Geographic Information System Technology Research Articles

Measuring Accessibility and Optimising Logistics of Marginal Land Grass Biomass in the Case of Northern Ostrobothnia, Finland

Abstract Grass biomass originating from marginal agricultural land unsuitable for food production can be utilised in variety of bio-based productions. The key profitability constraints for such productions are regional availability and transport costs. The aim of this paper is to methodologically test open access agricultural field parcel data – enabled by the EU INSPIRE directive – integrated with the road network in measuring biomass accessibility and optimising collection and transport using geographic information system (GIS) technology in two Finnish case areas. The analytical framework applies closest facility and vehicle routing analyses for tractor and truck transport scenarios. The key finding is that the area of field parcels and the amount of biomass accumulating within an observed area are not the only important factors influencing transport efficiency: cost-effectiveness of collection routes can be equally high in regions with scarce and abundant biomass areas.

Forest Fire Dynamics in Nepal’s Mid-hills: Insights from Spatial Analysis and Risk Mapping of Doti District

Forest fires have significantly contributed to forest degradation and pollution all over Nepal. Despite their high severity, limited studies have been conducted on the spatial-temporal analysis and risk mapping of these fires especially in the Mid-hill region. This study aims to fill this gap by analyzing Visible Infrared Imaging Radiometer Suite (VIIRS) data from 2012 to 2022, along with satellite imagery, using remote sensing and geographic information systems (GIS) technology. Nine variables, including land class, distance to roads, proximity to settlements, temperature, wind speed, precipitation, slope, aspect, and elevation, were utilized to identify forest fire patterns and create a fire risk map. A multi-parametric hierarchical weighted index model was employed, with multicollinearity checked (VIF<2) to ensure model accuracy and validated by Area Under Curve (AUC=0.787). The study revealed an increasing trend of forest fires, particularly during March to May, in broad-leaved forests near human interference. Out of the total forested area of 1447.58 km2, 42.9%, 46.03%, and 11.07% were classified under high, moderate, and low-risk zones, respectively. The study emphasizes the recurring forest fire problem in often-neglected Mid-hill districts and underscores the need to prioritize them in future strategies.

Agrivoltaic systems potentials in Sweden: A geospatial-assisted multi-criteria analysis

Agrivoltaic systems represent an intelligent solution combining electricity production from solar photovoltaic technology with agricultural production to avoid land use conflicts. Geographic Information System technologies can support the implementation and spread of agrivoltaic systems by identifying the most suitable areas using useful spatially explicit information concerning techno-agro-socio-economic criteria.In this study, we have developed a procedure to identify and classify suitable areas for agrivoltaic systems in Sweden. An Ordinal Priority Approach based multi-criteria decision-making algorithm is established to calculate the weights of the selected evaluation criteria through expert interviews. The land use data refers to the Corine Land Cover 2018 product.The results show that about 8.6% of the Swedish territory, approximately 38,485 km2, is suitable for installing agrivoltaic systems. Among this area, about 0.2% is classified as “excellent”, about 15% as “very good”, about 72% as “good”, about 13% as “moderate”, and about 0.1% as “poor”. Most “excellent”-classified areas are in Kalmar, Skåne, and Gotland. In contrast, most “very good” sites are in Skåne, Kalmar, and Östergötland.By deploying vertically mounted agrivoltaic systems with bifacial photovoltaic modules, the total potential installed capacity for “excellent” areas is about 2.5 GWp, while for areas classified “excellent” and “very good” is about 221 GWp. The total “excellent” areas can potentially supply about 2.4 TWh of electricity against the electricity consumption in 2021 of about 143 TWh. On the other hand, the land classified as “excellent” and “very good” could potentially provide about 207 TWh. The County of Västra Götaland shows the greatest potentials in terms of total potential electricity supply from agrivoltaic systems with about 227 TWh, followed by Skåne with a total potential of 206 TWh.

