Application Of Geographic Information System Research Articles

Analysis for an open-source library in database management systems

AbstractSpatial data management is crucial for applications like urban planning and environmental monitoring. While traditional relational databases are commonly used, they struggle with large and complex spatial data. NoSQL databases provide support for unstructured data and scalability. This article compares the performance and disk space usage of SQL Server (a relational database) and MongoDB (NoSQL database) using an open-source library. Experiments conducted with the OpenStreetMap dataset from Central America show that the MongoDB database outperformed the relational SQL Server database in most cases, offering practical advantages for spatial data management in Geographic Information System applications.

Enhancing integrated resource management through remote sensing and GIS

Integrated Resource Management plays a crucial role in sustainable development by ensuring efficient allocation and utilization of natural resources. Remote Sensing (RS) and Geographic Information System (GIS) have emerged as powerful tools for collecting, analyzing, and managing spatial data, enabling comprehensive and integrated decision-making processes. This review article uniquely focuses on Integrated Resource Management (IRM) and its role in sustainable development. It specifically examines the application of RS and GIS in IRM across various resource management domains. The article stands out for its comprehensive coverage of the benefits, challenges, and future directions of this integrated approach.

Application of GIS in Evaluating Suitable Clam Farming Site in Vembanad Lake, India

The present study identifies and quantifies appropriate sites for black clam farming in the Vembanad Lake using a geographical information system (GIS). The black clam, Villorita cpyrinoides, is the most important clam landed in India. Despite being a candidate species for aquaculture, the trials on farming of clams are very limited. The aim of this study was to select the most suitable sites for clam farming in Vembanad Lake based on the use of GIS-based models. For this, the importance of soil quality, water quality and infrastructure facilities were accessed using an analytical hierarchical process. The site suitability map was prepared using each attribute and divided into four classes, such as most suitable, moderately suitable, least suitable and poor. Water quality is found to play a major role (54%) compared to soil quality (24%) and infrastructure facilities (22%) for development of clam farms in Vembanad Lake. Salinity registered the highest importance (0.21) for the water quality suitability map as compared to other parameters like pH and dissolved oxygen. The total area covered under this study was 6471 ha out of which, 3121 ha (48%) was identified as most suitable and of the remaining 3350 ha, 1804 ha (28%) was identified as moderately suitable, 946 ha (15%) was identified as least suitable and 600 ha (9%) was identified as the poor site for clam farming in Vembanad Lake.

Preface

It is with great pleasure that we introduce the proceedings of The National Conference on GIS Application, hosted by the Vietnam National University of Agriculture on November 11-12, 2023. The conference, held under the theme “GIS Application: Digital transformation in natural resources and environmental management,” serves as a platform for the exchange of cutting-edge research and ideas within the dynamic landscape of Geographic Information Systems (GIS).In the context of Digital Transformation and Industry 4.0, this conference stands as a pivotal gathering aimed at exploring and leveraging GIS technologies for the sustainable management of natural resources and the environment. The event encompasses 8 sessions, each dedicated to a specific facet of GIS application, ranging from environmental and natural resource management to healthcare and urban infrastructure.The diverse array of sessions includes: GIS, GPS, and Remote Sensing in environmental and natural resources management; GIS, GPS, and Remote Sensing in land management, urban management, and infrastructure; GIS, GPS, and Remote Sensing in Climate Change research for natural disaster prevention and mitigation; GIS, GPS, and Remote Sensing in agriculture, forestry, and aquaculture; GIS and GPS in state management; GIS, GPS, and Remote Sensing in the field of medicine and public health care; GIS and GPS in water supply and drainage management and urban works; Artificial intelligence (AI), Big Data in the field of GIS.The response to the conference was overwhelming, with over 100 submitted papers reflecting the dedication and enthusiasm of researchers in the GIS community. Following a meticulous review process on the Easychair and Morressier platforms, 28 outstanding papers have been selected for publication in the IOP Conference Series: Earth and Environmental Science.We extend our sincere gratitude to all contributors, reviewers, and participants who have contributed to the success of this conference. It is our hope that these proceedings will serve as a valuable resource and inspire further advancements in GIS application for the betterment of our natural environment and resource management practices.We wish you an insightful and fruitful exploration of the diverse research presented in these proceedings.Sincerely,On behalf of editor boardProf. Dr. Nguyen Kim LoiDepartment of GIS and Natural ResourcesFaculty of Environment and Natural ResourcesNong Lam University, Ho Chi Minh CityVIETNAMList of Editor board is available in this Pdf.

