Project properties

Title Understanding the influence of remote sensing classification methods on smallholder irrigation in Mozambique
Group Water Resources Management group
Project type thesis
Credits 36
Supervisor(s) Gert Jan Veldwisch, Alex Bolding
Contact info
Begin date 2020/05/01
End date 2022/01/01
Description Country: Mozambique
Host institute: Resiliencia

Problem context
Smallholder irrigation is seen as a useful approach to improve agricultural productivity, increase food security, reduce poverty and increase resilience to climate variability. However, irrigation is not as productive and sustainable as it could be. Research suggests that the area covered by smallholder irrigation may be twice as large as official statistics mention, indicating that farmers do see irrigation as beneficial and are investing in expansion of irrigated areas. However, it is currently unknown how much area is irrigated and where this occurs. One way of finding out is by analysing satellite images (remote sensing).

Research Objective/Question
This research will try to understand spatio temporal dynamics of irrigated agriculture in two provinces of Mozambique (Gaza & Manica ) by comparing various remote sensing classification
A research question could be: How do different classification methods classify irrigated agriculture in Mozambique?

What is expected from the student (type of research)
The student is expected to compare various classification algorithms on a small agricultural area. Fieldwork to collect ground truthing data is needed. Programming skills are not necessary, but can be useful. Sufficient understanding of remote sensing is required.
Used skills Field observations ; literature review; sufficient
GIS/remote sensing skills