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Object-oriented industrial solid waste identification using HJ satellite imagery: a case study of phosphogypsum
Author(s): Zhuo Fu; Wenming Shen; Rulin Xiao; Wencheng Xiong; Yuanli Shi; Baisong Chen
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Paper Abstract

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.

Paper Details

Date Published: 25 October 2012
PDF: 7 pages
Proc. SPIE 8538, Earth Resources and Environmental Remote Sensing/GIS Applications III, 85380L (25 October 2012); doi: 10.1117/12.974476
Show Author Affiliations
Zhuo Fu, Ministry of Environmental Protection (China)
Wenming Shen, Ministry of Environmental Protection (China)
Rulin Xiao, Ministry of Environmental Protection (China)
Wencheng Xiong, Ministry of Environmental Protection (China)
Yuanli Shi, Ministry of Environmental Protection (China)
Baisong Chen, Chinese Academy of Fishery Sciences (China)

Published in SPIE Proceedings Vol. 8538:
Earth Resources and Environmental Remote Sensing/GIS Applications III
Shahid Habib; David Messinger; Antonino Maltese; Ulrich Michel; Daniel L. Civco; Manfred Ehlers; Karsten Schulz; Konstantinos G. Nikolakopoulos, Editor(s)

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