Geographic Information Processing Research Articles

Small-grid urban flood prediction model using Twitter data and population GPS data - an example of the 2019 Nagano city flood

In this study, a small-grid urban flood prediction model integrating Twitter data and population GPS data was constructed using the 2019 Nagano City flood as an example, and the validity of these two data for the model was determined. Using natural language processing techniques, Twitter data was filtered to extract real-time information relevant to flooding. At the same time, geographic information processing techniques were applied to analyze the population GPS data and obtain the distribution of the local population. Based on these two types of data, we combined with terrain, land use, traffic and infrastructure data related to flooding, a real-time flood prediction model was constructed using the random forest algorithm with a basic unit of a 70 m × 70 m grid. An analysis of the model accuracy showed that, the model that included both GPS and Twitter data showed an improvement in prediction accuracy of about 8% compared to flood prediction models that do not have these data sources. This indicated that the integrated use of Twitter and GPS data allowed us for a more accurate representation of the dynamic characteristics of flood disasters, thereby improving the performance of real-time flood prediction models and increasing real-time awareness of flood events. This approach provided effective flood monitoring methods for disaster management authorities.

A bottom-up nationwide analysis of sectoral land use reveals spatial heterogeneity across the United States

The high degree of urbanization and economic development in the United States has intensified competition for land resources, leading to land use conflicts and environmental challenges. Addressing these issues first requires an exploration of high-resolution, sector-specific land use patterns. However, existing land classification studies rarely provide spatially explicit data on urban land use across all sectors at a national level. This study aims to fill this gap by analyzing land use areas across various economic sectors in the United States, particularly focusing on urban impervious surfaces. Using a bottom-up approach, we created a full-sector land use inventory, integrating Points of Interest (POI) data, road networks, building characteristics, and geographic information processing techniques. Our primary innovation lies in the development of a spatially explicit database that details sector-specific land use areas nationwide. On this robust foundation, we further explored the heterogeneity of sectoral land use eco-efficiency (SLUEE) among different sectors and states, providing supplementary insights into spatial disparities in urban land use. Our findings reveal significant spatial heterogeneity, with service sectors dominating land use and exhibiting higher SLUEE compared to goods-producing industries. Key sectors such as Professional, Scientific, and Technical Services (441064.58 ha), and Administrative and Support Services (420148.34 ha) are prominent across states according to land use area, reflecting the country's service-oriented economy. Additionally, regional disparities in SLUEE are evident, with jurisdictions like Washington D.C., New York, and California demonstrating more efficient land use. Compared with traditional land use evaluations, our model effectively offers higher spatial resolution, down to the census block level, to sectoral land use evaluation. Building on this robust database, our SLUEE analysis has uncovered notable heterogeneity between sectors and states, offering new insights into cross-sectoral and inter-state land use dynamics that can inform and promote sustainable urban planning.

Indoor view-based visibility analysis using UAV and TLS point clouds with Line-of-Sight correction

Visibility analysis is a crucial geographic information processing method, used to assess the observable spatial range from a particular location under specific conditions. It has broad applications, such as urban planning, landscape design and environmental research. Laser scanning provides detailed and accurate 3D data for visibility analysis, called point cloud. However, certain deficiencies still exist in current point cloud-based visibility analysis methods. Few methods are developed from indoor perspective and the influence of point cloud void is rarely considered. Firstly, indoor viewpoints are generated based on the windows extracted from terrestrial laser scanning (TLS) point cloud and unmanned aerial vehicle (UAV) point cloud is used to provide 3D representation of the environment around the viewpoint. Then, a half-sphere viewshed is created for each indoor viewpoint to analyze the visible spatial range. In this step, a novel line-of-sight correction method is proposed based on the semantic information from UAV point cloud, to correct the biased observation distance resulted from point cloud voids. Lastly, the volume of visible space is calculated based on the corrected viewshed image, to evaluate the visibility of each indoor viewpoint. Our method is validated on two datasets. The results indicate that our method enables more accurate simulation of visible space compared with previous studies by considering the effect of point cloud void. The proposed method can support the urban design from the perspective of indoor visual perception and accurate calculation of other visual factors in visual quality evaluation.

