Periodic Reporting for period 1 - NATURE-FIRST (Forensic Intelligence and Remote Sensing Technologies for nature conservation)
Reporting period: 2022-09-01 to 2024-02-29
Knowledge gaps exist for many habitats and species (Biodiversity strategy). In response, the consortium ‘Forensic Intelligence and Remote Sensing Technologies for nature conservation’ (Nature FIRST) proposes a number of innovations for monitoring nature by combining ecology sciences and environmental forensics with environmental observations (satellite-based and on-site). This novel approach results in propositions and related services for: 1. Biodiversity monitoring in Natura 2000 areas, for both habitats and species; 2. Early warning systems for the prevention of Human-Wildlife Conflicts (HWC); 3. Management and compliance reporting.
Services include tools as well as methods, including software, checklists, instruction videos and more. The research objective is to move from a reactive approach and remediation of biodiversity loss to a preventive approach and a move from Human-Wildlife Conflict to Human-Wildlife Coexistence (HWCo). Existing technologies combined with new technologies and data science allow proactive nature conservation management. Semantic web technology is used to create knowledge-graphs that interlink and harmonise diverse data sources to provide new insights. Forensic data science and techniques are used to equip conservation managers with observation skills. These new observations are being combined with remote sensing data from wildlife cameras (camera-traps), drones and satellites, into automated risk and likelihood maps. Finally, predictive digital twins are being developed: two species related (bear and sturgeon) and one aimed at more integral biodiversity monitoring). Tools are co-developed with four field site partners, representing different habitat-species combinations in Europe. 1. Ancares-Courel in Spain (key species: bear, wolf), 2. Stara Planina Mountain (key species: bear, wolf) in Bulgaria, 3. Danube Delta (key species: sturgeon) in Romania, and 4. Maramures Transboundary Area (key species: bear, wolf, lynx, golden jackal) between Ukraine and Romania. A Policy Lab is to familiarise policy makers with the tools they can use for management as well as compliance assurance purposes.
Services include tools as well as methods, including software, checklists, instruction videos and more. The research objective is to move from a reactive approach and remediation of biodiversity loss to a preventive approach and a move from Human-Wildlife Conflict to Human-Wildlife Coexistence (HWCo). Existing technologies combined with new technologies and data science allow proactive nature conservation management. Semantic web technology is used to create knowledge-graphs that interlink and harmonise diverse data sources to provide new insights. Forensic data science and techniques are used to equip conservation managers with observation skills. These new observations are being combined with remote sensing data from wildlife cameras (camera-traps), drones and satellites, into automated risk and likelihood maps. Finally, predictive digital twins are being developed: two species related (bear and sturgeon) and one aimed at more integral biodiversity monitoring). Tools are co-developed with four field site partners, representing different habitat-species combinations in Europe. 1. Ancares-Courel in Spain (key species: bear, wolf), 2. Stara Planina Mountain (key species: bear, wolf) in Bulgaria, 3. Danube Delta (key species: sturgeon) in Romania, and 4. Maramures Transboundary Area (key species: bear, wolf, lynx, golden jackal) between Ukraine and Romania. A Policy Lab is to familiarise policy makers with the tools they can use for management as well as compliance assurance purposes.
3 scientific contributions have been published. One on Semantic, one on Digital Twins, and one elaborating on the use of EO in NF.
In the first 18 months of the project, we've developed and deployed the following technologies:
* adaptations and new functions in the Cluey Data Collector app to support data collection processes on all project sites, in their own languages.
* Focus data exploration and querying tool, for gaining a better understanding in the (quality and quantity of) data collection processes, and gaining instant insights in e.g. species distributions
* hotspot maps; riskmaps; patrol density maps
* observations reports; patrol reports
* automated generation of ecosystem basemaps
* semi-automated habitat classification model, integrated into the Sensing Clues platform
* Upload Service to allow users to include historic data and custom map layers
* digital twin (DT) of crane migrations in Europe (data-driven)
* Ecological Knowledge Model for knowledge-driven DTs
* agent based model on the sturgeon migration in the Danube Delta
* Monitoring and Evaluation ontology for relating field observations to SDGs
* Nature FIRST Knowledge Graph to enable taxonomic crossovers
In addition, we're working on the following technologies, which we intent to deploy and test in the 2nd half of 2024:
* camera-trap images classification, and the integration of the results in the Sensing Clues platform.
