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Tie-lines are used in aeromagnetic surveys to detect measurement errors and compensate for insufficient measurement data in the north-south direction. However, increasing the number of tie-lines to improve the accuracy of interpretation can be very challenging. The aim of this study was to overcome this issue by combining aeromagnetic and related multi-parametric data. Therefore, we generated an aeromagnetic map using simple kriging with local varying means (SK-lvm) based on topographic data correlated with the distribution patterns of the aeromagnetic data. The generated aeromagnetic map achieved reduced uncertainties and increased resolution compared with the conventional aeromagnetic map as a result of the interpolation of the magnetic data, which leveraged the dense distribution of the topographic data points and enabled a clearer analysis of geological structures. Generally, topographic and aeromagnetic data were positively correlated with deviating patterns displayed in some regions; however, all the regions shown were classified into Types 1–4 based on the correlation regression equation. Types 1 and 4 showed positive correlations, while Types 2 and 3 exhibited negative correlations with the following characteristics: Type 2 regions are characterized by high altitude and low magnetic anomalies, while Type 3 regions are characterized by low altitude and high magnetic anomalies. The analysis revealed that Type 2 regions are distributed around high-altitude mountainous areas covered with igneous and sedimentary rocks with low magnetic anomalies, whereas Type 3 regions abound with igneous rocks with high magnetic anomalies and mining sites in low-altitude alluvium or coastal areas. Thus, the proposed aeromagnetic map improved resolution and enhanced the reliability of the interpretations (compared with those of a conventional aeromagnetic map) by combining topographic datasets using SK-lvm to process and interprets the comprehensive aeromagnetic survey data. Moreover, the correlation analysis results for the two datasets are expected to serve as useful reference data for determining the characteristics type of rocks distributed in the study area. [ABSTRACT FROM AUTHOR]

Open research data refer to publicly available scientific information that can be accessed free of charge, usually provided by public data sources. Users must comply with specific requirements set by the institutions providing the data and always acknowledge the source of the data when processing, transmitting, storing or publishing it. One of the tasks of the BrineRIS project is the mapping of brine resources, requiring reliable data on the location of exploration facilities, environmental characteristics, brine exploitation parameters and formal and legal information. These data come from a review of various archives, databases and survey results. Initially, information on the location of the sources should be obtained, which may be available in publicly accessible databases. Next, geological and hydrogeological parameters, which can be obtained from scientific papers and reports, are useful. An important part of the project is also the analysis of legal regulations concerning water extraction and environmental protection. Therefore, data should be obtained from various sources, such as public administration, state institutions or research units. These will serve to develop the database needed to perform further analyses within the BrineRIS research project. It is therefore crucial to carefully collect, analyse and assess the usefulness of the data. [ABSTRACT FROM AUTHOR]

Abstract Open research data refer to publicly available scientific information that can be accessed free of charge, usually provided by public data sources. Users must comply with specific requirements set by the institutions providing the data and always acknowledge the source of the data when processing, transmitting, storing or publishing it. One of the tasks of the BrineRIS project is the mapping of brine resources, requiring reliable data on the location of exploration facilities, environmental characteristics, brine exploitation parameters and formal and legal information. These data come from a review of various archives, databases and survey results. Initially, information on the location of the sources should be obtained, which may be available in publicly accessible databases. Next, geological and hydrogeological parameters, which can be obtained from scientific papers and reports, are useful. An important part of the project is also the analysis of legal regulations concerning water extraction and environmental protection. Therefore, data should be obtained from various sources, such as public administration, state institutions or research units. These will serve to develop the database needed to perform further analyses within the BrineRIS research project. It is therefore crucial to carefully collect, analyse and assess the usefulness of the data.

Digital topographic maps are created in a series of scales from large to small, and the underlying spatial data is commonly organized as a multiscale database consisting of several levels of detail (LoDs). Spatial density of features (or spatial objects) in such database varies both between LoDs (coarser levels are less densely populated with features) and within each LoD (feature density changes over the area). While the former type of density variation is caused by generalization, the latter one is mainly conditioned by geographic location and its properties, such as landscape complexity or fraction of urban areas. Since topographic database LoDs are derived using different data sources and generalization techniques, there is a need for a method that can help with automated evaluation of resulting feature density in terms of its appropriateness for the specified location and level of detail. This paper provides such method by uncovering dependencies between the location properties and the density of spatial data in multiscale topographic database. Changes in feature density are modeled as a function of spatial (landscape complexity and terrain ruggedness) and non-spatial (land cover types ratio) measures estimated via independent data sources. Resulting model predicts how much higher or lower is the expected spatial density of features over the area in comparison to the average density for the LoD. This information can be used further to assess the fitness of the data to the desired level of detail of the topographic map.

This study aims at a comparative analysis of quantitative data, namely, OSM and BDOT10k. Analyses were conducted in a 1 km2 hexagonal grid, in seven test counties located in different regions of Poland, differing in the degree of urbanization, land cover and natural environment. It is assumed that the authors' consolidated regional classification of the Compound Correspondence Index CCIRn is attributed to the geometric mapping unit based on TOPSIS values, and their statistical measure of dispersion enables the comparison of datasets for individual geographically disjointed areas according to uniform criteria, e.g., the number of topographic features stored in analyzed datasets, both polygonal (buildings, forests, surface water) and linear (roads, watercourses, railroads). The final results of the regional assessment outperform the local classification giving a higher level of data compliance. Overestimation of regional concordance ranges from 9 to 20% of the county area, with an average of 3% reduction in the area where the two datasets (BDOT10k and OSM) have comparable information ranges. Areas of medium and high nonconformity are decreased by an average of 2.4%. [ABSTRACT FROM AUTHOR]

This paper presents empirical models developed through stepwise multiple linear regression to estimate the live fuel moisture content (LFMC) in a Mediterranean area. The models are based on LFMC data measured in 50 field plots, considering four groups with similar bioclimatic characteristics and vegetation types (trees and shrubs). We also applied a species-specific LFMC model for Rosmarinus officinalis in plots with this dominant species. Spectral indices extracted from Sentinel-2 images and their averages over the study time period in each plot with a spatial resolution of 10 m were used as predictors, together with interpolated meteorological, topographic, and seasonal variables. The models achieved adjusted R2 values ranging between 52.1% and 74.4%. Spatial and temporal variations of LFMC in shrub areas were represented on a map. The results highlight the feasibility of developing satellite-derived LFMC operational empirical models in areas with various vegetation types and taking into account bioclimatic zones. The adjustment of data through GAM (generalized additive models) is also addressed in this study. The different error metrics obtained reflect that these models provided a better fit (most adjusted R2 values ranged between 65% and 74.1%) than the linear models, due to GAMs being more versatile and suitable for addressing complex problems such as LFMC behavior. [ABSTRACT FROM AUTHOR]

This paper investigates user preferences and behaviour associated with 2D and 3D modes of urban representation within a novel Topographic Immersive Virtual Environment (TopoIVE) created from official 1:10,000 mapping. Sixty participants were divided into two groups: the first were given a navigational task within a simulated city and the second were given the freedom to explore it. A Head-Mounted Display (HMD) Virtual Reality (VR) app allowed participants to switch between 2D and 3D representations of buildings with a remote controller and their use of these modes during the experiment was recorded. Participants performed mental rotation tests before entering the TopoIVE and were interviewed afterwards about their experiences using the app. The results indicate that participants preferred the 3D mode of representation overall, although preference for the 2D mode was slightly higher amongst those undertaking the navigational task, and reveal that different wayfinding solutions were adopted by participants according to their gender. Overall, the findings suggest that users exploit different aspects of 2D and 3D modes of visualization in their wayfinding strategy, regardless of their task. The potential to combine the functionality of 2D and 3D modes therefore offers substantial opportunities for the development of immersive virtual reality products derived from topographic datasets.

