Background and activities
Hossein Nahavandchi is a professor of geodesy. His research interest is Earth monitoring/climate change using satellite (Gravimetry/Altimetry/GPS) data.
Biography: Hossein Nahavandchi holds a PhD degree (1998) from Royal Institute of Technology in Stockholm. His primary research interest is satellite Gravimetry, Altimetry and GPS. He has been lecturing in the Geomatics and Geodesy fields since 1990. Hossein’s career includes being a member of staff at Isfahan University (as Senior Lecturer and Head of Department), Royal Institute of Technology in Stockholm (as Research Associate), Tehran University (as Assistant Professor), and Norwegian University of Science and Technology (as Associate Professor and Professor). He also worked for Iranian National Mapping Authority and National Cartographic Center (NCC) in several functions. He has been Vice-Dean, Dean, and the Rector of the College of Engineering, Division Director, Chair of the Borad and Board member of Research and Planning Division, and Education Department in Iran. His research projects and other activities in Civil Engineering have attracted more than 120 million NOK to the university sector since 1991. They have also resulted in a strong international network. Over 155 publications and presentations are the results of his research projects.
My Research/Teaching Interests:
Current Research: GNSS Remote Sensing of the Arctic and Ocean using Spaceborne Reflectometry (Joint project of NTNU with GFZ)
Remote sensing using the signals of Global Navigation Satellite System (GNSS) is an established method providing a new source of observations for the study of the Earth and its atmosphere. GNSS Reflectometry (GNSS-R), a novel Earth observation technique, exploits the reflected GNSS signals from the land or water bodies to retrieve information about different geophysical parameters. This technique, in ground-based, air- or spaceborne configuration, has been widely used and still is being pursued for a variety of applications over land, ocean and ice. Different processing approaches could be used or developed to retrieve unprecedented high spatiotemporal resolution scatterometric or altimetric measurements from the reflectometry observations.
Several GNSS-R sensors onboard small satellite missions have already demonstrated the feasibility and competence of this technique. Although NASA CYGNSS (CYclone GNSS) mission currently provides GNSS-R data stream over tropical regions, the higher latitude regions as well as Polar waters are yet to be covered.
The joint project of Norwegian university of science and technology (NTNU) with GFZ will investigate the theory and design of an Earth remote sensing sensor onboard small satellites capable of measuring the oceanographic parameters related to altimetry in Norwegian and Polar waters. The project exploits GNSS-R (Global Navigation Satellite System - Reflectometry) concept which allows to use a relatively cost-efficient low-power passive sensor in a compact payload onboard future NTNU SmallSats.
The project provides required information about the methodology and instrumentation of an observing system with different geophysical parameters of interest such as sea ice thickness, sea surface height and wave height. The outcome will be implemented in the NTNU SmallSats and will be used operationally in an integrated maritime/Arctic observation network. It is foreseen to use in-situ measurements acquired by autonomous unmanned vehicle systems for calibration and enhancement of the GNSS-R products. The ultimate goal is to integrate the designed GNSS-R sensor in an integrated observation network to provide a high spatiotemporal resolution monitoring of the arctic and oceans, as the key components of the Earth’s climate system.
Left: Integrated Arctic and ocean observation network consisting of foreseen GNSS-R sensor onboard a SmallSat assisted and validated by low-altitude unmanned aerial vehicles (UAVs) and unmanned surface vehicles (USVs) for high resolution sea surface height and wave height measurements, and autonomous underwater vehicles (AUVs) for under-ice thickness measurements. Right: CYGNSS NBRCS (σ0) over two mid-latitude mesoscale ocean eddies near the south coast of Japan at two different times; in 3 dimensions in the local defined coordinate system. The evolution of the σ0 can be explained by the anomalies of sea surface temperature. The warm core of the top eddy produces higher wind speed (lower σ0) while the colder edges, by contrast, cause lower wind speeds (higher σ0).
Current Research: Assessing Groundwater depletion and dynamics using GRACE and hydrological data
Groundwater is a strategic reservoir and its shortage will cause the next global crisis. Water resource issues are often very complex and frequently require large amounts of diverse data. Collection of data by traditional means (e.g. fieldwork) can be quite difficult at times, especially in remote areas, as well as costly and resource intensive. The Gravity Recovery and Climate Experiment (GRACE) satellite gravity data can be very useful providing a cost-effective means of replacing or complimenting field data collection. GRACE satellites measure monthly changes in total terrestrial water storage by converting observed gravity anomalies into changes of equivalent water height. We use this methodology to process GRACE satellite-to-satellite tracking data to estimate groundwater depletion in the Middle East and a developed methodology to use GRACE data with enhanced spatial scale over Iran’s water basins. We remove leakage-in mass signals of the Caspian Sea and adding back the ocean model contribution that had apparently introduced a spurious positive trend over the Black Sea. To isolate the groundwater contributions, we develop a local hydrological model including soil moisture, snow, canopy, and river storage and subtract it from the GRACE total water storage results.
