Journal papers

Landslide susceptibility mapping using MT-InSAR and AHP enabled GIS based multi-criteria decision analysis


M. Devara, A. Tiwari, R. Dwivedi


Landslide susceptibility maps (LSMs) are generally prepared by integrating multiple prominent thematic layers, including DEM derived products (elevation, slope, and aspect), and other parameters such as lithology, geomorphology, LULC, etc. These parameters can be assigned optimum weights using the analytic hierarchy process (AHP) method, followed by a GIS-based weighted overlay analysis. In recent years, multi-temporal interferometric synthetic aperture radar (MT-InSAR) techniques have been rigorously explored, for land deformation detection and monitoring, by extracting highly stable measurement pixels using tens of SAR acquisitions simultaneously. In this research work, a GIS-based multi-criteria decision analysis to prepare LSMs is proposed, with MT-InSAR derived displacement estimates used as a critical input parameter. An LSM is generated by processing 20 ERS-1/2 and Envisat ASAR images, acquired over ∼120 sq. km wide river basin, located in Uttarakhand, India. The generated LSM is found to be congruent with the susceptible maps made available by the Geological Survey of India (GSI) under the National Landslide Susceptibility Mapping (NLSM) program. Preliminary results indicate that the majority of the unstable zones along the Alaknanda River are correctly identified. The approach is further implemented to generate an updated susceptibility map using 60 scenes of freely available Sentinel-1A dataset, followed by validation through actual field survey. This resulted in the generation of an updated susceptibility map, which helped in the identification of 44.5% new landslide susceptible zones (LSZs). Furthermore, the status of previously identified zones is also quantified. The performance of the proposed approach suggests its usability in generating and updating near-real-time LSMs. 

Spatial distribution of earthquake potential along the Himalayan arc


Y. Sharma, S. Pasari, K.-E. Ching, O. Dikshit, T. Kato, J.N. Malik, C.-P. Chang, and J.-Y. Yen


 To determine the spatial distribution of earthquake potential along the active Himalayan arc, we utilize GPS measurements and earthquake data. We derive horizontal velocity field and 2-D strain rates from a new set of 41 regional GPS stations along with 446 published velocities. We convert these strain rate tensors to geodetic moment rate build-up within 24 contiguous segments and compare to the seismic moment rate release derived from a reassessed earthquake catalog of 900 years. The geodetic to seismic moment rate ratio, an indicator of stored strain energy, varies from below unity to more than 50 in different segments. The estimated geodetic moment rate ranges from 1.7 × 1018 Nm/yr to 10.2 × 1018 Nm/yr, whereas the seismic moment rate ranges from 3.7 × 1016 Nm/yr to 5.1 × 1019 Nm/yr. This variation between the geodetic and seismic moment rate corresponds to a moment deficit rate of ~1.15×1017 Nm/yr to 7.97 × 1018 Nm/yr along various segments of the study region. The above moment deficit rate provides an equivalent earthquake potential of magnitude 5.7 − 8.2 in different segments. Specifically, the higher earthquake potential (Mw≥8.0) corresponds to the segments in the central seismic gap and the northeast part of Himalaya, whereas the lower earthquake potential (Mw<7.0) corresponds to the segments encompassing the rupture areas of recent large events. The present findings not only provide input constraints on the contemporary crustal deformation but also contributes to the time-dependent seismic hazard analysis along the Himalaya.

Contemporary Earthquake Hazards in the West-Northwest Himalaya: A Statistical Perspective through Natural Times


