Geographic Information System Database Research Articles

Elements’ Content in Stream Sediment and Wildfire Ash of Suburban Areas in West Attica (Greece)

The composition of sediments and other materials occurring in streams, geochemical processes within the drainage basin, and various land uses are among the main factors influencing stream water composition. Stream sediment and wildfire ash samples were gathered from the area studied. The applied methodology consists of aqua regia and Diethylene-Triamine-Penta-Acetic acid (DTPA) chemical extraction; Cation Exchange Capacity (CEC), pH, and soil organic matter (OM) determination; a Geographic Information System (GIS) database; factor analysis; and determination of the contamination factor (CF) for the assessment of contamination degree. This study aimed to evaluate the elements’ content in stream sediments of Kineta and Nea Peramos areas (West Attica, Greece) and investigate any relationship between elements (aqua regia and DTPA extracted) in stream sediment and ash in wildfire and flood-impacted areas. The stream sediments’ properties, the bioavailable forms of copper (Cu), iron (Fe), manganese (Mn) and zinc (Zn), and the total content of other potentially toxic elements in wildfire ash samples, are discussed. This research estimated moderate contamination for FeDTPA, MnDTPA and ZnDTPA in stream sediments of the study area. Contamination for CuDTPA and moderate contamination for ZnDTPA in the stream sediments of the Nea Peramos area was recorded. Factor analysis results suggested that the contents of FeDTPA, MnDTPA, CuDTPA and ZnDTPA in the study area’s stream sediments may affect the chemistry of stream water.

Associations between Children's Physical Activity and Neighborhood Environments Using GIS: A Secondary Analysis from a Systematic Scoping Review.

Regular participation in physical activity is essential for children’s physical, mental, and cognitive health. Neighborhood environments may be especially important for children who are more likely to spend time in the environment proximal to home. This article provides an update of evidence for associations between children’s physical activity behaviors and objectively assessed environmental characteristics derived using geographical information system (GIS)-based approaches. A systematic scoping review yielded 36 relevant articles of varying study quality. Most studies were conducted in the USA. Findings highlight the need for neighborhoods that are well connected, have higher population densities, and have a variety of destinations in the proximal neighborhood to support children’s physical activity behaviors. A shorter distance to school and safe traffic environments were significant factors in supporting children’s active travel behaviors. Areas for improvement in the field include the consideration of neighborhood self-selection bias, including more diverse population groups, ground-truthing GIS databases, utilising data-driven approaches to derive environmental indices, and improving the temporal alignment of GIS datasets with behavioral outcomes.

Methodology for Assessing the Transport Accessibility of Capital Objects in a Megacity Based on Geoinformation Data

Purpose: to present the author's methodology and the test results for calculating integral indicators of transport accessibility on the basis of weighted normalized private indicators for three housing estates in Moscow.Methods: the study is based on the application of methods for collecting factual material, its processing, systematic, comparative historical and structural-functional analysis, which were supplemented by multivariate analysis of secondary information using content analysis of existing methods for calculating indicators of transport accessibility of capital objects. The results and conclusions of the research are based on the use of the author's methodology for calculating integral indicators of transport accessibility based on weighted normalized private indicators for three housing estates in Moscow. The analysis of a possible set of criteria for assessing transport accessibility of housing estates in Moscow metropolis was carried out on the basis of the use of a geographic information system database GIS NextGIS QGIS.Results: a review of methodological approaches to the calculation of objective quantitative indicators characterizing the transport accessibility of capital objects is carried out; the author's methodology for calculating the integral indicators of the transport accessibility of residential complexes in Moscow is presented and tested on the basis of weighted normalized private criteria / indicators. The use of the authors’ methodology for calculating integral indicators of transport accessibility based on weighted normalized private criteria / indicators made it possible to calculate the values of indicators of transport accessibility for three housing estates in Moscow, calculate an integrated score for a set of transport accessibility criteria for each housing estate, to give a comparative quantitative assessment of their transport accessibility, to conduct a rating of housing estates in terms of their transport accessibility.Conclusions and Relevance: the presented results of approbation of the author's methodology for calculating the integral indicators of transport accessibility for housing estates in Moscow allow to conduct a comparative and dynamic analysis of housing estates (or larger units) transport accessibility. The results of such an analysis can be applied in order to develop programs for transport infrastructure development of the megacity as a whole, its certain districts and city parts, as well as to assess such programs efciency. The authors see the directions for future research in the defnition and calculation of indicators based on the city dwellers perception of the transport accessibility

