Sanid Chirakkal

About

Sanid Chirakkal received his Masters in Physicsfrom University of Calicut in 2009 and Ph.D. in Physical Sciences from Indian Institute of Space Science and Technology (IIST) in the year 2014. Dr. Chirakkal was a visiting fellow in the RS Labof the University of Trento, Italy in the year 2019as a part of India-Trento Programme for AdvancedResearch (ITPAR). Dr. Chirakkal joined Space Applications Centre (SAC/ISRO) in 2015 at the Microwave Techniques Development Division (MTDD). Dr. Chirakkal’s research interests are in the advanced areas of Synthetic Aperture Radar (SAR), such as SAR Polarimetry (PolSAR), Interferometry (InSAR) and Polarimetric SAR Interferometry (PolInSAR) as well as non-linear dynamical systems theory and mathematical ecology. After joining ISRO, Dr. Chirakkal contributed significantly toward the development of an indigenous SAR data processing software suite (MicrowaveData Analysis Software or MIDAS) which received an Indian copyright. In addition, he has played a key role in developing an end-to-end python based DInSAR processing tool for ISRO SAR missions and a PolInSAR module for forest height retrieval of Indian forests at SAC. Dr. Chirakkal received the ISRS (Indian Society of Remote Sensing) National Geospatial Award for the year 2020.

Employment

• Space Applications Centre Scientist
  2015 - Present

Education

• Indian Institute of Space Science and Technology Ph.D
  ? - 2014

Projects & Funding

Projects & funding information is unavailable.

Publications (15)

• A comparative study on the efficacy of dual-pol and full-pol ASAR data in radiative transfer modeling for forest above-ground biomass estimation
  International Journal of Remote Sensing 2024 DOI: 10.1080/01431161.2024.2302952
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• Seasonal Variability of Snow/Ice Facies Using Four Years of RISAT-1 MRS Data Over Glaciers in Himalayan–Karakoram Region
  IEEE Transactions on Geoscience and Remote Sensing 2023 DOI: 10.1109/TGRS.2023.3296683
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• Edge-Preserving classification of polarimetric SAR images using Wishart distribution and conditional random field
  International Journal of Remote Sensing 2022 DOI: 10.1080/01431161.2022.2054293
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• Polarimetric SAR Classification: Fast Learning with k-Maximum Likelihood Estimator
  2022 DOI: 10.1007/978-3-031-11346-8_25
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• Discrimination of multi-crop scenarios with polarimetric SAR data using Wishart mixture model
  Journal of Applied Remote Sensing 2021 DOI: 10.1117/1.jrs.15.034514
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• Modelling above ground biomass of Indian mangrove forest using dual-pol SAR data
  Remote Sensing Applications: Society and Environment 2021 DOI: 10.1016/j.rsase.2020.100457
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• A General Framework for Change Detection Using Multi-modal Remote Sensing Data
  IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 2021 DOI: 10.1109/jstars.2021.3119358
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• A knowledge-based approach for discriminating multi-crop scenarios using multi-temporal polarimetric SAR parameters
  International Journal of Remote Sensing 2019 DOI: 10.1080/01431161.2018.1558304
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• A Python Based InSAR Processing Tool For ISRO SAR Missions
  2019 URSI Asia-Pacific Radio Science Conference (AP-RASC) 2019 DOI: 10.23919/ursiap-rasc.2019.8738729
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• ANALYSIS OF PERFORMANCE OF FLAT EARTH PHASE REMOVAL METHODS
  ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences 2018 DOI: 10.5194/isprs-archives-xlii-5-207-2018
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