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Object-oriented industrial solid waste identification using HJ satellite imagery: a case study of phosphogypsum

文献类型： 外文期刊

作者： Fu, Zhuo 1 ; Shen, Wenming 1 ; Xiao, Rulin 1 ; Xiong, Wencheng 1 ; Shi, Yuanli 1 ; Chen, Baisong 2 ;

作者机构： 1.Minist Environm Protect China, Satellite Environm Ctr, Fengdedong Rd, Beijing 100094, Peoples R China

2.Chinese Acad Fishery Sci, Beijing 100141, Peoples R China

关键词： Object-oriented method;industrial solid waste;identification;HJ satellite imagery;phosphogypsum;Fuquan;Multiresolution segmentation;feature knowledge

期刊名称：EARTH RESOURCES AND ENVIRONMENTAL REMOTE SENSING/GIS APPLICATIONS III

ISSN： 0277-786X

年卷期： 2012 年 8538 卷

页码：

收录情况： SCI

摘要： The increasing volume of industrial solid wastes presents a critical problem for the global environment. In the detection and monitoring of these industrial solid wastes, the traditional field methods are generally expensive and time consuming. With the advantages of quick observations taken at a large area, remote sensing provides an effective means for detecting and monitoring the industrial solid wastes in a large scale. In this paper, we employ an object-oriented method for detecting the industrial solid waste from HJ satellite imagery. We select phosphogypsum which is a typical industrial solid waste as our target. Our study area is located in Fuquan in Guizhou province of China. The object-oriented method we adopted consists of the following steps: 1) Multiresolution segmentation method is adopted to segment the remote sensing images for obtaining the object-based images. 2) Build the feature knowledge set of the object types. 3) Detect the industrial solid wastes based on the object-oriented decision tree rule set. We analyze the heterogeneity in features of different objects. According to the feature heterogeneity, an object-oriented decision tree rule set is then built for aiding the identification of industrial solid waste. Then, based on this decision tree rule set, the industrial solid waste can be identified automatically from remote sensing images. Finally, the identified results are validated using ground survey data. Experiments and results indicate that the object-oriented method provides an effective method for detecting industrial solid wastes.

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