A hierarchical shape description approach and its application in similarity measurement of polygon entities

Spatial similarity provides an important basis for geographic information processing and is widely applied in multi-source data fusion and update, data retrieval and query, and cartographic generalization. To address the shape description and similarity measurement of polygon entities, this study presents a new hierarchical shape description approach and examines its application in similarity measurement of polygon entities. Using the rotation and segmentation methods, we first constructed a hierarchical shape description model for target polygon entities, followed by measurement of global and hierarchical shape description of polygon entities, respectively, using the farthest-point-distance and geometric feature description methods. Finally, we constructed a comprehensive similarity measurement model through a weighted integration of position, size, direction, and shape. The hierarchical shape description approach proposed in this paper can be applied to the shape similarity measurement of polygon elements, similarity measurement after spatial object simplification, and multi-scale polygon entity matching. The experimental results showed that the hierarchical shape description approach and similarity measurement model are able to effectively measure spatial similarity between different polygon entities, and have obtained good application results.

Application of Geographic Information Systems in the Study of COVID-19 in Morocco

Introduction: The 2019 coronavirus disease (COVID-19) was first identified as a respiratory disease that originated in Wuhan, Hubei Province, China. The WHO declared the COVID-19 outbreak a public health emergency of international concern on 30 January 2020. Morocco reported its first coronavirus case on 2 March 2020. During the week of 9-15 March 2020, Morocco took steps to limit the spread of the epidemic. This article describes the use of spatial data applications in epidemiological research in Morocco, specifically its response to the COVID-19 epidemic. Methods: To conduct this study, we relied on the use and analysis of data provided by the Moroccan Ministry of Health for the study period from May to July 2021, as well as the geographical and administrative map of the Kingdom of Morocco. Spatial analysis of COVID-19 was performed using ArcGIS 10.8 and QGIS, a geographic information processing software. Health data for the 12 regions of the Moroccan territory were presented in the number of COVID-19 cases as a discrete quantitative variable and over time as a continuous time variable. Results: According to a map created using GIS, the concentration of COVID-19 cases appeared to be highest in the Casablanca Settat region. Depending on the number of documented COVID-19 cases, regions were ranked as follows: Casablanca-Settat> Rabat-Sale-Kenitra> Marrakech-Safi > Fes-Meknes > Tangier-Tetouan-Alhouceima>Oriental>Souss-Massa > Béni Mellal-Khenifra> Draa-Tafilalet> Laayoune-Sakia El Hamra >Guelmim-Oued Noun > Dakhla-Oued Eddahab. The increase in cases in major cities was due to several factors, including demographic, social and environmental factors. This demonstrated the need to consider demographic contributions to environmental health. Demographic factors helped us understand the health of our environment empirically. Geography improved health decision-making and accountability. Incorporating the geographic context of the spread of COVID-19 helped decision-makers understand the impact of location on strategies and goals to combat this pandemic. Conclusion: This study identified areas with high and low COVID-19 clusters and hotspots. The produced maps can serve as an excellent management tool to control and effectively eliminate the COVID-19 pandemic, contributing to investments in epidemiological surveillance programs.

The Innovation of GIS Service Mode Based on “Grid Integration” and “Elastic Cloud”

Abstract This paper firstly investigates the theory and method of geospatial information services and grid integration model in the geographic information grid, intending to locate the parameter coordinates of the grid integration model into the GeoSOT-3D profiling framework. Secondly, the framework of the consumption structure between its services and cloud resources is established by the elastic cloud model based on the computation and storage capabilities provided by the shared grid infrastructure. And use the steady-state theoretical foundation for analysis to assess the service quality of each type of service and reflect the service quality of the GIS service model as a whole. Finally, a GIS service platform based on the grid integration model and elastic cloud model is constructed based on the existing open geographic information standards, service technology system, and grid technology. The research results show that the operation speed of the GIS service platform proposed in this paper is increased by 16.3%, the estimated cost has been reduced by 23.3%, and the service evaluation of the platform is improved by 43.6%. The GIS service platform based on the grid integration model and elastic cloud model has the advantages of global uniformity, multi-scale and spatial 2-3D consistency, which provides a new model with high economy and rapid response time for geographic information processing.

