Country-level fire perimeter datasets (2001–2021)
Fire activity is changing across many areas of the globe. Understanding how social and ecological systems respond to fire is an important topic for the coming century. But many countries do not have accessible fire history data. There are several satellite-based products available as gridded data, b...
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| Published in: | Scientific data Vol. 9; no. 1; pp. 458 - 8 |
|---|---|
| Main Authors: | , , , |
| Format: | Journal Article |
| Language: | English |
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London
Nature Publishing Group UK
30.07.2022
Nature Publishing Group Nature Portfolio |
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| ISSN: | 2052-4463, 2052-4463 |
| Online Access: | Get full text |
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| Abstract | Fire activity is changing across many areas of the globe. Understanding how social and ecological systems respond to fire is an important topic for the coming century. But many countries do not have accessible fire history data. There are several satellite-based products available as gridded data, but these can be difficult to access and use, and require significant computational resources and time to convert into a usable product for a specific area of interest. We developed an open source software package called Fire Event Delineation for python (FIREDpy) which automatically downloads and processes all of the source files for an area of interest from the MODIS burned area product, and runs a spatiotemporal flooding algorithm that converts those hundreds of grids into a single fire perimeter shapefile. Here we present a collection of fire event perimeter datasets for every country on the globe that we created using the FIREDpy software. We will continue to improve the efficiency and flexibility of the underlying algorithm, and intend to update these datasets annually.
Measurement(s)
Fire event occurrence • growth rate • size
Technology Type(s)
Satellite fire detections
Sample Characteristic - Environment
fire
Sample Characteristic - Location
global |
|---|---|
| AbstractList | Fire activity is changing across many areas of the globe. Understanding how social and ecological systems respond to fire is an important topic for the coming century. But many countries do not have accessible fire history data. There are several satellite-based products available as gridded data, but these can be difficult to access and use, and require significant computational resources and time to convert into a usable product for a specific area of interest. We developed an open source software package called Fire Event Delineation for python (FIREDpy) which automatically downloads and processes all of the source files for an area of interest from the MODIS burned area product, and runs a spatiotemporal flooding algorithm that converts those hundreds of grids into a single fire perimeter shapefile. Here we present a collection of fire event perimeter datasets for every country on the globe that we created using the FIREDpy software. We will continue to improve the efficiency and flexibility of the underlying algorithm, and intend to update these datasets annually.
Measurement(s)Fire event occurrence • growth rate • sizeTechnology Type(s)Satellite fire detectionsSample Characteristic - EnvironmentfireSample Characteristic - Locationglobal Fire activity is changing across many areas of the globe. Understanding how social and ecological systems respond to fire is an important topic for the coming century. But many countries do not have accessible fire history data. There are several satellite-based products available as gridded data, but these can be difficult to access and use, and require significant computational resources and time to convert into a usable product for a specific area of interest. We developed an open source software package called Fire Event Delineation for python (FIREDpy) which automatically downloads and processes all of the source files for an area of interest from the MODIS burned area product, and runs a spatiotemporal flooding algorithm that converts those hundreds of grids into a single fire perimeter shapefile. Here we present a collection of fire event perimeter datasets for every country on the globe that we created using the FIREDpy software. We will continue to improve the efficiency and flexibility of the underlying algorithm, and intend to update these datasets annually.Measurement(s)Fire event occurrence • growth rate • sizeTechnology Type(s)Satellite fire detectionsSample Characteristic - EnvironmentfireSample Characteristic - Locationglobal Measurement(s) Fire event occurrence • growth rate • size Technology Type(s) Satellite fire detections Sample Characteristic - Environment fire Sample Characteristic - Location global Fire activity is changing across many areas of the globe. Understanding how social and ecological systems respond to fire is an important topic for the coming century. But many countries do not have accessible fire history data. There are several satellite-based products available as gridded data, but these can be difficult to access and use, and require significant computational resources and time to convert into a usable product for a specific area of interest. We developed an open source software package called Fire Event Delineation for python (FIREDpy) which automatically downloads and processes all of the source files for an area of interest from the MODIS burned area product, and runs a spatiotemporal flooding algorithm that converts those hundreds of grids into a single fire perimeter shapefile. Here we present a