NDLI: Extracting fly ash site information using decision tree classification

Content Provider	IEEE Xplore Digital Library
Author	Jinfa Dong Qingsheng Liu Gaohuan Liu Wenming Shen Dan Huang
Copyright Year	2012
Description	Author affiliation: Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing, China (Jinfa Dong; Qingsheng Liu; Gaohuan Liu; Dan Huang) \|\| Satellite Environment Center, Ministry of Environmental Protection, Beijing, China (Wenming Shen)
Abstract	Fly ash not only pollutes the environment but also endangers the human health. Rapid, real-time, accurate identification of fly ash by means of remote sensing is of great significance for protecting the environment and the human health. In this paper, by analyzing the spectral information of the typical surface features in Baotou City, based on Landsat 5 TM image data, it adopted the decision tree classification to extract fly ash in the study area. Firstly, we analyze the spectral characteristics of the typical objects and the relationship between them in the study area. Secondly, we established the decision tree, used Soil-adjusted Vegetation Index (SAVI), Modified Normalized Difference Water Index (MNDWI), Normalized Difference Built-up Index (NDBI) and Spectrum Threshold Method to classify the image respectively. Ultimately, post-process the classified image with shape feature and location feature. The total classification accuracy was up to 70.7%. The experimental results show that the method is suitable for the automatic extraction of fly ash information, that what combined with the visual interpretation, can achieve high accuracy.
Starting Page	429
Ending Page	433
File Size	577514
Page Count	5
File Format	PDF
ISBN	9781467309653
e-ISBN	9781467309646
DOI	10.1109/CISP.2012.6469858
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-10-16
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Fly ash Roads Buildings decision tree classification fly ash remote sensing Indexes Data mining Decision trees Remote sensing
Content Type	Text
Resource Type	Article

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