Remote Sensing-Based Assessment of Soil and Water Pollution in Deep Excavation Scenario

Soil and water resource mismanagement can negatively intensify global poverty and jeopardize ecology. Soil can be contaminated by heavy metals, organic chemicals like biological pathogens, pesticides, micro plastics and nano particles. Contamination decreases the soil’s capability to yield food thereby affecting food production by means of pollution and disease. Moreover, soil contaminants move into rivers damaging the water quality. Numerous technologies have been established to tackle water and soil remediation, such as deep excavation technique where transportation of contaminated soils or water is done to remote unpopulated sites. Recent development in Remote Sensing and geographic information processing techniques have led to exciting new opportunities for investigating and closely monitoring environmental factors that influence key land and soil management approaches. Hence, this paper uses the Deep Excavation and Remote Sensing based Assessment Model (DERSAM) to assess the soil and water pollution in contaminated areas. The data are taken from the Europe soil contamination map to classify the contaminated and non-contaminated areas. This data obtained from the high-resolution satellite of Remote Sensing (RS) technique and Geographical Information System (GIS) with the parallel expansion of a fully assimilated geospatial database system that provides monitoring and feedback at suitable spatial scales. Thus, such data can be utilized for long-term environmental management and monitoring of remediation and rehabilitation of excavation areas. The numerical outcomes show that the recommended DERSAM model increases the land use and land cover change prediction by 90.2%, the classification ratio by 98.2%, the pollution reduction ratio by 96.6%, the soil contamination detection ratio by 95.9%, and the overall performance by 97.2% compared to other existing approaches.

An Automatic Counting Algorithm for Topographic Maps Based on Videos for Map Management

Topographic maps comprise a rich data source for the processing and analysis of geographic information. However, the management of paper topographic maps is still dominated by an inefficient manual method, and there is no counting equipment for topographic maps that is suitable for narrow map warehouse passages. The existing algorithms relating to paper counting require paper hardness and cannot directly obtain the internal information of topographic maps. To address the above problems, using a map inventory machine transformed from a paddle-type paper counting machine to perform a preliminary count and obtain the video data of the counting progress, an automatic counting algorithm for topographic maps for map management is proposed in this study. First, the periodic feature changes of all the targets and each individual target in the videos are analyzed. Second, a deformable parts model accelerated by fast feature pyramids and by reducing the region of interest is used for the object detection of mechanical wheels. The grayscale variance function is selected to quantify the quality change in the images. Finally, a fusion window counting model is constructed with the adaptive window and fixed window methods. The experimental results show that the average counting accuracy of the model is about 95%, which can verify the initial counting results of the machine and provide high-quality keyframes for the subsequent sheet designation recognition.

Geographical Information Processing and Geomorphological Characteristics Analysis of Central Rift in Ethiopia

Geographical Information Processing and Geomorphological Characteristics Analysis of Central Rift in Ethiopia

GeoGAT: Graph Model Based on Attention Mechanism for Geographic Text Classification

In the area of geographic information processing, there are few researches on geographic text classification. However, the application of this task in Chinese is relatively rare. In our work, we intend to implement a method to extract text containing geographical entities from a large number of network texts. The geographic information in these texts is of great practical significance to transportation, urban and rural planning, disaster relief, and other fields. We use the method of graph convolutional neural network with attention mechanism to achieve this function. Graph attention networks (GAT) is an improvement of graph convolutional neural networks (GCN). Compared with GCN, the advantage of GAT is that the attention mechanism is proposed to weight the sum of the characteristics of adjacent vertices. In addition, We construct a Chinese dataset containing geographical classification from multiple datasets of Chinese text classification. The Macro-F Score of the geoGAT we used reached 95% on the new Chinese dataset.

Geolocation of uterine cervical neoplasms (UCN) in the context of a prevention program in Tucumán, Argentina.

