Subjects -> GEOGRAPHY (Total: 493 journals)
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 Applied GeomaticsJournal Prestige (SJR): 0.733 Citation Impact (citeScore): 3Number of Followers: 4      Hybrid journal (It can contain Open Access articles) ISSN (Print) 1866-928X - ISSN (Online) 1866-9298 Published by Springer-Verlag  [2469 journals]
• Correction to: The interrelationship between LST, NDVI, NDBI, and land
cover change in a section of Lagos metropolis, Nigeria

PubDate: 2022-06-18

• Correction to: A novel architecture of Web-GIS for mapping and analysis of
echinococcosis in Poland

PubDate: 2022-06-10

• Groundwater potential recharge assessment in arid regions using GIS tool:
case of the Medenine shallow aquifer (Southeastern Tunisia)

Abstract: Abstract Potential recharge estimation becomes a necessity for the groundwater resource management. Nevertheless, many difficulties appear in the infiltration fraction determination. In arid and semi-arid regions, groundwater represents the main sources for sectors development (industrial, agriculture, domestic). The Medenine shallow aquifer (Southeastern Tunisia) was almost used for these purposes. It belongs to arid regions, and it is characterized by a limited groundwater recharge. In this case, the main objective of the present study is the estimation of the potential recharge areas. To attempt this aim, a synthetic approach, including (i) the thematic cartography method taking into account five parameters (lithology, slope, stream network, topography and land cover) and (ii) three numerical methods: the chloride model, the Fersi equations, and the Direction Générale des Ressources en Eaux (DGRE) coefficients, was applied. Each thematic map of all models was produced via the Geographic Information Systems (GIS). The thematic cartography method parameters were overlaid using the Raster Calculate Module of GIS tool. Obtained results show a detailed spatial distribution of potential recharge according to the different used parameters, but they neglect the precipitation parameter. Hence, application of the chloride and the FERSI equations shows a similar recharge spatial distribution with a little difference. Furthermore, the DGRE coefficient application shows the more reliable results since it considers both the rainfall and the deposit permeability. The obtained results prove that the GIS tool is a powerful tool for groundwater management and the design of a suitable exploration plan.
PubDate: 2022-06-08

• Comparison between orthometric, normal and spheroidal orthometric heights
over South Africa

Abstract: Abstract This study has been carried out to estimate the differences between spheroidal orthometric, orthometric and normal heights at 141 GPS/levelling stations over South Africa. The comparison is mainly conducted for the purpose of establishing a height system which is more consistent with the South African spheroidal orthometric height system. This is a necessary step towards establishment of a geoid consistent vertical datum as spheroidal orthometric height system applied in South Africa does not correspond to the vertical datum reference surfaces (geoid or quasigeoid). The differences between the orthometric and normal heights are estimated as a function of Bouguer gravity anomalies and the topographic height. The differences between the normal and spheroidal orthometric heights and the orthometric and spheroidal heights are estimated from normal gravity and interpolated actual gravity at the 141 GPS/levelling stations. The magnitudes of the separation between orthometric and normal heights over South Africa are relatively small. However, the land levelling datum (South African spheroidal orthometric height system) is more consistent with the normal height system than orthometric height system. The mean and standard deviation of the differences between orthometric and normal heights at 141 GPS/levelling stations are $$19.4\mathrm{ cm}$$ and $$\pm 17.6\mathrm{ cm}$$ , respectively. The separation between the spheroidal orthometric and normal heights is $$21.3\mathrm{ cm}$$ on average, with a standard deviation of $$\pm 23.8\mathrm{ cm}$$ . The separation between spheroidal orthometric and orthometric heights is $$40.7\mathrm{ cm}$$ on average, with a standard deviation of $$\pm 25.3\mathrm{ cm}$$ . These results indicate that normal height system and the corresponding surface, the quasigeoid model, should be adopted when developing a geoid consistent vertical datum over South Africa.
PubDate: 2022-06-07

