深入探讨湿地植被净初级生产力 (NPP)估算方法，定量评估湿地植被NPP空间格局，对于理解区域乃至全球的碳收支具有重要意义。基于光能利用率的估算模型是目前植被NPP估算的主要方法，但是针对湿地植被的相关研究还较少。本项目选择中国东北地区典型草本湿地为研究对象，通过野外观测、理论分析和计算机模拟等方法，研究不同植被指数与冠层叶绿素含量间的关系，比较分析不同波段组合的植被指数与光能利用率间的相关程度；选择估算草本湿地植被光能利用率的最优植被指数，建立基于植被指数的湿地植被NPP估算模型；基于高空间分辨率遥感影像和线性混合像元分解模型，实现草本湿地的高精度提取；进而完成典型样区草本湿地植被NPP估算；以湿地样带分析为途径，研究NPP格局和各环境要素及植被类型对草本湿地植被光能利用率和NPP的影响。本项目的实施有助于提高湿地植被定量遥感研究水平，并将为区域湿地固碳研究及湿地保护与管理提供科学依据。

There are very important significance for understanding regional, and even global, carbon budget and influences from global change that investigating the method of estimating marsh vegetation NPP (Net Primary Productivity) and evaluating quantitatively the spatial pattern of NPP. Estimation models based on light use efficiency are commonly used method for estimating vegetation NPP. The researches in relation to the method of estimating marsh NPP and pattern of NPP are limited. This project will select typical marshes in Northeast China to study the relations between different marsh vegetation indices and canopy chlorophyll content, compare and analyze the correlations between vegetation indices and marsh vegetation LUE (Light Use Efficiency), further to accomplish selecting the best vegetation index for simulation marsh vegetation LUE. Finally, we will develop a model based on multi-spectral vegetation index for marsh NPP estimation. And also, present study intend to accurately map marshes based on high-spatial resolution remote sensing images and linear spectral mixture analysis model, estimate NPP of typical marshes in Northeast China using the developed model, and discuss the spatial pattern of LUE and NPP and effects from temperature, solar radiation, and terrain and so on, through the transect analysis of typical marshes at various natural and environmental backgrounds. Implementation of this study project will be of benefit to advance the level of quantitative remote sensing and can provide scientific basis for regional wetland carbon sequestration research and wetland's conservation and management.