• 

  ASSESSING GREEN STORMWATER INFRASTRUCTURE RESEARCH AND GAPS IN ARID CLIMATES: A SYSTEMATIC REVIEW

  Mason, Jennifer; Reynolds, Julianna (The University of Arizona., 2025)

  The Green stormwater infrastructure approach to stormwater capture is a recommended alternative to traditional stormwater management approaches. Green stormwater infrastructure often includes capture methods such as bioretention ponds, rainwater harvesting systems, green roofs, and permeable pavements, which aim to limit runoff and enhance infiltration. In contrast, traditional stormwater capture methods like detention ponds and channelization focus on moving stormwater quickly. Most green stormwater infrastructure research has focused on temperate regions, but comparatively few researchers have studied semi-arid and arid climates. This study aims to evaluate the effectiveness and research coverage of green stormwater infrastructure in semi-arid and arid regions through a systematic literature review. Papers were selected based on defined criteria: studies from arid (less than 250 mm annual precipitation) and semi-arid regions (between 250 mm and 500 mm annual precipitation) classified as highly relevant (categories 1 or 2) based on findings related to peak flow, recharge, storage capacity, or runoff. Visualization diagrams were employed to identify geographic and methodological research gaps. The findings highlight a need for expanded empirical studies to validate green stormwater infrastructure model performance in arid climates.
• 

  TACOMA POWER PUBLIC SAFETY POWER SHUTOFF ASSESSMENT TOOL

  Korgaonkar, Yoga; Chew, Christina (The University of Arizona., 2025)

  Wildfires are quickly becoming one of the more prominent natural hazards to the Pacific Northwest in the United States of America. Power companies and utilities across the West Coast have adopted practices to better manage their role within their respective communities throughout all phases of Emergency Management. Washington State Department of Natural Resources has asked all utilities to draft a Wildfire Mitigation Plan, to include PSPS practices. This project aims to identify what happens when a wildfire is approaching Tacoma Power’s service territory under Public Safety Power Shutoff (PSPS) conditions, and the information needed to fight the fire in the event the water purveyor is an energized source. Emergency Management teams need access to this kind of information to be better prepared when coordinating resources to fight fires encroaching into urban areas. This project developed a Geographic Information System (GIS)-based application based on identifying areas of impact in the event of a PSPS, specifically on water purveyors throughout the Tacoma Power service territory. Information gathered from this assessment tool supports the Wildfire Mitigation Plan and process for Tacoma Power.
• 

  GROUNDWATER DEPLETION AND SUSTAINABILITY IN MERCED COUNTY, CALIFORNIA: ANALYZING CURRENT TRENDS SCENARIOS USING GIS TOOLS

  Korgaonkar, Yoga; Raju, Desiree (The University of Arizona., 2025)

  Merced County, California, located in the drought-prone Central Valley, relies heavily on groundwater to support its agricultural economy. This study estimates groundwater storage at the county level by integrating satellite-based remote sensing data with in situ well observations using geographic information systems (GIS) technology. Key datasets include the Gravity Recovery and Climate Experiment (GRACE) for terrestrial water storage anomalies, the Global Land Data Assimilation System (GLDAS) for soil moisture and snow water equivalent, and the Moderate Resolution Imaging Spectroradiometer (MODIS) for surface water detection. In situ groundwater level measurements from monitoring wells were used to validate and supplement satellite-based estimates. Coarse-resolution global datasets were downscaled using statistical interpolation and resampling methods to produce finer spatial outputs suitable for local analysis. Groundwater storage anomalies were derived by subtracting surface and subsurface components from total water storage. A multi-step processing workflow addressed spatial misalignment, temporal gaps, and scale mismatches across datasets. Results demonstrate that combining remote sensing with in situ data improves the spatial and temporal resolution of groundwater storage estimates. This integrative approach supports local water resource planning by offering scalable methods for tracking groundwater trends in data-limited regions.
• 

  ASSESSING EROSION CONTROL SUITABILITY WITH NORMALIZED DIFFERENCE INFRARED INDEX IN A SEMI-ARID WATERSHED

  Korgaonkar, Yoga; Rubio, Nelly (The University of Arizona., 2025)

