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]
• Ultra-resolution unmanned aerial vehicle (UAV) and digital surface model
(DSM) data-based automatic extraction of urban features using object-based
image analysis approach in Gurugram, Haryana

Abstract: Abstract Unmanned aerial vehicles (UAV) have emerged as flexible, swift, and economical imaging systems that have proven their feasibility in urban infrastructure mapping. However, data derived from such systems are not utilized thoroughly. In this study, an object-oriented, multiresolution segmentation-based workflow is explored to automatically extract the urban features such as buildings and roads that can revolutionize the pace of existing mapping methods. This paper contemplates the automatic object-oriented-based feature extraction process on 5-cm true color ortho-rectified images and digital surface model (DSM). The data was generated using the JOUAV/CW-10 model and a Sony Camera with a 40-megapixel resolution. The segmentation procedure was implemented, defining various parameters such as scale, shape, and compactness. Here, the optimum scale, shape, and compactness parameters chosen for buildings and road segmentation are 100, 0.6, and 0.8, and 50, 0.5, and 0.9, respectively. The object-based image analysis (OBIA) results were compared to manually digitized features to assess the accuracy of the automated process. The fractal border error accuracy is calculated for urban features such as roads and buildings. The OBIA results indicated that completeness, correctness, and quality of building features were 98.2%, 97.6%, and 95.9%, respectively. Similarly, the road features’ average completeness, correctness, and quality were 85.8%, 73.8%, and 68.2%, respectively, which is on the lower side due to obscuring of roads by the avenue trees. The methodology yielded promising results for urban feature extraction with substantial accuracy and can be implemented in other areas with little fine-tuning of feature extraction parameters.
PubDate: 2022-10-01

• An application of geospatial-based multi-criteria decision-making
technique to identify landslide susceptibility zones in the Ragnu Khola
River Basin of Darjeeling Himalayan region, India

Abstract: Abstract One of the most dangerous geo-hazards, landslides cause a progressive loss of rock and soil that have a negative impact on human lives, the ecosystem, and the global economy. Darjeeling Himalaya is one of the world’s young fold mountainous areas, often suffering from landslide hazards. Hence, the study identifies the landslide susceptibility zone in the Ragnu Khola River Basin of the Darjeeling Himalayan region by applying the geospatial-based MCDM technique. This research’s major goal is to identify whether this GIS-based multi-criteria decision-making (MCDM) technique is validated or not for landslide susceptibility zones (LSZ); if validated, then how much manifests for describing the LSZ in the study area. MCDM evaluation applies to determining weight value to integrate different thematic layers of river morphometry like drainage diversity (DD) parameters and relief diversity (RD) parameters. Both DD and RD have significant impacts on landslide intensity. Hence, both layers are combined using the analytical hierarchy process (AHP) of the MCDM technique for the final LSZ. The final result has been validated by ROC analysis using landslide occurring point data obtained from the Geological Survey of India (GSI). The outcome of the study shows that 1.45% and 17.83% of areas of the region fall in “very high” and “high” LSZ, which belongs to near Mull Gaon, Sanchal forest, and Alubri basty. Most of the area (47.70%) is observed in “moderate” LSZ. Only 1.32% and 31.7% are kept in “very low” and “low” LSZ, respectively, throughout the study area. The description capability of the technique for LSZ is significant as the area under the curve (AUC) is 72.10%. The validation of the study using the frequency density of the landslides (FDL) also indicates the “very high” LSZ is associated with the maximum (2.19/km2) FDL. The work will be necessary to develop the overall socio-economic condition of such kind of tectonically sensitive region through proper and effective planning.
PubDate: 2022-09-26

• Bathymetry from satellite images: a proposal for adapting the band ratio
approach to IKONOS data

