RiskFP is an existing prototype of a recent fire prevention tool, developed for fire prevention support to forest managers, involving geo-information and spatial data analysis, supported by Climate-KIC program (OASIS-FIRE, OASIS+, RiskFP projects). In this project, we will demonstrate its usefulness to the insurance sector. For this purpose, we will further adapt it to the end-user needs, in particular by technical adaptations (storm assessment, new damageability models, seasonal forecasting capability), and then by defining a suited business model coupled to the insurance premium itself as a product, explicitly on concrete business cases.
RiskFP is an existing prototype of a recent fire prevention tool, developed for fire prevention support to forest managers, involving geo-information and spatial data analysis, supported by Climate-KIC program (OASIS-FIRE, OASIS+, RiskFP projects). In this project, we will demonstrate its usefulness to the insurance sector. For this purpose, we will further adapt it to the end-user needs, in particular by technical adaptations (storm assessment, new damageability models, seasonal forecasting capability), and then by defining a suited business model coupled to the insurance premium itself as a product, explicitly on concrete business cases.
Delivering Efficiency and Customer Satisfaction to Claims and Underwriting wi...Precisely
Weather data is available everywhere, but in many cases, insurers still rely on manual intervention and visual review to assess its effect on claims and locations.
How can carriers take advantage of more accurate and timely weather data while reducing the reliance on inefficient manual claims processes?
For those situations where a manual, visual review is necessary, visualization of Dynamic Weather data must be simple, intuitive, and deliver insight and context typically not available from reviewing the data itself. Done correctly, visualization will accelerate data democratization and analytics so that more accurate, data-driven insights are available to all users throughout an organization.
Watch this webinar on-demand to:
• See examples of Dynamic Weather data being combined and visualized, along with aerial imagery and spatial data assets, enhancing existing claims and underwriting processes
• Hear about ways to manage claim adjuster workload and improve claim assignment efficiency
• Manage drivetimes and prioritize claim resource allocations in real-time
IRJET- Identification of Urban Heat Island using Satellite ImageriesIRJET Journal
This document discusses using satellite imagery to identify urban heat islands in Trivandrum, Kerala, India. It analyzes Landsat satellite data from 1990 and 2005 to estimate land surface temperatures. Land use maps were created from the satellite data and showed increased built-up areas over time. Surface temperature maps found urban areas had higher temperatures than rural areas, establishing the presence of an urban heat island effect. A temperature profile of a selected urban-rural section in both years also showed urban areas with higher temperatures. While temperatures decreased from 1990 to 2005 possibly due to rainfall, urban areas still showed relatively higher temperatures, demonstrating the ability of satellite data to identify urban heat islands.
Fires on mobile plant are an ongoing safety issue. A review of fire incident data from 2014-2018 found that open cut coal mines accounted for 60% of fires, with underground metal mines accounting for 30%. Known risks include hot surfaces and fluid leaks, while known controls include temperature control below 200°C and use of fire-resistant fluids. Planned inspections of open cut coal mines found issues with fire suppression systems and opportunities to better consider historical fire risks in risk assessments. Overall, the data analysis and inspections aim to reduce mobile plant fires through improved risk management, maintenance, and equipment design.
This document summarizes the final meeting of the WP2 Slope Project in Brussels on February 1, 2017. It discusses the completion of deliverables, data collection from various partners, tree classification and detection methods, estimation of environmental parameters, combining data sets from different sources, logistics modeling, and analytics. The meeting highlights that the project has proven the concept of combining data from remote sensing, UAVs, and TLS to map up to 1,000 hectares in a single flight and provide useful data for both harvesting and long-term forest management - providing a solution beyond the state of the art.
This document analyzes ecosystem functioning and recovery after extreme drought years in 2018 and 2019 in Switzerland using data from two long-term eddy covariance measurement sites. It finds that atmospheric and soil dryness were more severe in the low-elevation mixed forest in 2018 but more severe in the high-elevation coniferous forest in 2019. Both forests showed reductions in net carbon uptake during drought, though the low-elevation forest was more impacted. The coniferous forest also demonstrated a stronger physiological response to drought and a larger increase in water use efficiency. Overall, the years 2018 and 2019 had similar effects on ecosystem carbon uptake.
Comparison of CESAR energy simulation results with real data and a private co...Andrea Silvagni
The Combined Energy Simulation And Retrofitting (CESA) tool developed by EMPA in Zurich simulates the energy demand of large clusters of buildings, with the scope to aid policy interventions and retrofitting strategies.
In this project we analyze how the accuracy and precision of the simulation results versus real data.
1. The document discusses investigating fire-climate interactions under a changing climate. It examines the relationship between fire weather index (FWI) and burned area as a measure of fire activity.
2. There is a global relationship found between FWI and burned area using regression analysis. Areas most sensitive to changes in FWI are boreal forests, parts of Australia, and the Mediterranean.
3. Future projections using climate models show increases in FWI globally under moderate and high emissions scenarios, posing threats to fire-prone regions. However, uncertainties exist regarding long-term vegetation responses.
RiskFP is an existing prototype of a recent fire prevention tool, developed for fire prevention support to forest managers, involving geo-information and spatial data analysis, supported by Climate-KIC program (OASIS-FIRE, OASIS+, RiskFP projects). In this project, we will demonstrate its usefulness to the insurance sector. For this purpose, we will further adapt it to the end-user needs, in particular by technical adaptations (storm assessment, new damageability models, seasonal forecasting capability), and then by defining a suited business model coupled to the insurance premium itself as a product, explicitly on concrete business cases.
Delivering Efficiency and Customer Satisfaction to Claims and Underwriting wi...Precisely
Weather data is available everywhere, but in many cases, insurers still rely on manual intervention and visual review to assess its effect on claims and locations.
How can carriers take advantage of more accurate and timely weather data while reducing the reliance on inefficient manual claims processes?
For those situations where a manual, visual review is necessary, visualization of Dynamic Weather data must be simple, intuitive, and deliver insight and context typically not available from reviewing the data itself. Done correctly, visualization will accelerate data democratization and analytics so that more accurate, data-driven insights are available to all users throughout an organization.
Watch this webinar on-demand to:
• See examples of Dynamic Weather data being combined and visualized, along with aerial imagery and spatial data assets, enhancing existing claims and underwriting processes
• Hear about ways to manage claim adjuster workload and improve claim assignment efficiency
• Manage drivetimes and prioritize claim resource allocations in real-time
IRJET- Identification of Urban Heat Island using Satellite ImageriesIRJET Journal
This document discusses using satellite imagery to identify urban heat islands in Trivandrum, Kerala, India. It analyzes Landsat satellite data from 1990 and 2005 to estimate land surface temperatures. Land use maps were created from the satellite data and showed increased built-up areas over time. Surface temperature maps found urban areas had higher temperatures than rural areas, establishing the presence of an urban heat island effect. A temperature profile of a selected urban-rural section in both years also showed urban areas with higher temperatures. While temperatures decreased from 1990 to 2005 possibly due to rainfall, urban areas still showed relatively higher temperatures, demonstrating the ability of satellite data to identify urban heat islands.
