基于森林清查和遥感的城市森林净初级生产力估算

Estimation urban forests NPP based on forest inventory data and remote sensing

城市森林作为陆地生态系统的组成成分之一,研究其在全球碳循环中的地位和作用有很重要的意义。文章以上海城市森林为研究对象,开展基于基于森林清查数据和遥感技术的城市森林净初级生产力(NPP)估算研究。首先,根据选取上海市典型的森林植被类型,设置森林植被样方,测量反映植被生物学特性的特征参数,包括林龄、胸径、树高和叶面积指数(LAI)等,采用能反映林龄和蓄积量共同影响的生产力回归模型估算了样方NPP,建立了基于LAI的样方NPP回归模型;其次,利用一景相近时相的SPOT5影像,经进行几何纠正和辐射定标后,计算出能较好地反映植被特征和消除土壤背景影响的修正土壤调节植被指数(MSAVI),建立了基于MSAVI的区域森林LAI遥感估测模型;最后,根据建立的样方NPP回归模型以及区域LAI遥感估测模型,进行尺度化转换,估算出区域尺度上的上海城市森林净初级生产力。通过比较与前人运用传统方法研究估算的NPP,精度可达到89%,且本模型简单可行。因此本研究可为快速定量评估城市森林碳储量提供依据。

Urban forest is one of a main component of terrestrial ecosystems, it play an important role in terrestrial ecosystem carbon cycle. In this paper, based on foest inventory data and remote sensing technology, urban forest net primary productivity （NPP） was studied. Firstly, according to the status of the Shanghai Urban Forests and selected Shanghai typical forest vegetation types, the biological characteristics parameters of the vegetation was surveyed, including forest age, diameter at the breast height, height, and leaf area index （LAI）, etc.. Based on field forest inventory data, NPP of forests in the sample was estimated using the relationship between forest NPP and forest age and forest biomass. Then the regression model between NPP and LAI was set up; Secondly, using SPOT5 images, after geometric correction and radiometric calibration, modified asjust soil vegetation index （MSAVI） was calculated, which can reflect the elimination of soil and vegetation characteristics of the background factors. Then estimation LAI model was set up with SPOT5 MSAVI; finally, according the NPP regression model and LAI estimation model, NPP model was set up at regional scale in Shanghai. It provides a good method and theoreticly base for evaluating urban forest structure and ruction.