• Hybrid extraction of tectonic lineaments from digital elevation model

Abstract: Abstract The extraction of lineaments from spaceborne data is invaluable for a regional tectonic evaluation of rocks. In this study, a hybrid approach consisting of an automated and manual lineament extraction routine was applied for lineament generation using the Mandara Mountains as a case study. The workflow consists of filtering of a high-resolution digital elevation model, automatic extraction of lineaments, Euclidean distance analysis, binary discretisation, spatial integration and manual digitisation. Spatial and statistical techniques such as lineament orientation, lineament length distribution analysis, spatial density and fractal analysis were used in the evaluation of tectonic attributes. A total of eighty lineaments were extracted using the hybrid approach and a rose plot analysis suggests the dominance of NNE-SSW trend alongside less prominent alignment to the WNW-ESE, NE-SW and E-W. The statistically analysed lineament lengths displayed a mean length value of 9.4 km accompanied by a negatively skewed histogram pattern. The spatial density analysis of lineament trends suggests a mean lineament density of 0.68 and mean intersection density of 0.16. Fractal analysis of high lineament density zones suggests a relatively moderate to low fractal dimension value for both lineament trends and lineament intersection patterns. The lineaments within the Mandara Mountains are characterised by a poly deformational tectonic episode accompanied by relatively low fractal dimension which may advance possible reasons for its poor mineral resource potential.
PubDate: 2022-06-01

• Determinants of marginal area reforestation in the Western Carpathians in
the light of consecutive aerial photographs

Abstract: Abstract The quantification of reforestation on abandoned land is of high importance due to various environmental and socio-economic consequences. This article aims to determine the role of different factors in the reforestation of abandoned plots in particular mid-forest glades in the higher parts of the Western Carpathians and to detect the feature of plots covered prevalently with forest. The Reforestation Index (RI) was used to detect changes in reforestation. Bayesian multilevel zero-one inflated beta regression was used to determine the predictors of reforestation. Using the series of consecutive aerial photographs enabled the differences between features of plots with a faster rate of reforestation and plots covered entirely with forest to be shown. The most rapid changes in the RI were observed in plots with the lowest level of solar radiation (north exposure). In contrast, the highest RI concerns plots with south exposure, the highest mean slope, and within plots partly forested in the first year of observation. Such an attitude is crucial for areas where the precise date of land abandonment is unknown because it enables a determination of which type of plot was abandoned first.
PubDate: 2022-06-01

• A GIS-based assessment of long-term traffic accidents using spatiotemporal
and empirical Bayes analysis in Turkey

Abstract: Abstract The number of traffic fatalities continues to rise steadily throughout the world. In 2016, it reached 1.35 million. The spatiotemporal analysis makes a big contribution when used with spatial and statistical analysis together in terms of the understanding of the change. This study focuses on spatiotemporal fluctuations in traffic accident hotspots to gain useful insights into traffic safety in Turkey in 2004–2017 period. For this purpose, 372,800 accident records are arranged on a GIS platform. The areas that lack traffic safety and require more attention were determined using spatial, temporal, and empirical Bayesian analysis. Although similar results were detected with spatiotemporal and empiric Bayes analysis, spatiotemporal analysis was used to understand where traffic accidents clustering, and how the trends of traffic accidents change whether are increasing or decreasing. As a result of the analysis, an increasing trend has been found in many locations in Turkey from 2004 to 2017.
PubDate: 2022-06-01

• Geometric accuracy investigations of terrestrial laser scanner systems in
the laboratory and in the field

Abstract: Abstract This paper summarizes recent research into current terrestrial laser scanners undertaken by the HafenCity University Hamburg and gives an assessment of the geodetic accuracy of the latest generation of scanners. Three separate independent test methods are presented to investigate the geometric accuracy of terrestrial laser scanners under laboratory conditions: (a) distance measurement accuracy to b/w targets and spheres on the 20-m comparator track, (b) comparison of spatial distances in the 3D test field on b/w targets, and (c) investigation of the flatness deviation following the guideline VDI/VDE 2634 (VDI/VDE 2012) on a flat stone slab. The following laser scanners were tested in the lab: Leica BLK360 (2017), Leica RTC360 (2019), Z+F IMAGER 5016 (2019, 2020), Z+F IMAGER 5010 (2020), and Faro Focus3D X330 (2020). The reference measurements were realised with the Leica Absolute Tracker AT960 (2017, 2020) and with the Leica TS60 total station (2019). The results of the geometric accuracy tests in the laboratory show very small deviations in the range of 1–2 mm for most of the scanners, thus corresponding to the manufacturer’s specifications. In addition, five laser scanners were tested in accordance with instruction sheet 7-2014 of the German Society for Geodesy, Geoinformation and Land Management (DVW) for standardised testing of terrestrial laser scanners in the outdoor area of HafenCity University Hamburg. For the execution of the field test procedure, only the standard equipment and software of the respective manufacturers were used. The entire field test procedure, including data acquisition and evaluation, was completed within 4 to 5 h for each scanner. As expected, no significant distance or angle deviations were detected in any of the measurement systems, so that the tested laser scanners are ready-to-use, taking into account the measurement volume recorded.
PubDate: 2022-05-07