GIS Approach for Expressing Structural Landforms: Forms, Elements, and Relationships

A structural landform is defined by its surface morphology, controlled by tectonics, lithology (arrangement and resistance), and folded structures, and demonstrated by the characteristics and relationships between geological and geomorphic elements. It is very important to use geographic information system (GIS) technology to accurately describe and express elements of structural landforms and their relationships. In this study, a GIS approach for expressing structural landforms, based on “forms–elements–relationships”, was developed. The contributions of this paper are as follows: (1) Combined with the surface morphological characteristics, the structural landforms were abstracted into geological and geomorphic elements, and the characteristics and relationships of these elements were analyzed. (2) The elements of structural landforms and their relationships were abstracted into spatial objects and topological relationships. The spatial objects of the structural landform were designed based on the types and characteristics of structural landform elements. The topological relationships were developed based on the definition of the structural landform morphotype. (3) The structural landform markup language (SLML) method of “forms–elements–relationships” was created. (4) Two typical structural landforms, namely, Qixia Mountain and Gaoli Mountain, were used as examples to verify the feasibility and effectiveness of the GIS approach for expressing structural landforms. This paper describes and expresses the “forms–elements–relationships” of structural landforms from the perspective of GIS, which is expected to promote the joint development of structural geomorphology and GIS.

The photovoltaic potential for electric vehicle charging along highways: A Dutch case study

AbstractThe large‐scale deployment of photovoltaics (PVs) along highways has the potential for the generation of clean electricity without competing for land use or burdening the power grid since energy for electric vehicles (EVs) can be generated locally on wastelands along highways near service stations. An analysis was carried out to evaluate the feasibility of integrating vertical bifacial solar modules into noise barriers. The approach involved integrating geospatial data with PV potential data using geographic information systems (GIS) technology. The results show a potential of around 200 GWh/year if all current noise barriers along highways in the Netherlands are considered suitable for PV module integration. Three case studies have been analysed regarding specific service stations for specific road orientations. It is shown that solar energy can charge more than 300 vehicles per day by combining bifacial PV noise barriers and standard mono‐facial PV modules on publicly available land along the highway in all three case studies, which is sufficient to meet 80% of the expected EV charging demand along highways in 2030.

Effects of web geographic information system (GIS) technology and curriculum approaches on education for disaster risk reduction

Abstract. Disaster risk reduction education (DRRE) is a strategy to mitigate the harmful effects of disasters. The implementation of DRRE in schools is on the rise, and web geographic information system (GIS) technology in DRRE is becoming increasingly prevalent. However, little knowledge exists about whether students can improve their understanding of disaster risk reduction (DRR) through web GIS technology and which factors affect their learning of web hazard maps. This study has provided materials and curricula for DRR education in Chinese and Japanese high schools and utilized them eight times in the classroom between 2020 and 2022. These classes had three forms of implementation due to the COVID-19 pandemic: online, on-site and online–on-site mixed. The students first answered a pretest. Then they learned about DRR using the explanatory web pages and the web hazard maps by answering quizzes shown on the pages. After that, they answered a posttest and a questionnaire. Most students exhibit improved results after utilizing the digital DRR materials. This improvement is pronounced for the on-site implementations, while the mixed online–on-site implementation proves less effective. The pretest scores for the implementations using local disaster cases are low, but the subsequent improvement is significant. The ability of students to utilize electronic devices affects the learning of GIS-related content rather than other aspects. The daily use of online maps and attention to disaster prevention and mitigation affect the learning of all the materials. Increasing the use of online hazard maps is key to realizing social DRR.

Artificial Intelligence and Street Space Optimization in Green Cities: New Evidence from China

In the context of the green economy and sustainable urban development, the rapid expansion of urban construction has given rise to pressing public health concerns, notably environmental pollution and the increased prevalence of chronic illnesses linked to swift urbanization. These urban health issues are escalating, prompting significant attention to the concept of creating “healthy cities”. Meanwhile, the planning and design of urban street space have a far-reaching impact on urban residents’ quality of life and health. Urban planners are facing challenges and need to follow the principle of a green economy while meeting the needs of residents for public activities and adapting to motor vehicle traffic. This study explores the optimization of urban street space to promote the harmonious coexistence between people and cars. This study actively explores the relationship between health, urban environment, and social background, focusing on promoting the harmonious coexistence between people and vehicles, especially the optimization goal of sharing urban streets. The study’s main goal is to design a road that can meet the needs of citizens’ public activities and accommodate motor vehicles, which conforms to the principle of a green economy. To achieve this, geographic information system (GIS) technology and a genetic algorithm (GA) are employed to optimize shared urban street spaces. Among them, GIS tools are used for spatial simulation to evaluate the effect of different shared street space configurations. The urban shared street space is gradually optimized through GA’s selection, crossover, and mutation operations. Simulation experiments are conducted to determine the relationship between street space utilization and the elements of a healthy city, ultimately striving to identify the optimal design parameters for shared street spaces. The research results reveal that the urban street space is optimized from the three aspects of shared allocation of facilities resources, replacement of land use functions, and mixed layout of facilities, and the utilization rate of urban streets is finally ensured to reach 53.43%, fully assuming the essential functions of urban streets. This innovative approach bridges the gap between urban development and public health, offering valuable insights for sustainable urban space planning and enhanced living environments within the framework of the green economy.