Изучение почвенного покрова Чингирлауского района Западно-Казахстанской области Республики Казахстан на основе применения ГИС-технологий

Rational use and protection of soils in market conditions requires adequate application of new scientific and methodological approaches. One of such systems-analytical methods of organizing a soil cadastre is the combination of traditional ground-based methods with geographic information systems (GIS) technologies based on the widespread use of aerospace images of high resolutions. The totality of information necessary for mapping soil cover structures and their quantitative assessment is described in GIS databases. Data integration is implemented through a spatial and attributive component in the form of: the results of topographic and thematic maps. At the same time, the creation of attributive GIS databases involves the digitization of thematic maps linked in a single cartographic projection (which was a topographic map at a scale of 1:50,000). As results of the research, digital soil maps for the Chingirlau district of the West Kazakhstan region were created on the basis of GIS technologies, using the ArcGIS software products. It was established that within the limits of the Chingirlau district of the West Kazakhstan region, dark chestnut soils in combination with various soil combinations pre-dominate in the structure of the soil cover. They are formed on loess-like loams in the conditions of the dry steppe zone with a non-leaching type of water regime under fescue-grass, forb-grass-wormwood, meadowsweet-grass with wormwood plant communities. To improve the quality of generalized maps (district, regional, etc.), it is necessary to create objective automated methods for generalizing maps in a digital environment. A method for compiling a digital soil map using the ArcGIS soft-ware product, accessible to a wide range of GIS users, has been developed. To compile soil maps, it is possible to use any scanned cartographic bases, photoplans, and other raster materials. Based on the developed methodology, a large-scale soil map of the Chingirlau district of the West Kazakhstan region was created on the basis of soil maps of rural districts made using GIS technologies.

Radial Casting Algorithm for Extraction of Man-Made Features from High Resolution Digital Satellite Imagery

The extraction of man-made features from high resolution digital satellite imagery is an important step to underpin management of geo-information in any country. Man-made features and buildings in particular are required for various applications such as urban planning, creation of geographic information systems databases and generation of urban models. Manual extraction processes are expensive, labor intensive, need well trained personnel and cannot cope with high demand of geo-information and changing environment. This paper, presents a Radial Casting Algorithm (RCA) used to extract buildings from high resolution digital satellite imagery. The algorithm measures only a single point on an approximate center of the building on an image and the fine measurement is automatically determined. The algorithm is a modification from original snakes model developed by Kass et al whereby the external constraints energy term is removed which negatively affects the convergence properties of the contour to provide the ability of the snake contour to cope with high variability of buildings on an image. The algorithm was tested on three areas of different environment. The quantitative measures were employed to evaluate the accuracy, efficiency and capability of the algorithm which shows that the time of extracting a single building was reduced by 32 percent, the extraction rate was 92 percent and the Area coverage of extracted polygons was 98 percent.

Sistem Informasi Geografis Pada Kelompok Wanita Tani Berbasis Data Object

Geographical Information System technology (GIS) uses a document database (JSON) as an object that can be applied to geographic information systems using object data in the group of women farmers (KWT) in Lampung Province. The distribution of KWT in Lampung Province can be done using a geographic information system. The use of relational databases can be replaced by using the document database as a database on the distribution of KWT in Lampung Province. There are 3 data markers for example KWT in Lampung province using google maps. By using a JSON document as a document database as an object it is possible to serve as a geographic information system database.