Fires on mobile plant are an ongoing safety issue. A review of fire incident data from 2014-2018 found that open cut coal mines accounted for 60% of fires, with underground metal mines accounting for 30%. Known risks include hot surfaces and fluid leaks, while known controls include temperature control below 200°C and use of fire-resistant fluids. Planned inspections of open cut coal mines found issues with fire suppression systems and opportunities to better consider historical fire risks in risk assessments. Overall, the data analysis and inspections aim to reduce mobile plant fires through improved risk management, maintenance, and equipment design.
This document summarizes the final meeting of the WP2 Slope Project in Brussels on February 1, 2017. It discusses the completion of deliverables, data collection from various partners, tree classification and detection methods, estimation of environmental parameters, combining data sets from different sources, logistics modeling, and analytics. The meeting highlights that the project has proven the concept of combining data from remote sensing, UAVs, and TLS to map up to 1,000 hectares in a single flight and provide useful data for both harvesting and long-term forest management - providing a solution beyond the state of the art.
This document analyzes ecosystem functioning and recovery after extreme drought years in 2018 and 2019 in Switzerland using data from two long-term eddy covariance measurement sites. It finds that atmospheric and soil dryness were more severe in the low-elevation mixed forest in 2018 but more severe in the high-elevation coniferous forest in 2019. Both forests showed reductions in net carbon uptake during drought, though the low-elevation forest was more impacted. The coniferous forest also demonstrated a stronger physiological response to drought and a larger increase in water use efficiency. Overall, the years 2018 and 2019 had similar effects on ecosystem carbon uptake.
Comparison of CESAR energy simulation results with real data and a private co...Andrea Silvagni
The Combined Energy Simulation And Retrofitting (CESA) tool developed by EMPA in Zurich simulates the energy demand of large clusters of buildings, with the scope to aid policy interventions and retrofitting strategies.
In this project we analyze how the accuracy and precision of the simulation results versus real data.
1. The document discusses investigating fire-climate interactions under a changing climate. It examines the relationship between fire weather index (FWI) and burned area as a measure of fire activity.
2. There is a global relationship found between FWI and burned area using regression analysis. Areas most sensitive to changes in FWI are boreal forests, parts of Australia, and the Mediterranean.
3. Future projections using climate models show increases in FWI globally under moderate and high emissions scenarios, posing threats to fire-prone regions. However, uncertainties exist regarding long-term vegetation responses.
This document discusses progress on Task 2.1 of Project SLOPE. It outlines the participants in the task and their roles in collecting and analyzing forest information using remote sensing. Work completed so far includes acquiring satellite imagery of test sites, conducting trials combining aerial imagery and laser scanning in Ireland, and identifying additional test sites in Trento and Austria. The next steps are to get permission to fly in Italy, test equipment at new sites, finalize the methodology, and disseminate results.
Fire Proximity Awareness Monitoring with FMESafe Software
This document describes the evolution of Manitoba Hydro's fire proximity awareness system using geospatial data and FME. It summarizes how fire data was initially pulled from shapefiles then points to improve legibility. Weather and infrastructure data were also incorporated. FME was used to process the data, calculate proximity of fires to infrastructure, and track crew locations over time in response to fires. The system provides near real-time awareness of fire and weather conditions to help monitor risks to Manitoba Hydro assets and operations.
District heating potential in the Italian NECP: assessment through a new resi...IEA-ETSAP
District heating potential in the Italian NECP: assessment through a new residential model in TIMES-RSE
Ms. Corine Nsangwe Businge, RSE - Ricerca sul Sistema Energetico
The document describes requirements for building and delivering an integrated carbon information system prototype. The system will measure and monitor carbon stocks and benefits of projects to assess impacts, promote best practices, and enable policy analysis. It will integrate measurement methods including ground sampling, remote sensing, and modeling to quantify carbon sequestration. The system aims to apply emerging technologies to accurately measure land use changes and provide environmental and carbon risk information for projects.
Presentation at the Earth Observation Symposium of the German Aerospace Center (DLR) in Cologne, 25-06-2018.
The slides give an overview of the firemaps.net platform, and current R&D activities carried out on fire emissions and fire behaviour.
This document describes a research project that aims to develop a web-based system to automatically calculate and visualize large-scale energy performance maps of residential buildings in a city. The system would use existing data sources, an extended version of the TABULA/EPISCOPE project for calculating building energy parameters, and CityGML and WebGL standards for data storage and visualization. Preliminary results are presented for a service that assesses building energy performance at scale and visualizes the results in an intuitive 3D interface to help citizens, governments, and organizations analyze building energy efficiency across a city.
Project update on Enhancing Flexibility in TIMES: Introducing Ancillary Servi...IEA-ETSAP
This document discusses introducing ancillary services markets in the TIMES energy system model. It aims to capture the impacts of short-term variability from renewable energy on power system flexibility needs. The researchers are developing a mathematical specification of ancillary services reserves in TIMES and revising it based on real-world applications. They are also reviewing the design, implementation, testing and documentation of this extension to allow TIMES to endogenously model reserve capacity requirements and provision. A simple power system is demonstrated for testing the ancillary services market modeling capabilities.
Energy and environmental impacts of biomass use in the residential Sector: a ...IEA-ETSAP
The document analyzes the energy and environmental impacts of increased biomass use in residential heating in Italy through 2030 under various policy scenarios. It finds that:
1) Under a reference scenario that meets 2020 targets, biomass consumption in the residential sector increases to around 19 Mtoe by 2030, accounting for over 60% of fine particulate emissions.
2) A constant biomass scenario that limits consumption to 2014 levels still meets emissions reductions but achieves a slightly different energy mix.
3) A deeper decarbonization scenario reduces emissions 36% by 2030 primarily through reductions in transport, buildings, and industry, with renewables reaching 28% of total energy supply.
Addressing demand uncertainty in long-term planning modelsIEA-ETSAP
This document discusses addressing demand uncertainty in long-term energy planning models. It compares deterministic models using planning reserve margins to stochastic models that capture expected operational costs under different demand scenarios. Capturing multiple demand scenarios changes the optimal capacity mix by accounting for the expected costs of meeting variable demand. Stochastic models also endogenously assess renewable energy capacity credits over multiple time periods rather than fixing credits based on a single peak period. Accounting properly for demand uncertainty and renewable intermittency provides more robust optimal capacity planning outcomes.
Servizio Gestione Flussi Dati Energetici EdificiSUNSHINEProject
The document describes a Sensor Data Management service that was proposed as part of the Sunshine project. The service ingests energy consumption, indoor temperature, and weather data from various sources and stores it in a centralized database. It then visualizes the correlations between consumption and weather variables to help energy managers analyze building energy behavior. The service was demonstrated by analyzing consumption data from two pilot buildings in Ferrara, Italy.
This document summarizes work from Project SLOPE on collecting and analyzing forest information using remote sensing techniques. It describes using a UAV to acquire RGB and multispectral imagery of a test site in Annaberg, Austria. Terrestrial laser scanning was also used to generate digital terrain models, detect individual trees, and analyze tree characteristics like volume estimations. Field measurements were taken and compared to remote sensing data. The integration of remote sensing with field data helped improve forest inventory and management techniques.
