基于MODIS数据的朝鲜半岛土地利用变化信息提取

以朝鲜半岛为研究区域, 基于2000年和2007年的MOD IS数据, 应用线性光谱混合模型进行像元组分分解并提取分类特征, 对像元组分分解后有错分的地物类型结合纹理进行分析, 以决策树模型进行土地利用分类。结果表明, 像元组分分解后的决策树分类结果总体精度达78.346 5% , Kappa系数达0.681 3。与像元组分分解前最大似然法和决策树分类结果相比, 决策树分类精度优于最大似然法, 且像元组分分解方法提高了分类精度。经2000年和2007年像元组分分解后的决策树分类结果对比: 朝鲜耕地面积增加; 韩国耕地面积减少, 居民地面积增加。

Information extraction of land use change in Korean Peninsula based on MODIS data

In order to do land use classification by decision tree method (DTC) , the authors process pixel component unmixing and extract category features using linear spectral mixture model, and analyse the misclassified surface object type after pixel component unmixing which were combined with texture based on 2000 and 2007 MODIS data in Korean Peninsula. The analysis result shows the accuracy of DTC after pixel component unmixing is 78.346 5% and Kappa coefficient is 0.681 3. Compared with the classification results ofmaximum likelihood and DTC before pixel component unmixing, the classification accuracy of DTC is superior to maximum likelihood and the pixel component unmixing method improves the classification accuracy. According to the DTC classification results after pixel component unmixing of 2000 and 2007, the farmland area increased in northern Korean peninsula, while the farmland area decreased and the residential area increased in southern Korean peninsula.