Special Issue "Geodesy and Geomatics Engineering"

A special issue of Geosciences (ISSN 2076-3263).

Deadline for manuscript submissions: 15 June 2019

Special Issue Editor

Guest Editor
Dr. Jakub Szulwic

Politechnika Gdanska, Faculty of Civil and Environmental Engineering, Gdansk, Poland
Website | E-Mail
Interests: photogrammetry; coastal and offshore engineering; engineering geodesy; laser scanning; geoinformatics

Special Issue Information

Dear Colleagues,

I am pleased to invite you to publish your research in this Special Issue of Geosciences entitled “Geodesy and Geomatics Engineering”. The scope of this issue includes topics related to geodesy—from measurements of the Earth as a planet to detailed applications in surveying. Articles describing case studies in the aforementioned subjects may be admitted for publication (research using innovative measurement technologies is particularly desirable). Articles may include, but are not limited to, the following topics:

  • Terrestrial and mobile laser scanning, including maritime laser scanning
  • coastal and offshore geoengineering
  • engineering surveying and monitoring
  • engineering photogrammetry
  • natural resource monitoring and development
  • GIS applications
  • geoinformatics

Dr. Jakub Szulwic
Guest Editor

Manuscript Submission Information

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Geosciences is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 850 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • geodesy
  • geomatics engineering
  • surveying engineering
  • terrestrial and mobile laser scanning
  • coastal and offshore geoengineering
  • GIS applications

Published Papers (6 papers)

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Research

Open AccessArticle
The Noise Properties and Velocities from a Time-Series of Estonian Permanent GNSS Stations
Geosciences 2019, 9(5), 233; https://doi.org/10.3390/geosciences9050233
Received: 9 April 2019 / Revised: 15 May 2019 / Accepted: 16 May 2019 / Published: 21 May 2019
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Abstract
The aim of this study was to estimate the noise properties, velocities, and their uncertainties from a time-series of selected (~9 years long) Estonian continuously operating Global Navigation Satellite System (GNSS) stations. Two software packages based on different processing methods, Gipsy–Oasis and Bernese, [...] Read more.
The aim of this study was to estimate the noise properties, velocities, and their uncertainties from a time-series of selected (~9 years long) Estonian continuously operating Global Navigation Satellite System (GNSS) stations. Two software packages based on different processing methods, Gipsy–Oasis and Bernese, were used for daily coordinate calculations. Different methods and software (Tsview, Hector, and MIDAS) were used for coordinate time-series analysis. Outliers were removed using three different strategies. Six different stochastic noise models were used for trend estimation altogether with the analysis of the noise properties of the residual time-series with Hector. Obtained velocities were compared with different land uplift and glacial isostatic adjustment models (e.g., ICE-6G (VM5a), NKG2016LU, etc.). All compared solutions showed similar fit to the compared models. It was confirmed that the best fit to the time-series residuals were with the flicker noise plus white noise model (for the North and East component) and generalized Gauss–Markov model (for Up). Velocities from MIDAS, Tsview, and Hector solutions within the same time-series (Gipsy–Oasis or Bernese) agreed well but velocity uncertainties differed up to four times. The smallest uncertainties were obtained from Tsview; the MIDAS solution produced the most conservative values. Although the East and Up component velocities between Gipsy and Bernese solutions agreed well, the North component velocities were systematically shifted. Full article
(This article belongs to the Special Issue Geodesy and Geomatics Engineering)
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Graphical abstract

