基于面向对象的多源卫星遥感影像玉米倒伏面积提取

风灾引起的玉米倒伏可能导致玉米大量减产，利用遥感技术准确监测玉米倒伏面积与空间分布信息对灾情的评估非常重要。利用Planet和Sentinel-2影像分别结合面向对象与基于像元方法提取研究区玉米倒伏，同时评估了不同影像特征（光谱特征、植被指数和纹理特征）与不同分类方法（支持向量机法SVM、随机森林法RF和最大似然法MLC）对玉米倒伏提取精度的影响。结果表明：①使用高空间分辨率的Planet影像进行玉米倒伏提取的精度普遍高于Sentinel-2影像；②从分类精度和面积精度来看，Planet影像的光谱特征+植被指数+均值特征结合面向对象RF分类，总体精度和Kappa系数分别为93.77%和0.87，面积的平均误差最低为4.76%；③采用Planet和Sentinel-2影像结合面向对象分类提取玉米倒伏精度高于基于像元分类。研究不仅分析了面向对象方法的优势，还评估了使用不用影像数据结合面向对象方法的适用性，可以为遥感提取作物倒伏相关研究提供一定的借鉴。

Object-oriented Extraction of Maize Fallen Area based on Multi-source Satellite Remote Sensing Images

Maize lodging caused by wind disaster may lead to a large reduction in maize production. Using remote sensing technology to accurately monitor maize lodging area and spatial distribution information is very important for disaster assessment.In this paper， Planet and Sentinel-2 images are combined with object-oriented and pixel-based methods to extract maize lodging in the study area， and different image features （spectral features， vegetation index and texture features） and different classification methods （support vector machine SVM， Random forest method RF and maximum likelihood method MLC） influence on the extraction accuracy of corn lodging.The results show that： ① The accuracy of corn lodging extraction using Planet images with high spatial resolution is generally higher than that of Sentinel-2 images；② From the perspective of classification accuracy and area accuracy， the spectral features， vegetation index， and mean feature of Planet image combined with object-oriented RF classification， the overall accuracy and Kappa coefficient are 93.77% and 0.87， respectively， and the average area error is the lowest 4.76%；③The accuracy of extracting maize lodging using Planet and Sentinel-2 images combined with object-oriented classification is higher than that of pixel-based classification. This research not only analyzes the advantages of object-oriented methods， but also evaluates the applicability of using different image data combined with object-oriented methods， which can provide a certain reference for remote sensing to extract crop lodging related research.