Using open data to detect the structure and pattern of informal settlements: an outset to support inclusive SDGs’ achievement

The detection of informal settlements is the first step in planning and upgrading deprived areas order to leave no one behind SDGs. Very High-Resolution satellite images (VHR), have been extensively used for this purpose. However, as a cost-prohibitive data source, VHR might not be available all, particularly nations that are home many settlements. This study examines application open freely sources detect structure pattern Here, case Jakarta, Indonesia, Medium Resolution imagery (MR) derived from Landsat 8 (2020) was classified these classification done using Random Forest (RF) classifier through two complementary approaches develop training set. In approach, survey sets (Jakarta’s map 2015) visual interpretation Google Map build Throughout second round classification, OpenStreetMap (OSM) layers were approach training. Results validation test revealed better accuracy precision classification. proposed method provides an opportunity use detection, when: 1) more expensive high resolution accessible; 2) area interest larger than city; 3) physical characteristics differ significantly their surrounding formal area. presents globally accessible help achievement resilience SDGs