Tree Structure Damage Impact Predictive Model (treeS-DIP) Project
Tree Structure Damage Impact Predictive Model (treeS-DIP) Project
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The goal of the Tree Structure Damage Impact Predictive Model (TreeS-DIP) project was to give a prediction of tree structure damage within 48 hours after major events, such as hurricanes.
The goal of the Tree Structure Damage Impact Predictive Model (TreeS-DIP) project was to give a prediction of tree structure damage within 48 hours after major events, such as hurricanes.
This map is an example of one of the output products of the TreeS-DIP model - a classified damage product, where 0 represents no predicted damage, and 4 represents catastrophic predicted damage. This particular output is from a test run of the model on Hurricane Michael from 2018.
This map is an example of one of the output products of the TreeS-DIP model - a classified damage product, where 0 represents no predicted damage, and 4 represents catastrophic predicted damage. This particular output is from a test run of the model on Hurricane Michael from 2018.
My role in the project was to help in the development of input variables for the model, such as the Soil Wind Hazard index. That was created by using gSSURGO data and a SQL query to derive a wind hazard product, that I then reclassified into the product above.
My role in the project was to help in the development of input variables for the model, such as the Soil Wind Hazard index. That was created by using gSSURGO data and a SQL query to derive a wind hazard product, that I then reclassified into the product above.
My next major role in the project was to lead a sub-team that consisted of fire modelers I helped put together. The goal of the sub-team is to use the outputs of the model - for example, the classified damage output shown at the top of the page - as inputs for appropriate fire and fuels models for recovery after large-scale events.
My next major role in the project was to lead a sub-team that consisted of fire modelers I helped put together. The goal of the sub-team is to use the outputs of the model - for example, the classified damage output shown at the top of the page - as inputs for appropriate fire and fuels models for recovery after large-scale events.
The outcome of this sub-group was the creation of a workflow document that outlines the ideas and use-case scenarios that the group of fire modelers decided would be best given the output products from the TreeS-DIP model. Essentially, the document describes multiple possible workflows that were brainstormed given the model output data and other data sources the team could use. The document was a collaborative effort, with a rough draft being brought to the team, which they then edited and revised until each team member was satisfied with the result.
The outcome of this sub-group was the creation of a workflow document that outlines the ideas and use-case scenarios that the group of fire modelers decided would be best given the output products from the TreeS-DIP model. Essentially, the document describes multiple possible workflows that were brainstormed given the model output data and other data sources the team could use. The document was a collaborative effort, with a rough draft being brought to the team, which they then edited and revised until each team member was satisfied with the result.
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