Geographic Information System Technology Research Articles

ESTABLISHING MANGROVE FOREST PRODUCTS FOR ECO-TOURISM ACTIVITY AT KOTA KINABALU WETLAND RAMSAR SITE, SABAH. MALAYSIA

Mangrove forests are found ubiquitously across the global landscape and are known to assume a pivotal role in supporting the surrounding ecosystem. The study purposely estimates the ability of absorption in CO2 towards the subject area to understand the precautions of visitors in future demand. By leveraging the advanced technology of Geographic Information Systems (GIS) and employing carbon footprint analysis, the study estimated the daily footfall to the area and the resultant carbon footprint. The analysis conclusively revealed a surplus of minus 7,957.65 tons/year, indicating that the area can assimilate more CO2. This underscores the wealth of natural resources and the potential to accommodate a larger number of visitors in the future.

Soil Erosion Risk Analysis in the Ría de Arosa (Pontevedra, Spain) Using the RUSLE and GIS Techniques

Soil erosion in coastal areas, driven by global change and human activity, poses a significant threat to ecological and economic stability. This research investigates water erosion in the southeast of the Ría de Arosa (Pontevedra, Spain), utilizing the Revised Universal Soil Loss Equation model and Geographic Information System technologies. Key factors analyzed include rainfall erosivity, soil erodibility, topography, land cover, and conservation practices. High-resolution maps (1 × 1 m pixels) identified areas at high risk of erosion. Vulnerable zones, such as coastal cliffs and vineyards, show severe erosion rates exceeding 50 t/ha/year (>5 mm/year), with the most extreme zones reaching up to 200 t/ha/year (>200 mm/year). These results emphasize that intervention could be required or recommended. Suggested measures include reforestation, effective agricultural land management, or the implementation of vegetative barriers to reduce erosion. These areas, characterized by steep slopes and sparse vegetation, are particularly susceptible to soil loss, necessitating specific conservation efforts. The results underscore the need for sustainable coastal management practices and preventive strategies to protect this vulnerable coastal zone. Implementing these measures is crucial to mitigating the impacts of soil erosion, preserving natural resources, and ensuring long-term ecological and economic resilience in the region.

Applications of Marine Geographic Information Systems (GIS) in Ocean Surveying

This paper explores the key applications of Geographic Information Systems (GIS) in the field of marine surveying. GIS, as a powerful geospatial analysis tool, has played a significant role in marine surveying and ocean resource management. This paper begins by introducing the basic concepts of GIS and the importance of marine surveying. It then delves into four key application areas of GIS in marine surveying: marine map production, seafloor topography analysis, marine environmental monitoring, and ocean resource management. Each application area covers specific use cases and advantages of GIS technology. Finally, the paper summarizes the significant role of GIS in marine surveying and looks ahead to future developments.

Enhancing Fishing Efficiency with Geographic Information System and Optimized Methods

Traditional fishing techniques frequently lack efficiency and optimization, resulting in fishermen obtaining unsatisfactory yields. This study presents a novel approach by incorporating Geographic Information System (GIS) technology, notably utilizing Leaflet, to improve fishing techniques. The suggested system incorporates a LoRa node tool that logs the journeys of fishermen, offering comprehensive itineraries and data on the distribution of fish and unfavorable weather conditions. Notable outcomes were attained by employing the haversine approach to compute distances between the LoRa Gateway and different data points. The approach exhibited a negligible error margin of 0.157% in contrast to the calculations performed in Excel. In addition, the GPS accuracy testing produced remarkable results, with latitude and longitude errors of 0.000116% and 0.000002%, respectively. The LoRa system demonstrated a range of RSSI performance, with values ranging from -57 dBM at 50 meters to -121 dBM at 1500 meters. This range of performance guarantees dependable transmission of data over significant distances. The findings underscore the GIS-based strategy's efficacy in enhancing the effectiveness and precision of conventional fishing methods, presenting a promising technical improvement for the fishing sector.

