Results 1 to 10 of about 125,360 (145)

Forest Canopy Height Mapping by Synergizing ICESat-2, Sentinel-1, Sentinel-2 and Topographic Information Based on Machine Learning Methods

Remote Sensing, 2022
Spaceborne LiDAR has been widely used to obtain forest canopy heights over large areas, but it is still a challenge to obtain spatio-continuous forest canopy heights with this technology.
Zhilong Xi, Huadong Xu, Yanqiu Xing, Weishu Gong, Guizhen Chen, Shuhang Yang   +5 more
doaj   +4 more sources

Environmental drivers of spatial variation in tropical forest canopy height: Insights from NASA’s GEDI spaceborne LiDAR [PDF]

Proceedings of the National Academy of Sciences of the United States of America
Significance In this study, measurements from NASA’s Global Ecosystem Dynamics Investigation spaceborne LiDAR mission are used to understanding global-scale patterns of tropical forest canopy height. The study shows that elevation, dry season length, and
Marcos Longo, Michael Keller, Paul Moorcroft   +2 more
exaly   +3 more sources

Comparison of GEDI LiDAR Data Capability for Forest Canopy Height Estimation over Broadleaf and Needleleaf Forests

Remote Sensing, 2023
The GEDI LiDAR system was specifically designed to detect vegetation structure and has proven to be a suitable tool for estimating forest biophysical parameters, especially canopy height, at a global scale.
Manizheh Rajab Pourrahmati, Nicolas Baghdadi, Ibrahim Fayad   +2 more
doaj   +4 more sources

Mapping the Forest Canopy Height in Northern China by Synergizing ICESat-2 with Sentinel-2 Using a Stacking Algorithm

Remote Sensing, 2021
The forest canopy height (FCH) plays a critical role in forest quality evaluation and resource management. The accurate and rapid estimation and mapping of the regional forest canopy height is crucial for understanding vegetation growth processes and the
Fugen Jiang, Feng Zhao, Kaisen Ma, Dongsheng Li, Hua Sun   +4 more
doaj   +4 more sources

High-resolution mapping of forest canopy height using machine learning by coupling ICESat-2 LiDAR with Sentinel-1, Sentinel-2 and Landsat-8 data

International Journal of Applied Earth Observations and Geoinformation, 2020
Forest canopy height is an important indicator of forest carbon storage, productivity, and biodiversity. The present study showed the first attempt to develop a machine-learning workflow to map the spatial pattern of the forest canopy height in a ...
Wang Li, Zheng Niu, Rong Shang, Yuchu Qin, Li Wang, Hanyue Chen   +5 more
doaj   +4 more sources

Estimation of Forest Canopy Height and Aboveground Biomass from Spaceborne LiDAR and Landsat Imageries in Maryland

Remote Sensing, 2018
Mapping the regional distribution of forest canopy height and aboveground biomass is worthwhile and necessary for estimating the carbon stocks on Earth and assessing the terrestrial carbon flux. In this study, we produced maps of forest canopy height and
Mengjia Wang, Rui Sun, Zhiqiang Xiao
doaj   +4 more sources

Exploring the Relationship between Forest Canopy Height and Canopy Density from Spaceborne LiDAR Observations

Remote Sensing, 2021
Forest structure is a useful proxy for carbon stocks, ecosystem function and species diversity, but it is not well characterised globally. However, Earth observing sensors, operating in various modes, can provide information on different components of ...
Heather Kay, Maurizio Santoro, Oliver Cartus, Pete Bunting, Richard Lucas   +4 more
doaj   +4 more sources

Improving GEDI Forest Canopy Height Products by Considering the Stand Age Factor Derived from Time-Series Remote Sensing Images: A Case Study in Fujian, China

Remote Sensing, 2023
Forest canopy height plays an important role in forest resource management and conservation. The accurate estimation of forest canopy height on a large scale is important for forest carbon stock, biodiversity, and the carbon cycle. With the technological
Xiaocheng Zhou, Youzhuang Hao, Liping Di, Xiaoqin Wang, Chongcheng Chen, Yunzhi Chen, Gábor Nagy, Tamas Jancso   +7 more
doaj   +2 more sources

Predicting the Forest Canopy Height from LiDAR and Multi-Sensor Data Using Machine Learning over India

Remote Sensing, 2022
Forest canopy height estimates, at a regional scale, help understand the forest carbon storage, ecosystem processes, the development of forest management and the restoration policies to mitigate global climate change, etc.
Sujit M. Ghosh, Mukunda D. Behera, Subham Kumar, Pulakesh Das, Ambadipudi J. Prakash, Prasad K. Bhaskaran, Parth S. Roy, Saroj K. Barik, Chockalingam Jeganathan, Prashant K. Srivastava, Soumit K. Behera   +10 more
doaj   +2 more sources

Estimates of Forest Canopy Height Using a Combination of ICESat-2/ATLAS Data and Stereo-Photogrammetry

Remote Sensing, 2020
Forest canopy height is an indispensable forest vertical structure parameter for understanding the carbon cycle and forest ecosystem services. A variety of studies based on spaceborne Lidar, such as ICESat, ICESat-2 and airborne Lidar, were conducted to ...
Xiaojuan Lin, Min Xu, Chunxiang Cao, Yongfeng Dang, Barjeece Bashir, Bo Xie, Zhibin Huang   +6 more
doaj   +2 more sources