  Accurate assessment of soil moisture and infiltration capacity is essential for watershed management in semi-arid regions like Southern Arizona, USA. This study investigates the use of the Normalized Difference Infrared Index (NDII) to identify areas of low infiltration within the Walnut Gulch Experimental Watershed (WGEW), focusing on the driest (2020) and wettest (2022) monsoon seasons between 2015 and 2025. NDII, a remote sensing index sensitive to vegetation water content, serves as a proxy for root zone soil moisture. This study uses Landsat 8/9 imagery to analyze NDII changes between May and October and classify areas from low to high infiltration response. Comparing NDII change values across contrasting years highlights zones with persistent low infiltration. Identifying these areas is the first step toward developing a restoration strategy for semi-arid watersheds. A multi-criteria suitability analysis— incorporating slope, terrain ruggedness, road accessibility, and soil moisture data— prioritizes locations for erosion control structures (ECS). ECS offer a cost-effective restoration method by reducing water velocity and enhancing infiltration potential. Integrating NDII dynamics with hydrological and terrain factors provides a scalable, data-driven framework to support sustainable watershed restoration in arid environments.
• 

  SPATIOTEMPORAL ANALYSIS OF HAWAIIAN GREEN SEA TURTLE (CHELONIA MYDAS) STRANDINGS ON MAUI, HAWAII (2017-2024)

  Korgaonkar, Yoga; Cheung, Robin (The University of Arizona., 2025)

  Conserving key species, such as the Hawaiian green sea turtle (Chelonia mydas), requires understanding the spatial and temporal distribution of strandings. This project examines strandings on Maui from 2017 to 2024 using data collected by the Marine Institute at the Maui Ocean Center. Each record includes multiple data entries, including geospatial coordinates, suspected cause, mortality status, age class, sex, signs of injury or entanglement, presence of fibropapillomatosis, and rehabilitation outcomes for each stranded turtle. Spatial analysis was conducted in ArcGIS Pro using tools such as Kernel Density Estimation, Hot Spot Analysis (Getis-Ord Gi*), and Summary Statistics. Python scripting supports data preprocessing and field calculations. Among the 1,297 records analyzed, 88.7% of turtles were found alive, 7% were freshly dead, and 4.3% were in various stages of decomposition. No significant decomposition pattern was observed. Sex data was limited—77.2% undetermined, 12.8% female, and 10% male, hindering detection of sex-specific trends. Strandings were clustered along densely populated and tourist-heavy coastlines, likely influenced by both turtle behavior and observer bias. Remote or less accessible areas may be underrepresented. These results highlight the importance of expanding monitoring efforts in under-surveyed regions to improve data completeness. Future conservation strategies should consider limitations such as staff availability, funding, and access to isolated sites to ensure more comprehensive stranding assessments and effective protection of this threatened species.
• 

  SPATIO-TEMPORAL CLASSIFICATION OF WEST COAST WINE REGIONS USING VITICULTURAL CLIMATE INDICES

  Korgaonkar, Yoga; Bertolli, Caroline (The University of Arizona., 2025)

  Climate is a primary determinant of viticultural potential, directly influencing grape phenology, yield, and wine style. In recent decades, climate change has introduced increasingly complex challenges for vineyard managers and the wine industry. The critical objective of modern wine growing is to maximize yield and minimize water consumption without compromising quality. This research aims to assess how viticultural climate classifications have changed over time and what these shifts imply for sustainable vineyard adaptation. Using time series analysis of historical climate records and remote sensing data, vineyard regions are classified annually based on the Winkler Index. The study identifies trends in heat accumulation, temporal shifts in viticultural zones, and evolving regional suitability for grape production. These findings offer insights into the long-term effects of climate change on viticulture and aim to support evidence-based adaptation strategies and business decisions for growers and winemakers.
• 

  MODELING THE INTERSECTIONS OF URBAN HEAT ISLANDS AND VULNERABLE POPULATIONS IN SPOKANE, WASHINGTON

  Mason, Jennifer; Mendenhall, Jacqueline (The University of Arizona., 2025)

  As climate change continues to cause hotter summers and warmer winters, studying the effects of this heat is increasingly important so that mitigation steps can be taken now rather than when it becomes too late. The urban heat island effect is caused by urban surfaces retaining more solar radiation and emitting more heat than natural surfaces would. Urban heat islands pose threats to vulnerable populations, such as those who are of a lower socioeconomic status, the unhoused, and the elderly. The Spokane Metropolitan Area is the largest city in eastern Washington and has continually seen an increase in average summer temperatures over the past twenty years. Local communities and universities have begun to monitor how the more extreme heat events are affecting the local environment and planning for further changes, and the city’s Urban Forestry Department is working to increase the city’s tree canopy to 30% by 2030. This study uses a compilation of thermal data from the summer months of 2020 and 2024 to identify the hottest parts of the city, and census data to identify how those break down by demographic. Mitigation is modeled by using building footprints to showcase how a Cool Roof program would assist in dispersing heat more effectively.
• 

