Thesis subject
MSc thesis topic: Investigate density of cashew plantations in Odiènne, Cote D’Ivoire
This MSc thesis aims to analyse the density of cashew plantation in Odiènne, Cote D’Ivoire. Traditionally, cashew trees were planted by smallholder farmers to ensure and confirm ownership of land and to prevent desertification. This resulted in scattered cashew plantations, which are increasingly being used for commercial nut production. By determining the location and the quality of the plantation by its density, it will be possible to organise and improve the production of cashew nuts. Currently, the density of cashew plantations in the North of Cote D’Ivoire has been investigated in a previous thesis, but using different input data (Sentinel-2 (10m resolution) and PlanetScope (3-4m resolution), gave inconclusive results regarding the density. The aim of this thesis is to use (high resolution) satellite imagery in order to investigate the density of a cashew plantation in detail, using different density measures.
Cote D’Ivoire is the 3rd largest cashew producer in the world and most cashew plantations can be found in the North of the country. 780,000 tons of cashew nuts have been produced in Cote D’Ivoire in 2018 (World Bank, 2018), which is about a quarter of the global cashew production. Cashew trees were introduced in the country to reduce desertification in the region. Later, the commercial value (on commercial scale) of cashew became more important. An estimated 350,000 smallholder farmers are involved in production in Cote D’Ivoire (Coulibaly, 2018). Cashew nut trees are perennial trees, which are mostly harvested during the dry season (roughly February to April).
To make cashew cultivation commercial viable, it is important the cashew trees are planted in a low density. This enables better maintenance and harvesting for the cashews, but gives room for intercropping possibilities as well.
Objectives
- Develop a methodology for determining the density of cashew (plantations) with (high resolution) remote sensing data
Literature
- Mazzia V, Khaliq A, Chiaberge M.Improvement in Land Cover and Crop Classification based on Temporal Features Learning from Sentinel-2 Data Using Recurrent-Convolutional Neural Network (R-CNN). Applied Sciences. 2020; 10(1):238.
- Boafo, J. 2019.Expanding Cashew Nut Exporting from Ghana’s Breadbasket: A Political Ecology of Changing Land Access and Use, and Impacts for Local Food Systems. The International Journal of Sociology of Agriculture and Food. 25, 2 (Aug. 2019), 152-172.
- Bamba, Issouf, et al. "Cashew Nut is Reshaping the Rural Landscape of the Seguela Sub-Prefecture (Northwestern Côte d'Ivoire)." International Journal of Natural Resource Ecology and Management 4.1 (2019): 22.
Theme(s): Sensing & measuring; Empowering & engaging communities