GIS Spatial Analysis Research Articles

Migratable urban street scene sensing method based on vision language pre-trained model

We propose a geographically reproducible approach to urban scene sensing based on large-scale pre-trained models. With the rise of GeoAI research, many high-quality urban observation datasets and deep learning models have emerged. However, geospatial heterogeneity makes these resources challenging to share and migrate to new application scenarios. This paper introduces vision language and semantic pre-trained model for street view image analysis as an example. This bridges the boundaries of data formats under location coupling, allowing for the acquisition of text-image urban scene objective descriptions in the physical space from the human perspective, including entities, entity attributes, and the relationships between entities. Besides, we proposed the SFT-BERT model to extract text feature sets of 10 urban land use categories from 8,923 scenes in Wuhan. The results show that our method outperforms seven baseline models, including computer vision, and improves 15% compared to traditional deep learning methods, demonstrating the potential of a pre-train & fine-tune paradigm for GIS spatial analysis. Our model could also be reused in other cities, and more accurate image descriptions and scene judgments could be obtained by inputting street view images from different angles. The code is shared at: github.com/yemanzhongting/CityCaption.

Detailed Processes of Tidal Flat Geomorphology Evolution Based on Time-Series Satellite Images

In-depth understanding of long-term evolution of mega deltas with a large population is of great significance for national sustainability development programs. However, due to insufficient satellite images and its low temporal resolution, previous studies have only roughly explored the long-term evolution. To reveal the detailed delta evolution processes, Jiuduansha (JDS) upon the Yangtze estuary, which is one of the world’s mega deltas, was taken as an example. Based on the continuous time series of 792 satellite images between 1965 and 2021, this study combined the K-means classification, probability statistics, and GIS spatial analysis to generate the annual probability waterlines. Furthermore, the continuous time series of geomorphological features, position of waterlines and centroid change were determined. The results showed that the JDS exposed area presented a rapid growth trend. Specifically, in the early period (1965–1998), it presented a natural evolution state of “the head erosion, the tail deposition, and extending to the southeast”. In the recent period (1999–2021), the evolution state changed into the engineering-dominated evolution state of “erosion in the south, deposition in the north, continuous extension to the southeast, and overall northward movement”. The accelerated deposition of JDS over the recent 20 years has been mainly attributed to human activities, including the construction of Deep-water Navigation Channels and the vegetation promoting silting, followed by the upstream and downstream sediment sources. Current results suggest the JDS is likely to be more elongated in the SE-NW direction, with erosion in the southern region.

Site Selection of Affordable Housing in Direct Management Area under Jiangbei’s New District in Nanjing

Affordable housing is an effective approach for relieving the residential stress of moderate and low-income citizens; it is not only a macro study but also a micro one in the processive phase focusing on site selection and so on. From this view, the site selection of affordable housing in the direct management district under Jiangbei New District in Nanjing is analyzed, including summarizing the status quo and construction models of affordable housing’s site selection; quantifying the influential elements of site selection by the AHP method and GIS spatial analysis. The final result shows that the site of Jiangbei’s new district in Nanjing, with a score ranging from 2.7792 to 3.8572, is recommended for affordable housing. According to this result, the optimization strategy of affordable housing planning and location is put forward to ensure the balance of work and housing and the interests of low-income groups.

Snow avalanche susceptibility assessment based on ensemble machine learning model in the central Shaluli Mountain

The central part of the Shaluli Mountains is located in the Ganzi area, Sichuan Province, China, bordered by the Jinsha River and adjacent to Tibet. Frequent avalanches pose a serious threat to human activities and engineering construction such as the Sichuan-Tibet Railway under construction. Therefore, the evaluation of avalanche susceptibility in this area can not only help define the spatial pattern of avalanches on the Qinghai-Tibet Plateau but also provide references for the recognition and early warning of regional avalanche disasters. In this study, avalanche samples were selected by remote sensing interpretation supplemented by a detailed field survey, GIS spatial analysis, and data mining. Two statistical models [evidence confidence function (EBF) and certainty coefficient (CF)] combined with two machine learning models [logistic regression (LR) and multilayer perceptron (MLP)] were used to establish four integrated models (EBF-LR, CF-LR, EBF-MLP, and CF-MLP) as well as the traditional frequency ratio model (FR) for avalanche susceptibility evaluation. Finally, the results were checked for accuracy by Kappa coefficients and ROC curves. The CF-MLP (Kappa = 0.606, AUC = 0.910) model was the best avalanche susceptibility evaluation model for this study, the FR (Kappa = 0.584, AUC = 0.894) model had the next highest accuracy, and the combination of the CF algorithm and the machine learning model performed better than the EBF. The most important influencing factors were elevation, slope orientation, terrain moisture index, and January average temperature. The five models showed a high degree of consistency in the sensitivity to topographic factors during the evaluation of susceptibility. The avalanche susceptibility zoning map based on the CF-MLP model was obtained by the natural breakpoint method, and the areas with very high and high susceptibility accounted for about 10.01% and 15.33% of the total area, respectively.