Application of GIS in land unit mapping and evaluation of land suitability for agriculture in Uong Bi district – Quang Ninh province

This study aims to apply Geographic Information Systems (GIS) in land unit mapping and the evaluation of land suitability for agriculture in Uong Bi District, Quang Ninh Province, Vietnam. Given the complex and spontaneous changes in land usage driven by market fluctuations and environmental challenges, assessing land quality becomes crucial for sustainable agricultural development. Integrating soil, topographic, and climatic data within a GIS framework led to the creation of land unit maps for 40 different units in Uong Bi district, classified based on soil type, slope, soil depth, soil fertility, and hydrological conditions. The assessment of land suitability for seven main crops, including Litchi, Citrus, Dragon fruit, Cinnamon, Vegetables, Pine, and Macca, was conducted using the FAO framework for land evaluation. The results indicate that Pine and Cinamon have the highest arable area across all crops (with 15,895.40 ha and 15,502.40 ha respectively) while Vegetables show the lowest total arable area (4,063 ha). The findings provide valuable insights into the suitability of land for specific crops, facilitating informed decision-making to optimize land use and improve agricultural production.

Development of Soil Quality Databases and Land Potential Assessment Using GIS: A Case Study of Lao Cai Province, Vietnam

The utilization of Geographic Information Systems (GIS), particularly the Mapinfo software, is indispensable in the establishment of a land quality and land potential database encompassing each land parcel within Lao Cai province. Through a multifaceted approach involving data collection techniques, field surveys, data analysis, and the creation of both spatial and attribute databases, the GIS application in Lao Cai province has successfully compiled a comprehensive dataset. This dataset encompasses a range of layers, including boundaries, administrative demarcations, land use statuses, survey points, soil types, slope characteristics, soil depth, irrigation patterns, climatic conditions, soil fertility data, and transportation and hydrological information. The amalgamation of this spatial data with attribute data yields a comprehensive repository featuring information on 405 units of agricultural land quality and potential, in addition to 65 aggregated non-agricultural land parcels. This combined dataset functions as the foundational land quality and potential database for Lao Cai province. Assessment outcomes for land quality and land potential throughout the entire province reveal that 51.42% of the land exhibits low quality, 35.06% demonstrates moderate quality, and 13.52% boasts high quality. In terms of land potential, 29.15% is categorized as having low potential, 44.88% as having moderate potential, and 25.97% as having high potential. Furthermore, the precise delineation of land quality and potential for each land parcel within the database effectively caters to the information retrieval needs of land administrators and stakeholders. This research also seeks to contribute to the standardization of land databases at both the provincial and national levels, thereby bolstering land management efforts within the context of globalization, development, and climate change adaptation.

Geostatistics and GIS as a Technique for Chemical Soil Properties Mapping

Soil properties play a fundamental role in agriculture, and understanding their spatial distribution is essential for effective land management and increasing agricultural productivity. This study focuses on the application of geostatistics and Geographic Information Systems (GIS) as techniques for mapping soil properties, in the case of the Mozambique Sugar cane company (ADM) in Mafambisse, in the province of Sofala, Mozambique. The central objective is to demonstrate how geostatistics and GIS can be used to characterize and map soil properties. The research was materialized using field surveys that estimated the pH in the field of several sampling points at different depths in the irrigated perimeter of the ADM. Geostatistics is applied, using methods such as kriging and variogram analysis, allowing the creation of continuous maps that represent soil properties in unsampled locations. GIS is an essential tool for integrating geostatistical data and creating accessible and informative maps. The results of this study indicate that the combination of geostatistics and GIS offers an effective approach for mapping soil properties. This knowledge is crucial for Mozambique sugar cane company, an important company in the sugar industry, to optimize its agricultural practices, increase productivity and minimize environmental impacts. Thus, offering solid bases for making informed and sustainable agricultural decisions, contributing to efficient agricultural development in Mozambique and other regions with similar challenges.