S.Pasari, Y. Sharma


 Himalayan earthquakes have deep societal and economic impact. In this article, we implement a surrogate method of nowcasting (Rundle et al., 2016) to determine the current state of seismic hazard from large earthquakes in a dozen populous cities from India and Pakistan that belong to the west‐northwest part of Himalayan orogeny. For this, we (1) perform statistical inference of natural times, intersperse counts of small‐magnitude events between pairs of succeeding large events, based on a set of eight probability distributions; (2) compute earthquake potential score (EPS) of 14 cities from the best‐fit cumulative distribution of natural times; and (3) carry out a sensitivity testing of parameters—threshold magnitude and area of city region. Formulation of natural time (Varostos et al., 2005) based on frequency–magnitude power‐law statistics essentially avoids the daunting need of seismicity declustering in hazard estimation. A retrospective analysis of natural time counts corresponding to M≥6 events for the Indian cities provides an EPS (%) as New Delhi (56), Chandigarh (86), Dehradun (83), Jammu (99), Ludhiana (89), Moradabad (84), and Shimla (87), whereas the cities in Pakistan observe an EPS (%) as Islamabad (99), Faisalabad (88), Gujranwala (99), Lahore (89), Multan (98), Peshawar (38), and Rawalpindi (99). The estimated nowcast values that range from 38% to as high as 99% lead to a rapid yet useful ranking of cities in terms of their present progression to the regional earthquake cycle of magnitude ≥6.0 events. The analysis inevitably encourages scientists and engineers from governments and industry to join hands for better policymaking toward land‐use planning, insurance, and disaster preparation in the west‐northwest part of active Himalayan belt.

Quantifying the current state of earthquake hazards in Nepal


S. Pasari, Y. Sharma, Neha


 Quantitative estimates of present-day earthquake hazard in major cities are essential for effective policymaking, community development, and seismic risk reduction. In this study, we develop a statistical analysis of natural times in Nepal to compute earthquake potential score (EPS) that describes the current level of seismic progression of a city through irregular repetitive cycle of regional earthquakes. The method, known as earthquake nowcasting (Rundle et al., 2016), uses a discrete time domain of natural times, cumulative counts of small interevent earthquakes, to characterize the present state of fault system by way of considering all earthquake events, including dependent, induced, or triggered seismicity. Data analysis and statistical inference of natural times corresponding to M ≥ 6 events assign EPS values between 59% and 99% to 24 major cities of Nepal, with the scores of metropolitan areas Kathmandu (95%), Pokhara (93%), Lalitpur (95%), Bharatpur (93%), Biratnagar (92%), and Birganj (93%). Physically, these nowcast scores, viewed as a way of tectonic stress accumulation since the last event, provide a realistic estimate on how far along is a city in its earthquake cycle of large sized events at current time. The proposed analysis and emanated results produce valuable information to the academia, industry, and public on the current dynamical state of seismic hazard in the highly earthquake prone Nepal region.

A synoptic view of the natural time distribution and contemporary earthquake hazards in Sumatra, Indonesia


S. Pasari, A.V.H. Simanjuntak, A. Mehta, Neha, Y. Sharma


 Tectonic plate interactions in Sumatra have caused a range of devastating earthquake events. In this study, we develop an analytical framework, known as earthquake nowcasting (Rundle et al. in Earth and Space Science 3:480–486, 2016. 10.1002/2016EA000185), to assess the current dynamical state of earthquake hazards in Sumatra and adjacent islands from the empirical distribution of natural times, the cumulative counts of “small” events (say, M ≥ 4) between two successive “large” earthquakes (say, M ≥ 6.5). Based on 50 years of instrumental earthquake data, the best fit Weibull distribution assigns earthquake potential score between 29 and 96% to 19 large cities in the study region with the values (%) of Aceh (72), Bengkulu (34), Binjai (81), Jambi (35), Lahat (29), Lampung (45), Lhoksuemawe (54), Medan (75), Mentawai (76), Meulaboh (71), Nias (95), Palembang (80), Padang (74), Pekanbaru (39), Sabang (72), Siantar (82), Sibolga (92), Sinabang (96), and Tanjung Balai (55). These areal-source based nowcast scores, analogous to the tectonic stress buildup since the last major event, essentially provides a unique characterization of the current level of seismic progression of a city through its repetitive cycle of regional earthquakes. Inclusion of dependent events with aftershocks being more common and the concept of natural times are some of the distinctive advantages of the proposed method. The resulting natural time statistics and consequent earthquake potential scores will facilitate seismic risk estimation, multistate decision-making, and community awareness, leading to an efficient seismic risk reduction strategy in the densely populated study region.