Field Survey in the Middle Fortore Valley: A Preliminary Report

Abstract The Fortore Valley Project, which began in 2005 and is still ongoing, aims to create an archaeological map of the Fortore Valley. Several intensive and extensive survey campaigns were carried out in the territory of the middle valley. More than 100 km2 have been surveyed and more than 300 sites identified. This contribution analyzes the collected data and proposes a model of population evolution based on a GIS spatial analysis and a preliminary study of the finds. The artifacts found between 2005 and 2006 in the territory of Occhito Lake (Macchia Valfortore) provide a case study for understanding settlement patterns in the Fortore Valley.

Mapping the spatial dimension of food insecurity using GIS-based indicators: A case of Western Kenya

Food insecurity elimination is a major focus of the Sustainable Development Goals and addresses one of the most pressing needs in developing countries. With the increasing incidence of food insecurity, poverty, and inequalities, there is a need for realignment of agriculture that aims to empower especially the rural poor smallholders by increasing productivity to improving food security conditions. Repositioning the agricultural sector should avoid general statements about production improvement, instead, it should tailor to location-specific recommendations that fully acknowledge the local spatial diversity of the natural resource base that largely determines production potentials under current low input agriculture. This paper aims to deconstruct the complex and multidimensional aspect of food insecurity and provides policymakers with an approach for mapping the spatial dimension of food insecurity. Using a set of GIS-based indicators, and a small-area approach, we combine Principal Component Analysis and GIS spatial analysis to construct one composite index and four individual indices based on the four dimensions of food security (access, availability, stability, and utilization) to map the spatial dimension of food insecurity in Vihiga County, Kenya. Data were collected by the use of a geocoded household survey questionnaire. The results reveal the existence of a clear and profound spatial disparity of food insecurity. Mapping food insecurity using individual dimension indices provides a more detailed picture of food insecurity as compared to the single composite index. Spatially disaggregated data, a small area approach, and GIS-based indicators prove valuable for mapping local-level causative factors of household food insecurity. Effective policy approaches to combat food insecurity inequalities should integrate spatially targeted interventions for each dimension of food insecurity.

Grid computing method for atmospheric environmental capacity coupled with ventilation coefficient using CALPUFF simulation and GIS spatial analysis technology

ABSTRACT Atmospheric environmental issues have evolved from point source pollution to regional pollution, leading to controlling specific air pollutant emissions. A-value method has been found suitable for estimating large-scale atmospheric environmental capacity rather than small-scale, resulting in the inaccuracy of developing air pollution control strategy. This study proposed a grid computing method based on the CALPUFF modelling system and GIS spatial analysis tool. The meteorological data from the MM5 model were used to simulate the spatial distribution of air pollutants. The meteorological flow field data was used to simulate the ventilation coefficient. The A value was revised with the simulated to achieve accurate results of atmospheric environment capacity. The credibility was verified by applying this method to Fengtai District, Beijing, China. The research area was divided into small partitions via the ArcGIS spatial analysis tool. The simulation results agreed well with the observation data from actual monitoring stations, even for the PM10 concentration with the most significant error (MRE: 7.05%−13.28%, RMSE: 11.62–17.89, R 2: 0.84–0.90). The GIS spatial analysis tools were applied to match the underlying surface types and overcome the restrictions of administrative boundary management. The study proposed four schemes to achieve differentiated air pollutant emission reduction and develop suitable control strategies. Furthermore, this method can be applied on different scales of natural geographic boundaries and realize the precise spatial management of atmospheric environmental capacity.