e13535 Background: : UCN is one of the major public health problems in Tucumán, that must be related to the type of population to which it belongs (Rural or Urban). Geolocation allows the processing and analysis of geographic information whose results support decision-making in solving complex planning and management problems on the territory. The objective of this study is to carry out management quality controls of the PPCCUT (Programa de Prevención de Cáncer Cervical Uterino-Tucumán) to achieve adequate prevention and detection of uterine cervical lesions in the province. Methods: An observational cross-sectional study of 1343 women, (16-90 years), with a biopsy diagnosis UCN, under PPCCUT (years 2013-2020). Preanalytical work: allowed the review quality the registries and the diagnoses follow-up. Data recollection from SITAM (Online Information System for Screening), population registry database. Variables: Address: registered in SITAM, joined by information from the provincial female electoral roll 2019. Histological Diagnosis: High grade squamous intraepithelial lesion (HSIL), Invasive Squamous Carcinoma (ISC), Adenocarcinoma In situ (AIS), Invasive Adenocarcinoma (IDA). Analytical work: The conversion from address to latitude and longitude was performed by programming Google Sheet. This data was segmented by hospital center and opened in layers inside QGIS, as well as the map of Argentina. Results: Preanalytical. Register showed from 1343 patients received 1748 biopsies, were excluded 160 without address (incomplete data loading by the effectors). Lack of coordination in diagnosis area: 33 patients received first “in situ diagnosis” and in a short time later were consider “invasive lesions”. Some Patients had 2 bis 6 biopsies with same diagnosis. Analytical (geolocation): showed the influence of PPCCUT outside the province, including living abroad. It was found correlation between patients’ distribution with the population density. Conclusions: The importance of the work lays in the lack of antecedents in the application of the geolocation tool in programs of UCN in Tucumán and in other regions of Argentina. This allowed monitoring in different aspects of the programmatic management.

Using Citizen Sensing to Identify Heat-Exposed Neighbourhoods

Rural areas cool off by night but built-up urban areas lack similar relief and may threaten vulnerable people’s health during heat waves. Temperature varies within a city due to the heterogenous nature of urban environments, but official measurement stations are unable to capture local variations, since they use few measurement stations typically set up outside of urban areas. Meteorological measurements may as such be at odds with citizen sensing, where absolute accuracy is sacrificed in pursuit of increased coverage. In this article, we use geographic information processing methodologies and generate 144 hourly apparent temperature surfaces for Rotterdam during a six-day heat wave that took place in July 2019 in The Netherlands. These surfaces are used to generate a humidex degree hours (HDH) composite map. The HDH metric integrates apparent temperature intensity with duration into one spatially explicit value and is used to identify geographical areas in Rotterdam where citizens may experience adverse health effects of prolonged heat exposure. Combining the HDH map with demographic data allows us to identify the most heat-exposed areas with the largest share of vulnerable population. These neighbourhoods may be the locations most in need of adaptation measures.

Analysis of Location Selection of Public Service Facilities Based on Urban Land Accessibility.

Urbanization has been a flourishing process in a wide range of developing countries. The planning and construction of public service facilities is a crucial component of this process. Existing planning methods of public service facilities focused on macroscopic indicators like population and GDP. In this way, accessibility and transportation conditions were neglected. Four typical counties in China were selected as samples where travel surveys and questionnaire surveys on public service facilities were conducted. Taking education and medical care as representative public service facilities, this study used geographic information processing to connect the locations of public service facilities at all levels with the urban land accessibility. Then, analysis of variance was used to obtain correlations between the level of public service facilities and the urban land accessibility. The results showed that the urban land accessibility of locations of public service facilities follows a normal distribution. Categories of facilities showed significant difference on urban land accessibility. Therefore, intervals of urban land accessibility of locations of public service facilities within one standard deviation from the mean were constructed by category. These intervals built a connection between transportation conditions with locations of public service facilities. Corresponding relation of carbon emission of facility-related trips and urban land accessibility was established as an example of an application. Carbon emissions caused by facility-related trips can be reduced by locating facilities at locations with appropriate urban land accessibility.

Early warning expert decision system of water resource management based on Cloud Computing

In order to solve various problems caused by the lack of timely warning in water resources management, based on the current water resources informatization, an early warning expert decision-making system for water resources management based on cloud computing architecture is proposed. The system collects real-time data through the Internet of things interface layer, uses Web GIS to display geographic information and Ajax (asynchronous Javascript + XML) asynchronous interactive processing mode to speed up the response speed. Finally, an early-warning expert decision system for water resource management based on the cloud computing architecture is realized, which can monitor both the command center and the mobile terminal at the same time.

