GIS Platform Research Articles

Атласная информационная система «Региональные столицы Юга Европейской России»

Regional capitals are an important category of cities in the South of European Russia, where more than a quarter (25.6 %) of the population of the macroregion lives and a significant demographic potential of the region is concentrated. The south of European Russia includes regions with natural population growth which are rare for modern Russia, regions and capitals with high rates of migration growth, as well as territories with an unfavorable demographic situation. To study territories with such a differentiated multidimensional demographic situation, geoinformation technologies were used to consolidate statistical data from various sources, conduct spatial analysis, model and visualize the processes under study. The realization of this request is possible with the use of atlas information systems (AIS), which are actively used in various subject areas, including the study of socio-economic and demographic processes. As part of the research, we have developed an atlas information system “Regional Capitals of the South of European Russia”, consisting of 2 main blocks: a structural block includes a basic GIS platform, a cartographic framework, a geodata database and a modeling and visualization unit responsible for the preparation of cartographic and visual models. AIS contains 6 thematic sections: ethnodemographic and migration processes (“Population size”, “Demographic indicators”, “Migration indicators”, “Ethnic structure of the population”), “Covid-19” (contains indicators for the sick, deceased, cured of coronavirus infection, natural population growth), “Big Data (Big Data)” consolidating indicators on the real estate market and the urban environment quality index as important factors in the formation of the demographic and migration situation. This makes it possible to conduct modeling, thematic mapping, creation of various visual plots for comprehensive complex spatial analysis. It allows to increase the level of analytics in the process of making economically determined management decisions in the regional capitals of Southern European Russia. Additionally, the possibility of integrating AIS with Web services is described.

Climate web GIS platform for research of climate processes and responses to them: Potential and prospects

Climate web GIS platform for research of climate processes and responses to them: Potential and prospects

Геоинформационный мониторинг и моделирование процессов иммиграции студентов в Россию

The article presents the experience of developing geoinformation monitoring of foreign student immigration to Russia. A conceptual scheme of monitoring is proposed, its basic structures and principles of functioning are considered. It is proved that the use of geoinformation monitoring makes it possible to process large amounts of information, form databases, and perform qualitative evaluation and analytical procedures the aim of which is optimizing of management activity. The monitoring system is developed on the basis of the ArcGIS GIS platform and includes three main modules: organizational, visualization, expert-analytical, each of which represents certain functions. The central place of the article is devoted to examples of modeling processes and visualization of data characterizing foreign student immigration. According to the authors, the methods of cartographic anamorphic images and ring maps provide the greatest visibility. The possibilities of the centrographic method for calculating the center of gravity of foreign student immigration across Russia are demonstrated. The moving of the all-Russian center of gravity from Tatarstan to the southwest was revealed, which reflects a decrease in interest in Siberian scientific and educational centers and proves an increasing attractiveness of Southern European ones. Preliminary results have been obtained on the current state and transformation of the educational immigration space in Russia, the main feature of which is strong polarization. The uneven distribution of foreign students by region is obvious. The traditional centers of attraction are the capital territories and ancient university centers. At the same time, there is an activation of peripheral regional universities, increasing the recruitment of foreign students, increasing the status of the regions in which they are located. An important factor in choosing a university, along with the image, is the positional factor reflecting the influence of the location of the place of study in Russia.

Automatic update method of GIS platform drawing model based on machine learning

Aiming at the problem that the number of data bytes in the traditional automatic update technology of GIS platform is small, a method of automatic update of GIS platform graph model based on machine learning is studied. Firstly, the data of the GIS platform model is convolved by the iso-linear feature detection operator in the automatic updating technology of the GIS platform model, and the calculated data of the GIS platform model is expressed as spatial data. A reasonable updating criterion is established, the spatial relationship of GSI data is reconstructed by the measure of updating criterion, the data vector of GIS platform model updated within the updating time range is calculated, and the regional data elements in the space are constantly changed to complete the data updating of GIS platform model. The experimental results show that compared with the automatic updating method of GIS platform model, the proposed method can update more data bytes with the same number of data bytes.