S.2.g Meter and Sensor Data Management ServiceSUNSHINEProject
During the development of the SUNSHINE platform for building energy management, a Sensor Data Management Service was implemented to collect, store, and analyze various sensor data from pilot buildings. The service extends beyond traditional meter data to also manage indoor temperature, weather, and other sensor readings. It ingests data from different sources via FTP, Green Button, and WFS protocols and stores it uniformly in a PostgreSQL/PostGIS database following the Sensor Observation Service standard. Analysis of energy use data from two schools in Ferrara, Italy identified weekly and seasonal consumption patterns related to outdoor temperature variations.
AN XGBOOST-BASED REGRESSION MODEL FOR WILDFIRE IMPACT PREDICTIONIRJET Journal
This document presents a machine learning model for predicting wildfire risk and impact using meteorological data. It proposes an XGBoost regression model that takes temperature, humidity, wind speed, and previous moisture codes as input to predict the area impacted by wildfires. The system calculates moisture codes like FFMC, DMC, and DC from weather data, which are then used along with indices like ISI and BUI by the risk predictor (logistic regression model) to calculate fire probability and the impact predictor (XGBoost model) to estimate the affected area. It collects and preprocesses historical wildfire datasets to train the models. The trained models along with a user interface could help forest departments take preventive actions based on predicted risk and impact
IRJET- A Review of Fire Detection TechniquesIRJET Journal
This document reviews different techniques for fire detection. It discusses monitoring through observation towers, satellite-based monitoring, and systems using digital cameras and wireless sensor networks. Observation towers rely on human monitoring but have limitations. Satellite detection can find fires from space but provides intermittent coverage. Systems using cameras and sensors can automatically detect and verify fires with images. Wireless sensor networks are considered the best solution as sensor nodes can continuously monitor an area for temperature, smoke, and other indicators to detect fires early.
Development and Applications of Fire Danger Rating Systems in Southeast AsiaCIFOR-ICRAF
This document discusses the development and application of fire danger rating systems (FDRS) in Southeast Asia. It describes the Canadian Forest Fire Danger Rating System (CFFDRS) and how it was adapted for use in Southeast Asia through a project from 1999-2004. The project involved technical adaptation of the FDRS including fuel modeling, calibration of indices, and mapping of fuel types for the region. It also describes how the FDRS can support early warning of fire risk, monitoring of fire danger levels, and mitigation activities through interpretation of the fire weather index. The goal is to integrate FDRS products with fire suppression planning to allow more anticipatory mobilization of resources and improved fire management.
Using Data Integration to Deliver Intelligence to Anyone, AnywhereSafe Software
Data integration makes it possible to deliver intelligence and keep decision makers, first responders, and civilians informed. For over 20 years, FME has been trusted by federal governments to move data from nearly any source to the target destination, while saving time and budget resources.
With FME, federal governments can deliver open data, improve emergency & disaster response, enhance land management, turn public safety and defense into actionable results, and integrate & deliver location intelligence.
Building Climate Resilience: Translating Climate Data into Risk Assessments Safe Software
Climate change affects us all. It is an urgent issue that requires practical solutions to mitigate its impacts. Data is at the center of understanding this challenge. In this informative webinar, we will explore how data can be leveraged to translate climate change projections into tangible hazard and risk assessments at the local level.
The webinar will cover a range of topics: including flood, fire, heat, drought, population health, and critical infrastructure, among others. We will also highlight our partner and customer experiences in this field and present key results from our participation in recent OGC pilots on Climate Resilience and Disaster Response. We will also be joined by special guests sharing their experience in the AgriTech sector, where gathering metrics and data from sensors is helping to reduce the demand from farming on precious resources like water for irrigation.
Through live demos, attendees will gain practical knowledge in accessing climate services from USGS & Environment Canada and how to convert climate model NetCDF outputs into more GIS-friendly formats like geodatabase & GeoJSON.
Finally, we will address the significant gaps and challenges that remain in assessing climate-related hazards and risks, and explore how FME can play a critical role in addressing these gaps. Join us for this important discussion on how you can use FME to build resilience and mitigate the impacts of climate change.
This document summarizes the activities and effectiveness of the National Data Centre in Comoros. It discusses how the NDC was established in 2012 and the benefits it provides, including access to PTS data and knowledge exchange with the IDC. It describes how the NDC used data and knowledge from the IDC to analyze seismic events in Comoros, including converting local data to CSS format and assessing regional events from January to March 2014. The document also discusses the NDC's participation in the 2013 Nuclear Test Ban Treaty Organization Proficiency Test, where they analyzed seismic events in Europe with support from the German NDC. It concludes that PTS data and products are increasingly useful for the NDC's work, and suggests ways to
Refinement on Fire Danger Rating System (FDRS) to Reduce Peat Fires in MalaysiaGlobalEnvironmentCentre
This document discusses the refinement of Malaysia's Fire Danger Rating System (FDRS) to better monitor drought conditions, predict fires, and issue early warnings for peatland fires. It provides background on FDRS development in Malaysia, details a pilot project applying refined FDRS indices to a peat forest region, and outlines current and planned applications and products like increased weather stations, online mapping tools, and forecasting capabilities. The goal is to utilize FDRS as an early warning system to help environmental authorities curb land and peat fires causing air quality issues.
Integrated Fire Management, prescribed burning, and mitigation potentials und...CIFOR-ICRAF
Presented by Lara Steil (Brazilian National Center for prevention and fighting wildfire, Brazil) at webinar: "Wildfire management, emissions and NDCs in the dry tropics", on 25 November 2020
This document discusses progress on Task 2.1 of Project SLOPE. It outlines the participants in the task and their roles in collecting and analyzing forest information using remote sensing. Work completed so far includes acquiring satellite imagery of test sites, conducting trials combining aerial imagery and laser scanning in Ireland, and identifying additional test sites in Trento and Austria. The next steps are to get permission to fly in Italy, test equipment at new sites, finalize the methodology, and disseminate results.
Fire Proximity Awareness Monitoring with FMESafe Software
This document describes the evolution of Manitoba Hydro's fire proximity awareness system using geospatial data and FME. It summarizes how fire data was initially pulled from shapefiles then points to improve legibility. Weather and infrastructure data were also incorporated. FME was used to process the data, calculate proximity of fires to infrastructure, and track crew locations over time in response to fires. The system provides near real-time awareness of fire and weather conditions to help monitor risks to Manitoba Hydro assets and operations.
District heating potential in the Italian NECP: assessment through a new resi...IEA-ETSAP
District heating potential in the Italian NECP: assessment through a new residential model in TIMES-RSE
Ms. Corine Nsangwe Businge, RSE - Ricerca sul Sistema Energetico
The document describes requirements for building and delivering an integrated carbon information system prototype. The system will measure and monitor carbon stocks and benefits of projects to assess impacts, promote best practices, and enable policy analysis. It will integrate measurement methods including ground sampling, remote sensing, and modeling to quantify carbon sequestration. The system aims to apply emerging technologies to accurately measure land use changes and provide environmental and carbon risk information for projects.
Presentation at the Earth Observation Symposium of the German Aerospace Center (DLR) in Cologne, 25-06-2018.
