Resources

The Center for Applied Geographic Information Science (CAGIS) maintains advanced computing infrastructure, geospatial technologies, and field equipment to support computationally intensive geospatial research. These resources support GeoAI, spatial analysis and modeling, remote sensing, large-scale geospatial data processing, high-performance and parallel computing, spatial data management, field data collection, and Web GIS and application development.

In addition to CAGIS-managed computing infrastructure, researchers may use UNC Charlotte Research Computing resources for large-scale computational research. The University Research Computing, URC environment provides Slurm-based high-performance computing, including general-purpose CPU, large-memory, and GPU computing resources. CAGIS researchers may also leverage national-scale research cyberinfrastructure, including NSF ACCESS and the Open Science Grid, when appropriate for high-performance and high-throughput computing applications.

Computing Hardware

CAGIS maintains high-performance GPU workstations, large-memory systems, dedicated compute servers, and supporting computing infrastructure for research, teaching, and application development.

GPU and High-Memory Workstations

Amber – GPU Workstation

  • CPU: AMD Ryzen Threadripper PRO 5975WX, 32 cores, 3.6–4.5 GHz
  • GPU: Dual NVIDIA RTX A4500, 20 GB each
  • Memory: 128 GB
  • Storage: 1 TB NVMe + 4 TB HDD

Emerald – Large-Memory GPU Workstation

  • CPU: Intel Xeon w9-3475X, 36 cores, 2.2–4.8 GHz
  • GPU: NVIDIA RTX A6000, 48 GB
  • Memory: 1 TB
  • Storage: 4 TB NVMe

Diamond – GPU Workstation

  • CPU: AMD Ryzen Threadripper PRO 5975WX, 32 cores, 3.6–4.5 GHz
  • GPU: Dual NVIDIA RTX A4500, 20 GB each
  • Memory: 128 GB
  • Storage: 1 TB NVMe + 4 TB SSD

Onyx – CPU Workstation

  • CPU: Intel Xeon W-2295, 18 cores, 3.0–4.6 GHz
  • Memory: 64 GB
  • Storage: 3 TB NVMe

Wastewater – GPU Workstation

  • CPU: Intel Xeon W-2245, 8 cores, 3.9 GHz base frequency
  • GPU: Dual NVIDIA Quadro RTX 5000, 16 GB each
  • Memory: 64 GB
  • Storage: 512 GB SSD + 4 TB HDD

Compute Servers and Cluster

Data Center Server #1 – Research Services and Virtual Machines

  • CPU: Dual Intel Xeon Gold 6338N, 64 total cores, 2.2 GHz base frequency
  • Memory: 256 GB
  • Storage: 4 TB NVMe + 9 TB SSD + 8 TB HDD
  • Primary use: Research services, virtual machines, data services, and research application hosting

Data Center Server #2 – High-Performance Compute Server

  • CPU: Dual Intel Xeon Gold 6438M, 64 total cores, 2.2 GHz base frequency
  • Memory: 256 GB
  • Storage: Approximately 50 TB of local NVMe, SSD, and HDD storage
  • Primary use: Large-scale data processing, parallel computing, spatial modeling, and other computationally intensive research workloads

EEGS Research Server – High-Capacity Data and Compute Server

  • CPU: Dual Intel Xeon Gold 5420+, 56 total cores
  • Storage: 2 TB NVMe + 12 × 8 TB SSD
  • Primary use: High-capacity research data storage, large-scale data processing, and computational workloads

Windows Computing Cluster – 4 Nodes

  • Each computing node includes:
  • CPU: Intel Core i7-7700, 4 cores, 3.6–4.2 GHz
  • Memory: 16 GB
  • Storage: 256 GB SSD
  • Operating System: Windows

Legacy VM Server for Education

  • CPU: Intel Xeon E5-2603, 6 cores, 1.7 GHz
  • Memory: 16 GB
  • Storage: 4TB HDD

Legacy Storage Server for Backup

  • CPU: Intel Xeon E5-2660, 14 cores, 2.0 GHz
  • Memory: 32 GB
  • Storage: 4 × 8 TB SSD + 1TB OS

Field Hardware

CAGIS maintains a range of field instruments and platforms to support geospatial data collection, infrastructure inspection, remote sensing, and field-based research.

