Developing Digital Platform for Brazil - AgroBrazil + Sustentável Platform - AB+S


  • SOLICITATION NUMBER: 0002010084
  • INSTITUTION:  IBRD/IDA
  • ASSIGNMENT LOCATION: Brazil
  • ISSUE DATE AND TIME: Sep 09,2024 20:23
  • CLOSING DATE AND TIME: Sep 23,2024 23:59

The World Bank Group’s Agriculture and Food Global Practice (GP); is providing technical assistance to the Government of Brazil and its Ministry of Agriculture and Livestock (Ministerio da Agricultura e da Pecuaria – MAPA) on the design of a digital platform (AgroBrazil + Sustentável Platform - AB+S). This platform is intended to enhance the transparency; credibility; and trust within the Brazilian agriculture sector by improving the monitoring of sustainability and social inclusion criteria required by Brazilian public policies and programs; integrating data from several different databases; including PRODES. The proposed consultancy aims at providing technical assistance to support the creation of comprehensive land cover change maps; especially focusing on three modules (TerraClass; Traceability; and Eligibility models); utilizing advanced semi-automatic classification methods for all Brazilian biomes up until 2020.  These maps will serve as a critical reference for the enforcement of the European Union’s stringent zero deforestation policies; which aim to halt the trade of commodities sourced from areas deforested post-2020.The selected firm will closely collaborate with The Brazilian National Institute for Space Research (INPE); globally renowned for its long-standing expertise in deforestation mapping.  In particular; the firm will support INPE's efforts in developing a definitive baseline deforestation map that not only draws from PRODES but also integrates discernible deforestation patterns up to December 2020; including those beyond the scope of the PRODES timeline.. The adopted method shall be based on unsupervised pixel clustering algorithms: Hierarchical Clustering Algorithms (HCA) and the Self- Organizing Maps (SOM). Preliminary findings have demonstrated that the unsupervised classification approach successfully identifies deforestation in previously undisturbed areas across all biomes; achieving an accuracy comparable to that of PRODES. The widespread deployment of these methods across ecoregions in all Brazilian biomes is anticipated to yield optimal and precise results; thereby informing public policies aimed at achieving a substantial reduction in deforestation and the preservation of native vegetation.

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