Journal Article10.1016/J.COMPENVURBSYS.2011.11.001
An ontology of slums for image - based classification
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TL;DR: An ontological framework to conceptualize slums using input from 50 domain-experts covering 16 different countries is developed and serves as a comprehensive basis for image-based classification of slums, in particular, using object-oriented image analysis (OOA) techniques.
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About: This article is published in Computers, Environment and Urban Systems. The article was published on 01 Mar 2012.
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Citations
Characterizing Informal Settlement Dynamics Using Google Earth Engine and Intensity Analysis in Durban Metropolitan Area, South Africa: Linking Pattern to Process
TL;DR: In this article , an object-based image classification on PlanetScope imagery within the Google Earth Engine (GEE) platform was utilized to quantitatively investigate inter-category transitions at category and transition levels.
Automated detection of slum area change in Hyderabad, India using multitemporal satellite imagery
TL;DR: In this article, the authors presented an approach to automated identification of slum area change patterns in Hyderabad, India, using multi-year and multi-sensor very high resolution satellite imagery.
Slums, Space, and State of Health-A Link between Settlement Morphology and Health Data.
TL;DR: This study investigates how and on which spatial scale relationships between the settlement morphology and the health status of the inhabitants can be identified and develops a framework to investigate the relationship between space and health.
Urban slum detection using texture and spatial metrics derived from satellite imagery
TL;DR: In this article, a method for slum detection based on the morphology of the built environment is presented. But, the method is not suitable for large variations in slum types and definitions and the accuracy of agreement between the reference layer and slum classification was only 60 percent.
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