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Table 7 Examples of application of supervised classification techniques towards SDGs using EO data

From: Monitoring sustainable development by means of earth observation data and machine learning: a review

SDGs Field Main finding References
SGD 11 (Sustainable Cities and Communities) Land use Tested Sub-PB and Super-PB methodologies to map green spaces. The results showed that Super-PB approach was better for dense urban, sub-urban and rural subsets. However, for lower-resolution images, the Sub-PB approach performed better for dense urban and sub-urban subsets [136]
Land change Developed two CNN approaches: Early Fusion and Siamese Network to detect changes in pairs of images. Overall, the results proved that Siamese Network approach was the most accurate [144]
SGD 12 (Responsible Consumption and Production) Consumption Proved that CNNs combined with high-resolution images represent a precise and cost-effective methodology to calculate consumption expenditure and wealth in developing countries [145]
SDG 15 (Life on Land) Land cover Analysed 15 years of research on supervised classification methods and found that SVM was the most accurate among NN, RF and Decision Tree [146]