基于面向对象的黄土丘陵沟壑区梯田信息提取研究

Terrace Information Extraction in Loess Hilly-gully Region Landscape Based on Object-oriented Classification Method

研究区位于黄土丘陵沟壑区第二副区的彭阳县,以国产GF-2影像为数据源,首先按地形复杂度生态分区,选取4个典型试验区;其次应用多尺度分割和光谱差异分割相结合的方法,对试验区影像进行分割;然后重点基于面向对象分类方法,实现梯田信息的自动提取;最后采用参考对象一致性误差(OCE)分割评价准则,以目视解译结果为参考对象,对梯田提取结果进行精度评价。结果表明,基于面向对象分类,不同生态分区遥感影像在最优分割阈值时,梯田信息自动提取精度均达到65%以上,结合后期处理,可以高效、准确地从国产GF-2影像中提取复杂地貌区的梯田及空间分布等相关信息,为黄土丘陵沟壑区农业生产规划、水土流失防治提供基础数据,也提供了新的思路和合理的技术方法。

In order to study the terrace extraction technology in loess hilly-gully region landscape, the study selected Pengyang County, which is located in the second sub region of Loess Hilly-gully Region Landscape, as the research area. The study chooses GF-2 remote sensing image as the basic data. According to the research of terrain complexity of ecological zones selected four typical experimental area. Firstly, the image of the experimental area is segmented by the combination of multi-scale segmentation and spectral difference segmentation. Then, the object-oriented classification method is used to extract the terrace information. Finally, the accuracy of the extraction results is evaluated by using the criterion of reference object consistency error (OCE) segmentation, and the results of visual interpretation are taken as the reference object. The results show that the accuracy of automatic extraction of terrace information is more than 65% based on the object-oriented classification method when the remote sensing images of different ecological regions are in the optimal segmentation threshold. Combined with the later processing, the area and spatial distribution information of terraced fields in complex geomorphic areas can be extracted efficiently and accurately from the GF-2 remote sensing image. It provides the basic data for agricultural production planning, prevention and control of soil erosion in loess hilly-gully region landscape. This method can be extended to other counties in the loess hilly-gully region landscape, and provides new ideas and reasonable technical methods for automatic extraction of terrace information in loess hilly-gully region landscape by using high resolution remote sensing images.