Abstract
Improving the planning and provision of public services for those living in informal settlements depends on the availability of accurate demographic information. However, such data frequently do not exist because traditional survey and census methods are rarely successful in these environments. In this paper, the use of automatic feature extraction from aerial imagery is proposed as an alternative to these ground-based methods. We focus on the identification of roof and non-roof objects in an informal settlement called Diepsloot, situated close to Johannesburg in South Africa and home to approximately 200,000 people. Reference data provided by City Johannesburg Metropolitan Municipality authority is used to validate the results of our automated analysis, which achieved an overall accuracy of 80.5 % when compared to manual delineation.
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Acknowledgments
The authors would like to thank the following individuals and organisations for their time and support during the term of this project:
R Anderson (STATSSA), H Pienaar (Johannesburg Dept‘Dev’ and Planning), C Simms (ESRI South Africa), C Tanner (AOC GeoSpatial), M Thompson (Geo-TerraImage), D Tjia (Jo’burg Corporate GIS), J Verhulp (CDNGI Cape Town), I Guest (SATPLAN), P Ahmad (The City of Johannesburg), C Squarzoni (EXELIS), D Anagnostopoulos (Adonis Design), K Parry (STATS SA), S Williams (Welsh Branch), ESRI South Africa, Corporate Geo-Informatics City of Johannesburg, CDNGI South Africa and finally L Petricevic.
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Williams, N., Quincey, D. & Stillwell, J. Automatic Classification of Roof Objects From Aerial Imagery of Informal Settlements in Johannesburg. Appl. Spatial Analysis 9, 269–281 (2016). https://doi.org/10.1007/s12061-015-9158-y
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DOI: https://doi.org/10.1007/s12061-015-9158-y