Nova formula za izračun koeficijenta korelacije u geodetskim mjerenjima za mali broj opažanja

When performing geodetic surveys, the number of measurements is usually small, which in the case of dependent series of measurements leads to an underestimation of the correlation coefficient calculated by the standard formula. A new formula for determining the correlation coefficient is proposed. The values of correlation coefficients calculated by the new formula and by the known ones were compared for the number of measurements . It was found that the correlation coefficient values calculated by the new formula will have higher values as compared to the values calculated by the known formulas, i.e. these values will be less biased with respect to the true values of the correlation coefficients. The correlation coefficients obtained by the new formula will be maximal at an appropriate level of significance and number of degrees of freedom. With a large number of measurements, the values of correlation coefficients obtained by the new formula and by the formulas that are widely used in geodesy and photogrammetry will not differ significantly.Prilikom izvođenja geodetskih izmjera, broj mjerenja je obično mali što u slučaju serije ovisnih mjerenja dovodi do niske procjene koeficijenta korelacije izračunatog pomoću standardne formule. Predlaže se nova formula za određivanje koeficijenta korelacije. Uspoređene su vrijednosti koeficijenta korelacije izračunate pomoću nove formule i pomoću poznatih formula za broj mjerenja . Utvrđeno je da će vrijednosti koeficijenta korelacije izračunate novom formulom biti veće u usporedbi s vrijednostima izračunatima pomoću poznatih formula, odnosno te vrijednosti će biti manje pristrane u odnosu na prave vrijednosti koeficijenata korelacije. Koeficijenti korelacije dobiveni pomoću nove formule bit će maksimalni na odgovarajućoj razini značaja i broja stupnjeva slobode. Za veliki broj mjerenja, vrijednosti koeficijenata korelacije dobivene novom formulom i formulama čija je upotreba raširena u geodeziji i fotogrametriji neće se značajno razlikovati

Nova formula za izračun koeficijenta korelacije u geodetskim mjerenjima za mali broj opažanja

When performing geodetic surveys, the number of measurements is usually small, which in the case of dependent series of measurements leads to an underestimation of the correlation coefficient calculated by the standard formula. A new formula for determining the correlation coefficient is proposed. The values of correlation coefficients calculated by the new formula and by the known ones were compared for the number of measurements . It was found that the correlation coefficient values calculated by the new formula will have higher values as compared to the values calculated by the known formulas, i.e. these values will be less biased with respect to the true values of the correlation coefficients. The correlation coefficients obtained by the new formula will be maximal at an appropriate level of significance and number of degrees of freedom. With a large number of measurements, the values of correlation coefficients obtained by the new formula and by the formulas that are widely used in geodesy and photogrammetry will not differ significantly.Prilikom izvođenja geodetskih izmjera, broj mjerenja je obično mali što u slučaju serije ovisnih mjerenja dovodi do niske procjene koeficijenta korelacije izračunatog pomoću standardne formule. Predlaže se nova formula za određivanje koeficijenta korelacije. Uspoređene su vrijednosti koeficijenta korelacije izračunate pomoću nove formule i pomoću poznatih formula za broj mjerenja . Utvrđeno je da će vrijednosti koeficijenta korelacije izračunate novom formulom biti veće u usporedbi s vrijednostima izračunatima pomoću poznatih formula, odnosno te vrijednosti će biti manje pristrane u odnosu na prave vrijednosti koeficijenata korelacije. Koeficijenti korelacije dobiveni pomoću nove formule bit će maksimalni na odgovarajućoj razini značaja i broja stupnjeva slobode. Za veliki broj mjerenja, vrijednosti koeficijenata korelacije dobivene novom formulom i formulama čija je upotreba raširena u geodeziji i fotogrametriji neće se značajno razlikovati