The slides give an overview of the firemaps.net platform, and current R&D activities carried out on fire emissions and fire behaviour.
This document describes a research project that aims to develop a web-based system to automatically calculate and visualize large-scale energy performance maps of residential buildings in a city. The system would use existing data sources, an extended version of the TABULA/EPISCOPE project for calculating building energy parameters, and CityGML and WebGL standards for data storage and visualization. Preliminary results are presented for a service that assesses building energy performance at scale and visualizes the results in an intuitive 3D interface to help citizens, governments, and organizations analyze building energy efficiency across a city.
Project update on Enhancing Flexibility in TIMES: Introducing Ancillary Servi...IEA-ETSAP
This document discusses introducing ancillary services markets in the TIMES energy system model. It aims to capture the impacts of short-term variability from renewable energy on power system flexibility needs. The researchers are developing a mathematical specification of ancillary services reserves in TIMES and revising it based on real-world applications. They are also reviewing the design, implementation, testing and documentation of this extension to allow TIMES to endogenously model reserve capacity requirements and provision. A simple power system is demonstrated for testing the ancillary services market modeling capabilities.
Energy and environmental impacts of biomass use in the residential Sector: a ...IEA-ETSAP
The document analyzes the energy and environmental impacts of increased biomass use in residential heating in Italy through 2030 under various policy scenarios. It finds that:
1) Under a reference scenario that meets 2020 targets, biomass consumption in the residential sector increases to around 19 Mtoe by 2030, accounting for over 60% of fine particulate emissions.
2) A constant biomass scenario that limits consumption to 2014 levels still meets emissions reductions but achieves a slightly different energy mix.
3) A deeper decarbonization scenario reduces emissions 36% by 2030 primarily through reductions in transport, buildings, and industry, with renewables reaching 28% of total energy supply.
Addressing demand uncertainty in long-term planning modelsIEA-ETSAP
This document discusses addressing demand uncertainty in long-term energy planning models. It compares deterministic models using planning reserve margins to stochastic models that capture expected operational costs under different demand scenarios. Capturing multiple demand scenarios changes the optimal capacity mix by accounting for the expected costs of meeting variable demand. Stochastic models also endogenously assess renewable energy capacity credits over multiple time periods rather than fixing credits based on a single peak period. Accounting properly for demand uncertainty and renewable intermittency provides more robust optimal capacity planning outcomes.
Servizio Gestione Flussi Dati Energetici EdificiSUNSHINEProject
The document describes a Sensor Data Management service that was proposed as part of the Sunshine project. The service ingests energy consumption, indoor temperature, and weather data from various sources and stores it in a centralized database. It then visualizes the correlations between consumption and weather variables to help energy managers analyze building energy behavior. The service was demonstrated by analyzing consumption data from two pilot buildings in Ferrara, Italy.
This document summarizes work from Project SLOPE on collecting and analyzing forest information using remote sensing techniques. It describes using a UAV to acquire RGB and multispectral imagery of a test site in Annaberg, Austria. Terrestrial laser scanning was also used to generate digital terrain models, detect individual trees, and analyze tree characteristics like volume estimations. Field measurements were taken and compared to remote sensing data. The integration of remote sensing with field data helped improve forest inventory and management techniques.
S.2.g Meter and Sensor Data Management ServiceSUNSHINEProject
During the development of the SUNSHINE platform for building energy management, a Sensor Data Management Service was implemented to collect, store, and analyze various sensor data from pilot buildings. The service extends beyond traditional meter data to also manage indoor temperature, weather, and other sensor readings. It ingests data from different sources via FTP, Green Button, and WFS protocols and stores it uniformly in a PostgreSQL/PostGIS database following the Sensor Observation Service standard. Analysis of energy use data from two schools in Ferrara, Italy identified weekly and seasonal consumption patterns related to outdoor temperature variations.
AN XGBOOST-BASED REGRESSION MODEL FOR WILDFIRE IMPACT PREDICTIONIRJET Journal
This document presents a machine learning model for predicting wildfire risk and impact using meteorological data. It proposes an XGBoost regression model that takes temperature, humidity, wind speed, and previous moisture codes as input to predict the area impacted by wildfires. The system calculates moisture codes like FFMC, DMC, and DC from weather data, which are then used along with indices like ISI and BUI by the risk predictor (logistic regression model) to calculate fire probability and the impact predictor (XGBoost model) to estimate the affected area. It collects and preprocesses historical wildfire datasets to train the models. The trained models along with a user interface could help forest departments take preventive actions based on predicted risk and impact
IRJET- A Review of Fire Detection TechniquesIRJET Journal
This document reviews different techniques for fire detection. It discusses monitoring through observation towers, satellite-based monitoring, and systems using digital cameras and wireless sensor networks. Observation towers rely on human monitoring but have limitations. Satellite detection can find fires from space but provides intermittent coverage. Systems using cameras and sensors can automatically detect and verify fires with images. Wireless sensor networks are considered the best solution as sensor nodes can continuously monitor an area for temperature, smoke, and other indicators to detect fires early.
Development and Applications of Fire Danger Rating Systems in Southeast AsiaCIFOR-ICRAF
This document discusses the development and application of fire danger rating systems (FDRS) in Southeast Asia. It describes the Canadian Forest Fire Danger Rating System (CFFDRS) and how it was adapted for use in Southeast Asia through a project from 1999-2004. The project involved technical adaptation of the FDRS including fuel modeling, calibration of indices, and mapping of fuel types for the region. It also describes how the FDRS can support early warning of fire risk, monitoring of fire danger levels, and mitigation activities through interpretation of the fire weather index. The goal is to integrate FDRS products with fire suppression planning to allow more anticipatory mobilization of resources and improved fire management.
Using Data Integration to Deliver Intelligence to Anyone, AnywhereSafe Software
Data integration makes it possible to deliver intelligence and keep decision makers, first responders, and civilians informed. For over 20 years, FME has been trusted by federal governments to move data from nearly any source to the target destination, while saving time and budget resources.
With FME, federal governments can deliver open data, improve emergency & disaster response, enhance land management, turn public safety and defense into actionable results, and integrate & deliver location intelligence.
Building Climate Resilience: Translating Climate Data into Risk Assessments Safe Software
Climate change affects us all. It is an urgent issue that requires practical solutions to mitigate its impacts. Data is at the center of understanding this challenge. In this informative webinar, we will explore how data can be leveraged to translate climate change projections into tangible hazard and risk assessments at the local level.
The webinar will cover a range of topics: including flood, fire, heat, drought, population health, and critical infrastructure, among others. We will also highlight our partner and customer experiences in this field and present key results from our participation in recent OGC pilots on Climate Resilience and Disaster Response. We will also be joined by special guests sharing their experience in the AgriTech sector, where gathering metrics and data from sensors is helping to reduce the demand from farming on precious resources like water for irrigation.
Through live demos, attendees will gain practical knowledge in accessing climate services from USGS & Environment Canada and how to convert climate model NetCDF outputs into more GIS-friendly formats like geodatabase & GeoJSON.
Finally, we will address the significant gaps and challenges that remain in assessing climate-related hazards and risks, and explore how FME can play a critical role in addressing these gaps. Join us for this important discussion on how you can use FME to build resilience and mitigate the impacts of climate change.
