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6 minute read
Tackling wildfires with data: The MAPSS solution
By Dr Pieter Olivier, director, MAP Scientific Services (MAPSS)
Fire is an integral part of many landscapes globally, yet uncontrolled wildfires pose significant risks to people, the economy, and the environment. These risks are likely to get worse due to climate change. MAP Scientific Services (MAPSS), a leading Geographic Information System (GIS) company based in Pretoria, South Africa, is addressing this crisis by providing detailed spatiotemporal data on wildfire occurrences.
MAPSS’s goal is to create the most comprehensive dataset on wildfires globally and provide tools that make this data easy to use. This empowers stakeholders with critical information, raises wildfire awareness and supports clients in fulfilling their legal mandates.
The MAPSS approach to wildfire managementFor effective integrated fire management, we need to know how often, when and where wildfires happen. The only way to do this is to map fires at scale; in other words, map every fire every day and not only the big disaster fires when they occur.
By using advanced remote sensing technologies and in-house algorithms, MAPSS effectively map burnt areas and identify active fire locations 24-hours a day.
Since 2018, MAPSS have mapped nearly one million fires across South Africa. These equate to over 15 million hectares burnt.
MAPSS have worked with fire protection associations (FPAs), district and local municipalities, nongovernmental organisations and protected area management to provide wildfire data in an efficient and easy to use way, with major success and involvement in key areas relating to reporting veldfire statistics, planning mitigation strategies and conducting risk assessments on a regional and local level.
Since 2023, MAPSS are also actively mapping large conservation landscapes in Zambia, Mozambique and Zimbabwe.
Machine-learning algorithmMAPSS has developed a burnt area product that utilises a proprietary machine-learning algorithm that detects and automatically maps every burn scar that occurs within an area of interest within a five-to-tenday period depending on cloud free satellite imagery.
Burn scars are mapped at 10-metre resolution and include fires from as small as one hectare in extent.
Each mapped fire is assigned a unique ID and saved to a geospatial database. In addition, administrative regions eg, district, local and metropolitan municipalities, provinces, management zones eg fire protection association boundaries and land-cover classes summaries are assigned to each burn scar. Burn scars are also linked to ancillary data; for example, date and time, distance from roads, rivers, railways and/or settlements and town boundaries.
One of the major advantages of the MAPSS burnt area product is that it detects nearly 75 percent more fires than other available products at coarser resolutions eg, Moderate Resolution Imaging Spectroradiometer - 500m resolution (Figure 1).
This is important because smaller fires are a critical driver of burnt area and including these small fires in burnt area assessment is critical for accurate statistics, veldfire risk management, mitigation measures and emission estimates of biomass burning to national burdens of CO2. Accurate estimates of CO2 emissions are critical and crucial for effective climate policies, measuring progress towards emissions reduction targets and informing strategies for mitigating climate change impacts. Moreover, many control burns are relatively small fires, by mapping these accurately MAPSS support effective fire management and planning.
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Data sharing and access
Burnt areaBurn scar data are accessed through customised dashboards developed using Esri technology, the world’s leading provider of geospatial software. MAPSS have been an Esri Business Partner since 2018.
Dashboards include interactive maps, summary statistics and graphs and the ability to filter data according to administrative regions eg, district, local and metropolitan municipalities, province, land-cover classes, size and date.
Dashboards are continuously and automatically updated based on available cloud free satellite imagery. In addition, the latest Sentinel-2 imagery is provided as part of the solution, with weekly updated vegetation indices such as the Normalised Difference Vegetation Index (NDVI) and the Normalised Difference Water Index (NDWI).
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All data comply with geospatial standards for data exchange and all statistical data for burnt areas are accompanied with spatial data. GIS data are easily accessible and available in:• Shapefile format (polygons and points)• Raster format (imagery used for burnt area calculations)• As a geodatabase eg, file geodatabase• CSV or spreadsheet (Excel file)• GeoJSON• Feature Collection or• GeoPackage.
Additionally, industry-standard Web Map Services (WMS) and APIs, are available to facilitate seamless integration with existing systems. For example, burn scar data can be integrated with other wildfire software solutions such as Fireweb (www.firewebapp.com). Security includes user group management for differentiated content access and customisable user roles, such as viewers or editors, to accommodate varying levels of permissions.
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Active firesAs part of the MAPSS wildfire solution, we also provide near-real-time locations of active veldfires across an area of interest, updated multiple times a day. MAPSS makes use of Rapid Response data from the Land, Atmosphere Near real-time Capability for EOS (LANCE) system operated by NASA's Earth Science Data and Information System (ESDIS) and The European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT). In total, data from three different sensors (MODIS, VIIRS and SLSTR) onboard six different satellites are used to detect active fires.
This data is made available within three hours of detection. Each active fire is assigned a unique ID and saved to a geospatial database. In addition, administrative regions eg, district, local and metropolitan municipalities, province and land-cover classes are assigned to each active fire. Active fires are also linked to ancillary data; for example, date and time, distance from roads, rivers, railways and/or settlements and town boundaries.