Status: Archive (code is provided as-is, no updates expected)

Mapping Slums with Medium Resolution Satellite Imagery: a Comparative Analysis of Multi-Spectral Data and Grey-level Co-occurrence Matrix Techniques

This repo contains the code to reproduce the results obtained on the paper "Mapping Slums with Medium Resolution Satellite Imagery: a Comparative Analysis of Multi-Spectral Data and Grey-level Co-occurrence Matrix Techniques" accepted at the 3rd Workshop on Artificial Intelligence for Social Good (IJCAI 2021).

Files

• GLCM+CCF_majorityNonSlum.R and GLCM+CCF_majoritySlum.R have the code to create the Grey-level Co-occurrence Matrix features and classify the images using Canonical Correlation Forests.
• Spectral+CCF__majorityNonSlum.R and Spectral+CCF_majoritySlum.R have the code to classify the images using multi-spectral data and Canonical Correlation Forests.

Citation

@misc{demattos2021mapping,
      title={Mapping Slums with Medium Resolution Satellite Imagery: a Comparative Analysis of Multi-Spectral Data and Grey-level Co-occurrence Matrix Techniques}, 
      author={Agatha C. H. de Mattos and Gavin McArdle and Michela Bertolotto},
      year={2021},
      eprint={2106.11395},
      archivePrefix={arXiv},
      primaryClass={cs.CV}
}

Data

The data set used in this study is available at: https://drive.google.com/drive/folders/1yhDwR4zyPQO78x040uGCPqFarTDQ3yQm.

If using the dataset, please cite:

@inproceedings{gram-hansenMappingInformalSettlements2019,
	address = {New York, NY, USA},
	series = {{AIES} '19},
	title = {Mapping {Informal} {Settlements} in {Developing} {Countries} using {Machine} {Learning} and {Low} {Resolution} {Multi}-spectral {Data}},
	doi = {10.1145/3306618.3314253},
	booktitle = {Proceedings of the 2019 {AAAI}/{ACM} {Conference} on {AI}, {Ethics}, and {Society}},
	publisher = {Association for Computing Machinery},
	author = {Gram-Hansen, Bradley J. and Helber, Patrick and Varatharajan, Indhu and Azam, Faiza and Coca-Castro, Alejandro and Kopackova, Veronika and Bilinski, Piotr},
	month = jan,
	year = {2019},
	pages = {361--368}