Assessing the effectiveness of rangeland interventions in northern Kenya based on local knowledge and satellite imagery
The topic is also open and suitable for:
- GEM students in track 1 – GEM for Urban-Rural Interactions
- GEM students in track 3 – GEM for Ecosystems & Natural Resources.
Suggested elective courses:
- Environmental Monitoring with Satellite Image Time Series
- Quantitative remote sensing of vegetation parameters
- Weather Impact Analysis
- Python Solutions
The remote sensing work can build on an existing workflow written in R by Jasper Van doninck:
https://github.com/Space4Restoration/EnvImpactEval
The student should ideally spend a certain time in northern Kenya, although the length of this stay will depend on the student’s financial set-up (e.g. the RANGE-financed MSc students will be expected to spend more time in Kenya, but for other students this may be less and/or focus could be more in the remote sensing part. Advisor for this research will be the RANGE-funded PhD candidate Teyie Sharon.
The arid and semi-arid lands (ASALs) of northern Kenya face significant challenges due to climatic variability, land degradation, and resource-based conflicts. Livelihoods in these areas predominantly depend on livestock, with seasonal herd migration serving as a key strategy to ensure animals receive adequate food and water. However, frequent droughts, flooding, erosion, disease outbreaks, and the spread of non-palatable invasive species threaten the sustainable provision of ecosystem services essential for the various pastoral communities.
To address these challenges, both government and non-governmental organizations have implemented various interventions aimed at improving rangeland conditions, such as invasive species removal and soil and water conservation measures. However, to assess the success or failure of these interventions and determine their potential for scaling, it is crucial to monitor their effectiveness over time. This should involve long-term assessments to determine whether the benefits to rangeland health persist for years after the intervention.
Local resource users, who directly interact with the environment, are best positioned to assess the benefits of an intervention and identify any unintended negative side effects. Their input is therefore essential in creating effective indicators for intervention success. For instance, while remote sensing data may show a greening trend following an intervention, this may not reflect real benefits if the greening is due to the proliferation of undesirable invasive species (e.g., species that are not palatable to livestock). At the same time, satellite imagery can provide valuable insights into long-term impacts across large areas.
The PhD candidate’s project aims to bridge the gap between satellite imagery and local knowledge. The proposed MSc study will contribute to this by 1) broadening the regional scope of the research, and 2) conducting initial assessments to explore how satellite imagery can support effective before-after control-impact analysis.
The student will need to frame the final scientific objectives and align these with the plans of one of the PhD candidates under RANGE. Nonetheless, the following activities are foreseen to form part:
- Make an inventory (database) of existing rangeland interventions in the past 5 to 10 years in (part of) three northern counties in Kenya;
- Assess local opinions surrounding which elements of the intervention are successful, which not, and what indicators they use to assess this;
- Use a before-after control-impact (BACI) design to evaluate longer-term impacts of interventions, with the aid of satellite imagery.
The MSc project will form part of the large RANGE project (Resilient Approaches in Natural Rangeland Ecosystems), which is led by Mercy Corps and includes ITC as a main partner, particularly for working on the evidence basis on rangeland interventions for resilience. RANGE aims to strengthen the resilience of ASAL communities in three counties of northern Kenya: Marsabit, Samburu, and Isiolo. As part of RANGE, innovative data collection protocols will be developed and implemented. For 2024-2028 six PhD candidates and nine MSc students are funded through RANGE. This topic will align with (and contribute to) research by one of the PhD candidates.
- Meroni, M., Schucknecht, A., Fasbender, D., Rembold, F., Fava, F., Mauclaire, M., Goffner, D., Di Lucchio, L.M., & Leonardi, U. (2017). Remote sensing monitoring of land restoration interventions in semi-arid environments with a before–after control-impact statistical design. International Journal of Applied Earth Observation and Geoinformation, 59, 42-52 https://doi.org/10.1016/j.jag.2017.02.016
- Mishra, V., Limaye, A.S., Doehnert, F., Policastro, R., Hassan, D., Ndiaye, M.T.Y., Abel, N.V., Johnson, K., Grange, J., Coffey, K., & Rashid, A. (2023). Assessing impact of agroecological interventions in Niger through remotely sensed changes in vegetation. Scientific Reports, 13, 360 https://doi.org/10.1038/s41598-022-27242-3
- del Río-Mena, T., Willemen, L., Vrieling, A., & Nelson, A. (2023). How remote sensing choices influence ecosystem services monitoring and evaluation results of ecological restoration interventions. Ecosystem Services, 64, 101565 https://doi.org/10.1016/j.ecoser.2023.101565
Ample scope for adaptation exists. The work should support to spatial planning by providing evidence of interventions: as such within the RANGE project it will inform interventions and planning at county government level. Furthermore, there is a strong technical component (SIS and TE) in designing and applying remote sensing data effectively to understand the effect of interventions on biophysical indicators derived from satellite imagery.