Instructional Resources for Integrating Remote Sensing and Geographic Information Systems (GIS)    

Integrated Geospatial Education and Technology Training (iGETT) is a National Science Foundation supported project that helps two-year colleges meet the growing workforce need for geospatial skills. It enables educators to provide instruction that integrates remote sensing and GIS and provides on-line teaching resources. These include materials used in iGETT summer institutes and webinars and more than 30 student exercises developed by iGETT participants. The exercises support contextual learning through case studies that teach students to download and analyze remote sensing data and integrate it with GIS.

All iGETT instructional resources are available free for educational use through the links in the tables below.  They are organized by topic and remote sensing knowledge level (basic, introductory, and intermediate). Most student exercises assume that students already know how to use Esri’s ArcGISÔ software. The exercises listed below use ArcGISÔ 10 for both GIS and remote sensing analysis.  Alternative versions that use MultiSpecÔor ArcGISÔ 9 and ENVÔI (from Excelis VIS) are also accessible from the table, along with over 20 additional exercises that use ArcGISÔ 9.3 and ENVIÔ. The last section of the Table lists three Tutorials for use with students or faculty. 




Description/Title and Link to Resource

Competencies/Time Required

Remote sensing concepts and Landsat Imagery


PowerPoint explaining remote sensing concepts and Landsat data. (PPT)

Electromagnetic Spectrum, Landsat,
Basic scientific concepts – 1 lecture

Activity using a browser to access imagery and employ basic remote sensing concepts


Browser-based student exercises that introduce remote sensing concepts without downloading software
(Word / Pdf)

Land Use Change and NDVI – 1 lecture and lab

 Downloading remote sensing imagery from GloVis


Online video or step-by-step instructions for accessing and downloading Landsat images (Word)

Downloading imagery data from the web - One lab 



Description/Title and Link to Resource

Competencies/Time Required

Land Cover Change


Tracking Land Cover Change in the San Fernando Valley, California (Html / Word)

Download data, Pixel Values, Band Composites, NDVI, Unsupervised Classification – 2 lectures and 2 labs  

 Agriculture – Land Use Change and Drought

Examining Drought and Land Use Conflicts in Sudan ( Word)

Downloading MODIS data
Installing Custom Toolboxes
Importing NDVI
Creating appropriate maps


Using Soil Productivity to Assess Agricultural Land Values in North Dakota (Html / Word)

File management, accessing non-imagery and imagery data, Crop Productivity Index, composite images, unsupervised classification

Natural Hazards - Flooding

Determining Flood Risk in Iowa
(Html / Word)

Download data, Normalized Difference Water Index, Landsat and Spot imagery. Vector and raster integration, use of tools (Imagery and Spatial Analyst) to study flood boundaries

Land Cover Change

Comparing Land Cover Change and
Stream Quality in North Carolina

Land cover classification, land use, download data, clip, composite bands,  unsupervised classification, change detection, map creation



Description/Title and Link to Resource

Competencies/Time Required


Evaluating Insect Damage to Forest Resources in New Mexico (four-part exercise) (Html / Word)

Access Orthophotos, Landsat and Aster images, clipping, NDVI, composite images, use of shapefiles and GPS data, synthesis and analysis of vector and raster data.  2 lectures; 2 labs

Land Cover Change

Quantifying Land Cover Change in Maine (Html / Word)

Download Landsat from multiple dates, digital data to radiance, raster calculator, radiance to reflectance, cloud mask, digitize, composite bands, NDVI, supervised classification, training samples, ModelBuilder and workflow, change detection.  4 Lectures; 4 Labs.

Disaster Management -Wildfire

Mapping Wildfire Burn Severity in California (Word)

Download Landsat, digital number of pixel, composite images, readme files, training samples, supervised classification, create map layout.
2 Lectures; 2 labs.

Disaster Management - Wildfire

Classifying Wildfires in Southwestern United States (two-part exercise)
(Html / Word)

File management, download Landsat data, pixie values, composite bands, band combinations, GIS Data and overlays, spectral response, digital number to radiance to reflectance, NBR, dNBR, Classify, raster to vector, aggregate/cluster analysis, summary statistics. 2 lectures; 2 labs

The introductory and intermediate exercises listed above are also available in versions that use
MultiSpecÔ or ENVIÔ and ArcGIS 9.3.1Ô software. 
Click here for more information about 20 additional exercises based on ENVIÔ and ArcGISÔ 9.3.1.

Click here for additional links to resources including PowerPoints, videos, and
other materials used in iGETT




Description/Title and Link to Resource

Competencies/Time Required

Us of Imagery Tools in
ArcGIS 10

Teaches the use of many of the new imagery tools in ArcGIS 10 (assumes prior ArcGISÔ use) (Html)

Comprehensive list of common remote sensing techniques using Imagery and Classification Tools in ArcGISÔ 10.  One  to 5 lectures and Labs depending on the number of modules presented

Introduction to ArcGISÔ 10 beginning with basic skills and advancing to intermediate skills based on Disasters - Landslides

Five part tutorial (assumes no familiarity with ArcGISÔ 10) beginning with basic to advanced use of ArcGIS 10 including ModelBuilder functions and basic remote sensing tools. The context is a case study of landslide susceptibility in California.
(Html / Word)

Teaches beginning to advanced GIS software use, analysis techniques including ModelBuilder, map algebra and use of Imagery tools.
1 to 5 lectures; 5 Labs

Fundamental Remote Sensing Concepts

Free, online (downloadable) tutorial on remote sensing and science concepts from Natural Resources Canada

Introduces basic to intermediate level remote sensing concepts.
3 to 5 lectures or chapters as self study

























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