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This paper aims to convert surface data directly to a three-dimensional (3D) stereolithography (STL) part. The Geographic Information Systems (GIS) data available for a terrain are the data of its surface. It doesn’t have information for a solid model. The data need to be converted into a three-dimensional (3D) solid model for making physical models by additive manufacturing (AM).

A methodology has been developed to make the wall and base of the part and tessellates the part with triangles. A program has been written which gives output of the part in STL file format. The elevation data are interpolated and any singularity present is removed. Extensive search techniques are used.

AM technologies are increasingly being used for terrain modeling. However, there is not enough work done to convert the surface data into 3D solid model. The present work aids in this area.

The methodology removes data loss associated with intermediate file formats. Terrain models can be created in less time and less cost. Intricate geometries of terrain can be created with ease and great accuracy.

The terrain models can be used for GIS education, educating the community for catchment management, conservation management, etc.

The work allows direct and automated conversion of GIS surface data into a 3D STL part. It removes intermediate steps and any data loss associated with intermediate file formats.

The purpose of this study is to evaluate the reliability of the technique for estimating solar radiation in areas of rough topography and to detect the source of error and means for improvement.

Spatial data of the study area in the form of digital elevation model (DEM) coupled with geographic information system (GIS) were used to estimate the monthly solar radiation at locations with rough topography. The generated data were compared with measured data collected from all the selected locations using NASA data.

The results show that the variation in topographic parameters has a strong influence on the amount of solar radiation received by two close locations. However, the method performed well for solar radiation estimated in the areas of rough topography.

The proposed approach overestimates the monthly solar radiation as compared with NASA data due to the impact of topographic parameters accounted for by the model which are not accounted by conventional methods of measurements. This approach can be improved by incorporating the reflected component of radiation in the model used to estimate the solar radiation implemented in the GIS.

The approach of using GIS with DEM to estimate solar radiation enables to identify the spatial variability in solar radiation between two closest locations due to the influence of topographic parameters, and this will assist in proper energy planning and decision making for optimal areas of solar photovoltaic installation.

The purpose of this paper is to strive to develop a rock fall velocity model in C++ language and to give spatial attributes to the model using Geographic Information System (GIS) capabilities. Interaction between the parameters involved in the model is evaluated through GIS embedded techniques.

The mathematical model developed in C++ is based on the physical law of gravitation pull, adjudging the potential fall between two points at different elevation. Further, parameters influencing the velocity gradient – namely local relief, coefficient of land use friction, slope amount and slope length – are incorporated in the model. GIS is used extensively to generate the data required for the model. GIS capabilities are also explored for visualisation and interpretation of the model output. Section profiles and a co‐relation coefficient further strengthen the velocity map.

The rock fall velocity map generated using GIS shows variations in the velocity gradient at selected sections. It is concluded from analysis that friction values play a pivotal role in drastically changing the velocity gradient.

The model presented is restricted to rock fall velocity evaluation for a rectangular matrix of input data and spatial extent, rather than for specific locations. Incorporating parameters to delineate source areas and runout zones would produce a more realistic scenario. Trials along this line are in progress and are expected to be executed successfully very shortly.

The paper presents a versatile model with easily extractable parameters to compute rock fall velocity at a regional scale, conditioned for rugged terrain. The model has specific implications in infrastructure development and planning management for rocky terrain. Moreover, the model's output can be implemented effectively in preliminary investigations of the protection of forest development and erecting defensive measures in rock fall‐prone areas.

Not many models are available for rock fall velocity estimation on a regional scale. The model developed through this research work provides a platform for a regional‐scale study using parameters that can be easily derived from DEM and a land use map. It is reiterated that the model output is helpful for land planners and managers engaged in mountain development. The model is an effective tool in the strategic development of hazard management plans in slide‐prone areas.

Cartosat‐1 is the first Indian Remote Sensing satellite, developed for topographic mapping, able to collect in‐track high‐resolution stereo images with a 2.5 m pixel size. In the framework of the Cartosat‐1 Scientific Assessment Programme (C‐SAP), the Politecnico di Milano University (Italy) evaluated the performances of the Cartosat‐1 satellite in the generation of digital terrain models (DTMs) from stereo‐couples. The purpose of this paper is to describe in detail the outcomes for the Salon de Provence (France) test site, with respect to existing standards and products actually used in France and also to provide a comparison with the global Shuttle Radar Topography Mission's DTM freely available from by NASA.