The dynamic evolution of an industrial innovation ecosystem: a case study of Around-Tongji Knowledge Economy Circle (Shanghai)

Purpose The purpose of this paper is to analyse the development and evolution of industrial innovation ecosystems of Around-Tongji Knowledge Economy Circle from the three levels mentioned above, focusing on knowledge-producing populations, core populations and service-supporting populations, and to further develop this research framework by combining with the latest developments. Design/methodology/approach Based on the five-helix theory and economic census statistical data, this paper adopts geographic information system technology and examines the characteristics of the industrial innovation ecosystem and the synergistic evolution process in Around-Tongji knowledge economy circle. Findings The knowledge product populations lead the development of industries in Around-Tongji Knowledge Economy Circle. It contributes political capital output for the government. It innovates community cooperation and governance mode, and it improves the natural ecological environment. In the face of the changes and challenges in the development environment, the future development must be recognised from the height of the iterative development of the interaction mode between university knowledge production and economic and social development. Originality/value Based on the five-helix theory and economic census statistical data, this paper examines the characteristics of the industrial innovation ecosystem and the synergistic evolution process in Around-Tongji Knowledge Economy Circle. It further expands the research framework used to develop a synergistic evolution model, which reveals the interactive and synergistic relationship among the populations and the evolution characteristics of the entire industrial innovation ecosystem. This paper also provides useful perspectives for the study of the industrial innovation ecosystem.

Spatial Data Analysis of Sudden Epidemic Diseases Based on Case-Based Travel Data

In recent years, health geography has attracted the attention of more and more institutions and scholars in China, but as far as the results of a large number of studies are concerned, there are not many related types of research. Geographic Information System (GIS) and spatial data method can effectively deal with complex spatial data, time data and attribute data in diseases, analyze the relationship between the distribution and changes of diseases in different regions, and explore the causes of diseases and various environmental factors. According to the analysis results, the hierarchical model of spatial aggregation can find out the dynamic spatial distribution law of epidemic occurrence and prevalence more intuitively, and carry out epidemic detection and early warning in depth, thus laying the foundation for formulating appropriate prevention and control strategies. Corona Virus Disease 2019 is highly contagious, with diverse and complicated transmission methods, wide spread and high incidence. Therefore, taking Corona Virus Disease 2019 as an example, it is of great significance to study the application of spatial aggregation hierarchical model and spatial data analysis technology in epidemiology through GIS technology, especially in the spatial aggregation hierarchical model to visualize the travel data of epidemic cases and show the temporal and spatial distribution characteristics. In this work, Kriging interpolation will be tried to supplement the travel data of cases and then analyze the spatial data.

Slope visualisation and stability study using geographic information science

High-precision visualised three-dimensional (3D) slope modelling and stability analysis have benefited from the quick development of big data technology. This research aims to utilise unmanned aerial vehicle survey data to obtain influencing information on slope topography. A high-precision 3D surface model is established, which is then overlaid with 3D geological models and 3D mineral models constructed using geographic information system technology. This approach enables more efficient and accurate 3D visualisation modelling of slopes. Based on the 3D model, the search for the most dangerous sliding surface under rainfall conditions is completed. The average absolute error of sample points in the surface modelling effect verification experiment is less than 0.5 m, and the average relative error is less than 2%. These results indicate that the overall modelling effect of the 3D slope model can meet the requirements of subsequent stability analysis. According to the results of random simulation, the minimum safety factor on the most neutral surfaces is less than 1, which indicates that the slopes at some locations in this site do have the possibility of landslide. The neutral surface where the lowest safety factor appears can be used to pinpoint the position of the most hazardous sliding surface.

