Development of a scheme for atmospheric correction of Resourcesat-2 AWiFS data

Pandya, Mehul R.; Pathak, Vishal N.; Shah, Dipti; Trivedi, Himanshu J.; Chipade, Radhika; Singh, R. P.; Kirankumar, A. S.

doi:10.1016/j.jag.2015.04.004

Cited by 10 publications

(7 citation statements)

References 20 publications

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“…A Physics based scheme SACRS2 physics based scheme for atmospheric correction of RS2 AWiFS, LISS-III and LISS-IV satellite datasets has been recently developed at SAC [13] . This SACRS2 scheme for AWiFS is available at http://www.mosdac.gov.in/tools/SACRS2_Package.rar (Fig.1).…”

Section: Methodology and Data Usedmentioning

confidence: 99%

“…This SACRS2 scheme for AWiFS is available at http://www.mosdac.gov.in/tools/SACRS2_Package.rar (Fig.1). Now we have also developed schemes for LISS -III and LISS -IV sensors using methodology described in our earlier paper [13]. In this paper we have carried out atmospheric correction of all three sensors using newly developed SACRS2 scheme and compared their results with in-situ measurements.…”

Section: Methodology and Data Usedmentioning

confidence: 99%

“…The atmospheric correction model for the RS -2 AWiFS, LISS -III and LISS -IV sensors, which are particularly important over the Indian subcontinental have not been incorporated in any of the software's till now. We have developed a physics based atmospheric correction scheme specifically tuned for RS2 AWiFS, LISS -III and LISS-IV sensors at SAC, Ahmedabad and that scheme is called Scheme for Atmospheric Correction of Resourcesat-2 (SACRS2) [13] .…”

Section: Introductionmentioning

confidence: 99%

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Retrieval of surface reflectance from Resourcesat-2 AWiFS, LISS-3, and LISS-4 data using SACRS2 scheme

Pathak

Pandya²,

Shah³

et al. 2016

SPIE Proceedings

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Satellite based multispectral imagery contains various quantitative information related to surface and atmosphere. To extract the accurate information about surface, we need to correct atmospheric influence which is introduced by the atmosphere. Atmospheric correction of multispectral satellite imagery is an important prerequisite to derive geophysical parameters from satellite data. In this study surface reflectance is retrieved using the Scheme for Atmospheric Correction of Resourcesat-2 (SACRS2). The SACRS2 is physics based atmospheric correction scheme developed at Space Applications Centre (SAC), ISRO based on radiative transfer model 6SV (The Second Simulation of the Satellite Signal in the Solar Spectrum vector version). SACRS2 method is easily applicable for atmospheric correction of multispectral data. A detail analysis has been carried out to retrieve surface reflectance from Resourcesat-2 AWiFS, LISS-3 and LISS-4 data using SACRS2 method. The retrieved surface reflectance from SACRS2 for AWiFS, LISS-3 and LISS-4 have been compared with in-situ reflectance measurements. The comparison showed a good match of reflectance derived by SACRS2 scheme with the in-situ measurements.

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Section: Methodology and Data Usedmentioning

confidence: 99%

Section: Methodology and Data Usedmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Retrieval of surface reflectance from Resourcesat-2 AWiFS, LISS-3, and LISS-4 data using SACRS2 scheme

Pathak

Pandya²,

Shah³

et al. 2016

SPIE Proceedings

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“…The pre-processing of the ground reflectance from ASD spectroradiometer included conversion of raw data to reflectance at 1 nm using the Viewspec software and conversion of narrow bands to LISS III equivalent bands using spectral response function (SRF) of LISS III while pre-processing of LISS-III data included DN to radiance conversion, radiance to surface reflectance conversion using the atmospheric correction module, SACRS2 (a Scheme for Atmospheric Correction of Resourcesat-2 (RS2) AWiFS data) developed at SAC (Pandya et al 2015), extraction of reflectance at the sampling sites. Five narrow band indices, viz.…”

Section: Optical Data Processing and Generation Of VImentioning

confidence: 99%

Monitoring Cotton (Gossypium sps.) Crop Condition through Synergy of Optical and Radar Remote Sensing

Haldar¹,

Tripathy²,

Dave³

et al. 2018

Preprint

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Morphological parameters like cotton height, branches, Leaf Area Index and biomass are mainly affected by the vegetation water content (VWC). Periodical assessment of the VWC and crop parameters is required for timely management of the crop for maximizing yield. The study aimed at using both optical and microwave remotely sensed data to assess cotton crop condition based on the above mentioned traits. Vegetation indices (VI) derived from ground based measurements (5 narrow band and 2 broad band VIs) as well as satellite derived reflectance (2 broad band VIs) were assessed. Regression models were derived for estimating LAI, biomass and plant water content using the ground based indices and applied to the satellite derived spectral index (from LISS-III) map to estimate the respective parameters. HH and HV polarization from RISAT-1 were used to derive Radar Vegetation Index (RVI). The coefficient of determination of the model for estimating LAI, biomass and vegetation water content of cotton with optical vegetation index as input parameter were found to be 0.42, 0.51 and 0.52, respectively. The correlation between RVI and plant height, date of planting in terms of the age of the crop and vegetation water content were found to range between 0.4 to 0.6. The fresh biomass from RVI showed spatial variability from 100 gm -2 to 4000 gm -2 while the dry biomass map derived from NDVI showed spatial variability of 50 to 950 g m -2 for the study area. Plant water content in the district varied from 65 to 85%. The correlation between optical vegetation index and RVI was not significant. Hence a multiple linear regression model using both optical index (NDVI and LSWI) and SAR index (RVI) was developed to assess the LAI, biomass and plant water content. The model showed a R 2 of 0.5 for LAI estimation but not significant for biomass and water content. This study show Preprints (www.preprints.org) | NOT PEER-REVIEWED | cased the use of combined optical and microwave (C band) remote sensing for cotton condition assessment.

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“…However, there is no method available for atmospheric correction of RS2 sensors. Recently a new physics based model has been developed namely, SACRS2 (Scheme for Atmospheric Correction of ResourceSat-2) Pandya et al(2014aPandya et al( ,2014b for RS2-AWiFS data. This paper reports the results of a study that was carried out to compare various atmospheric correction models for the RS2 -AWiFS data.…”

Section: Introductionmentioning

confidence: 99%

Inter Comparison of Atmospheric Correction Models - SACRS2, FLAASH and 6SV Using Resourcesat-2 AWiFS Data

Pathak

Pandya

Shah³

et al. 2014

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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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.

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Development of a scheme for atmospheric correction of Resourcesat-2 AWiFS data

Cited by 10 publications

References 20 publications

Retrieval of surface reflectance from Resourcesat-2 AWiFS, LISS-3, and LISS-4 data using SACRS2 scheme

Retrieval of surface reflectance from Resourcesat-2 AWiFS, LISS-3, and LISS-4 data using SACRS2 scheme

Monitoring Cotton (Gossypium sps.) Crop Condition through Synergy of Optical and Radar Remote Sensing

Inter Comparison of Atmospheric Correction Models - SACRS2, FLAASH and 6SV Using Resourcesat-2 AWiFS Data

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