Newer imaging spectrometers require more experience to extract the full potential of the information embedded in the remote sensing data. In this report we highlight several analytical methods useful for detecting mine sites and mineral analysis. Monitoring and evaluation of geological conditions and hazardous wastes using remote sensing almost inevitably requires some assessment of vegetation condition or land cover disturbance, typically either observing poor vegetative growth or bare zones. Many mines or mineral outcrops or contaminant sources have small point-source locations within a larger geologic and ecological context. Often the goal is to identify these point sources due to their contrast with the surrounding vegetation and terrain.
Numerous factors create variability in satellite images that are imposed at multiple scales.
Topographic patterns, illumination conditions, and atmospheric composition at the time of measurement are factors that vary at larger spatial scales and need to be accounted for in the analysis. Of the factors affecting local scale are evidence of disturbance, low or no vegetation cover, and changes in vegetation distribution. Often only simple image analysis procedures are needed to extract information when combined with other spatial data, which overlays with mine site locations can provide. Because the department has a mines location database, this information will allow overlaying the site locations over the image to detect evidence for correct identification of mine locations, apparent size and extent of tailings and disturbance, evidence for erosion, and off-site transport. In addition to spectral methods, there are a number of methods to examine images for texture or spatial patterns in vegetation distribution that can be combined with ancillary data to improve predictions of site condition.