  THE VOICES OF WATER: DEVELOPMENT OF A PARTICIPATORY GEOGRAPHIC INFORMATION SYSTEM FOR SPATIOTEMPORAL WATER QUALITY MONITORING IN THE DOÑA JUANA VOLCANIC GEO-ECOSYSTEM AT NARIÑO, COLOMBIA

  Mason, Jennifer; Cañas, Samuel (The University of Arizona., 2025)

  This research presents the development and implementation of a cloud-based Participatory Geographic Information System (PGIS) for spatiotemporal water quality monitoring in the Doña Juana Volcanic Geo-ecosystem, Nariño, Colombia. Building upon prior transdisciplinary research conducted by the author—integrated local and generational knowledge with geochemical analysis of waters around the volcano— this work puts into use the four culturally recognized water types (mudas, orgánicas, tibias, and gordas) identified by inhabitants of Las Mesas and nearby villages within a web-accessible monitoring platform that enables continuous, community-driven data collection. The methodology employs a three-tiered architecture: (1) an ArcGIS Pro geodatabase with customized domains incorporating local water classifications; (2) ArcGIS Field Maps for offline-capable mobile data collection by trained community monitors; and (3) an ArcGIS Experience Builder web application providing real-time 3D visualization and spatiotemporal analysis. Community monitors were trained to use portable multiparameter probes to measure temperature (°C), pH, and total dissolved solids (ppm)—parameters that reflect hydrothermal activity through temperature variations, acidity changes, and mineral content fluctuations. This enables scientific documentation of physico-chemical characteristics in water that they have traditionally observed while maintaining correlations between quantitative data and established classifications for detecting possible volcanic or anthropic related changes. By integrating PGIS principles with community-based water monitoring, this research strengthens volcanic risk management through participatory approaches. Furthermore, this system empowers active environmental monitors capable of identifying anomalous patterns potentially signaling volcanic activity, fosters stronger socio-ecological relationships between inhabitants and their territory, and enhances response capacity. Ultimately, this work contributes to early warning systems research and establishes a replicable framework for community-based volcanic surveillance throughout Colombia and other Latin American regions where water, volcanoes, and communities are deeply interconnected.
• 

  WILDFIRE MITIGATION IN THE SULPHUR SPRINGS VALLEY OF ARIZONA: A CASE STUDY OF COST AND RISK FOR SULPHUR SPRINGS VALLEY ELECTRIC COOPERATIVE (SSVEC)

  Korgaonkar, Yoga; Lerman, Isaiah (The University of Arizona., 2025)

  Wildfires and electric utilities in Arizona maintain a complex and volatile relationship with one another. Mitigation of wildfire risks by SSVEC is imperative to keep electricity flowing for members while protecting assets and limiting liability. Analysis of field data and historical wildfire data in ArcGIS Pro and RStudio helped create a cost and risk analysis for SSVEC. The cost and risk analysis for SSVEC will allow for more informed decision making to tackle the problem of wildfire mitigation throughout the service territory. The results show high, moderate, and low risk wildfire areas based upon multiple criteria to aid in decision making on which areas should be addressed first for wildfire mitigation efforts. A plan of action to mitigate wildfire based upon the risk areas gives SSVEC an opportunity to plan future budgeting and labor efforts for this initiative.
• 

  BUILDING A GEODATABASE FOR THE AMERICAN AIR MAIL SOCIETY

  Korgaonkar, Yoga; Lopez, Mariejane (The University of Arizona., 2025)

  This project aimed to establish a foundational Geographic Information Systems technology base for the American Air Mail Society by creating a geodatabase to visualize the history of airmail and explore nationwide communication in the early days of aviation. It serves as a tool for the American Air Mail Society to better communicate, understand, and grasp various airmail related data, such as where airmail services were present in the United States and how it has changed. The project allows for analysis based on year, state, city, and specific routes, through its structured organization and integrated spatial data. The data conveys a glimpse into historical airmail operations, including Contract Airmail Routes from 1926, Transcontinental Air Transport routes from 1929, and Army Emergency flights undertaken in 1934. ArcGIS Pro was used to integrate the data provided by the American Air Mail Society, facilitating the visualization of routes through distinct symbology. Map layouts were created to showcase the three aforementioned airmail data sets in the geodatabase. This introduction to the visualization of the data yields a glimpse of the many opportunities of spatial data. It inspires the expansion and development of the American Air Mail Society’s foundation for ongoing historical airmail data visualization and analysis.
• 