Abstract: Abstract The acquisition of bathymetric data in shallower waters is difficult to attain using traditional survey methods because the areas to investigate may not be accessible to hydrographic vessels, due to the risk of grounding. For this reason, the use of satellite detection of depth data (satellite-derived bathymetry, SDB) constitutes a particularly useful and also economically advantageous alternative. In fact, this approach based on analytical modelling of light penetration through the water column in different multispectral bands allows to cover a big area against relatively low investment in time and resources. Particularly, the empirical method named band ratio method (BRM) is based on the degrees of absorption at different bands. The accuracy of the SDB is not comparable with that of traditional surveys, but we can certainly improve it by choosing satellite images with high geometric resolution. This article aims to investigate BRM applied to high geometric resolution images, IKONOS-2, concerning the Bay of Pozzuoli (Italy), and improve the accuracy of results performing the determination of the relation between band ratio and depth. Two non-linear functions such as the exponential function and the 3rd degree polynomial (3DP) are proposed, instead of regression line, to approximate the relationship between the values of the reflectance ratios and the true depth values collected in measured points. Those are derived from an Electronic Navigational Chart produced by the Italian Hydrographic Office. The results demonstrate that the adopted approach allows to enhance the accuracy of the SDB, specifically, 3DP supplies the most performing bathymetric model derived by multispectral IKONOS-2 images.
PubDate: 2022-09-17

• Insights into the morphometric characteristics of the Himalayan River
using remote sensing and GIS techniques: a case study of Saryu basin,
Uttarakhand, India

Abstract: Abstract The watershed’s hydrological response behavior can be elucidated by studying its various morphometric parameters with geographic information system (GIS) tools. The Saryu River, one of the major tributaries of the Ganga River system, was analyzed for a detailed study using Advanced Spaceborne Thermal Emission and Reflection (ASTER-30 m) data and topographic sheets of Survey of India. In total, 19 watersheds are identified within the basin for calculating the morphometric parameters in the linear, aerial, and relief directions. The total drainage area of the basin is 754.23 km2. Overall, the drainage pattern is dendritic to sub-dendritic and its topography, the underlying geology, and the rainfall all influence it. The study area is designated as a 6th-order basin having 3070 stream numbers with a cumulative length of 2912.44 km. The bifurcation ratio varies from 0.50 to 10, while the drainage density ranges from 0.94 to 1.33 km/km2. The physiography and the lithology of the region profoundly impact its stream order. The shape index, shape factor, and compactness coefficient indicate that the basin has moderate tectonic activity with moderate basin lag times and will take longer for peak flow to occur. In light of the study area’s relief characteristics, it has moderate to steep slopes, consequently experiencing low to moderate soil erosion. The study results can be used to formulate strategies for sustainable basin management.
PubDate: 2022-09-15

• Digital mapping and predicting the urban growth: integrating scenarios
into cellular automata—Markov chain modeling

Abstract: Abstract Predictive modeling and land use/land cover change studies in complex systems are well advanced. Cellular automata (CA)-Markov chain (MC) can be defined as one frequently preferred method for this purpose. This paper aims to adapt the CA-MC model to the simulation of residential areas in the city. The proposed method was tested in the city center of Kastamonu, Türkiye, using four time periods: 1985, 2011, 2015, and 2021. Spatio-temporal change maps were produced using ArcGIS 10.0 software. Land use simulation of the urban center, including residence units for 2031 and 2057, was performed using the integrated CA-MC technique. The method’s suitability was demonstrated with the Kappa index of agreement values (Kstandart: 0.93; Klocation: 0.98; Kno: 0.98; and KlocationStrata: 0.95). Within the scope of the study, two different scenarios were designed as short term (S1) and long term (S2). According to the predictions for 2031, there was a residential area increase of 15% in S1 and 29% in S2. When we reach 2057, these growth values were measured as 50% according to S1 and 72% according to S2.
PubDate: 2022-09-02

• Assessing the utility of Sentinel-2 MSI in mapping an encroaching
Serephium plumosum in South African rangeland

