TUP.P12: Data Fusion Applications: Vegetation |
Session Type: Poster
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Time: Tuesday, July 12, 17:20 - 19:00
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Location: Third Floor, South Hall, Poster Area
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Session Chair: Feng Gao, United States Department of Agriculture
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TUP.P12.59: ESTIMATING BOREAL FOREST CANOPY HEIGHT AND ABOVE GROUND BIOMASS USING MULTI-MODAL REMOTE SENSING; A DATABASE DRIVEN APPROACH
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Michael Benson; University of Michigan |
Leland Pierce; University of Michigan |
Kamal Sarabandi; University of Michigan |
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TUP.P12.60: ESTIMATING THE THREE DIMENSIONAL STRUCTURE OF HETEROGENEOUS FORESTS USING MULTI-MODAL REMOTE SENSING AND SENSOR EXTRAPOLATION TECHNIQUES
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Michael Benson; University of Michigan |
Leland Pierce; University of Michigan |
Kamal Sarabandi; University of Michigan |
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TUP.P12.61: RESEARCH ON YIELDS ESTIMATION AND YIELDS INCREASING POTENTIAL BY IRRIGATION OF SPRING MAIZE IN NORTHEAST CHINA
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Shanning Bao; State Key Laboratory of Remote Sensing Science |
Chunxiang Cao; State Key Laboratory of Remote Sensing Science |
Jianxi Huang; China Agricultural University |
Xiliang Ni; State Key Laboratory of Remote Sensing Science |
Min Xu; State Key Laboratory of Remote Sensing Science |
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TUP.P12.62: FUSION OF SCIAMACHY AND GOME-2 SATELLITE SUN-INDUCED FLUORESCENCE DATA
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Lian Song; Nanjing University |
Yongguang Zhang; Nanjing University |
Xin Qian; Nanjing University |
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TUP.P12.63: QUANTIFYING UNCERTAINTIES IN EVAPOTRANSPIRATION ASSIMILATION USING GENERALIZED GAUSSIAN DISTRIBUTION
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Shaohui Chen; Key Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences |
Shen Zhao; Key Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences |
Hongbo Su; Key Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences |
Jing Tian; Key Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences |
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