IGiS FOR MANAGING CITIES SMARTLY – URBAN GEOINFORMATICS

Abstract. A city is a geographic entity and should be efficiently analysed and optimised through the use of geo-spatial technology. The certification for a city to be ‘Smart’ is measured on the basis of the liveable index, adequacy of water supply, assured supply of electricity, proper sanitation and solid waste management, efficient urban mobility, public transport, affordable housing, robust information technology connectivity, transparent and good governance, safety and security of citizens, modernised health and education infrastructure and citizen participation which will lead to sustainable development. Smart Cities require a perfect balancing of modernisation of city infrastructure and leveraging technology. Smart cities require Geo-smart mapping and visualization capabilities with applications for protecting groundwater resources, locating schools and health centres, locating garbage dumps and toilets, designing bus routes. The indigenously developed integrated platform of GIS, Image Processing, Photogrammetry and CAD, called IGiS has been leveraged by Scanpoint Geomatics Limited, Ahmedabad (SGL), India for implementing the Enterprise GIS for 7 smart cities in India. A centralised geo spatial database with a standard data model compliant set of maps/layers has been created for each city. The spatial layers are derived from 30cm resolution satellite data. Point data (locational information) is generated using DGPS surveys. The city assets are geographically mapped at a scale of 1:2000 and organised in a spatial database. Inputs required for operations and maintenance of every utility/facility are geo tagged and stored in the database. Web & Mobile GIS applications & Citizen portal are developed using the indigenous platform. Integration with other e-governance applications and spatial layer requirements of the Integrated Command and Control Centre are supported through RestAPI & OGC compliant web services. SGL’s Mobile GIS framework named Qpad comes handy for spatial data verification. IoT devices are used to gain insights for real-time handling of critical situations or emergencies. Having laid the foundation for driving smart cities in terms of the spatial database at a scale of 1:2000, the stage is set to look forward to the results. Plugging revenue leakages, better traffic management, information at a click during peak of the Corona pandemic, effective usage of open spaces and barren areas, planning the utility requirements by the corporation to accommodate for the urban explosion is the kind of harvest that is anticipated with abated breath. This paper demonstrates the suitability and capability of the indigenously developed common platform for image processing and GIS (IGiS Enterprise Suite) in building Smart City Applications and quantifying the results.

Frequency ratio application for mapping flood susceptibility in Welang Watershed, East Java

Flood is one of the disaster threats downstream of Welang river, Pasuruan. A flood susceptibility map is needed to anticipate floods disasters. This research aimed to map flood Susceptibility in the Welang watershed using a Geographical Information System. In determining flood hazard, the Frequency Ratio (FR) approach was used. Flood locations were identified from the interpretation of field survey data as training data and model validation. The data were represented in a Digital Elevation Model (DEM) map, geological data, land use, river data, and Landsat Satellite Imagery and processed into a spatial database on the GIS platform. The factors that caused flooding consisted of Flood inventory, slope, Elevation, Topographic Wetness Index (TWI), Standardized Precipitation Index (SPI), Flow Accumulation, Distance to the river, River Density, Rainfall, Vegetation Index (NDVI), and Landuse. The map results with acceptable accuracy showed that the FR model gained an Area Under Curve (AUC) value of 90%, and the incidence for the Area Under Curve ( AUC ) was 93%. It is known that 1% of the flood-prone area is very high. The local Government can use the research to minimize the risk of flooding in the Welang watershed.

A Technological System for Post-Earthquake Damage Scenarios Based on the Monitoring by Means of an Urban Seismic Network.

A technological system capable of automatically producing damage scenarios at an urban scale, as soon as an earthquake occurs, can help the decision-makers in planning the first post-disaster response, i.e., to prioritize the field activities for checking damage, making a building safe, and supporting rescue and recovery. This system can be even more useful when it works on densely populated areas, as well as on historic urban centers. In the paper, we propose a processing chain on a GIS platform to generate post-earthquake damage scenarios, which are based: (1) on the near real-time processing of the ground motion, that is recorded in different sites by MEMS accelerometric sensor network in order to take into account the local effects, and (2) the current structural characteristics of the built heritage, that can be managed through an information system from the local public administration authority. In the framework of the EU-funded H2020-ARCH project, the components of the system have been developed for the historic area of Camerino (Italy). Currently, some experimental fragility curves in the scientific literature, which are based on the damage observations after Italian earthquakes, are implemented in the platform. These curves allow relating the acceleration peaks obtained by the recordings of the ground motion with the probability to reach a certain damage level, depending on the structural typology. An operational test of the system was performed with reference to an ML3.3 earthquake that occurred 13 km south of Camerino. Acceleration peaks between 1.3 and 4.5 cm/s2 were recorded by the network, and probabilities lower than 35% for negligible damage (and then about 10% for moderate damage) were calculated for the historical buildings given this low-energy earthquake.

