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Precision Agriculture in the 21st Century: Geospatial and Information Technologies in Crop Management
meteorological data into expert systems. These points were reiterated by Moran et al. (1997) in a recent review of the potential of remote sensing to acquire information for identifying and analyzing site-soil spatial and temporal variability within fields.
In the past 10 years there have been rapid advances in acquiring and processing multispectral imagery with multispectral video by using digital cameras from aircraft. This approach has the flexibility of aerial photography acquisition and the advantage of digital multispectral imagery (Moran et al., 1996; Pearson et al., 1994). Although most planning and effort are going into the development of satellite systems, aircraft-acquired imagery may continue to be needed when extremely high resolution imagery is required. Aircraft platforms also provide an opportunity for developing and testing new sensors (i.e., thermal infrared and hyperspectral sensors) for future satellite systems.
A sequence of remotely sensed images over time can provide information about crop growth and the spatial variation within fields. Detailed spatially distributed multitemporal information, in visual form, is not readily obtainable from conventional crop management systems or from site-specific crop management methods. Remotely sensed images (i.e., color infrared aerial photographs or multispectral images acquired from satellites or airplanes) show spatial and spectral variation resulting from soil and crop characteristics. These images show the state or condition of fields when the images were acquired. One of the most useful aspects of remote sensing is its ability to generate images showing the spatial variation in fields caused by natural and cultural factors. This information is not limited by sampling interval or geostatistical interpolations (Moran et al., 1997). Images acquired at different times during a season can be used to determine changes such as growth rates and condition. These data, in turn, can be compared with data from previous years and may be helpful in predicting yield.
Commercial interest is growing in the potential of remote sensing to contribute to site-specific crop management, particularly as precision agriculture techniques are being developed and the possibility of routine, frequent acquisition of remote sensing data by satellites seems likely. Several earth-observing satellites are scheduled for launch over the next decade by governments and private industries. By 2005, 40 or more land observation satellites are expected be available (Stoney, 1996). Many of these satellites will acquire imagery with spatial resolutions ranging from 1-3 meters for panchromatic images to 3-15 meters for multispectral imagery. Others will have resolutions of 10-30 meters but with additional spectral bands, including thermal infrared on LANDSAT-7. Still other systems will collect radar data at varying resolutions. These sensors have promise for many types of measurements beyond identifying crop type, including monitoring crop stresses and condition, soil properties, and moisture. A major research challenge is the development of robust image analysis methods for agriculture, and a major educational need is training satellite data providers to meet agriculture needs.