Promoting the sustainable development of CCUS projects: A multi-source data-driven location decision optimization framework

Carbon Capture, Utilization, and Storage (CCUS) technology is vital for achieving global carbon reduction targets. However, the uncertainties in technology and economic viability are influenced by location. To promote the sustainable development of CCUS technology, the study proposes a data-driven framework for optimizing location decisions. Firstly, the framework considers multiple factors, including geospatial data on resources, risks, power production, transportation, and environment. It also evaluates qualitative and quantitative data across economic, social, environmental, and technological dimensions. Secondly, the two-stage model is conducted as follows: Using Geographic Information System (GIS) technology, the first stage identifies suitable regions for CCUS projects, while the second stage prioritizes these regions using the TODIM method. Further, validated in China, the Junggar Basin, Tarim Basin, Ordos Basin, Sichuan Basin, and Bohai Rim Basin are identified as suitable for CCUS deployment. The Huaneng Luohuang Power Plant is the most conducive location for CCUS projects as pilot demonstrations. Final sensitivity analysis, scenario analysis, and comparative analysis have respectively affirmed the stability, dynamism, and reliability of the model. These analyses have also been instrumental in elucidating the final preferred outcomes under various decision-making preferences and strategic orientations. The framework for decision-making and data-driven priority model for CCUS projects layout proposed in the study can provide technical support and practical evidence for decision-makers in planning CCUS projects and formulating supportive policies.

Application of UAV Technology for Vegetation Community Identification in Coastal BRIS Wetland

Unmanned aerial vehicles (UAV) based methods for reconnaissance activities aim to update wetlands’ health status and are safer and cost-effective considering that wetlands normally have saturated soils, dense vegetation and wildlife. Vegetation survey work in wetland areas needs many staff to ensure the safety of researchers and equipment. This paper describes the application of UAV technology to identify and demarcate vegetation communities in a dense BRIS (beach ridges interspersed with swales) coastal wetland. The methodology employed in this research has two steps. The first step involves the utilisation of UAV imagery and Geographic Information System (GIS) technology. The second step entails ground truthing, which involves validating tree species using 15 quadrants. The utilisation of UAVs in conjunction with ArcGIS 10.3 demonstrated that the unique characteristics of tree canopy morphology and tree heights could be assessed and analysed. The UAV-GIS results are compared to ground truthing results to validate tree communities’ demarcation. The findings indicate that integrating two datasets, particularly tree canopy morphology and tree height, produced an acceptably accurate vegetation community demarcation. The tree canopy form of Hibiscus tiliaceus (Bebaru) was differentiated from the canopies of Acacia mangium and Nypa fruticans by analysing the image. The tree height analysis involved using ArcGIS 10.3 software to generate the digital surface model (DSM) and digital terrain model (DTM). Validation results indicate an 87% accuracy in the demarcation work. Hence, identification and demarcation of the vegetation communities could be achieved by utilising both tree canopy morphology and tree height data obtained from UAV.

Quantifying the influencing factors of the thermal state of permafrost in Northeast China

In Northeast China, permafrost is controlled by a combination of biotic, climatic, physiographic, and anthropogenic factors. Due to the complexity of these governing or influencing factors, it is challenging to exactly describe the features of the Xing’an permafrost in Northeast China. By integrating remote sensing (RS) and geographic information system (GIS) technologies, we have quantified these influencing factors of permafrost changes as an important approach to understanding the nature of latitudinal and mountain permafrost in Northeast China at the mid-latitudes in the Northern Hemisphere. In this study, we combine Geographical Detector (Geodetector) model, trend analysis, and multi-source RS data to quantify the controlling or influencing factors of permafrost thermal state and of permafrost changes, and explain the interactions among permafrost, environment, and climate. The results indicate that, at the regional scale, changes in the thermal state of permafrost are primarily governed or influenced by mean annual land surface temperature (MALST), precipitation, and snow cover duration (SCD). Topographic factors also affect the spatial patterns of permafrost development. Additionally, in the context of climate warming, the insulation effect of snow cover on the permafrost is weakened, or has been weakening. Moreover, the interactive effects among various factors significantly enhance their explanatory power for changes in the thermal state of permafrost. The study emphasizes the complexity of the interactions among permafrost, climate, and the environment, and highlights the significance of understanding these interactions for regional socio-economic development, ecological management, carbon pool stabilization, and research on future climate change in Northeast China.

