Geographic Information System Technology Research Articles

Methods of building database to establish flooding map for coastal areas using a combination of artificial intelligence and GIS technology

As a country with a coastline stretching from North to South, in recent years natural disasters, especially floods and inundation, have severely affected people and properties in Vietnam. In order to prevent and control natural disasters and adapt to climate change, there have been many researches to establish the flood-related map in the country. Among the methods of creating flood maps, the application of AI (Artificial Intelligence) combined with GIS (Geography Information System) has outstanding advantages due to its ability to handle a mixture of many types of input data in a geographical space unification. This method is also used widely in the world in general and Vietnam in particular. When applying the aforementioned method, building the input database of machine learning and artificial intelligence models is an essential issue. Based on the Sentinel-1, Landsat 8/9 images, digital elevation model (DEM), and soil maps, the authors have built the input database for modeling by using AI models. This paper introduces the method of building the input database for making flood maps using machine learning, and artificial intelligence combined with GIS. The computation process is divided into two steps: (1) Editing the component data layers from input data and (2) Standardization of data to transfer the component data layers into the same unit with the standard data format of Weka software. The research’s results are 11 data layers including the flood map in the past, elevation, slope, slope direction, curvature, terrain energy, geology, land use, soil, NDVI, NDWI for Quang Nam province.

A geospatial approach for assessing urban flood risk zones in Chennai, Tamil Nadu, India.

Chennai,the capital city of Tamil Naduin India, has experienced severalinstances ofsevere flooding over the past two decades, primarily attributed to persistent heavy rainfall. Accurate mapping of flood-prone regions in the basin is crucialfor thecomprehensive flood risk management. This study usedthe GIS-MCDAmodel, a multi-criteria decision analysis (MCDA) model that incorporated geographic information system(GIS) technology to support decision making processes. Remote sensing, GIS, and analytical hierarchy technique (AHP) were used to identify flood-prone zones andto determine the weights of various factors affecting flood risk, such as rainfall, distance toriver, elevation, slope, land use/land cover, drainage density, soil type, and lithology. Four groups (zones) were identified by theflood susceptibility mapincluding high, medium, low, and very low. These zones occupied16.41%, 67.33%, 16.18%, and 0.08% of the area, respectively. Historical flood events in the study area coincided with the flood risk classification and flood vulnerability map. Regions situated close to rivers, characterized by low elevation, slope, and high runoff density were found to be more susceptible to flooding. The flood susceptibility map generated by the GIS-MCDA accurately described the flood-prone regions in the study area.

Sebaran Objek Wisata Bahari di Kecamatan Nusaniwe, Kota Ambon Berbasis Sistem Informasi Geografis

The utilization of geographic information systems (GIS) can make a significant contribution in analyzing the distribution of marine tourism objects in Nusaniwe District. This will help to make better decisions in developing supporting infrastructure, promotion, and improving the quality of services for tourists. This research utilizes Geographic Information System (GIS) technology to map the distribution of marine tourism objects in Nusaniwe District, Ambon City. The results showed that there are eight tourist attractions in Nusaniwe District including; Pintu Kota, Namalatu Beach, Santai Beach, Lima Jari Beach - Dutch Pool, Amahusu Beach, Batu Lubang Beach, Wainitu Beach and Tanjung Nusaniwe. The results of Mapping the distribution of marine tourism objects in Nusaniwe District are expected to help the community in the destination of traveling in Ambon City, especially marine tourism and also useful for the Ambon City government, especially the Tourism Office so that in the future it continues to pay attention and continues to develop marine tourism objects in Ambon City as one of the tourist attractions in Nusaniwe District.