Open AccessArticle
Estimating Residential Property Values on the Basis of Clustering and Geostatistics
Geosciences 2019, 9(3), 143; https://doi.org/10.3390/geosciences9030143
Received: 7 February 2019 / Revised: 20 March 2019 / Accepted: 21 March 2019 / Published: 24 March 2019
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Abstract
The article presents a two-stage model for estimating the value of residential property. The research is based on the application of a sequence of known methods in the process of developing property value maps. The market is divided into local submarkets using data [...] Read more.
The article presents a two-stage model for estimating the value of residential property. The research is based on the application of a sequence of known methods in the process of developing property value maps. The market is divided into local submarkets using data mining, and, in particular, data clustering. This process takes into account only a property’s non-spatial (structural) attributes. This is the first stage of the model, which isolates local property markets where properties have similar structural attributes. To estimate the impact of the spatial factor (location) on property value, the second stage involves performing an interpolation for each cluster separately using ordinary kriging. In this stage, the model is based on Tobler’s first law of geography. The model results in property value maps, drawn up separately for each of the clusters. Experimental research carried out using the example of Siedlce, a city in eastern Poland, proves that the estimation error for a property’s value using the proposed method, evaluated using the mean absolute percentage error, does not exceed 10%. The model that has been developed is universal and can be used to estimate the value of land, property, and buildings. Full article
(This article belongs to the Special Issue Geodesy and Geomatics Engineering)
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Open AccessArticle
Geoscience Methods in Real Estate Market Analyses Subjectivity Decrease
Geosciences 2019, 9(3), 130; https://doi.org/10.3390/geosciences9030130
Received: 9 February 2019 / Revised: 8 March 2019 / Accepted: 11 March 2019 / Published: 16 March 2019
Cited by 1 | PDF Full-text (5787 KB) | HTML Full-text | XML Full-text
Abstract
Real estate management, including real estate market analysis, is part of a so-called geosystem. In recent years, the popularity of creating various types of systems and automatic solutions in real estate management, including those related to property classification and valuation, has been growing [...] Read more.
Real estate management, including real estate market analysis, is part of a so-called geosystem. In recent years, the popularity of creating various types of systems and automatic solutions in real estate management, including those related to property classification and valuation, has been growing in the world, mainly to reduce the impact of human subjectivity, to increase the scope of analyses and reduce research time. A very important fact that should be underlined is that properties are strongly related to geolocation (space) and strongly determine it. Authors proposed in the paper solutions that highlight implementation of geoscience and “geo-approach” combined with fuzzy logic methods that allow to decrease subjectivity in property analyses and diminish uncertainty in decision making process. The proposed methodology involves three main problematic components of decision support system in property investment analyses development with the use of geo-technologies such as: determination of the database model; elaboration geo-property-zones with geoprocessing activities; identification of homogeneous group of properties transactions. The influence of spatial decision factor determined in the study lead to objective and precise calculation of value differentiation from 22 to 43% depending on the property’s remoteness to the sea. Full article
(This article belongs to the Special Issue Geodesy and Geomatics Engineering)
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Open AccessArticle
The Optimal Location of Ground-Based GNSS Augmentation Transceivers
Geosciences 2019, 9(3), 107; https://doi.org/10.3390/geosciences9030107
Received: 16 January 2019 / Revised: 24 February 2019 / Accepted: 26 February 2019 / Published: 27 February 2019
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Abstract
Modern Global Navigation Satellite Systems (GNSS) allow for positioning with accuracies ranging from tens of meters to single millimeters depending on user requirements and available equipment. A major disadvantage of these systems is their unavailability or limited availability when the sky is obstructed. [...] Read more.
