ISPRS-Archives The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ISPRS-Archives Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci. 2194-9034 Copernicus Publications Göttingen, Germany 10.5194/isprs-archives-XLVIII-1-W2-2023-559-2023 CAPACITY BUILDING FOR GIS-BASED SDG INDICATORS ANALYSIS WITH GLOBAL HIGH-RESOLUTION LAND COVER DATASETS Oxoli D. https://orcid.org/0000-0002-3226-5586 1 Reyes S. R. 2 Peng S. 3 Brovelli M. A. 1 Coetzee S. 4 Ivanova I. 5 Leonardi J. A. 1 Rawal D. 6 Vacca G. 7 Zlatanova S. 8 Dept. of Civil and Environmental Engineering, Politecnico di Milano, P.zza Leonardo da Vinci 32, 20133 Milano, Italy United Nations Satellite Centre, United Nations Institute for Training and Research, United Nations Building, Bangkok, Thailand National Geomatics Center of China, Beijing, China Dept. of Geography, Geoinformatics and Meteorology, University of Pretoria, Hatfield Campus, Lynnwood Road, Hatfield, 0083 Pretoria, South Africa School of Earth and Planetary Sciences, Curtin University, Kent Street Bentley, Perth, Australia Dept. of Languages and Literatures, Communication, Training and Society, Laboratory of Geomatics Guido Barbina, Udine University, Via Palladio 8, 33100 Udine, Italy Dept. of Civil and Environmental Engineering and Architecture, University of Cagliari, Piazza D’Armi, 09123 Cagliari, Italy School of Built Environment, University of New South Wales, 2052 Sydney, Australia 13 12 2023 XLVIII-1/W2-2023 559 564 Copyright: © 2023 D. Oxoli et al. 2023 This work is licensed under the Creative Commons Attribution 4.0 International License. To view a copy of this licence, visit https://creativecommons.org/licenses/by/4.0/ This article is available from https://isprs-archives.copernicus.org/articles/XLVIII-1-W2-2023/559/2023/isprs-archives-XLVIII-1-W2-2023-559-2023.html The full text article is available as a PDF file from https://isprs-archives.copernicus.org/articles/XLVIII-1-W2-2023/559/2023/isprs-archives-XLVIII-1-W2-2023-559-2023.pdf

The support of geospatial data and technologies for the United Nations Sustainable Development Goals (SDG) framework is critical for assessing and monitoring key indicators, revealing the planet’s trajectory towards sustainability. The availability of global open geospatial datasets, especially high-resolution land cover datasets, provides significant opportunities for computing and comparing indicators across different regions and scales. However, barriers to their proficient use remain due to a lack of data awareness, management and processing capacities using geographic information systems software. To address this, the ”Capacity Building for GIS-based SDG Indicator Analysis with Global High-resolution Land Cover Datasets” project created open training material on discovering, accessing, and manipulating global geospatial datasets for computing SDG indicators. The material focuses on water and terrestrial ecosystems, urban environments, and climate, by leveraging world-class global geospatial datasets and using the Free and Open Source Software QGIS. The training material is released under a Creative Commons Attribution 4.0 License, ensuring broad accessibility and facilitating continuous improvement.