The paper describes the estimation of covariance parameters in least squares collocation (LSC) by the cross-validation (CV) technique called leave-one-out (LOO). Two parameters of Gauss-Markov third order model (GM3) are estimated together with a priori noise standard deviation, which contributes significantly to the covariance matrix composed of the signal and noise. Numerical tests are performed using large set of Bouguer gravity anomalies located in the central part of the U.S. Around 103 000 gravity stations are available in the selected area. This dataset, together with regular grids generated from EGM2008 geopotential model, give an opportunity to work with various spatial resolutions of the data and heterogeneous variances of the signal and noise. This plays a crucial role in the numerical investigations, because the spatial resolution of the gravity data determines the number of gravity details that we may observe and model. This establishes a relation between the spatial resolution of the data and the resolution of the gravity field model. This relation is inspected in the article and compared to the regularization problem occurring frequently in data modeling.
Land use/land cover (LULC) maps are important datasets in various environmental projects. Our aim was to demonstrate how GEOBIA framework can be used for integrating different data sources and classification methods in context of LULC mapping.We presented multi-stage semi-automated GEOBIA classification workflow created for LULC mapping of Tuszyma Forestry Management area based on multi-source, multi-temporal and multi-resolution input data, such as 4 bands- aerial orthophoto, LiDAR-derived nDSM, Sentinel-2 multispectral satellite images and ancillary vector data. Various classification methods were applied, i.e. rule-based and Random Forest supervised classification. This approach allowed us to focus on classification of each class ‘individually’ by taking advantage from all useful information from various input data, expert knowledge, and advanced machine-learning tools. In the first step, twelve classes were assigned in two-steps rule-based classification approach either vector-based, ortho- and vector-based or orthoand Lidar-based. Then, supervised classification was performed with use of Random Forest algorithm. Three agriculture-related LULC classes with vegetation alternating conditions were assigned based on aerial orthophoto and Sentinel-2 information. For classification of 15 LULC classes we obtained 81.3% overall accuracy and kappa coefficient of 0.78. The visual evaluation and class coverage comparison showed that the generated LULC layer differs from the existing land cover maps especially in relative cover of agriculture-related classes. Generally, the created map can be considered as superior to the existing data in terms of the level of details and correspondence to actual environmental and vegetation conditions that can be observed in RS images.
In this publication, the strategy of land resources administration is presented on the basis of consideration of proposed result factors. The research methodology is based on the use of the PESTLE analytical model in conjunction with economic-mathematical modeling. The scientific novelty of the publication is developing the technology of administration of land resources on the basis of cadastral and other statistical information, which allows obtaining scientifically grounded solutions on the use of land resources. Considering the process of Land Resources Administration as a procedure based on making certain decisions when creating a management system which takes into account the internal and external relationships in this system, the postulate is about determining the degree of trust in this system, establishing economic, environmental and social risks when using it. To a certain extent, the process of Land Resources Administration is a prediction of the effective use of this natural potential in the future. It should be noted that the reliability of the forecast decision depends on the nature and parameters of uncertainties and the duration of their validity. Consequently, while making operational decisions on land resources for a short perspective, the forecasting is more reliable than for a long one. It becomes an effective mechanism of objective evaluation of the state of land resources and the prospects for their use. In this publication the main influencing decision making factors and the technological scheme of the solution of the problem are given.
One of the important issues concerning development of spatial data infrastructures (SDIs) is the carrying out of economic and financial analysis. It is essential to determine expenses and also assess effects resulting from the development and use of infrastructures. Costs and benefits assessment could be associated with assessment of the infrastructure effectiveness and efficiency as well as the infrastructure value, understood as the infrastructure impact on economic aspects of an organisational performance, both of an organisation which realises an SDI project and all users of the infrastructure. The aim of this paper is an overview of various assessment methods of investment as well as an analysis of different types of costs and benefits used for information technology (IT) projects. Based on the literature, the analysis of the examples of the use of these methods in the area of spatial data infrastructures is also presented. Furthermore, the issues of SDI projects and investments are outlined. The results of the analysis indicate usefulness of the financial methods from different fields of management in the area of SDI building, development and use. The author proposes, in addition to the financial methods, the adaptation of the various techniques used for IT investments and their development, taking into consideration the SDI specificity for the purpose of assessment of different types of costs and benefits and integration of financial aspects with non- financial ones. Among the challenges are identification and quantification of costs and benefits, as well as establishing measures which would fit the characteristics of the SDI project and artefacts resulting from the project realisation. Moreover, aspects of subjectivity and variability in time should be taken into account as the consequences of definite goals and policies as well as business context of organisation undertaking the project or using its artefacts and also investors.