Analysis of road accidents due to obstruction in sight distance caused by foggy weather using Geographic Information System (GIS) and Artificial Neural Network (ANN) at Jumja along Thimphu-Phuentsholing Highway (Asian Highway 48)

Road accident analysis is a crucial technique for determining what elements contribute to collisions and can help lower the accident rate. The consideration of sight distance is a crucial component of highway geometric design in order to guarantee effective traffic operations with the highest level of safety at an affordable price. Road accidents frequently result from reduced visibility caused by foggy weather, hence there is increased interest in studying this issue. This study aims to determine and correlate sight distance, fog blockage, and their effects on traffic accidents at Jumja along Thimphu-Phuentsholing Highway (Asian Highway 48). Data gathering and prediction was aided by the usage of Geographic Information Systems and Artificial Neural Network technologies. Temperature, relative humidity and wind speed for seven years from 2017 to 2023 were considered for fog occurrence to train Artificial Neural Network. Visibility was trained and predicted for summer and winter seasons since the occurrence of fog is prevalent during these seasons. As a result, a correlation value R of 0.998 was found, proving the findings to be almost accurate. This study offers a thorough investigation of how sight distance contributes to traffic accidents at Jumja region. A conclusive finding addressing the significance of sight distance as a contributing factor to traffic accidents due to fog invisibility along Jumja region was made after completion of this study.

Analisis Sebaran Konversi Lahan Pertanian di Kecamatan Muara Bangkahulu Kota Bengkulu

This study aims to determine the pattern of land use change and the pattern of distribution of land conversion that occurred in Muara Bangkahulu District in the period 2010-2022. This study uses a quantitative method with a spatial analysis approach that utilizes Geographic Information System technology and surveys to conduct ground checks in the field on the interpretation of land conversion results from satellite imagery data. The analysis used is nearest neighbor analysis and descriptive analysis. The results showed that there were only two patterns of land change that occurred in Muara Bangkahulu District, namely oil palm plantation areas turning into residential areas and agricultural areas turning into residential areas. The high rate of change of land use into residential areas is due to the subsidized housing program in Muara Bangkahulu District. The pattern of distribution of land conversion that occurs can be seen through the pattern of distribution of settlements in Muara Bangkahulu District which is included in the random category with a value of T = 1.064934 meaning that land conversion occurs in each village and the change tends to be permanent because it has changed its function to become built-up land or settlements.

Agricultural wetland utilization based on land cover restoration and water–ecosystem nexus

Abstract Wetlands, as a special ecological environment, are not only important biodiversity conservation areas but also one of the important agricultural resources. Agriculture plays an irreplaceable role in human society. It is directly related to human survival and development, and is also a part of people's environmental awareness and cultural inheritance. Based on the principles of sustainable development and strengthening environmental protection, people should pay more attention to the development and improvement of agriculture. However, with the advancement of urbanization, the area of wetlands continues to decrease, causing damage to ecosystems and posing a threat to some agricultural production. This article combined the transfer matrix of agricultural wetland utilization, landscape change rate, and landscape pattern index, used RS (Remote Sensing) and GIS (Geographic Information System) technologies to analyze the dynamic changes in agricultural wetland utilization and landscape of Honghu Lake in the Four Lakes region, and explored its changing factors. The results indicated that the construction land area showed an increasing trend in 2016, 2019, and 2022, while the wetland area of rice fields showed a first decreasing and then increasing trend.

Future paths for GIS in K-12 education: A review of possibilities and constraints

Geographic information systems (GIS) have been highlighted as essential future knowledge and are increasingly integrated in people’s everyday lives through applications, tracking, and global positioning systems (GPS). Still, applications and re-search of GIS technology for teaching and learning in kindergarten to grade 12 (K-12) education are limited. Through a scoping review of contemporary literature, this study identifies and discuss possibilities and constraints for GIS in K-12 education. Data were collected and analyzed with directed content analysis, using affordances as a theoretical lens, to identify possibilities and constraints of GIS for K-12 education. The study highlight themes of possibilities and constraints for further investigation. The possibilities of GIS for K-12 education include accessibility, transdisciplinary, and beyond classroom; and the constraints include skills and attitude, higher education and support, and teachers’ knowledge. The theoretical contribution of the study is a conceptual model for how possibilities and constraints of GIS for K-12 education relates to reaching educational goals. Findings of the study have practical implications for teachers and other stakeholders on the use of GIS in K-12 classrooms. The study also provides several suggestions for future research on GIS in K-12 education.

