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.
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.
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.
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.
Unmanned aerial vehicles are increasingly being used in close range photogrammetry. Real-time observation of the Earth’s surface and the photogrammetric images obtained are used as material for surveying and environmental inventory. The following study was conducted on a small area (approximately 1 ha). In such cases, the classical method of topographic mapping is not accurate enough. The geodetic method of topographic surveying, on the other hand, is an overly precise measurement technique for the purpose of inventorying the natural environment components. The author of the following study has proposed using the unmanned aerial vehicle technology and tying in the obtained images to the control point network established with the aid of GNSS technology. Georeferencing the acquired images and using them to create a photogrammetric model of the studied area enabled the researcher to perform calculations, which yielded a total root mean square error below 9 cm. The performed comparison of the real lengths of the vectors connecting the control points and their lengths calculated on the basis of the photogrammetric model made it possible to fully confirm the RMSE calculated and prove the usefulness of the UAV technology in observing terrain components for the purpose of environmental inventory. Such environmental components include, among others, elements of road infrastructure, green areas, but also changes in the location of moving pedestrians and vehicles, as well as other changes in the natural environment that are not registered on classical base maps or topographic maps.
In recent years, Global Navigation Satellite Systems (GNSS) have gained great importance in terms of the benefits it provides such as precise geodetic point positioning, determining crustal deformations, navigation, vehicle monitoring systems and meteorological applications etc. As in Turkey, for this purpose, each country has set up its own GNSS station networks like Turkish National Permanent RTK Network analyzed precise station coordinates and velocities together with the International GNSS Service , Turkish National Fundamental GPS Network and Turkish National Permanent GNSS Network (TNPGN) stations not only are utilized as precise positioning but also GNSS meteorology studies so total number of stations are increased. This work is related to the reactivated of the TRAB IGS station which was established in Karadeniz Technical University, Department of Geomatics Engineering. Within the COST ES1206 Action (GNSS4SWEC) KTU analysis center was established and Trop-NET system developed by Geodetic Observatory Pecny (GOP, RIGTC) in order to troposphere monitoring. The project titled “Using Regional GNSS Networks to Strengthen Severe Weather Prediction” was accepted to the scientific and technological research council of Turkey (TUBITAK). With this project, we will design 2 new constructed GNSS reference station network. Using observation data of network, we will compare water vapor distribution derived by GNSS Meteorology and GNSS Tomography. At this time, KTU AC was accepted as E-GVAP Analysis Centre in December 2016. KTU reference station is aimed to be a member of the EUREF network with these studies.
We evaluated the performance of nine machine learning regression algorithms and their ensembles for sub-pixel estimation of impervious areas coverages from Landsat imagery. The accuracy of imperviousness mapping in individual time points was assessed based on RMSE, MAE and R 2 . These measures were also used for the assessment of imperviousness change intensity estimations. The applicability for detection of relevant changes in impervious areas coverages at sub-pixel level was evaluated using overall accuracy, F-measure and ROC Area Under Curve. The results proved that Cubist algorithm may be advised for Landsat-based mapping of imperviousness for single dates. Stochastic gradient boosting of regression trees (GBM) may be also considered for this purpose. However, Random Forest algorithm is endorsed for both imperviousness change detection and mapping of its intensity. In all applications the heterogeneous model ensembles performed at least as well as the best individual models or better. They may be recommended for improving the quality of sub-pixel imperviousness and imperviousness change mapping. The study revealed also limitations of the investigated methodology for detection of subtle changes of imperviousness inside the pixel. None of the tested approaches was able to reliably classify changed and non-changed pixels if the relevant change threshold was set as one or three percent. Also for five percent change threshold most of algorithms did not ensure that the accuracy of change map is higher than the accuracy of random classifier. For the threshold of relevant change set as ten percent all approaches performed satisfactory.