Necessity of Terrain Correction in Magnetotelluric Data Recorded from Garhwal Himalayan Region, India

The magnetotelluric (MT) method is one of the useful geophysical techniques to investigate deep crustal structures. However, in hilly terrains, e.g., the Garhwal Himalayan region, due to the highly undulating topography, MT responses are distorted. Such responses, if not corrected, may lead to the incorrect interpretation of geoelectric structures. In the present paper, we implemented terrain corrections in MT data recorded from the Garhwal Himalayan Corridor (GHC). We used AP3DMT, a 3D MT data modeling and inversion code written in the MATLAB environment. Terrain corrections in the MT impedance responses for 39 sites along the Roorkee–Gangotri profile in the period range of 0.01 s to 1000 s were first estimated using a synthetic model by recording the topography and locations of MT sites. Based on this study, we established the general character of the terrain and established where terrain corrections were necessary. The distortion introduced by topography was computed for each site using homogenous and heterogeneous models with actual topographic variations. Period-dependent, galvanic and inductive distortions were observed at different sites. We further applied terrain corrections to the real data recorded from the GHC. The corrected data were inverted, and the inverted model was compared with the corresponding inverted model obtained with uncorrected data. The modification in electrical resistivity features in the model obtained from the terrain-corrected response suggests the necessity of terrain correction in MT data recorded from the Himalayan region.

Micro-Topography Mapping through Terrestrial LiDAR in Densely Vegetated Coastal Environments

Terrestrial Light Detection And Ranging (LiDAR), also referred to as terrestrial laser scanning (TLS), has gained increasing popularity in terms of providing highly detailed micro-topography with millimetric measurement precision and accuracy. However, accurately depicting terrain under dense vegetation remains a challenge due to the blocking of signal and the lack of nearby ground. Without dependence on historical data, this research proposes a novel and rapid solution to map densely vegetated coastal environments by integrating terrestrial LiDAR with GPS surveys. To verify and improve the application of terrestrial LiDAR in coastal dense-vegetation areas, we set up eleven scans of terrestrial LiDAR in October 2015 along a sand berm with vegetation planted in Plaquemines Parish of Louisiana. At the same time, 2634 GPS points were collected for the accuracy assessment of terrain mapping and terrain correction. Object-oriented classification was applied to classify the whole berm into tall vegetation, low vegetation and bare ground, with an overall accuracy of 92.7% and a kappa value of 0.89. Based on the classification results, terrain correction was conducted for the tall-vegetation and low-vegetation areas, respectively. An adaptive correction factor was applied to the tall-vegetation area, and the 95th percentile error was calculated as the correction factor from the surface model instead of the terrain model for the low-vegetation area. The terrain correction method successfully reduced the mean error from 0.407 m to −0.068 m (RMSE errors from 0.425 m to 0.146 m) in low vegetation and from 0.993 m to −0.098 m (RMSE from 1.070 m to 0.144 m) in tall vegetation.

The Gravity Effect of Topography: A Comparison among Three Different Methods

In this paper, three different methods for computing the terrain correction have been compared. The terrain effect has been accounted for by using the standard right parallelepiped closed formula, the spherical tesseroid and the flat tesseroid formulas. Particularly, the flat tesseroid approximation is obtained by flattening the top and the bottom sides of the spherical tesseroid. Its gravitational effect can be computed as the gravitational effect of a polyhedron, i.e. a three-dimensional body with flat polygonal faces, straight edges and sharp corners or vertices. These three methods have been applied in the context of a Bouguer reduction scheme. Two tests were devised in the Alpine area in order to quantify possible discrepancies. In the first test, the terrain correction has been evaluated on a grid of points on the DTM. In the second test, Bouguer gravity anomalies were computed on sparse observed gravity data points. The results prove that the three methods are practically equivalent even in an area of rough topography though, in the second test, the Bouguer anomalies obtained by using the tesseroid and the flat tesseroid formulas have slightly smaller RMSs than the one obtained by applying the standard right parallelepiped formula.

Detecting Calving Events of Icebergs D-28 and B-49 using High Resolution Sentinel-1A SAR Data

