About Me
Hi. I am from Agra, India. I am a physicist and Geoinformation and Remote Sensing scientist with an M.Sc. in Physics from the Indian Institute of Science Education and Research (IISER) Mohali (2014), and an M.Sc. in GIScience and Earth Observation (GFM) from ITC (2018). I am now pursuing a Ph.D. with Dr. Ling Chang in SAR interferometry with focus on improving the InSAR parameter estimation using time series modelling and on developing robust disaster prediction models using precursory surface deformations. My research interests include light-matter interaction, image processing, Radar Remote Sensing, geodesy, and scientific computing. I have a passion for experimental physics, Newtonian mechanics, electromagnetism, radar data science and for developing tools dedicated towards environmental protection and disaster impact reduction. I have, in the past, been involved in projects related to Environment Management with IISc Bangalore and also for the development of efficient fleet management systems with the Logistics industry. My hobbies include doing yoga, playing football, reading non-fiction, socializing and hiking.
Expertise
Earth & Environmental Sciences
# Aboveground Biomass
# Modeling
# Scanner
# Sinkhole
# Time Series
Engineering & Materials Science
# Long Short-Term Memory
# Time Series
Social Sciences
# Regression
Faculty of Geo-Information Science and Earth Observation (ITC), Department of Earth Observation Science (EOS)Publications
Recent
Kulshrestha, A.
, Chang, L.
, & Stein, A. (2022).
Supervised LSTM modelling for classification of sinkhole-related anomalous InSAR deformation time series. 1-2. Abstract from EGU General Assembly 2022, Vienna, Austria.
https://meetingorganizer.copernicus.org/EGU22/EGU22-4618.html
Kulshrestha, A.
, Chang, L.
, & Stein, A. (2021).
Sinkhole scanner: A new method to detect sinkhole-related spatio-temporal patterns in insar deformation time series.
Remote sensing,
13(15), 1-20. [2906].
https://doi.org/10.3390/rs13152906
Mukhopadhyay, R., Kumar, S.
, Aghababaei, H.
, & Kulshrestha, A. (2021).
Estimation of aboveground biomass from PolSAR and PolInSAR using regression-based modelling techniques.
Geocarto international.
https://doi.org/10.1080/10106049.2021.1878289
Courses Academic Year 2021/2022
Courses in the current academic year are added at the moment they are finalised in the Osiris system. Therefore it is possible that the list is not yet complete for the whole academic year.
Courses Academic Year 2020/2021
Contact Details
Visiting Address
University of Twente
Faculty of Geo-Information Science and Earth Observation
ITC
(building no. 75), room 2-038
Hengelosestraat 99
7514AE Enschede
The Netherlands
Mailing Address
University of Twente
Faculty of Geo-Information Science and Earth Observation
ITC
2-038
P.O. Box 217
7500 AE Enschede
The Netherlands