Abstract: Abstract Grassland has a rich biodiversity that provides critical ecosystem services such as water supply and flow regulation, carbon storage and erosion control. In South Africa, grassland is a source of readily available grazing for both livestock and wildlife for farmers. Despite the relative importance of grassland, it faces many challenges that include unsustainable land use practices (overgrazing), bush encroachment and invasive alien plants (IAPs). Serephium plumosum (S. plumosum) is an encroacher shrub that has been declared through legislation as problematic in some parts of South Africa. This aggressive encroacher shrub has endangered the existence of palatable grassland of about 11 million hectares in South Africa. This research investigated the utility of the freely available Sentinel-2 multispectral imagery and two classifier approaches, random forest (RF) and support vector machine (SVM), in mapping S. plumosum at Telperion and Ezemvelo nature reserves in South Africa. S. plumosum and other land cover classes were successfully mapped using spectral reflectance with the overall accuracy of 97.42% and 95.48% for RF and SVM, respectively. Grassland was found to be the most common land cover class representing about 41%. S. plumosum covered 13% of the study area and more significantly represented a 24% encroachment of grassland. Having successfully mapped S. plumosum through Sentinel-2 MSI, this provides for a viable method of mapping this problematic shrub which will be beneficial to both private farmers and environmentalists. Future research could focus on mapping and understanding the historical distribution of this aggressive shrub and modelling of future invasions.
PubDate: 2022-09-01

• Geospatial technology–based analysis of land use land cover dynamics and
its effects on land surface temperature in Guder River sub-basin, Abay
Basin, Ethiopia

Abstract: Abstract Land surface temperature (LST) is increasing due to the decline of vegetation cover and an increase in barren land in the Guder River sub-basin. In the present study, LST, Normalized Difference Vegetation Index (NDVI), Normalized Difference Bareness Index (NDBaI), and land use land cover (LULC) and the relationship between them were estimated using thermal bands and multispectral bands from Landsat TM from 1990, ETM + from 2000, and OLI/TIRS from 2020. The LST of the study area is increased by 11.3 °C from 1990 to 2020 due to the loss of vegetation cover and expansion of barren land. The relationships between LST, NDVI, and NDBaI were estimated using correlation analysis. The NDBaI has strong positive relationship with LST (R2 = 0.96), while NDVI has a strong negative relationship with LST (R2 = 0.96). The mean LST was increased over cultivated land and bare land by 11.3 °C and 10.6 °C from 1990 to 2020, respectively. Consequently, expansion of cultivated land and bare land was the main reason for the increase of LST. We recommend that decision-makers and concerned stakeholders to promote the importance of vegetation cover in climate change mitigation and minimizing LST.
PubDate: 2022-09-01

• GNSS-SDR pseudorange quality and single point positioning performance
assessment

Abstract: Abstract In recent years, we have witnessed a growing demand for GNSS receiver customization in terms of modification of signal acquisition, tracking, and processing strategies. Such demands may be addressed by software-defined receivers (SDRs) which refers to an ensemble of hardware and software technologies and allows re-configurable radio communication architectures. The crux of the SDRs is the replacement of the hardware components through software modules. In this paper, we assess the quality of GNSS observables acquired by SDR against the selected u-blox low-cost receiver. In the following, we investigate the performance level of single point positioning that may be reached with an ultra-low-cost SDR and compare it to that of the low-cost GNSS receiver. The signal quality assessment revealed a comparable performance in terms of carrier-to-noise density ratio and a significant out-performance of the u-blox over SDR in terms of code pseudorange noise. The experimentation in the positioning domain proved that software-defined receivers may offer a position solution with three-dimensional standard deviation error at the level of 5.2 m in a single point positioning mode that is noticeably poorer accuracy as compared to the low-cost receiver. Such results demonstrate that there is still room for SDR positioning accuracy improvement.
PubDate: 2022-08-26

• Combination of close-range and aerial photogrammetry with terrestrial
laser scanning to answer microbiological and climatological questions in
connection with lava caves