Application of geographic information systems for zoning tourism clusters in the Voronezh Region: economic effect

The article examines the economic effect of using geographic information systems (GIS) to create tourism clusters in regions, such as the Voronezh Region, and considers how this approach in the study opens up new opportunities for attracting tourists and increasing economic activity. The article analyzes how GIS contributes to the formation of tourism clusters in the region and what economic benefits this brings. A tourism cluster is an association of tourism enterprises, services, and infrastructure in a specific geographical area. GIS zoning of clusters opens the way to synergy and interaction among industry participants, which helps to increase the attractiveness of the region for tourists and raise the economic potential in the development of the hospitality sector.

Application of Satellite Observation and GIS in Mapping Greenhouse Gases in Part Delta State, Nigeria

The present study aimed to apply satellite observation and Geographic Information System (GIS) to map GHGs in Delta State, Nigeria. Carbon monoxide (CO), nitrous oxide (N O), and sulfur dioxide (SO ) constituted the main GHGs studied. The2 2 datasets covering January 2019 to December 2022 were sourced from the archive of Copernicus Atmosphere Monitoring Service Emissions of Atmospheric Compound and Compilation of Ancillary Data. The Google Earth Engine framework, the inverse distance weighting interpolation algorithm in ArcGIS 10.8 software, and Microsoft Excel were deployed in data analyses. In general, the results showed remarkable seasonal oscillation in the mean concentration of CO, with peak values in January and February, while the lowest mean concentration was observed in October. Higher values of NO were observed2 from November to February and the lowest values in July. July also recorded the highest SO values, with the lowest mean2 observable atmospheric concentrations in August, in addition to remarkable insignificant values in 2020–2022. Besides, the 12 geospatial models (maps) also depicted the spatio-temporal distribution of CO, NO , and SO concentrations from 2019 to2 2 2022 for easy visualization and facilitation of workable policies towards global warming mitigation. The paper recommended the establishment of well-equipped and functional ground-based GHG observatories with early warning systems across the state. This will facilitate real-time GHG monitoring, early warning forecasts, and stimulate scholarship on global warming and climate change.

Low-Cost Data, High-Quality Models: A Semi-Automated Approach to LOD3 Creation

In the dynamic realm of digital twin modeling, where advancements are swiftly unfolding, users now possess the unprecedented ability to capture and generate geospatial data in real time. This article delves into a critical exploration of this landscape by presenting a meticulously devised workflow tailored for the creation of Level of Detail 3 (LOD3) models. Our research methodology capitalizes on the integration of Apple LiDAR technology alongside photogrammetric point clouds acquired from Unmanned Aerial Vehicles (UAVs). The proposed process unfolds with the transformation of point cloud data into Industry Foundation Classes (IFC) models, which are subsequently refined into LOD3 Geographic Information System (GIS) models leveraging the Feature Manipulation Engine (FME) workbench 2022.1.2. This orchestrated synergy among Apple LiDAR, UAV-derived photogrammetric point clouds, and the transformative capabilities of the FME culminates in the development of precise LOD3 GIS models. Our proposed workflow revolutionizes this landscape by integrating multi-source point clouds, imbuing them with accurate semantics derived from IFC models, and culminating in the creation of valid CityGML LOD3 buildings through sophisticated 3D geometric operations. The implications of this technical innovation are profound. Firstly, it elevates the capacity to produce intricate infrastructure models, unlocking new vistas for modeling digital twins. Secondly, it extends the horizons of GIS applications by seamlessly integrating enriched Building Information Modeling (BIM) components, thereby enhancing decision-making processes and facilitating more comprehensive spatial analyses.