Integrated Decision Support System for Pluvial Flood-Resilient Spatial Planning in Urban Areas

Flood-resilient spatial planning in urban areas involves designing and implementing structural and nonstructural measures. For the latter, urban planners apply a precautionary principle, which is normally not grounded in the actual performance of the urban drainage system (UDS). This approach, however, fails during weather extremes with heavy precipitation. This paper presents a new concept for reducing pluvial flood risks in the urban planning process. The novelty of the developed planning support system named Extreme Weather Layer (EWL) is that it creates dynamic interlinkages between land developments, the performance of UDS, and other factors that contribute to flood risk. The EWL is built on the digital twin of the existing UDS and delivers an easy-to-use concept, where the end user can analyze hydraulic modelling results interlinked with climate scenarios using the GIS platform. This allows planning specialists to consider land use and soil types in the urban environment to simulate the response of the storm water system and the catchments to different rainfall events. This proposed approach was piloted in Haapsalu (Estonia) and Söderhamn (Sweden). The resulting planning support system, which performs as a set of layers within municipalities’ GIS, allows decision makers to understand and predict the impact of various spatial planning decisions on the pluvial flood risk.

Retraction Note: Stability of slope rainfall condition based on GIS and nutrition intervention of football training

This paper mainly studies the problems related to the evaluation of high slope intelligent area under rainfall conditions and, through the unified design method, saturation unsaturation theory, marginal equilibrium neural network theory, and GIS, based on Fengjie area, studies the rainfall conditions and the evaluation of high and low slope stability in intelligent area. This paper provides a positive research and practice way for GIS intelligence and is establishing an intelligent regional evaluation system based on GIS platform. As the goal of high slope stability research under rainfall conditions, the intelligent regional evaluation map based on slope stability can become an important basis for Fengjie region to prevent and control global disasters. Although football training is scientific, scientific and reasonable use of nutrition intervention measures can improve the training efficiency of football players, increase the time of athletes to bear the extreme sports load, delay the fatigue of sports, and ultimately improve the performance of athletes. This study is based on the investigation and field test of nutritional intervention of football players and puts forward and proves the practical basis and empirical effect of nutritional supplements in football players. The purpose is to provide an effective basis for supporting football players’ nutritional supplements through targeted case studies. According to the research of GIS, it is applied to the slope rainfall and football training nutrition intervention, which can effectively improve the slope rainfall and football training nutrition intervention.

DEVELOPMENT OF THE IM4MANILABAY MAPABLE WEB PORTAL

Abstract. Products and outputs for water quality monitoring are made available in the IM4ManilaBay MapABLE Web Portal, a web-based GIS platform that serves as a repository of processed maps for Manila Bay and linked systems. The Portal is also linked with the MASDAN mobile application that has been developed to allow the public to report different environmental issues. The web development involved the utilization of geospatial content management system, spatial database system, operating systems, programming, and style language. Services included frontend and backend development. The Web Portal serves as a repository for all outputs derived for water quality monitoring. It contains processed results, technical overview on the developed models and tools, historical data viewing and use of basic geoprocessing tools, and viewing of reported incidents from the MASDAN app. It is expected that the Web Portal will contribute significantly in the efforts of communities and environmental agencies to implement policies for sustainable development and management of Manila Bay and its watershed.

