Paper
14 July 2003 Application of RS and GIS on analyzing forest crown canopy interception amount to annual precipitation in mountainous forest region in southeast China
Author Affiliations +
Proceedings Volume 4890, Ecosystems Dynamics, Ecosystem-Society Interactions, and Remote Sensing Applications for Semi-Arid and Arid Land; (2003) https://doi.org/10.1117/12.466900
Event: Third International Asia-Pacific Environmental Remote Sensing Remote Sensing of the Atmosphere, Ocean, Environment, and Space, 2002, Hangzhou, China
Abstract
The crown canopy interception amount to precipitation has nearly relationships to forest species, density, coverage degree and heights etc. Difficulties to analyze crown canopy interception amount to precipitation are attributed to the widespread forest areas with complicated plants species and sparse precipitation observation stations in East China. Resolving these problems are the keys of the study. The author took Guixi County that is located in Jiangxi Province in Southeast China with subtropical climate as an experimental area to study the variation features of forest crown canopy interception to annual precipitation involved trees species, altitudes and geographical locations applying RS and GIS technology, which can provide scientific basis to dynamic research on hydrology ecological capacities of forest.
© (2003) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Li Wei "Application of RS and GIS on analyzing forest crown canopy interception amount to annual precipitation in mountainous forest region in southeast China", Proc. SPIE 4890, Ecosystems Dynamics, Ecosystem-Society Interactions, and Remote Sensing Applications for Semi-Arid and Arid Land, (14 July 2003); https://doi.org/10.1117/12.466900
Lens.org Logo
CITATIONS
Cited by 1 scholarly publication.
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Remote sensing

Geographic information systems

Data modeling

RGB color model

Vegetation

Analytical research

Hydrology

Back to Top