Groundwater changes in six different Iran's water basins using GRACE data between 2003 and 2013
Current Research: Quantifying land subsidence and groundwater exploitation using InSAR time series and in-situ measurements
Land subsidence due to the overdrafting of groundwater resources for industrial and agricultural purposes is a geological hazard that affects many urban and agricultural areas in the world. Several environmental effects and consequences are associated with land subsidence including damage to infrastructures and buildings, increased risk of flooding in coastal areas and accelerated erosion along Earth fissures and drainage systems. Monitoring the spatial extent and temporal evolution of surface deformation associated with fluid withdrawal is critical to mitigate hazards associated with this phenomenon. Among ground and space-based geodetic methods used for measuring land subsidence, space-borne InSAR enables a unique imaging capability for the assessment of subsidence in response to fluid extraction from subsurface reservoirs. Using SAR data from the ENVISAT, ALOS and Sentinel-1 satellites, we analyzed nearly a decade of land subsidence in the Rafsanjan region in Iran. An InSAR time-series analysis showed a persistent pattern of subsidence, with peak values found west of the city of Rafsanjan.
Average velocity maps derived from (a) ENVISAT descending, (b) ENVISAT ascending, (c) ALOS, (d) Sentinel-1 ascending, and (e) Sentinel-1 descending. The observation periods corresponding to the velocity maps are shown in (f).
We have also worked on large-scale national high-quality SAR monitoring of Norway. As an example, an interferogram over Norway has been shown in Figure below. We are working with ionospheric and tropospheric corrections.
An interfeogram over Norway using Sentinel-1 data
Standard methodology of the SAR and InSAR technique in displacement mapping has been improved. We implemented a polarimetric optimization approach on Sentinel-1 dual-polarization (VV–VH) images to improve the standard persistent scatterer interferometric synthetic aperture radar (PS-InSAR) method. Combining persistent scatterers (PS) and distributed scatterers (DS) is important for effective displacement monitoring using time-series of SAR data. However, for large stacks of SAR data, the DS analysis using existing standard algorithms becomes a time-consuming process. SqueeSAR is an approach for extracting signals from DS. We optimized this technique and evaluated the performance of our approach on 50 Sentinel-1 images acquired over Trondheim in Norway. We have made the SqueeSAR selection algorithm 98% more efficient and more robust in the case of few images. We implemented our approach in the StaMPS/MTI processing chain to deliver a time-series of combined PS and DS more efficiently than the existing StaMPS/MTI combined algorithm.
Surface displacement velocity over Trondheim with standard and optimized methods
Current Research: Quantifying water vapor contents by homogenization of GNSS time series
Quantifying water vapor, a major greenhouse gas of the atmosphere, is necessary for the climate and meteorological applications. Global Navigation Satellite System (GNSS) signals are promising measuring tools for monitoring water vapor content, but the use of GNSS products for estimating climatic trend requires homogeneity assessment in order to increase reliability and accuracy of the results. We have developed a data homogenization method based on singular spectrum analysis as a subspace-based technique. The ERA-Interim simulated data has been selected as the reference dataset. After homogenization, we used Principle Component Analysis (PCA) method to extract climate signals. We employed our developed technique over 214 permanent GNSS stations over Germany between 2010 and 2016 (7 years).
Left: A component of homogenized GNSS-derived dataset reflecting the overall classification of the climate in Germany. Right: The climatic divisions based on Köppen Climate Classification system.
Recently completed research: Greenland Ice-mass balance from satellite gravity observations
The Gravity Recovery and Climate Experiment (GRACE) satellite mission provides temporal variations of Earth gravity field with a period of around one month. GRACE measures changes in Earth's gravity field caused by regional shifts in the Earth's mass, including ice sheets, oceans and Water stored in the soil and in underground aquifers. We used GRACE data to estimate the rate of ice mass variability over Greenland. The Figure below shows monthly ice mass changes summed over the entire Greenland ice sheet, between April 2002 and February 2010, estimated in Gigatonne grom three GRACE data sets released by GFZ (Potsdam), JPL(California) and CSR (Texas). Note that this plot shows deviation from the average ice mass over the 2002 to 2010 period. It does not mean that the ice sheet was gaining ice before 2006 but that ice mass was over the 2002 to 2010 average. The ice mass was below the 2002 to 2010 average after 2006. The trend of the best fitting straight line for CSR data is -163±20 Gigatonne per year. The results also indicate the the ice-mass loss rate has been increasing in the time period between 2002 and 2010.
Recently completed research: Ocean circulation in North Atlantic and the Arctic sea from satellite altimetry observations
The Ocean plays a key role in determining the global climate. To develop techniques for pridicting furure climate, one must undrestand the dynamics of the global ocean circulation. A viable approach to observing the global and regional ocean circulations with sufficient resolution is the use of a satellite radar altimeter to measure the Mean Sea Surface (MSS) height. Multiple radar altimetry data from ESA satellites of ENVISAT, ERS-1 and ERS-2 and NASA satellite of GFO were used to determine the NTNU MSS model. NTNU MSS model is used to derive the mean dynamic topography and the ocesn circulation as it is shown in the Figure below. This plot shows the surface currents system in the North Atlantic and the Arctic sea for the time period 1993-2007. Flow of warm water is shown as red arrow and cold water as blue arrow. The Northward flow of warm water in the North Atlantic is partly balanced by southward flow of clod water in the East Greenland. Note that the detalied surface currents are not shown in this picture.