A Multiscale Approach for the Seismic Vulnerability Assessment of Historical Centres in Masonry Building Aggregates: Cognitive Approach and Interdisciplinary Perspectives

ABSTRACT The seismic vulnerability assessment of masonry building aggregates involves different variables, many of which are of uncertain evaluation. To this aim, in this paper, a holistic multiscale approach for their seismic vulnerability assessment is presented. The methodology concerns an integrated knowledge-based approach combining different strategies through interdisciplinary perspectives. The procedure joins several aspects, involving two scales of interest, the urban and the aggregate level. Every phase is related to the acquisition of different information, the selection of alternative vulnerability methodologies, the adoption of different informative management systems. GIS and BIM platforms have been used to gather the data adopted in the vulnerability assessment; their collection is still useful for wider managements for the preservation of the historical centres’ heritage. At each level, the provided information allowed the definition of the seismic vulnerability assessment through coherent methodologies. The in-depth analyses regarding the cognitive acquisitions were followed by more detailed procedures for the vulnerability assessment. The multiscale approach has been finally applied to the city of Scarperia, founded a few kilometres from Florence during the Medieval Age and characterized by a medium seismicity. The outcomes of the research denounce the differences within the considered levels, highlighting the importance of the conducted improvements.

Spatial variation of heavy metal contamination in roadside soil from hilly terrain of the north-western Himalaya

ABSTRACT Fuel-based vehicular emission has been recognised as a potential contributor to the declining air quality and heavy metal contamination of soils. The present study investigated heavy metal contamination in roadside soil along national highway (NH)-21 and a link road in hilly terrain of the Kullu district, north-western Himalaya, India. The soil samples were analysed for pH, EC and heavy metals, viz., Zn, Fe, Mn, Cu, Pb, Ar and Cr. The heavy metal concentrations were evaluated as per the guidelines provided by competent authorities. The spatial distribution of heavy metal contaminants was depicted in maps using the GIS platform. The pH of the soil was slightly acidic to neutral. The reference sites from the rural area represent the lower heavy metals contamination comparison to the locations along the highway. The heavy metal concentrations decreased with the increasing distance from the edge of the road, while their distribution and mobility were influenced by natural as well human-induced sources. The present study provides the baseline data to optimise the scale of sampling in the hilly terrains that is capable of capturing the effect of the diffuse source for efficient pollution abatement strategies.

Landslide Hazard Zonation along the MH SH-73 at Kelghar Ghat, Satara, Maharashtra

Road transportation is the most common victim of landslide in the world. The present study investigates the landslide hazard zonation along the MH SH-73 at Kelghar ghat between Medha and Mahabaleshwar hill station of Maharashtra. Remote Sensing and GIS were used for the landslide hazard zonation of this section. The ghat section was buffered 100 m on both side to define the extent of study area based on the field investigation. The study incorporated predefined important landslide causative factors, viz. slope, rainfall, relief, lithology, soil depth, soil erosion, soil texture, land use / land cover, drainage distance, drainage density, lineament distance, lineament density, aspect, temperature, landslide inventory and in this approach fifteen thematic layers were prepared in GIS platform. The weight and score were assigned to each thematic layer based on heuristic approach on their relative importance in causing landslide. Multi-criteria model in ArcGIS 10.5 software were used for the mapping landslide hazard zones and it were classified into six zones: very high (1.3 %), high (1.7 %), moderate (3.4 %), low (7.6 %) very low (8.4 %) and no risk zone (77.7 %). The final result of this research can help for proper mitigation and adaptation measures for engineers, planners and administrators for this ghat section. Keywords: GIS, Landslide Hazard Zonation, Remote Sensing, Susceptibility, Sahyadri, Kelghar.

Evaluation of data-driven model and GIS technique performance for identification of Groundwater Potential Zones: A case of Fincha Catchment, Abay Basin, Ethiopia

Study regionFincha Catchment, Abay Basin, Ethiopia. Study focusThe study evaluates the performance of the data-driven (ANN) model and GIS technique for the exploration of groundwater potential zones. Lineament density, drainage density, slope, LULC, rainfall, soil, geology, and geomorphology were used as the criteria for the delineation of groundwater potential zones. The criteria were ranked and weighted in the ANN and AHP approaches. Weighted overlay analysis in the GIS platform was used in both methods to delineate the potential zones. The accuracy of the delineated groundwater potential zones in both cases was evaluated by the ROC curve developed from the pumping rate. New hydrological insights for the regionFive and four classes of groundwater potential zones were delineated in ANN and GIS respectively. This indicates that the performance of the ANN model in delineating the groundwater potential zones was better than the GIS technique. The accuracy of the predicted potential zones was evaluated and AUC computed from the ROC curve in both methods revealed an agreement of 96 % and 91 % were made between the ground-truthing points and the ANN model and between GIS platforms respectively. The performance of the ANN was better than the GIS technique in delineating the potential zones. Finally, it is concluded that the ANN model is an effective tool for the delineation of groundwater prospective zones.