Empirical comparison between stochastic and deterministic modifiers over the French Auvergne geoid computation test-bed


R. Goyal, J. Ågren, W.E. Featherstone, L.E. Sjöberg, O. Dikshit, N. Balasubramanian


Since 2006, several different groups have computed geoid and/or quasigeoid (quasi/geoid) models for the Auvergne test area in central France using various approaches. In this contribution, we compute and compare quasigeoid models for Auvergne using Curtin University of Technology’s and the Swedish Royal Institute of Technology’s approaches. These approaches differ in many ways, such as their treatment of the input data, choice of type of spherical harmonic model (combined or satellite-only), form and sequence of correction terms applied, and different modified Stokes’s kernels (deterministic or stochastic). We have also compared our results with most of the previously reported studies over Auvergne in order to seek any improvements with respect to time [exceptions are when different subsets of data have been used]. All studies considered here compare the computed quasigeoid models with the same 75 GPS-levelling heights over Auvergne. The standard deviation for almost all of the computations (without any fitting) is of the order of 30–40 mm, so there is not yet any clear indication whether any approach is necessarily better than any other nor improving over time. We also recommend more standardisation on the presentation of quasi/geoid comparisons with GPS-levelling data so that results from different approaches over the same areas can be compared more objectively.

Comparison and Validation of Satellite-Derived Digital Surface/Elevation Models over India


R. Goyal, W.E. Featherstone, O. Dikshit, N. Balasubramanian


India presents among the world’s most topographically complex geomorphologies, with land elevations ranging from –2 m to + 8586 m and terrain gradients sometimes exceeding 45°. Here, we present an evaluation of four freely available digital surface models (DSMs) on a model-to-model basis, as well as a validation using independent ground-truth data from levelled benchmarks in India. The DSMs tested comprise SRTM1″, SRTM3″, ASTER1″ and Cartodem1″ [an India-only model]. Along with these four DSMs, the MERIT3″ digital elevation model (DEM) is also tested with the ground-truth data. Our results for India indicate some mismatch of these DEMs/DSMs from their claimed accuracies/precisions. All DSMs/DEMs (except for ASTER) have > 90% of pixels satisfying ± 16 m at the one-sigma level, but only in the low-lying (< 500 m) parts of India, i.e. the Gangetic plains and the Thar desert.

Spatial-spectral computation of local planar gravimetric terrain corrections from high-resolution digital elevation models


R. Goyal, W.E. Featherstone, D. Tsoulis, O. Dikshit


Computation of gravimetric terrain corrections (TCs) is a numerical challenge, especially when using very high-resolution (say, ∼30 m or less) digital elevation models (DEMs). TC computations can use spatial or/and spectral techniques: Spatial domain methods are more exact but can be very time-consuming; the discrete/fast Fourier transform (D/FFT) implementation of a binomial expansion is efficient, but fails to achieve a convergent solution for terrain slopes >45°. We show that this condition must be satisfied for each and every computation-roving point pair in the whole integration domain, not just at or near the computation points. A combination of spatial and spectral methods has been advocated by some through dividing the integration domain into inner and outer zones, where the TC is computed from the superposition of analytical mass-prism integration and the D/FFT. However, there remain two unresolved issues with this combined approach: (1) deciding upon a radius that best separates the inner and outer zones and (2) analytical mass-prism integration in the inner zone remains time-consuming, particularly for high-resolution DEMs. This paper provides a solution by proposing: (1) three methods to define the radius separating the inner and outer zones and (2) a numerical solution for near-zone TC computations based on the trapezoidal and Simpson's rules that is sufficiently accurate w.r.t. the exact analytical solution, but which can reduce the computation time by almost 50 per cent.

Signal contribution of the polar and the inclined pairs in a Bender configuration


A. Yadav, B. Devaraju, M. Weigelt


The Bender configuration comprises of two GRACE-like pairs, one in a polar orbit and the other in an inclined orbit. While the polar pair covers the entire globe, the inclined pair does not cover the higher latitudes. Similarly, the polar orbit due to its north-south orientation is able to capture features that are predominantly oriented in the east-west direction, but the inclined pair does not have any such issues. In this scenario, we would like to know the signal contribution of the polar and inclined pairs to the different spherical harmonic coefficients. Furthermore, this contribution analysis will enable us to understand the strengths and weaknesses of the GRACE(-FO) mission. In this study we use simulated data for analysing the signal contribution of the two pairs of satellites.