• GIS-based spatial prediction of poor-drainage areas using frequency ratio:
a case study of Tekirdag Province, Turkey

Abstract: Abstract The present study aims to identify the distribution and the sensibility ratios of the poorly drained areas of Tekirdag Province. GIS-based frequency ratio (FR) was used to detect areas that are likely to limit agricultural production due to poor drainage. Sensitive areas were identified and classified using susceptibility analysis. Spatial features were calculated and mapped using FR by combining the factors that could cause the drainage problem in the study area. The results indicated that the drainage conditions in the majority of the study area fall in well-drained (20.14%) and somewhat excessively drained (18.22%) classes. Furthermore, the study area was found to be 50.99% well suited, 11.66% suited, 13.35% moderately suited, and 24.00% unsuited, respectively, for agricultural production. About one-third of the unsuited area was found to be under agro-production. Furthermore, agriculturally suited areas were located mostly in plateaus and sloping lands. On the other hand, unsuited areas were located in the lowland areas where the groundwater level is high, the slope is low, and alluvial lithology and heavily textured soil features are present, while most of the scrublands, forest lands, and vineyard land use classes are located in well-drained areas in both provincial boundaries and the hotspot areas. On the other hand, agriculture, paddy fields, barren lands, pasture, and settlements are mostly located in poorly drained areas. To minimize the effect of the drainage problems, it is crucial to detect poorly drained areas using susceptibility analysis on agricultural areas. As a result, the spatial distribution of poor drainage areas can be mapped precisely and so contribute to agricultural productivity. Thus, sustainable agricultural policies can be developed by contributing to the agricultural economy and food security.
PubDate: 2022-04-29

• Change detection of land cover/land use dynamics in arid region of
Bahawalpur District, Pakistan

Abstract: Abstract Satellite remote sensing is an established geospatial technique that provides a precise method of land use and land cover evaluation at a global, regional, or local scale. The current study aims to assess the land cover and land use change of an arid region in Southern Punjab of Pakistan, i.e., Bahawalpur District. Landsat data is more consistent and pragmatic in providing historical imageries of the earth’s surface for conducting such studies for the last 50 years. Satellite data employed in current research includes Landsat 5 TM for historical years of 1987, 1998, and 2009 and Landsat 8 OLI for the t year of 2020. Maximum likelihood supervised classification and change detection techniques are applied to calculate area percent change, annual dynamic rate of change in specific time intervals. Remote sensing indices normalized difference vegetation index and normalized difference bareness index are also employed techniques for change detection procedures in this study. Results show that agriculture area expanded at the rate of 2.3% and barren land reduced at dynamic rate of − 0.5% from 1987 to 2020. Linear regression analysis reveals a strong correlation coefficient R2 of 0.99 between population growth rate and agriculture growth rate with 0.03 level of significance, 0.58 between agriculture growth rate and barren land reduction rate. Vegetation and bareness index-based change detection showed a 13.4% significant decline in bareness and 16.8% increase in vegetation mostly in southern side of the district towards lesser Cholistan. Linear regression between vegetation and bareness index also showed significant correlation R2 of 0.83 in 1987 and 0.91 in 2020. Significant land use change in this arid region is deteriorating the natural environment and arid ecosystem of the study area. Study provides a good example for local stakeholders to identify the more vulnerable parts of land use change in the district for better and sustainable land use planning.
PubDate: 2022-04-29

• Evaluating flood risk management practices and vulnerability mapping in
Alawuha watershed (North Wollo Zone, Ethiopia) using GIS and remote
sensing

Abstract: Abstract The current magnitude of flooding in Ethiopia is unprecedented. It is a typical disaster in Ethiopia with the evidence of the recent Dire Dawa and Omo River surroundings, especially during the rainy season. The situation resulted in much human death and destruction of infrastructures in different parts of the country, and the Alawuha watershed is among the typical areas for this problem. The study’s aim was to evaluate the flood risk management practices and map flood-vulnerable areas in the Alawuha catchment. Geographic information system (GIS) multi-criteria analysis and remote sensing with field verification were employed to meet the objective of this study. Slope, elevation, rainfall, drainage density, soil type, and distance to rivers are flood event aggravating factors in this study. These factors were weighted accordingly with their contribution to flood hazards. In addition, land use/land cover (LULC) and population distribution were identified as flood vulnerability factors. The weighted overlay analysis result shows that Sanka, Afrikari, Gedo-ber, Hara, and the surroundings, Woldia, were identified as high flood risk areas of the watershed. To minimize this problem, applying physical and biological measures at the watershed level is recommended.
PubDate: 2022-04-20