PEMETAAN PRASARANA DAN KONTUR KAMPUS UNIVERSITAS WIRARAJA BERDASARKAN CITRA PENGINDRAAN JAUH

Wiraraja University campus from its establishment in 1986 to 2023 has a period of 37 years which has experienced many developments, especially learning infrastructure. The development of infrastructure needs to be mapped to determine the distribution of learning infrastructure on the Wiraraja University campus. The utilization of geographic information system (GIS) technology and the development of infrastructure on the Wiraraja University campus, it is necessary to map the infrastructure and contours on the Wiraraja University campus which will later obtain an overview of the infrastructure. The purpose of the study was to determine the infrastructure map and the percentage of infrastructure to the overall land and contour map of Wiraraja University campus. The research used Google Earth and ArcMap. The research data collection was carried out by field survey and data collection of infrastructure on the campus of Wiraraja University and the research data was carried out by frequency analysis.
 Land use on the campus of Wiraraja University is divided into the categories of buildings, sports fields, covered and open parking, parks, roads and vacant land. The land area of Wiraraja University campus based on Google Earth images with the digitization method is 22,711.86 m2. The largest land use is used as a building at 37.54%, while the smallest land use is used as a covered parking lot at 1.78%. The elevation of the Wiraraja University campus is between 3.67 - 5.94 m elevation and the highest elevation is 5.94 meters and the lowest elevation is 3.67 meters above mean sea level.

Application of Geographic Information System in Assessing Rooftop Photovoltaic Potential

Achieving net-zero carbon emissions is a fundamental way to slow global warming, and dealing with massive carbon emissions from the construction industry is a priority. These days, with the growth of the clean energy industry, the market for photovoltaic (PV) power generation using solar energy is booming. In order to estimate PV power potential on a large scale, geographic information systems (GIS) have been applied in case studies in selected areas; however, there is a lack of overview of the comprehensive application of GIS technology in this subject. In this paper, the application of GIS in estimating PV potential is thoroughly analyzed from three perspectives: data source, application, and limitation. In terms of data source, this paper classifies the data into low, medium, and high precision, and the merits and demerits of each class are analyzed. The paper divides the application into two parts: calculating the received solar energy and the available roof area. The former analyses two available plug-ins in GIS software and a calculation formula that combines with GIS. The latter includes a variety of methods for calculating the total roof area, shading effects, vegetation coverage, and tilt & Azimuth. Although using GIS to estimate PV potential is well-developed, there are still limitations regarding accuracy, speed, and data accessibility. This paper hopes to contribute to the estimation of PV power potential to reach a higher level of accuracy and maturity in order to promote more projects and constructions with large-scale PV power generation systems. Indeed, the future of PV power generation is promising and will be a significant step towards net-zero carbon dioxide emissions for all humankind.

Activity Theory Approach and Geographic Information Systems Affordance for Effective Land Management and Administration Actualization

This research explores the challenges and drivers of Geographic Information Systems (GIS) affordance actualization within the Ministry of Land and Survey, Yola, Nigeria. The problem at hand is the underutilization of GIS technology in many public organizations, often resulting in failed projects and misfit due to cultural inclinations. To address this issue, Activity Theory was employed as a theoretical framework, innovatively applying it to the interpretation of human-technology interactions within a public sector setting. An in-depth interpretive research study at the Ministry of Land and Survey (MLS) was conducted, focusing on the sub-unit triangular and subject-cascaded models guided by integrated nested Activity Theory. The research reveals novel insights into the application of GIS in public organizations. The findings underscore the critical role of factors such as funding, legitimization, technology (tools), user cognition, geo-visualization, spatial infrastructure, and outcomes in facilitating GIS affordance actualization. These elements have been redefined within the context of land administration in public organizations. The research introduces two new theoretical constructs, "Spatial Data Infrastructure" and "Geo-visualization," further extending the integrated Activity Theory constructs. The importance of this study lies in its potential to inform GIS professionals, developers, and policymakers. The newly developed mid-level theoretical model, Spatial Information Affording Approach (SISAA) offers a comprehensive framework for designing effective GIS systems that streamline land transactions, enhance revenue generation, reduce land disputes, and bolster the overall integrity of land administration in public sectors. This research contributes not only to the Nigerian context but also holds relevance for public organizations worldwide that use GIS in land management. In conclusion, this study bridges a significant gap in the current body of knowledge by providing a spatially enabled theoretical framework for GIS applications in culturally organized public organizations. It has the potential to drive improvements in land administration and promote the successful implementation of GIS in the public sector, aligning with global agendas such as the Sustainable Development Goals (SDGs).

