The CHOVE-CHUVA Earth observation platform to monitor socio-environmental dynamics in Mato Grosso, Brazil

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Authors: Damien Arvor, Julien Denize, Léa Rouxel, Vincent Dubreuil, Uelison Mateus Ribeiro, Beatriz Miky Funatsu, Julie Betbeder, Agnès Bégué, Vinicius de Freitas Silgueiro, Carlos A. da Silva, André Pereira Dias, Margareth Simões
+3 more R. P. D. Ferraz, Patrick Calvano Küchler, Arnaud Bellec
Cited by: 0
References: 81

Abstract

Remote sensing science is expected to produce spatio-temporal indicators to help societies to address major global challenges. In this regard, we have implemented the CHOVE-CHUVA web platform to monitor socio-environmental dynamics in the Brazilian Amazon state of Mato Grosso. Result of a long-term collaboration between research labs, local NGOs, and administrations, this Space for Climate Observatory initiative relies on two major pillars: (1) visualizing and computing spatio-temporal indices derived from Earth Observation data and (2) collecting citizen information as part of collaborative science. A major asset of the platform is to gather, visualize, and process data covering a wide range of themes such as land status, land use, climate, natural vegetation, agriculture, and hydrology. The collaborative information refers to land use types that are still unusual in Mato Grosso, i.e., forest restoration and low-carbon agricultural practices. The implementation of the platform was based on a French open source geospatial data infrastructure named PRODIGE. Prospects for enhancing the platform include integrating new thematic information, making better use of raw Earth Observation data, improving interactions with end-users to better capture their interpretation of socio-environmental dynamics, and improving the platform's efficiency to update data and process large study areas.

Fields of Study & Subjects

Remote Sensing in Agriculture Remote Sensing and Land Use Land Use and Ecosystem Services

Publication details

Journal / source
Scientific Reports
Volume
16
Issue
1
Pages
6497–6497
Publication date
28 January 2026
Language
EN