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.
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.
This article analyzes the technology of creating and updating a digital topographic map using the method of mapping (generalization) on an updated map with a scale of 1 : 25;000 based on the source cartographic material. The main issue in the creation of digital maps is the study of map production accuracy and error analysis arising from the process of map production. When determining the quality of a digital map, the completeness and accuracy of object and terrain mapping are evaluated. The correctness of object identification, the logical consistency of the structure, the and representation of objects are assessed. The main and the most effective method, allowing to take into account displacement errors for the relief during image processing, is orthotransformation, but the fragment used to update the digital topographic map needs additional verification of its compliance with the scale requirements of the map. Instrumental survey will help to clearly identify areas of space image closer to nadir points and to reject poor quality material. The software used for building geodetic control network should provide stable results of accuracy regardless on the scale of mapping, the physical and geographical conditions of the work area or the conditions of aerial photography.
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.
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.
Polish spatial data infrastructure dates back 2010, the year when the Spatial Information Infrastructure Act transposing INSPIRE Directive entered into force. The present study provides valuable insight into the current status of Polish spatial data infrastructure (PSDI) as well as lessons learnt from so far efforts in implementing the principles and provisions of the INSPIRE Directive. Particular respect is given to policy, interoperability of data as well as cooperation between actors involved in PSDI establishment and maintenance. Data managed by the Surveyor General (SG), perceived as a backbone of a spatial data infrastructure, are of special importance. Finally, some conclusions and recommendations for further developments are given to foster SDI implementation in Poland. Results of the analysis clearly show that Polish spatial data infrastructure is in line with INSPIRE, and in a half of way being fully operational.
Population density varies sharply from place to place on the whole territory of Poland. The largest number of people per 1 km2 is 21,531, while uninhabited areas account for about 48% of the country. Such uneven, non-Gaussian distribution of the data causes some difficulty in choosing the classification method in geometric choropleth maps. A thorough evaluation of a geometric choropleth map of population data is not possible using only traditional indicators such as the Tabular Accuracy Index (TAI). That is why the aim of the article is to develop an innovative index based on distance analysis and neighbour analysis of grid cells. Two indexes have been suggested in this paper: the Spatial Distance Index (SDI) and the Spatial Contiguity Index (SCI). The paper discusses the use of five classification methods to evaluate choropleth maps of population data, like head-tail breaks, natural breaks, equal intervals, quantile, and geometrical intervals. A comprehensive assessment of such geometric choropleth maps is also done. The research was conducted for the whole territory of Poland, using data from the 2011 National Census of Population and Housing. Population data are presented in the 1km grid. The results of the analysis are shown on thematic maps. A compatibility of the choropleth maps with urban-rural typology of the OECD (Organisation for Economic Co-operation and Development) was also checked.
In this paper, two techniques for calculating the geoid-to-quasigeoid separation are employed. One of them is GPS/Levelling customary method as a criterion where the geoid undulation and height anomaly are computed by subtracting the ellipsoid height attained via GPS from the orthometric height and normal height, respectively. Another approach is Sjöberg’s equation. We have used of the ICGEM website for definition of the variables of the Sjöberg’s equation, as the applied reference model is the EGM2008 global geopotential model and WGS84 reference ellipsoid. The investigations are performed over the stations of the GPS/Leveling network related to three selected areas in desert, mountain and flatland namely the Lout, Zagros and Khuzestan in Iran and afterward the correlation coefficient between the geoid-to-quasigeoid separation calculated using the satellite data in Sjöberg’s equation and GPS/Levelling method is estimated. The results indicate a straight correlation between the estimated separations from the two methods as its value for the Lout is 0.754, for the Zagros is 0.497 and for the Khuzestan is 0.659. consequently, using the satellite data in Sjöberg’s equation for the regions where there are not the GPS/Levelling and land gravity data, specially for the even areas, yield a satisfactory response of the geoidto-quasigeoid separation.