SPATIO-TEMPORAL ANALYSIS OF THE EFFECTS OF URBAN GROWTH ON URBAN HEAT ISLAND: CASE OF KONYA, TURKIYE

Abstract. The increase in impermeable surfaces within the urban areas contributes to local and regional-scale climate changes. This phenomenon, called "Urban Heat Island," is observed as the temperature in urban areas is higher than rural areas and natural landscape areas on the urban fringe. In recent years, advances in remote sensing and geographic information system technologies have enabled the urban heat island effect to be determined more quickly, economically, and accurately. In this study, the rapidly increasing urbanization in Konya, Türkiye and the resulting urban heat island effect have been analyzed. The study consists of four steps. In the first step, land surface temperatures for 1990 and 2022 of Konya city center were determined using the thermal band of Landsat-5 TM and Landsat-8 OLI satellite images. Then, satellite images were classified using the maximum likelihood method to determine land use and land cover in Konya. The effects of land use types and urban growth on urban heat island were examined. The Normalized Difference Vegetation Index (NDVI) and Normalized Difference Built-Up Index (NDBI) analyses were examined the statistical relationships between land surface temperature. The last step, the urban heat island effects of different types of regions in the city center of Konya were determined based on their urban form, texture, structure, landscape, and planning strategy. As a result of the study, measures that can be taken especially in spatial planning and design policies have been identified to reduce and prevent the urban heat island in Konya.

Quantitative Precipitation Estimation in the Tianshan Mountains Based on Machine Learning

Precipitation in the Tianshan Mountains is abundant, and the quantitative estimation of precipitation in mountainous areas is important to the application and evaluation of regional water resources. With remote sensing technology, satellite inversion of precipitation can estimate precipitation in mountainous areas. However, the Tianshan Mountain terrain is complex, and the spatiotemporal variation in precipitation is large, so the accuracy of satellite precipitation inversion is not high. Here, precipitation data from around 1000 automatic weather stations in the Tianshan Mountains are used to study the correction technology of the Integrated Multisatellite Retrievals for the Global Precipitation Measurement (GPM) mission’s (IMERG) monthly precipitation products using stepwise regression (STEP), geographically weighted regression (GWR), and random forest (RF). First, geographic information system technology was used to extract topographic variables from a digital elevation model, and vegetation indexes, which are important precipitation indicators, were introduced as explanatory factors to correct satellite precipitation data. Second, GPM IMERG precipitation was corrected by establishing the stepwise regression, the geographically weighted regression model, and the random forest model. The three correction methods can improve the GPM IMERG in terms of relative bias, root mean square error, correlation coefficient, and Nash–Sutcliffe efficiency, while the random forest method shows better corrections than the two traditional methods. For dense rainfall stations, the geographically weighted regression method is as effective as random forest. For different altitudes, the results show that RF has the best correction effect in the first three zones, but the correction effect in the last zone (over 3000 m) is worse than STEP. This study provides a practical reference method for estimating precipitation data in the non-rainfall observation area, which helps to deepen the scientific understanding of the water resource distribution in the Tianshan Mountains and provide scientific data support for regional hydrological and meteorological research.

Applying spatial decision support for maternal mortality analysis in a Brazilian state

The interface between Decision Support Systems (DSS) and Geographical Information Sys-tems (GIS) generates Spatial Decision Support Systems (SDSS) which aid in the deci-sion-making process, particularly in situations where spatial attributes play a pivotal role in achieving accurate conclusions. By integrating conventional decision criteria with spatial crite-ria and visualization through the adoption of SDSS and geographic information systems tech-nologies, a comprehensive analysis is ensured. The primary aim of this research is to exemplify an application of SDSS to support analyses and decisions on a specific issue in Public Health. The focus lies on assessing cities within the state of Pernambuco (Brazil) that exhibit the high-est rates of maternal mortality. This approach promises to offer valuable insights and aid in making informed decisions to address critical maternal health issues in the region.