The paper presents the results of real time measurements of test geodetic control network points using the RTK GPS and RTX Extended technologies. The Trimble RTX technology uses the xFill function, which enables real measurements without the need for constant connection with the ASG EUPOS system reference stations network. Comparative analyses of the results of measurements using the methods were performed and they were compared with the test control network data assumed to be error-free. Although the Trimble RTX technology is an innovative measurement method which is rarely used now, the possibilities it provides in surveying works, including building geodetic control networks, are satisfactory and it will certainly contribute to improving the organisation of surveying works.
MP estimation is a method which concerns estimating of the location parameters when the probabilistic models of observations differ from the normal distributions in the kurtosis or asymmetry. The system of Pearson’s distributions is the probabilistic basis for the method. So far, such a method was applied and analyzed mostly for leptokurtic or mesokurtic distributions (Pearson’s distributions of types IV or VII), which predominate practical cases. The analyses of geodetic or astronomical observations show that we may also deal with sets which have moderate asymmetry or small negative excess kurtosis. Asymmetry might result from the influence of many small systematic errors, which were not eliminated during preprocessing of data. The excess kurtosis can be related with bigger or smaller (in relations to the Hagen hypothesis) frequency of occurrence of the elementary errors which are close to zero. Considering that fact, this paper focuses on the estimation with application of the Pearson platykurtic distributions of types I or II. The paper presents the solution of the corresponding optimization problem and its basic properties. Although platykurtic distributions are rare in practice, it was an interesting issue to find out what results can be provided by MP estimation in the case of such observation distributions. The numerical tests which are presented in the paper are rather limited; however, they allow us to draw some general conclusions.
The construction of transmission infrastructure and its functioning imposes the obligation on transmission companies to have a legal title to land. Both in Poland and in Canada, the title particularly results from the established easements subject to registration in public information systems. Due to different historical, social, and economic conditions, the specificity of legal regulations and technical solutions related to the registration of rights to land property is different in both countries. This results from the functioning and the substantive scope of particular systems of information on land property. Such systems are regulated by independent, internal rules of each of the countries. In Poland, easement is subject to registration in the land and mortgage register. In Canada, a federation country, it depends on legal regulations of particular provinces. The research objective of the article is the analysis of the way of registration of easements established for transmission companies in Poland and in Canada in the Ontario and Quebec provinces. The analysis covers the scope of registration of the said right in systems of information on land property. The evaluation of the applied solutions particularly involves pointing out those which to the greatest extent guarantee the safety of land property turnover. The best result is obtained in Canada in the Ontario province.
From the theory of reliability it follows that the greater the observational redundancy in a network, the higher is its level of internal reliability. However, taking into account physical nature of the measurement process one may notice that the planned additional observations may increase the number of potential gross errors in a network, not raising the internal reliability to the theoretically expected degree. Hence, it is necessary to set realistic limits for a sufficient number of observations in a network. An attempt to provide principles for finding such limits is undertaken in the present paper. An empirically obtained formula (Adamczewski 2003) called there the law of gross errors, determining the chances that a certain number of gross errors may occur in a network, was taken as a starting point in the analysis. With the aid of an auxiliary formula derived on the basis of the Gaussian law, the Adamczewski formula was modified to become an explicit function of the number of observations in a network. This made it possible to construct tools necessary for the analysis and finally, to formulate the guidelines for determining the upper-bounds for internal reliability indices. Since the Adamczewski formula was obtained for classical networks, the guidelines should be considered as an introductory proposal requiring verification with reference to modern measuring techniques.
