These are reflections on data components I used for my GIS, Remote Sensing, and Modeling work.
The data is useful to estimate how fast the soil will warm and dry out. When spatially applied to a map it can suggest where winter annual weeds can take a foothold and take advantage of the site.
Aspect should be reclassified so NE sites have the lowest value and SW sites the highest value when used in a site susceptibility model.
Hill shade should use a date when the sun angle and azimuth is at maximum to show the land that gets full sun and areas with not so much direct sun.
If large weed patches are visible then an image will detect the patch. Nothing special about the sensor just the ability to collect large areas becomes critical when mapping invasive species. Timing and spatial resolution is the most critical to success. Ideally the background plants should be a difference color than the plants you want to detect. If the patch size is 1 m and the image spatial resolution is 30 m the patch will not be detectable. The worst case is to have scattered a invasion where the background vegetation masks the detection or to have the weeds and background vegetation the same color through the season, i.e. grasses.
Imagery was useful to identify sites susceptible to invasion rather than direct detect. My models used Blue, Green, Red and NIR bands plus NDVI (Normalized Difference Vegetation Index) as base components with additive components (elevation, slope, aspect and hill shade) with climate data to find sites susceptible to specific invasive species invasion on the landscape. The imagery is still being used to identify the large weed patches as well as vegetation that will support new invasion. Timing of image acquisition is critical and requires midsummer when greatest variability in green color and cloud free. Climate data includes annual rainfall, sunny days, min and max temperature for a 10 year average. Data gets old fast so update regularly. I also use a road and hydrology buffer to refine some model results for species associated with transportation and water. My models have a 10 meter resolution.
My modeling tool is MAHALCLASS in Terrset software. This soft classifiers defers making a definitive judgment about the class membership of any pixel but groups by assigning a degree of membership to each species in the training data. The math behind MAHALCLASS is based on Mahalanobis distance, a multivariate equivalent of a z-score.
GIS maps do not work for all when the data is misrepresented by the user. Check the data before blindly using.
Many users represent large spatial data as points or lines rather than polygon. Love one state based data set where 1,000 acre leafy spurge infestation was a point data. And a weed supervisor mapping his yellow starthistle infestation as all areas below 2,500 elevations. Interesting, but no value for using in GIS and Remote Sensing applications.
Layer data is old when positional error were tolerated. For example scanned ownership maps used by county may have property boundaries many feet off.
Susceptibility models do not work for all species and tends to be week on grasses that seem to be everywhere (annual bromes) or weeds that humans love to cultivate in fields. Sometimes we are our worst enemy and spread invasive species.
Areas where Susceptibility models have failed:
Utah State University declared my rush skeleton weed model failed, but on further examination 95% of failures were in:
County maintenance yards where county weed control workers stored equipment and chemicals
County managed gravel piles
School bus storage lots for rural schools
Public park's land where it was being renovated to reduce annual grassy weeds
Fremont County declared my leafy spurge model failed, but on further examination the failure was where equipment was brought in to make a new road through forest land. Sadly, the road was not on the map yet and the GIS filter did not detect.
A Nevada County Weed person complained by yellow starthistle model did not work in his county because he only had two small populations. He thought the areas indicating the site was susceptible look like it should be there but it was not. My comment to him was give it time because it is coming.