A Multi-Stage Approach Combining Very High-Resolution Satellite Image, GIS Database and Post-Classification Modification Rules for Habitat Mapping in Hong Kong

Identification and mapping of various habitats with sufficient spatial details are essential to support environmental planning and management. Considering the complexity of diverse habitat types in a heterogeneous landscape, a context-dependent mapping framework is expected to be superior to traditional classification techniques. With the aim to produce a territory-wide habitat map in Hong Kong, a three-stage mapping procedure was developed to identify 21 habitats by combining very-high-resolution satellite images, geographic information system (GIS) layers and knowledge-based modification rules. In stage 1, several classification methods were tested to produce initial results with 11 classes from a WorldView-2/3 image mosaic using a combination of spectral, textural, topographic and geometric variables. In stage 2, modification rules were applied to refine the classification results based on contextual properties and ancillary data layers. Evaluation of the classified maps showed that the highest overall accuracy was obtained from pixel-based random forest classification (84.0%) and the implementation of modification rules led to an average 8.8% increase in the accuracy. In stage 3, the classification scheme was expanded to all 21 habitats through the adoption of additional rules. The resulting habitat map achieved >80% accuracy for most of the evaluated classes and >70% accuracy for the mixed habitats when validated using field-collected points. The proposed mapping framework was able to utilize different information sources in a systematic and controllable workflow. While transitional mixed habitats were mapped using class membership probabilities and a soft classification method, the identification of other habitats benefited from the hybrid use of remote-sensing classification and ancillary data. Adaptive implementation of classification procedures, development of appropriate rules and combination with spatial data are recommended when producing an integrated and accurate map.

Estimating global oilfield-specific flaring with uncertainty using a detailed geographic database of oil and gas fields

Associated gas flaring during crude oil production is an important contributor to global warming. Satellite technology has made global flaring monitoring possible with high spatial resolution. In this study, we construct a granular database to geographically match global oil and gas fields with remote sensing flaring data from the Visible Infrared Imaging Radiometer Suite from 2012 to 2019. The geographic information system database contains over 50 000 oil and gas fields and around 4700 infrastructure sites (e.g. refineries, terminals) in 51 countries and regions, representing 96% of global oil production and 89% of natural gas production. Over 2900 fields and 140 infrastructure sites in 47 countries contain matching flares. The annual matched flare volume covers 89%–92% of the satellite-estimated flaring volume of these countries and 85%–87% of total worldwide volume detected by the satellite. In 2019, a set of 263 ‘high-flare’ fields (which flare more than 0.1 billion cubic meters per year) account for 67% of the total matched satellite-estimated volume. These fields are mainly concentrated in the Persian Gulf, West and East Siberia, Eastern Venezuela Basin, Permian and Williston Basins in the United States, the Gulf of Mexico, and West and North Africa. Accounting for asymmetric instrument uncertainty suggests that country-level flaring rates are accurate to within −8% to +29%, the global average within 1%.

Fractional Linear Regression Equation in Agricultural Disaster Assessment Model Based on Geographic Information System Analysis Technology

Abstract This article combines geographic information system (GIS) technology and database technology to analyse agricultural, natural disasters. The article uses a fractional linear regression equation to define the comprehensive intensity grading standard of the disaster-causing factors of torrential rain. At the same time, we use GIS to superimpose the agricultural vulnerability index into the storm disaster risk zoning to obtain the degree of agricultural impact under different levels of risk. At the end of the thesis, the model is applied to actual case analysis to verify the effectiveness of the algorithm model.

Road Identification Through Efficient Edge Segmentation Based on Morphological Operations

Road identification from high-precision images is important to programmed mapping, urban planning, and updating geographic information system (GIS) databases. Manual identification of roads is slow, costly, and prone to errors. Therefore, it is a hot topic among remote sensing experts to develop programmed techniques for road identification from satellite images. The main challenge lies in the variation of width and surface contents between roads. This paper presents a road identification and extraction strategy for satellite images. The strategy, denoted as ESMIRMO, recognizes roads in satellite images through edge segmentation, using morphological operations. Specifically, morphological operations were employed to enhance the quality of the original image, laying a good basis for accurate road detection. Next, edge segmentation was adopted to detect the road in the original image accurately. After that, the proposed strategy was compared with traditional methods. The comparison shows that our strategy could identify roads from satellite images more accurately than traditional methods, and overcome many of their limitations. Overall, our strategy manages to enhance the quality of satellite images, pinpoint roads in the enhanced images, and provide drivers and repairers with real-time information on road conditions.