The object of the research is the forces and devices of topographic support of the operational command troops. The work highlights the recommendations regarding the composition of the forces and devices of topographical support of the operational command troops. The analysis of the nature of the armed struggle of the last decades shows a sharp increase in the need of the troops (forces) for information provision, in particular in the provision of topogeodesic information (geospatial information) of the armed forces, the timeliness and reliability of which affects the course and results of military operations. One of the types of geospatial data that is needed by the military both in peacetime and in a special period are topographic maps, they are the main source of information about the terrain and the objects on it. Nowadays, the state of topographic information on most nomenclature sheets of topographic maps of the territory of Ukraine does not meet the modern requirements of the troops. The successful implementation of the task of updating topographical information is facilitated by the use of the most acceptable and economically justified composition of forces and devices of topographical support of troops. However, the experience of geodetic support during the operational training of troops (forces), the operation of the United Forces in the east of the country and the large-scale armed aggression by the Russian Federation showed that the currently available forces and devices of geodetic support of the troops are not capable of fulfilling the entire scope of the assigned tasks. This especially applies to operational commands. Therefore, in order to successfully carry out changes in the system of topographic support regarding the necessary composition of forces and devices of this support, appropriate scientific researches were conducted. This, in turn, will provide an opportunity to improve existing methods and develop recommendations regarding the necessary composition of forces and devices of topographic support for the troops of the operational command. The mentioned recommendations will make it possible to justify the composition of the forces and devices of topographical support of the troops of the operational command by the persons planning the operations of the groups of troops (forces). [ABSTRACT FROM AUTHOR]

Mapping the distribution and type of land use and land cover (LULC) is essential for watershed management. The Tigris-Euphrates basin is a transboundary region in the Middle East shared between six countries, but a recent fine-scale LULC map of the area is lacking. Using Landsat-8 time series, a 30-m resolution LULC map was produced for the Tigris-Euphrates basin. In total, 1184 Landsat scenes were processed within the Google Earth Engine (GEE). For the collection of ground truth data, differential manifestations of green cover were considered by dividing the study area into five climatic regions and the training samples were taken from each sub-region. To account for the temporal variation of LULC types, six two-month interval composite layers, including the spectral and thermal bands of Landsat-8, texture and spectral indices, as well as topographic factors were created for the target year 2019. Image segmentation and classification were performed using the simple non-iterative clustering (SNIC) and Random Forest (RF) algorithms, respectively. A computationally effective parallel processing approach was developed, which created a number of tiles and sub-tiles and a bulk command was converted into smaller parallel commands. The generated LULC map showed a satisfactory overall accuracy of 91.7%, with the highest User’s accuracy in water and wetland, and the lowest in rainfed crop and rangeland and the highest Producer’s accuracy in water and barren areas, and the lowest in garden and rangeland. This study highlights the necessity of using multi-temporal data for LULC mapping, in particular, multi-temporal NDVI, for the separation of different green cover types in arid and semi-arid environment.

This study aims at a comparative analysis of quantitative data, namely, OSM and BDOT10k. Analyses were conducted in a 1 km2 hexagonal grid, in seven test counties located in different regions of Poland, differing in the degree of urbanization, land cover and natural environment. It is assumed that the authors’ consolidated regional classification of the Compound Correspondence Index CCIRn is attributed to the geometric mapping unit based on TOPSIS values, and their statistical measure of dispersion enables the comparison of datasets for individual geographically disjointed areas according to uniform criteria, e.g., the number of topographic features stored in analyzed datasets, both polygonal (buildings, forests, surface water) and linear (roads, watercourses, railroads). The final results of the regional assessment outperform the local classification giving a higher level of data compliance. Overestimation of regional concordance ranges from 9 to 20% of the county area, with an average of 3% reduction in the area where the two datasets (BDOT10k and OSM) have comparable information ranges. Areas of medium and high nonconformity are decreased by an average of 2.4%.

Nowadays volunteered geographic information (VGI) and collaborative mapping projects such as OpenStreetMap (OSM) have gained popularity as they not only offer free data but also allow crowdsourced contributions. Spatial data entry in this manner creates quality concerns for further use of the VGI data. In this regard, this article focuses on the assessments of geometric and semantic quality of the OSM building features (BFs) against a large-scale topographic (TOPO) data belonging to some areas of Istanbul. The comparison is carried out based on the one-to-one matched BFs according to a geometric matching ratio. In geometric terms, various parameters of position (i.e. X, Y), size (i.e. area, perimeter and granularity), shape (i.e. convexity, circularity, elongation, equivalent rectangular index, rectangularity and roughness index), and orientation (i.e. orientation angle) elements are computed and compared. In semantic terms, BF type coherences are evaluated. According to the findings of geometric quality, the average positional difference was less than three meters. In addition, the perimeter values tended to decrease while area and granularity values tended to increase in OSM data against TOPO data. Those showed that the level of the detail of the OSM BFs was lower than TOPO BFs in general. This was also confirmed by the decreasing tendency of shape complexity according to the parameters of shape element. Orientation angle differences was often low except for some special cases. It was found that the scale of the OSM dataset, even though not homogenous, approximately corresponded to the lower limit of medium scale maps (i.e. 1:10,000) or a slightly smaller scale. According to the findings of semantic quality, in case of the presence of specific type definition, the coherence was rather high between OSM and TOPO BFs while the most OSM BFs did not have a specific type attribute. This study showed that the matching process needed some improvements while the followed approach was largely successful in the evaluation of the matched buildings from geometric and semantic aspects.