Coupling driving factors of eco-environmental protection and high-quality development in the yellow river basin

Most cities in the Yellow River Basin are located in the central and western regions of China. Restricted by historical evolution, natural environment, resource endowments and other conditions, the economic and social development model of the Yellow River Basin region is outdated, and the level of economic and social development is relatively lagging, which hinders its coordinated development of ecology and economy. This paper uses the coupling coordination degree model, GIS spatial analysis method, NAR neural network model, spatial autoregression, and geographically weighted regression model to investigate the coupling coordination level, spatial differentiation characteristics, future development trend, and coupling driving factors of eco-environmental protection and high-quality development in the Yellow River Basin. The results show that From 2003 to 2018, the level of eco-environmental protection and high-quality development in most areas of the Yellow River Basin gradually improved, presenting a spatial imbalance characteristic of “high in the east and low in the west. The coupling coordination degree of eco-environmental protection and high-quality development in various regions of the Yellow River Basin increased year by year during the survey period. In 2018, most cities had been transformed into intermediate coordinated development areas, and most cities in Inner Mongolia and the middle and lower reaches south of the Yellow River have been upgraded to a well-coordinated development stage. The coupled and coordinated development relationship between eco-environmental protection and high-quality development in the Yellow River Basin has significant spatial agglomeration characteristics, and the local spatial positive correlation gradually increases. From 2019 to 2023, the average level of coupling coordination between eco-environmental protection and high-quality development in the Yellow River Basin during the forecast period is 0.802, 0.807, 0.809, 0.813, and 0.816, respectively, all of which have entered a stage of well-coordinated development. The coupled driving factors of ecological protection and high-quality development in the Yellow River Basin are ranked from strong to weak: energy utilization, urbanization, water resources development, and industrialization. Among them, the degree of energy utilization is the root of the differentiation of coupling coordination between eco-environmental protection and high-quality development in 74 regions of the Yellow River Basin. This study puts forward two strategic suggestions based on the optimal utilization strategy of energy and water resources and the coordinated promotion strategy of industrialization and urbanization, which has great practical and scientific significance for promoting the coordinated development of ecological environment protection and high-quality development in the Yellow River Basin.

GIS-Based Medical Resource Evaluation Method

As one of the public service resources, medical and health care has a great guarantee for people’s healthy life and life safety and is an important part of ensuring the normal and orderly operation of urban functions. This paper takes the spatial pattern of urban medical resources in Hohhot as the research object and collects three types of urban medical resources, including clinics (health centers), specialized hospitals, and general hospitals, a total of 1300 sample points, based on GIS spatial analysis methods, using the average nearest neighbor, kernel density estimation method, standard deviation ellipse method, and accessibility measure to analyze the spatial distribution of medical resources. The results show that the medical resources in the urban area of Hohhot are all in a state of agglomeration, but due to the different functions of different types of medical resources, their distribution ranges and distribution directions also show different characteristics. Saihan District, Yuquan District in the southwest, has fewer medical facilities resources, and the distribution of the accessibility of the three types of medical facilities is quite different. Therefore, the spatial balance of comprehensive medical resources in the urban area of Hohhot needs to be further improved. The results of this paper have implications for the layout of medical facilities and planning has important reference significance.

COVID 19: Are Our Green Areas Enough for People’s Well-being

Malaysians’ overall well-being, particularly in urban areas, has been seriously affected physically and emotionally due to the series of imposed lockdowns in the country. The number of mental health problems such as depression, anxiety, and loneliness has increased tremendously during the lockdown period. Various studies suggest that these mental health issues could be coped with if people are allowed to access urban greeneries and public green spaces during the pandemic. However, the degree to how adequate existing green areas are to fulfil an urban community’s needs with strict social distancing compliance is still vaguely interpreted in the literature. It is still arguable that the current 10 per cent green area requirement is still relevant to the current context of the COVID-19 pandemic. This study aims to determine the sufficient amount of green areas for people’s well-being during the pandemic, based on the local population, accessibility to green areas, and compliance with the new norm of social distancing by a minimum of one meter. Therefore, an urban neighbourhood in Iskandar Puteri, Johor, Malaysia was selected and simulated using GIS spatial analysis based on the highlighted parameters. As a result, the study found that the current size of existing green areas in the neighbourhood is insufficient in terms of compliance with the parameters, especially Malaysia’s social distancing requirements. This study could provide a platform for future planning to include pandemic risk reduction into urban planning policies, especially in the context of Malaysia, to cater to future uncertainties