Location-Based Management of Paleontological Collections using Open Source GIS Software

Management of Natural History collections, particularly paleontological collections, is usually structured around specimens. However, it might not be feasible when the collections are incorporated from sources where the whole cycle of specimen collection is unknown, making it hard to determine what fossils belong to a single specimen and if these specimens belong to a single fossil-assemblage, taxon or individual. The Sociedade de História Natural from Torres Vedras (Portugal) manages such collections using a management strategy approach based on the spatial location from where the fossils were found. To achieve this, we have implemented a methodology for field collection and developed a spatial database in PostgreSQL/PostGIS to manage the entire stages of paleontological collections management. On top of the database, a second layer of web services, Web GIS (Geographical Information System) applications, and desktop GIS, all based on QGIS, are also under development to facilitate access to data stored in the database to internal and external researchers and partners, as well public institutions. This effort is made in close collaboration with in-house actors and stakeholders and has yielded promising results. The development of this system provides four advantages: (i) it played an essential role in supporting the transfer of the collection to new storage facilities; (ii) it provides overviews of the distribution of the characteristics of the collections; (iii) it enhances institutional partnerships by providing consistent and reliable data and(iv) it supports the establishment and development of research lines.

Identification of Groundwater Potential Based on Remote Sensing and Geographic Information Systems in The City of Padang

Water is a basic need for living creatures, including humans. The need for water can be obtained from various sources, including: rainwater, surface water, or groundwater. The estimated quantity and distribution of water on earth is 97% of the water on earth is in the sea and the remaining 1.7% is at the earth's poles in the form of ice, 1.7% is underground water and only 0.1% is as water. surface and atmosphere. Padang City still lacks clean water, because Padang City PDAM water often experiences problems. So many people use drilled wells or dug wells. Therefore, it is very necessary to identify groundwater in Padang City. Identification of Padang City's groundwater potential in this research uses Remote Sensing data and Geographic Information Systems. The Geographic Information System application is used to identify groundwater potential through overlaying a tiered quantitative method on the parameters of vegetation density, land cover, soil texture, rock type, rainfall and slope to obtain the distribution of groundwater potential. The results of this research are that the groundwater potential in Padang City consists of several classes, namely no potential, low, medium and high. Groundwater potential in Padang City is dominated by low groundwater potential covering an area of 37,369,903 Ha, medium area covering an area of 25,159,745 Ha, high potential covering an area of 7,493.06 Ha and no potential area covering an area of 113,030 Ha. Based on validation using data from 59 drilled wells in Padang City which was overlaid with a groundwater potential map for Padang City, it was found that 11 (18.65%) drilled wells were not suitable and 48 (81.35%) drilled wells were suitable.

Kaedah dan Kegunaan dalam Perlaksanaan Integrasi BIM-GIS dan Potensinya dalam Pengurusan Sistem Saliran: Satu Tinjauan

The ability of Geographic Information System (GIS) applications to manage three-dimensional (3D) data is increasing along with advancements in current technology, and this ability can be further enhanced through the integration of Building Information Modeling (BIM) technology. While the combination of BIM and GIS technologies provides significant benefits to human life, there are several challenges and limitations that need to be addressed for successful implementation. Therefore, research on previous articles will be conducted to examine the challenges and potential of this integration. This paper will begin with searching for relevant previous articles using appropriate keywords on Web of Science and Scopus. The search will be conducted in two parts, articles related to BIM-GIS integration with keywords "BIM" AND "GIS," and articles concerning the usage of 3D data in GIS applications for drainage system management using keywords "GIS" AND "3D" AND "DRAINAGE." From these articles, observations will be made regarding (1) the structure of BIM-GIS integration data, (2) implemented integration methods, (3) utilization of integration models, and (4) the potential of BIM-GIS Integration in managing 3D drainage system data. The research identifies key challenges in BIM-GIS integration, including differences in class numbers, dissimilar class arrangement, geometry creation methods, and georeference system application. To address these challenges, standard protocols based on specific requirements need to be established by considering organizational needs to ensure a consistent integration process. The paper also recognizes significant potential in employing BIM-GIS integration for drainage system management.

Application of Geographical Information Systems in Sustainability in the Malaysian Context: A Review

The depletion of natural resources to meet growing demands for food, fuel, and fibre due to population growth and urbanisation has led to significant environmental damage in Malaysia. Hence, greenhouse gases have increased atmospheric greenhouse gas (GHG) levels, contributing to global warming and climate change. From developing software to analysing data, GIS is influenced by political, economic, and social factors throughout its production process. This paper introduces a structured framework aimed at conducting an extensive literature review study on the application of the Geographic Information System (GIS) to sustainability in Malaysia. The framework delineates essential steps and factors for identifying pertinent literature, assessing prior research, amalgamating outcomes, and pinpointing research voids. Adhering to this framework enables researchers to methodically scrutinise and appraise existing literature, furnishing a thorough depiction of the present state of knowledge within the application of GIS to sustainability in Malaysia. This literature review highlights GIS as a critical tool for promoting sustainable management across various domains, including flood hazard management, urban planning, agriculture, forest monitoring, transportation, air quality management, and water resource management, by providing access to data, models, and mapping.