• Quantifying and assessing land use and land cover changes around the
critical waterbodies — a case study of Bhagirathi-Hooghly floodplain,
East India

Abstract: Abstract The study strictly inclined to the Land Use and Land Cover (LULC) change mapping and assessing, surrounding and inside the abandoned natural river cutoffs and oxbow lakes of Bhagirathi-Hooghly river in the stretch between Katwa and Kalna, East India. Landsat satellite images of selected years (1990, 2000, 2013, and 2020) and supervised classification technique (Maximum Likelihood Classifier) were used for mapping and assessing LULC classification in four selected Areas of Interest, namely A, B, C, and D. Six LULC classes were adopted by deeply observing the selected areas: vegetation, waterbody, sandy land, bare and fallow land, agricultural land, and settlement and built up. LULC matrixes prepared for evaluating the land transformation in three decades (1990–2020). The study results witnessed a huge transformation of land by anthropogenic pressures and river channel migration. In every region, the waterbody area declines and transforms mostly to the fallow land and agricultural land. On the other side, settlement and built-up areas were increased by primarily occupying the agricultural land, bare and fallow land, and vegetation. In the last three decades, a massive expansion happened in agricultural land except region C, primarily for the conversion of bare and fallow land. Except for region B, the conversion of agricultural, bare and fallow, and settlement and built up land to vegetation has triggered the growth of vegetation area. Therefore, the transformation of land, primarily driven by anthropogenic activities, requires utmost concern. The study findings help in proper integrated LULC and resource management, planning, and sustainable development.
PubDate: 2022-04-09
DOI: 10.1007/s12518-022-00435-1

• The interrelationship between LST, NDVI, NDBI, and land cover change in a
section of Lagos metropolis, Nigeria

Abstract: Abstract In recent times, there has been renewed interest in understanding the dynamics of land cover change and its relationship with several environmental parameters. This study assesses the interrelationship between land surface temperature (LST), normalized difference vegetation index (NDVI), normalized difference built-up index (NDBI), and land cover change in Amuwo-Odofin Local Government Area of Lagos State, Nigeria. Multi-temporal and multi-spectral Landsat imageries for years 2002, 2013, 2016, and 2019 served as the primary dataset. Using the parallelepiped classifier, the imageries were classified into five land cover classes — mixed vegetation, bare land, built-up area, water body, and wetland. The spectral indices (NDVI and NDBI) were computed and the LST was determined using a single-channel algorithm. Land cover transition matrices were calculated to examine the proportion of land cover change between classes, including the unchanged areas. Pearson’s correlation analysis enabled an analysis of the interdependence or interrelationship in the distribution of the parameters. From 2002 to 2019, the highest land cover transitions recorded were bare land to built-up area (12.64 km2), mixed vegetation to built-up area (21.55 km2), wetland to mixed vegetation (8.87 km2), and mixed vegetation to bare land (8.46 km2). There was a negative correlation between LST and NDVI, and between NDVI and NDBI. The distribution of the LST, NDVI, and NDBI varied correspondingly in accordance with land cover changes. The increase in built-up area could be the major driver of the observed changes in LST, NDBI, and NDVI, with an observed relationship that NDBI and LST values increase with increase in built-up areas.
PubDate: 2022-04-06
DOI: 10.1007/s12518-022-00434-2

• Precise estimation of horizontal displacement by combination of multi-GNSS
(Galileo and GPS) observations via the LS-VCE method

Abstract: Abstract In the present study, the role of the stochastic model in processing GNSS observations and determining the horizontal displacement parameters is investigated. Stochastic modeling has been evaluated using two approaches; (1) nominal weight and (2) estimated weight. The former is based on the experimental fixed values, meanwhile the latter is based on the least-square variance components estimation (LS-VCE) method, which is implemented for GNSS observations to estimate the components of variance of observations directly. In this research showed that the stochastic model plays an important role in detecting small displacements. For this purpose, a high-precision displacement simulator which can move accurately at short distances in one direction as well as on a horizontal plane was used. A simulated displacement motion experiment was performed. Derived displacements were compared with simulated (real) displacements along with their accuracy in two modes using only GPS and multi-GNSS as well as the two weighting modes provided. The results of the coordinate comparison show that the stochastic model based on the LS-VCE in the PPP method gives a difference of 0 and − 1.9 mm for the east–west and north–south components, while the use of nominal weight, a difference of − 1.9 and − 1.1 mm. Also, the maximum accuracy improvement in this case for these two coordinate components is 7.8 and 4 mm, respectively, also considering the combination of multi-GNSS observations, the accuracy of the coordinate components and the horizontal component in the weight estimation model has provided an improvement of 5.8 and 5.3 mm. In general, the combination of observations has increased the accuracy of the displacement component compared to the single system.
PubDate: 2022-03-31
DOI: 10.1007/s12518-022-00432-4

