Tracing how Landsat data is used to inform burnt acreage in an emergency stabilization Burned Area Emergency Response BAER for the 2012 High Park Fire in Colorado
Wildfires can cause complex problems, from severe loss of vegetation and soil erosion, to a decrease in water quality and possible flash flooding (www.nifc.gov). The US Department of Interior defines "emergency stabilization" as “Planned actions to stabilize and prevent unacceptable degradation to natural and cultural resources, to minimize threats to life and property resulting from the effects of a fire, or to repair/replace/construct physical improvements necessary to prevent degradation of land or resources" (Bureau of Land Management Handbook H-1742-1, Rel. 1-1702). In this use-case, we examine how an emergency stabilization Burned Area Emergency Response (BAER) report for the 2012 High Park Fire (east of Fort Collins, CO) uses Landsat data to inform an estimate of burn severity quoted in the report. This BAER report documents the initial damage assessment, and proposes remediative actions to mitigate identified threats to critical values like roads, water diversion infrastructure, water quality, flooding, debris flow, invasive species, and cultural resources.
The narrative below, assembled from draft concept maps developed for the specific purpose of demonstrating the potential for capturing transdisciplinary processes as concept maps, is an informal way to tell the story of how Landsat data can be used to inform the "Burn Severity" section of a BAER report. A more formal representation of this provenance trace is beyond the scope of this experiment. The first three "steps" in this narrative are similar to the narrative "Tracing how Landsat data helps foster fire-adapted communities in Colorado through data-driven, science-informed planning."
Nodes below that are clickable retrieve the underlying concept maps that provide more details relevant to the narrative. These underlying concept maps will not tell the whole story: references in each concept map point to documents and websites for future information. You may also notice that the underlying concept maps use slightly formalized expressions compared to the narrative below. This is because those underlying concept maps are drafted with the intent of possible re-use by machine algorithms in the future. Those maps constitute a "Genome Library" by which an algorithmic "Genome Assembler" can design a risk mitigation plan that is customized for the intended context-of-use.
The nodes below are clickable, but you would be left scrolling around madly within the restricted size window. Click here instead to render the full-scale concept map below in your browser window.