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.
CAPACITY BUILDING FOR GIS-BASED SDG INDICATORS ANALYSIS WITH GLOBAL HIGH-RESOLUTION LAND COVER DATASETS
Oxoli, D.;Brovelli, M. A.;Leonardi, J. A.;
2023-01-01
Abstract
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.File | Dimensione | Formato | |
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2023_Oxoli_GSW_ISPRS_SDGs.pdf
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