Development of a Cyberinfrastructure for Assessment of the Lower Rio Grande Valley North and Central Watersheds Characteristics

Lower Laguna Madre (LLM) is designated as an impaired waterway for high concentrations of bacteria and low dissolved oxygen. The main freshwater sources to the LLM flow from the North and Central waterways which are composed of three main waterways: Hidalgo/Willacy Main Drain (HWMD), Raymondville Drain (RVD), and International Boundary & Water Commission North Floodway (IBWCNF) that are not fully characterized. The objective of this study is to perform a watershed characterization to determine the potential pollution sources of each watershed. The watershed characterization was achieved by developing a cyberinfrastructure, and it collects a wide inventory of data to identify which one of the three waterways has a major contribution to the LLM. Cyberinfrastructure development using the Geographic Information System (GIS) database helped to comprehend the major characteristics of each area contributing to the watershed supported by the analysis of the data collected. The watershed characterization process started with delineating the boundaries of each watershed. Then, geospatial and non-geospatial data were added to the cyberinfrastructure from numerous sources including point and nonpoint sources of pollution. Results showed that HWMD and IBWCNF watersheds were found to have a higher contribution to the water impairments to the LLM. HWMD and IBWCNF comprise the potential major sources of water quality impairments such as cultivated crops, urbanized areas, on-site sewage facilities, colonias, and wastewater effluents.

Effect of various interlayers on the performance of cesium formamidinium lead mixed halide (CsFAPbX3) – Formamidinium tin iodide (FASnI3) two-terminal tandem solar cell

In this work, 2D-Sentaurus TCAD has been used to investigate two terminal all-perovskite tandem solar cells (TSCs) having the structure Glass | ITO | PEDOT:PSS | CsFAPbX3| PCBM | Interlayer | PEDOT:PSS | FASnI3| PCBM | Ag. The thicknesses of active perovskite layers for both the bottom (FASnI3) and top (CsFAPbX3) sub-cells have been optimized for maximizing the device efficiency. Various metals (Ag, Au, Ti, Al, etc.), transparent conducting oxides (TCOs) such as ITO, FTO, and ZnO, and a polymer (PFN-Br) have been investigated for the interlayer. The dependence of solar cell performance on the thicknesses and optical constants of these interlayers, and on the angle of light incidence (θ) have been analyzed using the integrated optical generation rates. The metal-interlayer TSCs show a monotonic decrease in efficiency with increasing interlayer thickness. A 1 nm Ti-interlayer, for example, gave an efficiency of 12.9% at normal incidence. On the other hand, ITO-interlayer TSC gave its highest efficiency at an optimum interlayer thickness of 5 nm. While some of the metal-interlayer TSCs have been found to generate power for θ values up to 80°, those with more commonly used interlayers such as Ag and Au showed poor angle dependence. TSCs with all the TCO- as well as the PFN-Br- interlayers gave their highest efficiencies at oblique angles of incidence rather than at normal incidence. A peak efficiency of 12.55% was obtained at an angle of 50° for the TSC with this interlayer. To estimate the maximum amount of energy that these TSCs can generate in an year, the energy densities generated per day (Eday) were integrated and compared using the solar irradiation and temperature data from Photovoltaic Geographical Information System (PVGIS-SARAH, European Commission) database. Among all the interlayers studied here, Ti and ITO have been found to be the best metal and TCO respectively. For example, despite generating the highest short circuit current density at normal incidence, the Ag-interlayer TSC generates 79% and 82% lower energy density than these TSCs on the longest day of the year.