Source Sink Matching for Field Scale CCUS CO2-EOR Application in Indonesia

The carbon capture utilization and storage (CCUS) referred in this paper is limited to the use of CO2 to the enhanced oil recovery (CO2-EOR). The CCUS CO2-EOR technology can magnify oil production substantially while a consistent amount of the CO2 injected remains sequestrated in the reservoir, which is beneficial for reducing the greenhouse gas emission. Therefore, this technology is a potentially attractive win-win solution for Indonesia to meet the goal of improved energy supply and security, while also reducing CO2 emissions over the long term. The success of CCUS depends on the proper sources-sinks matching. This paper presents a systematic approach to pairing the CO2 captured from industrial activities with suitable oil fields for CO2-EOR. Inventories of CO2 sources and oil reservoirs were done through survey and data questionnaires. The process of sources-sinks matching was preceded by identifying the CO2 sources within the radius of 100 and 200 km from each oil field and clustering the fields within the same radius from each CO2 source. Each cluster is mapped on the GIS platform included existing and planning right of way for trunk pipelines. Pairing of source-sink are ranked to identify high priority development. Results of this study should be interest to project developers, policymakers, government agencies, academicians, civil society and environmental non-governmental organization in order to enable them to assess the role of CCUS CO2-EOR as a major carbon management strategy.

GIS-BASED VIEWSHED ANALYSIS ON THE CONSERVATION PLANNING OF HISTORIC TOWNS: THE CASE STUDY OF XINCHANG, SHANGHAI

Abstract. This paper discuss an application of the GIS software to analysis the visual effect from specific observation points in the historic towns. The viewshed tool in GIS platforms, including ArcGIS and QGIS, are applied in order to generate observation points and viewshed maps. Dozens of key nodes are selected in Xinchang Ancient Town, such as the protected buildings, the historic bridges, and the historic street intersections, as the observation points of viewshed analysis. The result of the analysis is to generate the viewshed map from each observation point. Subsequently, the observation points are merged and the result of the viewshed analysis of the whole ancient town is created. Based on the viewshed analysis results, the characteristics of the visual effect in the town with gentle terrain and dense building is discussed. The features of the ancient town remind elements that need attention in conservation planning, and guides the building regulation within and outside the set boarder of the protected area.

Cloud Computing and Internet of Things in the Evaluation of Ecological Environment Quality in Rural Tourist Areas in Smart Cities

With the increase of tourist environment, the real-time monitoring of ecological environment has become a concern. This study mainly discusses the application of cloud computing and Internet of things in the evaluation of ecological environment quality of rural tourism areas in a smart city. In this study, the real-time monitoring of the atmosphere, water, and meteorological data is collected through the GPRS data transmission module and then sent back to the local server by the GPRS network, and the obtained non-real-time and real-time data are used to establish the ecological monitoring database, the database analysis of its information, and get real-time data, monthly data, and longer cycle data. In the cloud GIS platform, there are multiple subnodes. The split tasks can be processed by each subnode through a map, and the results after processing can be summarized through reduce, which completes the implementation process of the whole idea of map reduce. Monitoring station management is mainly to establish monitoring stations in rural tourism areas and collect first-hand environmental monitoring data by using temperature, humidity, infrared, ultrasonic, and other sensors and cameras. The monitoring objects are the air quality, water quality, meteorology, etc. of the scenic area, mainly showing the location of monitoring stations and the placement of sensors. At the same time, an LED screen is set at the monitoring station to display the air quality data of the scenic spot. The data content is introduced into the DPSIR model, combined with social and economic data; according to the ecological health grading evaluation standard, the evaluation score and health grade are obtained and the ecological health status of rural tourism area is judged and evaluated. When the amount of data is less than 500 MB, there is little difference between the storage speed of the cloud GIS platform and single machine, but with the continuous increase of the amount of data, the storage speed of the cloud GIS platform is significantly higher than that of a single machine. This study is helpful in improving the ecological environment quality of rural tourism areas.

