A V Kulkarni
Articles written in Journal of Earth System Science
Volume 113 Issue 1 March 2004 pp 117-128
The sensor onboard the satellite views the earth as a plain surface and consequently the satelliteobtained spectral radiances cannot represent true values over a mountainous terrain. The relative magnitudes of terrain slope and its aspect with respect to the sun's position will determine the amount of direct solar radiation incident on an undulating surface. Estimation of spectral reflectance from satellite data forms an important component in many of the snow and glacier studies. The spectral reflectance of snow is influenced by its various parameters. The changes in snowpack characteristics as a result of various metamorphic processes, with age, can cause variations in its spectral reflectances. Since, the terrain geometry also modifies the amount of reflected radiation from a rugged surface, one has to correct the estimated spectral reflectances for terrain topography so as to use them in deriving the snowpack characteristics accurately. Also, the amounts of melt runoff originating from glaciers having different slopes and orientations will not be the same. Considering these aspects, a model has been developed to estimate the terrain corrected spectral reflectances over the Himalayan terrain using the Linear Imaging Self Scanner-III data of the Indian Remote Sensing Satellite. The model computes spectral reflectances from satellitebased radiance measurements and includes the effect of the terrain topography on the incident solar radiation. The terrain slope and its aspect are generated from the digital elevation model of the region. The analysis carried out over the Beas Basin, Himachal Pradesh, India, indicated a variation of 22% in the amount of incident solar radiation for an increase of 10‡ in terrain slope. Further, the terrain with south-east aspect received maximum amount of solar radiation. The large differences observed between the uncorrected and terrain corrected reflectances in the shortwave infrared band (B5), which is not saturated over the snow covered region, suggest that the terrain slope and its aspect cannot be neglected in estimating the accurate spectral reflectances over the Himalayan terrain.
Volume 118 Issue 5 October 2009 pp 525-538
In the present paper,a methodology has been developed for the mapping of snow cover in Beas basin,Indian Himalaya using AWiFS (IRS-P6)satellite data.The complexities in the mapping of snow cover in the study area are snow under vegetation,contaminated snow and patchy snow. To overcome these problems,ﬁeld measurements using spectroradiometer were carried out and reﬂectance/snow indices trend were studied.By evaluation and validation of different topographic correction models,it was observed that,the normalized difference snow index (NDSI)values remain constant with the variations in slope and aspect and thus NDSI can take care of topography effects.Different snow cover mapping methods using snow indices are compared to ﬁnd the suitable mapping technique.The proposed methodology for snow cover mapping uses the NDSI (estimated using planetary re ﬂectance),NIR band reﬂectance and forest/vegetation cover information.The satellite estimated snow or non-snow pixel information using proposed methodology was validated with the snow cover information collected at three observatory locations and it was found that the algorithm classify all the sample points correctly,once that pixel is cloud free.The snow cover distribution was estimated using one year (2004 –05)cloud free satellite data and good correlation was observed between increase/decrease areal extent of seasonal snow cover and ground observed fresh snowfall and standing snow data.
Volume 120 Issue 2 April 2011 pp 321-328
Snow is a highly reflecting object found naturally on the Earth and its albedo is highly influenced by the amount and type of contamination. In the present study, two major types of contaminants (soil and coal) have been used to understand their effects on snow reflectance in the Himalayan region. These contaminants were used in two categories quantitatively – addition in large quantity and addition in small quantity. Snow reflectance data were collected between 350 and 2500 nm spectral ranges and binned at 10 nm interval by averaging. The experiment was designed to gather the field information in controlled conditions, and radiometric observations were collected. First derivative, band absorption depth, asymmetry, percentage change in reflectance and albedo in optical region were selected to identify and discriminate the type of contamination. Band absorption depth has shown a subtle increasing pattern for soil contamination, however, it was significant for small amounts of coal contamination. The absorption peak asymmetry was not significant for soil contamination but showed a nature towards left asymmetry for coal. The width of absorption feature at 1025 nm was not significant for both the contaminations. The percentage change in reflectance was quite high for small amount of coal contamination rather than soil contamination, however, a shift of peak was observed in soil-contaminated snow which was not present in coal contamination. The albedo drops exponentially for coal contamination rather than soil contamination.
Volume 122 Issue 4 August 2013 pp 957-966
Indian National Satellite (INSAT) 3A was launched in the year 2003 with communication and remote sensing payloads. The later payloads contain very high resolution radiometer (VHRR) and charge coupled devices (CCD) camera. In this paper, post-launch calibration of INSAT 3A CCD is discussed. A cross radiometric calibration was carried out with well calibrated advanced wide field of view sensor (AWiFS) of Indian Remote Sensing Satellite (IRS P6). Three concurrent scenes of December, January and February were used in this study. Calibration was carried out under different land cover classes such as snow, vegetation, forest, water and cloud. Regression analysis suggests correlation coefficient of 0.95, 0.92 and 0.60 for Red, NIR and SWIR channels with slope values 1.839, 1.589 and 2.232, respectively. New calibration coefficients were used to estimate at-sensor radiance and reflectance in all the three channels. Dynamic range of reflectances was found to be improved by using new calibration coefficients. Normalized difference snow index and vegetation index (NDSI and NDVI) have shown an improvement with new coefficients and were found closer to represent in situ data of different land covers and cloud.