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.



Remote Sensing
GRS has extensive experience in developing high quality GIS data from digital imagery. Whether collected from aircraft or satellites, digital images can be used as a very cost-effective source material for developing an accurate and complete land base for your GIS. GRS has thousands of hours of experience using aerial and satellite imagery from a wide variety of government and private sources. We have compiled geospatial data for both small and large projects ranging from subdivisions to hundreds of thousands of acres.