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).
There are many ways to map irrigation with satellite imagery and many choices, such as which sensors, algorithms, which and how many classes, their descriptions, and training and validation data. All of these choices need to be aligned with what it is that should be mapped, namely irrigated agriculture. Smallholder agriculture consists of many small plots (0.5-2 ha fields) all with different crops, cropping patterns, irrigation methods, planting dates, field shapes and many more differences. This makes it difficult to generalise models and it would be valuable to understand how choices affect the classification results, such as a bias towards certain characteristics (e.g. crop type).
The following objectives give an idea of the many possibilities for a research:
- Identify different crop types and determine biomass production with crop models
- Determine how much water is used by the crops (evapotranspiration) for a water balance
- Identify drivers of change in irrigated areas, such as climate and location, but also social factors such as economic change, road construction, access to markets or institutional changes.
- How can irrigated agriculture best be distinguished from rainfed agriculture and other land uses/covers.
- Analyse how the different choices in classification steps affect the eventual results or focus on one specific step.
- Vogels, M. F., De Jong, S. M., Sterk, G., Douma, H., & Addink, E. A. (2019). Spatio-temporal patterns of smallholder irrigated agriculture in the horn of Africa using GEOBIA and Sentinel-2 imagery. Remote Sensing, 11(2), 143.
- Beekman, W., Veldwisch, G. J., & Bolding, A. (2014). Identifying the potential for irrigation development in Mozambique: Capitalizing on the drivers behind farmer-led irrigation expansion. Physics and Chemistry of the Earth, Parts A/B/C, 76, 54-63.
- Ozdogan, M., Yang, Y., Allez, G., & Cervantes, C. (2010). Remote sensing of irrigated agriculture: Opportunities and challenges. Remote sensing, 2(9), 2274-2304.
- It is possible to do fieldwork in the provinces Manica and Gaza in Mozambique.
- Preferably work in R or Google Earth Engine
Theme(s): Sensing & measuring; Modelling & visualisation