comparison of ground-ag贵宾会

research and technological advances in the field of remote sensing have greatly enhanced the ability to detect and quantify physical and biological stresses that affect the productivity of agricultural crops. recently, researchers have evaluated remote-sensing techniques for estimating the nitrogen (n) status of growing crops by determining the appropriate wavelength or combination of wavelengths to characterize crop n deficiency (gitelson, girtz, and merzlyak 2003; schlemmer et al. 2005). reflectance in specific visible and near-infrared regions of the electromagnetic spectrum has proved useful in detection of plant stresses that can sometimes be related to nutrient deficiencies after additional evaluation. the spectral quality of light reflected from leaves has long been relied upon as an indicator of plant stress and crop vigor. the spectral characteristics of radiation that is reflected, transmitted, or absorbed by leaves can provide specific information about the physiological response to growth conditions and plant adaptations to the environment. it is commonly reported that plant leaves have a low reflectance in the visible spectral region because of strong absorption by chlorophyll and relatively high reflectance of near-infrared radiation because of internal leaf scattering. several studies have shown good relationships among spectral reflectance, chlorophyll content, and n status in green vegetation (blackmer et al. 1996a). vegetation indexes provide a very simple yet elegant method for extracting the green plant quantity signal from complex canopy spectra. the use of reflectance ratios to analyze spectra has allowed the identification of reflectance bands corresponding to the absorption bands of specific pigments (chappelle, kim, and mcmurtrey 1992). many indexes computed as differences, ratios, or linear combinations of reflectance in visible and near infrared (nir) wavebands (richardson and wiegand 1977; tucker 1979; wiegand et al. 1991) have been used for evaluation of various vegetation parameters. sometimes these index values can be misleading when multiple stresses occur (schepers et al. 1996). multispectral vegetation indices derived from crop-canopy reflectance data in relatively wide wavebands can be used to monitor the growth response of plants in relation to environmental factors. specifically, ground-based crop-canopy sensors can measure the amount of light reflected from nearby surfaces such as leaf tissue or soil and are in contrast to aircraft or satellite platforms that generate photographs or various types of digital images.