INFRA-BIM FOR BUSINESS PROCESSES’ MANAGEMENT IN ROAD CONSTRUCTION AND OPERATION

Introduction: The article addresses the business processes of the construction and operation of linear road sections. In the course of the study, we analyzed the geographic information system (GIS) of Avtodor company (developer: Indor-Soft, Tomsk) and its use in the operation and maintenance of transport infrastructure facilities at such road sections. In particular, we studied the construction of the Far West Krasnodar Bypass (FWKB), which is part of the North-South transport corridor, and its implementation by means of InfraBIM modeling. Purpose of the study: We aimed to describe the structured GIS database of Avtodor company by connecting various InfraBIM tools for the purposes of data generation and road model update. Methods: Analyzing the GIS of Avtodor company when using an InfraBIM model of road infrastructure, we studied the following: use of GIS features at the facility; asynchronous editing and selection of data without access to the Internet; database update. Results: InfraBIM models of linear road sections, developed in the implementation of such projects as the FWKB, make it possible to optimize time and save money when planning and introducing measures during the operation of transport infrastructure facilities.

A new GIS database documenting the prevalence of U.S. air service development incentives

New air service routes are viewed as an important driver of local and regional economic growth by some communities. In the United States (U.S.), this recognition has led to an increase in: (1) the number of airports offering air service incentive agreements, and (2) the frequency with which new agreements are initiated. Despite the recognized economic importance of air service incentives, and an identified need for a database categorizing U.S. air service incentives, no such database existed. This project fills that gap by compiling a database for all 382 U.S. commercial airports included in the Federal Aviation Administration’s 2017 Terminal Area Forecast and makes it publicly available to other researchers via an online geographic information system (GIS) tool. In this paper, we describe this new database, provide a descriptive analysis of air service incentive agreements in the U.S., and identify topics future research can investigate using our database. It is our hope that this database will serve as a foundation on which to build new research related to air service incentive programs.

Particularities of Forest Dynamics Using Higuchi Dimension. Parâng Mountains as a Case Study

The legal or illegal losses and the natural disturbance regime of forest areas in Romania generate major imbalances in territorial systems. The main purpose of the current research was to examine the dynamics of the complexity of forests under the influence of forest loss but also to compare the applicability of Higuchi dimension. In this study, two fractal algorithms, Higuchi 1D (H1D) and Higuchi 2D (H2D), were used to determine qualitative and quantitative aspects based on images obtained from a Geographic Information System (GIS) database. The H1D analysis showed that the impact of forest loss has led to increased fragmentation of the forests, generating a continuous increase in the complexity of forest areas. The H2D analysis identified the complexity of forest morphology by the relationship between each pixel and the neighboring pixels from analyzed images, which allowed us to highlight the local characteristics of the forest loss. The H1D and H2D methods showed that they have the speed and simplicity required for forest loss analysis. Using this methodology complementary to GIS analyses, a relevant status of how forest loss occurred and their impact on tree-cover dynamics was obtained.

Exploring Plantation Development and Land Cover Changes in the Meme-Mungo Corridor of Cameroon

There is an apparent nexus between the development of plantations and changes in landcover. The Meme-Mungo Corridor is an example par excellence of a tropical plantation corridor in Cameroon which has witnessed significant expansion in tropical plantations of cocoa, banana, rubber and oil palm, among others. This paper analyzes the connection between land cover changes and plantation development over a 42-year period (1960 and 2012). A total of 100 households were sampled using the systematic sampling technique. Furthermore, multispectral data, obtained from the Global Land Cover Facility (GLCF, 2005) were used in the classification of the study area. These images were processed using Geographic Information System (GIS) and Remote Sensing (RS) software and further compiled into a GIS database using ESRI ArcGIS software. The results showed that between 1960 and 2012, a more than 50% increase in the surface area of plantation crops was registered, leadingto a corresponding change in the land cover situation. Based on this, the study probed into the implications of further plantation development on land cover; further land cover changes could be attributed to the extension of plantations. This paperrecommends among others, the need for intensive agriculture to be encouraged so as to ensure an increase in agricultural output against the backdrop of a decline in agricultural space. Furthermore, augmenting agro-product value chains will stem the loss of agro-produce due to perishability. This will contribute to regulate extensive plantation development in the area.