Abstract: Abstract Combining photogrammetric reconstruction (close-range photogrammetry, CRP) and airborne photogrammetry through the structure from motion method (SFM) with terrestrial three-dimensional (3D) laser scanning (TLS), Maelstrom Cave on Big Island, Hawaii (USA), was mapped in three dimensions. The complementary properties of the two methods generated an overall model that depicted significant features of the cave both spatially and visually. Through various processes, the complex geometric quantities were derived from the model that can be used to answer microbiological and climatological questions. In this report, the procedure for the three-dimensional acquisition of the terrain surface above Maelstrom Cave as well as the interior of the cave with TLS and SFM is described. It is shown how the different data sets were combined and contrasted, including a comparison of geometries from the different survey operations. Finally, the editing processes used to quantify and simplify the cave geometry are presented, as well as the analysis of the ellipses generated accordingly to determine the geometric quantities. Through the analysis of the cave geometry, important geometric properties of the Maelstrom Cave could be quantified and categorized. In this way, an effective tool was developed to directly correlate the structure of the cave system with climatological and microbiological parameters in order to answer the corresponding questions.
PubDate: 2022-08-25

• Sea surface temperature prediction model for the Black Sea by employing
time-series satellite data: a machine learning approach

Abstract: Abstract High temporal resolution remote sensing images provide continuous data about the marine environment, which is critical for gaining extensive knowledge about the aquatic environment and marine species. Sea surface temperature (SST) is one of the basic parameters that can be obtained with the help of remote sensing. Long-term alterations in the SST can affect the aquatic environment and marine species, such as the life expectancy of anchovies in the Black Sea. Forecasting the dynamics of SSTs is crucial for detecting and eliminating the SST-oriented impacts. The goal of the current study is to construct a predictive model to estimate the daily SST value for the mid-Black Sea using a machine learning approach by employing time-series satellite data from 2008 to 2021. Turkey’s mid-Black Sea coastal line, comprising Ordu, Samsun, and Sinop stations, was chosen as the study area. The SST predictive model was represented by applying the recurrent neural network (RNN) long- and short-term memory (LSTM). Adam stochastic optimization was used for validation, and the mean square error (MSE) for each location was found to be 0.914, 0.815, and 0.802, respectively. The findings indicate that our model is significantly promising for accurate and effective short- and midterm daily SST prediction.
PubDate: 2022-08-23

• Peri-urban area delineation and urban sprawl quantification in
Thiruvananthapuram Urban Agglomeration, India, from 2001 to 2021 using
geoinformatics

Abstract: Abstract In Southeast Asia, rising population, economic growth, and lack of land supply in the city core have led to the widespread irreversible land cover transformation in peri-urban areas. Such extensive and haphazard urban growth in peri-urban areas raises concern about analyzing and promoting planned urban growth. Therefore, this paper attempts to assess land cover changes from 2001 to 2021 and delineate peri-urban areas of a midsized Indian city, i.e., Thiruvananthapuram Urban Agglomeration (UA) using geoinformatics. The maximum likelihood supervised classification tool in ArcGIS 10.3 was used to prepare land cover maps for 2001, 2007, 2014, and 2021. Further, the presence of urban sprawl in the peri-urban areas was detected through Shannon’s entropy index. The urban sprawl typologies in the peri-urban areas were quantified using the adjacent neighborhood relationships concept. The results revealed rapid growth in built-up land cover and decline in non-built-up land cover within Thiruvananthapuram UA during the study period. Peri-urban areas were delineated based on nine indicators, such as total population, population growth, population density, literacy rate, percentage of the male workforce, percentage of the female workforce, agricultural land cover, distance from urban core, and percentage of cultivators to agricultural workers. A rise in Shannon’s entropy index from 1.59 in 2001 to 2.05 in 2021 exhibited the occurrence of rapid urban sprawl in the peri-urban areas. Dominance of discontinuous low-density development, i.e., scatter development typology of urban sprawl, was observed in peri-urban areas of Thiruvananthapuram UA. Such studies using geoinformatics would assist local governments in scientifically formulating sustainable urban policies and plans.
PubDate: 2022-08-22

• Integration of geospatial technologies with multiple regression model for
urban land use land cover change analysis and its impact on land surface
temperature in Jimma City, southwestern Ethiopia

