Geostatistical modeling using LiDAR-derived prior knowledge with SPOT-6 data to estimate temperate forest canopy cover and above-ground biomass via stratified random sampling
The State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing, China; University of Chinese Academy of Sciences, Beijing, China; Department of Remote Sensing and Photogrammetry, Finnish Geodetic Institute, Masala, Finland; Research Institute of Forest Resource Information Techniques, Chinese Academy of Forestry, Wanshoushanhou, Beijing, China; Laboratory of Digital Earth Sciences, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing, China; Olympic Science and Technology Park of CAS, P.O. Box 9718, No. 20, Datun Road, Beijing, China
Recommended Citation:
Li W,, Niu Z,, Liang X,et al. Geostatistical modeling using LiDAR-derived prior knowledge with SPOT-6 data to estimate temperate forest canopy cover and above-ground biomass via stratified random sampling[J]. International Journal of Applied Earth Observation and Geoinformation,2015-01-01,41