  DETERMINING OPTIMAL CELL TOWER LOCATIONS IN RUGGED TERRAIN WITH A VIEWSHED ANALYSIS

  Mason, Jennifer; Lehnig, Bryan (The University of Arizona., 2025)

  As the national telecommunication grid continues to expand it provides millions of Americans with reliable communication services, such as cellphone reception. However, large portions of the country, particularly remote and rugged regions, still lack consistent or any coverage. Addressing these gaps is crucial, especially for emergency response, where instant communication can significantly improve outcomes. This case study focuses on Logan Canyon, Utah, where Highway 89 traverses a region with no existing cell phone reception. This lack of coverage poses safety risks, especially in the event of an emergency. A suitability analysis was performed using line-of-sight methods to identify optimal locations for telecommunication towers. A 3D elevation model was created by melding high-resolution digital elevation models (DEMs) and LiDAR point clouds to simulate both bare earth elevation and canopy cover height. Using the highway centerline as a reference a line-of-sight analysis identified high-visibility areas. The areas of highest visibility were then identified, and a second line-of-sight analysis was performed, accounting for direct signals as well as diffraction and reflection effects, to refine the potential coverage area. Results suggest that strategically placing telecommunication towers within Logan Canyon could significantly improve cellular coverage along Highway 89. However, the analysis also indicates diminishing returns with additional towers, emphasizing the importance of balancing infrastructure costs with coverage benefits. While this study is specific to Logan Canyon, its methodology provides a framework that can be adapted to other regions facing similar connectivity challenges.
• 

  MICRO-SCALE ECOLOGY, MACRO-SCALE IMPACT: A RANKED SUITABILITY ANALYSIS FOR UPDATING OREGON’S CONSERVATION OPPORTUNITY AREAS USING LEVEL IV ECOREGIONS

  Mason, Jennifer; Booth, Cameron D. (The University of Arizona., 2025)

  With environmental conservation continuing to be a paramount issue in the modern world, many state government agencies are looking to develop conservation efforts to curb various risk factors. Oregon is a state leading the way in comprehensive conservation strategy. Currently, the state has developed conservation opportunity areas (COA’s), prime locations for conservation efforts, built on the backbone of the level III ecoregion framework. With the publication of the level IV ecoregion framework in 2014, this analysis aims to determine which level IV ecoregions have the least coverage in the current COA locations, and to use a ranked suitability analysis approach to locate additional, alternative locations for COA’s to bolster level IV ecoregion ecosystems within the state. Results showed five ecoregions with less than 1% coverage. Ranked suitability analysis showed multiple areas of high-ranking opportunity areas for further conservation.
• 

  RISING FROM THE FLAMES: TRACKING NATURE'S RESILIENCE AFTER THE BLUE CUT FIRE

  Mason, Jennifer; Bain, Roger (The University of Arizona., 2025)

  Post-fire recovery assessment is critical for wildland-urban interface management and climate adaptation planning, yet quantitative relationships between environmental controls and regeneration success remain poorly understood in Mediterranean ecosystems. This research addresses the fundamental problem of predicting recovery patterns through comprehensive dual-index analysis combining Normalized Difference Vegetation Index and Normalized Burn Ratio assessments of vegetation regeneration following the 2016 Blue Cut Fire across 37,020 acres in San Bernardino County, California. Six time periods of Landsat 8/9 imagery spanning 2016-2025 were processed using automated workflows, integrated with comprehensive topographic analysis quantifying slope gradient and aspect orientation effects through advanced statistical modeling. The dual-index approach provided unprecedented cross-validation of recovery patterns, with NDVI analysis achieving 98% successful natural regeneration averaging 129.0% of pre-fire conditions while NBR analysis confirmed 80% significant improvement from immediate post-fire conditions. Results revealed counter-intuitive patterns challenging conventional ecological theory: moderate slopes achieved 132.6% recovery compared to flat slopes at 124.6%, contradicting erosion control predictions. Quadratic regression modeling provided exceptional validation with R² = 0.9573, mathematically proving optimal recovery occurs at 26.5° slope gradient. Circular regression explained 87.3% of aspect-related recovery variation, with north-facing slopes achieving superior recovery across both indices. The convergence of findings across independent analytical approaches demonstrates that environmental controls explain greater than 85% of recovery variation, providing robust quantitative frameworks for predicting post-fire regeneration success. Results suggest Mediterranean fire-adapted ecosystems possess exceptional natural recovery potential, enabling resource managers to prioritize limited restoration funds toward other ecosystem priorities rather than widespread intervention following similar fire events.
• 