The Spatial Pattern Evolution of Urban Innovation Actors and the Planning Response to Path Dependency: A Case Study of Guangzhou City, China

The capacity for urban innovation is a significant symbol of contemporary urban development. In order to promote sustainable urban innovation, it is crucial to match and optimize innovation spaces, actors, and their behavioral needs. Based on the data from patent inventions, which are commonly used to represent urban innovation, in this study, we investigated the formation mechanism of Guangzhou’s innovation pattern and its characteristics from 1990 to 2020 using Geographic Information System (GIS) technology. The results indicated that Guangzhou’s innovation spaces developed a center-radiation structure of “two districts and seven cores”. We investigated the path dependence of spaces, actors, and behavioral needs by examining the interaction between the innovation space layout and behavioral needs. The findings provide theoretical support for the city’s sustainable development in terms of innovation in the future.

Within the Range of the Watchtowers: Nature and Purpose of Late Bronze Age Hilltop Buildings in the Blagoevgrad Basin, Southwestern Bulgaria

Abstract The Struma/Strymon River valley, due to its key geographical position, carving a corridor in mountain massifs, served as a natural communication route between the north: south-eastern and central Balkans and further on – Central Europe, and the south: the coast of the Aegean Sea. The lack of detailed studies of the settlement pattern have not allowed for complete characterization of its role in the cultural contacts of prehistoric communities. Fortunately, this state of research is changing, due to the carrying out intensive field surveying, and recording of archaeological sites. As a result of it, evidence of the flourishing of settlements in the Late Bronze Age and the transition period between the Bronze Age and the Iron Age were recorded. In addition to flat settlements, “atypical” sites were also identified – called the Kamenska Chuka-type, named after the first discovered site of this type, located in naturally defensive and hard-to-reach places with a wide observation views. From the very moment of discovery, researchers have been speculating about the functions of these archaeological sites. The aim of this article is to attempt to explain some issues – nature and purpose related to Kamenska Chuka-type sites and verify the theses put forward by researchers of the topic, using geographic information system (GIS) technology and freely available spatial data, combining them with traditional archaeological data.

The spatial-temporal distribution of hepatitis B virus infection in China,2006–2018

ObjectivesHepatitis B is a liver disease caused by Hepatitis B virus (HBV) infection and is highly prevalent in China. To better understand the epidemiological characteristics of hepatitis B in China and develop effective disease control strategies, we employed temporal and spatial statistical methods.MethodsWe obtained HBV incidence data from the Public Health Science Data Center of the Chinese Center for Disease Control and Prevention for the years 2006 to 2018. Using Geographic Information System (GIS) and SaTScan scanning technology, we conducted spatial autocorrelation analysis and spatiotemporal scan analysis to create a map and visualize the distribution of hepatitis B incidence.ResultsWhile hepatitis B incidence rebounded in 2011 and 2017, the overall incidence in China decreased.In the trend analysis by item, the incidence varies from high to low. The global spatial autocorrelation analysis revealed a clustered distribution, and the Moran index analysis of spatial autocorrelation within local regions identified five provinces as H-H clusters (hot spots), while one province was an L-L cluster (cold spot). Spatial scan analysis identified 11 significant spatial clusters.ConclusionsWe found significant clustering in the spatial distribution of hepatitis B incidence and positive spatial correlation of hepatitis B incidence in China. We also identified high-risk times and regional clusters of hepatitis B incidence.

Utilizing Deep Learning and Spatial Analysis for Accurate Forest Fire Occurrence Forecasting in the Central Region of China

Forest fires in central China pose significant threats to ecosystem health, public safety, and economic stability. This study employs advanced Geographic Information System (GIS) technology and Convolutional Neural Network (CNN) models to comprehensively analyze the factors driving the occurrence of these fire events. A predictive model for forest fire occurrences has been developed, complemented by targeted zoning management strategies. The key findings are as follows: (i) Spatial analysis reveals substantial clustering and spatial autocorrelation of fire points, indicating high-density areas of forest fire occurrence, primarily in Hunan and Jiangxi provinces, as well as the northeastern region. This underscores the need for tailored fire prevention and management approaches. (ii) The forest fire prediction model for the central region demonstrates exceptional accuracy, reliability, and predictive power. It achieves outstanding performance metrics in both training and validation sets, with an accuracy of 86.00%, precision of 88.00%, recall of 87.00%, F1 score of 87.50%, and an AUC value of 90.50%. (iii) Throughout the year, the occurrence of forest fires in central China varies by location and season. Low-occurrence periods are observed in summer and winter, particularly in Hunan and Hubei provinces, due to moderate weather conditions, agricultural practices, and reduced outdoor activities. However, spring and autumn also present localized risks due to uneven rainfall and dry climates. This study provides valuable insights into the dynamics of forest fire occurrences in central China, offering a solid framework for proactive fire management and policy formulation to effectively mitigate the impacts of these events.