The adjustment problem of the so-called combined (hybrid, integrated) network created with GNSS vectors and terrestrial observations has been the subject of many theoretical and applied works. The network adjustment in various mathematical spaces was considered: in the Cartesian geocentric system on a reference ellipsoid and on a mapping plane. For practical reasons, it often takes a geodetic coordinate system associated with the reference ellipsoid. In this case, the Cartesian GNSS vectors are converted, for example, into geodesic parameters (azimuth and length) on the ellipsoid, but the simple form of converted pseudo-observations are the direct differences of the geodetic coordinates. Unfortunately, such an approach may be essentially distorted by a systematic error resulting from the position error of the GNSS vector, before its projection on the ellipsoid surface. In this paper, an analysis of the impact of this error on the determined measures of geometric ellipsoid elements, including the differences of geodetic coordinates or geodesic parameters is presented. Assuming that the adjustment of a combined network on the ellipsoid shows that the optimal functional approach in relation to the satellite observation, is to create the observational equations directly for the original GNSS Cartesian vector components, writing them directly as a function of the geodetic coordinates (in numerical applications, we use the linearized forms of observational equations with explicitly specified coefficients). While retaining the original character of the Cartesian vector, one avoids any systematic errors that may occur in the conversion of the original GNSS vectors to ellipsoid elements, for example the vector of the geodesic parameters. The problem is theoretically developed and numerically tested. An example of the adjustment of a subnet loaded from the database of reference stations of the ASG-EUPOS system was considered for the preferred functional model of the GNSS observations.
Land surveyors, photogrammetrists, remote sensing engineers and professionals in the Earth sciences are often faced with the task of transferring coordinates from one geodetic datum into another to serve their desired purpose. The essence is to create compatibility between data related to different geodetic reference frames for geospatial applications. Strictly speaking, conventional techniques of conformal, affine and projective transformation models are mostly used to accomplish such task. With developing countries like Ghana where there is no immediate plans to establish geocentric datum and still rely on the astro-geodetic datums as it national mapping reference surface, there is the urgent need to explore the suitability of other transformation methods. In this study, an effort has been made to explore the proficiency of the Extreme Learning Machine (ELM) as a novel alternative coordinate transformation method. The proposed ELM approach was applied to data found in the Ghana geodetic reference network. The ELM transformation result has been analysed and compared with benchmark methods of backpropagation neural network (BPNN), radial basis function neural network (RBFNN), two-dimensional (2D) affine and 2D conformal. The overall study results indicate that the ELM can produce comparable transformation results to the widely used BPNN and RBFNN, but better than the 2D affine and 2D conformal. The results produced by ELM has demonstrated it as a promising tool for coordinate transformation in Ghana.
One of the fundamental problems of modern geodesy is precise de fi nition of the gravitational fi eld and its changes in time. This is essential in positioning and navigation, geophysics, geodynamics, oceanography and other sciences related to the climate and Earth’s environment. One of the major sources of gravity data is satellite altimetry that provides gravity data with almost 75% surface of the Earth. Satellite altimetry also provides data to study local, regional and global geophysical processes, the geoid model in the areas of oceans and seas. This technique can be successfully used to study the ocean mean dynamic topography. The results of the investigations and possible products of altimetry will provide a good material for the GGOS (Global Geodetic Observing System) and institutions of IAS (International Altimetry Service). This paper presents the achievements in satellite altimetry in all the above disciplines obtained in the last years. First very shorly basic concept of satellite altimetry is given. In order to obtain the highest accuracy on range measurements over the ocean improved of altimetry waveforms performed on the ground is described. Next, signi fi cant improvements of sea and ocean gravity anomalies models developed presently is shown. Study of sea level and its extremes examined, around European and Australian coasts using tide gauges data and satellite altimetry measurements were described. Then investigations of the phenomenon of the ocean tides, calibration of altimeters, studies of rivers and ice-sheets in the last years are given.
A condition which determines the location of technical infrastructure is an entrepreneur holding the right to use the property for construction purposes. Currently, there are parallel separate legal forms allowing the use of a real property for the purpose of locating transmission lines, i.e. transmission easement (right-of-way) established under the civil law and expropriation by limiting the rights to a property under the administrative law. The aim of the study is to compare these forms conferring the right to use real properties and to analyze the related surveying and legal problems occurring in practice. The research thesis of the article is ascertainment that the current legal provisions for establishing legal titles to a property in order to locate transmission lines need to be amended. The conducted study regarded legal conditions, extent of expropriation and granting right- of-way in the city of Krakow, as well as the problems associated with the ambiguous wording of the legal regulations. Part of the research was devoted to the form of rights to land in order to carry out similar projects in some European countries (France, Czech Republic, Germany, Sweden). The justification for the analysis of these issues is dictated by the scale of practical use of the aforementioned forms of rights to land in order to locate technical infrastructure. Over the period of 2011-2014, 651 agreements were concluded on granting transmission right-of-way for 967 cadastral parcels owned by the city of Krakow, and 105 expropriation decisions were issued, limiting the use of real properties in Krakow.