Assessing the Impact of Engineering Measures and Vegetation Restoration on Soil Erosion: A Case Study in Osmancık, Türkiye

The prioritization of preventing soil loss in Türkiye’s watersheds has become a pressing concern for planners. Numerous mathematical models are presently utilized on a global scale for soil erosion prediction. One such model is the Revised Universal Soil Loss Equation (RUSLE), commonly used to estimate average soil loss. Recently, there has been an increased emphasis on utilizing USLE/RUSLE in conjunction with Geographic Information System (GIS) technology, enabling grid-based analysis for predicting soil erosion and facilitating control measures. This study evaluates the effectiveness of erosion and flood control initiatives started in the 1970s within the Emine Creek watershed and its tributary rivers in Osmancık, Türkiye, utilizing RUSLE/GIS technologies. Two distinct maps illustrating the potential erosion risks were produced for two distinct temporal intervals, and a comparative analysis was conducted to evaluate the alterations that transpired. The implementation of various measures such as terracing, afforestation, and rehabilitation in the watershed led to a notable prediction of decreasing soil loss in the watershed. From 1970 to 2020, the rate of estimated soil loss was reduced from 417 to 256 metric tons per hectare per year, demonstrating the effectiveness of soil conservation measures in a semi-arid and weakly vegetated area at reducing potential soil loss.

Monitoring of Surface Water bodies in Mainpuri District Using Remote Sensing and GIS Technology

Abstract: These days, a range of analytical tasks are carried out using popular, computer-dependent, time-oriented methodologies such as remote sensing and GIS (Geographic Information System) technology. Remote sensing technology provides a synoptic perspective that aids in mapping the dynamics of surface water bodies at regional and global scales. With this study, we can gather information on seasonal changes over time in the Mainpuri District because variations in the distribution of surface water have an impact on the hydrogeology and physical surroundings of the area. Mainpuri District has a Ramsar site named Saman Bird Sanctuary, which is home to a significant number of migratory and local migratory birds, primarily Sarus cranes. The research demonstrated that the area's abundance of waterbodies benefits biodiversity by giving migratory birds enough food and shelter. Shrinkage and expansion in surface water bodies are useful for determining the ecology of the region. In the current work, pre-monsoon and post-monsoon multi-temporal Landsat satellite images have been used to monitor spatiotemporal changes in the water bodies’ surface area in the Mainpuri District of Uttar Pradesh, India. In the north-west to southeast of the district, waterbodies' temporal changes show a 60% sharp decline in the number of waterbodies from 1992 to 2022.

Crimeline: Empowering Public Safety with GIS-Based Crime Incident Reporting

"Crimeline" is an innovative mobile application that revolutionizes the reporting and analysis of crime incidents thanks to a geographic information system (GIS) technology. This app allows citizens to report crimes in real time and facilitates data-driven decision making for law enforcement. By visualizing crime incidents on an interactive map, "Crimeline" empowers citizens and law enforcement to work together to combat criminal activity and improve public safety. This article presents the evolution and impact of the "Criminal Line", showing how its geographic information system (GIS)-based approach is changing the way crime incidents are managed for organizations community is safer

Mastodon footprints found to be water erosion in the Quebrada de Chalán (Licto, Ecuador).

The Chalan ravine is a deep bed creek that runs through Licto (Ecuador). It has been known since the 19th century for the abundance of paleontological remains of Pleiostocene fauna and megafauna in its profiles, where entire remains of mastodons were recovered. The abundance of these remains made one of the high areas, where marmites exist in different forms, was traditionally considered as mastodon footprints. Archaeological prospecting, geographic information system (GIS) technology, unmanned aerial vehicle (UAV), photogrammetry, and the geological study of the place, allowed us to determine that the mythical traces of mastodon were marmites made by the water erosion produced in the same ravine over time.