Site selection decision for biomass cogeneration projects from a sustainable perspective: A case study of China

Biomass energy has made significant contributions to energy demand and environmental protection. The purpose of this study is to establish a new integrated method adapted to the site selection of biomass cogeneration projects. The highlight lies in the integration of Multiple Criterion Decision Making methods with Geographic Information System at different stages. This study takes Henan Province as an example to introduce the application of this model. Stage I preliminary screening stage: use Geographic Information System and Fuzzy Best Worst Method to classify the suitability level of project site selection within the research area. Identify alternative solutions in areas with high suitability and large patch area. Stage II selection stage: Calculate the indicator weights using Criteria Importance Through Intercriteria Correlation method first; Then use the Multi-attributive Border Approximation Area Comparison method to select the optimal factory site. Using geographic information system technology, the factory is selected to be built in an area with a suitable value greater than 7 in Xiangcheng County, Zhoukou City. Finally, the obstacle model diagnoses the direction of optimizing the location environment. This study provides a theoretical reference for the new construction, renovation and expansion of biomass cogeneration projects.

Application of GIS and IoT Technology based MCDM for Disaster Risk Management: Methods and Case Study

This study proposes a two-phase framework to enhance disaster management strategies for flooding using Geographic Information System (GIS) and Internet of Things (IoT) real-time data obtained using drones. The first phase aims to predict the governorate most prone to flooding using GIS and four forecasting models. The second phase involves selecting optimal locations for drone takeoff and landing using GIS with multi-criteria decision making. The neutrosophic ordinal priority approach is used to weight the criteria for selecting the best locations. A case study from the Egyptian Mediterranean Coast is used to measure the effectiveness and applicability of the framework. Results indicate that the Port Said governorate is the most vulnerable to flooding, and the top 10 suitable sites for drone takeoff and landing are suggested for this governorate. The limitations of the case study are discussed, such as data availability and reliability, as well as potential biases in the methodology. This study suggests future research directions to address these limitations and enhance the effectiveness of the proposed framework. Overall, this study contributes to the field of disaster risk management by providing a practical and innovative approach to enhance disaster preparedness and response using GIS and IoT technologies.

Agricultural Land Use Planning on Sustained Basis Using Landform and Land Evaluation Approach with Geospatial Analysis (a case study in East Barito District, Central Kalimantan Province)

Spatial planning for agricultural land use is required since the region with its land resource has an opportunity to be opened and cultivated. On the other side, balanced environment should be maintained in order to achieve sustainability for future use. Land resources information can then be used as basic information and prerequisite for analysis and evaluation in planning process. Because of the lack of data, this study was conducted to generate and provide land resource information. Landform approach using raster surface analysis and slope classification derived from digital elevation model (DEM) was then used to determine agricultural land regions. Procedure of land suitability evaluation in addition to geographic information system (GIS) technology were applied to define specific kind of use for lands. In the case of East Barito as study areas, mainly on the basis of landform analysis, the region can be classified into 6 slope classes i.e. <3%; 3-8%; 9-15%; 16-25%; 26-40%; dan >40%. The result of land suitability evaluation integrated into GIS environment establish that arable lands is still available with total area of 226,211 hectare (59.11%) of total study areas. Furthermore, the region can then be delineated for group of commodities involving food crops, estate crops, and forest as well with each total area 62,291 hectares (17.96%), 183,107 hectares (52.78%) and 101,513 hectares (29.26%), respectively. Several restrictive factors that should be considered include slopping lands and peat depth. Any appropriate and specific programs for agricultural development can then be formulated in land use planning process.

Decision-theoretic rough set model and spatial analysis-based waste-to-energy incineration plant site selection: a case study in first-tier cities of China.

Selecting a sustainable waste-to-energy (WTE) incineration plant site is important for handling huge challenges created by on-going municipal solid waste. However, many studies with WTE incineration plant site problems fail to determine alternative evaluation criteria and cities beforehand, which may increase decision costs and evaluation risks. This paper proposes a novel methodology based on decision-theoretic rough set model and suitable analysis for selecting the optimal WTE incineration plant site. Firstly, from the features of cities, alternative evaluation criteria are determined by three-phase method. Considering different geographical features, a geographical index system is established. Secondly, subjective and objective criteria weights are determined by an improved DEMATEL (Decision Making Trial and Evaluation Laboratory) method and TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) method-based linear programming model under the hesitant fuzzy linguistic context, respectively. Subjective and objective criteria weights are combined to form the final criteria weights by building an optimization model. Thirdly, the decision-theoretic rough set model is utilized to select alternative WTE incineration plant sites. We utilize spatial analysis adopting Geographic Information System technology to rank all alternative cities to build facilities. Finally, a numerical case is performed to illustrate the feasibility of the proposed methodology. The sensitivity analysis with the parameter [Formula: see text] ranking from 0 to 1 is performed, the result confirms that the proposed methodology has better robustness. Compared with the multi-criteria decision-making methods, the effectiveness and superiority of the proposed methodology are demonstrated.