This paper investigates user preferences and behaviour associated with 2D and 3D modes of urban representation within a novel Topographic Immersive Virtual Environment (TopoIVE) created from official 1:10,000 mapping. Sixty participants were divided into two groups: the first were given a navigational task within a simulated city and the second were given the freedom to explore it. A Head-Mounted Display (HMD) Virtual Reality (VR) app allowed participants to switch between 2D and 3D representations of buildings with a remote controller and their use of these modes during the experiment was recorded. Participants performed mental rotation tests before entering the TopoIVE and were interviewed afterwards about their experiences using the app. The results indicate that participants preferred the 3D mode of representation overall, although preference for the 2D mode was slightly higher amongst those undertaking the navigational task, and reveal that different wayfinding solutions were adopted by participants according to their gender. Overall, the findings suggest that users exploit different aspects of 2D and 3D modes of visualization in their wayfinding strategy, regardless of their task. The potential to combine the functionality of 2D and 3D modes therefore offers substantial opportunities for the development of immersive virtual reality products derived from topographic datasets. [ABSTRACT FROM AUTHOR]

Increasing river floods and infrastructure development in many parts of the world have created an urgent need for accurate high-resolution flood hazard mapping for more efficient flood risk management. Mapping accuracy hinges on the quality of the underlying Digital Terrain Model (DTM) and other spatial datasets. This article presents a processing strategy to ensure consistent adaption of countrywide spatial datasets to the requirements of hydraulic modelling. The suggested methods are automatized to a large extent and include (i) automatic fitting of river axis positions to the DTM, (ii) detection of culverts and obstacles in the river channel (iii) Smooth elimination of obstacles by interpolation along the river axes (iv) geometric detection of water-land borders and the top edge of embankments for (v) integration of the submerged river bed geometry into the DTM. The processing chain is applied to a river network (33880 km) and a DTM from Airborne Laser Scanning (ALS) with 1 m spatial resolution covering the entire territory of Austria (∼84000 km2). Thus, countrywide consistency of data and methods is achieved along with high local relevance. Semi-automatic validation and extensive manual checks demonstrate that processing significantly improves the DTM with respect to topographic and hydraulic consistency. However, some open issues of automatic processing remain, e.g. in case of long underground river reaches.

The paper proposed a methodology for dasymetric development of a detailed population map for a city environment. The recalculation of population is based on linking the national database on buildings (BDOT) with the available statistical information about population density. The experiment was conducted in the city of Cracow, using demographic data with a high level of detail, related to the urban units of the city. The generation of population maps was performed for several options, dividing the buildings depending on their characteristics and location. The optimisation stage was based on a properly adjusted surface-weight method of correlation, where the global number of people in the city was used, while the statistical data from 141 urban units was considered to be reference data. The obtained results justify the division into single-family and multi-family buildings. The original connection between the function of population and the inhabitable area of a building (41 m2/person) was differentiated during optimisation: for single-family houses (84 m2/person) and for multi-family houses (37 m2/person). Due to this, the MAPE errors were improved from 48% to 30%, and RMSE from 2896 to 2684. Having performed additional segmentation of urban units according to the average inhabitable areas per person recorded for them, the parameters dropped down to: MAPE 10%, RMSE 1146.

• Using semantic segmentation for crack feature detection. • Create a training dataset from images of laboratory samples with fatigue fractures. • Topography data calculated form BSE SEM-images using shape-from-shading. • Simultaneous use of SE, BSE and topography data to predict crack features. • Study on relevant input data for deep neuronal network training in fractography. Fractography plays a critical role in failure analysis of engineering components and has a considerable importance for safety investigations. Usually, the interpretation of fracture surfaces is done by experts with the help of literature and experimental data, that requires a lot of experience. The use of deep learning (DL) with neural networks in failure analysis becomes more and more relevant with the rapidly developing possibilities. Especially, the modern network architectures can assist fractographers in determining various fracture features on SEM images of the fracture surfaces. The basis for the best possible evaluation is the understanding of the influence of the input data used for training deep neural networks (DNN). Therefore, this study discusses the influence of the selection of the input data used for the prediction quality of these networks in order to take this into account for future data acquisition. Specimens of various metallic materials were subjected to fatigue cracking experiment under laboratory conditions. The fractured surfaces were then imaged using various modes or detectors (such as SE, BSE and topography) in SEM, and those captured images were used to create a training data set. The relevance of the individual data for the quality of the prediction is determined by a specific combination of the different detector data. For the training, the well-established architecture of a UNet-ResNet34 with a fixed set of hyperparameters is used. It has been found in this present study that the combination of all input data significantly increases the prediction accuracy, whereby even the combination of SE and BSE data provides considerable advantages over the exclusive use of SE images. [ABSTRACT FROM AUTHOR]

With the continuous development of science and technology, volunteer geographic information (VGI) has become one of the most important data sources in geographic data acquisition. In order to make more efficient use of such volunteered data, the VGI is often needed to be integrated to the corresponding traditional datasets. We develop a special case of data integration between the topographic dataset of ATKIS maintained by German Surveying and Mapping Agencies and the AOSD data primarily collected by numerous enthusiasts (volunteers) of jogging, hiking, biking (including road and mountain), etc. Considering that the VGI of AOSD reveals quite different LODs (level of details) to the traditional topographic dataset of ATKIS, we put forward a new approach to realize highly automatic and accurate integrations of these two datasets. The proposed approach is characterized by 4 processes: (1) intelligent segmentation of the road features, (2) road-networks matching between different datasets, (3) data integration between different road networks and (4) internal data matching and integration in the conflated road network. Experimental results demonstrate high performance with respect to matching rate, matching accuracy and computing speed in a number of large test areas. [ABSTRACT FROM AUTHOR]

Population data are generally provided by state census organisations at the predefined census enumeration units. However, these datasets very are often required at userdefined spatial units that differ from the census output levels. A number of population estimation techniques have been developed to address these problems. This article is one of those attempts aimed at improving county level population estimates by using spatial disaggregation models with support of buildings characteristic, derived from national topographic database, and average area of a flat. The experimental gridded population surface was created for Opatów county, sparsely populated rural region located in Central Poland. The method relies on geolocation of population counts in buildings, taking into account the building volume and structural building type and then aggregation the people total in 1 km quadrilateral grid. The overall quality of population distribution surface expressed by the mean of RMSE equals 9 persons, and the MAE equals 0.01. We also discovered that nearly 20% of total county area is unpopulated and 80% of people lived on 33% of the county territory.

The article focuses on the challenges of digitizing watercourse datasets for Artificial intelligence (AI)-based feature extraction. It highlights the limitations of traditional mapping methods and the need for more accurate label data. It discusses arbitrary classification of natural phenomena, topographic data layers, and factors like overgrowth and elevation changes. It reports the challenges, manual digitization remains crucial for machine learning recognition.

Abstract With a little more than 100 years since the publication of seminal and field-defining investigations, active tectonics is still a relatively young sub-discipline of structural geology. This research field addresses the accumulation of strain due to plate tectonic motion and more importantly release thereof through the occurrence of earthquakes (or other strain-releasing events). In that regard, active tectonics aims to characterize the incremental steps of plate tectonics. Determining earthquake chronologies, fault slip rates, and other common objectives importantly feed into our understanding of, for example, fault mechanics and crustal rheology. Characterizing the recurrence of large and potentially devastating earthquakes, is further motivated by seismic hazard assessment and risk mitigation. The primary data source in active tectonics is surface and shallow subsurface evidence of faulting –presenting itself in topographic and stratigraphic data sets respectively. Field observations and air photo interpretation of displaced stratigraphic and geomorphic markers were used almost 40 years ago to formulate end-member models of earthquake recurrence. Technological developments since then –especially within the last two decades– have dramatically increased the abundance and resolution of topographic data sets and the ability to date stratigraphic units and geomorphic surfaces, enabling the formulation of better-informed conceptual models of earthquake recurrence. Here, we provide an overview of the high-resolution topographic data sets and dating methods that enabled the recent advances of active tectonics. Graphical abstract Image 1 Highlights • Advances in active tectonics in 4D, spatially 3D plus temporal dimension. • Overview of global and local topographic data sets and obtaining methods. • Advances in Quaternary dating methods. [ABSTRACT FROM AUTHOR]

