Relevant bibliographies by topics / INSAT-3D Imager

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Academic literature on the topic 'INSAT-3D Imager'

Author: Grafiati
Published: 3 June 2025
Last updated: 1 August 2025

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Journal articles on the topic "INSAT-3D Imager"

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Prakash, S., D. Jindal, N. Badal, B. Kartikeyan, and B. Gopala Krishna. "Radiometric Quality Evaluation of INSAT-3D Imager Data." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-8 (November 28, 2014): 299–305. http://dx.doi.org/10.5194/isprsarchives-xl-8-299-2014.

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INSAT-3D is an advanced meteorological satellite of ISRO which acquires imagery in optical and infra-red (IR) channels for study of weather dynamics in Indian sub-continent region. In this paper, methodology of radiometric quality evaluation for Level-1 products of Imager, one of the payloads onboard INSAT-3D, is described. Firstly, overall visual quality of scene in terms of dynamic range, edge sharpness or modulation transfer function (MTF), presence of striping and other image artefacts is computed. Uniform targets in Desert and Sea region are identified for which detailed radiometric perfo
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Patel, P., H. Bhatt, and A. K. Shukla. "Absolute Vicarious Calibration of recently launched Indian Meteorological Satellite: INSAT-3D imager." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-8 (November 28, 2014): 291–98. http://dx.doi.org/10.5194/isprsarchives-xl-8-291-2014.

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Looking towards the advancements and popularity of remote sensing and an ever increasing need for the development of a variety of new and complex satellite sensors, it has become even more essential to continually upgrade the ability to provide absolute calibration of sensors. This article describes a simple procedure to implement post-launch calibration for VIS and SWIR channels of INSAT-3D imager over land site (Little Rann of Kutch (ROK), Gujarat) on three different days to account for characterization errors or undetermined post-launch changes in spectral response of the sensor. The measur
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Jindal, D., S. Prakash, J. Sanghvi, B. Kartikeyan, and B. Gopala Krishna. "INSAT-3D Quality Analysis System (i3dQAS)." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-8 (November 27, 2014): 257–63. http://dx.doi.org/10.5194/isprsarchives-xl-8-257-2014.

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INSAT-3D, an advanced meteorological satellite of ISRO carrying Imager and Sounder payloads is designed for acquiring data required for detailed climatological applications. At established data centres, Raw (L-0) data is processed to generate systematically corrected (Level-1) and geo-physical (Level-2) products which are further disseminated for use in climate related studies. Data quality evaluation (DQE) of basic data products of INSAT-3D is being operationally carried out at MOSDAC, Ahmedabad to monitor in-orbit sensor health, quantify data quality and provide feedback to various missions
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Venkat Ratnam, Madineni, Alladi Hemanth Kumar, and Achuthan Jayaraman. "Validation of INSAT-3D sounder data with in situ measurements and other similar satellite observations over India." Atmospheric Measurement Techniques 9, no. 12 (2016): 5735–45. http://dx.doi.org/10.5194/amt-9-5735-2016.

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Abstract. To date, several satellites measurements are available which can provide profiles of temperature and water vapour with reasonable accuracies. However, the temporal resolution has remained poor, particularly over the tropics, as most of them are polar orbiting. At this juncture, the launch of INSAT-3D (Indian National Satellite System) by the Indian Space Research Organization (ISRO) on 26 July 2013 carrying a multi-spectral imager covering visible to long-wave infrared made it possible to obtain profiles of temperature and water vapour over India with higher temporal and vertical res
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Gangwar, Rishi Kumar, and Pradeep Kumar Thapliyal. "Variational Based Estimation of Sea Surface Temperature from Split-Window Observations of INSAT-3D/3DR Imager." Remote Sensing 12, no. 19 (2020): 3142. http://dx.doi.org/10.3390/rs12193142.

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Infrared (IR) radiometers from geostationary (GEO) satellites have an advantage over low-earth orbiting (LEO) satellites as they provide continuous observations to monitor the diurnal variations in the sea surface temperature (SST), typically better than 30-minute interval. However, GEO satellite observations suffer from significant diurnal and seasonal biases arising due to varying sun-earth-satellite geometry, leading to biases in SST estimates from conventional non-linear regression-based algorithms (NLSST). The midnight calibration issue occurring in GEO sensors poses a different challenge
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Mishra, M. K., G. Rastogi, and P. Chauhan. "Operational Retrieval of aerosol optical depth over Indian subcontinent and Indian Ocean using INSAT-3D/Imager product validation." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-8 (November 28, 2014): 277–82. http://dx.doi.org/10.5194/isprsarchives-xl-8-277-2014.