• Bayesian approach in stability analysis of monitoring networks of
structures

Abstract: Abstract Monitoring networks are designed for deformation detection of structures regarding the determining of the size and direction of movement. The iterative observations of network point coordinates are used in this regard. By integrating these observations with network coordinate data, one can obtain an estimate of precise positions in the defined datum. For the network on which the continuous observations are made, the network stability must be analysed, and appropriate constraints are applied. Proof of the stability of base points is one of the fundamental issues in deformation analysis that is usually ignored in the implementation. In this study, the Bayesian approach is used to integrate the network observations in the form of the likelihood function with the prior distribution of network coordinates, and one can obtain an estimation of the posterior distribution of precise positions. Converting the linear inner constraints to prior information about the unknown parameters with a uniform distribution in the Bayesian method is the main idea of this study. Estimation of the posterior data in different epochs results in the displacement vectors. The IWST (Iterative Weighted Similarity Transformation) algorithm using the LAS (Least Absolute Sum) is implemented based on the displacement vector. The method that minimizes the L1-norm of the displacement is used to identify unstable points. By identifying the unstable points, the displacement of these points relative to the stable points in the network can be calculated. Finally, the calculated displacement is tested for significance. A classical least-squares method based on linear inner constraints was also applied to compare the result. A simulated network was considered to investigate the ability of the presented approach. The results of the simulated network data processing show that the proposed method is well capable of detecting the applied deformation. Also, as a practical application of the proposed method, the horizontal off-dam network (outside deformation monitoring network) of the Karkheh Dam has been analysed. Numerical results show a good performance of this technique in monitoring the displacements of the off-dam network.
PubDate: 2022-03-31
DOI: 10.1007/s12518-022-00430-6

• A GIS-based approach for identification of optimum runoff harvesting sites
and storage estimation: a study from Subarnarekha-Kangsabati Interfluve,
India

Abstract: Abstract Water scarcity in the Subarnarekha-Kangsabati Interfluve region is making a barrier in the development of the area. Although this region used to receive on an average 139 cm of rainfall yearly, but as runoff, most of the rainwater drains out from this region left behind huge water scarcity problems for the inhabitants. The runoff harvesting is a reliable technique for mitigating of water scarcity. Suitable runoff harvesting sites identification is very much significant for surface water management. In this study, six hydro-environmental factors are considered to analyze the gravity of the problem and to bring out its possible solution. The relative importances of these factors in runoff harvesting sites delineation have been figured out using the multi-criteria analysis technique. The final runoff harvesting site map, which is prepared with 83.33% accuracy, has been prepared by integrating all thematic layers in ArcGIS platform using weighted linear combination method. The results that have revealed from the study show about 46.41% of areas have high to very high suitability for runoff harvesting. This final runoff harvesting site map is 83.33% accurate with the reference layer. Suitable 15 sites have been proposed for dam construction after evaluating the feasibility of this study. The water storage capacities of four proposed reservoir sites among out of 15 have also been computed. These four proposed reservoirs will be capable to supply 426.26 million cubic meters of water for different uses, which will largely solve the water scarcity-related problems of the studied region.
PubDate: 2022-03-29
DOI: 10.1007/s12518-022-00433-3

• Monitoring the change of Turkey’s tourism city Antalya’s Konyaaltı
shoreline with multi-source satellite and meteorological data

