Aggregates
; Infrared devices
; Mixtures
; Radiometers
; Reflection
; Leaf Area Index
; MODIS collection 6
; Sub pixels
; Uncertainty
; Water effects
; Pixels
; accuracy assessment
; land cover
; Landsat
; leaf area index
; MODIS
; pixel
; solar radiation
; uncertainty analysis
State Key Laboratory of Remote Sensing Science, Jointly Sponsored by Aerospace Information Research Institute, Chinese Academy of Sciences and Beijing Normal University, Beijing, 100101, China; Department of Earth and Environment, Boston University, Boston, MA 02215, United States; Macro Agriculture Research Institute, College of Resource and Environment, Huazhong Agricultural University, Wuhan, 430070, China; Department of Global Ecology, Carnegie Institution for Science, Stanford, CA 94305, United States; Faculty of Geosciences and Environmental Engineering, Southwest Jiaotong University, Chengdu, 610031, China; School of Land Science and Techniques, China University of Geosciences, Beijing, 100083, China; School of Environmental and Resources Science, Zhejiang A & F University, Lin'an, 311300, China
Recommended Citation:
Xu B.,Li J.,Park T.,et al. Improving leaf area index retrieval over heterogeneous surface mixed with water[J]. Remote Sensing of Environment,2020-01-01,240