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Aerosol optical depth (AOD) over Indian subcontinent and Indian Ocean region is derived operationally for the first time from the geostationary earth orbit (GEO) satellite INSAT-3D Imager data at 0.65 μm wavelength. Single visible channel algorithm based on clear sky composites gives larger retrieval error in AOD than other multiple channel algorithms due to errors in estimating surface reflectance and atmospheric property. However, since MIR channel signal is insensitive to the presence of most aerosols, therefore in present study, AOD retrieval algorithm employs both visible (centred at 0.65
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Dey, I., M. V. Shukla, P. K. Thapliyal, and C. M. Kishtawal. "Evaluation of operational INSAT-3D UTH product, using Radiosonde, Meteosat-7 and NCEP Analysis." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-8 (November 27, 2014): 247–52. http://dx.doi.org/10.5194/isprsarchives-xl-8-247-2014.

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Recently available satellite observations from the water vapor channel (6.5–7.1 μm) of the Imager on-board India's geostationary satellite, INSAT-3D have been used to estimate Upper Tropospheric Humidity (UTH). In this study, operationally retrieved UTH product has been compared and validated for the period of Jan–Jun, 2014, using in-situ and satellite measurements. In-situ measurements of UTH have been indirectly derived using humidity profiles obtained from a network of radiosonde stations from NOAA/ESRL database. Meteosat-7 UTH products have been used as satellite measur
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Satapathy, J., P. K. Thapliyal, M. V. Shukla, and C. M. Kishtawal. "Synergistic use of Imager Window observations for Cloud Clearing of Sounder Observation for INSAT-3D." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-8 (November 28, 2014): 315–20. http://dx.doi.org/10.5194/isprsarchives-xl-8-315-2014.

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The retrieval of atmospheric temperature and water vapor profiles from infrared Sounder are severely limited by the presence of cloud. Therefore, retrieval from infrared sounding observations is performed only over clear-sky atmospheric conditions. The probability of finding a clear-sky pixel at spatial resolution of 10 km is found to be very small globally. This study presents a quantitative analysis of the clear-sky probability that is carried out for different months over the Indian region for INSAT-3D Sounder. The probability of a clear-sky is found to be ~7 % for the field of view of 10 k
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Kumawat, Nandkishor, K. N. Babu, Mehul R. Pandya, Saurabh Tripathi, and V. Sathiyamoorthy. "Towards Accurate Radiometric Calibration of INSAT-3D and INSAT-3DR IMAGER: Addressing Uncertainty and Error Sources." International Journal of Remote Sensing 44, no. 20 (2023): 6298–328. http://dx.doi.org/10.1080/01431161.2023.2265541.

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Ojha, Satya P., and Randhir Singh. "Physical retrieval of sea-surface temperature from INSAT-3D imager observations." Tellus A: Dynamic Meteorology and Oceanography 71, no. 1 (2019): 1554421. http://dx.doi.org/10.1080/16000870.2019.1657767.

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Book chapters on the topic "INSAT-3D Imager"

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Shastry, K. Aditya, B. S. Aneesh, M. P. Chinmay, C. Gowtham Patel, and G. N. Shashank. "Enhancing Cyclone Preparedness: Deep Learning Methods with INSAT-3D Satellite Imagery." In Communications in Computer and Information Science. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-81369-6_16.

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Pal, Soumyajit, Uma Das, and Oishila Bandyopadhyay. "Detecting Tropical Cyclones in INSAT-3D Satellite Images Using CNN-Based Model." In Communications in Computer and Information Science. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-31407-0_27.

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Kumar, Divvela Vishnu Sai, Deepak Arora, and Shivam Tiwari. "Enhanced Cyclone Intensity Estimation Through CNN Analysis of INSAT-3D IR Imagery." In Lecture Notes in Networks and Systems. Springer Nature Singapore, 2025. https://doi.org/10.1007/978-981-97-8836-1_30.

