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Evaluation of topographic effects on multiscale leaf area index estimation using remotely sensed observations from multiple sensors
Jin, Huaan1; Li, Ainong1; Xu, Webdng1,2; Xiao, Zhiqiang3; Jiang, Jingyi4; Xue, Huazhu2
Corresponding AuthorLi, Ainong(ainongli@imde.ac.cn)
2019-08-01
Source PublicationISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING
ISSN0924-2716
Volume154Pages:176-188
AbstractLocal topography significantly affects remotely sensed reflectance data and subsequently impacts leaf area index (LAI) retrieval over mountainous areas. Therefore, mountain vegetation LAI mapping from satellite observations at multiple scale levels is often obstructed by topographic distortion. To analyze the effects of topography on multiresolution LAI retrievals, consistent LAI estimations were first generated across six spatial scales (i.e., 960 m, 480 m, 240 m, 120 m, 60 m and 30 m) from MODIS and Landsat OLI reflectance data using the ensemble multiscale filter (EnMsF) approach over rugged surfaces. Subsequently, the topographic influence on LAI was evaluated based on spatial patterns and retrieval accuracies at multiple scale levels by comparing the EnMsF-based multiscale LAI results obtained before and after terrain correction of a Landsat image. The results demonstrated that the multiresolution LAI values retrieved from topographically corrected surface reflectance data outperformed those without topographic correction, regardless of various slopes or aspects at the 30 m scale or the differences in spatial resolutions. The accuracies were determined for the retrieved LAI values before (coefficient of determination (R-2) = 0.32 and root mean square error (RMSE) = 1.03) and after (R-2 = 0.60 and RMSE = 0.82) topographic correction when compared to the field measurements over slopes facing toward the sun at the 30 m resolution. The R-2 and RMSE values were 0.57 and 0.54, respectively, for the LAI estimations with terrain corrections in the shady aspects. Moreover, the topographic effect on the LAI estimations depended on our spatial scales. The finer the spatial resolution is, the more significant the topographic effects on the multiscale LAI retrieval are, and vice versa. Thus, the results of this study open an encouraging path to deepen the understanding of terrain effects on multiscale LAI estimations, and further improve the LAI retrieval algorithm across different spatial scales over mountainous areas.
KeywordLeaf area index MODIS Landsat Multiscale Mountainous areas
DOI10.1016/j.isprsjprs.2019.06.008
Indexed BySCI
WOS KeywordESSENTIAL CLIMATE VARIABLES ; ENSEMBLE FILTERING SYSTEM ; LAI PRODUCTS ; GEOV1 LAI ; MODIS ; MODEL ; VALIDATION ; VEGETATION ; ALGORITHM ; IMPLEMENTATION
Language英语
Funding ProjectNational Natural Science Foundation of China[41671376] ; National Natural Science Foundation of China[41631180] ; National Natural Science Foundation of China[41301385] ; National Key Research and Development Program of China[2016YFA0600103] ; Sichuan Science and Technology Program[2019YJ0007]
WOS Research AreaPhysical Geography ; Geology ; Remote Sensing ; Imaging Science & Photographic Technology
WOS SubjectGeography, Physical ; Geosciences, Multidisciplinary ; Remote Sensing ; Imaging Science & Photographic Technology
WOS IDWOS:000480671500014
Funding OrganizationNational Natural Science Foundation of China ; National Key Research and Development Program of China ; Sichuan Science and Technology Program
PublisherELSEVIER
Citation statistics
Document Type期刊论文
Identifierhttp://ir.imde.ac.cn/handle/131551/26971
Collection山地灾害与地表过程重点实验室
数字山地与遥感应用中心
Corresponding AuthorLi, Ainong
Affiliation1.Chinese Acad Sci, Inst Mt Hazards & Environm, Res Ctr Digital Mt & Remote Sensing Applicat, Chengdu 610041, Sichuan, Peoples R China
2.Henan Polytech Univ, Sch Surveying & Land Informat Engn, Jiaozuo 454150, Henan, Peoples R China
3.Beijing Normal Univ, Fac Geog Sci, Beijing 100875, Peoples R China
4.UAPV, INRA, EMMAH, F-84000 Avignon, France
First Author Affilication中国科学院水利部成都山地灾害与环境研究所
Corresponding Author Affilication中国科学院水利部成都山地灾害与环境研究所
Recommended Citation
GB/T 7714
Jin, Huaan,Li, Ainong,Xu, Webdng,et al. Evaluation of topographic effects on multiscale leaf area index estimation using remotely sensed observations from multiple sensors[J]. ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING,2019,154:176-188.
APA Jin, Huaan,Li, Ainong,Xu, Webdng,Xiao, Zhiqiang,Jiang, Jingyi,&Xue, Huazhu.(2019).Evaluation of topographic effects on multiscale leaf area index estimation using remotely sensed observations from multiple sensors.ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING,154,176-188.
MLA Jin, Huaan,et al."Evaluation of topographic effects on multiscale leaf area index estimation using remotely sensed observations from multiple sensors".ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING 154(2019):176-188.
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