Geospatial Technologies Lab Solutions and Services

At the Geospatial Technologies Laboratory we are committed to providing geospatial solutions for our graduate students, faculty and partners in the areas of geographic information systems, global positioning systems, remote sensing, landscape ecology, and home range applications for wildlife and habitat management. When starting a project please consider the following:




Before you start a research project that requires spatial data and analysis we suggest the following solutions via our ERSI web courses or GIS courses provided by the Department of Geosciences:




  • Basics of map projections


  • Finding Geographic data in ArcGIS


  • Referencing data to real-world locations using ArcGIS


  • Getting started with GIS


Once you are ready to start your research project the following spatial solutions are available:




1. Geographic information systems




a. Software: ESRI ArcGIS, Quantum GIS, and Open Jump


b. Solutions:




i. Feature creation (points, lines, polygons)


ii. Raster and vector data fusion


iii. Distance estimation between features


iv. Data import and export


v. Geoprocessing tools


vi. Random point generation


vii. Mapping and cartography


viii. Spatial data quality assurance and quality control


ix. Creating and editing metadata


x. ArcGIS online services


xi. Solving spatial problems using ArcGIS




2. Global positioning systems




a. Software: ArcPAD, Collector.


b. Solutions:




i. Field data collection


ii. Data integration in GIS


iii. GPS training




3. Remote sensing




a. Software: ERDAS imagine, Terrset


b. Solutions:




i. Data acquisition


ii. Data pre-processing


iii. Image classification


iv. Principal component analysis


v. Water extraction models


vi. Indices estimation (e.g. normalized difference vegetation index [NDVI])


vii. Data post-processing


viii. Data fusion


ix. Time series analysis


x. Remote sensing data integration with ArcGIS


xi. Unmanned aerial vehicle data collection


xii. Unmanned aerial vehicle data analysis


xiii. 3D models in remote sensing




4. Landscape Analysis




a. Software: Fragstats, CONEFOR, ArcGIS, R


b. Solutions:




i. Point pattern analysis


ii. Graph theory analysis


iii. Landscape pattern analysis


iv. Spatial autocorrelation analysis


v. Random point analysis


vi. Focal statistics


vii. Spatial aggregation


viii. Basics of animal movement


ix. Connectivity analysis


x. Fragmentation analysis


xi. Landscape spatial and temporal dynamics


xii. Landscape conservation design




5. Home Range analysis




a. Software: BIOTAS, HRT, Animal Space use, Open Jump, R


b. Solutions:




i. Home range estimation in BIOTAS


ii. Home range estimation in HRT


iii. Home range estimation in Animal Space use


iv. Home Range Estimation in Open Jump


v. Home range estimation in R (click here to view "Analyzing Wildlife Telemetry Data in R" by John Leonard)




6. Additional solutions:




i. Habitat suitability modelling


ii. Location calculation from telemetry data