Abstract
Accurate estimates of cultivated area and crop yield are critical to our understanding of agricultural production and food security, particularly for semi-arid regions like the Sahel of West Africa, where crop production is mainly rain-fed and food security is closely correlated with the inter-annual variations in rainfall. Several global and regional land cover products, based on satellite remotely-sensed data, provide estimates of the agricultural land use intensity, but the initial comparisons indicate considerable differences among them, relating to differences in the satellite data quality, classification approaches, and spatial and temporal resolutions. Here, we quantify the accuracy of available cropland products across Sahelian West Africa using an independent, high-resolution, visually interpreted sample dataset that classifies all points across West Africa using a 2-km sample grid (~500,000 points for the study area). We estimate the “quantity” and “allocation” disagreements for the cropland class of eight land cover products in five Western Sahel countries (Burkina Faso, Mali, Mauritania, Niger, and Senegal). The results confirm that coarse spatial resolution (300 m, 500 m, and 1000 m) land cover products have higher disagreements in mapping the fragmented agricultural landscape of the Western Sahel. Earlier products (e.g., GLC2000) are less accurate than recent products (e.g., ESA CCI 2013, MODIS 2013 and GlobCover 2009). We also show that two of the finer spatial resolution maps (GFSAD30, and GlobeLand30) using advanced classification approaches (random forest, decision trees, and pixel-object combined) are currently the best available products for cropland identification. However, none of the eight land cover databases examined is consistent in reaching the targeted 75% accuracy threshold in the five Sahelian countries. The majority of currently available land cover products overestimate cultivated areas by an average of 170% relative to the cropland area in the reference data.
Highlights
Inter-annual variability in crop production associated with climate variability, pests, and diseases is a global concern, for developing countries, where rural communities often lack the capital to help them cope with crop failures and food shortages [1]
We focus on reporting the cropland class user’s accuracy, the quantity and allocation disagreements based on Pontius and Millones [14], and the good practices of map accuracy assessment suggested in Olofsson et al [15]
This is the case in Mauritania, where the disagreement due to allocation is negligible compared with the quantity disagreement, resulting in a large overestimation in the total number of pixels identified as crop in the land cover products, relative to the reference data
Summary
Inter-annual variability in crop production associated with climate variability, pests, and diseases is a global concern, for developing countries, where rural communities often lack the capital to help them cope with crop failures and food shortages [1]. Food security is one of the major challenges faced by rural communities in developing countries. In this context, accurate estimates of the cultivated area, as part of crop yield and monitoring programs, are critical to our understanding of agricultural production, food security, and the associated social and economic issues [2]. Several freely-accessible global land cover products, including agricultural land cover classes, are available at varying spatial resolutions. These products utilize different sources of satellite data and implement different classification approaches, with varying accuracy and spatial resolution [4]. A more detailed regional assessment, for the West African Sahel, of these global products has so far not been published
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