This building block is centered on the use of Convolutional Neural Networks (CNNs), including Siamese and Autoencoder architectures, to detect and identify individual jaguars based on unique features such as rosette patterns and morphology. These algorithms process camera-trap data efficiently, reducing the time required for analysis and providing critical insights for decision-making in conservation.

FFMA delivers real-time weather forecasts, disaster alerts, and ocean state information in regional languages, ensuring accessibility for diverse fishing communities across India.

Dynamic risk maps, built using GIS and geospatial analysis, identify high-risk areas and guide resource allocation. This tool can be used for urban planning, disaster risk reduction, or managing natural resources like water or land.

The system combines data from drones, satellites, camera traps, and geospatial tools to create a comprehensive monitoring framework. This approach can be adapted for other environmental challenges, such as flood monitoring, by integrating relevant data sources specific to those contexts.

It is the analysis that produces a map with the gradient of vulnerability to the potential impacts of mining tailings dam collapses for environmental risk management. It is the product of cross-referencing information on the impact of potential environmental degradation resulting from the collapse of mining dams and the sensitivity of biodiversity.

Process that defines the most suitable areas for offsetting environmental impacts based on analyses of the similarity of the composition of biodiversity and geodiversity sensitive to mining. This map assumes that the best place to invest efforts to offset the impacts of a mining activity will be those that share the largest number of conservation targets affected by the project. To this end, a spatially explicit hierarchical cluster analysis was performed, with the aid of the vegan and sf packages of the R statistical program, which indicates a gradient of similarity between impacted and protected areas, grouped into groups and clusters for offsetting.

This is a stage in the integration of information to generate a map that indicates the different levels of compatibility between the conservation of biodiversity and speleological heritage and mining, in search of solutions that help to avoid, mitigate and compensate for environmental impacts. This product is obtained by overlaying the Exposure to Impacts with the map of Sensitive Areas of Biodiversity and Speleological Heritage, which makes it possible to understand the gradient of compatibility between biodiversity conservation and mining, by pointing out: (i) which areas should be avoided and which should be prioritized for investments in mineral exploration; (ii) the environmental cost associated with each locational choice; and (iii) the type of mitigating measures to be adopted with greater intensity in each location. The method used to develop the tool can be easily replicated for other locations and even other threat vectors. 

Process of drawing up a gradient of biodiversity and speleological heritage to mining, which reflects increasing levels of vulnerability of conservation targets. We used Systematic Conservation Planning tools and concepts such as complementarity, representativeness, efficiency, irreplaceability, and vulnerability to generate the information behind the sensitivity of biodiversity. The biodiversity sensitivity map summarizes information on the components of biodiversity and geodiversity that are sensitive to the impacts of mineral exploration activities, such as their biological and ecological characteristics and the landscape factors that influence their distribution. In addition, a list of conservation targets is generated with the components of biodiversity and geodiversity that are eligible as conservation targets because they are sensitive to the chronic and acute impacts of mining. The targets could become even more vulnerable if preventive and impact mitigation measures were not adopted. Its realization depends on the systematization and construction of a wide variety of information on species, environmental variables and land use. It is a collaborative process that requires the participation of specialists and researchers to gather and validate the results.It is also the stage in which more information generated from the assessment of the risk of extinction of fauna species produced by ICMBio and Flora, under the responsibility of the Centro Nacional de Conservação da Flora (CNCFlora)  are incorporated into the tool. From this perspective, the process is a clear example of the application of scientific and participatory knowledge together with government management information around a common objective of environmental conservation and impact mitigation.

Process in which the actual chronic impacts of mining activity on the landscape, such as habitat loss, fragmentation and degradation, are estimated. This generates a gradient of exposure of biodiversity and speleological heritage and denotes increasing levels of severity of environmental damage. It involves liaising with sectoral bodies, systematizing environmental data and validating the results of the estimates generated with specialists. The methods used are those corroborated by the scientific community that can be replicated in any location and at different scales of the landscape.

The forestry sector is suffering from corruption and is limiting benefits for local and Indigenous communities. Our solution allows local communities to tackle forest illegalities and land rights violations and at the same time to secure their land rights and economic rights over forest resources by monitoring and protecting their territory, reinforcing sustainable development and autonomy.  Data collected through the tool also supports judicial or non-judicial cases when local and indigenous communities suffer human rights abuses.