Amendment to the Act on special rules of preparation and implementation of investment in public roads resulted in an accelerated mode of acquisition of land for the development of roads. The decision to authorize the execution of road investment issued on its basis has several effects, i.e. determines the location of a road, approves surveying division, approves construction design and also results in acquisition of a real property by virtue of law by the State Treasury or local government unit, among others. The conducted study revealed that over 3 years, in this mode, the city of Krakow has acquired 31 hectares of land intended for the implementation of road investments. Compensation is determined in separate proceedings based on an appraisal study estimating property value, often at a distant time after the loss of land by the owner. One reason for the lengthy compensation proceedings is challenging the proposed amount of compensation, unregulated legal status of the property as well as imprecise legislation. It is important to properly develop geodetic and legal documentation which accompanies the application for issuance of the decision and is also used in compensation proceedings.
One of the more important elements of spatial information infrastructure is the organisational structure defining the obligations and dependencies between stakeholders that are responsible for the infrastructure. Many SDI practitioners and theoreticians emphasise that its influence on the success or failure of activities undertaken is significantly greater than that of technical aspects. Being aware of the role of the organisational structure in the creating, operating and maintenance of spatial information infrastructure (SII), Polish legislators placed appropriate regulations in the Spatial Information Infrastructure Act, being the transposition of the INSPIRE Directive into Polish Law. The principal spatial information infrastructure stakeholders are discussed in the article and also the scope of cooperation between them. The tasks and relationships between stakeholders are illustrated in UML, in both the use case and the class diagram. Mentioned also are the main problems and obstructions resulting from imprecise legal regulations.
The wide access to source data, published by numerous websites, results in situation, when information acquisition is not a problem any more. The real problem is how to transform information in the useful knowledge . Cartographic method of research, dealing with spatial data, has been serving this purpose for many years. Nowadays, it allows conducting analyses at the high complexity level, thanks to the intense development in IT technologies, The vast majority of analytic methods utilizing the so-called data mining and data enrichment techniques, however, concerns non-spatial data. According to the Authors, utilizing those techniques in spatial data analysis (including analysis based on statistical data with spatial reference), would allow the evolution of the Spatial Information Infrastructure (SII) into the Spatial Knowledge Infrastructure (SKI). The SKI development would benefit from the existence of statistical geoportal. Its proposed functionality, consisting of data analysis as well as visualization, is outlined in the article. The examples of geostatistical analyses (ANOVA and the regression model considering the spatial neighborhood), possible to implement in such portal and allowing to produce the “cartographic added value”, are also presented here
The issue of line simplification is one of the fundamental problems of generalisation of geographical information, and the proper parameterisation of simplification algorithms is essential for the correctness and cartographic quality of the results. The authors of this study have attempted to apply computational intelligence methods in order to create a cartographic knowledge base that would allow for non-standard parameterisation of WEA (Weighted Effective Area) simplification algorithm. The aim of the conducted research was to obtain two independent methods of non-linear weighting of multi-dimensional regression function that determines the “importance” of specific points on the line and their comparison to each other. The first proposed approach consisted in the preparation of a set of cartographically correct examples constituting a basis for teaching a neural network, while the other one consisted in defining inference rules using fuzzy logic. The obtained results demonstrate that both methods have great potential, although the proposed solutions require detailed parameterisation taking into account the specificity of geometric variety of the source data.
Land consolidation procedures are an attempt to comprehensively change the existing spatial structure of land in rural areas. This treatment also brings many other social and economic benefits, contributing to the development of consolidated areas. Land consolidation in mountain areas differs in many respects from those implemented in areas with more favorable conditions for the functioning of agriculture. The unfavorable values of land fragmentation indices, terrain conditions and lower than the average soil quality affect both the dominant forms of agricultural activity and the limited opportunities to improve the distribution of plots in space, parameters of shape, and the area as a result of land consolidation. For this reason, the effectiveness of land consolidation in mountain areas can be achieved by improving the quality of transportation network and the accessibility of the plots, arranging ownership issues and improving the quality of cadastral documentation. This article presents the evaluation of the measures of effectiveness of land consolidation realized in mountain areas on the example of Łetownia Village in the Małopolska Province, located in the southern part of Poland. Selected village is an area with unfavorable conditions for the functioning of agriculture and high values of land fragmentation indices.