The paper proposed a methodology for dasymetric development of a detailed population map for a city environment. The recalculation of population is based on linking the national database on buildings (BDOT) with the available statistical information about population density. The experiment was conducted in the city of Cracow, using demographic data with a high level of detail, related to the urban units of the city. The generation of population maps was performed for several options, dividing the buildings depending on their characteristics and location. The optimisation stage was based on a properly adjusted surface-weight method of correlation, where the global number of people in the city was used, while the statistical data from 141 urban units was considered to be reference data. The obtained results justify the division into single-family and multi-family buildings. The original connection between the function of population and the inhabitable area of a building (41 m2/person) was differentiated during optimisation: for single-family houses (84 m2/person) and for multi-family houses (37 m2/person). Due to this, the MAPE errors were improved from 48% to 30%, and RMSE from 2896 to 2684. Having performed additional segmentation of urban units according to the average inhabitable areas per person recorded for them, the parameters dropped down to: MAPE 10%, RMSE 1146. [ABSTRACT FROM AUTHOR]

Abstract: Measuring fault offsets preserved at the ground surface is of primary importance to recover earthquake and long‐term slip distributions and understand fault mechanics. The recent explosion of high‐resolution topographic data, such as Lidar and photogrammetric digital elevation models, offers an unprecedented opportunity to measure dense collections of fault offsets. We have developed a new Matlab code, 3D_Fault_Offsets, to automate these measurements. In topographic data, 3D_Fault_Offsets mathematically identifies and represents nine of the most prominent geometric characteristics of common sublinear markers along faults (especially strike slip) in 3‐D, such as the streambed (minimum elevation), top, free face and base of channel banks or scarps (minimum Laplacian, maximum gradient, and maximum Laplacian), and ridges (maximum elevation). By calculating best fit lines through the nine point clouds on either side of the fault, the code computes the lateral and vertical offsets between the piercing points of these lines onto the fault plane, providing nine lateral and nine vertical offset measures per marker. Through a Monte Carlo approach, the code calculates the total uncertainty on each offset. It then provides tools to statistically analyze the dense collection of measures and to reconstruct the prefaulted marker geometry in the horizontal and vertical planes. We applied 3D_Fault_Offsets to remeasure previously published offsets across 88 markers on the San Andreas, Owens Valley, and Hope faults. We obtained 5,454 lateral and vertical offset measures. These automatic measures compare well to prior ones, field and remote, while their rich record provides new insights on the preservation of fault displacements in the morphology. [ABSTRACT FROM AUTHOR]

Detailed information on spatial patterns of tree species diversity (TSD) is essential for biodiversity assessment, forest disturbance monitoring, and the management and conservation of forest resources. TSD mapping approaches based on the Spectral Variability Hypothesis (SVH) could provide a reliable alternative to image classification methods. However, such methods have not been tested in large-scale TSD mapping using Sentinel-1 and Sentinel-2 images. In this study, we developed a new workflow for large-scale TSD mapping in an approximately 4000 km2 temperate montane forest using Sentinel-1 and Sentinel-2 imagery-based heterogeneity metrics and topographic data. Through a systematic comparison of model performance in 24 prediction scenarios with different combinations of input variables, and a correlation analysis between six image heterogeneity metrics and two in-situ TSD indicators (species richness S and Shannon-Wiener diversity H′), we assessed the effects of vegetation phenology, image heterogeneity metrics, and sensor type on the accuracy of TSD predictions. Our results show that (1) the combination of Sentinel-1 and Sentinel-2 imagery produced higher accuracy of TSD predictions compared to the Sentinel-2 data alone, and that the further inclusion of topographic data yielded the highest accuracy (S : R 2 = 0.562 , RMSE = 1.502; H′ : R 2 = 0.628, RMSE = 0.231); (2) both Multi-Temporal and Spectral-Temporal-Metric data capture phenology-related information of tree species and significantly improved the accuracy of TSD predictions; (3) texture metrics outperformed other image heterogeneity metrics (i.e., Coefficient of Variation, Rao's Q, Convex Hull Volume, Spectral Angle Mapper, and the Convex Hull Area), and the enhanced vegetation index (EVI) derived image heterogeneity metrics were most effective in predicting TSD; and (4) the spatial distribution of TSD showed a clear decrease trend along the altitudinal gradient (r = −0.61 for S and − 0.45 for H′) and varied significantly among forest types. Our results suggest a good potential of the SVH-based approaches combined with Sentinel-1 and Sentinel-2 imagery and topographic data for large-scale TSD mapping in temperate montane forests. The TSD maps generated in our study will be valuable for forest biodiversity assessments and for developing management and conservation measures. [Display omitted] • The Spectral Variation Hypothesis was tested in a temperate montane forest using Sentinel-2 images. • Tree species diversity mapping was affected by sensor type, vegetation phenology, and image heterogeneity metric. • Texture metrics outperformed other heterogeneity metrics in predicting tree species diversity. • The EVI-derived spectral heterogeneity metrics correlated most with tree species diversity. • Topographic variables improved the mapping accuracy of tree species diversity. [ABSTRACT FROM AUTHOR]

The Shallow Subsurface Radar (SHARAD), a sounding radar equipped on the Mars Reconnaissance Orbiter (MRO), has produced highly valuable information about the Martian subsurface. In particular, the complicated substructures of Mars such as polar deposit, pedestal crater and the other geomorphic features involving possible subsurface ice body has been successfully investigated by SHARAD. In this study, we established a 3D subsurface mapping strategy employing the multiple SHARAD profiles. A number of interpretation components of SHARAD signals were integrated into a subsurface mapping scheme using radargram information and topographic data, then applied over a few mid latitude Lobate Debris Aprons (LDAs). From the identified subsurface layers of LDA, and the GIS data base incorporating the other interpretation outcomes, we are expecting to trace the origin of LDAs. Also, the subsurface mapping scheme developed in this study will be further applied to other interesting Martian geological features such as inter crater structures, aeolian deposits and fluvial sediments. To achieve higher precision sub-surface mapping, the clutter simulation employing the high resolution topographic data and the upgraded clustering algorithms assuming multiple sub-surface layers will be also developed. [ABSTRACT FROM AUTHOR]

From several decades ago, the average shear wave velocity for the top 30 m ( Vs30 ) has been proposed as one of the important factors that reflects the amplification behavior of a site. Most of seismic design standards such as National Earthquake Hazards Reduction Program in the United States and Standard No. 2800 in Iran emphasize on the use of Vs30 measurements for site classification according to the soil type. As an important step in profound seismic risk reduction to earthquakes, a site effect study was conducted at a nationwide scale. We followed an indirect method to produce Vs30 map of Iran from geological and topographical data. The outputs indicate that hybrid Vs30 map has better performance than single topography-based Vs30 map. The amplitude map deduced from Vs30 and geology maps then is used for seismic microzonation of Tabriz city and extent of geographical distribution of damage for a possible deterministic scenario (M=7) is investigated through considering different fragility curves to describe damaging behavior of ordinary building types in the city. [ABSTRACT FROM AUTHOR]