Deep learning networks for selection of measurement pixels in multi-temporal SAR interferometric processing


A. Tiwari, A.B. Narayan, O. Dikshit


In multi-temporal SAR interferometry (MT-InSAR), persistent scatterer (PS) pixels are used to estimate geophysical parameters, essentially deformation. Conventionally, PS pixels are selected based on the estimated noise present in the spatially uncorrelated phase component along with look-angle error in a temporal interferometric stack. In this study, two deep learning architectures, namely convolutional neural network for interferometric semantic segmentation (CNN-ISS) and convolutional long short term memory network for interferometric semantic segmentation (CLSTM-ISS), based on learning spatial and spatio-temporal behaviour, respectively, were proposed for selection of PS pixels. These networks were trained to relate the interferometric phase history to its classification into phase stable (PS pixels) and phase unstable (non-PS pixels) measurement pixels using ~10,000 real world interferometric patch images of different study sites containing man-made objects, forests, vegetation, uncropped land, water bodies, and areas affected by lengthening, foreshortening, layover and shadowing. The networks were trained using training labels obtained from the Stanford method for Persistent Scatterer Interferometry (StaMPS) algorithm. However, pixel selection results, evaluated using a combination of R-index, Similar Time Series Interferometric Pixel (STIP) maps and a classified image of the test dataset, reveal that CLSTM-ISS estimates improved the classification of PS and non-PS pixels as compared to those of StaMPS and CNN-ISS. The predicted results show that CLSTM-ISS reached an accuracy of 93.50%, higher than that of CNN-ISS (89.21%). CLSTM-ISS also improved the density of reliable PS pixels compared to StaMPS and CNN-ISS. Further, the architecture outperformed StaMPS, and is expected to compete with other MT-InSAR algorithms in terms of computational efficiency.

Estimation of Snow Depth in the Hindu Kush Himalayas of Afghanistan During Peak Winter and Early Melt Season


A.B. Mahmoodzada, D. Varade and S. Shimada


The Pamir ranges of the Hindu Kush regions in Afghanistan play a substantial role in regulating the water resource for the middle eastern countries. Particularly, the snowmelt runoff in the Khanabad watershed is one of the critical drivers for the Amu River, since it is a primary source of available water in several middle eastern countries in the off monsoon season. The purpose of this study is to devise strategies based on active microwave remote sensing for the monitoring of snow depth during the winter and the melt season. For the estimation of snow depth, we utilized a multi-temporal C-band (5.405 GHz) Sentinel-1 dual polarimetric synthetic aperture radar (SAR) with a differential interferometric SAR (DInSAR)-based framework. In the proposed approach, the estimated snowpack displacements in the VV and the VH channels were improved by incorporating modeled information of snow permittivity, and the scale was enhanced by utilizing snow depth information from the available ground stations. Two seasonal datasets were considered for the experiments corresponding to peak winter season (February 2019) and early melt season (March 2019). The results were validated with the available nearest field measurements. A good correlation determined by the coefficient of determination of 0.82 and 0.57, with root mean square errors of 2.33 and 1.44 m, for the peak winter and the early melt season, respectively, was observed between the snow depth estimates and the field measurements. Further, the snow depth estimates from the proposed approach were observed to be significantly better than the DInSAR displacements based on the correlation with respect to the field measurements.

A framework for automatic classification of mobile LiDAR data using multiple regions and 3D CNN architecture


B. Kumar, G. Pandey, B. Lohani, S.C. Misra


This paper proposes a framework for automatic classification of mobile laser scanner (MLS) point cloud using multi-faceted multi-object convolutional neural network (MMCN). The proposed method takes a full three-dimensional (3D) point cloud as input and outputs a class label for each point. Unlike other existing classification methods for MLS data, the proposed method is not dependent on any parameter or its tuning. The proposed MMCN uses multiple objects of a sample, defined by different sizes of the sample, in addition to the different facets obtained by rotating about the various axes, thus adding more information during the training and testing stages.