collection of fire event perimeter datasets for every country on the globe that we created using the FIREDpy software. We will continue to improve the efficiency and flexibility of the underlying algorithm, and intend to update these datasets annually.Fire activity is changing across many areas of the globe. Understanding how social and ecological systems respond to fire is an important topic for the coming century. But many countries do not have accessible fire history data. There are several satellite-based products available as gridded data, but these can be difficult to access and use, and require significant computational resources and time to convert into a usable product for a specific area of interest. We developed an open source software package called Fire Event Delineation for python (FIREDpy) which automatically downloads and processes all of the source files for an area of interest from the MODIS burned area product, and runs a spatiotemporal flooding algorithm that converts those hundreds of grids into a single fire perimeter shapefile. Here we present a collection of fire event perimeter datasets for every country on the globe that we created using the FIREDpy software. We will continue to improve the efficiency and flexibility of the underlying algorithm, and intend to update these datasets annually. Fire activity is changing across many areas of the globe. Understanding how social and ecological systems respond to fire is an important topic for the coming century. But many countries do not have accessible fire history data. There are several satellite-based products available as gridded data, but these can be difficult to access and use, and require significant computational resources and time to convert into a usable product for a specific area of interest. We developed an open source software package called Fire Event Delineation for python (FIREDpy) which automatically downloads and processes all of the source files for an area of interest from the MODIS burned area product, and runs a spatiotemporal flooding algorithm that converts those hundreds of grids into a single fire perimeter shapefile. Here we present a collection of fire event perimeter datasets for every country on the globe that we created using the FIREDpy software. We will continue to improve the efficiency and flexibility of the underlying algorithm, and intend to update these datasets annually. Measurement(s) Fire event occurrence • growth rate • size Technology Type(s) Satellite fire detections Sample Characteristic - Environment fire Sample Characteristic - Location global Fire activity is changing across many areas of the globe. Understanding how social and ecological systems respond to fire is an important topic for the coming century. But many countries do not have accessible fire history data. There are several satellite-based products available as gridded data, but these can be difficult to access and use, and require significant computational resources and time to convert into a usable product for a specific area of interest. We developed an open source software package called Fire Event Delineation for python (FIREDpy) which automatically downloads and processes all of the source files for an area of interest from the MODIS burned area product, and runs a spatiotemporal flooding algorithm that converts those hundreds of grids into a single fire perimeter shapefile. Here we present a collection of fire event perimeter datasets for every country on the globe that we created using the FIREDpy software. We will continue to improve the efficiency and flexibility of the underlying algorithm, and intend to update these datasets annually. |
| ArticleNumber | 458 |
| Author | Mahood, Adam L. Lindrooth, Estelle J. Cook, Maxwell C. Balch, Jennifer K. |
| Author_xml | – sequence: 1 givenname: Adam L. orcidid: 0000-0003-3791-9654 surname: Mahood fullname: Mahood, Adam L. email: admahood@gmail.com organization: Earth Lab, Cooperative Institute for Research in Environmental Sciences, University of Colorado Boulder, Water Resources, USDA-ARS – sequence: 2 givenname: Estelle J. orcidid: 0000-0003-4899-8861 surname: Lindrooth fullname: Lindrooth, Estelle J. organization: Earth Lab, Cooperative Institute for Research in Environmental Sciences, University of Colorado Boulder, Applied Math, University of Colorado Boulder – sequence: 3 givenname: Maxwell C. orcidid: 0000-0003-4865-5025 surname: Cook fullname: Cook, Maxwell C. organization: Earth Lab, Cooperative Institute for Research in Environmental Sciences, University of Colorado Boulder, Geography, University of Colorado Boulder – sequence: 4 givenname: Jennifer K. orcidid: 0000-0002-3983-7970 surname: Balch fullname: Balch, Jennifer K. organization: Earth Lab, Cooperative Institute for Research in Environmental Sciences, University of Colorado Boulder, Geography, University of Colorado Boulder |
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| Cites_doi | 10.1641/0006-3568(2001)051[0933:TEOTWA]2.0.CO;2 10.1002/ecs2.2591 10.1071/WF16003 10.1126/science.1163886 10.1016/j.rse.2018.08.005 10.5194/essd-10-2015-2018 10.1890/ES11-00345.1 10.1007/s11192-020-03805-x 10.4996/fireecology.0301003 10.25810/vr03-8y36 10.1038/s41597-019-0312-2 10.3390/rs8080663 10.3390/rs12122061 10.1029/2003EO490001 10.1071/WF14190 10.1126/science.aal4108 10.1016/j.rse.2016.02.054 10.1016/j.rse.2013.12.008 10.1111/j.1365-2486.2008.01754.x 10.1071/WF15082 10.3390/rs12213498 10.1002/2014GL059576 10.5194/essd-2018-89 10.5067/MODIS/MCD12Q1 10.1002/ecs2.2594 |
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| Title | Country-level fire perimeter datasets (2001–2021) |
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