The Cartosat‐1 data processing was done using the commercial off‐the‐shelf software ENVI®, selected for investigating the capabilities and limits of the system using standard image processing tools, so from the point of view of a typical remote sensing user. The data processing involved the following aspects: data pre‐processing; optimization of the DTM's extraction procedure; analysis of the influence of ground control points' (GCPs) in the generated DTMs; analysis of the influence of the DTM's resolution in the elevation accuracy; and post‐processing refinement.

When generating relative DTMs an error was observed in elevation of some hundreds of meters. After georeferencing, the root mean square error (RMSE) was between 9.0 and 14.2 m and the LE90 between 16.1 and 19.0 m. When generating absolute DTMs, the optimum number of GCPs was found to be 9, with a regular geometric distribution (4.6 m RMSE and 6.5 m LE90 for 10 m grid cell size). Post‐processing may be applied to enhance results (1.6 m RMSE and 2.0 m LE90 for 10 m grid cell size). In this case, the absolute DTMs fulfilled and also overcame the standards required for the IGNs and Spot Image's Reference 3D®.

This paper describes the outcomes of the C‐SAP led by the International Society for Photogrammetry and Remote Sensing and the Indian Space Research Organisation for evaluating the capabilities of the last Cartosat‐1 satellite. The aim is to provide remote sensing users a comprehensive study about the potentialities and limits of the Cartosat‐1 images for multi‐resolution DTM generation (from 5 to 90 m grid cell size).

The purpose of the present work is to develop a methodology for making physical models of catchment areas and terrains by rapid prototyping (RP) using geographic information systems (GIS) data. It is also intended to reduce data loss by minimising intermediate data translations.

The GIS data of a catchment area or a terrain were directly translated to an stereo lithography (STL) file. The STL surface was then manipulated in Magics‐RP to obtain a solid STL part, which can then be downloaded to a RP machine to obtain a physical model or representation of a terrain or catchtment area.

Intricate geometries of landforms were created with ease and great accuracy in RP machines. Terrain models were created in less time and lower cost than with conventional methods.

DEM ASCII XYZ (digital elevation model) data were used to input the required GIS data of specific terrains. Software can be developed for translation and manipulation of DEM, STL and other relevant file formats. This will eliminate any data loss associated with intermediate file transfer.

Terrain models were created with ease and great accuracy in RP machines. It takes less time and can be done more cost‐effectively. Terrain models have intricate geometries and for complex models, it may take months to make using conventional methods.

STL surfaces were obtained directly from GIS data for terrain modeling. This work fulfils the need of terrain modeling for catchment management, town‐planning, road‐transport planning, architecture, military applications, geological education, etc.

The purpose of this paper is to assess the vulnerability of the Kesennuma area in Japan to a tsunami disaster and to map the area of inundation.

Digital elevation model (DEM) data and ALOS image were used to create maps of the parameters of this study area: elevation, slope, coastal proximity, river, and land use. An analytical hierarchy process was used to assign weights to each parameter and a spatial multi-criteria analysis was applied through cell-based modelling for vulnerability mapping.

The vulnerability map shows that 17.679 km2 of the area could be inundated by a tsunami. High vulnerability areas were mostly found in coastal areas with a sloping coast and a cape area. A low elevation and the presence of rivers or water channels are factors that increase the impact of tsunamis. Inundation areas were predicted to spread in areas identified as having either high vulnerability or slightly high vulnerability.

Because of the limited geospatial data, the authors encourage further studies using DEM data with a high spatial resolution.

The results of this research can be used as basic information for disaster mitigation and urban planning in coastal areas.

This research creates a new approach for assessing which areas could be inundated by tsunamis, based on the vulnerability map generated through remote sensing and spatial multi-criteria analysis. Moreover, the parameters used are very close to those of actual inundation maps.