* monitoring changes in habitats, NDVI and other satellite-mage derived indexes, and species distributions
In the first 18 months of the project, we've developed and deployed the following technologies:
* adaptations and new functions in the Cluey Data Collector app to support data collection processes on all project sites, in their own languages.
* Focus data exploration and querying tool, for gaining a better understanding in the (quality and quantity of) data collection processes, and gaining instant insights in e.g. species distributions
* hotspot maps; riskmaps; patrol density maps
* observations reports; patrol reports
* automated generation of ecosystem basemaps
* semi-automated habitat classification model, integrated into the Sensing Clues platform
* Upload Service to allow users to include historic data and custom map layers
* digital twin (DT) of crane migrations in Europe (data-driven)
* Ecological Knowledge Model for knowledge-driven DTs
* agent based model on the sturgeon migration in the Danube Delta
* Monitoring and Evaluation ontology for relating field observations to SDGs
* Nature FIRST Knowledge Graph to enable taxonomic crossovers
In addition, we're working on the following technologies, which we intent to deploy and test in the 2nd half of 2024:
* camera-trap images classification, and the integration of the results in the Sensing Clues platform.
* monitoring changes in habitats, NDVI and other satellite-mage derived indexes, and species distributions
More timely, accurate, reliable and credible information to prioritise interventions to protect and preserve biodiversity: Through the implementation of the Cluey Data Collector app; automated creation of risk maps and ecosystem basemaps; semi-automated creation of habitat maps. In addition, our methods also brought to light gaps in knowledge and data related to the monitoring and protection of the sturgeon.
Easier access to data to monitor ecosystems, habitats and species: Through integration of the Habitat (3edata) and cam-trap (traptagger) classification technologies with the Sensing Clues platform, and the development of routines to automatically generate ecosystem basemaps.
Integrated knowledge graphs as a standardised tool in reporting: Implemented in the reporting engines (3) and maps (3).
User recommended training and capacity building programmes available for other organisations: Several beneficiaries were able to engage and motivate external (legal) stakeholders to join the forensics training in South Africa.
Uptake of the NATURE-FIRST approach, methodology and tools for Natura and other sites beyond the four involved in the project. The Cluey Data Collector training, which originally was given by Sensing Clues, has been taken over by WWF Ukraine to train their respective stakeholders.
Moreover:
* Sensing Clues was able to bring the enhanced and newly developed tools in their current client-base.
* 3edata knew to secure interest for demonstrations in Spain from the regional government (Galicia) up to the national government in Madrid (Ministry of Environment).
Easier access to data to monitor ecosystems, habitats and species: Through integration of the Habitat (3edata) and cam-trap (traptagger) classification technologies with the Sensing Clues platform, and the development of routines to automatically generate ecosystem basemaps.
Integrated knowledge graphs as a standardised tool in reporting: Implemented in the reporting engines (3) and maps (3).
User recommended training and capacity building programmes available for other organisations: Several beneficiaries were able to engage and motivate external (legal) stakeholders to join the forensics training in South Africa.
Uptake of the NATURE-FIRST approach, methodology and tools for Natura and other sites beyond the four involved in the project. The Cluey Data Collector training, which originally was given by Sensing Clues, has been taken over by WWF Ukraine to train their respective stakeholders.
Moreover:
* Sensing Clues was able to bring the enhanced and newly developed tools in their current client-base.
* 3edata knew to secure interest for demonstrations in Spain from the regional government (Galicia) up to the national government in Madrid (Ministry of Environment).