MSc thesis subject: Remote sensing based SDG indicator monitoring

The United Nations has recently adopted "Transforming our World: The 2030 Agenda for Sustainable Development”. Comprising a set of 17 Sustainable Development Goals (SDGs) with 169 associated targets, the 2030 Agenda builds on the achievements of the Millennium Development Goals (MDGs). The 17 ambitious, universal and transformative Goals are interlinked and capture the three pillars of sustainable development -economic, social and environmental.

Progress towards the SDG targets is monitored by a number of measurable indicators. Some of these indicators can potentially be monitored using existing remote sensing (RS) datasets and products, including land cover maps. Several potential topics could be explored with this in mind.


One of the three following objectives or a student’s own similar idea should be developed:

  1. Assessing the potential for available global geospatial datasets to measure and monitor the SDG indicators. An evaluation of the available datasets (land cover or wider geospatial datasets), and their strengths (thematic, spatial and temporal detail etc.) as well as the indicators and their data needs could be undertaken. Some indicators could be selected to further illustrate the use of global datasets for monitoring multiple indicators.
  2. Measuring and monitoring a selected indicator. An indicator of choice, will be assessed in one country /region or comparable countries / regions. Some indicators have well developed methodologies, and we focus mainly on those with less developed methods (tier 3 or 2). The trend over space and time can be assessed, and the implications of using different input datasets (including national datasets if available) will be evaluated. The following indicators could be explored, although the option to assess others could be discussed:

    • 2.4.1 Proportion of agricultural area under productive and sustainable agriculture
    • 9.1.1 Proportion of the rural population who live within 2 km of an all-season road
    • 11.3.1 Ratio of land consumption rate to population growth rate
    • 11.7.1 Average share of the built-up area of cities that is open space for public use for all, by sex, age and persons with disabilities. In this case, the focus could be use of RS datasets to identify green spaces in cities, and ancillary data could be used as available to estimate the social aspect of the indicator.
  3. Assessing trade-offs between SDGs. The SDGs represent a wide variety of topics, and in some cases, a positive outcome in one will likely lead to a negative outcome in another. For example, measures on reducing poverty might lead to decreased levels of sustainable agriculture , or food security affected by changes to agricultural areas or expansion of urban areas. Multiple potentially conflicting indicators could be mapped over time, using available geospatial datasets to identify potential conflicts and synergies.



  • GIS software knowledge (no specific courses are required)

Theme(s): Integrated Land Monitoring