Integrated Design Scheme of Coastal Urban Planning Based on GIS Method

Wang, Y. and Yu, S., 2020. Integrated design scheme of coastal urban planning based on GIS method. In: Yang, Y.; Mi, C.; Zhao, L., and Lam, S. (eds.), Global Topics and New Trends in Coastal Research: Port, Coastal and Ocean Engineering. Journal of Coastal Research, Special Issue No. 103, pp. 328–332. Coconut Creek (Florida), ISSN 0749-0208.In order to improve the feasibility of the overall design scheme of coastal urban planning, a general design scheme of coastal urban planning based on Geographic Information System (GIS) is proposed. This paper constructs a geographic information analysis model, which combines information fusion with large data information processing methods, and carries out geographic information data fusion and processing analysis of coastal urban planning. According to the distribution attributes of the data, the collected geographic information data are clustered. Fuzzy C-means clustering method is used to realize coastal urban planning geographic information data fusion clustering. Based on the adaptive correlation integral matching method, the geographic information data clustering centers of coastal urban planning are searched to realize data correlation mining. Principal component analysis is used to mine the key information of coastal urban planning and clustering, and to guide the optimal design of coastal urban planning. Finally, the software is designed and simulated. The results show that the method is effective in the overall design of coastal urban planning. Through GIS geographic information fusion and dispatch, the feasibility of coastal urban planning and design is improved.

أثر تطبيق إلکتروني مستند إلى جانبي الدماغ(Mind 42) في تنمية مهارات معالجة المعلومات الجغرافية والاتجاه نحو التطبيقات الإلکترونية لدى طلاب الصف الأول الثانوي

هدفت الدراسة إلى توظيف تطبيق إلكتروني قائم على التعلم المستند إلى جانبي الدماغ (Mind 42) لتدريس الجغرافيا، وقياس أثره في تنمية مهارات معالجة المعلومات، والاتجاه نحو التطبيقات الإلكترونية، وقد تكونت عينة الدراسة من (62) طالبا من طلاب الصف الأول الثانوي بمدرسة نزة الهيش الثانوية المشتركة؛ قسمت إلى مجموعتين إحداهما تجريبية عددها (31) طالبا، والأخرى ضابطة عددها (31) طالبا، حيث درست المجموعة التجريبية باستخدام تطبيق (Mind 42)، بينما درست المجموعة الضابطة بالطريقة المعتادة ، وتم استخدام منهج البحث الوصفي والمنهج التجريبي ذو التصميم شبه التجريبي لتحقيق أهداف الدراسة وإعداد أدواته، التي تمثلت في: اختبار مهارات معالجة المعلومات الجغرافية، ومقياس الاتجاه نحو التطبيقات الإلكترونية في تعلم الجغرافيا. وقد أوضحت نتائج الدراسة وجود فروق ذات دلالة إحصائية عند مستوى (0.05) في التطبيق البعدي لاختبار مهارات معالجة المعلومات ، ومقياس الاتجاه نحو التطبيقات الإلكترونية في تعلم الجغرافيا لصالح طلاب المجموعة التجريبية، كما أظهرت النتائج أن حجم التأثير(2) لتطبيق (Mind 42) كبير في تنمية مهارات معالجة المعلومات الجغرافية، والاتجاه نحو التطبيقات الإلكترونية في تعلم الجغرافيا، وتم تقديم مجموعة من التوصيات والمقترحات التي ترتبط بالتطبيق المستند إلى جانبي الدماغ(Mind 42) في بيئة التعلم والتعليم. ,The aim of this study is to employ an electronic application based on brain-based learning (Mind42) to teach geography, to measure its impact on the development of information processing skills, and to move towards Electronic applications, the research sample consisted of (62) students of the first grade of secondary stage in Naza Elhesh secondary school mixed, They were divided into two groups; experimental group of (31) students and control group of (31) students. The descriptive research methodology and the experimental approach with quasi-experimental design were used to achieve the objectives of the Study and the preparation of its tools which consisted of a test for processing geographical information skills, and a measure of the trend towards electronic applications in learning geography. The results showed that there were statistically significant differences at the level (0.05) in the post application to the information processing and analysis skills test and measure of the trend towards electronic applications in learning geography for the benefit of experimental group students. The results also showed that the effect size (2) for the application of Mind 42 are significant in the development of geographic information processing skills, and the trend towards electronic applications in learning geography. A set of recommendations and suggestions that relate to the brain sides-based application (Mind 42) in teaching and learning environment was presented.

