modeling Bayesian inference observational error uncertainty analysis |
领域 | 资源环境 |
收录类别 | SCI-E |
WOS记录号 | WOS:000477616900002 |
WOS关键词 | LEAF-AREA INDEX ; TIME-SERIES ; GLOBAL PRODUCTS ; PART 1 ; MODIS ; VEGETATION ; LAI ; ALGORITHM ; RADIATION ; FRACTION |
WOS类目 | Environmental Sciences ; Limnology ; Water Resources |
WOS研究方向 | Environmental Sciences & Ecology ; Marine & Freshwater Biology ; Water Resources |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.173/C666/handle/2XK7JSWQ/183956 |
专题 | 资源环境科学 |
作者单位 | 1.Univ New South Wales, Sch Civil & Environm Engn, UNSW Water Res Ctr, Kensington, NSW, Australia; 2.Univ Calif Riverside, Dept Environm Sci, Riverside, CA 92521 USA; 3.Natl Univ Singapore, Dept Stat & Appl Probabil, Singapore, Singapore |
推荐引用方式 GB/T 7714 | Tang, Yating,Marshall, Lucy,Sharma, Ashish,et al. Ecohydrologic Error Models for Improved Bayesian Inference in Remotely Sensed Catchments[J]. WATER RESOURCES RESEARCH,2019,55(6):4533-4549. |
APA | Tang, Yating,Marshall, Lucy,Sharma, Ashish,Ajami, Hoori,&Nott, David J..(2019).Ecohydrologic Error Models for Improved Bayesian Inference in Remotely Sensed Catchments.WATER RESOURCES RESEARCH,55(6),4533-4549. |
MLA | Tang, Yating,et al."Ecohydrologic Error Models for Improved Bayesian Inference in Remotely Sensed Catchments".WATER RESOURCES RESEARCH 55.6(2019):4533-4549. |
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