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2021 ◽  
Vol 15 (2) ◽  
pp. 273-280
Author(s):  
Paul-Vivian Sion ◽  
Mihaela Avram ◽  
Mihail Luca

The phenomenon of hydrodynamic erosion affects the riverbeds in which sub-crossings of pipes or bridges are located. The depth of erosion is determined at a point in the riverbed by the use of specialized computational relationships. For some works located in the riverbed it is necessary to know the erosion depths on the perimeter of the flow section. The analysis models used to investigate the phenomenon of hydrodynamic erosion were: a - topographic model; b - calculation relations from the technical regulations; c - erosion simulation model on a river section. The obtained results were materialized by the evolution of the erosion depths on the considered river sector over an interval of about 5-15 years. The depth of erosion on the lower course of the Moldova River showed values from 0.75 m to 1.65 m on a research sector. The research results were capitalized on the design of the rehabilitation works of the constructions present in the riverbed.



2021 ◽  
Author(s):  
Qing Liu ◽  
Michael Schmidt ◽  
Laura Sánchez

<p>In this study, we investigate the optimal combination of local gravity observations and their contributions to the regional quasi-geoid model. The study area is located in Colorado, USA, with two types of regional data sets, namely terrestrial gravity data and airborne gravity data, available within the “1 cm geoid experiment”. The approach based on series expansions in terms of spherical radial basis functions (SRBF) is applied, which has been developed at DGFI-TUM in the last two decades. We use two different types of basis functions covering the same spectral domain separately for the terrestrial and the airborne measurements. The Shannon function is applied to the terrestrial data, and the Cubic Polynomial (CuP) function which has smoothing features is applied to the airborne data for filtering their high-frequency noise.</p><p>To assess the contributions of the regional terrestrial and airborne gravity data to the final quasi-geoid model, four solutions are compared, namely the combined solution, the terrestrial only, the airborne only, and finally the model only solution, i.e., only the global gravity model and the topographic model are used without any gravity data from regional measurements. By adding the terrestrial data to the GGM and the topographic model, the RMS error of the quasi-geoid model w.r.t the validation data (the mean solution of independent computations delivered by fourteen institutions from all over the world) drops from 4 to 1.8 cm, and it is further reduced to 1 cm by including the airborne data.</p>



Author(s):  
Xiang Zou ◽  
Jianping Song ◽  
Liang Chen ◽  
Ying Mao


2020 ◽  
Vol 94 (10) ◽  
Author(s):  
Qing Liu ◽  
Michael Schmidt ◽  
Laura Sánchez ◽  
Martin Willberg

Abstract This study presents a solution of the ‘1 cm Geoid Experiment’ (Colorado Experiment) using spherical radial basis functions (SRBFs). As the only group using SRBFs among the fourteen participated institutions from all over the world, we highlight the methodology of SRBFs in this paper. Detailed explanations are given regarding the settings of the four most important factors that influence the performance of SRBFs in gravity field modeling, namely (1) the choosing bandwidth, (2) the locations of the SRBFs, (3) the type of the SRBFs as well as (4) the extensions of the data zone for reducing the edge effect. Two types of basis functions covering the same spectral range are used for the terrestrial and the airborne measurements, respectively. The non-smoothing Shannon function is applied to the terrestrial data to avoid the loss of spectral information. The cubic polynomial (CuP) function which has smoothing features is applied to the airborne data as a low-pass filter for filtering the high-frequency noise. Although the idea of combining different SRBFs for different observations was proven in theory to be possible, it is applied to real data for the first time, in this study. The RMS error of our height anomaly result along the GSVS17 benchmarks w.r.t the validation data (which is the mean results of the other contributions in the ‘Colorado Experiment’) drops by 5% when combining the Shannon function for the terrestrial data and the CuP function for the airborne data, compared to those obtained by using the Shannon function for both the two data sets. This improvement indicates the validity and benefits of using different SRBFs for different observation types. Global gravity model (GGM), topographic model, the terrestrial gravity data, as well as the airborne gravity data are combined, and the contribution of each data set to the final solution is discussed. By adding the terrestrial data to the GGM and the topographic model, the RMS error of the height anomaly result w.r.t the validation data drops from 4 to 1.8 cm, and it is further reduced to 1 cm by including the airborne data. Comparisons with the mean results of all the contributions show that our height anomaly and geoid height solutions at the GSVS17 benchmarks have an RMS error of 1.0 cm and 1.3 cm, respectively; and our height anomaly results give an RMS value of 1.6 cm in the whole study area, which are all the smallest among the participants.