Accounting in a smart city with the combined use of the Internet of Things and geographic information systems

Introduction.The current stage of development of the smart city concept requires the development of effective digitalization techniques for accounting processes. To optimize the management of economic institutions and the smart city as a whole, multidimensional accounting information is required, generated by the Internet of Things (IoT) technology in combination with information about the territorial presence of residents. Zoning of the urban space forms an additional information resource for accounting and management purposes, which determines the importance and demand for scientific and applied developments in this area.The aim of the article is to improve of the accounting in a smart city in the conditions of the combined use of Internet of Things technology (IoT) and geographic information systems (GIS) in various sectors of the economy.Methods. Carrying out scientific research to achieve its goal involves the use of a systematic methodological approach in combination with innovative, functional methods and methodological tools of generalization, bibliographic, and comparative analysis.Results. The feasibility of the combined use of the Internet of Things (IoT) technology and geographic information systems (GIS) in accounting in the conditions of a smart city has been substantiated. The methodology for processing accounting information using IoT and GIS technology has been improved in the economic sectors of the smart city, such as passenger transportation in terms of accounting for the expenses and revenues of carriers based on data on the number and duration of trips; parking - accounting for the expenses and revenues of parking operators depending on the number and duration of vehicle parking; fuel and energy sector and housing and communal services - accounting for the consumption of energy resources using automated meters in consumers and providers of municipal services; ecology and urban planning - calculation and accounting of rental rates of municipal property and local business taxation based on data on the ecological and urban attractiveness of the location; healthcare - accounting for the expenses and revenues of healthcare facilities taking into account the quantitative and time parameters of medical services to residents; other areas and administrative services - accounting taking into account the number of people who received the services, and so on. Common accounting dominants for different economic sectors in a smart city have been identified: automation, two-dimensional calculation units, spatial connectivity, analytical capability, integration, object-based identification, completeness of accounting, reduced periodicity, and so on. Adherence to these accounting dominants ensures transparency, reliability, completeness, timeliness, and fairness in processing accounting information for management purposes in a smart city.Prospects. The methodology of using accounting information provided by IoT and GIS technologies for digitizing the management of smart city functioning is the subject of further scientific research.

Determination of the relationship between tectonic and karstification using morphometric indices in Bozburun Peninsula, Marmaris, Türkiye

Bozburun Peninsula (Marmaris) attracts attention because it contains various karstic shapes on limestones belonging to different periods and it is also an important area in terms of tectonic activity. This study examines the area sizes of the karstic shapes determined by satellite images, topographic maps and field studies, the elevations, slopes, depth value ranges and extensions where they are clustered and the fault lines affecting them have been determined. In order to explain this effect quantitatively, the elongation ratio (RE) and elongation direction (EA α) from morphometric shape indices were used. Poljes, on the other hand, were evaluated in more detail separately from dolines and uvalas, the pitting rates (PR) was calculated. It was understood that in this study which Remote Sensing (RS), Geographic Information System (GIS) technologies and field observations were correlated, folds and fractures that occurred in the Western Taurus Karst Region during the paleotectonic and neotectonic periods had a positive effect on karstification, and it was determined the lie of the karstic shapes to a great extent resemblance to the lie of the faults.

Ivermectin and doxycycline treatments against Onchocerciasis: Adaptations and impact among semi-nomadic population in Massangam Health District, Cameroon.

We trialed strategies to reach semi-nomadic population with interventions targeting onchocerciasis including a combination of community knowledge and Geographical Information System (GIS) technology; nomad-specific sensitization; and mobile outreach. The interventions included ivermectin (ivm) mass drug administration (MDA) and treating infected individuals (found upon skin snip microscopy test) with doxycycline for 35 days. Microscopy-negative snips were further tested by Polymerase Chain Reaction (PCR). After 8 months, individuals immigrating or emigrating constituted 47% of the initial population; 59% of individuals not born in the area have immigrated during the last five years; 28% (age>9) reportedly never taken ivm; 72% (compared to 51% previously) of eligible population (age ≥ 5 years) took ivm; and 47% (age > 8, not pregnant, not breastfeeding, not severely ill,) participated in the test. A high prevalence of onchocerciasis,15.1%, was found upon microscopy & PCR test; 9/10 tested by skin snip microscopy and PCR at follow-up were all negative. Microfilaria prevalence and intensity upon skin snip microscopy reduced significantly from baseline following the intervention (8.9% to 4.1%, p = 0.032; 0.18 to 0.16, p = 0.013, respectively). The strategies considerably increased reach to nomadic camps. Treating with doxycycline in combination with ivm is feasible and has led to a significant reduction in infection level within one year among the semi-nomads. Being potentially curative in one intervention round, this combination should be considered for population group faced with challenges of achieving adequate coverage and adhesion to ivm MDA over prolonged period (>10 years).