  • Trimble R12i GNSS System – Survey-grade GNSS receiver supporting high-accuracy RTK positioning and GIS field data collection.
  • Trimble GeoXM/XT – Rugged handheld GNSS devices for mobile mapping and field-based GIS data collection.
  • Laser Technology TruPulse® – Laser rangefinder for measuring distance, height, inclination, and remotely locating features during field surveys.
  • Anysun Self-Leveling Sewer Inspection Camera – 200-ft waterproof pipeline camera system for inspecting and documenting underground pipes, drainage systems, and other infrastructure.
  • DJI Phantom 4 Drone – Aerial imaging platform for field documentation, remote sensing, mapping, and photogrammetric applications.
  • DJI Matrice 400 Drone – Enterprise-grade drone platform supporting advanced aerial mapping, remote sensing, infrastructure inspection, and multiple sensor payloads.
  • Leo Rover 1.8 Ground Robot – ROS-based mobile robotic platform for autonomous navigation, mobile sensing, computer vision, and field research.

Computing Software and Development Technologies

CAGIS uses a combination of commercial, open-source, and AI-enabled technologies to support geospatial analysis, remote sensing, GeoAI, spatial data management, high-performance data processing, field data collection, and Web GIS and application development.

GIS and Spatial Analysis

  • ArcGIS Pro – desktop GIS, geoprocessing, spatial analysis, cartography, 3D analysis, and visualization
  • QGIS – open-source GIS, spatial analysis, geospatial data management, and visualization

Remote Sensing and Geospatial Data Processing

  • ENVI – remote sensing, image processing, and geospatial analysis
  • ERDAS IMAGINE – raster, imagery, and remote sensing analysis
  • GDAL/OGR – raster and vector geospatial data processing, transformation, and format conversion

Programming, Data Science, and GeoAI

  • Python – geospatial analysis, automation, large-scale data processing, modeling, APIs, and application development
  • R – statistical computing, spatial analysis, visualization, and research workflows
  • GeoPandas, Rasterio, NumPy, pandas, and scikit-learn – scientific computing, geospatial data processing, and machine learning
  • PyTorch and deep-learning frameworks – GeoAI, computer vision, spatial machine learning, and deep-learning research

AI-Assisted Research and Software Development

  • OpenAI ChatGPT – AI-assisted research, technical writing, workflow development, data and code interpretation, documentation, and research support
  • OpenAI Codex – agentic software development, code generation, debugging, testing, code review, refactoring, and application development

AI-assisted workflows are used with appropriate human review and verification and in accordance with applicable University data, security, and research requirements.

Spatial Databases and Enterprise GIS

  • PostgreSQL/PostGIS – relational and spatial database management, spatial querying, and large-scale geospatial data storage
  • ArcGIS Enterprise – enterprise GIS, geospatial services, data management, and Web GIS
  • ArcGIS Online – hosted mapping, data sharing, collaboration, dashboards, and web applications
  • GeoServer – open-source geospatial web services and interoperable spatial data publishing

Web GIS and Application Development

  • React – development of interactive web applications, dashboards, and geospatial user interfaces
  • JavaScript and TypeScript – client-side and full-stack web application development
  • MapLibre GL JS – high-performance interactive web mapping and geospatial visualization
  • OpenLayers and Leaflet – interactive web mapping and GIS application development
  • Python-based web and API frameworks – development of geospatial APIs, analytical services, dashboards, and decision-support applications

Field and Mobile GIS

  • ArcGIS Field Maps – mobile GIS, field data collection, asset inspection, and field operations
  • ArcGIS Survey123 – form-based surveys and geospatial field data collection
  • QField – open-source mobile GIS, offline field data collection, GNSS integration, and customized mobile geospatial workflows
  • GNSS-integrated GIS workflows – high-accuracy field mapping and research data collection