The aim of the research was to analyze the possibility of using mobile laser scanning systems to acquire information for production and/or updating of a basic map and to propose a no-reference index of this accuracy assessment. Point clouds have been analyzed in terms of content of interpretation and geometric potential. For this purpose, the accuracy of point clouds with a georeference assigned to the base map objects was examined. In order to conduct reference measurements, a geodetic network was designed and also additional static laser scanning data has been used. The analysis of mobile laser scanning (MLS) data accuracy was conducted with the use of 395 check points. In the paper, application of the total Error of Position of the base-map Objects acquired with the use of MLS was proposed. Research results were related to reference total station measurements. The resulting error values indicate the possibility to use an MLS point cloud in order to accurately determine coordinates for individual objects for the purposes of standard surveying studies, e.g. for updating some elements of the base map content. Nevertheless, acquiring MLS point clouds with satisfying accuracy not always is possible, unless specific resolution condition is fulfilled. The paper presents results of accuracy evaluation in different classes of base-map elements and objects.
Terrestrial laser scanner (TLS) is a new class of survey instruments to capture spatial data developed rapidly. A perfect facility in the oil industry does not exist. As facilities age, oil and gas companies often need to revamp their plants to make sure the facilities still meet their specifications. Due to the complexity of an oil plant site, there are difficulties in revamping, having all dimensions and geometric properties, getting through narrow spaces between pipes and having the description label of each object within a facility site. So it is needed to develop an accurate observations technique to overcome these difficulties. TLS could be an unconventional solution as it accurately measures the coordinates identifying the position of each object within the oil plant and provide highly detailed 3D models. This paper investigates creating 3D model for Ras Gharib oil plant in Egypt and determining the geometric properties of oil plant equipment (tank, vessels, pipes . . . etc.) using TLS observations and modeling by CADWORX program. The modeling involves an analysis of several scans of the oil plant. All the processes to convert the observed points cloud into a 3D model are described. The geometric properties for tanks, vessels and pipes (radius, center coordinates, height and consequently oil volume) are also calculated and presented. The results provide a significant improvement in observing and modeling of an oil plant and prove that the TLS is the most effective choice for generating a representative 3D model required for oil plant revamping.
This paper provides analyses of the accuracy and convergence time of the PPP method using GPS systems and different IGS products. The official IGS products: Final, Rapid and Ultra Rapid as well as MGEX products calculated by the CODE analysis centres were used. In addition, calculations with weighting function of the observations were carried out, depending on the elevation angle. The best results were obtained for CODE products, with a 5-minute interval precision ephemeris and precise corrections to satellite clocks with a 30-second interval. For these calculations the accuracy of position determination was at the level of 3 cm with a convergence time of 44 min. Final and Rapid products, which were orbit with a 15-minute interval and clock with a 5 minute interval, gave very similar results. The same level of accuracy was obtained for calculations with CODE products, for which both precise ephemeris and precise corrections to satellite clocks with the interval of 5 minutes. For these calculations, the accuracy was 4 cm with the convergence time of 70 min. The worst accuracy was obtained for calculations with Ultra-rapid products, with an interval of 15 minutes. For these calculations, the accuracy was 10 cm with a convergence time of 120 min. The use of the weighting function improved the accuracy of position determination in each case, except for calculations with Ultra-rapid products. The use of this function slightly increased the convergence time, in addition to the CODE calculation, which was reduced to 9 min.
Generally, gross errors exist in observations, and they affect the accuracy of results. We review methods to detect the gross errors by Robust estimation method based on L1-estimation theory and their validity in adjustment of geodetic networks with different condition. In order to detect the gross errors, we transform the weight of accidental model into equivalent one using not standardized residual but residual of observation, and apply this method to adjustment computation of triangulation network, traverse network, satellite geodetic network and so on. In triangulation network, we use a method of transforming into equivalent weight by residual and detect gross error in parameter adjustment without and with condition. The result from proposed method is compared with the one from using standardized residual as equivalent weight. In traverse network, we decide the weight by Helmert variance component estimation, and then detect gross errors and compare by the same way with triangulation network In satellite geodetic network in which observations are correlated, we detect gross errors transforming into equivalent correlation matrix by residual and variance inflation factor and the result is also compared with the result from using standardized residual. The results of detection are shown that it is more convenient and effective to detect gross errors by residual in geodetic network adjustment of various forms than detection by standardized residual.