Enhancing Cybersecurity through the Integration of Geographic Information Systems Technologies

Enhancing Cybersecurity through the Integration of Geographic Information Systems Technologies

Land use hierarchical mapping for delineation of groundwater potential zones in the Ba river basin using satellite imagery and GIS technology

Abstract The evaluation of groundwater potential is crucial for the best use and replenishment of groundwater resources, as well as for the appropriate growth and administration of a region. To study groundwater potential, it is necessary to analyze the factors that directly affect this resource. In addition to the criteria that contribute to the formation of groundwater, such as rainfall, land cover, geology, slope, etc., land use types and their infiltration capacity are also the main factors affecting the groundwater prospect. In recent years, remote sensing and geographic information systems (GIS) have emerged as the most important technologies in the field of groundwater research, which aid in determining groundwater potential. This paper presents a method to generate the land use hierarchical map based on the level of impact on the formation of groundwater in the Ba river basin using GIS technology and remote sensing. According to the classification result, the three classes of groundwater potential zones including “low”, “moderate”, “high” occupy 1.51%, 77.43%, and 21.06% of the study area respectively. The findings can be validated with the actual groundwater level at some locations that are evenly distributed throughout the basin. The obtained results indicate that there is an agreement between groundwater potential levels at each actual location and those depicted on the land use hierarchical map. The methodology utilized in this study is reliable, accurate and can be used to generate hierarchical maps of additional parameters. This paper will be a useful document for groundwater potential zoning in the study area

Research on the construction of intangible cultural heritage corridors in the Yellow River Basin based on geographic information system (GIS) technology and the minimum cumulative resistance (MCR) model

Objectively and accurately identifying the spatial structure and protection scope of intangible cultural heritage and constructing intangible cultural heritage corridors are crucial for the comprehensive systematic protection of intangible cultural heritage and the synergistic development of the region. However, the current research on intangible cultural heritage is limited to the protection and development of intangible cultural heritage in specific locations or specific areas. Thus, systematic and holistic research perspectives are relatively limited. Therefore, this study employs geographic information system spatial analysis and the minimum cumulative resistance model to construct an intangible cultural heritage corridor in the Yellow River Basin. This study aims to establish a systematic protection method and framework for intangible cultural heritage. The results show the following: (1) The intangible cultural heritage in the Yellow River Basin has a large-scale centralized distribution and small-scale scattered distribution, which provides an important spatial basis for the construction of intangible cultural heritage corridors. (2) Overall, intangible cultural heritage corridors can be more effectively constructed in the eastern region of the Yellow River Basin than in the western region, with 84.6% of the area being suitable and 15.4% being unsuitable. (3) Based on the suitability analysis, the "18 + N" corridor system of intangible cultural heritage in the Yellow River Basin, distributed across the eastern, central and southern regions, is constructed. The major corridor has a suitable width of 60–100 km, a total length of 11,935 km, and an area of 625,976 km2–919,942 km2, and can connect 634–711 intangible cultural heritage sites in series. On this basis, this study proposes a multilevel construction system for intangible cultural heritage corridors in the Yellow River Basin that integrates the "network structure–spatial scope" and "element–axis–region" levels. This approach culminates in a pattern of intangible cultural heritage protection and development in the Yellow River Basin characterized by "connecting points into lines, distributing in groups, and linking regions." This study reveals that combining geographic information system spatial analysis tools with a minimum cumulative resistance model effectively identifies potential heritage corridor networks and clarifies the hierarchical relationships of heritage element protection in the study area. This approach provides a reference model for the comprehensive protection and systematic development of intangible cultural heritage in the Yellow River Basin. Furthermore, the effectiveness and universality of this framework make it applicable to the protection and development of other similar international heritage areas.

