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Deriving Maximum Light Use Efficiency From Crop Growth Model and Satellite Data to Improve Crop Biomass Estimation
Dong, Taifeng1; Liu, Jiangui1; Qian, Budong1; Jing, Qi1; Croft, Holly2; Chen, Jingming2; Wang, Jinfei3; Huffman, Ted1; Shang, Jiali1; Chen, Pengfei1,4
2017
Source PublicationIEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING
ISSN1939-1404
Volume10Issue:1Pages:104-117
Corresponding AuthorHuffman, Ted(Ted.Huffman@agr.gc.ca) ; Shang, Jiali(Jiali.Shang@agr.gc.ca)
AbstractMaximum light use efficiency (LUEmax) is an important parameter in biomass estimation models (e.g., the Production Efficiency Models (PEM)) based on remote sensing data; however, it is usually treated as a constant for a specific plant species, leading to large errors in vegetation productivity estimation. This study evaluates the feasibility of deriving spatially variable crop LUEmax from satellite remote sensing data. LUEmax at the plot level was retrieved first by assimilating field measured green leaf area index and biomass into a crop model (the Simple Algorithm for Yield estimate model), and was then correlated with a few Landsat-8 vegetation indices (VIs) to develop regression models. LUEmax was then mapped using the best regression model from a VI. The influence factors on LUEmax variability were also assessed. Contrary to a fixed LUEmax, our results suggest that LUEmax is affected by environmental stresses, such as leaf nitrogen deficiency. The strong correlation between the plot-level LUEmax and VIs, particularly the two-band enhanced vegetation index for winter wheat (Triticum aestivum) and the green chlorophyll index for maize (Zea mays) at the milk stage, provided a potential to derive LUEmax from remote sensing observations. To evaluate the quality of LUEmax derived from remote sensing data, biomass of winter wheat and maize was compared with that estimated using a PEM model with a constant LUEmax and the derived variable LUEmax. Significant improvements in biomass estimation accuracy were achieved (by about 15.0% for the normalized root-mean-square error) using the derived variable LUEmax. This study offers a new way to derive LUEmax for a specific PEM and to improve the accuracy of biomass estimation using remote sensing.
KeywordCrop biomass Landsat-8 operational land imager (OLI) light use efficiency (LUE) maize winter wheat
DOI10.1109/JSTARS.2016.2605303
WOS KeywordGROSS PRIMARY PRODUCTION ; LEAF-AREA INDEX ; PHOTOSYNTHETICALLY ACTIVE RADIATION ; CORN-YIELD ESTIMATION ; REMOTE-SENSING DATA ; CERES-MAIZE MODEL ; VEGETATION INDEXES ; ECOSYSTEM PRODUCTION ; PRIMARY PRODUCTIVITY ; SOYBEAN CROPLANDS
Indexed BySCI
Language英语
Funding ProjectAgriculture and Agri-Food Canada ; Canadian Space Agency
Funding OrganizationAgriculture and Agri-Food Canada ; Canadian Space Agency
WOS Research AreaEngineering ; Physical Geography ; Remote Sensing ; Imaging Science & Photographic Technology
WOS SubjectEngineering, Electrical & Electronic ; Geography, Physical ; Remote Sensing ; Imaging Science & Photographic Technology
WOS IDWOS:000391719900010
PublisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Citation statistics
Cited Times:9[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.igsnrr.ac.cn/handle/311030/65087
Collection中国科学院地理科学与资源研究所
Corresponding AuthorHuffman, Ted; Shang, Jiali
Affiliation1.Agr & Agri Food Canada, Ottawa Res & Dev Ctr, Ottawa, ON K1A 0C6, Canada
2.Univ Toronto, Dept Geog, Toronto, ON M5S 3G3, Canada
3.Univ Western Ontario, Dept Geog, London, ON N6A 5C2, Canada
4.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China
Recommended Citation
GB/T 7714
Dong, Taifeng,Liu, Jiangui,Qian, Budong,et al. Deriving Maximum Light Use Efficiency From Crop Growth Model and Satellite Data to Improve Crop Biomass Estimation[J]. IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING,2017,10(1):104-117.
APA Dong, Taifeng.,Liu, Jiangui.,Qian, Budong.,Jing, Qi.,Croft, Holly.,...&Chen, Pengfei.(2017).Deriving Maximum Light Use Efficiency From Crop Growth Model and Satellite Data to Improve Crop Biomass Estimation.IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING,10(1),104-117.
MLA Dong, Taifeng,et al."Deriving Maximum Light Use Efficiency From Crop Growth Model and Satellite Data to Improve Crop Biomass Estimation".IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING 10.1(2017):104-117.
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