El género Eucalyptus presenta gran potencial con fines comerciales y es la especie de árbol más plantada en Brasil. Las perspectivas del cambio climático en las proyecciones futuras del IPCC (Intergovernmental Panel on Climate Change) indican que se pueden producir pérdidas significativas en las actividades agrícolas y forestales. El objetivo de este estudio fue determinar las zonas aptas para plantaciones de Eucalyptus grandis, sobre la base de datos climatológicos y de relieve en los escenarios futuros. El trabajo fue desarrollado en la provincia del Espirito Santo (ES-Brasil). Fueron utilizadas las normales de clima obtenidas de estaciones pluviométricas. El balance de agua se calculó por el método de Tornthwaite y Mather. Se estimó la temperatura con base en los datos de latitud y altitud. Se utilizaron los datos SRTM para obtener la altitud y la declividad para las zonas de mecanización agrícola. Para la interpolación de los datos se utilizó el método del inverso del cuadrado de la distancia. Los datos de escenarios futuros se obtuvieron del modelo HADCM3 del IPCC en escenarios A (pesimista) y B (optimista) estimados para los años de 2020, 2050 y 2080. Se estima que las zonas aptas para plantaciones se redujeron en ambos escenarios, llegando a la reducción de 71,7% y 82,5% en el escenario A y B, respectivamente para el año de 2080. El déficit de agua actuó como un factor limitante en la plantación. Deben llevarse a cabo nuevos estudios relacionando la aptitud de la especie en el contexto del cambio climático.The genus Eucalyptus presents a large commercial potential and it is the arboreal species most planted in Brazil. Perspectives of climate change in the future projections of the IPCC (Intergovernmental Panel on Climate Change) indicate that productivity losses may occur in diverse agricultural and forestry crops. The objective of this study was to determine the zones apt for planting of eucalyptus based on relief and climate data for current and future scenarios. The study was developed in the state of Espírito Santo, Brazil, and normal climatological data was obtained from rain gauges. The water balance was calculated by the Tornthwaite and Mather methodology. Temperature was estimated using data of latitude and altitude. Data from the SRTM were used to obtain the altitude and zone of agricultural mechanization, based on slopes. For interpolation of the data, the inverse square distance method was used. The future data were estimated by the HADCM3 model of the IPCC in scenarios: A (pessimistic) and B (optimistic) for the years of 2020, 2050 and 2080. It is estimated that the zones suitable for planting are reduced in both scenarios, diminishing by 71.1% and 82% for scenarios A and B, respectively in the year 2080. The water deficit acted as a limiting factor for planting. Due to the complexity of interactions of biotic and abiotic factors, new capability studies should be performed in the context of climate change.

Agencija RS za okolje je s sredstvi EU začela izvajati projekt nadgradnje sistema za spremljanje in analiziranje stanja vodnega okolja v Sloveniji. Poimenovala ga je BOBER, kar je kratica za Boljše Opazovanje za Boljše Ekološke Rešitve. Temeljni cilj je zagotoviti meteorološke in hidrološke meritve, ki bodo omogočile celovito spremljanje in analiziranje stanja vodnega okolja v Sloveniji. V okviru projekta je bil razvit sistem, s katerim se na podlagi hidrološkega in meteorološkega opazovanja ter napovedi meteoroloških modelov spremlja hidrološko stanje in napovedujejo razmere za šest dni vnaprej. Hidrologi sistem uporabljajo kot kakovosten pripomoček za pregled hidrološkega stanja, pripravo hidrološke napovedi in pravočasno opozarjanje pred poplavami. Za učinkovito opozarjanje širše javnosti hidrološki prognostični sistem dopolnjuje sistem Hidroalarm. Hidrološki prognostični sistem združuje raznolike naloge, ki jih lahko povežemo v štiri sklope: upravljanje podatkov, vzpostavitev računskih modulov, postavitev kontrolnega in upravljavskega mehanizma ter predstavitev rezultatov v spletnem prostorskem prikazu. Pri izdelavi sedanjega sistema smo imeli malo dostopnih geoinfromacijskih virov, namenjenih modeliranju v vodarski stroki, in pogosto smo naleteli na neenotne tipe geodetskih podatkov, ki smo jih potrebovali. V prispevku sta opisana vzpostavljanje sedanjega sistema in njegov nadaljnji razvoj, opredeljene so tudi potrebe po enotnem javnem zbiranju prostorskih vodarskih podatkov za dolgoročni razvoj vodarske stroke ; The Slovenian Environmental Agency (SEA) has started a project entitled “Upgrading the system for monitoring and analysing the state of the water environment”, which is partly financed through the European Cohesion Fund. The project was named “BOBER” (Better Observation for Better Environmental Response). The wider purpose of the project is to increase the capacity of the SEA to monitor, examine and forecast water cycle factors. The Flood Forecasting System (FFS) has been developed in the framework of the BOBER project. The system provides an overview over forecasts of river discharges and water levels for six days ahead. The FFS is becoming a basic operational tool for the preparation and issuing of daily hydrological forecasts and flood warnings by the Flood Forecasting Department of the SEA. To issue effective flood warnings to the general public, the Hydroalarm system has been implemented. The setup of the FFS is strongly connected to sufficient and available spatial data sources. The FFS combines different tasks; data management, model calibration, decision and management support systems, which are combined through a graphical user interface. During the project, few data sources appropriate for modelling purposes were found. Quite frequently the gathered data were available in different usable formats and needed transformation to usable forms. The discussion in the article focuses on the required data sources needed to develop flood forecasting systems and future spatial and other data requirements for the upgrading and further development of water management sector.

Topografski podatki, kot pomemben del Nacionalne prostorske podatkovne infrastrukture, so bili v letih po osamosvojitvi Slovenije deležni velike pozornosti, postali so splošno dostopni, bili so dopolnjeni in medsebojno usklajeni. V zadnjem desetletju pa se je vlaganje v topografske podatke v Sloveniji zelo omejilo, zato danes nikakor več ne moremo biti zadovoljni z njihovim stanjem. V prispevku pregledno predstavljamo stanje topografskih podatkov v Sloveniji, analiziramo njihovo kakovost in ustreznost za potencialne in dejanske uporabnike. Posvetimo se izvornim posnetkom stanja, kot je sistemsko ciklično aerosnemanje (CAS), in iz njega izvedenemu proizvodu, ortofotu. Kakovost ortofota je precej odvisna od kakovosti modela reliefa. Topografski podatki so vodeni posamično v sklopu posameznih vsebinskih baz (REZI, ZK GJI, grafični del katastra stavb) ter združeno v topografskih bazah in kartah različnih ravni podrobnosti (DTK 5, DTK 25, DTK 50, sistem DPK). Analizirano stanje primerjamo s stanjem v nekaterih sosednjih ali primerljivih državah ; Topographic data, an important part of the National Spatial Data Infrastructure, have been given serious attention since Slovenia’s independence. It has become publicly available, updated and harmonised. Financing of topographic data in Slovenia has significantly decreased over the previous decade. As a result, the present status is far from acceptable or expected. The current status of the topographic data, as well as its quality and usability for potential users is discussed in this article. The overview starts with basic source data, aerial surveys, photographs and orthophotos. The quality of orthophotos largely depends on the DTM quality. Topographic data is nowadays organised in thematic datasets (geographical names, building cadastre, etc.) or joined in datasets of different levels of accuracy and details. The status in Slovenia is compared to those in some neighbouring and other comparable countries.

