应用LandsatETM数据估算鄱阳湖湿生植被生物量

An Estimation of Wetland Vegetation Biomass in the Poyang Lake Using Landsat ETM Data

利用 2 0 0 0年的 Landsat ETM数据 ,首次采用全数字化遥感定量方法对鄱阳湖湿生植被的生物量及其分布进行调查研究。首先 ,用该时相卫星数据制作假彩色合成图象 ,以该图象为主要依据之一 ,设计了野外生物量采样路线与样点 ,并在地形图和 GPS的帮助下 ,实时地开展了湿生植被生物量的野外实地采样。然后 ,在室内将采样点坐标和 Landsat ETM图象坐标进行几何纠正和匹配 ,将坐标统一转换为等积圆锥投影。再逐个坐标点比较采样数据与 ETM4波段数据和 NDVI、DVI和第一主成分数据之间的线性相关关系。统计分析的结果表明 ,采样数据与 ETM4波段数据有最好的正相关 ,其相关系数达到 0 .86。采样数据与 DVI、NDVI数据的相关系数分别为 0 .83、 0 .80。采样数据与第一主成分数据之间的相关关系不显著 ,仅 0 .40。基于这一比较 ,建立了采样数据与 ETM 4波段数据的线性相关模型。据此 ,用 ETM 4波段计算出鄱阳湖 4月份湿生植被的总生物量为 3.8× 1 0 9kg。

The Poyang Lake is the largest freshwater lake in China with an area of about 3 000 km 2 This paper conducted a digital and rapid investigation of the lake's wetland plant biomass using Landsat ETM data acquired on April 16,2000 First, using the false color composite derived from the ETM data as one of the main references, the authors planned a reasonable field sampling route for the biomass, and then carried out it during April 18 28,2000 Based on geometric correction of both the sampling data and the ETM data to an area equal projection of Albers, the linear relationships among the field biomass and some transformed data from the ETM data and the band 4 were calculated statistically The results show that the sampling data has the best positive correlation to the band 4 data with a coefficient of 0 86, followed by the DVI and NDVI data with coefficients of 0 83 and 0 80 respectively Therefore, a linear regression model established by using the field data and band 4 data was used to estimate the total biomass of the whole Poyang Lake, and to make the map of the biomass distribution It is shown that the remote sensing technology has many advantages over the traditionally used method engaged in the biomass investigation in a lake, especially a lake with large surface area