Remote sensing data and GIS techniques have been used to create thematic maps for assessment and estimation of landslide hazards, in Pos Slim‐Cameron Highlands area, Peninsula Malaysia. The Landsat TM5 scene was used to extract land use parameter of the study area. The digital elevation model (DEM) was generated from digitised topographic maps to produce slope risk map, aspect risk map and height risk map. From these data, a simple algorithm is created to classify the area into different risk zones. By overlaying all hazard maps, a final hazard map is produced. The integration of GIS with remotely sensed data might greatly facilitate classifying landslide areas to three categories; low risk, medium risk and high risk.

The purpose of this paper is to utilise the interactive view capability of the geographical information system (GIS) for the geological interpretation in Klang Valley, Malaysia.

Topographical map scale of 1:10 000 was used to generate digital elevation model (DEM). The geological map was draped over the DEM to create a 3D perspective view. The geological interpretation was undertaken using the 3D capability of the GIS software.

From the study, five lineaments which could possibly be the newly identified faults and one lithological boundary have been delineated.

Although these findings need to be rechecked in the field, they show the capability of the DEM application in structural geology interpretation.

The results obtained from this study demonstrate the capability of utilising a geological map draped over DEM for structural geological interpretation. Thus the technique may increase the interpretation accuracy.

The major outcome of this research is the possible use of DEM in the application of geological study.

Risk assessment is imperative for disaster risk reduction. The risk is rooted to various physical, social, economic, demographic and environmental factors that determine the probable magnitude of loss during an extreme event. By way of bringing a conceptual model into practice, this paper aims to examine the flood risk of the Srinagar city.

The “risk triangle” model has been adopted in the present investigation evaluating parameters, reflective of hazard (intensity), exposure (spatial) and vulnerability (sensitivity) using Landsat-8 operational land imager scene (10 September 2014), global positioning system, Cartosat-1 digital elevation model and socioeconomic and demographic data (Census of India, 2011). The authors characterise flood hazard intensity on the basis of variability in water depth during a recent event (September 2014 Kashmir flood); spatial exposure as a function of terrain elevation; and socioeconomic structure and demographic composition of each municipal ward of the city as a determinant factor of the vulnerability. Statistical evaluation and geographic information system-based systematic integration of all the multi-resolution data layers helped to develop composite flood risk score of each ward of the city.

Principal deliverable of this study is flood risk map of the Srinagar city. The results reveal that approximately 46 per cent of the city comprising 33 municipal wards is at high risk, while rest of the area, i.e. 17 and 37 per cent, exhibit moderate and low levels of risk, constituting 23 and 12 municipal wards, respectively. It is very likely that the municipal wards expressing high risk may witness comparatively more damage (impact) during any future flood event. Thus, there is a need of planned interventions (structural and non-structural) to minimise the emergent risk.

Very rare attempts have been made to bring theoretical models of disaster research in practice; this is mainly because of the complexities associated with the data (selection, availability and subjectivity), methodology (integration, quantification) and resolution (spatial scales). In this direction, this work is expected to have considerable impact, as it provides a clear foundation to overcome such issues for the studies aiming at disaster risk assessment. Furthermore, using varied primary and secondary data, this paper demonstrates the relative (municipal wards) flood risk status of the Srinagar city, which is one of the key aspects for flood hazard mitigation.

This paper aims to discuss rising sea levels at the global, regional, and community scale and illustrate the necessity for public comprehension and involvement. It also aims to demonstrate geographic information systems (GIS) as an efficient tool for modeling and disseminating information with the expectation that coastal communities will benefit by joining in a process to integrate this knowledge into broad‐based decision making.

GIS is capable of creating, analyzing, and displaying sea level rise scenarios enabling local officials to address the negative effects of elevated sea levels by allowing them to identify both built and biotic communities that are at risk, assess the situation, and develop mitigation strategies. The paper makes use of a case study of Daytona Beach, Florida, to examine the impacts of storm surge.

A GIS model, produced for south Florida integrating land use and elevation data to illustrate locations that lie below five feet, reveals that heavily populated urban areas in Miami‐Dade County could be inundated during extreme high tide and storm surge events. The GIS also indicates that much of the Florida Keys has elevations below five feet and is at risk of flooding if sea levels rise at projected rates.

The case study of Daytona Beach, Florida, can be replicated at other coastal locations by using GIS to assimilate spatial data and generate meaningful graphic models to be interpreted by those responsible for minimizing the risks from rising sea levels.