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