Identifying green leaf and leaf phenology of individual trees and forests by time series satellite imagery and the chlorophyll and green leaf indicator (CGLI)
Identifying green leaf and leaf phenology of individual trees and forests by time series satellite imagery and the chlorophyll and green leaf indicator (CGLI)
Baihong Pan1, Xiangming Xiao1, Li Pan2, Andrew D Richardson3, Yujie Liu4, Yuan Yao5, Cheng Meng6, Yanhua Xie7, Chenchen Zhang1 and Yuanwei Qin8, (1)School of Biological Sciences, Center for Earth Observation and Modeling, University of Oklahoma, Norman, United States, (2)University of Oklahoma, School of Biological Sciences, Norman, United States, (3)Northern Arizona University, School of Informatics, Computing and Cyber Systems & Center for Ecosystem Science and Society; Center for Ecosystem Science and Society, Northern Arizona University, Flagstaff, AZ, USA, Flagstaff, United States, (4)Northern Arizona University, School of Informatics, Computing and Cyber Systems & Center for Ecosystem Science and Society, Flagstaff, United States, (5)Department of Microbiology and Plant Biology, Center for Earth Observation and Modeling, University of Oklahoma, Norman, United States, (6)University of Oklahoma Norman Campus, School of Biological Sciences, Norman, United States, (7)University of Oklahoma, Department of Geography and Environmental Sustainability, Norman, United States, (8)Hohai University, College of Geography and Remote Sensing, Jiangsu Key Laboratory of Soil and Water Processes in Watershed, Nanjing, China