@article{jones_vukomanovic_nowell_mcgovern_2024, title={MAPPING WILDFIRE JURISDICTIONAL COMPLEXITY REVEALS OPPORTUNITIES FOR REGIONAL CO-MANAGEMENT}, volume={84}, ISSN={["1872-9495"]}, DOI={10.1016/j.gloenvcha.2024.102804}, abstractNote={Wildfires often burn across boundaries affecting multiple jurisdictions, landowners and levels of government. Wildfire co-management across jurisdictions is expected to increase in complexity as wildfire severity, size, and frequency increase due to climate change, and growing populations bring more people into close proximity with wildfire. A systematic method to assess jurisdictional complexity for wildfire management is needed to effectively allocate resources and plan for future wildfire management conditions. Here, we developed an open-source framework of decision rules to count jurisdictions and landowners by coupling nearly 9,000 historic wildfire footprints that occurred across 43 U.S. states between 1999 and 2020 with geospatial jurisdictional data. We found that the number of annual wildfires greater than 500 acres has increased through time, with a proportional increase in the number of the highly complex (>7 jurisdictions; >3 levels of government) wildfires. Most wildfires burned 2–3 jurisdictions and 1 or 2 land ownerships, and the most common co-managed wildfires occurred on federal and private lands. On average, the western United States, specifically the Mediterranean California ecoregion, has more jurisdictionally complex wildfires, but the eastern United States, namely the Appalachian Mountains, has localized areas that experienced multiple wildfires with high and varied jurisdictional complexity. The prairies of Texas contained the largest extent of average low complexity wildfires. Of the 43 states that contained a wildfire, 41 had a census place that was burned or within 5 miles of a wildfire boundary, and overall, the annual number of census places near wildfires appears to be increasing through time. We demonstrate a framework that can be used to quantify jurisdictional complexity from observed wildfire boundaries and provide a baseline for discussing jurisdictional complexity at a national, regional, and sub-regional scale. This framework may also be adapted to other hazards or multi-jurisdictional phenomena that have geospatial boundary objects.}, journal={GLOBAL ENVIRONMENTAL CHANGE-HUMAN AND POLICY DIMENSIONS}, author={Jones, Kate and Vukomanovic, Jelena and Nowell, Branda and Mcgovern, Shannon}, year={2024}, month={Jan} }
 @article{jones_vukomanovic_2023, title={Mapping South Florida Daily Fire Risk for Decision Support Using Fuel Type, Water Levels, and Burn History}, volume={6}, ISSN={["2571-6255"]}, DOI={10.3390/fire6060236}, abstractNote={Mapping fire risk in South Florida depends on spatially varying water levels, fuel characteristics, and topography. When surface water levels recede below the lowest topographic features (cypress strands, marshes, etc.), the ecosystem loses its natural, wetted fire breaks, and landscape-level fire risk increases. We developed a geospatial method to generate daily, categorical fire risk maps; the maps visualize low-to-high risk areas using a newly developed 100 m DEM, modeled water levels, fuel types, and fire management units. We assigned fire risk by creating a water level distribution for each unique combination of fuel type and fire management unit; fire risk was then assigned for each pixel based on risk percentiles commonly used by fire management agencies. Assigning risk based on unique fuel types and management units helped avoid over- or under-assigning fire risk that may occur when applying landscape-level “average” risk relationships. Daily maps also incorporated (1) energy release component data to better estimate fuel moisture and (2) historical burn footprints to reduce risk in recently burned areas. Our data-driven approach generated at management-relevant spatial scales may enable more informed prescribed burn planning and may increase the efficiency of staff and resource allocation across the landscape on high-wildfire-risk days.}, number={6}, journal={FIRE-SWITZERLAND}, author={Jones, Kate and Vukomanovic, Jelena}, year={2023}, month={Jun} }
 @article{robbins_loudermilk_reilly_o'brien_jones_gerstle_scheller_2022, title={Delayed fire mortality has long-term ecological effects across the Southern Appalachian landscape}, volume={13}, ISSN={["2150-8925"]}, url={https://doi.org/10.1002/ecs2.4153}, DOI={10.1002/ecs2.4153}, abstractNote={Abstract}, number={6}, journal={ECOSPHERE}, publisher={Wiley}, author={Robbins, Zachary J. and Loudermilk, E. Louise and Reilly, Matthew J. and O'Brien, Joseph J. and Jones, Kate and Gerstle, Christopher T. and Scheller, Robert M.}, year={2022}, month={Jun} }
 @article{yoshizumi_coffer_collins_gaines_gao_jones_mcgregor_mcquillan_perin_tomkins_et al._2020, title={A Review of Geospatial Content in IEEE Visualization Publications}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-85100716572&partnerID=MN8TOARS}, DOI={10.1109/VIS47514.2020.00017}, abstractNote={Geospatial analysis is crucial for addressing many of the world’s most pressing challenges. Given this, there is immense value in improving and expanding the visualization techniques used to communicate geospatial data. In this work, we explore this important intersection – between geospatial analytics and visualization – by examining a set of recent IEEE VIS Conference papers (a selection from 2017-2019) to assess the inclusion of geospatial data and geospatial analyses within these papers. After removing the papers with no geospatial data, we organize the remaining literature into geospatial data domain categories and provide insight into how these categories relate to VIS Conference paper types. We also contextualize our results by investigating the use of geospatial terms in IEEE Visualization publications over the last 30 years. Our work provides an understanding of the quantity and role of geospatial subject matter in recent IEEE VIS publications and supplies a foundation for future meta-analytical work around geospatial analytics and geovisualization that may shed light on opportunities for innovation.}, journal={2020 IEEE VISUALIZATION CONFERENCE - SHORT PAPERS (VIS 2020)}, author={Yoshizumi, Alexander and Coffer, Megan M. and Collins, Elyssa L. and Gaines, Mollie D. and Gao, Xiaojie and Jones, Kate and McGregor, Ian R. and McQuillan, Katie A. and Perin, Vinicius and Tomkins, Laura M. and et al.}, year={2020}, pages={51–55} }