ANALYSIS OF LANDSLIDE SUSCEPTIBILITY IN KLATEN REGENCY

Landslide disasters are frequently occurring events in Indonesia. The northern part of Klaten Regency, situated on the slopes of Mount Merapi, and the southern part, which directly borders limestone hills, are vulnerable to landslides due to their elevated terrain. This research aims to investigate the role of Geographic Information Systems (GIS) in analyzing, mapping, and identifying areas prone to landslide disasters. Mapping landslide susceptibility as a GIS application aims to be a disaster mitigation effort, thereby minimizing the resulting impacts and losses. The mapping is conducted based on the Puslattinak method, using several parameters such as rainfall, slope, rock types, land use, and soil types. This mapping employs a weighted multi-level analysis method, where each parameter has a different weight depending on its influence on landslide disasters. The results of this research include the Landslide Susceptibility Map of Klaten Regency in 2022. According to the research findings, Klaten Regency is divided into three susceptibility classes: low (17,868.23 hectares), medium (41,494.22 hectares), and high (10,533.96 hectares), with rainfall intensity being the most influential parameter

Image Quality Assessment of Multi-Satellite Pan-Sharpening Approach: A Case Study using Sentinel-2 Synthetic Panchromatic Image and Landsat-8

INTRODUCTION: The satellite's physical and technical capabilities limit high spectral and spatial resolution image acquisition. In Remote Sensing (RS), when high spatial and spectral resolution data is essential for specific Geographic Information System (GIS) applications, Pan Sharpening (PanS) becomes imperative in obtaining such data. 
 OBJECTIVES: Study aims to enhance the spatial resolution of the multispectral Landsat-8 (L8) images using a synthetic panchromatic band generated by averaging four fine-resolution bands in the Sentinel-2 (S2) images. 
 METHODS: Evaluation of the proposed multi-satellite PanS approach, three different PanS techniques, Smoothed Filter Intensity Modulation (SFIM), Gram-Schmidt (GS), and High Pass Filter Additive (HPFA) are used for two different study areas. The techniques' effectiveness was evaluated using well-known Image Quality Assessment Metrics (IQAM) such as Root Mean Square Error (RMSE), Correlation Coefficient (CC), Erreur Relative Globale Adimensionnelle de Synthèse (ERGAS), and Relative Average Spectral Error (RASE). This study leveraged the GEE platform for datasets and implementation.
 RESULTS: The promising values were provided by the GS technique, followed by the SFIM technique, whereas the HPFA technique produced the lowest quantitative result. 
 CONCLUSION: In this study, the spectral bands of the MS image’s performance show apparent variation with respect to that of the different PanS techniques used.

Suitability and Carrying Capacity of Aquatic Environment for Shrimp Culture in Sarjo District, Pasangkayu Regency West Sulawesi

The potential of coastal and marine resources in Indonesia is so diverse both in terms of quantity and quality, should be able to contribute greatly to the economic growth of the State of Indonesia. The purpose of this stydy is to assess the level of land suitability and carrying capacity of the pond environment for shrimp culture in Sarjo District Pasangkayu Regency. The research was conducted using survey method, measuring biological, physical and chemical parameters. The observed data consisted of temperature, turbidity, TSS, current direction and speed, tides, pH, salinity, dissolved oxygen, ammonia, nitrate, nitrite, phosphate, BOD, COD, BOT, and plankton. Based on biological, physical and chemical data, an analysis of the suitability of the pond area was carried out using the geographic information system (GIS) Arc View GIS Application Version 3.3. The results of the level of suitability of land for shrimp culture in Sarjo District was very suitable 154.88 hectare; 2) Suitable 77.16 hectare and quite suitable 27.26 hectare. Overall land for aquaculture in each area is traditional 732.95 hectare, semi-intensive 1,589.12 hectare and intensive 247.83 hectare. The environmental carrying capacity of intensive shrimp cultivation ponds with an estimated maximum production of 42.63 tons ha-1, with a permitted pond area that does not exceed the environmental carrying capacity is 166.07 ha; semi-intensive cultivation with a maximum production of 153.49 tons ha-1 MT-1, the permitted pond area so as not to exceed the environmental carrying capacity is 597.85 hectare, traditional cultivation with a maximum production of 3.4 tons MT-1 with a supported pond area of 2,569 ha in Sarjo District, Pasangkayu Regency.