Suvremene tehnologije geodetske podrške u planiranju radova u visokogradnji

The work shows the shortcomings of traditional geodetic technologies in the limited space of a modern construction site on the basis of research and analysis of literature sources, regulatory and production base of geodetic support in the construction of multi-storey buildings. Today, electronic tacheometers are used to perform planning works, which allowed to perform planning of building structures without bringing the building axes of the building to the ground, which, in its turn, had an extremely positive effect on compliance with deadlines of construction. When creating a support base on prefabricated horizons during the construction of buildings up to 150 m, it is suggested to use satellite technology with subsequent planning of building structures directly using electronic tacheometers.U radu se prikazuju nedostaci tradicionalnih tehnologija u ograničenom prostoru suvremenoga gradilišta na temelju istraživanja i analize literature, regulatorne i proizvodne osnove geodetske podrške u izgradnji višekatnih zgrada. Danas se elektronički tahimetri primjenjuju za provedbu radova u planiranju, što je omogućilo izvođenje planiranja građevinskih konstrukcija bez spuštanja građevnih osi objekta na tlo što je imalo pozitivan učinak na poštivanje rokova izgradnje. Prilikom uspostave potporne osnove na montažnim horizontima tijekom izgradnje zgrada visine do 150 m predlaže se primjena satelitske tehnologije s naknadnim planiranjem građevinskih konstrukcija primjenom elektroničkih tahimetara

Temporal Variations in Land Surface Temperature within an Urban Ecosystem: A Comprehensive Assessment of Land Use and Land Cover Change in Kharkiv, Ukraine

Peer reviewed: TrueAcknowledgements: The author Lillia Hebryn-Baidy expresses her gratitude to the British Academy and the Council for At-Risk Academics for providing support to this research study through the Researchers at Risk Research Support Grants. Sincere gratitude goes to the Department of Geography at the University of Cambridge and the Scott Polar Research Institute for their support throughout the research process. The author Vadym Belenok expresses his gratitude to the Ukrainian-Polish project “Urban greenery monitoring as an element of sustainable development principles and green deal implementation”.Publication status: PublishedRemote sensing technologies are critical for analyzing the escalating impacts of global climate change and increasing urbanization, providing vital insights into land surface temperature (LST), land use and cover (LULC) changes, and the identification of urban heat island (UHI) and surface urban heat island (SUHI) phenomena. This research focuses on the nexus between LULC alterations and variations in LST and air temperature (Tair), with a specific emphasis on the intensified SUHI effect in Kharkiv, Ukraine. Employing an integrated approach, this study analyzes time-series data from Landsat and MODIS satellites, alongside Tair climate records, utilizing machine learning techniques and linear regression analysis. Key findings indicate a statistically significant upward trend in Tair and LST during the summer months from 1984 to 2023, with a notable positive correlation between Tair and LST across both datasets. MODIS data exhibit a stronger correlation (R2 = 0.879) compared to Landsat (R2 = 0.663). The application of a supervised classification through Random Forest algorithms and vegetation indices on LULC data reveals significant alterations: a 70.3% increase in urban land and a decrement in vegetative cover comprising a 15.5% reduction in dense vegetation and a 62.9% decrease in sparse vegetation. Change detection analysis elucidates a 24.6% conversion of sparse vegetation into urban land, underscoring a pronounced trajectory towards urbanization. Temporal and seasonal LST variations across different LULC classes were analyzed using kernel density estimation (KDE) and boxplot analysis. Urban areas and sparse vegetation had the smallest average LST fluctuations, at 2.09 °C and 2.16 °C, respectively, but recorded the most extreme LST values. Water and dense vegetation classes exhibited slightly larger fluctuations of 2.30 °C and 2.24 °C, with the bare land class showing the highest fluctuation 2.46 °C, but fewer extremes. Quantitative analysis with the application of Kolmogorov-Smirnov tests across various LULC classes substantiated the normality of LST distributions p > 0.05 for both monthly and annual datasets. Conversely, the Shapiro-Wilk test validated the normal distribution hypothesis exclusively for monthly data, indicating deviations from normality in the annual data. Thresholded LST classifies urban and bare lands as the warmest classes at 39.51 °C and 38.20 °C, respectively, and classifies water at 35.96 °C, dense vegetation at 35.52 °C, and sparse vegetation 37.71 °C as the coldest, which is a trend that is consistent annually and monthly. The analysis of SUHI effects demonstrates an increasing trend in UHI intensity, with statistical trends indicating a growth in average SUHI values over time. This comprehensive study underscores the critical role of remote sensing in understanding and addressing the impacts of climate change and urbanization on local and global climates, emphasizing the need for sustainable urban planning and green infrastructure to mitigate UHI effects

