基于融合时间特征Landsat影像的水稻面积提取

Paddy Fields Area Extraction Based on Landsat Data with Integrating Temporal Features

以洞庭湖区典型的产量大县——南县为研究区,针对Landsat回访周期较长及长江中下游阴雨天气较多的特点,利用STARFM模型融合高时间分辨率的MODIS数据与中等空间分辨率的Landsat TM数据,获取融合时间特征的Landsat TM时序数据,基于作物物候特征提取水稻的种植面积,并与单时相Landsat TM影像分类结果进行对比分析。结果表明,基于时序Landsat NDVI数据的水稻作物分类精度较之单时相Landsat TM影像分类结果有较大的提高。

Taking Nan County, a typical paddy production county in Dongting Lake area, as the study area, we used remote sensing data to derive the paddy area. According to the return cycle of the Landsat and rainy weather of the middle and lower reaches of Yangtze River, we utilized spatio-temporal adaptive reflectance fusion model(STARFM) to fuse MODIS data with high temporal resolution and Landsat data with moderate spatial resolution, and produced the time series Landsat TM data with temporal features. And then, we used Landsat data with integrating temporal features and SVM to extract the paddy fields area based on crop phenology characteristics. The results indicate that the classification accuracy of paddy has been improved by using time series Landsat NDVI data.