The need for high-resolution data in African savanna landscapes can complicate mapping land cover types. The NICFI Satellite Data Program provides free imagery to help users map these regions in detail.
Recent publications highlight the benefits of using high-resolution satellite imagery and machine learning algorithms as powerful tools for mapping land cover types in data-sparse landscapes. The research titled “A super-ensemble approach to map land cover types with high resolution over data-sparse African savanna landscapes” uses the NICFI Basemaps and Sentinel 1 images to create land cover maps. By analyzing the spectral characteristics of the vegetation and using machine learning algorithms, they improved land cover maps over sparse landscapes, such as those found in Tanzania.
The resulting land cover map can provide valuable information on numerous ecological applications, including tracking agricultural activities, deforestation and the sustainability of protected regions.
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