Determining the form of error distribution of geodetic measuring

Industrial equipment is a dynamic system and has deformations not only during installation but also during operation. Under the influence of variable load and displacement of the center of gravity, the soil under the foundation settles unevenly, and accordingly, the equipment deforms unevenly, which is a threat to the equipment, the greater the load corresponds to more subsidence.Separation of partial deformations from full is important for determining the elements of straightening equipment for its uninterrupted and trouble-free operation. The presence of significant total deformation does not affect the performance of the equipment. The most critical deformations are partial deformations. Absolute vertical deformations are calculated as the difference in sediment between adjacent sediment marks, which are fixed on the equipment in the same measurement cycle.Comparing the values of deformations with the allowable technical conditions, decide on the need for straightening and adjustment of equipment.The accuracy of installation is characterized by a tolerance of 0.1÷0.5 mm on the relative position of the equipment, which is conjugate mounted at a distance of several tens or hundreds of meters. For installation of the equipment with such accuracy carry out special geodetic works with use of methods and technical means of measurements specially developed for this purpose in geodesy, metrology and mechanical engineering

Accuracy of coordinate determinations of the network of protected zone points according to the results of GNSS observations

The article examines errors of the planned position of the points of the educational and research site “Fortuna” of the Chernihiv Polytechnic National University (Ukraine), located in a forested area. Kinematic positioning has been performed using a GNSS receiver GeoMax Zenith 10/20 in real time mode. The network of permanent satellite GNSS stations System NET has been used as a coordinate basis. RTK Master Auxiliary Corrections (MAX) technology has been used to form the corrective amendments. The calculation of RTK corrections has been performed using the software package Leica GNSS Spider v4.3. The Transverse Mercator cartographic projection has been used to determine the flat rectangular coordinates in the USK-2000 system. The values of the coordinates determined in the RTK mode have been compared with the coordinates obtained by the method of electronic polygonometry, which are estimated to be 3 times more accurate. Coordinate differences have formed error vectors. As a result of analysis of the vector field, a stable tendency has been established: the deviation of the planned coordinates of the site points, determined by the method of GNSS-observations in real time mode and located in the forest park zone, in the direction of the base station

Supplementary data for "Temporal Variations in Land Surface Temperature within an Urban Ecosystem: A Comprehensive Assessment of Land Use and Land Cover Change in Kharkiv, Ukraine"

Supplementary data to support the paper "Temporal Variations in Land Surface Temperature within an Urban Ecosystem: A Comprehensive Assessment of Land Use and Land Cover Change in Kharkiv, Ukraine" S1: Table of Landsat satellite images used in analysis of Urban Heat Island effect in Kharkiv, Ukraine S2: Table listing calculated values of Land Surface Temperature for different land cover types in Kharkiv, Ukraine. S3. Table of land surface temperature thresholds used to discriminate different land cover types in Kharkiv, Ukraine (April to September 1996-2023). S4. Maps of surface urban heat island (SUHI) strength in Kharkiv, Ukraine, for July of various years between 1996 and 2022

Temporal Variations in Land Surface Temperature within an Urban Ecosystem: A Comprehensive Assessment of Land Use and Land Cover Change in Kharkiv, Ukraine

