|YOUNG, KENDAL - Us Forest Service (FS)|
|Schrader, Theodore - Scott|
Submitted to: USGS - Scientific Investigations Report
Publication Type: Government Publication
Publication Acceptance Date: 6/30/2014
Publication Date: 7/15/2014
Citation: Young, K., Schrader, T.S. 2014. Predicting risk of invasive species occurrence - remote-sesning strategies. Scientific Investigations Report 2012-5162 Early Detection of Invasive Plants-Principles and Practices p. 59-77.
Interpretive Summary: Knowledge of invasive species occurrence, distribution, and potential invasion pathways is important in developing appropriate long-term monitoring protocols. Costs associated with ground-based visits, however, preclude the National Park Service from inventorying all associated park lands to determine invasive species presence. One potentially cost-effective approach in identifying potential occurrences of invasive species is to predict their distributions by using remotely sensed data and knowledge of species ecology and environ-mental tolerances. Once potential areas of invasive species occurrences are predicted, ground reconnaissance can be more effectively used and applied to an early-detection context for monitoring, verification, and control.
Technical Abstract: Remote sensing is a means to describe characteristics of an area without physically sampling the area. Remote sensors can be mounted on a satellite, plane, or other airborne structure. Remotely sensed data allow for landscape perspectives on management issues. Sensors measure the electromagnetic energy reflected from an object or area on the Earth’s surface. These sensors measure energy at wavelengths that are beyond the range of human vision. The guiding principal is that different objects (for example, soils, plants, buildings, water) reflect and absorb light differently at varying wave¬lengths. Graphically plotting the amount of radiation reflected at a given wavelength provides a unique signature for an object, especially if there is sufficient spectral resolution to distinguish its spectrum from those of other objects. Reflectance of clear water is typically low, with initial higher reflectance values in the blue end of the spectrum, which decreases as wavelength increases. Vegetation reflectance is typically low in both the blue and red regions of the spectrum due to absorption by chlorophyll. Because reflectance values peak at the green region, vegetation appears green. In the near infrared (NIR) region, reflectance is much higher than that in the visible bands due to leaf cellular structure. Therefore, vegetation can be identified by the high NIR but generally low visible reflectance. Spectral reflectance curves can be used to discriminate between vegetation types or plant species.