Capacity Building for GIS-based SDG Indicator Analysis with Global High-resolution Land Cover Datasets

ISPRS Educational and Capacity Building Initiative 2022

In the framework of the United Nations Sustainable Development Goals (UN SDGs), the support of geospatial data and technologies has turned out to be critical for both the assessment and the monitoring of key indicators, revealing the trajectory of our planet and society towards sustainability. The increasing availability of global open geospatial datasets - above all the global high-resolution land cover (HRLC) datasets - opens newsworthy opportunities for the computation and comparison of these indicators across different geographical regions as well as multiple spatial and temporal scales. The added value of these datasets is tangible, especially for developing countries, where often such information is only partially available from local authorities. Nevertheless, there are still several barriers to their proficient use due to the lack of data management and processing capacity using proper Geographic Information Systems (GIS) software tools.

In view of the above, this project, supported by the Educational and Capacity Building Initiative 2022 of the International Society of Photogrammetry and Remote Sensing (ISPRS), addresses the creation of open training material covering the complete learning process of discovering, accessing and manipulating global open geospatial datasets for computing SDG indicators, with a focus on those directly connected to marine and terrestrial ecosystems, urban environment, and climate. To ensure the widest possible accessibility, the material primarily leverages the Free and Open Source Software (FOSS) QGIS and it is released under a Creative Commons Attribution 4.0 License (CC BY 4.0).

Contents:

• 1. Background
  • 1.1. Introduction to United Nations Sustainable Development Goals
  • 1.2. Geospatial data and technologies for SDGs
• 2. Data
  • 2.1. Global High-resolution Land Cover datasets
  • 2.2. Other relevant global geospatial datasets for SDGs
• 3. Tools
  • 3.1. QGIS
  • 3.2. Key QGIS functionalities for SDG indicators computation
• 4. Case studies
  • 4.1. Forest area as a proportion of total land area [15.1.1]
  • 4.2. Ratio of land consumption rate to population growth rate [11.3.1]
  • 4.3. Proportion of the rural population who live within 2 km of an all-season road [9.1.1]
  • 4.4. Change in the extent of water-related ecosystems over time [6.6.1]

• Credits

Important

This project was funded by the International Society of Photogrammetry and Remote Sensing (ISPRS) within the Educational and Capacity Building Initiative 2022.

Note

All materials in this web-book are from public literature and the Internet. Unintended use herein of the copyrighted material is purely for educational purposes

License Creative Commons Attribution 4.0 License (CC BY 4.0)