Abstract: Abstract Rapid urbanization and population growth are the main problems faced by developing countries that lead to natural resource depletion in the periphery of the city. This research attempts to analyze the impacts of urban land use land cover (LULC) change on land surface temperature (LST) from 1991 to 2021 in Jimma city, southwestern Ethiopia. Landsat Thematic Mapper (TM) 1991, Landsat Enhanced Thematic Mapper Plus (ETM +) 2005, and Landsat-8 Operational land imagery (OLI)/Thermal Infrared Sensor (TIRS) 2021 were used in this study. Multispectral bands and thermal infrared bands of Landsat images were used to calculate LULC change, normalized difference vegetation index (NDVI), normalized difference built-up index (NDBI), and LST. The LULC of the study area was classified using a supervised classification method with the maximum likelihood algorithm. The results of this study clearly showed that there is a negative correlation between vegetation cover and LST. The decrease in vegetation coverage and expansion of impervious surfaces lead to elevated LST in urban areas. The loss of vegetation cover contributed to the increasing trend of LST. Moreover, the conversion of vegetation cover to impervious surfaces aggravates the problem of LST. The results revealed that the built-up area was increased at a rate of 0.4 km2/year from 1991 to 2021. The vegetation cover in the city declined due to urban expansion to the periphery of the city. Consequently, the dense vegetation and sparse vegetation were converted into built-up areas by approximately 5.2 km2 during the study period. The mean LST of the study area increased by 10.3 °C from 1991 to 2021 during the winter season in daytime. To improve the problems of climate change around urban areas, all stakeholders should work together to increase the urban green space coverage, which will contribute a significant role in mitigating LST and the urban heat island effect. More specifically, all residents could be accessible to public green spaces around big cities.
PubDate: 2022-08-22

• Positional accuracy assessment of historical Google Earth imagery in Lagos
State, Nigeria

Abstract: Abstract The horizontal accuracy of historical Google Earth (GE) images at four epochs between the years 2000 and 2018, and the vertical accuracy of its elevation data within Lagos State, in Nigeria, are respectively evaluated by comparison with a very high–resolution digital orthomosaic and comparison with 558 ground control points. Two readily available 30-m digital elevation models (DEMs) — the Shuttle Radar Topography Mission (SRTM) v3.0 and the Advanced Land Observing Satellite World 3D (AW3D) DEM v2.1. — were also compared with GE elevations. A novel approach for assessing the space–time variations in the magnitude and direction of errors in GE imagery is presented. For horizontal accuracy, the root mean square errors (RMSEs) are as follows — year 2000 (16.9 m), year 2008 (16.4 m), year 2012 (6.1 m) and year 2018 (6.1 m). The most recent GE imagery (year 2018) had the least horizontal error while year 2000 had the largest horizontal error. The horizontal shift was skewed towards the western and north-western directions, indicative of systematic error. In terms of the vertical accuracy, GE elevation data had the lowest accuracy and highest RMSE of 6.21 m followed by AW3D with an RMSE of 4.39 m and SRTM with an RMSE of 3.68 m.
PubDate: 2022-07-23
DOI: 10.1007/s12518-022-00449-9

• Producing WorldView-2 fused images of superior quality by the novel
ELSHORA fusion technique

Abstract: Abstract In this study, the novel ELSHORA fusion technique was developed for the fusion of the WorldView-2 satellite panchromatic (PAN) and multispectral (MS) images. This fusion technique has the advantage of overcoming the weaknesses of the other existing fusion techniques and producing fused images of superior spectral and spatial quality for all land cover types. This technique uses a modification coefficient for each MS band according to its intersecting area with the PAN band to ensure that only the wavelengths of the MS bands within the PAN band range participate in the definition of the I image, and the I image will be a weighted average of the eight modified MS bands. These modification coefficients will help in the preservation of the original colors as well as achieve spatial and temporal transferability for the ELSHORA fusion technique. This technique also uses an additional coefficient for the NIR band in the agricultural areas to indicate the correct effect of the vegetation, as its reflectance is high in the NIR band. This vegetation coefficient will achieve the performance stability for the ELSHORA fusion technique across the different types of land cover. To evaluate the performance of the ELSHORA fusion technique, it was compared to six standard image fusion techniques: modified IHS, Ehlers fusion, hyper-spherical color space, principal component analysis, Brovey transform, and multiplicative resolution merge. These fusion techniques were utilized to merge the spatial and spectral information of four datasets of WorldView-2 satellite PAN and MS images covering different land cover types: agricultural, urban, and mixed areas. The four datasets were chosen in two different places and acquired at two different times to evaluate the spatiotemporal transferability of the ELSHORA fusion technique. The fused images were compared to the PAN and MS images, as well as to each other, statistically and visually. The results demonstrated the superiority of the ELSHORA fusion technique for all types of land cover. It can effectively generate sharper fused images without color distortion at different times and places.
PubDate: 2022-07-21
DOI: 10.1007/s12518-022-00451-1