Estimation of Determinants of Farmland Abandonment and Its Data Problems

Abandoned farmland is particularly problematic in developed countries where agriculture has a comparative disadvantage in terms of effective use of land resources invested over time. While many studies have estimated the causes of these problems, few have discussed in detail the impact of data characteristics and accuracy on the estimation results. In this study, issues related to the underlying data and the estimation of the determinants of farmland abandonment were examined. Most previous studies on farmland abandonment in Japan have used census data as the basis of their analyses. However, census data are recorded subjectively by farmers. To address this, surveys of abandoned farmland are being conducted by a third party, and the results are compiled into a geographic information system (GIS) database. Two types of datasets (subjective census data and objective GIS data) were examined for their estimation performance. Although the two sets of data are correlated, there are considerable differences between them. Subjective variables are compatible with subjective data, and objective variables are compatible with objective data (meaning that parameters are easily identified). Original data for analysis, such as policy variables, are compatible with objective data. In policy evaluation research, attention should be paid to objective data collection.

The impact of Zika in Minas Gerais, Brazil: epidemiological profile and spatial diffusion of the disease, 2015-2019

Objective: To overview the epidemiological profile for Zika in MG and map its spatial diffusion from 2015 (onset of the outbreak) to 2019. Method: this is a descriptive observational study based on three secondary databases: Disease Notification System (SINAN), the Brazilian Institute of Geography and Statistics (IBGE) and the Health Surveillance Secretariat of Minas Gerais State (SVS-SES/MG). The spatial diffusion of the confirmed cases was georeferenced with Geographic Information Systems (GIS) and Geographic Database (BDG), using ArcGIS 10.3 software. Results: in Minas Gerais, the spread of Zika was similar to other regions of Brazil. 10,465 cases were confirmed and of these, 26.5% were pregnant women. Almost 80% of the reported cases were female. The first cases were recorded in 2015, reaching all 13 regions in 2016, declining in 2017 and 2018, increasing again in 2019. Final considerations: in addition to socio-economic inequalities in Minas Gerais, it can be argued that women who are young, mixed-race, with low-education and from vulnerable areas are more likely to be affected by the disease. The analysis of disease epidemiology and mapping may better access disease impact, thus contributing to more adequate public health policies and planning.

Characterisation of the Historic Urban Landscape through the Aristotelian Four Causes: Towards Comprehensive GIS Databases

The Historic Urban Landscape provides a basis to comprehensively study the city, considering the numerous agents and stakeholders involved in the urban phenomenon. However, the characterisation of the city is challenging, due to the numerous ways of reading and using the city. Although several theoretical approaches address the process of documenting the city, there is still a gap related to the design of a generalised, holistic, and comprehensive framework. This article aims to contribute to this purpose by discussing the concept of the Historic Urban Landscape (HUL) and its implications for the characterisation of the urban phenomena. The Aristotelian theory of the causes is proposed here as a suitable approach for the description, characterisation, and analysis of virtually any entity by first discussing its theoretical basis and then testing it in a real building located in the historical city, Guimarães, Portugal. A set of tools related to Geographic Information System databases are comprehensively explored during the implementation process of the approach, allowing to identify and discuss a set of limitations, challenges, and opportunities.

A systematic method to develop three dimensional geometry models of buildings for urban building energy modeling

Three dimensional (3D) geometric models of buildings are foundational for urban building energy modeling. A complete 3D geometric model contains building-relevant information like building footprint, height and Window-to-Wall Ratio (WWR). Existing methods creating these models have certain limitations, such as unavailability of Geographic Information System (GIS) databases and Light Detection and Ranging (LiDAR) data for many cities, and restricted flying space for Unmanned Aerial Vehicles (UAV). To tackle these issues, this study has developed a systematic method developing 3D geometric models, with 1) building footprint acquired from combination of two internet maps, namely Baidu Map and OpenStreetMap; 2) building height estimated from the number of storeys for residential buildings and determined using the building vertical edge method for non-residential buildings, and 3) building WWR calculated from buildings’ elevation images using an Artificial Intelligence (AI). The validation work revealed that more than 85 % of acquired building footprints had absolute relative errors less than 10 %, and this percentage was 87 %, 74 % and 75 %, for height of residential buildings, height of non-residential buildings and WWR, respectively. To demonstrate the application of the method, a newly developed urban district in Nanjing, China was used as a case study.