Effect of grain size on remotely sensed spectral reflectance of sandy desert surfaces

2004 ◽  
Vol 89 (3) ◽  
pp. 272-280 ◽  
Author(s):  
Gregory S Okin ◽  
Thomas H Painter
2010 ◽  
Vol 2 (2) ◽  
pp. 416-431 ◽  
Author(s):  
Craig S. Daughtry ◽  
Guy Serbin ◽  
James Reeves ◽  
Paul Doraiswamy ◽  
Earle Raymond Hunt

2008 ◽  
Vol 49 ◽  
pp. 139-144 ◽  
Author(s):  
E. Zege ◽  
I. Katsev ◽  
A. Malinka ◽  
A. Prikhach ◽  
I. Polonsky

AbstractThis paper presents a new simple and efficient algorithm to retrieve the effective snow grain size and soot concentration from spectral reflectance on snow measured by optical instrument on a satellite. This algorithm was recently developed and will be used for integrated ice–atmosphere–ocean monitoring in the framework of the DAMOCLES program. The algorithm is based on an analytical approach to snow optics. In this approach snow is considered as a close-packed medium with irregularly shaped grains rather than with independent spherical particles. Unlike the known conventional algorithms, the developed algorithm uses no a priori snow optical model. The analytical nature of this algorithm provides a very fast inversion of the reflection data. The developed algorithm was realized and validated for the GLI and MODIS instruments. The algorithm can be generalized for other satellite instruments with appropriate spectral channels. Finally, the results of verifications using a computer simulation are discussed.


2011 ◽  
Vol 5 (1) ◽  
pp. 203-217 ◽  
Author(s):  
H. S. Negi ◽  
A. Kokhanovsky

Abstract. In the present paper, spectral reflectance measurements of Himalayan seasonal snow were carried out and analysed to retrieve the snow albedo and effective grain size. The asymptotic radiative transfer (ART) theory was applied to retrieve the plane and spherical albedo. The retrieved plane albedo was compared with the measured spectral albedo and a good agreement was observed with ±10% differences. Retrieved integrated albedo was found within ±6% difference with ground observed broadband albedo. The retrieved snow grain sizes using different models based on the ART theory were compared for various snow types and it was observed that the grain size model using two channel method (one in visible and another in NIR region) can work well for the Himalayan seasonal snow and it was found consistent with temporal changes in grain size. This method can work very well for clean, dry snow as in the upper Himalaya, but sometimes, due to the low reflectances (<20%) using wavelength 1.24 μm, the ART theory cannot be applied, which is common in lower and middle Himalayan old snow. This study is important for monitoring the Himalayan cryosphere using air-borne or space-borne sensors.


Author(s):  
Mark Jakubauskas ◽  
Kevin Price

Remotely sensed multispectral data collected from satellites provide a systematic, synoptic ability to assess conditions over large areas on a regular basis. Early use of this satellite data for land cover mapping was based on spectral differences of cover types, with little integration of ancillary data such as soils or topographic information (Iverson et al. 1990). In recent years, concurrent with trends toward integrating remotely sensed and ancillary data for improved classification accuracy (Cibula and Nyquist 1987; Frank 1988), there has been increasing interest in utilizing remotely sensed data for extracting biophysically important variables, relating observed spectral reflectance to leaf area index, biomass, net primary productivity, and vegetation moisture content (Waring et al. 1986; Hobbs and Mooney 1990). The concept of using remotely sensed spectral data to map and monitor the progress of succession within forests and other environments has not been extensively explored. However, the capability to map and predict successional stages of forest habitat types on a landscape to regional scale has important implications for animal habitat management, assessment of insect infestation susceptibility, prediction of fire behavior, and evaluation of plant and animal species diversity. Ecological models based on established successional change rates and trends permit the prediction of future environmental conditions, landscape patterns, and the propagation and effects of disturbances across these landscapes (Hall et al. 1988; Romme 1982). Despain (1990) provides two examples where information on habitat and cover types is important for park management purposes: the cumulative effects model for grizzly bears; and the prediction, assessment, and management of mountain pine beetle outbreaks in conifer forests. Accurate mapping of habitat and cover types can provide information on the distribution and pattern of specific plant communities important to animal species for food, cover, and breeding ground (Knight and Wallace 1989). The ability to map and predict successional stages of forest habitat types has implications for prediction of fire behavior and spread. Previous studies (Despain 1990; Romme and Despain 1989; Romme 1982; Taylor 1969) have noted the relationship between forest age and fire susceptibility. Older stands are comparatively more flammable than younger stands due to fuel accumulations on the ground and in the canopy, and have a higher propensity to propagate and sustain extensive crown fires. Spatial patterns of cover types may also be important, with a highly fragmented landscape mosaic providing natural firebreaks under typical weather conditions. Consequently, as Despain (1990) has noted, the ability to map forest habitat and cover types is of importance for estimation of fire intensity and spread. The use of a single habitat type provides a logical unit for environmental stratification of the study site. Since a habitat type integrates vegetation, climate, topography, and soils (Pfister and Amo 1980), using a single habitat type forces a restriction to selective ranges in climate, topography, and soils types. These constrictions will minimize the effects of abiotic variation on the recorded spectral reflectance, allowing analysis of spectral variation to be concentrated on the changes in biotic factors associated with succession.


2002 ◽  
Vol 34 ◽  
pp. 71-73 ◽  
Author(s):  
Robert O. Green ◽  
Jeff Dozier ◽  
Dar Roberts ◽  
Tom Painter

AbstractTwo spectral snow-reflectance models that account for the effects of grain-size and liquid-water fraction are described and initial validation results presented. The models are based upon the spectral complex refractive index of liquid water and ice in the region from 400 to 2500 nm. Mie scattering calculations are used to specify the essential optical properties of snow in the models. Two approaches are explored to model the effect of liquid water in the snow. The first accounts for the liquid water as separate spheres interspersed with ice spheres in the snow layer. The second accounts for the liquid water as coatings on ice grains in the snow layer. A discrete-ordinate radiative transfer code is used to model the spectral reflectance of the snow for the Mie-calculated optical properties. Both the interspersed- and coated-sphere models show that the snow-absorption feature at 1030 nm shifts to shorter wavelength as the liquid-water content increased. The expression of these shifts is different for the two models. A comparison of the models with a spectral measurement of frozen and melting snow shows better agreement with the coated-sphere model. A spectral fitting algorithm was developed and tested with the coated-sphere model to derive the grain-size and liquid-water fraction from snow spectral reflectance measurements. Consistent values of grain-size and liquid water were retrieved from the measured snow spectra. This research demonstrates the use of spectral models and spectral measurements to derive surface snow grain-size and liquid-water fraction. The results of this research may be extended to regional and greater scales using data acquired by airborne and spaceborne imaging spectrometers for contributions to energy balance and hydrological modeling.


2001 ◽  
Vol 32 (1) ◽  
pp. 13-26 ◽  
Author(s):  
Tsutomu Nakamura ◽  
Osamu Abe ◽  
Tomohiro Hasegawa ◽  
Reina Tamura ◽  
Takeshi Ohta

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