  UNDERSTANDING IMPACTS OF SEVERE WILDFIRE TO ARIZONA MOUNTAIN FOREST: AN ANALYSIS OF 2 LARGE WILDFIRES IN THE MADREAN SKY ISLANDS

  Mason, Jennifer; Wilson, Matthew (The University of Arizona., 2025)

  Two large and destructive wildfires, the Frye Fire (2017) and the Bighorn Fire (2020), occurred within two mountain ranges within the Arizona Madrean Sky Island ecoregion, the Santa Catalina Mountains and Pinaleño Mountains respectively. Both wildfires are described by varying degrees of burn severity, each consuming large portions of high elevation (> 7000 ft) coniferous forest following previous large and destructive stand replacing wildfire events within similar footprints. Given the immense transition in forest type and structure across drastic elevational gradients unique to these mountain ranges, there is a need to understand the relative recovery associated with Sky Island forest structure following large mountain-wide fire events. Providing 1) a visual representation of localized precipitation conditions prior to the wildfire events, 2) a remote sensing index driven fire effects analysis, and 3) a change detection analysis to forest structure, may help to better understand trends of wildfire to these unique ecosystems. Using Sentinel-2 derived satellite imagery, a series of spectral indices (Normalized Difference Vegetation Index, Normalized Burn Ratio Plus, Normalized Difference Infrared Index, and Burn Area Index for Sentinel-2) were calculated to identify burn severity, vegetation loss and 5-year post fire recovery potential to provide more accurate estimates to areas most likely to have undergone forest type conversion.
• 

  IMPACT OF CLIMATE CHANGE ON WHISKY PRODUCTION

  Mason, Jennifer; LaMunyon, Christine (The University of Arizona., 2025)

  Climate change is altering environmental conditions critical to Scotch whisky production, specifically optimal precipitation and temperatures for barley yields. This study employs geospatial analysis to assess climate patterns and agricultural shifts within whisky-producing regions of Scotland. Climate data from the UK Met Office and agricultural reports from the Scottish Government are used to analyze temperature and precipitation trends impacting barley farming. Statistical modeling determines correlations between climate trends and whisky production factors, with choropleth maps and temporal analysis graphs visualizing the findings. The results provide insights into the vulnerabilities of whisky production and inform adaptation strategies for distilleries. Understanding these environmental impacts is crucial for sustaining the industry amid ongoing climate shifts.
• 

  UNDERSTANDING FATAL CRASHES IN PORTLAND: A SPATIAL ANALYSIS OF SOCIOECONOMIC, BUILT ENVIRONMENT AND VEHICLE SPEED FACTORS

  Korgaonkar, Yoga; Salas-Niño, Liliana (The University of Arizona., 2025)

  This article presents a case study analyzing the opportunities provided by the Portland open data repository on vehicle speed to explore the relationship between vehicle speed and road safety. While the influence of vehicle speed on road safety has been well-documented on highways and freeways, where free flow conditions are generally uninterrupted by pedestrians or bus stops, this study shifts focus to urban core roads, which include arterials and collector roads. These types of roads account for 69% of road fatalities in the U.S. and are characterized by a higher density of diverse road users, making the interaction between vehicle speed and safety more complex. Using Geographically Weighted Poisson Regression (GWPR), the study examines the associations between vehicle speed and fatal road crashes at the block group level. The goal is to assess the significance of vehicle speed in predicting fatal crashes while identifying spatial variability across the city. This analysis aims to provide insights that could inform localized interventions, particularly in ethnically diverse areas that disproportionately bear the burden of road fatalities.
• 

  Increased Frequency and Potential Environmental Impacts from Oil Spills After Hurricane Landfalls

  Korgaonkar, Yoga; Scher, Benjamin (The University of Arizona., 2025)