Shipping Container Counting Approach Using Unmanned Aerial Vehicle (UAV) and ArcGIS

In Malaysia, the existing of counting approach on the shipping container at depot is carried out by manual based system. This has made the efficiency of the method to be questioned which can be solved through automation. Under previous studies, Unmanned Aerial Vehicle (UAV) is demonstrated for automatic counting of cars and trees. Therefore, the possibility for shipping container counting is highly required in which promotes low-cost alternative and automatedpilot for data collection. Based on this study, the aerial images captured using UAV is combined with geographical information processing software, ArcGIS, towards automated approach for container counting. The overlapping aerial images are post-processed using photogrammetric technique to produce Digital Surface Model (DSM) that represents the ground and above surface feature’s elevations. Then, the constructed DSM is filtered to develop Digital Terrain Model (DTM) where it represents the ground surface’s elevation only. Then, container’s candidates are isolated using subtraction of the DTM from DSM to generate normalized DSM (nDSM) which represents the heights of container’s stacks. From the standard size and height of one container from ISO, the number of containers is extracted. The ModelBuilder tool available in ArcGIS is customized for automated geographical information processing. From results, the proposed approach contributed to 100% of counting accuracy. Keywords: Unmanned Aerial Vehicle, Counting, Shipping Container, ArcGIS, ModelBuilder

Geographic Information System in Mapping Land Use in South Aceh District


 
 
 
 The dawn of the age of computerization has opened up a new horizon and paradigm in the decision making process and dissemination of information. In the past difficulties arise when a large bulk of data representing of modeling a certain phenomenon was to be compiled because these data were often detached from each other. With Geographic Information System (GIS), the storing, administration, processing, manipulation, analysis and exhibition of important data in a system of information can be done with ease and speed. This study attempts to represent and model the available data of Sourt Aceh Selatan concerning its administrative boundaries, land, geology, land use and slope, Using ArcGIS 10.3, a GIS software that is capable to represent spatial data as well as attributes of the study areas. the results of rms error on landsat 8 oil images obtained mean 0.51, GIS technology in civil engineering work is normally used in the planning and preparation of a new land for the development of a housing complex.
 
 
 

From location tracking to personalized eco-feedback: A framework for geographic information collection, processing and visualization to promote sustainable mobility behaviors

Nowadays, most people carry around a powerful smartphone which is well suited to constantly monitor the location and sometimes even the activity of its user. This makes tracking prevalent and leads to a large number of projects concerned with trajectory data. One area of particular interest is transport and mobility, where data is important for urban planning and smart city-related activities, but can also be used to provide individual users with feedback and suggestions for personal behavior change. As part of a large-scale study based in Switzerland, we use activity tracking data to provide people with eco-feedback on their own mobility patterns and stimulate them to adopt more energy-efficient mobility choices. In this paper we explore the opportunities offered by smartphone based activity tracking, propose a general framework to exploit location data to foster more sustainable mobility behavior, describe the technical solutions chosen and discuss a range of outcomes in terms of user perception and sustainability potential. The presented approach extracts mobility patterns from users’ trajectories, computes credible alternative transport options, and presents the results in a concise and clear way. The resulting eco-feedback helps people to understand their mobility choices, discover the most non-ecological parts of their travel behavior, and explore feasible alternatives.

Extracting the curve-number map of watersheds of Lighvan Chay in GIS environment

One of the factors involved in the planning of water resources, is calculating the amount of runoff resulting from rainfall. Many of catchments in our country do not have hydrometric stations. Implementation water resource development projects, requires estimating these information.SCS method is one of the customary methods for solving this problem and as information required for this method, we can mention the runoff curve-number. This article has been performed about the Lighvan Chay catchment in East Azerbaijan and its purpose is the extraction of runoff curve number. To determine the curve-number, the land-use map and the soil map of the area have been prepared and then it is modulated in ArcGIS and the calculations have been performed. Using geographic information processing system, the weighted average value of the curve has been estimated under moisture condition and its amount is about 85.3 .According to that the highest level of catchment obtained about 86. Comparing the results with curve numbers showed us that the obtained numbers are so close to each other and therefore the offered method is an easy and fast method for obtaining the curve number of catchments.