Conference publications

Validation of sea surface heights from satellite altimetry along the Indian coast


M. Murshan, B. Devaraju, N. Balasubramanian, O. Dikshit


 Satellite altimetry provides measurements of sea surface height of centimeter-level accuracy over open oceans. However, its accuracy reduces when approaching the coastal areas and over land regions. Despite this downside, altimetric measurements are still applied successfully in these areas through altimeter retracking processes. This study aims to calibrate and validate retracted sea level data of Envisat, ERS-2, Topex/Poseidon, Jason-1, 2, SARAL/AltiKa, Cryosat-2 altimetric missions near the Indian coastline. We assessed the reliability, quality, and performance of these missions by comparing eight tide gauge (TG) stations along the Indian coast. These are Okha, Mumbai, Karwar, and Cochin stations in the Arabian Sea, and Nagapattinam, Chennai, Visakhapatnam, and Paradip in the Bay of Bengal. To compare the satellite altimetry and TG sea level time series, both datasets are transformed to the same reference datum. Before the calculation of the bias between the altimetry and TG sea level time series, TG data are corrected for Inverted Barometer (IB) and Dynamic Atmospheric Correction (DAC). Since there are no prior VLM measurements in our study area, VLM is calculated from TG records using the same procedure as in the Technical Report NOS organization CO-OPS 065.

Forest Fire Risk Assessment for Sikkim using Earth Observation (EO) Datasets and Multi Criteria Decision Making Technique.


  A. Laha, R. Sinha, B. Nagarajan.


 Forest fires significantly influence the whole ecosystem by increasing the mortality rate of vegetation and by regulating the exchange of carbon, water, and other particulate matter between land and atmosphere. Recent climate change and anthropogenic activities are increasing the incidents of forest fires, degrading rich forest biodiversity and, their functioning. It is therefore of paramount importance to design effective strategies for protecting the forest areas. Understanding the spatial distribution of forest fires and identification of the Forest Fire Risk (FFR) zones is urgently needed to propose effective forest fire management strategies by advising efficient and practical mitigation measures.

 A protocol has been developed in this work to produce the FFR maps for the entire Sikkim state using the earth observation datasets and multi-criteria decision-making technique, i.e., AHP (Analytical Hierarchy Process) in a GIS (Geographic Information System) framework. We selected 9 different parameters (vegetation type, vegetation density, land surface temperature, elevation, slope, aspect, and distance from settlements, river, and roads) based on the understanding of the factors influencing the spatial distribution of forest fires in the region. Our results show that more than 50% area of all the districts is under high risk zones except North Sikkim, which lies at an altitude of 500m to 8056m and is mostly covered with snow. The model showed an accuracy of 82.36%, which implies that a large number of past forest fire incidence overlay the high risk zone of the state. Further analysis concluded that moderate dense forest of this region is more prone to fire, whereas aspect and human density differentiate very high and high risk zones. This model has provided a geographical representation of fire ignition probability and identifies high-risk areas in different regions.

Indian Plate Motion Revealed by GPS Observations: Preliminary Results.


 Neha, Y. Sharma, S. Pasari


 In this study, we present a brief summary of the motion of the Indian plate and its interior deformation. An analysis of four GPS stations across the Indian subcontinent provides evidence of convergence towards the Eurasian plate at a velocity of about 50 mm/yr in the northeast direction. Our analysis shows that the internal deformation of the Indian plate is very low (~1±3 mm/yr) and the whole Indian plate interior behaves like a solid rigid plate. In addition, we observe that the Indian subcontinent is subsiding at a rate of ~3±1 mm/yr. Along the Himalayan arc, we find high velocity gradient which conforms to the rapid deformation along the plate boundary. Finally, we argue that the past earthquakes and possible future earthquakes along the plate interior depend either upon the internal lithospheric stress or on the stress from the plate boundary (i.e. Himalaya).

Towards the derivation of Multiple Representation Database.


 J. Boodala, O. Dikshit, N. Balasubramanian


 This paper presents the background study carried out to design the derivation process of the Multiple Representation Database (MRDB). A topographic feature, for example, a building, is represented differently at different levels of detail (LoDs). When these different representations of a topographic feature are stored and linked, then it forms MRDB. In the proposed design, MRDB is created automatically by the model generalization process. The flowline of the model generalization is designed by studying various existing data specifications, data models, and data products of different scales. The ScaleMaster diagram is used to represent the knowledge that drives the automatic model generalization. The generalization engine discussed in this paper is currently being implemented using the selection criteria, constraints, and model generalization operators tabulated in the ScaleMaster diagram. The results of this generalization engine will be used to maintain the link between different LoDs, thus creating MRDB.


Book Chapter(s)

Spatial Data Infrastructure and Generalization.


