This project is to replace a physical, dedicated GIS workstation with an Azure Virtual Machine (VM). It is driven by the need to replace a physical desktop GIS workstation that has reached the end of its warranty and would otherwise require an updated hardware purchase every few years. Instead of committing to a fixed hardware configuration, the project proposes using an Azure virtual machine to run ArcGIS Pro, building on existing organizational use of Azure VMs for simulation and compute-intensive workloads. A virtualized GIS workstation allows CPU, GPU, memory, and storage resources to be adjusted over time as program needs change, rather than being locked into a single physical system. This approach improves performance for demanding GIS tasks while avoiding the cost and disruption of repeated hardware refresh cycles. In addition, the cloud-hosted environment provides low-latency access to shared datasets and enables GIS specialists to securely access the workstation from a wider range of locations and endpoint devices.

Documented evidence supporting this project includes an increase in requests to integrate data from multiple programs and sources into dashboard formats for UCF and SLM. The warrantee replacement cycle results in performance degradation as the hardware gets older with data volumes and analytical complexity predicted to grow. Updates to the State Forest Action Plan require processing increasingly large statewide datasets, and the addition of LiDAR to forest inventory measurements introduces substantially larger and more complex spatial datasets, including higher-resolution raster products for forest stewardship plan development. These workloads involve variable and difficult-to-predict compute demands that are less efficiently supported by fixed desktop resources. NJFS is already using a cloud-based virtual machine approach for simulation modeling, demonstrating improved performance and more efficient resource use. The project is further supported by an established governance structure through the ongoing DoIT and BGIS partnership.

Setup complete and operational by April 3, 2026