Preparing Cadastral Map Databases for Mosul District

Investigates the development and implementation of digital cadastral map databases for Mosul District, Iraq, addressing the transition from traditional paper-based systems to modern geospatial technologies. The research explores the integration of Geographic Information Systems (GIS), remote sensing, and Global Positioning System (GPS) technologies to enhance cadastral mapping processes. Encompass data collection from diverse sources, including high-resolution satellite imagery, aerial photography, and existing cadastral maps. A comprehensive analysis of data types— vector, raster, Triangulated Irregular Network (TIN), and tabular—is conducted to establish an optimal database structure. The study delineates the technical capabilities of GIS in data processing, spatial analysis, and model preparation, emphasizing the importance of data accuracy and consistency. A systematic approach to data entry, including map scanning, georeferencing, and digitization, is presented. The research outlines the creation of a multi-layered geographic database, incorporating both spatial and descriptive data. Protocols for database updating using satellite imagery and field surveys are developed, ensuring the currency and reliability of cadastral information. The results demonstrate significant improvements in data management, spatial analysis capabilities, and information accessibility compared to traditional methods. The study concludes that digital cadastral databases offer enhanced decision-making support for land administration and urban planning in Mosul District. Contributes to the body of knowledge on modernizing cadastral systems in developing regions, providing insights into technological integration, data standardization, and the challenges associated with transitioning to digital cadastral management systems. The findings have implications for policy makers and land administrators seeking to implement similar systems in comparable urban contexts.

HISTORICAL AND CULTURAL HERITAGE OF BUNDELKHAND REGION CONSERVATION, VISUALIZATION, USING G.I.S TECHNOLOGIES

This research paper investigates the conservation, visualization, and study of Bundelkhand's historical and cultural heritage using Geographic Information Systems (GIS) technologies. Located in central India, Bundelkhand is renowned for its rich historical sites, including ancient temples, forts, and palaces. These sites face significant preservation challenges due to environmental degradation, neglect, and socio-economic constraints. This study explores the application of GIS technologies in documenting, analyzing, and visualizing Bundelkhand's heritage. GIS offers powerful tools for creating detailed inventories, assessing the physical condition of structures, monitoring changes, and enhancing public engagement through immersive visualizations. The paper highlights the transformative potential of GIS in heritage conservation through case studies of the Khajuraho temples and the Orchha Fort Complex, demonstrating how GIS facilitates comprehensive documentation, condition assessment, and informed conservation strategies. While GIS technologies present numerous benefits, such as enhanced data integration and improved spatial analysis, challenges related to data accuracy, technical expertise, and resource constraints must be addressed. The study underscores the need for a balanced approach that combines traditional conservation methods with advanced GIS technologies to ensure the sustainable preservation of Bundelkhand's cultural legacy. By leveraging GIS, conservationists, researchers, and policymakers can safeguard Bundelkhand's heritage, promote sustainable tourism, and foster a deeper appreciation for the region's rich cultural history. This research contributes to the broader discourse on digital transformation in heritage conservation, emphasizing the critical role of GIS in preserving and promoting cultural heritage in the digital age.

The investigation of traffic flow prediction and optimization based on Spark

Spark and flink have made great strides in big data processing in recent years. Although the current spark can process a large amount of data at the same time, it still has a lot of shortcomings in the transparency, credibility, and practicality of the model. This paper provides a comprehensive overview of how to tackle the performance bottlenecks, insufficient model interpretability, and lack of regional adaptability faced by Spark and Flink in big data processing. It discusses the introduction of interpretable algorithms such as SHAP and LIME to enhance the transparency and user trust of neural network models. Then it discusses how to combine time-aware transfer learning and Geographic Information Systems (GIS) technology to enhance the technology generalization and adaptability of Spark machine learning models. Time-aware transfer learning uses historical datas temporal evolution to ensure models perform well in new time periods or scenarios, while GIS technology enables more precise predictions and analyses based on geographical data, enhancing spatial adaptability. Lastly, the study explores hybrid processing strategies by integrating Apache Flink, Kafka Streams, and Spark batch processing frameworks. This approach not only facilitates efficient real-time data processing and detailed analysis but also enhances the models flexibility and processing capabilities in complex data scenarios. By integrating these techniques, it is possible to improve the efficiency and effectiveness of big data processing frameworks in addressing complex real-world challenges, thereby advancing technology and application development in related fields.

