FIRECAST is a novel simulation tool for forecasting burned area anomalies through linking seasonal climate predictions with parsimonious empirical climate fire models.
Active R&D is initiated.
This includes analytical studies and laboratory studies to physically validate the analytical predictions of separate elements of the technology. Examples include components that are not yet integrated or representative.
We assess the forecasting skill of the system as it is a prototype real-time operational forecast system. This seasonal fire forecast system is based on operational dynamical climate forecast systems. In addition, all the forecasts are done by using cross-validation in order to evaluate the predictions as if they were done operationally, including the steps of the bias correction of the seasonal climate data and of the calibration of the fire-climate models. Moreover, to avoid artificial skill, the observed series are de-trended and standardized in each step of the cross-validation, avoiding using observation of the predicted year.

How does it work?

Our strategy for seasonally forecasting burned area anomalies consists in linking seasonal climate predictions with parsimonious empirical climate–fire models using the standardized precipitation index as the climate predictor for burned area.

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SIDS disaster Risk Reduction Portal

The SIDS Disaster Risk Reduction (DRR) Portal enhances ‘risk-reduction’ and ‘information and knowledge-sharing’ for Small Island Developing States by providing an access point for a range of available open data, information, tools and best practices. While the portal provides a uniform collection of data, enabling cross-country sharing of best practices, the unique characteristics and challenges of the various SIDS is acknowledged.
Active R&D is initiated.
This includes analytical studies and laboratory studies to physically validate the analytical predictions of separate elements of the technology. Examples include components that are not yet integrated or representative.
In upcoming months (first quarter of 2018) we will develop a first version for four SIDS countries (St. Maarten, Curacao, Aruba and Surinam) focusing on information and knowledge transfer to support the SIDS with the preparation for extreme weather events, e.g. cyclones and very heavy rainfall. In the second version we extend the portal with additional functionalities and information for six additional SIDS-countries in the Caribbean and/or Pacific. We want to test and evaluate the first version during a field trip with students (schedule early spring 2018). The project is financed by the Ministry of Foreign Affairs and the Ministry of Infrastructure, Public Works and Water Management of The Netherlands.

How does it work?

The portal aspires to make public information and open data available. The information on the portal is ordered per SIDS country. The portal contains information on the relevant sea and/or inland related water threats for each SIDS, such as floods caused by heavy rainfall or typhoons and coastal erosion. The portal provides technical (hydrological and geophysical), meteorological, socio-economical and financial datasets, models and reports. Furthermore, the portal is a platform to share and discuss knowledge and experiences regarding executed and running projects, and to explore project opportunities and project development, and discussion.

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Wildfire Defense Platform

Our approach consists in showing the good side of the drone utilization for forests, in surveillance, forest conservation mapping, environmental crimes vigilance, among so many other possible roles, trough a constellation of small drones(+ 100) constantly surveying and gathering DATA. It is also important to inform Authorities and Population that there is already fully tested technology on solar and non-solar RC drones/planes that can fly for 8+ hours for accomplish this missions.
Active R&D is initiated.
This includes analytical studies and laboratory studies to physically validate the analytical predictions of separate elements of the technology. Examples include components that are not yet integrated or representative.
Drones with long flight times are now very common among technology and hobbyist communities. There are countless examples of its usability and crowd testing. In this case, we have the job of selecting and choosing the best of the deeply tested technologies available, in a way that better fits our needs. Our team has long experience in drone development, but in order to test further (more units) further investment will be also needed.

How does it work?

As explained, this project consists in showing the good side of the drone utilization for forests, in surveillance, forest conservation mapping, environmental crimes vigilance, among so many other possible roles, trough a constellation of small drones (+100 ) that can fly over 8 hours, continuously connected by 3G/Lte, constantly surveying and gathering data.

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Flood Local Tool - Albania

Stream automatic gauges play a critical role in complex contingency plans for flood management and decision making. Automatic stations are used to send streamflow data and water levels anywhere in the world. The Flood Local Tool consists of an automatic flow river gauge station comprised by a water level sensor, a data logger, and a GPRS module to communicate stream water levels to electronic tables, mobile internet or sirens.
Active R&D is initiated.
This includes analytical studies and laboratory studies to physically validate the analytical predictions of separate elements of the technology. Examples include components that are not yet integrated or representative.
The innovation is still under formulation and conceptual development. It has not known technological limitations. The connection between the different components has been already tested and can be functional and well-integrated. For testing purposes, the Drini I Lezhes River (city of Lezha) and the River Gjanica (city of Fier) are proposed as potential testing sites.

How does it work?

The station has three main components: a water level sensor, a data logger and the GPRS module which connects with the control center that collects the information. The water level sensor is an electronic equipment used for the measurement of hydrostatic pressure in surface waters. The data logger is the component that stores the raw data, and convert them into usable data, and it can be set up and managed by distance. The GPRS module is the component that makes possible the communication of the station with the control center which can be located anywhere. Using the mobile internet, it is possible to receive the data from the control center during a reconfiguration or emergency call.

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Application Framework with Drone system

System for early warning and monitoring composed by: on site sensors (e.g. along a river); an automated application framework to provide warning system features; fitted for communication with deployable system like drones that can perform a variety of monitoring tasks providing data to the application framework.
Active R&D is initiated.
This includes analytical studies and laboratory studies to physically validate the analytical predictions of separate elements of the technology. Examples include components that are not yet integrated or representative.
Selected for Testing
Selected for Testing: This innovation has been selected by BRIGAID because of its promising value for reducing the risks or the impacts of extreme hydro-climatological events. After a rigorous assessment, BRIGAID has positively approved the innovator’s testing plan, and decided to provide ongoing support for the testing activities.
Currently the proposed innovation is a proof of concept and it is necessary to define the IT platform with the framework able to integrate the drone/fleet of drones operations.

How does it work?

System for early warning and monitoring (in case, for example, of flood or river / sea contamination) composed by: • on site sensors (e.g. along a river); • an automated warning system; • fitted for communication with deployable system like drones that can perform a variety of monitoring tasks providing data to the DSS. The sensors aim at monitoring the river in real time, looking for readings outside normal parameters to detect problems. In case of problems, an automated warning system will ask to deployable systems fleet to inspect the affected area, taking pictures, recording videos or even deploying extra sensors (this feature will be tested by means of simulations). This makes it possible to have a complete report to be sent to the public bodies (municipality, civil protection & public safety bodies) in the required format, thus speeding up the process to solve the emergency and preventing its extension. The warning system should use different input: • sensors data (e.g. level of the river water, pH, chemical composition of the water); • calls from citizens (automated call center); • social media analysis to automatically see if anyone is talking about problems in the river.

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