This document summarizes the activities and effectiveness of the National Data Centre in Comoros. It discusses how the NDC was established in 2012 and the benefits it provides, including access to PTS data and knowledge exchange with the IDC. It describes how the NDC used data and knowledge from the IDC to analyze seismic events in Comoros, including converting local data to CSS format and assessing regional events from January to March 2014. The document also discusses the NDC's participation in the 2013 Nuclear Test Ban Treaty Organization Proficiency Test, where they analyzed seismic events in Europe with support from the German NDC. It concludes that PTS data and products are increasingly useful for the NDC's work, and suggests ways to
Refinement on Fire Danger Rating System (FDRS) to Reduce Peat Fires in MalaysiaGlobalEnvironmentCentre
This document discusses the refinement of Malaysia's Fire Danger Rating System (FDRS) to better monitor drought conditions, predict fires, and issue early warnings for peatland fires. It provides background on FDRS development in Malaysia, details a pilot project applying refined FDRS indices to a peat forest region, and outlines current and planned applications and products like increased weather stations, online mapping tools, and forecasting capabilities. The goal is to utilize FDRS as an early warning system to help environmental authorities curb land and peat fires causing air quality issues.
Integrated Fire Management, prescribed burning, and mitigation potentials und...CIFOR-ICRAF
Presented by Lara Steil (Brazilian National Center for prevention and fighting wildfire, Brazil) at webinar: "Wildfire management, emissions and NDCs in the dry tropics", on 25 November 2020
"Emergency plan to secure winter: what are the measures set up by RTE?" by Sophie Diakhate, Ingénieure Génie électrique, Consultante en énergie et utilities at Yélé
Abstract: The french electric system is currently going through an exceptional crisis, threatening the electric supplies for this winter, and potentially the next ones. As the guarantor of the balance between supply and demand, RTE must assume the security of supply security in France. They set up an emergency plan to secure winters. Yélé helps RTE to carry on that plan.
We are going to see what are the primary measures proposed by RTE for the winter 2022-2023, and the options for individuals and the industry to reduce the risks of network load shedding.
Modelling of wireless sensor networks for detection land and forest fire hotspotTELKOMNIKA JOURNAL
Indonesia located in South East Asia countries with tropical region, forest fires in Indonesia is
one of big issue and disaster because it happens in almost of every year, this is because of some of region
consist of peat land that high risk for fire especially in dry season. Riau Province is one of region that
regularly incident of forest fire with affected the length and breadth of Indonesia. Propose development of
Wireless Sensor Networks (WSNs) for detection of land and forest fire hotspot in Indonesia as well as one
of the main consents in this research, case location in Riau province is at one of the regions that high risk
forest fire in dry season. WSNs technology used for ground sensor system to collect environmental data.
Data training for fire hotspot detection is done in data center to determine and conclude of fire hotspot then
potential to become big fire. The deployment of sensors located at several locations that has potential for
fire incident, especially as data shown in previous case and forecast location with potential fire happen.
Mathematical analysis is used in this case for modelling number of sensors required to deploy and the size
of forest area. The design and development of WSNs give high impact and feasibility to overcome current
issues of forest fire and fire hotspot detection in Indonesia. The development of this system used WSNs
highly applicable for early warning and alert system for fire hotspot detection.
This document discusses fires in Portugal and efforts to predict burnt area from available data to optimize firefighting resources. It notes that while burnt area is a metric, emissions generated by fires that affect air quality are a bigger problem. The document explores using weather data, GPS data, and fire timestamps from 2013 onward to predict burnt area, noting the data needs cleaning. It shows a model accurately predicted 95% of actual burnt area and that some districts have mostly intentional fires while others are mainly due to negligence, requiring better prevention. The full research is available on GitHub.
How climate data can help address the climate challengeEsri UK
Climate change has already altered the weather we experience and the magnitude of impacts from extreme temperatures and rainfall. These impacts manifest locally and can cause human causalities and damage to infrastructure and natural systems. In future, some further climate change is now inevitable, but the rate and magnitude of change will depend on global greenhouse gas emissions. New data and tools to use the data are available to help plot a path through the climate and weather challenges, enabling organisations at all scales to adapt to the changing conditions.
6.1.3 Methodologies for climate rational for adaptation NAP Events
1) Understanding long-term climate trends through the use of climate indices is important for robust decision-making and adaptation planning. Climate indices can help distinguish climate change signals from natural variability.
2) Sector-specific climate indices that are relevant to agriculture, health, energy and other sectors can demonstrate links between climate and impacts and support adaptation planning and funding proposals.
3) Resources like ClimPACT2 software, ClimDEX data, and Expert Team on Sector-specific Climate Indices workshops help countries access and use climate indices for their adaptation needs.
This document discusses using geostationary satellites to predict aviation weather hazards like downbursts and fog. It describes how satellite measurements can be used to calculate indices like the Microburst Wind Potential Index (MWPI) to forecast downburst wind speeds up to 3 hours in advance. Case studies of downbursts in Southern California in 2014 and fog in Salt Lake City in 2015 are presented, showing how satellite data matched observations. The conclusions emphasize that MWPI has conditional skill in forecasting thunderstorm winds and that fog can be detected using infrared channel brightness temperature differences from GOES satellites.
Wind_resource_assessment_using_the_WAsP_software_DTU_Wind_Energy_E_0174_.pdfMohamed Salah
This document provides an introduction to wind resource assessment using the WAsP software. It describes how wind resource assessment is used to estimate the wind resource potential at a site based on meteorological measurements and numerical modelling. The WAsP software implements a wind atlas methodology using measured wind data to generate a generalised wind climate, which can then be applied to a site to produce a predicted wind climate and estimate annual energy production considering wake losses from the wind farm layout. Validation, uncertainties and site conditions are also discussed.
The document provides an overview of the 2012/13 fire season briefing. It summarizes the 2011/12 fire season, outlines the key themes and seasonal outlook to be discussed in scenario workshops. It also reviews command and control arrangements, safety procedures, warning systems, resources and additional information sources for the upcoming fire season.
SteadyMet provides short-term solar power production forecasts using numerical weather prediction models and an expert system combining artificial intelligence, statistical, and physical models. Forecasts are produced from 0 to 10 days ahead at time intervals from one minute and are updated twice daily. The service forecasts production at various geographical levels from country to individual sites taking local weather peculiarities into account through its self-learning module.
The document summarizes climate change work from the Met Office including the development of climate services to meet adaptation needs. It provides examples of climate services like the Virtual Met Mast tool for wind energy planning and reports on climate modeling projections showing continued warming and changes in precipitation patterns. It also discusses the Met Office's contributions to understanding the recent pause in warming, including the potential role of ocean heat uptake.
This document describes the development of a GIS service using CloudEO Platform data and tools to visualize areas in El Salvador that have a higher susceptibility to landslides based on slope, rainfall data, and historical landslide events, with the goal of providing early warning systems that are accessible via mobile, desktop, and web applications. The process involves collecting and interpolating rainfall observations, reclassifying the data according to warning levels, and intersecting it with pre-generated slope data to identify at-risk areas. Screenshots from the service show maps highlighting susceptible regions based on real-time rainfall observations.