Landscape Preference of Rural Cultural Tourism Tourists Based on GIS Spatial Statistical Technology and Emotion Analysis

How to combine GIS spatial statistics technology to realize the intelligent and efficient classification of tourists’ landscape preferences is a hot spot in the direction of rural cultural tourism. Based on this, this paper studies the emotion analysis strategy based on GIS spatial statistical method in the field of landscape preference of rural cultural tourism tourists. Firstly, an intelligent and efficient classification model based on remote sensing discrete expansion algorithm is proposed. Combined with the observation strategy of common emotional rules in the landscape preference analysis of rural cultural tourism tourists, the landscape preference of rural cultural tourism tourists is processed with high quantitative emotional information, so as to realize the intelligent separation of preference, and then the error of discrete remote sensing data expansion model is corrected. Secondly, the judgment function of emotional rules is constructed, and the commonly used data layer-driven decentralized method is used in preference classification to eliminate the secondary factors in the landscape preference analysis of rural cultural tourism tourists. At the same time, the remote sensing discrete expansion algorithm is used to optimize and improve the emotional rules of high-volume emotional information based on GIS spatial statistical method. Finally, through the design of confirmatory experiments, the results show that the landscape preference analysis model based on GIS spatial statistics method and remote sensing discrete expansion algorithm is more efficient than the conventional preference classification method.

Landslide susceptibility assessment for warning of dangerous areas in Tan Uyen district, Lai Chau province, Vietnam

ABSTRACT This paper presents the results of applying GIS–MCA–AHP integrated model in landslide susceptibility assessment for warning of dangerous areas in the Tan Uyen district of Vietnam. The main research method is a Multi-criteria assessment that is based on a hierarchical analysis process and a combination of the GIS spatial analysis model. Research results have shown four main groups of factors causing landslides including hydrogeological factors, topographic and geomorphological factors, surface cover factors and human impact factors. The landslide susceptibility assessment map has identified 22.69% of the area (204.96 km2) with a high and very high risk of landslides. Based on the overlapping population distribution map and landslide susceptibility assessment map. It has been shown that residential areas, including 723 households located at a high risk of landslides need to be moved to a safe area. This is a very significant research direction in a warning and minimizing the risk of landslides in mountainous areas of Vietnam.

Regression-based spatial GIS analysis for an accurate assessment of renewable energy potential

This work aims to evaluate technically and economically the performance of a large photovoltaic power plant, emphasizing the potential of the eastern region of Morocco for the production of electricity and hydrogen. We used weather data from about 24 cities and based on the simulation of a 110 MW power plant by the SAM (System Advisor Module) software. The required data is collected and then implemented in a regression model to obtain a suitable energy production equation. This assessment method aims to provide high-resolution GIS maps and provide accurate data on the techno-economic potential of the plant in the region as well as the amounts of hydrogen that can be produced. The findings reveal that at the regional level, the simulation of the available power plant potential gives good results. The use of a regression model instead of the interpolation methods provided by GIS software allows us to obtain a better cartographic resolution, this last one depends certainly on the resolution of the spatial data used in the prediction, as far as data resolution and quality are good, as far as the results are better too.

Study on the Spatial Allocation of Receding Land and Water Reduction under Water Resource Constraints in Arid Zones