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Kumar, Amit, Anil Kumar Singh, Nitesh Awasthi, and Virendra Singh. "Natural Hazard." In Interdisciplinary Approaches to Information Systems and Software Engineering. IGI Global, 2019. http://dx.doi.org/10.4018/978-1-5225-7784-3.ch006.

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Tropical cyclones are also known as typhoons or hurricanes. Also, special emphasis is given on the various aspects associated with cyclogenesis, like the six essential parameters required for cyclogenesis as given by W. M. Grey, and Dvorak technique is discussed in this chapter. INSAT-3D is an indigenous advanced dedicated meteorological satellite in geostationary orbit, which was launched on 26th July 2013. INSAT-3D was declared operational by IMD on 15th January 2014. INSAT-3D has four payloads, namely. IMAGER, SOUNDER, data relay transponder (DRT), and satellite aided search, aid and rescue
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Conference papers on the topic "INSAT-3D Imager"

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Vasanthi, D., A. Arul Jothi, Sivasakthi Thanigainathan, and H. Keerthivasan. "Cyclone Intensity Estimation Using INSAT-3D IR Imagery." In 2024 IEEE 5th India Council International Subsections Conference (INDISCON). IEEE, 2024. http://dx.doi.org/10.1109/indiscon62179.2024.10744256.

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Swetha, K., Neelima Gogineni, Gundeti Srinivas, E. N. Vijaya Kumari, Manohar Madgi, and T.Benarji. "Cyclone Intensity Estimation based on Deep Learning using INSAT-3D IR Image." In 2024 8th International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC). IEEE, 2024. http://dx.doi.org/10.1109/i-smac61858.2024.10714758.

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Parihar, Shailesh, A. K. Sharma, A. K. Mitra, et al. "Calibration strategy of INSAT-3D meteorological satellite imager using the moon at IMD, New Delhi." In SPIE Asia-Pacific Remote Sensing, edited by Allen M. Larar, Prakash Chauhan, Makoto Suzuki, and Jianyu Wang. SPIE, 2016. http://dx.doi.org/10.1117/12.2224543.

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Indira Rani, S., Ruth Taylor, John P. George, and E. N. Rajagopal. "Use of INSAT-3D sounder and imager radiances in the 4D-VAR data assimilation system and its implications in the analyses and forecasts." In SPIE Asia-Pacific Remote Sensing, edited by Eastwood Im, Raj Kumar, and Song Yang. SPIE, 2016. http://dx.doi.org/10.1117/12.2223496.

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Vayadande, Kuldeep, Tejas Adsare, Tejas Dharmik, Neeraj Agrawal, Aishwarya Patil, and Sakshi Zod. "Cyclone Intensity Estimation on INSAT 3D IR Imagery Using Deep Learning." In 2023 International Conference on Innovative Data Communication Technologies and Application (ICIDCA). IEEE, 2023. http://dx.doi.org/10.1109/icidca56705.2023.10099964.

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N, Uma, Jithin Vinod, K. M. Komal, and Joshua James. "Deep Learning Based Cyclone Intensity Estimation using INSAT-3D IR Imagery." In 2024 IEEE International Conference on Interdisciplinary Approaches in Technology and Management for Social Innovation (IATMSI). IEEE, 2024. http://dx.doi.org/10.1109/iatmsi60426.2024.10502881.

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Sena S, Divya Vasantha, Sanjay B, Julius Fusic S, and Hariprasad M. "Cyclone Intensity Estimation Based on Deep - Learning Using Insat 3D IR Imagery." In 2023 International Conference on Energy, Materials and Communication Engineering (ICEMCE). IEEE, 2023. http://dx.doi.org/10.1109/icemce57940.2023.10434169.

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A, Archana, Martina Jose Mary M, Shyamala Devi R, and Yogeshkannah K. "Cyclone Intensity Estimation Leveraging Graph Convolution Recurrent Networks and INSAT 3D Imagery." In 2024 IEEE International Students' Conference on Electrical, Electronics and Computer Science (SCEECS). IEEE, 2024. http://dx.doi.org/10.1109/sceecs61402.2024.10481869.

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A, Pugazhenthi, and Lakshmi Sutha Kumar. "Cloud Extraction from INSAT-3D Satellite Image by K-Means and Fuzzy C-Means Clustering Algorithms." In 2020 International Conference on System, Computation, Automation and Networking (ICSCAN). IEEE, 2020. http://dx.doi.org/10.1109/icscan49426.2020.9262330.

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