IMHE OpenIR  > 数字山地与遥感应用中心
Derivation of temporally continuous LAI reference maps through combining the LAINet observation system with CACAO
Yin, Gaofei1,2; Li, Ainong1; Jin, Huaan1; Zhao, Wei1; Bian, Jinhu1,3; Qu, Yonghua4,5,6; Zeng, Yelu2; Xu, Baodong2,3
Corresponding AuthorAinong Li
2017
Source PublicationAGRICULTURAL AND FOREST METEOROLOGY
ISSN0168-1923
EISSN1873-2240
Volume233Pages:209-221
SubtypeArticle
Abstract

Leaf area index (LAI) products are now routinely generated from remote sensing and widely used in most land surface process models. Assessing the uncertainties associated with these LAI products is essential for their proper application. In validation activities, LAI reference maps serve as the bridge to upscale the field measurements to coarse resolution. Currently, the temporally continuous validation is attracting increasing attention. Therefore, there is an urgent requirement for the temporally continuous LAI reference maps. However, two main problems hinder the generation of temporally continuous LAI reference maps: 1) How to obtain temporally continuous field measurements, effectively and inexpensively? 2) How to obtain temporally continuous and fine spatial resolution satellite images which are synchronous with the field measurements? This paper proposed a method to address the above two problems based on the combination of the wireless sensor network technology and a data blending approach. Firstly, the temporally continuous effective LAI was obtained through the analysis of multi-angle gap fraction measured by LAINet observation system (developed with wireless sensor network technology), and the temporally continuous NDVI was reconstructed through CACAO (Consistent Adjustment of the Climatology to Actual Observations, a data blending approach). Then, a transfer function relating reconstructed NDVI to field measured LAI was calibrated through exponential function fitting. Finally, the temporally continuous LAI reference maps were generated by applying the calibrated transfer function to the reconstructed NDVI. Performances of the proposed method were evaluated over a crop site. Results show that the reconstructed LAI reference maps agree well with the original LAI reference maps derived from the Landsat-8 OLI NDVI (R-2 = 0.90, RMSE = 0.27 at 30 m resolution, R-2 = 0.97, RMSE = 0.09 at 1 km resolution). The derived temporally continuous LAI reference maps were then used as benchmark to validate the MOD15A2 LAI product. Generally, the MOD15A2 LAI has a relatively high accuracy (R-2=0.53, RMSE= 0.31), and captures the overall vegetation phenology well. But its value shows an obvious underestimation with a bias of -0.30. The results of this study contribute to the assessment of temporal dynamics of uncertainty in LAI products, which will benefit the long-term vegetation monitoring and data assimilation. (C) 2016 Elsevier B.V. All rights reserved.

KeywordLeaf Area Index (Lai) Validation Temporal Continuity Lainet Observation System Consistent Adjustment Of The Climatology To Actual Observations (Cacao)
WOS HeadingsScience & Technology ; Life Sciences & Biomedicine ; Physical Sciences
DOI10.1016/j.agrformet.2016.11.267
WOS Subject ExtendedAgriculture ; Forestry ; Meteorology & Atmospheric Sciences
Indexed BySCI
WOS KeywordLEAF-AREA INDEX ; WIRELESS SENSOR NETWORK ; LANDSAT SURFACE REFLECTANCE ; ESSENTIAL CLIMATE VARIABLES ; IN-SITU MEASUREMENTS ; HEIHE RIVER-BASIN ; TIME-SERIES ; VEGETATION INDEXES ; MODIS DATA ; SEASONAL-VARIATION
Language英语
Quartile1区
TOP
WOS SubjectAgronomy ; Forestry ; Meteorology & Atmospheric Sciences
WOS IDWOS:000393259400019
Funding OrganizationNational Natural Science Foundation of China(41631180 ; National Key Research and Development Program of China(2016YFA0600103) ; Open Fund of State Key Laboratory of Remote Sensing Science(OFSLRSS201613) ; China Postdoctoral Science Foundation(2016M592712) ; CAS "Light of West China" Program ; Youth Talent Team Program of Institute of Mountain Hazards and Environment, CAS(SDSQB-2015-02) ; 41601403 ; 41531174 ; 41571373 ; 41271433 ; 41301385 ; 41271348)
Citation statistics
Cited Times:23[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.imde.ac.cn/handle/131551/18484
Collection数字山地与遥感应用中心
Affiliation1.Chinese Acad Sci, Inst Mt Hazards & Environm, Res Ctr Digital Mt & Remote Sensing Applicat, Chengdu 610041, Peoples R China
2.Chinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote Sensing Sci, Beijing 100101, Peoples R China
3.Univ Chinese Acad Sci, Coll Resources & Environm, Beijing 100049, Peoples R China
4.Beijing Normal Univ, State Key Lab Remote Sensing Sci, Res Ctr Remote Sensing, Beijing 100875, Peoples R China
5.Beijing Normal Univ, GIS, Beijing 100875, Peoples R China
6.Beijing Normal Univ, Sch Geog, Beijing 100875, Peoples R China
First 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
Yin, Gaofei,Li, Ainong,Jin, Huaan,et al. Derivation of temporally continuous LAI reference maps through combining the LAINet observation system with CACAO[J]. AGRICULTURAL AND FOREST METEOROLOGY,2017,233:209-221.
APA Yin, Gaofei.,Li, Ainong.,Jin, Huaan.,Zhao, Wei.,Bian, Jinhu.,...&Xu, Baodong.(2017).Derivation of temporally continuous LAI reference maps through combining the LAINet observation system with CACAO.AGRICULTURAL AND FOREST METEOROLOGY,233,209-221.
MLA Yin, Gaofei,et al."Derivation of temporally continuous LAI reference maps through combining the LAINet observation system with CACAO".AGRICULTURAL AND FOREST METEOROLOGY 233(2017):209-221.
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