芦苇湿地植被NPP估算方法探索与应用

作为表征湿地生态系统健康的重要指标，湿地植被净初级生产力（NPP）的精准估算对于理解全球变化以及区域碳循环具有重要的支撑作用。基于Landsat 8 OLI遥感影像和大量实测数据，以光能利用率模型基本结构式为基础，构建和评价了芦苇湿地植被NPP估算的不同遥感驱动模型，并以东北3个典型芦苇湿地保护区为例进行了验证与应用。结果表明：以NPP = f（f（VI₁）） × f（VI₂） 结构与NDVI和MSAVI两个植被指数作为自变量的模型最优，模型精度为89.2%，明显高于NPP低空间分辨率产品和CASA模型的模拟结果。根据该模型估算的东北地区七星河、查干湖和双台河口芦苇湿地的NPP均值分别为3 001、3 050和3 621 gC·m^–2·a^–1。受水文条件和人类活动影响，各湿地样区间NPP具有典型的空间分布异质性。实验提出的框架模型可为小尺度上湿地生态系统健康评估或湿地生态系统恢复效果评价等指标获取提供方法借鉴。

Exploration and Application of NPP Estimation Model for Phragmites Australis Wetlands

Researches on Net Primary Productivity （NPP） of wetland vegetation are of great significance to the study of global change and carbon cycle. Taking three typical wetland samples in Northeast China as study area， based on Landsat 8 OLI and a large number of field data， this paper contrasted the combination forms of the basic structural formula of light utilization model. Results show that the model based on structure of NPP = f（f（VI₁））×f（VI₂） and two vegetation indices （NDVI and MSAVI） are optimal， with an accuracy of 89%， which was higher than those ofMODIS BIO-BGC and CASA model. In 2014， mean NPP of Phragmites australis for Qixinghe， Chaganhu and Shuangtaihekou wetland was 3 001， 3 050 and 3 621 gC·m^–2·yr^–1， respectively. NPP is obvious different spatially in three wetland samples， which is mainly influenced by hydrological conditions and human activities. For Phragmites australis wetland with small spatial scale， remote sensing method can be used to estimate NPP conveniently and efficiently. This study can provide a reference and guide for the study of wetland vegetation NPP regionally.