Michell's GIS Journey

 In this analysis, I modeled potential movement corridors for black bears between two protected areas within the Coronado National Forest. Using data layers such as land cover, elevation, and roads, I developed a habitat suitability model that reflects black bears’ preferences and movement constraints. To begin, I reclassified land cover, elevation, and proximity to roads into suitability scores, where lower scores indicate more favorable habitat. These criteria were combined using a weighted overlay, giving the most weight to land cover, followed by elevation and distance to roads. The combined suitability map was then inverted to create a cost surface, representing the ease of movement across the landscape. Next, I converted the protected area boundaries into raster format and applied cost distance analysis to calculate the minimum movement cost from each park across the landscape. Summing the two cost distance outputs highlighted areas with the lowest cumulative travel cost, whi...

  In the first part of this week’s GIS assignment, I performed a land suitability analysis using a weighted overlay method to evaluate potential areas for development based on a combination of environmental and infrastructure-related criteria. The goal was to classify land into five suitability categories, from 1 (least suited) to 5 (most suited), using raster data and weights assigned to different input layers. The analysis involved two main scenarios. In the first scenario, I applied equal weights to each factor: land cover, soil type, slope, distance to streams, and distance to roads. This provided a baseline for comparison. In the second scenario, I applied alternative weights, assigning a higher importance to slope (40%) and reduced weights to the other factors. This alternative approach reflected a scenario where terrain steepness plays a more critical role in site selection. The final results were visualized in a side-by-side map layout, with consistent symbology and classif...

  In the wake of Hurricane Sandy’s landfall in New Jersey, we conducted a GIS-based structural damage assessment focused on a section of the impacted coastline. The goal was to digitize damage data using FEMA-relevant categories and determine patterns in relation to distance from the shoreline. This assessment provided crucial insights that could support insurance claims, emergency response planning, and future risk mitigation strategies. To complete the analysis, we first created a polyline feature class to represent the pre-storm coastline using historical imagery. Then, using post-storm aerial photos, we manually digitized points for each structure along a specific stretch of the coast and classified them into five damage categories: No Damage, Affected, Minor Damage, Major Damage, and Destroyed. We created buffer zones at 100-meter intervals from the coastline to segment the structures into distance bands and used spatial analysis tools to calculate the number of structures per...