Since 2013, the European Urban Resilience Forum (https://urbanresilienceforum.eu) has offered a unique platform where city representatives and stakeholders from various local and regional institutions come together to exchange and discuss strategies and actions to adapt to climate change and build urban resilience. The slides have been in the session “Connecting up the dots between science, municipalities, insurance and climate risk assessment” organised byInsurance2020/OasisHub project
Since 2013, the European Urban Resilience Forum (https://urbanresilienceforum.eu) has offered a unique platform where city representatives and stakeholders from various local and regional institutions come together to exchange and discuss strategies and actions to adapt to climate change and build urban resilience. The slides have been in the session “Connecting up the dots between science, municipalities, insurance and climate risk assessment” organised byInsurance2020/OasisHub project
Since 2013, the European Urban Resilience Forum (https://urbanresilienceforum.eu) has offered a unique platform where city representatives and stakeholders from various local and regional institutions come together to exchange and discuss strategies and actions to adapt to climate change and build urban resilience. The slides have been in the session “Connecting up the dots between science, municipalities, insurance and climate risk assessment” organised byInsurance2020/OasisHub project
Oasis Loss modelling framework has built up over the last 5 years a group of 43 (Re)Insurance companies and over 100 associate partners. There has been a focus on data and model interoperability and the needs of model developers to encourage a wider supply of insight from academia. This has all focused on the specific needs of one of the largest users of climate and risk data, the Insurance industry.
Oasis Loss modelling framework has built up over the last 5 years a group of 43 (Re)Insurance companies and over 100 associate partners. There has been a focus on data and model interoperability and the needs of model developers to encourage a wider supply of insight from academia. This has all focused on the specific needs of one of the largest users of climate and risk data, the Insurance industry.
The document provides an update on the progress of various tasks under the H2020_Insurance Project Meeting. It summarizes the status of technical development of the eMarket portal and its integration with other tools. It discusses the acquisition of partner/providers and publishing of datasets and models on the portal. It outlines the ongoing go-to-market and sales and marketing program. Finally, it notes interactions with stakeholders, data management under the project, and planned communications activities.
This document discusses work package 2.3.1 which aims to assess climate risk for vulnerable patient groups in Berlin and Potsdam from heat stress and air pollution and investigate if climate-adapted hospitals can reduce impacts. The work will create models for each district to estimate future healthcare burdens and evaluate adaptation strategies. Next steps include defining the modeling strategy, creating datasets for each district, and mapping hospital admissions. Analysis shows radiant cooling systems in patient rooms provide clinical benefits. Stakeholders were identified and services proposed including a risk database and operational forecasting system.
About 30 million people work in the agricultural sector in Tanzania, and as irrigation schemes are fairly underdeveloped, most of them are highly vulnerable to weather-related yield losses. This vulnerability might accelerate under climate change conditions, and the financial uncertainty of the farmers inhibits implementation of improved and resilient farming systems, endangering food security. Our methodology, tested at the plot, county and national scale, has the potential to hugely support agricultural development and can be a means to adapt to climate variability and change.
The Future Danube Model is a multi-hazard and risk model suite for the Danube region which has been developed in the OASIS project. The model comprises modules for estimating potential perils from heavy precipitation, heatwaves, floods, droughts, and damage risk considering hydro-climatic extremes under current and climate change conditions.
Building on existing hospitalization and health insurance data and experiences gained in previous projects, we will quantify the sensitivity of vulnerable population (e.g. chronic sick patients with a cardiopulmonary disease) to climate variability (heat stress, often amplified by air contamination). The product is the “health damage function”, linking climate (extremes) to impacts on population (morbidity and mortality) and costs (hospitalization, medication).This “health damage function” will allow the public and private health insurances to assess the impacts (hospital admissions, numbers of days in hospitals, health care measures for those not in hospitals, deaths, etc.) depending upon a particular climate event.
The Future Danube Model is a multi-hazard and risk model suite for the Danube region which has been developed in the OASIS project. The model comprises modules for estimating potential perils from heavy precipitation, heatwaves, floods, droughts, and damage risk considering hydro-climatic extremes under current and climate change conditions.
The Future Danube Model is a multi-hazard and risk model suite for the Danube region which has been developed in the OASIS project. The model comprises modules for estimating potential perils from heavy precipitation, heatwaves, floods, droughts, and damage risk considering hydro-climatic extremes under current and climate change conditions.
The document describes the Future Danube Model, which is a model chain used to simulate riverine and pluvial flood hazards and risks in the Danube basin under current and future climate conditions. The model chain includes regional climate models, a weather generator, hydrological and hydraulic models, and probabilistic flood loss models. It is used to generate flood hazard and risk maps, estimate how flood frequencies may change in the future, and calculate potential economic losses from flooding. The results are intended to help urban planners and the insurance industry assess and adapt to flood risks.
The document describes methods used in the Future Danube Model to assess climate change impacts on current and future flood risk in the Danube River basin. Stochastic weather generators were used to simulate thousands of years of daily weather data based on outputs from regional climate models under historical and future climate scenarios. This data was fed through hydrological and hydraulic models to generate flood hazard maps and assess changes in flood risk over time. The model chain and results were made available on the OASIS Loss Modeling Framework to provide risk information to the insurance sector.
This document summarizes a presentation on the Horizon2020 Insurance project. It discusses using climate science to help the insurance sector. The project is demonstrating adding value from climate services in the Danube basin by modeling floods. It presents results on changing flood frequency from climate change. It also discusses modeling pluvial flooding in cities and supporting infrastructure investments. Other areas discussed include modeling tropical cyclones, forest fires, health impacts, and crop insurance solutions to enhance food security in Africa. The goal is to show how climate data and models can provide robust risk information to help insurers and policymakers.
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2. 2
A Presentation by OASIS | Horizon2020 Insurance
www.h2020insurance.oasishub.co
Introduction
Objectives and contributors
The Forest Demonstration aims to further develop the RISKFP tool in
order to demonstrate the value of climate services for the insurance
sector for fire and storm risks.
New services have been developed to provide risk representations in
phase with the needs expressed in the (re)insurance sector:
- The main service consists in the generation of “fire realistic disaster
scenarios” that can be used to complete information from historical
data and to compute probable maximum loss (PML).
- The other services provide general information which aims at raising
knowledge on the risk level in a specific region. These new risk
representations are:
• Rapid response risk mapping;
• Large databases of ‘critical landscape pattern’ (days of extreme
weather conditions) for fire and storm risks, projectable in next
season and in the long-term future;
• Risk reduction at the junction of forest and cities;
• Impact calculation that is based on damage function definition
(CO2, biomass burnt, financial loss) that used RDS as input.
