Compared to non-imaging instruments, imaging spectrometers (ISs) can provide detailed information to investigate the influence of scene components on the bidirectional reflectance distribution function (BRDF) of a mixed target. The research reported in this article investigated soil surface reflectance changes as a function of scene components (i.e. illuminated pixels and shaded pixels), illumination and viewing zenith angles, and wavelength. Image-based BRDF data of both rough and smooth soil surfaces were acquired in a laboratory setting at three different illumination zenith angles and at four different viewing zenith angles over the full 360°azimuth range, at an interval of 20°, using a Specim V10E IS (Specim, Spectral Imaging Ltd., Oulu, Finland) mounted on the University of Lethbridge Goniometer System version 2.5 (ULGS-2.5). The BRDF of the smooth soil surface was dominated by illuminated pixels, whereas the shaded pixels were a larger component of the BRDF of the rough soil surface. As the illumination zenith angle was changed from 60°to 45°and then to 30°, the shadowing effect decreased, regardless of the soil surface. Soil surface reflectance was generally higher at the backscattering view zenith angles and decreased continuously to forward scattering view zenith angles in the light principal plane, regardless of the wavelength, due to the Specim V10E IS seeing more illuminated pixels in the backscattering angles than in the forward scattering angles. Higher soil surface reflectance was observed at higher illumination and viewing zenith angle combinations. For both soil surface roughness categories, the BRDF exhibited a greater range of values in the near-infrared than at the visible wavelengths. This research enhances our understanding of soil BRDF for various soil roughness and illumination conditions.
Ground reference data are important for understanding and characterizing angular effects on the images acquired by satellite sensors with off-nadir capability. However, very few studies have considered image-based soil reference data for that purpose. Compared to non-imaging instruments, imaging spectrometers can provide detailed information to investigate the influence of spatial components on the bidirectional reflectance distribution function (BRDF) of a mixed target. This research reported in this paper investigated soil spectral reflectance changes as a function of surface roughness, scene components and viewing geometries, as well as wavelength. Soil spectral reflectance is of particular interest because it is an essential factor in interpreting the angular effects on images of vegetation canopies. BRDF data of both rough and smooth soil surfaces were acquired in the laboratory at 30 o illumination angle using a Specim V10E imaging spectrometer mounted on the University of Lethbridge Goniometer System version 2.5 (ULGS-2.5).The BRDF results showed that the BRDF of the smooth soil surface was dominated by illuminated pixels, whereas the shaded pixels were a larger component of the BRDF of the rough surface. In the blue, green, red, and near-infrared (NIR), greater BRDF variation was observed for the rough than for the smooth soil surface. For both soil surface roughness categories, the BRDF exhibited a greater range of values in the NIR than in the blue, green, or red. The imaging approach allows the characterization of the impact of spatial components on soil BRDF and leads to an improved understanding of soil reflectance compared to non-imaging BRDF approaches. The imaging spectrometer is an important sensor for BRDF investigations where the effects of individual spatial components need to be identified.
Growing evidence of global climate change has led to global concerns over the vulnerability of agriculture to drought. Located in a semiarid environment, southern Alberta has suffered significant losses of agricultural productivity due to drought hazards in recent decades. Understanding the relationship between crop production and drought conditions is essential for coping with increasingly uncertain climate conditions. This study attempts to quantify the magnitude of crop production vulnerability to drought in southern Alberta. The standard precipitation index is used to measure drought stress in the region. The empirical results provide a detailed picture of the spatial variation in crop production vulnerability to varying drought conditions. Vulnerability maps from this study reveal that pockets in the study area may experience significant productivity loss given the existing level of adaptive capacity. While the irrigation districts have been associated with a lower level of vulnerability than dryland outside the irrigated region, uncertain water supply under varying climatic conditions coupled with increasing water allocation for non‐agricultural uses may increase the vulnerability in these districts.
This research investigates the relationship between agricultural production and the occurrence of meteorological droughts over time. A remote sensing approach is developed to estimate the yield of cereal crops based on the remotely sensed data in the study area. The yield estimates from remotely sensed imageries provide a primary data source to measure agricultural well-being and quantify agricultural vulnerability to drought. The drought condition as the stressor to agricultural production systems is characterized using the standard precipitation index (SPI). The results of the study indicate that crop production system in Southern Alberta is very vulnerable to drought. About half of the study area is associated with a high to extremely high vulnerability. If the drought trend in the recent past repeats itself in the near further, it can be expected that crop production in these areas will be seriously threatened.
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