- Satellite Positioning GPS
- Satellite Gravimetry and Altimetry
- Climate Change Studies
- Polar Research
- Ocean Circulation and Transport
- TBA4852 Interdisciplinary Teamwork
- TBA4565 Geomatics, Specialization Course
- TBA4560 Geomatics, Specialization Project
- TBA4231 Applied geomatics
- TBA4236 Theoretical geomatics
- TBA4245 Geodesy
- TBA4251 Programming in geomatics
- TTT4234 Space Technology I
- TBA4925 Geomatics, Master Thesis
- BA8200 Advanced Theory of Errors and Adjustment
- BA8202 Advanced Physical Geodesy
- BA8604 Satellite Gravimetry and Altimetry
- BA8605 Advanced Global Positioning System (GPS)
- BA8203 An integrated Earth System Approach to the Study of Ocean Climate
- Arctic and Antarctic Mass balance (Ice loss) from satellite gravity and satellite altimetry measurements
- Ocean Circulation and Transport Between the North Atlantic and Arctic sea (OCTAS)
- New improvments in Geoidal height modeling
- Development of a regional GPS-based model of Ionospheric for Norway
- Arctic geoid for ocean circulation, sea-ice exploration and climate change
Scientific, academic and artistic work
A selection of recent journal publications, artistic productions, books, including book and report excerpts. See all publications in the database
- (2021) Remote Sensing of Precipitation Using Reflected GNSS Signals: Response Analysis of Polarimetric Observations. IEEE Transactions on Geoscience and Remote Sensing.
- (2021) On the Response of Polarimetric GNSS-Reflectometry to Sea Surface Roughness. IEEE Transactions on Geoscience and Remote Sensing. vol. 59 (9).
- (2020) Towards a zero-difference approach for homogenizing GNSS tropospheric products. GPS Solutions. vol. 24 (8).
- (2020) First Evidence of Mesoscale Ocean Eddies Signature in GNSS Reflectometry Measurements. Remote Sensing. vol. 12 (542).
- (2020) Modeling and Prediction of Regular Ionospheric Variations and Deterministic Anomalies. Remote Sensing. vol. 12 (6).
- (2020) Evaluation of CYGNSS Observations for Flood Detection and Mapping during Sistan and Baluchestan Torrential Rain in 2020. Water. vol. 12 (7).
- (2020) Improving tropospheric corrections on large-scale Sentinel-1 interferogramsusing a machine learning approach for integration with GNSS-derived zenithtotal delay (ZTD). Remote Sensing of Environment. vol. 239 (111608).
- (2019) Spaceborne GNSS-R Observations of Mesoscale Ocean Eddies; Preliminary Results from Cygnss Mission. IEEE International Geoscience and Remote Sensing Symposium proceedings.
- (2018) Persistent Scatterer Analysis Using Dual-Polarization Sentinel-1 Data: Contribution From VH Channel. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. vol. 11 (9).
- (2018) Efficient Ground Surface Displacement Monitoring Using Sentinel-1 Data: Integrating Distributed Scatterers (DS) Identified Using Two-Sample t-Test with Persistent Scatterers (PS). Remote Sensing. vol. 10 (5).
- (2017) Quantifying groundwater exploitation induced subsidence in the Rafsanjan plain, southeastern Iran, using InSAR time-series and in situ measurements. Engineering Geology. vol. 218.
- (2017) Accuracy investigation of UAV Photomapping. Kart og Plan. vol. 77 (3).
- (2017) Seasonal variation analysis of Greenland ice mass time-series. Acta Geodaetica et Geophysica Hungarica. vol. 53 (1).
- (2016) Deformation analysis of the Trondheim city from SAR Interferometry. ESA SP.
- (2016) Multi-sensor InSAR analysis of surface displacement over coastal urban city of Trondheim. Procedia Computer Science. vol. 100.
- (2015) GRACE-derived ice-mass loss spread over Greenland. Journal of Geodetic Science. vol. 5 (1).
- (2013) Ocean Wave Measurement Using GPS Buoys. Journal of Geodetic Science. vol. 3 (3).
- (2013) Steric sea level changes from ENVISAT and GRACE in the Nordic Seas. ESA SP.
- (2013) Geoid-type surface determination using a gravimetric quasigeoid model and GNSS/leveling data- A case study in eastern Norway. Kart og Plan. vol. 73.
- (2012) Mass balance and mass loss acceleration of the Greenland ice sheet (2002 – 2011) from GRACE gravity data. Journal of Geodetic Science. vol. 2 (2).