Forest Demonstrator components
Technical
contributors
On-demand Realistic Disaster Scenarios (RDS) generation
Tecnosylva with
weather inuuts
from ARIA
On-demand local fire risk mapping (RRM)
Tecnosylva with
weather inputs
from ARIA
Regional mapping of fire risk - ‘Critical landscape pattern’ ARIA
Fuelmap information Tecnosylva
Regional storm risk database ARIA
Regional Fire & storm seasonal forecast projection ARIA
Regional IPCC fire & storm projection ARIA with PIK inputs
On-demand wildland-urban interface risk indicator
AMU with ARIA weather
inputs
Impact calculation on RDS sample ONFI
General integrated platform RISFKP-insurance ARIA
3. 3
A Presentation by OASIS | Horizon2020 Insurance
www.h2020insurance.oasishub.co
Implementation plan
WP Title Lead
5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4
13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36
2.3.2 Forest demonstrator AT
Tasks & Sub-Tasks Involved
Task 2.3.2.3 Prepare and run demonstrations AT, ONFI,AMU,
TSYL,PIK, Fresh-T,
Imperial
D2.3.2.3
D2.3.2.4
D2.3.2.6
D2.3.2.6
• run the climate module for past/present climate fire risk indicators over the 2 demo zones
• adapt and run the climate&impact modules for storm risk and for long-term IPCC scenarios for
storm&fire risks, over the 2 demo zones
• adapt the climate module for seasonal forecast over the 2 demo zones
• if seasonal forecast provides some predictability, run to complete on the 2 demo zones
Task 2.3.2.4 Develop business cases and business model ONFI,AT, TSYL,
FRe
D2.3.2.5
D2.3.2.5
• List sub-tasks relating to this task
Task 2.3.2.5 Go to market (emarketplace connections, business development) BetterPoints,
ONFI, AT, TSYL,
Fre
D2.3.2.7
D2.3.2.8
D2.3.2.7
D2.3.2.9
build first communication for existing RISKFP tool, with past/present climate fire risk over
existing French demo zone
Deliverables
Deliverables & Milestones
D2.3.2.1 Needs assessment report (12)
D2.3.2.2 Prototype of new RiskFP-insurance (12) ==>D2.3.2.2a = concept 1 + D2.3.2.2b =concept2
D2.3.2.3 Report on input data specification of each demonstration (15) ==> remove
D2.3.2.4 Report on validation plan of each demonstration (18)
D2.3.2.5 Business cases and business model report (24)
D2.3.2.6 Final demonstration report (24) ==> postpone at M30
D2.3.2.7 Go to market roadmap (24)
D2.3.2.8 Sample data from demonstrations to be used on the emarketplace, compatible with OASIS technical platform (27)
D2.3.2.9 Report on implemented business actions (36)
2018 2019 2020
4. 4
A Presentation by OASIS | Horizon2020 Insurance
www.h2020insurance.oasishub.co
Key activities, highlight and progress
Run demonstrations
Zone 2 –
East
of Melbourne
Zone 3 –
Walhalla
Zone 1 – West
of Sydney
5. 5
A Presentation by OASIS | Horizon2020 Insurance
www.h2020insurance.oasishub.co
Key activities, highlight and progress
Run demonstrations
Forest Demonstrator components
Functionally
implemented
in the web
tool?
Calibrated over which
demo zones in
Australia ?
Missing inputs First results available? Validation
On-demand RDS generation Yes Zones 2 & 3 - Yes Yes
On-demand local fire risk map Yes Zones 2 & 3 - Yes /
Regional mapping of fire risk - ‘Critical landscape
pattern’
Yes Zones 1,2 & 3 - Yes /
Fuelmap information
No (sold separately
by Tecnosylva)
Zones 2&3 (but not
imported in the tool)
No fuel map for zone 1 Yes /
Regional storm risk database (based on same
weather stations as fire risk)
Yes Zones 1,2 & 3 - Yes /
Regional Fire & storm seasonal forecast projection Yes Zones 1,2 & 3
Processing of ECMWF data is
ongoing
available M25 /
Regional IPCC fire & storm projection Yes Zones 1,2 & 3 -
CLP have been computed
from data provided by PIK
but further analyses needed
/
On-demand wildland-urban interface risk indicator Yes
Zones 2 & 3 + additional
zone over South-East
France
- Yes /
Impact calculation on RDS sample Partially Zones 2 or 3 RDS to be provided by TSL Yes to be completed On going
6. 6
A Presentation by OASIS | Horizon2020 Insurance
www.h2020insurance.oasishub.co
Realistic Disaster Scenarios tool validation
Fuel map calibration
Calibrated fuel-map inputs of the areas of interest
Zone 2 (Melbourne):
Realistic Disaster Scenarios and Rapid Response Maps
Example generated on live demo with the webGIS tool …
Zone 3 (Walhalla):
7. 7
A Presentation by OASIS | Horizon2020 Insurance
www.h2020insurance.oasishub.co
Realistic Disaster Scenarios tool validation
Historical fire data
Historical fires data for main fires gathered by an Australian Fire Expert (ECO-FUEGO = ARIA sub-contractor) for the
areas of interest (zones 2 & 3):
• Fire Synopsis
• Fire Spread map (perimeters)
• Fire ignitions locations
• Fire weather data from weather stations
• Fire History prior to the bushfire occurrence
Historical fires used to validate the RDS tool
Zone Name Date Start time Finish time Fire duration
2 Bunyip ridge
Track
7/02/2009 12:00 22:30 10h
3 Aberfeldy-
Donnellys
17/01/2013 11:48 04:00
(18/01/2013
)
16.25h
8. 8
A Presentation by OASIS | Horizon2020 Insurance
www.h2020insurance.oasishub.co
Realistic Disaster Scenarios tool validation
Historical fire data
Fire characteristics summary:
• Fire ignited approximately at 80Km east of
Melbourne in the Bunyip State park due to a
lightning strike on the 4/02/2009 being supressed
that same day.
• Next day fire reignited escaping the containment
lines due to the inaccessibility of vehicles in steep
terrain.
• On the morning of the 7th of February strong NW
wind caused fire spotting over the eastern control
line and severe fire behaviour, and after 12:00h over
the SE containment lines.
• Wind direction changed from NW to SW on the late
afternoon from 17:30h on which intensified greatly
the fire spread.
BUNYIP RIDGE TRACK bushfire – PERIMETER
9. 9
A Presentation by OASIS | Horizon2020 Insurance
www.h2020insurance.oasishub.co
Realistic Disaster Scenarios tool validation
Simulation results
Real fire data simulation inputs:
• Hourly weather data
• Fire ignition lines
• Vegetation fuels
• Digital Elevation Model
Simulation results summary:
• The simulation fire perimeters obtained with the RDS fire model
(brown) fit quite well the real fire perimeter isochrones (purple),
specially on the limits of the fire perimeter.
• The influence of the wind change from NW to NE on the spread
behaviour can be observed in the behaviour of the simulated fire
isochrones.
• In the RDS results the SE area did not burn due to the following
facts:
• The SE part is burned due to fire spotting phenomena which
is not calculated by the RDS simulation model.
• The fuels existing in this SE area are mainly agriculture lands
that have a null or very low spread rate.
Important remark: The RDS fire model does not take into account the
fire suppression activities carried out by the suppression resources
on the field.
10. 10
A Presentation by OASIS | Horizon2020 Insurance
www.h2020insurance.oasishub.co
Realistic Disaster Scenarios tool validation
Historical fire data
ABERFELDY-DONNELLYS bushfire
Fire characteristics summary:
• Fire started on 18/01/2013 at private land from a
small pile of burning papers which escaped to State
Forest.