 J. Boodala, O. Dikshit, N. Balasubramanian





A deep learning approach for efficient multi-temporal interferometric synthetic aperture radar (MT-InSAR) processing


 A.Tiwari, A.B. Narayan, O. Dikshit


 Multi-temporal interferometric synthetic aperture radar (MT-InSAR) technique has been effectively used to monitor deformation events over the last two decades. The processing steps generally involve pixel selection, phase unwrapping and displacement estimation. The pixel selection step takes most of the processing time, while a reliable method for phase unwrapping is still not available. This study demonstrates the effect of using deep learning (DL) architectures for MT-InSAR processing. The architectures are applied to reduce time computations and further to improve the quality of pixel selection. Some promising results for pixel selection have been shown earlier with the proposed architecture. In this study, we investigate the performance of the proposed architectures on newer datasets with larger temporal interval. To achieve this objective, the models are retrained with interferometric stacks covering larger temporal period and large time steps (for better estimation of interferometric phase components). Pixel selection results are compared with those obtained using open access algorithms used for MT-InSAR processing.

Establishment of State-of-the-Art Geodesy Village in India: Current status and Outlook


 S. Dhar, A. Tiwari, B. Nagarajan, B. Devaraju, O. Dikshit, J. Prakash, P. Mishra, D. Agarwal, V. Sharma, D. Varade, A. Laha, A. Kumar, S. Singh, A.B. Narayan, R. Goyal, V. Kumar


 National Centre for Geodesy (NCG) has been established in IIT Kanpur, India with the vision of acting as a hub of excellence in geodetic research at the National and International level. Working towards its mission, it has initiated this state-of-the- art establishment for improving the space geodetic infrastructure of the country and encouraging more researches in the geodesy field. The presentation will discuss the current status of the planned core site and its future establishments. It will provide detailed description of all the facilities installed in the site right now, and the future extensions. This new core-site will house facilities for three technologies – Space, Time and Earth gravity domain. The main purpose of establishing this site is for improving the realization of terrestrial and celestial reference frames, Earth Orientation Parameters (EOPs) and other data products essential for understanding the Earth’s environment. This co-located site with four space geodetic techniques will help in the International campaign for determination of TRF with 1mm accuracy and 0.1 mm/yr. stability. Moreover, this site location will improve the uniformity in geographical distribution of the ITRF observatories and the necessity of this station has been confirmed by simulation modelling.

Comparison of spectral methods for the evaluation of Stokes integral


 A.B. Narayan, A. Tiwari, G. Sharma, B. Devaraju, O. Dikshit


 The spherical approximation of the fundamental equation of geodesy defines the boundary value problems. Stokes’s integral provides the solution of boundary value problems that enables the computation of geoid from the properly reduced gravity measurements to the geoid. The stokes integral can be evaluated by brute-force numerical integration, spectral methods, and least-squares collocation. There is a trade-off between computation time and accuracy when we chose numerical integration technique or any spectral method. This research will compare time complexity and the accuracy of different spectral methods (1D-FFT, 2D-FFT, Multi-band FFT) and numerical integration technique for the region in the lower Himalaya, around Nainital, Uttarakhand, India.

Importance of Shared Vocabularies in Deriving Geographic Data of Varying Levels of Detail.


 J. Boodala, O. Dikshit, N. Balasubramanian,



Optimal choice of the number and configuration of VLBI global observing system in India.


