Mapping Land Cover Change Across Senegal with Convolutional Neural Networks and Very High Resolution Data
Abstract
In the last 30 years, West Africa's population has more than doubled; growing 2.7% annually. By 2030, 490 million people are expected to live in the region, resulting in additional demands on natural resources in the agricultural and forestry sectors. The West African Sahel region is an epicenter of land cover change hotspots which have not been sufficiently documented, due to the inability of multi-temporal moderate resolution observations to adequately resolve widespread sub-hectare changes. Widespread reforestation in dryland agriculture regions, expansion of irrigated rice cultivation, dryland agriculture extensification and clearing of natural savanna have been reported, but are poorly mapped and quantified.
With the availability of wall-to-wall commercial data and access to efficient supercomputing resources, we are developing CNN models to document land cover change at regional scales and with very high spatial resolution. Here we present preliminary results from our work on mapping changes in irrigated rice, dryland agriculture, and individual trees.- Publication:
-
AGU Fall Meeting Abstracts
- Pub Date:
- December 2022
- Bibcode:
- 2022AGUFM.B42G1723W