林业科技开发2012，Vol.26Issue(3)：90-96,7.DOI:10.3969/j.issn.1000-8101.2012.03.022
基于CASA模型的瓦屋山林场植被净初级生产力估算
Estimation of net primary productivity by a satellite data-driven Carnegie-Ames-Stanford Approach model in Wawu Mountain forest farm
摘要
Abstract
Based on geographic information system and remote sensing technology, by use of the improved CASA (Camegie-Ames-Stanford Approach) model, Landsat TM remote sensing image, meteorological data and compartment, the net primary productivity (PNPP) of Wawu Mountain forest farm was estimated during 2008 to 2009. By use of the relationship of forest biomass and PNPP, the results of CASA model was verified in Wawu Mountain forest farm. The results indicated that CASA model can be used to estimate vegetation PNPP well, and can be applied in Wawu Mountain forest farm vegetation net productivity estimation. The differences of the PNPP among different vegetation types were marked . According to the high and low order, the estimatedPNpp of the vegetation were as follows: Populus devidiana, Quercus acuttisima, Castanea mol-lissima, Pinus massoniana, P. elliotlii, shrub, Cunninghamia lanceolata, Taxodium ascendens. The seasonal change of the PNPP in Wawu Mountain forest farm was marked. The PNPP was high in summer, and next high in spring and autumn, and lowest in winter. Mainly due to different season which has the different environmental factors, and the sun radiation is the most important factor among many factors.关键词
CASA模型/遥感/净初级生产力/森林生物量Key words
CASA model/remote sensing/net primary productivity/forest biomass引用本文复制引用
耿君,阮宏华,涂丽丽,吴国训..基于CASA模型的瓦屋山林场植被净初级生产力估算[J].林业科技开发,2012,26(3):90-96,7.基金项目
国家林业公益性行业科研专项项目(编号:200804006). （编号:200804006）