• Spatial–temporal prediction model for land cover of the rural–urban
continuum axis between Ar-Riyadh and Al-Kharj cities in KSA in the year of
2030 using the integration of CA–Markov model, GIS-MCA, and AHP

Abstract: Abstract The spatiotemporal analysis of land use/land cover change and monitoring, modeling, and forecasting the future of land uses are considered challenges facing planners and decision-makers in developing countries. These challenges are increased in neighborhood areas surrounding large cities, which are known as the “rural–urban continuum”. These areas have become the preferred areas for resettlement for most urban residents. The objectives of the present study were to (1) monitor the land cover change in the rural–urban continuum axis between the Ar-Riyadh and Al-Kharj cities during the period 1988–2020, (2) simulate the future growth of land cover up to the year 2030 using the Cellular Automated Markov Model (CA-Markov), and (3) improve the ability of CA-Markov to predict the future by integrating multi-criteria analysis based on geographic information systems (GIS-MCA) and analytic hierarchy process (AHP) method. The results of the study revealed large changes in the land cover in the rural–urban continuum axis between the Ar-Riyadh and Al-Kharj cities. About 60 km2 of agricultural land has been lost, with an average annual decrease of 2 km2. The industrial and urban areas were increased with growth rate of 4%. There were five categories of spatial suitability, ranging between 32 and 86%, and 70% or higher is the recommended percentage for future land uses. The industrial use was the most likely land use in 2030, as it recorded an increase of 27.1 km2 over the year 2020.
PubDate: 2022-07-20
DOI: 10.1007/s12518-022-00448-w

• Accuracy of GNSS RTK/NRTK height difference measurement

Abstract: Abstract The absolute error of ellipsoidal heights that may be achieved from Real-Time Kinematic/Network Real-Time Kinematic Global Navigation Satellite Systems (RTK/NRTK GNSS) measurements varies between 3 and 5 cm. Although the vertical root mean square (RMS) error reported by receivers generally has smaller values, it can only be treated as a measure of the precision of the obtained results. Nowadays, real-time GNSS measurements are commonly used to implement surveys with increased accuracy. In some cases, it may be of concern to determine the height difference with real-time techniques than the height itself. The use of height difference may be applicable when a point with a known height is available. This offers the possibility of transferring the known height to a distant point using GNSS technology instead of geometric leveling, which is more labor-intensive. The aim of the study was to verify if achieving accuracy better than 2 cm in ellipsoidal height difference using RTK/NRTK GNSS is possible, providing special conditions of measurement. In this paper, the results of research consisting of RTK/NRTK measurement of specific points with fixed heights in various terrain conditions are presented. A single GNSS reference station was used as a base station to determine ellipsoidal height in RTK mode and Ground-Based Augmentation System (GBAS) for measurements in NRTK mode. Comparison of the ellipsoidal height difference to the results of precise leveling allows us to determine ellipsoidal height measurement errors. The measurements were carried out in open terrain, with the covered horizon (under trees) and in urbanized areas (high buildings). The method proposed by the authors in this paper does not require knowledge of the quasi-geoid model, neither normal correction to obtain measurement results.
PubDate: 2022-07-13
DOI: 10.1007/s12518-022-00450-2

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

PubDate: 2022-06-18
DOI: 10.1007/s12518-022-00446-y

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

PubDate: 2022-06-10
DOI: 10.1007/s12518-022-00447-x

• 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
DOI: 10.1007/s12518-022-00444-0

• 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
DOI: 10.1007/s12518-022-00443-1

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