The withdrawal of cultivated land policy is not only an important task to promote cultivated land rest and alleviate the contradiction between supply and demand of water resources in arid areas, but also an important way to realize the sustainable development of agriculture and social economy. This study adopted the minimum per capita area method, ESPR (Exposure-Sensitivity-Pressure-Response) vulnerability assessment model, grey prediction model, and GIS spatial analysis. Furthermore, based on the characteristics of water resource constraints in the arid zone, Manas County was used as the study area. By exploring and analyzing the area of land retreat, through identifying its occurrence and position, the spatial zoning layout of land retreat can be realized to guarantee the effective implementation of water retreat and reduction. The following points were noted from the results: (1) the upper and lower limits of the area of receding land in Manas County were measured using the minimum per capita area method and the principle of balancing water supply and demand. The receding land in Manas County measured 16,493.68–20,749.90 hm2, which accounted for 24.31–30.58% of the total area of cultivated land. (2) The results obtained from constructing the ESPR vulnerability assessment model, used to assess the vulnerability of cultivated land in Manas County, showed that the overall vulnerability of cultivated land in Manas County was high, with 94.74% of the county’s cultivated land being moderately vulnerable or worse, which necessitates the optimization of land use. (3) The area of cultivated land withdrawal under the water resource constraint was used as a constraint for the withdrawal of cultivated land. Based on the evaluation of the vulnerability of cultivated land, with the results arranged from small to large, it was concluded that the area of cultivated land withdrawal in Manas County could reach up to 16,787.34 hm2. There are four types of cultivated land withdrawals: desertified withdrawal, saline withdrawal, groundwater overexploitation withdrawal, and soil contamination withdrawal. The results of this study can provide a reference for Manas County to scientifically formulate a reasonable and orderly withdrawal system of farmland to reduce water use.

Spatial Evaluation of Villages and Towns Based on Multi-Source Data and Digital Technology: A Case Study of Suining County of Northern Jiangsu

Based on the research on the current situation and transformation path of the spatial construction of villages and towns in northern Jiangsu, “compactness” and “convenience” are extracted as the elements of spatial evaluation. With multi-source data, comprehensively using ENVI remote sensing image interpretation, GIS spatial analysis, Fragstats landscape index calculation, entropy weight–TOPSIS comprehensive evaluation, and SPSS cluster analysis, a “digital full cycle” of a research framework for the spatial evaluation of villages and towns is built. In this paper, Suining County is taken as the research object, and the spatial construction level of its villages and towns is studied. The research results show that at the county level, the spatial compactness of villages and towns roughly presents the characteristics of an “X” pattern, decreasing from the middle to the four sides, while facility convenience generally presents the characteristics of a right “人” (Chinese character) pattern. At the town level, facility convenience basically presents the pattern characteristics of the “center-node” differentiation structure. The research aims to guide villages and towns to solve the current dilemma of spatial construction, promote the construction of digital villages and towns, and impel the digital transformation of the village and town evaluation system, data, and methods, so as to provide real-time, quantitative, and accurate data and method support for planning and decision-making in villages and towns.

Study on distribution characteristic of tourism attractions in international cultural tourism demonstration region in South Anhui in China.

Taking data of tourism attractions in international cultural tourism demonstration region in South Anhui in China, this study summarized the distribution characteristics of tourism attractions in region by applying GIS spatial analysis method such as nearest neighbor distance index and kernel density estimation method, and explored how natural conditions, urban infrastructure, social and economic development affect the distribution in order to better understand the distribution of regional tourism resources and serve the direction of tourism development. The study found that the tourist attractions in the demonstration area have a significant agglomeration on the whole, with Huangshan City as the main center and other districts and counties as the sub centers, presenting the trend of hierarchical development. In different kinds of tourism attractions, the distribution of natural tourism attractions and rural pastoral tourism attractions highly related to the topography. And the distribution of modern recreational tourism attractions and humanistic tourism attractions is closely related to hydrology. In terms of urban infrastructure, modern recreational tourism attractions hold the best accessibility with transportation. The core area of the demonstration region include Huangshan City, Chizhou city and Xuancheng city has better tourist industry development. Tourist attractions in other areas are relatively scarce, but the hold great potential for development in the future.

A GIS-Based Spatiotemporal Modelling of Urban Traffic Accidents in Tabriz City during the COVID-19 Pandemic

The main aim of the present study was to investigate the spatiotemporal trends of urban traffic accident hotspots during the COVID-19 pandemic. The severity index was used to determine high-risk areas, and the kernel density estimation method was used to identify risk of traffic accident hotspots. Accident data for the time period of April 2018 to November 2020 were obtained from the traffic police of Tabriz (Iran) and analyzed using GIS spatial and network analysis procedures. To evaluate the impacts of COVID-19, we used the seasonal variation in car accidents to analyze the change in the total number or urban traffic accidents. Eventually, the sustainability of urban transport was analyzed based on the demographic and land use data to identify the areas with a high number of accidents and its respective impacts for the local residences. Based on the results, the lockdown measures in response to the pandemic have led to significant reductions in road traffic accidents. From the perspective of urban planning, the spatiotemporal urban traffic accident analysis indicated that areas with high numbers of elderly people and children were most affected by car accidents. As we identified the hotspots of urban traffic accidents and evaluated their spatiotemporal correlation with land use and demography characteristics, we conclude that the results of this study can be used by urban managers and support decision making to improve the situation, so that fewer accidents will happen in the future.