<p>Detecting iceberg calving events and subsequently tracking their movement is important because large icebergs can create problem in shipping and navigation. This study discusses two calving events that took place at 1) Amery ice shelf (East Antarctica) in September 2019 and 2) Pine Island Glacier’s floating ice shelf (West Antarctica) in February 2020. Though the calving that occurred in September 2019 does not have any impact on climate change, it is considered to be the most significant calving event on Amery ice shelf since 1963-64. The gigantic tabular iceberg officially named D-28 measures more than 600 square-miles. On the other hand, Pine Island is considered as the fastest retreating glaciers in Antarctica. This calving event gave rise to smaller icebergs, the largest of which was 120 square-miles, big enough to earn it a name: B-49. Though ice calving is a normal phenomenon at the ice shelves, the front of the glacier is stable if the rate of calving is in synchronization with the glacier’s forward flow. But, at Pine Island, the rate of disintegration has increased more than the glacier's speed to push the inland ice into Pine Island Bay. On-screen digitization approach of analysing time series dataset of glacier front positions is conventional, time consuming and subjective. To track the movement of icebergs D-28 and B-49, present study has detected rifts using canny edge detection filter and textural measures. We have utilized the Sentinel 1A SAR C-band (GRD) EW mode (Resolution (Rg x Az): 93 x 87 m and pixel spacing 40 x 40 m) images pertaining to the Amery ice shelf for Sep 2020-Mar 2020 and Pine Island Glacier with Pine Island Bay for Dec 2019-Mar 2020. All the images were processed for calibration (sigma0), speckle filtering (refined Lee), terrain correction (Range Doppler) and dB conversion using SNAP tool. Terrain correction has been performed using RAMP v2 DEM (200 m) and all the images have been projected to WGS 84/Antarctic Polar Stereographic projection and converted into dB. Through image interpretation, it is revealed that as of Mar 2020, iceberg D-28 has rotated almost 90 degrees anti-clockwise and drifted slightly northward away from Cape Darnley. In case of iceberg B-49, it is observed that the western portion of the calved ice, including the largest iceberg, has rapidly rotated out into Pine Island Bay, whereas the eastern half, including many smaller shards of ice, is following in similar fashion.</p>

Comparison of different topographic mass integration schemes in topographic reduction and its impact on geoid modeling: a case study in the Colorado area

<p>Topographic reduction is one of the most imperative steps in geoid modeling, where the gravity field inside the masses needs to be modeled. This is quite challenging because no one can measure gravity inside the topography at a desired resolution (only a very limited number of borehole gravity measurements are available in the whole world). Therefore, topographic mass modeling is usually treated either by the residual terrain modeling (RTM) or by the Helmert’s 2<sup>nd</sup> condensation among other alternative reduction schemes. All of these topographic reductions need intense computation efforts for the integration of topographic mass induced gravity effects. Currently, the most popular tool for topographic mass modeling is the ‘tc’ program available in the GRAVSOFT package. In this program, the mass elements provided by a digital terrain model (DTM) are treated as rectangular prisms which cannot directly take the Earth curvature into account and suffer from geometrical shape change due to meridian convergence. In this study, the tesseroids which are naturally obtained from a DTM are employed and their gravity effects are precisely evaluated by numerical integrations. Four topographic mass integration schemes are proposed and programmed in FORTRAN. Their computational performances in computing the RTM effect, terrain correction, and total topographic effect with and without using parallelizing technique are tested in the Colorado area. Then they are applied to local geoid modeling to see the geoid model differences among these various integration schemes in the RTM case. The numerical findings reveal that: (1) The application of parallelization techniques can greatly reduce the computation time without the loss of any computation accuracy; (2) Among the four integration schemes, the maximum absolute difference of RTM effect, terrain correction, and total topographic effect is about 3 mm, 6 cm, and 7.5 cm for the height anomaly, and 4 mGal, 3 mGal, and 40 mGal for the gravity anomaly; (3) In the RTM case, the geoid model difference can reach a maximum of 1 cm in the target area, and a larger difference should be expected in areas with rougher terrain; (4) The effects on geoid models from mass density anomalies is bigger than the counterparts from DTM errors.</p>

Features of apparent resistivity anomaly of CSAMT and prospects of oil shale in Tongchuan area of southern Ordos basin, China

Four CSAMT (Controlled Source Audio-frequency Magnetotelluric) profiles were conducted in early 2011 in order to investigate the distribution rules of oil shale in Tongchuan area of southern Ordos basin. After terrain correction, we high-pass filtered the resulting images to prepare the 2D CSAMT apparent resistivity profiles for further analysis. Specifically, we correlated the high-pass filtered apparent resistivity anomalies to the distribution of oil shale seen in three available wells. The results show a close relationship between the oil shale distribution and the anomalously high apparent resistivity belt-like anomalies in the Tongchuan area. Our analysis indicates two prospective areas with different depths for oil shale within the study area.

UAV-Based Terrain Modeling under Vegetation in the Chinese Loess Plateau: A Deep Learning and Terrain Correction Ensemble Framework

Accurate topographic mapping is a critical task for various environmental applications because elevation affects hydrodynamics and vegetation distributions. UAV photogrammetry is popular in terrain modelling because of its lower cost compared to laser scanning. However, this method is restricted in vegetation area with a complex terrain, due to reduced ground visibility and lack of robust and automatic filtering algorithms. To solve this problem, this work proposed an ensemble method of deep learning and terrain correction. First, image matching point cloud was generated by UAV photogrammetry. Second, vegetation points were identified based on U-net deep learning network. After that, ground elevation was corrected by estimating vegetation height to generate the digital terrain model (DTM). Two scenarios, namely, discrete and continuous vegetation areas were considered. The vegetation points in the discrete area were directly removed and then interpolated, and terrain correction was applied for the points in the continuous areas. Case studies were conducted in three different landforms in the loess plateau of China, and accuracy assessment indicated that the overall accuracy of vegetation detection was 95.0%, and the MSE (Mean Square Error) of final DTM (Digital Terrain Model) was 0.024 m.