<会議発表論文>
Detection of Slums from Very High-Resolution Satellite Images Using Machine Learning Algorithms: A Case Study of Fustat Area in Cairo, Egypt

作成者
本文言語
出版者
発行日
収録物名
開始ページ
終了ページ
会議情報
出版タイプ
アクセス権
Crossref DOI
概要 Slums are a global urban challenge, particularly in big cities in most developing countries where they are growing faster than governments control. However, detection of slums is a big challenge for s...uch countries due to fast growing there and difficulty of field survey. To address this challenge, this study uses a novel method to detect slums from very high-resolution (VHR) satellite images using machine learning algorithms and roads network derived from OpenStreetMap. This method has been applied to Fustat Area in the center of Cairo, Egypt where slums highly exist. The result of this study has detected eight slums with areas that ranged from 2.4 ha to 28.3 ha. The accuracy of the result has been verified by the kappa index which showed a high accuracy of 0.93. The results of this study are important for planners and decision makers to help them in developing such areas.続きを見る

本文ファイル

p219 pdf 1.29 MB 299  

詳細

PISSN
EISSN
レコードID
主題
登録日 2020.10.23
更新日 2021.03.25

この資料を見た人はこんな資料も見ています