 S. Singh, R. Goyal, N. Balasubramanian, B. Devaraju, O. Dikshit


 The need of the geodetic VLBI stations in South Asia region has been discussed and suggested for decades to have a uniform global VLBI network and relatively more accurate realisation of ITRF. With the recent initiative of National Centre for Geodesy, India, setting up of a few VLBI stations in the country is being proposed. India spans from latitude 8.4º N to 37.6º N and longitude 68.7º E to 97.25º E and encompasses a diversified topography with a plethora of geodynamical activities. Along with contributions to the international geodetic campaigns, we would like to choose the locations of these VGOS stations so that these can be an aid to the Indian geodetic infrastructure along with several other studies of national importance. For multitude of reasons, the prospective sites for establishing VGOS stations in India are: 1) IIST Ponmudi campus, 2) Mt. Abu Observatory, PRL, 3) IIT Kanpur and 4) NE-SAC, Shillong. The approximate longitudinal extent of 20º and latitudinal extent of 18º between these prospective sites are worth exploiting for determining the angle of the Earth rotation (dUT1) and polar motion, respectively. In this study, we present the comparison results of the solutions with and without additional VGOS station in India. For this, we first generated an optimised schedule for a classical VGOS/R1 session, using VieVS, with existing stations using the comparatively more important optimisation criteria (duration, sky-coverage, number of observations and idle time) and corresponding weight factors. The simulation result of the best schedule is kept as our reference solution. With respect to this reference network, we further generated optimised schedules by including the prospective stations from India (different combinations of the four proposed stations). We present our analysis due to change in network geometry, and therefore, we compare the variations in the repeatability values of the estimated EOPs with the addition of VGOS station(s) in India.

Subtleties in spherical harmonic synthesis of the gravity field.


  R. Goyal, S.J. Claessens, W.E. Featherstone, O. Dikshit


 Spherical harmonic synthesis (SHS) can be used to compute various gravity functions (e.g., geoid undulations, height anomalies, deflections of vertical, gravity disturbances, gravity anomalies, etc.) using the 4pi fully normalised Stokes coefficients from the many freely available Global Geopotential Models (GGMs). This requires a normal ellipsoid and its gravity field, which are defined by four parameters comprising (i) the second-degree even zonal Stokes coefficient (J2) (aka dynamic form factor), (ii) the product of the mass of the Earth and universal gravitational constant (GM) (aka geocentric gravitational constant), (iii) the Earth's angular rate of rotation (ω), and (iv) the length of the semi-major axis (a). GGMs are also accompanied by numerical values for GM and a, which are not necessarily identical to those of the normal ellipsoid. In addition, the value of W0, the potential of the geoid from a GGM, needs to be defined for the SHS of many gravity functions. W0 may not be identical to U0, the potential on the surface of the normal ellipsoid, which follows from the four defining parameters of the normal ellipsoid. If W0 and U0 are equal and if the normal ellipsoid and GGM use the same value for GM, then some terms cancel when computing the disturbing gravity potential. However, this is not always the case, which results in a zero-degree term (bias) when the masses and potentials are different. There is also a latitude-dependent term when the geometries of the GGM and normal ellipsoids differ. We demonstrate these effects for some GGMs, some values of W0, and the GRS80, WGS84 and TOPEX/Poseidon ellipsoids and comment on its omission from some public domain codes and services (isGraflab.m, harmonic_synth.f and ICGEM). In terms of geoid heights, the effect of neglecting these parameters can reach nearly one metre, which is significant when one goal of modern physical geodesy is to compute the geoid with centimetric accuracy. It is also important to clarify these effects for all (non-specialist) users of GGMs.

Indian gravimetric geoid model


 R. Goyal, W.E. Featherstone, S.J. Claessens, O. Dikshit, N. Balasubramanian



Geodetic monitoring of the hydrological changes in Nepal Himalaya.


  J.D. Ray, B. Devaraju, M.S.M. Vijayan, W. Godah


 Mass of the Earth's system although remains constant, it gets transported between various Earth's system components. These mass transports are found to induce deformations of the Earth's surface known as surface mass loading and are driven by climate patterns. Therefore, temporal mass variations within the Earth's system and hence surface mass loading is the direct impact of climate change. One of the major sources of mass transport in the Indian subcontinent is the monsoon. This subcontinent receives a significant amount of rainfall during the monsoon period. The mass transports caused by the Indian monsoon deform the Earth's surface which can be detected with space geodetic techniques such as Global Navigational Satellite Systems (GNSS) and dedicated gravity satellite missions, in particular, the Gravity Recovery and Climate Experiment (GRACE) and GRACE-Follow on (GRACE-FO) satellite missions. The overarching objective of this study is to monitor the hydrological changes in Nepal Himalaya using geodetic data. In particular, it is aimed at investigating the contribution of mass transports from various catchments in the Nepal Himalaya and its surrounding areas to the hydrological signal observed by the continuously operating GPS (Global Positioning System) stations. GRACE/GRACE-FO satellite missions' data, hydrological models and spatio-temporal modelling techniques have been used to ascertain the aforementioned contribution. The results obtained were presented, analysed and discussed.