  The increased frequency of oil spills, specifically after hurricanes, can have lingering effects throughout the ecosystem and can cause complexities while restorative efforts are underway. Certain environmentally sensitive areas require different restoration techniques to allow for proper removal of oil with minimal disturbance to the habitat. This project aims to compare oil spills immediately after a hurricane and a non-hurricane event, allowing for a visual representation of increased frequency. Displaying environmentally sensitive areas within the reach of oil spills will illustrate potential impacts of protected and vulnerable land. With numerous sources of publicly available data, we can display where and how much sensitive land may be impacted. Analyzing distance from oil spills, focusing on protected habitats, and concentrating on the most vulnerable and sensitive land will give a precise picture of the lasting impacts of a hurricane. This study looked at two different four-day periods. The first one during normal weather events, and the second was immediately after the landfall of Hurricane Ida. Results show that there was a 600 percent increase in pollution events over a four-day period. This project focuses on one specific hurricane event but provides valuable information. With more time and personnel this process can easily be scaled up to each hurricane that makes landfall in the U.S. Understanding increases in pollution events beforehand, knowing which areas are most vulnerable, and ensuring resources can be deployed easier and faster can allow for less impacts on wildlife and the environment.
• 

  Wildland Fire Risk Analysis on the Fort Apache Indian Reservation

  Korgaonkar, Yoganand; Edwards, Desiree (The University of Arizona., 2025)

  Wildfires pose a significant threat to natural resources, communities, infrastructure like homes on the Fort Apache Indian Reservation. This project developed a GIS- based wildfire risk assessment model utilizing available data and analytical tools in ArcGIS Pro. The analysis incorporated key environmental variables including fuel models from LANDFIRE, topographic features derived from USGS Earth Explorer, and proximity to communities. A weighted overlay approach was applied to classify areas into no risk. low, moderate, high and extreme wildfire risk zones. By adapting methodologies like kriging and weighted overlay, this study has ensured a replicable and objective assessment and framework. The final wildfire risk maps are able to support land managers in prioritizing mitigation efforts and resource allocation for planning and emergency response efforts.
• 

  A Modelbuilder Workflow for Automating Contour Generation from High-Resolution Elevation Data in a Mosaic Dataset

  Korgaonkar, Yoganand; Dunn, Amy (The University of Arizona., 2025)

  This project streamlines the topographic-contour generation process for the New Mexico Bureau of Geology and Mineral Resources (NMBGMR). Historically, the NMBGMR generated contours internally to leverage access to high-resolution elevation rasters and maintain control over the level of detail and smoothness. Creating contours from elevation data involves a multi-step workflow requiring manual input, mosaicking, reprojecting, clipping, appending data, field calculations, and generalization. This work develops an automated geoprocessing tool using ModelBuilder in ArcGIS Pro, replacing manual steps with a simplified, repeatable process. The model uses a mosaic dataset to efficiently manage the multiple raster tiles used to generate contours. Integrated into the tool is the optional capability of unit conversion, allowing for the creation of contours in either meters or feet, automated clipping to a designated map extent, contour creation at designated intervals, appending to an existing feature class, and attribute calculations. Testing on map areas with steep, mountainous terrain confirmed that the model accurately replicates the original workflow while reducing complexity. The outcome is a user-friendly tool that standardizes contour creation and improves the efficiency of GIS specialists/cartographers when building map kits used by field geologists. This advancement allows for consistent and rapid production of accurate, map-scale appropriate contours to provide topographic context for the overlying geologic data and supports the production of high-quality cartographic layouts.
• 

  Automated Evacuation Routing with ArcGIS Network Analyst

  Korgaonkar, Yoganand; Bangs, Michael (The University of Arizona., 2025)

  Efficient and adaptive evacuation routing is essential for public safety during disasters such as wildfires, floods, and debris flows. Many traditional evacuation planning methods lack real-time adaptability and fail to account for road closures, congestion levels, and network constraints. This project develops an automated evacuation routing model using ArcGIS Network Analyst, integrating geospatial analysis techniques to generate optimized evacuation routes based on user-defined evacuation zones. A web-based application enables emergency managers to define evacuation zones by drawing a polygon, which triggers the routing model to compute optimal evacuation routes in real time. The model incorporates road closures, restricted access roads, and functional classifications to ensure that only available and suitable roads are used for evacuation. By analyzing residential parcel densities within the evacuation zone, the system assigns congestion penalties to road segments, dynamically influencing optimal route selection. The script automatically identifies exit points at the boundary of the evacuation zones where roads provide safe egress, ensuring logical and efficient evacuation paths. The model was tested using a road network dataset for Santa Barbara County to evaluate its effectiveness in real-world scenarios. This framework is scalable and adaptable, allowing emergency managers to tailor evacuation planning for various disaster scenarios and apply the model to different geographic regions and network datasets. By leveraging network analysis, GIS automation, and interactive web mapping, this project enhances disaster preparedness and response efforts, providing a flexible, real-time evacuation planning tool that supports data-driven decision-making and ensures safer and more efficient evacuations.

View more