GRS has developed specialized algorithms and processes to enable the extraction of complex features from digital imagery. Our approach, called Discrete Classification, enables the use, evaluation, and identification of individual features and characteristics found in the image data set. GRS has developed Confusion and Fidelity Reports to identify sources of confusion, in terms of botanical/land cover characteristics and verify the fidelity of classification efforts before any actual image classification maps are ever developed. The ability to deal with individual training site data is a tremendous advantage over the more traditional clustered training data approach that is so often used. GRS has also performed projects requiring the manual interpretation and extraction of GIS features from digital photographic images as well as high-resolution satellite images. GRS image classification projects have resulted in the creation of complex GIS layers with associated database tables consisting of detailed quantitative descriptions of classified features.
Using satellite imagery, GRS is capable of mapping anywhere in the world. Currently available images, from mid-range resolution (like Landsat) to high-resolution, enable GRS to develop accurate and reliable vector, raster, and attribute data. GRS utilizes satellite imagery for land cover mapping, change detection analysis, forest land inventory, topographic 
modeling, and as a baseline data for future evaluation.
GRS is a leader in the use of Image Classification techniques to produce vegetation and land cover maps. Using proprietary techniques for image processing, GRS has successfully mapped millions of acres to a highly accurate level of detail. GRS is able to map specific vegetation estimates for timber size, species composition, percent vegetation cover, and vegetation structure.
GRS has developed GRS_covmatrixsum and GRS_aggregate for support of our innovative image processing techniques. These two processes are instrumental in the processing of image class maps and the aggregation of large scale raster data into smaller scale vector-based polygon databases.
GRS provides end-to-end solutions for landcover mapping including all aspects of the process from planning to reporting.
- Project Planning and Needs Assessment
- Field Sample Design
- Field Sampling Logistics
- Field Data Collection
- Vegetation and Ecological Ordination
- Image Acquisition
- Image Compilation and Quality Assurance
- Image Correction/Terrain Normalization
- Image Classification
- Pixel Aggregation into Polygons
- Segmentation
- Accuracy Assessment Sample Design
- Accuracy Assessment
- Map Production
- Reporting
