Monitoring agriculture in Ethiopia based on an earth observation time series
Remote Sensing for large-scale agricultural investment areas in Ethiopia – agricultural monitoring based on Earth observation time-series ⎮ Poster: © German Aerospace Center (DLR)
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To assess land use for agricultural production and differentiate between crop types within the three study areas, an analysis of earth observation data time series was conducted.
The current land use/land cover was determined by utilizing Sentinel-2 and Sentinel-1 time series data, along with digital elevation model data to identify cropland areas. Subsequently, time-series data from Sentinel-1 and Sentinel-2 were employed to distinguish among 20 different crop types cultivated in these regions.
The process involved supervised classification, using field data on crop types and sample data on land use/land cover, and training and applying random forest classifiers with selected spectral and temporal metrics.
The cloud processing environment of Google Earth Engine was chosen, facilitating the utilization of the classification procedure by regional experts without the need for extensive computational power or software.
Genanaw Alemu (Genanaw.email@example.com), Rahel Hailu (firstname.lastname@example.org)