• Fire initially spread towards SW crossing the
Aberfeldy River initially affected by calmer local
wind fields channelled by the river and the valley (5-
10Km/h which then turned to a strong surface wind
(30-40Km/h) that greatly increased the fire rate of
spread.
11. 11
A Presentation by OASIS | Horizon2020 Insurance
www.h2020insurance.oasishub.co
Realistic Disaster Scenarios tool validation
Simulation results
Real fire data simulation inputs:
• Hourly weather data
• Fire ignition lines
• Vegetation fuels
• Digital Elevation Model
Simulation results summary:
• In the simulation result we can observe the effect of the two
different wind patterns, i.e. first the effect of the calm local
wind (isochrones close to each other) and then the effect of
the fast surface wind field. (isochrones with certain distance)
• It is a wind-driven fire, the simulation isochrones tendency
fits quite well to the original fire perimeter. The observed
differences are due to the intervention of the fire
suppression resources.
• Again, the spotting of the fire is not simulated due to the fact
that the fire model does not contemplate fire spotting
phenomena during the simulation.
12. 12
A Presentation by OASIS | Horizon2020 Insurance
www.h2020insurance.oasishub.co
Impact on GHG emissions
Methodology
Biomass Map
From WRI (based 2000)
LULC map
From Sentinel (based 2018)
Biomass classification map up
todate
(Mb)
Sentinel 2 (optical)
Fire spread / RDS
map
Biomass burnt
GHG emissions from
fire (CO2, CH4, N2O,
etc..)
13. 13
A Presentation by OASIS | Horizon2020 Insurance
www.h2020insurance.oasishub.co
Impact on GHG emissions
Estimated GHG emissions from Aberfeldy-Donnellys bushfire
Start Date: 17/01/2013
Time Ignition: 11:48
Surface Burnt: 20 000 ha
Emission factors g/kg (GeF):
CO2: 1569; CO: 107
CH4: 4.7
N2O: 0.26; Nox: 3
Combustion factor (Cf) for Temperate forests: 0.45
GHG = (AreaBurnt*Biomass*Cf*Gef)/1000 (IPCC)
Average of biomass impacted/ha : 135t
Estimated Co2 emissions : 1 991 Ktons
Estimated CO emissions : 290 Ktons
Estimated CH4 emissions : 12 780 tons
Estimated N2O emissions : 707 tons
Estimated NOx emissions : 8 157 tons
14. 14
A Presentation by OASIS | Horizon2020 Insurance
www.h2020insurance.oasishub.co
Business activity: current status
Key activities, highlight and progress
Business tasks team
• ARIA: transversal + Forestry Latin America
• ForestRe: Insurance sector transversal
• ONFI: Forest owners
• Technosylva: Insurance sector – USA (to come)
Activities already performed
• Supporting partners interviews
• Discussion with other players from the insurance sector, agrobusiness and forest owners.
• Coverage goes beyond the sole insurance sector as the service also attends operational
needs.
• Exploration of other demands as for example the parametric insurance.
• Exploration of partnerships and possible collaboration (AGVESTO)
15. 15
A Presentation by OASIS | Horizon2020 Insurance
www.h2020insurance.oasishub.co
Business activity: scan of the contacts
Key activities, highlight and progress
Risk FP modules Potential clients already identified Additional interviews still to come
On-demand Realistic Disaster Scenarios (RDS) generation
Willis, AON Portland, SwissRe, SCOR
State of Ceara, Brazil
Arauco
Cundinamarca, Colombia
Other insurance companies
Other utilities
Other agrobusiness companies
Forest owners for REDD+
On-demand local fire risk mapping
Willis
Suzano
Electricity Utilities: Enel, State Grid,
Energisa
Regional mapping of fire risk - ‘Critical landscape pattern’
Allianz, SwissRe, Willis RN
AON Brazil with Klabin
Fuelmap information
SwissRe
State of Cear
Regional storm risk database Klabin
Regional Fire & storm seasonal forecast projection Klabin
Regional IPCC fire & storm projection
SwissRe
Klabin
SCOR
On-demand wildland-urban interface risk indicator
Arauco
CPMC
CO2/GHG calculation module Forest owners
16. 16
A Presentation by OASIS | Horizon2020 Insurance
www.h2020insurance.oasishub.co
Business activity: forthcoming activities
Key activities, highlight and progress
Planned activities
• Preparation of a short notice and standard PPT presentation – June 19
• Budget & commercial offer for the service – June 19
• Visits and calls with clients – July / September 19
• Reporting to H2020 – October 19
Discussion with partners about the post H2020 strategy
• Collaboration perspectives – technical / commercial
Business as usual
• Reply to potential demands as they come
17. 17
A Presentation by OASIS | Horizon2020 Insurance
www.h2020insurance.oasishub.co
Business opportunities
Key activities, highlight and progress
Potential commercial offer 1 (ForestRe)
• Meeting with the finance director of one on the biggest global timber investment and
management companies in Portland (September 2018).
• After many conference calls this company is seriously investigating the execution of RiskFP on
one of its Australian investments.
• This would be a cost borne by the client, and as such is a far more realistic testing of the RDS
concept and service.
• Negotiations are in progress in April 2019.
Potential commercial offer 2 (ARIA)
• Discussion with a major Chilean company to sell RISK FP service with a main focus on WUI.
• At the end of 2018, we have already performed 5 different studies on interfaces which were
chosen by the client to showcase the efficiency of the propagation model and the possibility to
simulate different fire scenarios.
• The results were very promising and we structured a proposal for the implementation of the
service after the fire season ends.
• Discussions are in progress in April 2019.
18. 18
A Presentation by OASIS | Horizon2020 Insurance
www.h2020insurance.oasishub.co
User engagement, Dissemination, Communication
Key activities, highlight and progress
Already performed:
• Presentation of the WUI Services at the Firemen and Civil protection headquarter ENTENTE VALABRE (Aix-en-
Provence South of France) - ARIA
• Participation to the 15th International Wildland Fire Safety Summit and 5th Human Dimensions of Wildland Fire
Conference (Dec 2018, USA, https://www.iawfonline.org/event/15th-international-wildland-fire-safety-summit-and-
5th-human-dimensions-conference/) - TECHNOSYLVA
• Fernandez et al., 2018: Modelling fire spread and damage in wildland-urban interfaces, Advances in Forest Fire
Research – ARIA,AMU
Forthcoming soon:
• Presentation at Dana international forest investment conference (London, 7-9 May 2019,
https://danaevents.co.nz/2019london/) - FORESTRE
• Presentation of riskFP at the next OASIS Conference (London, June 2019) – ARIA with support of OASIS LMF
• Organisation of a workshop to present and demonstrate the WUI service to local authorities at county level (June 2019)
- ARIA
• Participation to Innovative4climate (Singapore,June 2019, https://www.cvent.com/events/innovate4climate/event-
summary-decee7fe0cf94765af069f3e7c52ff47.aspx) - ONFI
• Presentation at Dana international forest investment conference (London, 21-23 July 2019,
https://danaevents.co.nz/2019brisbane/): "Innovations in the Australian Forest Industry Sector“ - FORESTRE
19. 19
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