Author(s):  
Rizki Atthoriq Hidayat ◽  
Natasyah Febriani ◽  
Muhammad Hanif ◽  
Henzulkifli Rahman

Helmeted hornbill (Rhinoplax vigil) is a protected wildlife in Indonesia according to enactment no. 5, 1999 about Conservation of Natural Resources and its Ecosystems and Government Regulation no. 9, 1999 about plant and wildlife preservation. Helmeted Hornbill habitats spread in five country regions: Myanmar, Thailand, Malaysia (Malayan Peninsula and Serawak), Brunei, and Indonesia (Sumatra and Borneo). Silokek Geopark which located in Sijunjung Regency, West Sumatra Province, Indonesia is an identified location of Helmeted Hornbill habitat existence. Beside its uniqueness in physics, this bird also have an ecological function as seed dispersal in nature. The utilization of Remote Sensing (RS) technology and and Geographic Information System (GIS) is highly useful in identification the Helmeted Hornbill habitat distribution in this research. Geographic dateset used in this research are Landsat OLI 8 imagery, Shuttle Radar Topographic Model (SRTM), Coordinate points of Helmeted Hornbill existence and location assesment, and other dataset related to administration boundary in Silokek Geopark. This research aims to find conservation priority zone of Helmeted Hornbill in Silokek Geopark. By utilizing Maximun Entropy (MaxEnt) algorithm with finding points and location assessment, we can determine the distribution of Helmeted Hornbill habitat in Silokek Geopark based on habitat likeness. This research produces the model of conservation priority zones in geopark silokek which are distributed in hilly protected forest area and the distributions are concentrated in the center and noth east part of our researc area. This model is highly influenced by forest texture (25.7%), distance of patches (24.3%), and distance of settlement.



2019 ◽  
Vol 13 (1) ◽  
pp. 51-56
Author(s):  
Ivan Landek ◽  
Saša Cvitković ◽  
Milan Rezo

In 1992, the State Geodetic Administration started with the development of cartography in the Republic of Croatia. After making a certain number of studies, STOKIS (the Official Topographic-Cartographic Information System) was defined. Topographic and cartographic data models were then defined by STOKIS. According to the STOKIS guidelines, the Croatian topographic information system (CROTIS) was developed as a data model and on the basis of CROTIS, the Basic Topographic Database (TTB) was established. One thematic entity contained in CROTIS 2.0, and whose data is often used, is the object entity of Hydrography. This article will provide an insight into the need to expand/correct the TTB data model in relation to the underlying basic package and the object entity of Hydrography, all in line with international standards and the INSPIRE directive.



2019 ◽  
Vol 9 (1) ◽  
pp. 29-40
Author(s):  
P. Zingerle ◽  
R. Pail ◽  
M. Scheinert ◽  
T. Schaller

Abstract The AntGrav project, funded by the German Research Foundation (DFG) has the main objective to homogenize and optimize Antarctic gravity field information. Within this project an evaluation procedure is needed to inspect all different kind of gravity field surveys available in Antarctica. In this paper a suitable methodology is proposed. We present an approach for fast 3D gravity point data reduction in different spectral bands. This is achieved through pre-calculating a fine 3D mesh of synthesized gravity functionals over the entirety of the Antarctic continent, for which two different global models are used: the combined satellite model GOCO05s for the long-wavelength part, and the topographic model Earth2014 for the shorter wavelengths. To maximize the applicability separate meshes are calculated for different spectral bands in order to specifically reduce a certain band or a selected combination. All meshes are calculated for gravity anomalies as well as gravity disturbances. Utilizing these meshes, synthesized gravity data at arbitrary positions is computed by conventional 3D interpolation methods (e.g. linear, cubic or spline). It is shown that the applied approach can reach a worst-case interpolation error of less than 1 mGal. Evaluation results are presented for the AntGG grid and exemplary for the in-situ measurements of the AGAP and BAS-LAND campaigns. While general properties, large-scale errors and systematic effects can usually be detected, small-scale errors (e.g. of single points) are mostly untraceable due to the uncertainties within the topographic model.





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