Modern Global Navigation Satellite Systems (GNSS) allow for positioning with accuracies ranging from tens of meters to single millimeters depending on user requirements and available equipment. A major disadvantage of these systems is their unavailability or limited availability when the sky is obstructed. One solution is to use additional range measurements from ground-based nodes located in the vicinity of the receiver. The highest accuracy of distance measurement can be achieved using ultra wide band (UWB) or ZigBee phase shift measurement. The position of the additional transmitter must be carefully selected in order to obtain the optimal improvement in the dilution of precision (DOP), which reflects the improvement in the geometry of solution. The presented case study depicts a method for selecting the optimal location of a ground-based ranging source. It is based on a search of a minimum DOP value as a transmitter location function. The parameters of objective function are the elevation and azimuth of the transceiver. The solution was based on a limited-memory Broyden–Fletcher–Goldfarb–Shanno with Box constraints (L-BFGS-B) method and a numerical optimization algorithm for parameter value estimation. The presented approach allows for the selection of the optimal location of a ground-based source of ranging signals in GNSS processing from a geometry of solution point of view. This can be useful at the design stage of an augmentation network of ground-based transceivers. This article presents a theoretical basis and a case study presenting the selection of the optimal location of a ground-based ranging source. Full article
(This article belongs to the Special Issue Geodesy and Geomatics Engineering)
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Open AccessArticle
Down-Sampling of Point Clouds for the Technical Diagnostics of Buildings and Structures
Geosciences 2019, 9(2), 70; https://doi.org/10.3390/geosciences9020070
Received: 18 December 2018 / Revised: 24 January 2019 / Accepted: 27 January 2019 / Published: 30 January 2019
Cited by 1 | PDF Full-text (5319 KB) | HTML Full-text | XML Full-text
Abstract
Terrestrial laser scanning (TLS) is a non-destructive testing method for the technical assessment of existing structures. TLS has been successfully harnessed for monitoring technical surface conditions and morphological characteristics of historical buildings (e.g., the detection of cracks and cavities). TLS measurements with very [...] Read more.
Terrestrial laser scanning (TLS) is a non-destructive testing method for the technical assessment of existing structures. TLS has been successfully harnessed for monitoring technical surface conditions and morphological characteristics of historical buildings (e.g., the detection of cracks and cavities). TLS measurements with very high resolution should be taken to detect minor defects on the walls of buildings. High-resolution measurements are mostly needed in certain areas of interest, e.g., cracks and cavities. Therefore, reducing redundant information on flat areas without cracks and cavities is very important. In this case, automatic down-sampling of datasets according to the aforementioned criterion is required. This paper presents the use of the Optimum Dataset (OptD) method to optimize TLS dataset. A Leica ScanStation C10 time-of-flight scanner and a Z+F IMAGER 5016 phase-shift scanner were used during the research. The research was conducted on a specially prepared concrete sample and real object, i.e., a brick citadel located on the Kościuszko Mound in Cracow. The reduction of dataset by the OptD method and random method from TLS measurements were compared and discussed. The results prove that the large datasets from TLS diagnostic measurements of buildings and structures can be successfully optimized using the OptD method. Full article
(This article belongs to the Special Issue Geodesy and Geomatics Engineering)
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Open AccessArticle
A Comparative Study of the AHP and TOPSIS Techniques for Dam Site Selection Using GIS: A Case Study of Sistan and Baluchestan Province, Iran
Geosciences 2018, 8(12), 494; https://doi.org/10.3390/geosciences8120494
Received: 31 October 2018 / Revised: 11 December 2018 / Accepted: 12 December 2018 / Published: 17 December 2018
Cited by 4 | PDF Full-text (2974 KB) | HTML Full-text | XML Full-text
Abstract
The application of multiple criteria decision-making (MCDM) techniques in real-life problems has increased in recent years. The need to build advanced decision models with higher capabilities that can support decision-making in a broad spectrum of applications, promotes the integration of MCDM techniques with [...] Read more.
The application of multiple criteria decision-making (MCDM) techniques in real-life problems has increased in recent years. The need to build advanced decision models with higher capabilities that can support decision-making in a broad spectrum of applications, promotes the integration of MCDM techniques with applicable systems, including artificial intelligence, and Geographic Information Systems (GIS). The Analytic Hierarchy Process (AHP) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) are among the most widely adopted MCDM techniques capable of resolving water resources challenges. A critical problem associated with water resource management is dam site selection. This paper presents a comparative analysis of TOPSIS and AHP in the context of decision-making using GIS for dam site selection. The comparison was made based on geographic and water quality criteria. The geographical criteria are geology, land use, sediment, erosion, slope, groundwater, and discharge. The water quality criteria include Soluble Sodium Percentage, Total Dissolved Solid, Potential of Hydrogen, and Electrical Conductivity of water. A ratio estimation procedure was used to determine the weights of these criteria. Both methods were applied for selection of optimal sites for dams in the Sistan and Baluchestan province, Iran. The results show that the TOPSIS method is better suited to the problem of dam site selection for this study area. Actual locations of dams constructed in the area were used to verify the results of both methods. Full article
(This article belongs to the Special Issue Geodesy and Geomatics Engineering)
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