## 2 Non Destructive Sensing
### Remote Sensing  
Remote sensing technology from ground, air, or space-based platforms is capable of providing detailed spectral, spatial and temporal information on vegetation health, and vigor; and it has significant crop yield estimation applications [90, 91, 92]. Spatial resolution is a measure of the smallest object detectable on the ground. The number of available image-forming pixels in the sensor itself, and its distance from the ground, contribute to determining the pixel-size on the ground and the overall image footprint. The smallest object that can be directly detected by the sensor is 30 m (Landsat) or 20 m (SPOT) in each dimension [93]. More recently, high resolution satellites such as IKONOS, which provides 4 m resolution multispectral imagery are available, but the cost of such data remains a significant impediment to its widespread use [94] IKONOS- panchromatic can provide 1 m resolution. Airborne mounted sensors such as airborne digital cameras or video systems, which are flown up to 3 km above the ground, generally have 1- to 2-m pixels and corresponding image footprints of the order of 100 Ha [94]. Radiometric resolution specifies the number of discrete spectral levels available to individual pixels to record the intensity of measured radiation from a target in a given waveband. In practice, however, n-bit systems tend to only have (n-2)-bits of information in image pixels as usually the lowest 2-bits of data carries the system noise, including dark-current and thermal noise [95, 96]. Temporal resolution or, more simply, revisit-frequency is an important attribute of any sensor when used for commercial monitoring or management purposes. Typical commercial satellites like the American Landsat and French SPOT satellites have revisit intervals of 16 and 26 days, respectively. IKONOS revisit timing ranges from 1 to 3 days. Aircraft mounted sensors, on the other hand, are more amenable to user-defined visitations, and have the added advantage of being able to operate under a high-cloud base. The spectral resolution is the number of wavebands of data that can be simultaneously recorded at each pixel. The amount of sunlight reflected off a target is described in terms of the target's reflectance profile. All photosynthesizing plants do not reflect much light in blue or red wavelengths because chlorophylls (and related pigments) absorb much of the incident energy in these wavelengths for the process of photosynthesis [97]. In the near infrared wavelengths (wavelengths greater than about 700 nm) photosynthesizing plants reflect large proportions of the incident sunlight (in excess of 65%). These wavelengths, to which the human eye is insensitive, can be detected by appropriate instruments. The amount of sunlight reflected in these wavelengths is very sensitive to leaf cell structure and this is influenced by water content [98]. A consequence of the upper limit on the amount of data that can be processed and stored in real-time by any remote sensing system is the compromise between spatial, radiometric and spectral resolution. In general, this equates to a trade-off between spatial and spectral resolution. The terms multispectral and hyperspectral are often interchanged, although they usually define instruments according to the number of wavebands of information that is recorded for each image pixel [97]. The more general adjective'multispectral' is used to describe instruments that record information in only a small number of wavebands; typically 2-10. Hyperspectral instruments record information in a large number of wavebands, typically greater than 10. Spectral vegetation indices reduce the multiple-waveband data at each image pixel to a single numerical value (index), and many have been developed to highlight changes in vegetation condition [99, 100]. Vegetation indices utilize the significant differences in reflectance of vegetation at green, red and near infrared wavelengths. Predicting the probability of biological invasion and probable invaders has been a long-standing goal of ecologists.