Resumo

RAMIREZ GUTIERREZ, Miguel Ángel; LASSO RODRIGUEZ, Juan Carlos  e  DURAN GIL, Carlos Alberto. Integration of statistical information and Earth observations for the calculation of SDG 11.3.1 and 11.7.1 indicators in Colombia, applying Random Forest classification techniques. Cuad. Geogr. Rev. Colomb. Geogr. [online]. 2023, vol.32, n.1, pp.226-257.  Epub 08-Mar-2024. ISSN 0121-215X.  https://doi.org/10.15446/rcdg.v32n1.98039.

This article presents the calculation of the SDG 11.3.1 and 11.7.1 indicators in Colombia, integrating statistical and geospatial information, as essential sources to achieve a robust and territorially disaggregated measurement. Based on the processes defined by UN-Habitat, it develops a methodology with a geospatial emphasis, supported by the processing of satellite images through the Random Forest supervised classification algorithm, to obtain the metrics required in the calculation of the two indicators, such as built-up areas, urban land consumption, and open spaces, together with integrated analysis of statistical information. The SDG 11.3.1 indicator for the 2015-2020 period was calculated for 63 cities, whose national value of 0.43 highlights that efficient land use is made in the country, while SDG 11.7.1 for the year 2018 was calculated in a representative sample of nine cities, which indicates that at the national level 33.2 % of built areas are allocated to open spaces for public use. These results make the country a regional benchmark in the monitoring of the SDGs, highlighting the possibility of updating the results in the future, thanks to automated processing in the cloud using scripts developments.

Palavras-chave : algorithm; random forest; geospatial data; sustainable development; statistics; satellite imagery.

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