GIS and GNSS Integration Techniques for Earth Observations

Abstract: The term "GNSS," or global navigation satellite system, refers to any satellite navigation system with global coverage. To determine your current location, GNSS devices and receivers employ geolocation information from satellite navigation systems. Trilateration is the basis for how navigation satellites operate. An object's position on the spheroid is defined by its latitude, longitude, and altitude above mean sea level. Today, the utilisation of Global Navigation Satellite Systems (GNSS) technology is required for a wide range of uses, including engineering, cities, and defence. Geographic Information Systems (GIS) can be integrated with GPS to create powerful tools for mapping and spatial analysis. This integration allows for precise display of geographic characteristics on maps, land use planning, response to emergencies, and management of natural resources. Precision agriculture is one area where GNSS and GIS are integrated, enabling farmers to gather precise position data while operating machinery. GNSS and GIS integration can be done through position-focused and technology-focused integration. Position-focused integration uses GNSS technology to locate items or features on the earth's topography, while technology-focused integration enhances the utility and accuracy of GNSS data using GIS applications and technology. Both forms of integration provide potent solutions for various industries.

Evaluating land suitability for kemiri (Aleurites moluccana) as a multi-purpose tree species in community agroforestry land within Langkat District, North Sumatra

Evaluating land suitability for Aleurites moluccana in community agroforestry land within Langkat District, North Sumatra, is crucial for promoting sustainable development, enhancing livelihoods, and preserving ecosystems while honoring local traditions and cultures. The primary objective of this research was to evaluate and map the land suitability for A. moluccana within Langkat District, located in North Sumatra, Indonesia. To gather the necessary data, this study employed a survey method, involving the collection of soil samples from ten distinct land units within the field. The assessment of land suitability was carried out using the matching method. Geographic Information System (GIS) technology was utilized to create maps illustrating the distribution of land suitability, while a Global Positioning System (GPS) was employed to accurately record the coordinates of the collected soil samples. The findings revealed that within Gunung Ambat, Simpang Kuta Buluh, Rumah Galuh, and Telagah Village, the actual land suitability classes for A. moluccana were classified as moderately suitable (S2) and marginally suitable (S3). The prevailing limiting factors in this region were temperature (tc) and the characteristics of the root zone medium (rc). Consequently, this influenced the potential land suitability classes for A. moluccana, resulting in classifications ranging from highly suitable (S1) to moderately suitable (S2) and marginally suitable (S3). By implementing land suitability evaluation for A. moluccana in community agroforestry land, promoting sustainable land use, enhancing livelihoods, and conserving natural resources.

Research on the Application of Geographic Information Systems in the Construction of Smart Cities

With the continuous deepening of globalization and informatization, the construction of smart cities is gradually becoming a core strategy in the process of urban modernization. In this strategy, Geographic Information Systems (GIS) play a crucial technical support role. This article adopts a case study method, taking the construction of a smart city in Nanjing as the specific research object, and deeply explores the practical application of GIS in key fields such as urban planning, environmental protection, and traffic management. Through comprehensive analysis of these examples, this article systematically summarizes the significant achievements of GIS technology in improving urban management efficiency, optimizing decision support systems, enhancing public service levels, and promoting sustainable urban development. The research results indicate that GIS technology provides solid data support and decision-making support for the core areas of cities through precise integration and analysis of geographic information. GIS technology not only optimizes the layout of urban infrastructure, but also significantly enhances the city's response to emergency events through real-time monitoring and dynamic simulation, while promoting efficient allocation and utilization of urban resources. The research conclusion points out that, GIS technology is the cornerstone of smart city construction, greatly enhancing the scientific and forward-looking nature of urban management. The effective application of GIS has opened up new avenues for intelligent and refined urban management, significantly improving the quality of life of residents and providing solid technical support for the sustainable development of cities.