基于Landsat TM和ENVISAT ASAR数据的鄱阳湖湿地植被生物量的反演

作为湿地生态系统的重要组成部分,湿地生物量是衡量生态系统健康状况的关键指标。由于光学遥感对植被垂直分布探测的局限,使得植被指数反映生物量变化的灵敏度下降。利用C波段SAR反演生物量时,对于低中等生物量,含水量高的湿地地表的后向散射对总雷达后向散射的影响会在雷达图像上出现类似光学遥感中"异物同谱"的现象。本文用光学遥感中NDVI、RVI和DVI三种植被指数对生物量变化的敏感性,利用改进的MIM-ICS模型,对湿地植被各散射分量进行模拟分析,建立符合湿地植被类型的各散射分量模拟数据库,以LandsatTM和Envisat ASAR交替极化数据为基础,选择植被指数DVI=0.45为阈值,将湿地植被分割为低叶片密度植被区和高叶片密度植被区,分别应用统计回归模型和半经验微波散射模型,对两个区域植被生物量进行反演。最后,得到整个鄱阳湖湿地生物量为2.1×10⁹kg。研究表明,对于生物量动态范围较大的地区,采用光学和雷达遥感相结合可以有效地提高湿地植被生物量反演的精度,克服光学遥感探测植被垂直分布能力有限和雷达遥感受背景影响大的不足。

Estimation of Wetland Vegetation Biomass in the Poyang Lake Area Using Landsat TM and ENVISAT ASAR Data

Wetland vegetation is one of the important components of wetland ecosystems,and its biomass is the key indicator of the health status of the wetland ecosystems.The sensitivity of near-infrared band to biomass decreases as the vegetation density increases.In contrast,there is no significant change in red spectral reflectivity,so the vegetation index cannot reflect changes in high-density vegetation area.When using C-band SAR data to estimate the biomass in areas with low-and middle-biomass,the radar backscattering from the wetland soil with a great deal of water behind the canopy results in the phenomenon that different biomass have the similar total radar scattering coefficient in the radar images.In this paper,we have done research on the sensitivity to the biomass for three kinds of optical remote sensing vegetation indices NDVI,RVI and DVI,the use of improved MIMICS model to simulate different scattering components of wetland vegetation,and on seting up the simulation database of all components of wetland vegetation backscattering.Then we offer a method with Landsat TM and ENVISAT ASAR alternating polarization data,selecting the vegetation index DVI = 0.45 as the threshold to divide the wetland of Poyang Lake into two parts： the vegetation with low leaf density and high leaf density.For DVI 0.45 the areas with low leaf density,there is high linear correlation between vegetation index and biomass,so we apply the statistical analysis to build a linear regression model using the samples.For DVI=0.45 the areas with high leaf density,due to the decline of the effects from the soil backscattering behind vegetation canopy,it can be used in C-band approximate microwave scattering models in the canopy to estimate these vegetation biomass such as Carex,Reed.Finally,the entire wetland biomass of Poyang Lake is approximately 2.1？？09kg.The accuracy of the result is higher than the previous result that only uses optical remote sensing data in high leaf density.Hence,combining the merits of optical and radar remote sensing can effectively enhance inversion accuracy of the entire wetland vegetation biomass.