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ABSTRACT:Remote sensing measurements from space born sensors are strongly attenuated by the scattering and absorption processes through atmospheric molecules, aerosols and gases (ozone, water vapour, oxygen etc). The process of removing the atmospheric interference from the satellite-level signal is called atmospheric correction. Atmospheric correction can be performed through various methods such as, empirical method, semi-physical method, detailed radiative transfer models. Various methods exist for atmospheric correction of available global sensors such as NOAA-AVHRR, MODIS-Terra/Aqua, MERIS, Landsat-TM/ETM etc. However, there was no method available for atmospheric correction of the IRS data sets. A new physics-based model called Scheme for Atmospheric Correction of ResourceSat-2 AWiFS data (SACRS2) has been developed at Space Applications Centre (SAC) specifically tuned for the RS2-AWiFS sensor. This model has been developed from theoretical signal simulations using the 6SV (The Second Simulation of the Satellite Signal in the Solar Spectrum vector version) code. A detail analysis was carried out to perform inter comparison of the results of SACRS2 model with standard atmospheric correction models such as FLAASH (Fast Line-of-sight Atmospheric Analysis of Spectral Hypercube) and 6SV on RS2-AWiFS data. In turn, the performance of all three models was compared to in-situ measurements carried out over an experimental site located in the Kutch desert for seven RS2-AWiFS overpasses. The results showed a fairly good match of reflectance derived by all three correction models with the in-situ measurements.

ABSTRACT:The Indian Remote Sensing (IRS) satellite series has been providing data since 1988 through various Earth observation missions. Before using IRS data for the quantitative analysis and parameter retrieval, it must be corrected for the atmospheric effects because spectral bands of IRS sensors are contaminated by intervening atmosphere. Standard atmospheric correction model tuned for the IRS sensors was not available for deriving surface reflectance. Looking at this gap area, a study was carried out to develop a physicsbased method, called SACRS2-a Scheme for Atmospheric Correction of Resourcesat-2 (RS2) AWiFS data. SACRS2 is a computationally fast scheme developed for correcting large amount of data acquired by RS2-AWiFS sensor using a detailed radiative transfer model 6SV. The method is based on deriving a set of coefficients which depend on spectral bands of the RS2-AWiFS sensor through thousands of forward signal simulations by 6SV. Once precise coefficients of all the physical processes of atmospheric correction are determined for RS2-AWiFS spectral bands then a complete scheme was developed using these coefficients. Major inputs of the SACRS2 scheme are raw digital numbers recorded by RS2-AWiFS sensor, aerosol optical thickness at 550 nm, columnar water vapour content, ozone content and viewing-geometry. Results showed a good performance of SACRS2 with a maximum relative error in the SACRS2 simulations ranged between approximately 2 to 7 percent with respect to reference 6SV computations. A complete software package containing the SACRS2 model along with user guide and test dataset has been released on the website (www.mosdac.gov.in) for the researchers.

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Heat Waves can have notable impacts on human mortality, ecosystem, economics and energy supply. The effect of heat wave is much more intense during summer than the other seasons. During the period of April to June, spells of very hot weather occur over certain regions of India and global warming scenario may result in further increases of such temperature anomalies and corresponding heat waves conditions. In this paper, satellite observations have been used to detect the heat wave conditions prevailing over India for the period of May-June 2015. The Kalpana-1 VHRR derived land surface temperature (LST) products have been used in the analysis to detect the heat wave affected regions over India. Results from the analysis shows the detection of heat wave affected pixels over Indian land mass. It can be seen that during the study period the parts of the west India, Indo-gangetic plane, Telangana and part of Vidarbh was under severe heat wave conditions which is also confirmed with Automatic Weather Station (AWS) air temperature observations.