The paper deals the procedures and processes in the modeling of topographic data. There are some fazes and procedures of modeling of topographic data in digital form. It deals in capturing, modeling, distributing and archiving of data. Sometimes many procedures are need for convertion and transformation from one format to other, from one system to other. The procedure of modeling data is a very important way and with computer-aided along with a certain degree of automatizaton that is useful for using and updating of topographic contents. .

Through the project Production of an object-oriented conceptual data model and production of GML application schema, the CROTIS data model is fully conformed to the latest ISO and OGC standards. A new data model, a new schema for data exchange and a new data catalogue have been encompassed within the project. The main elements of the project are presented in this article. The modelling was done for the purpose of data model improvement, according to standards that provide the methods and properties for display of model objects and model attributes. UML (Unified Modelling Language) is used for formal description of the data. A logical data model in UML enables the implementation of GIS, including the database as well. The automatic generation of a GML application schema was developed from UML. Data description is contained in the data catalogue, which resulted automatically from data model.Ključne riječi

Croatian project Cartographic Data Model (KMP) has been started as a component of the STOKIS (SGA, 1995, Official Topographic and Cartographic Information System) project. The cartographic data model conforms to CROTIS (Topographic Information System of the Republic of Croatia). It enables the generation of the cartographic database from topographic one. Classification of data is performed by logical grouping of objects and depends on geometry, type and properties of features. The cartographic data model describes structure of cartographic database and all attributes, categories, types and fields. Description of geometry and exchange of data is performed according to the specification of ISO Standards, adapted by Technical Committee ISO/TC 211, Geographic information/Geomatics and OpenGIS Consortium. Creation of the cartographic data model is the basis for the creation of cartographic database. The next step is direct implementation of vector model that contains graphic and alphanumeric elements. The cartographic key must stay identical to TK25 and maps of other scales.

Craters are distinctive features on the surfaces of most terrestrial planets. Craters reveal the relative ages of surface units and provide information on surface geology. Extracting craters is one of the fundamental tasks in planetary research. Although many automated crater detection algorithms have been developed to exact craters from image or topographic data, most of them are applicable only in particular regions, and only a few can be widely used, especially in complex surface settings. In this study, we present a machine learning approach to crater detection from topographic data. This approach includes two steps: detecting square regions which contain one crater with the use of a boosting algorithm and delineating the rims of the crater in each square region by local terrain analysis and circular Hough transform. A new variant of Haar-like features (scaled Haar-like features) is proposed and combined with traditional Haar-like features and local binary pattern features to enhance the performance of the classifier. Experimental results with the use of Mars topographic data demonstrate that the developed approach can significantly decrease the false positive detection rate while maintaining a relatively high true positive detection rate even in challenging sites. [ABSTRACT FROM AUTHOR]

The urban environment dominates the world over and some regions, such as Europe, are highly urbanized. Today, 72% of Europe's population lives in cities, towns, and suburbs. Cities are characterized by a high concentration of people, dense built-up area, highly developed transport infrastructure and services, and relatively weak and scattered urban greenery. However, the structure of the city is not uniform and the built-up area in cities becomes less compact the further away from the city center. On the outskirts of the city, built-up areas are becoming dispersed, there is more undeveloped land, the transport network is less dense, and finally the urban environment mixes with rural areas, creating the so-called transition area. The environmental dimension of city life is essential to the health and well-being of its inhabitants as well as to the quality of the surrounding territories, and therefore of great importance to decision-makers at all levels of government, from local to national and European. Appreciating the role of maps and cartographic visualizations in supporting decision making e.g. Medyńska-Gulij et al. (2021), our research aims to demonstrate the complex geovisualization of urban area from topographic data. In particular, we focus on the visualization of buildings and surrounding elements of "grey infrastructure" such as, roads, tramways, and utilities that determine a city's layout as well as "green infrastructure", i.e. street trees, lawns, parks, community gardens, green roofs. The problem discussed in these considerations is the use of visual variables, both classical (Bertin) and new ones, as well as cartographic methods that enable the presentation of topographic data on a quantitative, ordinal, and qualitative scales. We focus mainly on the cartographic presentation of those areas of the city where multi-family buildings (block of flats) with educational facilities (such as schools or kindergartens), shops, as well as a local road, streets trees, lawns dominate. This study has become an inseparable part of the authors' research field focused mainly on modern visualization including topography and land cover e.g. Calka et al. (2016), Horbiński and Medyńska-Gulij (2017), Smaczyński et al. (2020), Wielebski et al. (2020). Topographic data collected mainly by the National Mapping Agencies in the form of a database with the level of detail corresponding to the map scale of 1: 10,000 are used for visualization e.g. Akiyama et al. (2019). Object location, geometry (area, height), object type and distance to other topographic objects were presented in quantitative, qualitative, and ordinal scales, respectively. One of the housing estates in Poznań was selected as the test area. Complex, alternative visualizations concern open topographic data provided by the Surveyor General of Poland publicly available via the spatial data infrastructure national geoportal e.g. Izdebski et al., (20121), Bielecka and Medyńska-Gulij (2015) geoportal.gov.pl. [ABSTRACT FROM AUTHOR]

A method enabling the object-oriented image analysis of landscape elements incorporating topographic data was designed and tested on a Japanese countryside target area. IKONOS data (four multispectral bands with a spatial resolution of 4 m and a panchromatic band with a spatial resolution of 1 m) acquired on 23 April 2001 were used. Definiens v.5 software (Definiens AG, München, Germany) was employed for the classification. The initial segmentation was multiresolution and bottom-up, and each segment identified was considered to be one object. Two classifications employing the same landscape elements and ground truth data were implemented. One classification adopted an object-based image analysis classification method based on spectral characteristics; the other utilized an object-oriented image analysis (OOIA) that allows for a suitable scale parameter to be selected independently for each landscape element. In addition, topographic data derived from field surveys (walking surveys) and topographic maps were used to create a topographic database delineating the boundary between valley bottoms and the adjacent slopes (elevation: about 10 m). These data were then integrated into the OOIA analysis. The accuracies of the two classifications were assessed by comparing the results to a master landscape map produced directly from aerial photographs and on-site observations. The object-oriented method using the topographic data resulted in a higher overall kappa coefficients (0.63-0.47) than the object-based method. These results indicate that object-oriented image analysis of very high resolution data used in combination with topographic data can be an effective tool for landscape classification in Japan, where historical land-use patterns have resulted in finely dissected landscapes. [ABSTRACT FROM AUTHOR]