Analysis of Distribution Patterns of Environmental Risk Factors with Malaria Incidents in the Working Area of the Tanjung Tiram Community Health Center, Batu Bara Regency

<p><em>Environmental conditions have a big influence on the incidence of malaria because a bad environment can increase the breeding and proliferation of Anopheles mosquitoes. The aim of this research is to determine environmental risk factors and distribution patterns of malaria in the Tanjung Tiram Community Health Center working area, Batubara Regency. This research method is analytical observational with a case control research design and an ecological approach. This research was conducted in the working area of the Tanjung Tiram Health Center, Batu Bara Regency, which was carried out from April to July 2023. Population 40,604 people. The sampling technique was purposive sampling so that the research sample was 100 people. Data collection uses questionnaires and observation sheets. Data analysis using the bivariate Chi square test on SPSS version 20 software and Analysis of malaria case distribution mapping using the Geographic Information System (GIS) application to describe the distribution pattern of malaria in Batubara Regency. The results of the study show that there is a relationship between environmental risk factors such as ceilings (p-value=0.000), wall type (p-value=0.000), ventilation (p-value=0.000), wall density (p-value=0.000), partitions on windows (p-value=0.000), the presence of puddles (p-value=0.000), gutters (p-value=0.000) and swamps around the house (p-value=0.000). The distribution of Malaria cases in Tanjung Tiram District, Batubara Regency is not spread across all areas in the district, this means that the highest number of malaria cases occur in mixed plantation areas. By depicting the distribution pattern in the form of a map, it can optimize the reduction in the incidence of malaria cases.</em></p><p><em> </em></p><strong><em>Keywords: Environment, Geographic Information System, Malaria</em></strong>

Geographic Information System (GIS) Application in Soil Fertility Management: A Review

As the global population expected to reach 10 billion by 2050 and arable land decreases, innovative soil management strategies are required to maximize agricultural productivity while preserving natural resources. GIS, as a powerful technology, offers a comprehensive solution by enabling the collection, storage, analysis, and visualization of spatial data for agricultural purposes. By integrating GIS with sensors, communication technologies, and data analytics, precision agriculture is possible, allowing for efficient use of agricultural inputs and reduced environmental impact. GIS technology facilitates the simulation and modeling of biological ecosystems, providing valuable insights for sustainable soil management. It has diverse applications in agriculture, ranging from soil nutrient mapping to yield estimations and runoff detection. GIS works by overlaying various layers of information onto digital maps, allowing for the identification of relationships and patterns that are crucial for optimizing soil fertility. Detailed maps created through GIS highlight the distribution of soil nutrients, pH levels, and moisture content, enabling informed decision-making on fertilizer use, irrigation techniques, and land management practices. By harnessing the power of GIS, farmers and land managers can make data-driven decisions that maximize agricultural productivity, conserve resources, and protect soil health for future generations. The integration of GIS with other technologies further enhances its effectiveness in soil fertility management. Overall, GIS is a valuable tool for understanding and managing soil fertility, contributing to sustainable agriculture and food security.

Behind Every Good Lie Is a Grain of Truth

Abstract Drawing on the experiences of the 2020 Taiwanese and Moldovan presidential elections, this article develops a framework to better understand whether certain aspects of identity can predict a constituency’s demand for foreign disinformation during contentious election cycles. The model bridges key tenets of Monroe E. Price’s “market for loyalties” metaphor with geographic information system applications to identify areas where a constituency’s willingness to exchange loyalty for disinformation is expected to be salient within these postimperial polities. The article concludes by outlining the theoretical implications for focused policy interventions in Taiwan and Moldova.