The Reintroduction Analysis of European Bison (Bison bonasus L., 1758) in the North of Romania and the Identification of the Most Favourable Locations

We analysed the possibility of reintroducing the European bison (Bison bonasus L.) in the north of Romania—in Suceava, Neamț, and Maramureș counties—as well as increasing the wild European bison population in Neamț county to improve the genetic quality of the existing population. Currently, there is a population of over 50 individuals in the wild in Vânători Neamț Natural Park, Romania. At the same time, an attempt was made to identify the connecting corridors between the free European bison in Neamț county and other populations through new nuclei of European bison released in Suceava and Maramureș counties. In this regard, the hunting grounds with the highest ecological potential for the analysed species were identified using GIS spatial analysis techniques. The aim was also to trace possible ecological corridors linking different reintroduction locations, taking into account the ecological claims of the species. The analysis also followed the size of the European bison groups to be released, the sex ratio of each group, and the periodicity of their releasing. In order to reach viable populations, scenarios and simulations were carried out depending on the age, number, and sex of the relocated specimens. In this regard, the dynamics and the minimum viable population that could survive without risk of extinction were highlighted. The analysis showed that the analysed area has a high potential for the reintroduction of European bison in the wild. The release and creation of new European bison nuclei in the wild creates the premises for natural contacts with the existing free populations in the wild, genetic improvement, and increasing fauna diversity with ecological, social, and economic implications.

The spatial and temporal differentiation characteristics of cultural heritage in the Yellow River Basin.

Understanding the temporal and spatial distribution characteristics of the cultural heritage of the Yellow River Basin can effectively improve the scientific understanding of the historical changes, environmental evolution, and cultural and economic development of the Yellow River Basin and thus provide a scientific and reasonable decision-making basis for the protection and development of its cultural heritage. The research object of this paper are the national cultural relic protection units. These are examined using the GIS spatial analysis method to explore the spatial and temporal distribution characteristics and spatial structure of 2,102 national material cultural heritage sites in the Yellow River basin. The results show that the spatial distribution of cultural heritage has a significant spatial agglomeration effect. The whole basin is concentrated in stable high- and low-value areas, and the difference between the high- and low-value areas is clear. Some aspects of the spatial structure heterogeneity are strong, showing a low value dispersion distribution trend. In different periods, the distribution direction and scope of cultural heritage have low ranges of rotation, a clear direction, and a high degree of centripetal distribution. The spatial and temporal distribution of cultural heritage is the result of the combined action of natural geographical environment such as climate change, topography, river hydrology, and human environment such as administrative institutional changes, ideological evolution, and social and economic development.

Spatial optimal allocation of land resources in Fengweihan, Kaishan, Laos

Objective: Through the spatial optimal allocation of land resources to improve the efficiency of land use, promote the rational layout of various industries and infrastructure, and provide a theoretical basis for the comprehensive development of regional social economy. Methods: Combining GIS spatial analysis technology, logistic regression analysis method and CLUE-S model, taking Kaishan Fengweihan City, Laos, as the research area, the research on the spatial optimal allocation of land resources was carried out. Under the constraints of spatial suitability and quantitative structure, the spatial optimal allocation of land resources in Fengweihan city of Kaishan is carried out based on the land demand, limiting factors, conversion rules and spatial characteristics. Results: Urban construction land and paddy fields expanded to suitable areas on the original basis, and the forestry land with sparse distribution was reduced correspondingly due to development and utilization, while other land types did not change significantly in quantity and space. Conclusion: Urbanization construction and agricultural development can provide the foundation and support for the economic development of Kaishan Fengweihan city. At the same time, it is necessary to give consideration to ecological protection and promote the overall, coordinated and sustainable use of land resources.