The All-Weather Volcano Topography Imaging Sensor remote sensing instrument is a custom-built millimeter-wave (MMW) sensor that has been developed as a practical field tool for remote sensing of volcanic terrain at active lava domes. The portable instrument combines active and passive MMW measurements to record topographic and thermal data in almost all weather conditions from ground-based survey points. We describe how the instrument is deployed in the field, the quality of the primary ranging and radiometric measurements, and the postprocessing techniques used to derive the geophysical products of the target terrain, surface temperature, and reflectivity. By comparison of changing topography, we estimate the volume change and the lava extrusion rate. Validation of the MMW radiometry is also presented by quantitative comparison with coincident infrared thermal imagery. [ABSTRACT FROM PUBLISHER]

A blind watermarking technique for protecting topographic data from illegal use is proposed, taking into account four rules, i.e., usability, invisibility, robustness, and blindness. The technique firstly determines two feature layers and selects the key points from each layer as watermark embedding positions; then it shuffles the watermark and embeds the watermark in the two layers, respectively. To detect the watermark, a similar process for obtaining the feature layers and the key points in the watermark embedding process is carried out first; then the coordinates of the key points are detected to extract the embedded watermark; finally, the similarity degrees of the two versions of the extracted watermark is calculated, by which the conclusion on whether the data contains the watermark is made. Our experiments show that the technique can resist the attacks from data format change, random noise, similarity transformation, and data editing to some extent. [ABSTRACT FROM AUTHOR]

The Slovenian Environmental Agency (SEA) has started a project entitled "Upgrading the system for monitoring and analysing the state of the water environment", which is partly financed through the European Cohesion Fund. The project was named "BOBER" (Better Observation for Better Environmental Response). The wider purpose of the project is to increase the capacity of the SEA to monitor, examine and forecast water cycle factors. The Flood Forecasting System (FFS) has been developed in the framework of the BOBER project. The system provides an overview over forecasts of river discharges and water levels for six days ahead. The FFS is becoming a basic operational tool for the preparation and issuing of daily hydrological forecasts and flood warnings by the Flood Forecasting Department of the SEA. To issue effective flood warnings to the general public, the Hydroalarm system has been implemented. The setup of the FFS is strongly connected to sufficient and available spatial data sources. The FFS combines different tasks; data management, model calibration, decision and management support systems, which are combined through a graphical user interface. During the project, few data sources appropriate for modelling purposes were found. Quite frequently the gathered data were available in different usable formats and needed transformation to usable forms. The discussion in the article focuses on the required data sources needed to develop f lood forecasting systems and future spatial and other data requirements for the upgrading and further development of water management sector. [ABSTRACT FROM AUTHOR]

Our research is concerned with automated generalisation of topographic vector databases in order to produce maps. This article presents a new, agent-based generalisation model called CartACom (Cartographic generalisation with Communicating Agents), dedicated to the treatment of areas of low density but where rubber sheeting techniques are not sufficient because some eliminations or aggregations are needed. In CartACom, the objects of the initial database are modelled as agents, that is, autonomous entities, that choose and apply generalisation algorithms to themselves in order to increase the satisfaction of their constraints as much as possible. The CartACom model focuses on modelling and treating the relational constraints, defined as constraints that concern a relation between two objects. In order to detect and assess their relational constraints, the CartACom agents are able to perceive their spatial surroundings. Moreover, to make the good generalisation decisions to satisfy their relational constraints, they are able to communicate with their neighbours using predefined dialogue protocols. Finally, a hook to another agent-based generalisation model – AGENT – is provided, so that the CartACom agents can handle not only their relational constraints but also their internal constraints. The CartACom model has been applied to the generalisation of low-density, heterogeneous areas like rural areas, where the space is not hierarchically organised. Examples of results obtained on real data show that it is well adapted for this application. [ABSTRACT FROM PUBLISHER]

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Topographic data, an important part of the National Spatial Data Infrastructure, have been given serious attention since Slovenia's independence. It has become publicly available, updated and harmonised. Financing of topographic data in Slovenia has significantly decreased over the previous decade. As a result, the present status is far from acceptable or expected. The current status of the topographic data, as well as its quality and usability for potential users is discussed in this article. The overview starts with basic source data, aerial surveys, photographs and orthophotos. The quality of orthophotos largely depends on the DTM quality. Topographic data is nowadays organised in thematic data sets (geographical names, building cadastre, etc.) or joined in data sets of different levels of accuracy and details. The status in Slovenia is compared to those in some neighbouring and other comparable countries. [ABSTRACT FROM AUTHOR]

This paper aims to assess the effect of incorporating topographical data with geostatistical interpolation for monthly rainfall and temperature in Ping Basin, Thailand. The spatial interpolation techniques based on 11 semivariogram models of 4 main sub-types of cokriging with 3 topographical variables: elevation, longitude, and latitude have been applied in this study. The best interpolation models from cokriging technique on mean monthly rainfall and mean monthly temperature are selected by Akaike Information Criterion (AIC) based on partial sill, range and nugget that the best monthly models of kriging technique is operated in same mentioned selection. In addition, an assessment of the effective results of the cokriging interpolation models is performed by 2 approaches: i) comparing the errors of the best results from other interpolations excluding topographic data with the least MAE, MRE and RMSE value and ii) comparing the accuracy of results from Multiple Linear Regression (MLR) with the coefficient of determination (r2). It was found that cokriging models of mean monthly rainfaJI and mean monthly temperature have more effectiveness than other interpolations excluding topographic data and MLR including topographic data. Therefore, this study can use the best results of sub-type and semivariog· am model from cokriging including topographic variables for mean monthly rainfall and mean monthly temperature surface interpolation. [ABSTRACT FROM AUTHOR]

In this study, an artificial neural network (ANN) model developed in order to estimate the average monthly soil temperatures in the Aegean Region of Turkey based on the topographic data. The soil temperatures, which have been taken from İzmir, Muğla, Aydın, Denizli, Uşak, Manisa, Kütahya and Afyonkarahisar meteorological stations, have been measured between the years 2000 and 2006 by the Turkish State Meteorological Service (TSMS), and temperatures have been measured at depths of 5, 10, 20, 50 and 100 cm respectively below the ground level. The latitude, longitude, altitude, depth and lunar information have been used in the input layer of the built artificial neural network model while the soil temperatures recognized as a target data have been used in the output layer. An estimation model has been developed employing MATLAB program and the derived results have been compared with the actual values. As a result, it has been seen that the error values have been found within the acceptable limits. [ABSTRACT FROM AUTHOR]

The article evaluates the ability of digital filters to improve topographic representation, using a Gaussian noise removal filter, the proprietary filters commonly applied to these datasets, and a terrain sensitive filter, similar to those applied to laser altimetry data. It assesses topographic representation in terms of both absolute accuracy measured with reference to independent check data and derived geomorphological variables, including slope, upslope contributing area, topographic index and landslide failure probability, from a steepland catchment in northern England. The results suggest that proprietary filters often degrade or fail to improve precision.

