A Novel Method for Forest Leaf Area Index Inversion Using Lidar Data
نویسندگان
چکیده
منابع مشابه
Inversion of Forest Leaf Area Index Based on Lidar Data
Leaf area index (LAI) is an important parameter of vegetation ecosystems, which can reflect the growth status of vegetation, and its inversion result has important significance on forestry system. The inversion values of forest LAI exists a certain deviation using traditional method. The airborne LiDAR technology adopts a new type of aerial earth observation method and makes it possible to esti...
متن کاملUsage of Lidar Data for Leaf Area Index Estimation
Leaf area index (LAI) can be measured either directly, using destructive methods, or indirectly using optical methods that are based on the tight relationship between LAI and canopy light transmittance. Third, innovative approach for LAI measuring is usage of remote sensing data, especially airborne laser scanning (ALS) data shows itself as a advisable source for purposes of LAI modelling in la...
متن کاملMapping urban forest leaf area index with airborne lidar using penetration metrics and allometry
a r t i c l e i n f o Keywords: Airborne lidar Leaf area index Urban ecosystem analysis Hemispherical photography Allometry Vegetation structure In urban areas, leaf area index (LAI) is a key ecosystem structural attribute with implications for energy and water balance, gas exchange, and anthropogenic energy use. In this study, we estimated LAI spatially using airborne lidar in downtown Santa B...
متن کاملLeaf area index estimates obtained for mixed forest using hemispherical photography and HyMap data
The Leaf Area Index (LAI) is an important measure in many ecological applications because vegetation-atmosphere processes of the canopy, such as photosynthesis are controlled by the foliage and play an essential role in the carbon cycle. Therefore accurate determination of LAI is of great interest. Forest LAI is difficult to estimate due to the complex structure of the canopy and its high varia...
متن کاملJoint leaf chlorophyll content and leaf area index retrieval from Landsat data using a regularized model inversion system (REGFLEC)
a King Abdullah University of Science and Technology, Water Desalination and Reuse Center, Kingdom of Saudi Arabia b European Commission, Joint Research Centre, Institute for Environment and Sustainability, Ispra, Italy c USDA-ARS Hydrology and Remote Sensing Laboratory, Beltsville, MD, USA d Center for Advanced Land Management Information Technology (CALMIT), School of Natural Resources, Unive...
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ژورنال
عنوان ژورنال: The Open Cybernetics & Systemics Journal
سال: 2015
ISSN: 1874-110X
DOI: 10.2174/1874110x01509010565