Seasonal analysis and mapping of air pollution (PM10 and SO2) during Covid-19 lockdown in Kocaeli (Türkiye)

The Covid-19 epidemic has adversely affected the world in terms of health, education, economic, tourism, social and psychological. During to the epidemic, different measures were taken to prevent the epidemic, such as travel bans, curfews, stopping in production. These measures have reduced and improved air pollution. Within the scope of this study, the change in air pollution in Kocaeli between 2019 and 2021 was examined monthly. PM10 and SO2 maps were created with inverse distance weighted (IDW) technique using geographic information systems technology (GIS). The year 2020, when Covid-19 measures were taken, was compared with 2019 and 2021. Change maps were created by taking the difference between 2020-2019 and 2021-2020 with GIS technology. As a result of the research, it was determined that the level of air pollution decreased in 2020. On the contrary, in 2021, an increase in air pollution levels was observed. In the study, a decrease was observed in PM10 concentration during the Covid-19 lockdowns, however a decrease was not observed for SO2.

The potentiality of GIS for assessing soil pollution – A review

The assessment of soil pollution is only one instance where geographic information systems (GIS) have shown to be an invaluable tool in environmental management and assessment. Globally, there is growing worry over soil pollution since it can have catastrophic repercussions on plant, animal, and human life. A more in-depth understanding of the scope and severity of contamination is made possible by GIS, which offers a flexible and all-encompassing method to studying and assessing soil pollution. With the aid of GIS technology, precise maps of soil contamination may be produced by combining data from numerous sources, such as remote sensing, aerial photography, and ground surveys. This information can then be evaluated using a variety of techniques, such as spatial analysis, to pinpoint polluted areas, possible sources of pollution, and the effects they are most likely to have on the environment and human health. By making it easier to identify sensitive regions that need additional research or remediation, GIS can also help with the analysis of the risk of pollutant movement and dispersion. Comparing GIS to conventional methods for assessing soil pollution has various benefits. First of all, it enables a more thorough and in-depth examination of the degree and breadth of contamination, enabling the identification of locations that need urgent care. Second, it makes it easier for different stakeholders, such as environmental agencies, researchers, and policymakers, to share data and information, enabling better decision-making. Thirdly, it makes it possible to monitor and control soil contamination more effectively, allowing for the early detection of potential issues and the implementation of suitable corrective actions. In general, GIS technology is a useful tool for assessing soil pollution since it offers a more thorough and knowledgeable approach to environmental management. It is a crucial tool for environmental experts engaged in the assessment and control of soil pollution due to its capacity to combine different data sources, perform spatial analysis, and promote information sharing.

SISTEM INFORMASI GEOGRAFI FASILITAS MASJID DI KELURAHAN JAKASAMPURNA, BEKASI BARAT

Geographic Information Systems (GIS) have become an important tool in the management of spatial information in various fields, including religion and belief. Regarding Islamic places of worship, mosques have a central role as centers of worship, community activities, and social. With the increasing role of geospatial technology, the application of GIS in the management and mapping of mosque locations has become an interesting and relevant research area. This abstract discusses the use of GIS technology in the management and mapping of mosque locations. The author outlines how geospatial technology has been used to collect, integrate, and analyze mosque-related data, such as the mosque's geographic location, existing facilities, and other related data. The purpose of this writing is to build a Geographic Information System that can convey information in the form of locations and facilities in the Jakasampurna area mosque.In addition, this paper also considers the benefits of implementing GIS in mosque management and mapping, including management efficiency, community needs analysis, and sustainable development planning.