Various sectors of the economy such as transport and renewable energy have shown great interest in sea bed models. The required measurements are usually carried out by ship-based echo sounding, but this method is quite expensive. A relatively new alternative is data obtained by airborne lidar bathymetry. This study investigates the accuracy of these data, which was obtained in the context of the project ‘Investigation on the use of airborne laser bathymetry in hydrographic surveying’. A comparison to multi-beam echo sounding data shows only small differences in the depths values of the data sets. The IHO requirements of the total horizontal and vertical uncertainty for laser data are met. The second goal of this paper is to compare three spatial interpolation methods, namely Inverse Distance Weighting (IDW), Delaunay Triangulation (TIN), and supervised Artificial Neural Networks (ANN), for the generation of sea bed models. The focus of our investigation is on the amount of required sampling points. This is analyzed by manually reducing the data sets. We found that the three techniques have a similar performance almost independently of the amount of sampling data in our test area. However, ANN are more stable when using a very small subset of points.
The processing of cartographic data demands human involvement. Up-to-date algorithms try to automate a part of this process. The goal is to obtain a digital model, or additional information about shape and topology of input geometric objects. A topological skeleton is one of the most important tools in the branch of science called shape analysis. It represents topological and geometrical characteristics of input data. Its plot depends on using algorithms such as medial axis, skeletonization, erosion, thinning, area collapse and many others. Area collapse, also known as dimension change, replaces input data with lower-dimensional geometric objects like, for example, a polygon with a polygonal chain, a line segment with a point. The goal of this paper is to introduce a new algorithm for the automatic calculation of polygonal chains representing a 2D polygon. The output is entirely contained within the area of the input polygon, and it has a linear plot without branches. The computational process is automatic and repeatable. The requirements of input data are discussed. The author analyzes results based on the method of computing ends of output polygonal chains. Additional methods to improve results are explored. The algorithm was tested on real-world cartographic data received from BDOT/GESUT databases, and on point clouds from laser scanning. An implementation for computing hatching of embankment is described.
The paper attempts to determine an optimum structure of a directional measurement and control network intended for investigating horizontal displacements. For this purpose it uses the notion of entropy as a logarithmical measure of probability of the state of a particular observation system. An optimum number of observations results from the difference of the entropy of the vector of parameters X X ˆ H ' corresponding to one extra observation. An increment of entropy interpreted as an increment of the amount of information about the state of the system determines the adoption or rejection of another extra observation to be carried out.
The paper presents the operation of two neuro-fuzzy systems of an adaptive type, intended for solving problems of the approximation of multi-variable functions in the domain of real numbers. Neuro-fuzzy systems being a combination of the methodology of artiﬁcial neural networks and fuzzy sets operate on the basis of a set of fuzzy rules “if-then”, generated by means of the self-organization of data grouping and the estimation of relations between fuzzy experiment results. The article includes a description of neuro-fuzzy systems by Takaga-Sugeno-Kang (TSK) and Wang-Mendel (WM), and in order to complement the problem in question, a hierarchical structural self-organizing method of teaching a fuzzy network. A multi-layer structure of the systems is a structure analogous to the structure of “classic” neural networks. In its ﬁnal part the article presents selected areas of application of neuro-fuzzy systems in the ﬁeld of geodesy and surveying engineering. Numerical examples showing how the systems work concerned: the approximation of functions of several variables to be used as algorithms in the Geographic Information Systems (the approximation of a terrain model), the transformation of coordinates, and the prediction of a time series. The accuracy characteristics of the results obtained have been taken into consideration.
The key to fingerprint positioning algorithm is establishing effective fingerprint information database based on different reference nodes of received signal strength indicator (RSSI). Traditional method is to set the location area calibration multiple information sampling points, and collection of a large number sample data what is very time consuming. With Zigbee sensor networks as platform, considering the influence of positioning signal interference, we proposed an improved algorithm of getting virtual database based on polynomial interpolation, while the pre-estimated result was disposed by particle filter. Experimental result shows that this method can generate a quick, simple fine-grained localization information database, and improve the positioning accuracy at the same time.