Intelligent Lithology Identification Methods for Rock Images Based on Object Detection

Lithology identification is a crucial step in geological research. In recent years, the development of artificial intelligence technologies has provided new insights into solving problems associated with subjectivity and labor intensity of traditional manual identification. However, when rocks are identified in situ, existing algorithms cannot accurately identify them if the image features of different types of rocks are similar or the rock textures are varied. In this regard, the study of lithology identification for the rock images captured from the field was carried out. First, the object detection algorithm of single shot multibox detector was improved by adding residual net and adaptive moment estimation, and a lithology identification model was constructed. Second, based on the above improved algorithm, the technologies of database and geographic information system were combined to develop an integrated identification method. Third, the proposed methods were applied to 12 types of rocks in Xingcheng area, China, for testing their validity, and feasibility in field geological surveys. Finally, the effects of learning rate and batch size on the identification were discussed, as the epoch number was increased. We found that the average accuracies of the improved single shot multibox detector and integrated method were 89.4% and 98.4%, respectively. The maximum accuracy could even reach 100%. The identification results were evaluated based on accuracy, precision, recall, F1-score, and mean average precision. It was demonstrated that the integrated method has a strong identification ability compared with other neural network methods. Generally, a small learning rate can lead to low loss and high accuracy, whereas a small batch size can lead to high loss and high accuracy. Moreover, the newly proposed methods helped to improve the lithology identification accuracy in the field and support the study of intelligent in situ identification for rock images.

Evaluating the Influence of Land Use and Landscape Pattern on the Spatial Pattern of Water Quality in the Pearl River Basin

Differences in land use and landscape patterns have become crucial factors affecting regional water quality. In order to investigate the effects of different land use and landscape patterns on water quality, this study used dissolved oxygen (DO), ammonia nitrogen (NH4+-N), and potassium permanganate index (CODMn) from 147 conventional water quality monitoring stations in the Pearl River basin of China from January to December 2021 as representative water quality parameters. The quantitative relationship between land use, landscape pattern, and water quality in the Pearl River basin was investigated using geographic information system technology (GIS) and partial least squares (PLS). The results showed that the overall water quality of the Pearl River basin was relatively positive and mainly threatened by organic pollution. The water quality of the Pearl River basin was affected by the spatial characteristics of land use and landscape pattern, showing a poorer spatial pattern on the eastern and western ends and a better one in the central part of the basin. The developed PLS regression model could better explain the quantitative relationship between water quality, land use, and landscape pattern, concluding that unused urban land has the greatest impact on water quality, with an impact coefficient of more than 0.10. The interspersion juxtaposition index (IJI) for representing landscape patterns had the greatest impact on water quality indicators, with an impact coefficient of −0.15 on DO, 0.13 on NH4+-N, and 0.15 on CODMn, respectively. Meanwhile, land use types such as unused land and water and landscape patterns indicated by the Shannon diversity index (SHDI) and the contagion index (CONTAG) had significant effects on watershed water quality. The results of the study provide a reference value for the optimal adjustment of land use structure and water quality improvement in the basin.

Advancements and Applications of Drone-Integrated Geographic Information System Technology—A Review

Drones, also known as unmanned aerial vehicles (UAVs), have gained numerous applications due to their low cost, ease of use, vertical takeover and landing, and ability to operate in high-risk or hard-to-reach areas. The contribution of this review is that of building the bridge between drone technology and its application and advancements in the field of Geographic Information System (GIS). The integration of drones and GIS is valuable as it reduces costs and improves accessibility for geospatial data collection. Traditional methods involving aircraft for aerial photography are expensive, requiring the hiring of aircraft, pilots, and photographers. Drones equipped with advanced cameras and artificial intelligence software can replace the conventional technique and at the same time, be economical and time-efficient. The integration of drones and GIS is expected to bring revolutionary benefits in the fields of precision agriculture, urban planning, emergency health response, disaster management, the development of smart cities, food delivery, etc. In this paper, a state-of-the-art review of the deployment of drone-integrated GIS applications in different fields is presented. Numerous techniques and associated challenges related to their development, formulation, implementation, and regulation are highlighted. It has been concluded that drone-integration solutions in GIS improve efficiency and accuracy, enhance the decision-making process, and facilitate better real-time monitoring. The findings of this review paper are intended to help and benefit researchers, business developers, emergency service providers, industrialists, and policymakers.