Desertification Land Information Extraction Based on Object-Oriented Classification Method | 面向对象的沙化土地信息提取

Chino. 以沙化土地典型分布区――甘肃省民勤县为研究对象,以高空间分辨率影像SPOT5与30mDEM为主要数据源,采用面向对象的影像分析方法,对影像进行多尺度、多层次的分割、合并,在此基础上,通过构建多重规则集,对影像进行基于知识的模糊分类,可较为准确地实现沙化土地信息的识别与提取。本文为解决基于高空间分辨率影像进行沙化土地信息准确提取提供一个有效途径,为防沙治沙决策提供科学依据。

Inglés. Desertification of land was the significant environmental issue threatening human existence. Desertification land area was 1 731 100 km2 in 2009, occupying 18.03% of China＇ s total land area. Remote sensing is an effective method monitoring the desertification land. With the development of remote sensing technology, high spatial resolution remote sensing image gradually becomes main data source of resolving the desertification land information extraction. The traditional remote sensing image classification method based on pixel has some difficulties in treating the high spatial resolution remote sensing images, however, the object-oriented classification method might overcame the limit of using the pixel as basic treatment unit. Minqin County, a typical desertification land distribution region, was used as studied object in this paper, the high spatial resolution remote sensing images SPOT5 and 30 m DEM were used as date sources, the multi-scale and multi-level segmentation of remote sensing images was conducted by using the object-oriented classification method. Based on these results, the remote sensing images were subjected to fuzzy image classification based on knowledge by constructing multiset, and thus relatively accurately realize the recognition and extraction of desertification land information. This paper would provide an effective path for resolving the accurate extraction of desertifieation land information based on the high spatial resolution remote sensing images and also provide scientific proofs for sand prevention and control.