StormCloud™
Rapid assessment of forest disturbances using remote sensing.
Initiated in 2020, the StormCloud system is a project of the Spatial Ecology and Conservation (SPEC) Lab at the University of Florida (www.speclab.org) and is developed, coded, and maintained by (PI) Eben Broadbent. Objectives include the integration of cloud-based 'artificial intelligence' analyses of satellite radar, lidar, and optical remote sensing sensors, and Forest Inventory and Analysis (FIA) plot data, to enable rapid, online, and user accessible, assessments of ecological damage from hurricanes and other natural disturbances. While a key focal area is the Southeast United States, capabilities are being developed for application across the US. Key outputs include continuous and categorical damage assessments maps in the near-real time (NRT) and rapid time periods, and outputs related to area damaged, areas subsequently logged, carbon impacts of the disturbance events and logging, and species level assessments at the pixel to county to regional spatial scales.
The complete StormCloud framework integrates closely with the SPEC Lab's Big Plot Network — our GatorEye drone-lidar plot network distributed across the South East — to establish solid baselines and enable rapid, multi-temporal analyses of forest disturbances, classes, and ecological impacts, including carbon, shortly after disturbances - specifically Hurricane landfall events. Big plots are of sufficient spatial extent (250x250 m to 500x500 m) to permit the required calibration and validation for larger extent StormCloud analyses. They are installed using our GatorEye drone systems and from our ORC (terrestrial) and ORCA (marine) mobile ground control stations.
Please email [email protected] with any questions, requests, or issues. Funding support gratefully acknowledged from the USDA McIntire-Stennis, UF IFAS, FIA USFS, FAMU CSER, and the SPEC Lab. Special thanks to Angelica Almeyda Zambrano, Gabriel Prata, Todd Schroeder, Jason Drake, and Paul Medley
The web app may take several minutes to load, depending on computing resources and internet speed. It is recommended to click the link to open the app, then return after approximately five minutes to check its status. During the loading process, temporary error messages (e.g., related to map loading) may appear, but these typically resolve automatically. Allow the app to continue running until it fully loads, which is usually within about five minutes. All results are beta and proof-of-concept use only.
Please note that this is NOT a static hosted map service, which are more rapid to display, rather it fully runs the analytical workflows from scratch with the most updated satellite imagery and input data, which is required for rapid assessment following disturbance events (e.g., hurricanes). We are working to create rapid display static web-hosted products as well for convenience purposes.
An detailed overview of StormCloud and collaborating components was given to NASA AEOIP.
A link to view the presentation is available here.
Rapid assessment of forest disturbances using remote sensing.
Initiated in 2020, the StormCloud system is a project of the Spatial Ecology and Conservation (SPEC) Lab at the University of Florida (www.speclab.org) and is developed, coded, and maintained by (PI) Eben Broadbent. Objectives include the integration of cloud-based 'artificial intelligence' analyses of satellite radar, lidar, and optical remote sensing sensors, and Forest Inventory and Analysis (FIA) plot data, to enable rapid, online, and user accessible, assessments of ecological damage from hurricanes and other natural disturbances. While a key focal area is the Southeast United States, capabilities are being developed for application across the US. Key outputs include continuous and categorical damage assessments maps in the near-real time (NRT) and rapid time periods, and outputs related to area damaged, areas subsequently logged, carbon impacts of the disturbance events and logging, and species level assessments at the pixel to county to regional spatial scales.
The complete StormCloud framework integrates closely with the SPEC Lab's Big Plot Network — our GatorEye drone-lidar plot network distributed across the South East — to establish solid baselines and enable rapid, multi-temporal analyses of forest disturbances, classes, and ecological impacts, including carbon, shortly after disturbances - specifically Hurricane landfall events. Big plots are of sufficient spatial extent (250x250 m to 500x500 m) to permit the required calibration and validation for larger extent StormCloud analyses. They are installed using our GatorEye drone systems and from our ORC (terrestrial) and ORCA (marine) mobile ground control stations.
Please email [email protected] with any questions, requests, or issues. Funding support gratefully acknowledged from the USDA McIntire-Stennis, UF IFAS, FIA USFS, FAMU CSER, and the SPEC Lab. Special thanks to Angelica Almeyda Zambrano, Gabriel Prata, Todd Schroeder, Jason Drake, and Paul Medley
The web app may take several minutes to load, depending on computing resources and internet speed. It is recommended to click the link to open the app, then return after approximately five minutes to check its status. During the loading process, temporary error messages (e.g., related to map loading) may appear, but these typically resolve automatically. Allow the app to continue running until it fully loads, which is usually within about five minutes. All results are beta and proof-of-concept use only.
Please note that this is NOT a static hosted map service, which are more rapid to display, rather it fully runs the analytical workflows from scratch with the most updated satellite imagery and input data, which is required for rapid assessment following disturbance events (e.g., hurricanes). We are working to create rapid display static web-hosted products as well for convenience purposes.
An detailed overview of StormCloud and collaborating components was given to NASA AEOIP.
A link to view the presentation is available here.
Access to the most recent web app version is provided below
StormCloud App - dynamic methods doc (likely outdated due to rapid advances)
Individual modules for more rapid viewing * these are modules within the full StormCloud - they may not be as updated as the full workflow, but will load faster in most cases for viewing purposes.
Logging App
Carbon App
StormCloud App - dynamic methods doc (likely outdated due to rapid advances)
Individual modules for more rapid viewing * these are modules within the full StormCloud - they may not be as updated as the full workflow, but will load faster in most cases for viewing purposes.
Logging App
Carbon App
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Disclaimer: This is a beta system. The results provided are intended for preliminary and informational purposes only. We make no representations or warranties regarding accuracy or completeness and disclaim liability for any damages arising from use. Users are solely responsible for interpretation and application. Portions of the software development and text revisions were completed with assistance from AI tools. System powered by Google Earth Engine, utilizing low- to zero-carbon energy sources.
