This project evaluates the potential visual impact of proposed wind turbines within a mountainous landscape using terrain-based visibility modeling and 3D visualization techniques. The objective was to identify areas from which one or more turbines would be visible and to assess how local topography influences visual exposure across the surrounding region.
A high-resolution digital elevation model (DEM) was obtained from the U.S. Geological Survey and processed within ArcGIS Pro. Proposed turbine locations were digitized as point features and attributed with realistic structure heights to represent modern utility-scale wind turbines. The DEM served as the primary surface for terrain analysis and 3D rendering.
A frequency-based viewshed analysis was performed using the DEM and turbine point features to model line-of-sight visibility across the landscape. Observer offsets were derived from turbine height attributes, while a standard human eye-level offset was applied to represent ground-level viewing conditions. The resulting raster quantifies cumulative visibility, indicating the number of turbines visible from each location rather than a simple visible/non-visible classification.
The viewshed results were visualized in both two-dimensional map layouts and a three-dimensional local scene. The 3D environment integrates terrain, satellite imagery, extruded turbine features, and semi-transparent visibility layers to illustrate how ridgelines, slopes, and elevation changes limit or enhance visual exposure. Terrain profile concepts and line-of-sight relationships were emphasized to support interpretability.
The final outputs combine spatial analysis with clear cartographic and 3D visualization techniques, demonstrating practical skills in terrain modeling, raster analysis, attribute-driven geoprocessing, and environmental visualization. This project reflects workflows commonly used in environmental impact assessments, renewable energy planning, and visual resource management, and highlights the use of GIS to support spatial decision-making.
This analysis supports early-stage renewable energy planning by identifying areas where wind resources, terrain constraints, and land-use considerations align. By integrating spatial suitability modeling with environmental context, the results help planners and developers prioritize viable turbine locations before committing to costly field studies. The workflow is designed to reduce siting risk, surface conflicts early, and provide clear, defensible spatial justification for planning and stakeholder discussions.
