Computer Science > Computer Vision and Pattern Recognition
[Submitted on 13 Jun 2022 (v1), last revised 9 May 2023 (this version, v5)]
Title:Satellite-based high-resolution maps of cocoa planted area for Côte d'Ivoire and Ghana
View PDFAbstract:Côte d'Ivoire and Ghana, the world's largest producers of cocoa, account for two thirds of the global cocoa production. In both countries, cocoa is the primary perennial crop, providing income to almost two million farmers. Yet precise maps of cocoa planted area are missing, hindering accurate quantification of expansion in protected areas, production and yields, and limiting information available for improved sustainability governance. Here, we combine cocoa plantation data with publicly available satellite imagery in a deep learning framework and create high-resolution maps of cocoa plantations for both countries, validated in situ. Our results suggest that cocoa cultivation is an underlying driver of over 37% and 13% of forest loss in protected areas in Côte d'Ivoire and Ghana, respectively, and that official reports substantially underestimate the planted area, up to 40% in Ghana. These maps serve as a crucial building block to advance understanding of conservation and economic development in cocoa producing regions.
Submission history
From: Nikolai Kalischek [view email][v1] Mon, 13 Jun 2022 12:58:35 UTC (19,617 KB)
[v2] Fri, 8 Jul 2022 09:37:00 UTC (19,644 KB)
[v3] Thu, 6 Oct 2022 06:46:42 UTC (19,644 KB)
[v4] Mon, 10 Oct 2022 07:57:34 UTC (19,644 KB)
[v5] Tue, 9 May 2023 08:58:11 UTC (23,131 KB)
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