Large-Scale Landslide Susceptibility Mapping Using an Integrated Machine Learning Model: A Case Study in the Lvliang Mountains of China

Integration of different models may improve the performance of landslide susceptibility assessment, but few studies have tested it. The present study aims at exploring the way to integrating different models and comparing the results among integrated and individual models. Our objective is to answer this question: Will the integrated model have higher accuracy compared with individual model? The Lvliang mountains area, a landslide-prone area in China, was taken as the study area, and ten factors were considered in the influencing factors system. Three basic machine learning models (the back propagation (BP), support vector machine (SVM), and random forest (RF) models) were integrated by an objective function where the weight coefficients among different models were computed by the gray wolf optimization (GWO) algorithm. 80 and 20% of the landslide data were randomly selected as the training and testing samples, respectively, and different landslide susceptibility maps were generated based on the GIS platform. The results illustrated that the accuracy expressed by the area under the receiver operating characteristic curve (AUC) of the BP-SVM-RF integrated model was the highest (0.7898), which was better than that of the BP (0.6929), SVM (0.6582), RF (0.7258), BP-SVM (0.7360), BP-RF (0.7569), and SVM-RF models (0.7298). The experimental results authenticated the effectiveness of the BP-SVM-RF method, which can be a reliable model for the regional landslide susceptibility assessment of the study area. Moreover, the proposed procedure can be a good option to integrate different models to seek an “optimal” result.

RETRACTED ARTICLE: Prediction of mountain landslide susceptibility and influencing factors of green landscape design on both sides of roads

By collecting basic data about the geological environment of the study area, this article introduces the geological environment of the study area in mountainous areas. Use data model, logistic regression model, and spatial logistic regression model to estimate the landslide susceptibility of the area and divide the research area. Based on the GIS platform and the regression model data model, seven evaluation factors were selected-altitude, rock characteristics, distance to the river, distance to the road, distance to the fault zone, vegetation and rainfall, etc. Using spatial logistic regression model and information model to carry out landslide risk prediction and regional assessment in this area, it shows that the development of mountain landslide disasters in the study area has considerable spatial effects. The areas with extremely high and high susceptibility to mountain landslides are mainly distributed in the study area. The southwest region is mainly distributed along rivers, both sides of roads, and near fault zones; most of the low- and medium-risk areas are scattered in higher altitude areas, with large slopes, low human activities, and high vegetation coverage. At the same time, the issue of green landscape setting on both sides of the highway is also mentioned. The green landscape system is composed of the highway itself and the attached green spaces on both sides. At present, many studies on the landscape system of the two roads are focused on improving the engineering technology of the main body of the highway and improving the landscape effect. The attached green space on both sides of the road is taken as the main focus of the research. The green space on both sides of the road is an important part of the ecological zone and plays an irreplaceable ecological role. Therefore, this paper conducts a more in-depth study on the use of disaster-prone prediction technology to study landslides and the current green landscape design on both sides of the road.

3D GIS Platform for Flood Wargame: A Case Study of New Taipei City, Taiwan

Wargames have been promoted by local governments in Taiwan since 2009, as they require far fewer resources than full-scale exercises. Previously, wargame scenarios were divulged before their launch, enabling participants to formulate response plans in advance, which made them ineffective. Currently, wargames in which scenarios are not shared in advance require a common platform for debriefing players regarding their planned actions. Owing to its geographical location, Taiwan is prone to significant flooding disasters. To assist in making countermeasures, we created a 3D GIS-based Flood Wargame Assistance Platform (FWGAP) for conducting rapid spatial analyses. Flooded areas are estimated in the FWGAP in three ways: (1) using a digital terrain model (DTM) with designated flood center and depth; (2) applying historical flooding spots; and (3) potential flooding maps. A FWGAP can estimate affected and vulnerable populations and has functions for locating resources such as shelters and hospitals near the flooded areas. Its integrated use of closed-circuit televisions, Google Street View maps, and 3D buildings to display flooded areas realistically ensures greater fidelity. This study reports on the city- and the district-level applications of the FWGAP. The results of the survey undertaken indicates that 56% of the participants agreed that the FWGAP enables disaster relief resources to be located on a GIS map. About half of the participants believed that a no-script flooding wargame using a FWGAP could help to identify problems in standard operation procedures and promote greater horizontal coordination among departments.