Through the project Production of an object-oriented conceptual data model and production of GML application schema, the CROTIS data model is fully conformed to the latest ISO and OGC standards. A new data model, a new schema for data exchange and a new data catalogue have been encompassed within the project. The main elements of the project are presented in this article. The modelling was done for the purpose of data model improvement, according to standards that provide the methods and properties for display of model objects and model attributes. UML (Unified Modelling Language) is used for formal description of the data. A logical data model in UML enables the implementation of GIS, including the database as well. The automatic generation of a GML application schema was developed from UML. Data description is contained in the data catalogue, which resulted automatically from data model. [ABSTRACT FROM AUTHOR]

Detailed soil maps are required for land evaluation and subsequent comprehensive land-use planning of the Jordanian arid to semi-arid area. The purity and the details of a suitability map are improved when a detailed soil map is used to produce it. This paper investigates the use of Landsat TM images and topographic data to assist in differentiating areas which represent soil-mapping units, at a detailed level. A 3-D view of Landsat TM image data using an air photo-derived DEM proved the best method to assist in this differentiation. Overlaying the soil observation points enhances this view, and provides a tool to validate the delineation. Further research is needed to investigate the interactive use of air photo or satellite image-derived DEMs and satellite data, with more focus on-site-specific planning and field verification of the technique. [Copyright &y& Elsevier]

We investigate users' wayfinding behaviour in a Topographic Immersive Virtual Environment (TopoIVE) created from urban topographic data. The experiment involved 60 participants: 30 were given a navigational task and 30 were allowed to freely explore a simulated city. Participants used a Head-Mounted Display (HMD) Virtual Reality (VR) app to enable them to switch between 2D and 3D modes of visualization. Their locations within the TopoIVE were recorded and analysed. Although several participant variables were tested (including their VR experience), the results reveal that different wayfinding solutions were adopted by males and females. The findings also suggest that users referred to both 2D and 3D modes of visualization in their wayfinding strategy. We therefore recommend that developers of virtual environments should consider how different strategies are adopted by different users. [ABSTRACT FROM AUTHOR]

Different methods have been proposed to create seismic site condition maps. Ground-based methods are time-consuming in many places and require a lot of manual work. One method suggests topographic data as a proxy for seismic site condition of large areas. In this study, we mainly focused on the use of an ASTER 1c digital elevation model (DEM) to produce Vs30 maps throughout Iran using a GIS-based regression analysis of Vs30 measurements at 514 seismic stations. These maps were found to be comparable with those that were previously created from SRTM 30c data. The Vs30 results from ASTER 1c estimated the higher velocities better than those from SRTM 30c. In addition, a combination of ASTER 1c and SRTM 30c amplification maps can be useful for the detection of geological and geomorphological units. We also classified the terrain surface of six seismotectonic regions in Iran into 16 classes, considering three important criteria (slope, convexity and texture) to extract more information about the location and morphological characteristics of the stations. The results show that 98% of the stations are situated in six classes, 30% of which are in class 12, 27% in class 6, 17% in class 9, 16% in class 3, 4% in class 3and the rest of the stations are located in other classes. [ABSTRACT FROM AUTHOR]

Summary: In recent years, geospatial data have exploded to massive volume and diversity and subsequently cause serious usability issues for researchers in various scientific areas. This paper describes a cyberGIS community data service framework to facilitate geospatial big data access, processing, and sharing based on a hybrid supercomputer architecture. Specifically, the framework aims to enhance the usability of national elevation dataset released by the U.S. Geological Survey in the contiguous United States at the resolution of 1/3 arc‐second. A community data service, namely TopoLens, is created to demonstrate the workflow integration of national elevation dataset and the associated computation and analysis. Two user‐friendly environments, including a publicly available web application and a private workspace based on the Jupyter notebook, are provided for users to access both precomputed and on‐demand computed high‐resolution elevation data. The system architecture of TopoLens is implemented by exploiting the ROGER supercomputer, the first cyberGIS supercomputer dedicated to geospatial problem‐solving. The usability of TopoLens has been acknowledged in the topographic user community evaluation. [ABSTRACT FROM AUTHOR]

Virtual reality (VR) is a display and control technology that provides an interactive computer-generated threedimensional environment to a user, often via a Head Mounted Display (HMD). VR delivers an immediate and immersive sensory experience of simulated worlds (which may or may not resemble reality), particularly of environments that might otherwise be physically inaccessible to the user due to their location, scale, time or danger. Although the first VR systems began to emerge in the 1960s, their relevance to cartographic applications has only recently become an explicit focus of research. Moreover, the potential of VR technology to visualize topographic databases has yet to be explored by cartographers. In this experiment, we designed a VR application of a fictitious city derived from state 1:10,000 topographic data (Polish Database of Topographic Objects BDOT10k) to test user preferences for 2D or 3D urban geovisualizations. The app allows the user to switch between 2D and 3D representations of buildings in the simulation using a remote controller. This functionality enabled participants of the experiment to freely select 2D or 3D mode and for their preferences to be recorded and measured. Our experiment involved two groups, one based in Poland and one in the UK, each comprising 30 participants (students enrolled on a Geography undergraduate course at each author's institution). Participants performed spatial ability tests to help ensure consistency in the sample and each group was divided into two sub-groups. Participants in the first subgroup were each given a navigation task that required their movement across the simulated city from point A to point B in the shortest possible time. Those in the second sub-group were given the freedom to explore the simulated city without being given a specific navigational task. We then interviewed participants in order to understand their own perception of their experiences in using the app. The results indicate the preferences of the two groups and sub-groups of participants. In particular, we establish whether users preferred the 2D mode for the navigational task and the 3D mode for free exploration. The findings suggest how producers of topographic datasets might develop the functionality of their products using VR. [ABSTRACT FROM AUTHOR]

Dolique, F., Jeanson, M. and Besson, J., 2007. A monitoring network for assessing the impact of extreme marine meteorological events on tropical beaches. Journal of Coastal Research, SI 50 (Proceedings of the 9th International Coastal Symposium), 77 – 81. Gold Coast, Australia, ISSN 0749.0208 Since 2003, a monitoring network of the dynamics of sandy beaches has been in operation in three tropical sites: Martinique (French West Indies), Tahiti and Moorea (French Polynesia) and Mayotte (Mozambique Channel). The objective of this network is to measure the impact of extreme weather-related marine events (storms, cyclones, strong swells, surges...) on beaches with varied structural settings and sedimentary environments. The methodology consists in the installation of observatories on the dynamics of sandy beaches in different morphological and sedimentary contexts. A "state zero" is established from a combination of satellite imagery, low altitude digital imagery and topographic and hydrodynamic measurements. These measurements are reiterated after an extreme event in order to apprehend the importance of morphological change, impact dampening and recovery. The monitoring is then continued over regular intervals with the aim of determining rates of morphological and sediment budget recovery until equilibrium is restored. This experimental network design will subsequently be extended to other tropical beaches located on the propagation paths of cyclones. [ABSTRACT FROM AUTHOR]