Remote sensing technologies are critical for analyzing the escalating impacts of global climate change and increasing urbanization, providing vital insights into land surface temperature (LST), land use and cover (LULC) changes, and the identification of urban heat island (UHI) and surface urban heat island (SUHI) phenomena. This research focuses on the nexus between LULC alterations and variations in LST and air temperature (Tair), with a specific emphasis on the intensified SUHI effect in Kharkiv, Ukraine. Employing an integrated approach, the study analyzes time-series data from Landsat and MODIS satellites, alongside Tair climate records, utilizing machine learning techniques and linear regression analysis. Key findings indicate a statistically significant upward trend in Tair and LST during summer months from 1984 to 2023, with a notable positive correlation between Tair and LST across both datasets. MODIS data exhibit a stronger correlation R² = 0.879, compared to Landsat R² = 0.663. The application of supervised classification through Random Forest algorithms and vegetation indices on LULC data reveals significant alterations, manifested as a 70.3% increase in urban land, concurrently with a decrement in vegetative cover, especially 15.5% reduction in dense vegetation and a 62.9% decrease in sparse vegetation. Change detection analysis elucidates a 24.6% conversion of sparse vegetation into urban land, underscoring a pronounced trajectory towards urbanization. Temporal and seasonal LST variations across different LULC classes were analyzed using kernel density estimation (KDE) and boxplot analysis. Urban areas and sparse vegetation had the smallest average LST fluctuations, at 2.09°C and 2.16°C, respectively, but recorded the most extreme LST values. Water and dense vegetation classes exhibited slightly larger fluctuations of 2.30°C and 2.24°C, with the bare land class showing the highest fluctuation 2.46°C, but fewer extremes. Quantitative analysis with the application of Kolmogorov-Smirnov tests across various LULC classes substantiated the normality of LST distributions p > 0.05 for both monthly and annual data sets. Conversely, the Shapiro-Wilk test validated the normal distribution hypothesis exclusively for monthly data, indicating deviations from normality in the annual data. Thresholded LST classifies urban and bare lands as warmest classes with 39.51°C, 38.20°C and water by 35.96°C and dense vegetation 35.52°C, sparse vegetation 37.71°C as coldest, a trend consistent annually and monthly. The analysis of SUHI effects demonstrates an increasing trend in UHI intensity, with statistical trends indicating a growth in average SUHI values over time. This comprehensive study underscores the critical role of remote sensing in understanding and addressing the impacts of climate change and urbanization on local and global climates, emphasizing the need for sustainable urban planning and green infrastructure to mitigate UHI effects

Device for automated leveling

The article describes the issue of automation of surface leveling performed during the reconstruction of artificial aerodrome covers. The existing methods of surface leveling using satellite technologies, electronic (digital) and laser rotational levels are described. The main drawbacks of existing methods are analyzed, the essence of which is reduced mainly to the large amount of manual measurements. A new mobile device for automated surface leveling is proposed, the distinctive parts of which are mobile platform, leveling optoelectronic device (LOED) and ultrasonic location block. The LOED includes lenses and a double Charge-Coupled Device (CCD) Matrix. To perform the leveling of the surface in the leveling marking the ends of the leveling lines, which are parallel to the longitudinal axis of the leveling plot is done. The leveling lines fix two points (benchmarks) where elevation points are first-order as compared with elevation points of leveling the surface. Two reference sighting targets on the benchmarks are installed. In the memory of the device such data as: instrumental elevations, elevations LOED and elevations sighting targets, as well as the scanning step are entered. The device LOED is installed to the alignment between sighting targets the position in the alignment of the images of targets on the display are controlled. The device is installed sequentially to the points of scanning the surface along the alignment line and define the readings on the LOED matrixes at the points of leveling the surface during stops or movement of the device on the alignment line. As a result of measurements in automatic mode, the instrumental elevations along the alignment line with an adjustable scan step are obtained. Such a device due to increased mobility is effective for leveling large and length areas, such as take-off and landing strip, take-off starts, airplane platforms, etc

Device for automated leveling

The article describes the issue of automation of surface leveling performed during the reconstruction of artificial aerodrome covers. The existing methods of surface leveling using satellite technologies, electronic (digital) and laser rotational levels are described. The main drawbacks of existing methods are analyzed, the essence of which is reduced mainly to the large amount of manual measurements. A new mobile device for automated surface leveling is proposed, the distinctive parts of which are mobile platform, leveling optoelectronic device (LOED) and ultrasonic location block. The LOED includes lenses and a double Charge-Coupled Device (CCD) Matrix. To perform the leveling of the surface in the leveling marking the ends of the leveling lines, which are parallel to the longitudinal axis of the leveling plot is done. The leveling lines fix two points (benchmarks) where elevation points are first-order as compared with elevation points of leveling the surface. Two reference sighting targets on the benchmarks are installed. In the memory of the device such data as: instrumental elevations, elevations LOED and elevations sighting targets, as well as the scanning step are entered. The device LOED is installed to the alignment between sighting targets the position in the alignment of the images of targets on the display are controlled. The device is installed sequentially to the points of scanning the surface along the alignment line and define the readings on the LOED matrixes at the points of leveling the surface during stops or movement of the device on the alignment line. As a result of measurements in automatic mode, the instrumental elevations along the alignment line with an adjustable scan step are obtained. Such a device due to increased mobility is effective for leveling large and length areas, such as take-off and landing strip, take-off starts, airplane platforms, etc