Abstract: Abstract Uncontrolled tourism activities cause the destruction of nature and deterioration of the ecological balance. Since coastal areas are both economically and socially important, monitoring shoreline changes has become one of the important research areas. Monitoring short-term and long-term changes in coastal areas is important to prevent damages that may occur due to natural and human factors and protect the shorelines. In this study, which is an important tourist city of Antalya, Turkey, and the world, coastal changes using historical and recent satellite data have been analyzed. The focus of the study is to analyze long-term coastal change with Landsat data and the data obtained every 5 years between 1985 and 2020 and to analyze short-term change with annual Sentinel-2 data between 2015 and 2020. In the study, water areas on the coastline were determined by object-based classification and multiresolution segmentation method with the Modified Normalized Difference Water Index (MNDWI). The obtained shorelines were analyzed with the Digital Shoreline Analysis System (DSAS) tool and the changes in the coastal areas were determined statistically. Five-year and 35-year changes were compared with Linear Regression Rate (LRR) and End Point Rate (EPR) analyses. As a result of the study, when the Pearson’s r value between EPR and LRR was examined, r was found 0.916 and 0.944 for 5-year and 35-year data, respectively. Spatial resolution in satellite images is vital for shoreline detection. However, the most optimal way to detect long-term changes in the shoreline is to use Landsat data. Although the spatial resolution of Landsat data, it has been observed that the power to analyze annual variation differences is lower than Sentinel-2.
PubDate: 2022-03-25
DOI: 10.1007/s12518-022-00431-5

• An integrated approach of the analytic network process and barometer model
mapping of human settlement sustainability in Ardebil Province, Iran

Abstract: Abstract The main objective of this research is to evaluate the economic, social, and environmental aspects for sustainability assessment in Ardabil Province, Iran. We applied an analytic network process (ANP) approach to 10 economic indices, 16 indicators, and 24 environmental indices to reveal the relative importance of each indicator. The economic and social aspects yielded reasonably high sustainability values while the environmental aspects turned out to have a low sustainability value. In terms of human well-being, of the ten counties studied, the city of Sareyn turned out to be unsustainable, eight cities yielded average levels of sustainability, and the city of Ardebil reached an almost sustainable level. In relation to the ecosystem well-being, seven counties were almost unsustainable, while the two counties Pars Abad and Meshkinshahr average level of sustainability and the city of Ardebil reached an almost sustainable level. Results of this research outlined that an integrated approach of ANP and barometer model can be applied sustainable modeling efficiently. These results are discussed with decision makers and authorities in Ardebil provinces for the purpose of regional planning and sustainable development. In addition, results derived from this research can make an important contribution to the further development of political sustainability related decisions in particular. The main novelty of this research is to present a new and efficient approach for sustainability assessment tasks by means of integrating the analytic network process and barometer model.
PubDate: 2022-03-25
DOI: 10.1007/s12518-022-00426-2

• Sources of aerosol optical depth and its distribution in Abbay basin,
Ethiopia

PubDate: 2022-03-23
DOI: 10.1007/s12518-022-00428-0

• The use of linear smoothing methods to remove artefacts resulting from the
seabed’s DTM lossy compression

Abstract: Abstract The article describes research on the use of local linear smoothing methods to remove artefacts resulting from the lossy compression of seabed’s digital terrain model (DTM). In practice, when creating seabed models, DTM based on a regular grid is most often used. When recording larger surfaces, the amount of data collected in the structure can be very large (millions or even hundreds of millions of points) as discussed by Maleika et al. (2011). In such a case, it is possible to significantly reduce the amount of this data by using lossy compression methods. The vast majority of these methods divide the entire surface into small blocks and compress each of them independently. In the process of reconstruction (decompression), clearly visible distortions called artefacts form at the boundaries (edges) of these blocks. In the study, the author described the methods of linear data approximation, enabling the removal of distortions at the boundaries of blocks in the lossy compression/reconstruction process, while maintaining high model accuracy and International Hydrographic Organization (IHO) standards. During the research, methods based on polynomials (from the 1st to 9th degree) and linear approximation, cubic approximation and smoothing spline interpolation were tested. The developed smoothing method was then modified to work locally in places where compression artefacts occur. In the next stage, distortion-dependent smoothing was additionally developed so that the power of the smoothing method would be dependent on the amount of the distortion present. All tests were carried out with the use of three different test surfaces, assessing the obtained results both objectively (calculating the model error at the 95% confidence level) and subjectively (by visually assessing the distortions at the interface of the compression blocks). The results obtained were presented on many figures and tables and interpreted. Finally, the test plots after the developed distortion-dependent local smoothing method were shown in order to assess the obtained effects. The experiments presented in the paper and the results obtained show the true potential of linear smoothing methods in removing distortions resulting from the use of lossy compression methods of seabed’s DTM.
PubDate: 2022-03-17
DOI: 10.1007/s12518-022-00427-1

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