基于MODIS与TM遥感影像的植被盖度提取算法比较

摘要

The study proposed how to extract the vegetation coverage precisely on a large scale and in short time using the MODIS Normal Different Vegetation Index (NDVI) and the multi-spectral image Landsat TM without ground measurements: Get the vegetation coverage making use of the two method of empirical model and dimidiate pixel model. Then the results were compared among different models on basis of the TM coverage with higher precision. The conclusion is that in the study area where vegetation coverage is distributing equably,regression models are better than dimidiate pixel model in extracting the vegetation coverage in larger sample scale,especially to the nonlinear model,besides,the errors caused by noise and geometric registration can be reduced effectively.%利用MODIS NDVI与Landsat TM多光谱遥感影像,提出在缺少地面实测数据的情况下如何快速获得精准的大范围高时效植被覆盖度.利用经验模型与像元二分模型分别计算MODIS影像的植被盖度,然后以TM影像估算出的精度较高的植被盖度为基准,选取检验样本,比较不同模型的结果.分析结果表明:在地表植被分布均匀的研究区内,较大样方建立的非线性经验模型比像元二分模型能更好地提取较大范围内的植被盖度信息,有效地减少MODIS因噪声和几何配准问题使提取结果产生的误差.