Chenghai Yang
U.S. Department of Agriculture 相关阅读

Remote sensing applications in precision agriculture and pest detection have been steadily increasing in recent years due to improvements in spatial and spectral resolutions of remote sensing imagery. Airborne multispectral and hyperspectral imagery has been more widely used for precision agriculture because of its finer spatial and spectral resolution than satellite imagery. However, recent launches of high resolution satellite multispectral sensors (i.e., IKONOS, QuickBird, GeoEye-1 and WorldView-2) should revitalize the scientific and commercial communities for more remote sensing research and applications in agriculture. With increased use of precision agriculture techniques, information concerning within-field yield variability is becoming important for effective crop management. Despite the commercial availability of yield monitors, many harvesters are not equipped with them. Moreover, yield monitor data can only be used for after-season management. Yield maps estimated from remote sensing imagery obtained during the growing season has the potential not only for after-season management, but also for within-season management. In addition to crop growth monitoring and yield estimation, airborne and high resolution satellite imagery has found many other precision agriculture applications, including soil mapping, water assessment, nutrient management and pest detection. Remotely sensed imagery has been used to map soil organic matter, soil moisture content, and soil salinity, but imagery alone has significant limitations in developing reliable maps of soil properties. A combination of imagery, ground-based sensors and laboratory testing is necessary for accurate soil mapping. Remote sensing has been used to monitor plant water status and measure evapotranspiration rates and crop coefficients for irrigation scheduling. This information enables farmers to more accurately adjust irrigation timing and amounts to avoid critical soil water deficits. Nutrient management is one of the main challenges facing crop production. Remote sensing has proven to be useful for detecting nitrogen deficiencies so that timely and site-specific application can be made to improve nitrogen use efficiency and avoid yield loss. However, monitoring other nutrient deficiencies can be a challenge. Any pest that causes sufficient plant stress to distort the reflectance characteristics of crop foliage is a candidate for detection by means of remote sensing. Remote sensing has been successful for detecting and mapping numerous crop pests (weeds, diseases and insects). However, early detection remains difficult. As remote sensing imagery is becoming more available and less expensive, it will present a great opportunity for both growers and researchers to more effectively use this data source for precision agriculture applications.
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