GIS Spatial Analysis Research Articles

Research on the Spatial Network Structure of Tourist Flows in Hangzhou Based on BERT-BiLSTM-CRF

Tourist flows, crucial information within online travelogues, reveal the interactive relationships between different tourist destinations and serve as the nerve center and link of the tourism system. This study takes Hangzhou, China, as a case to investigate the spatial network structure of its tourist flows. Firstly, a BERT-BiLSTM-CRF model and pan-attraction database are built to extract tourist attractions from online travelogues and create the tourist flow matrix. Then, this study uses social network analysis (SNA) to examine the structure of the tourist flow network from a county-level perspective. Additionally, GIS spatial analysis methods are applied to analyze the evolution of the tourist gravity center and standard deviation ellipse (SDE) of the network. The results reveal that the identification performances of the tourist flow extraction model this study proposed are significantly better than those of previous mainstream models, with an F1 value of 0.8752. Furthermore, the tourist flow network in Hangzhou displays a relatively sparse and unbalanced distribution, forming a “Core–Semi-Periphery–Periphery” structure. Lastly, from 2020 to 2022, the network’s gravity center experienced a shift towards the southwest, paralleled by an initial expansion and subsequent contraction of the SDE in the same southwest direction. These findings provide valuable insights into the spatial network structure of tourism in Hangzhou and can serve as a reference for policymakers to promote the “all-for-one” tourism.

Geographic Information System (GIS) Spatial Analysis to Detect the Distribution Pattern of Unused Land Fires at Ogan Ilir Regency

Land fires pose a serious threat to the environment and communities in Ogan Ilir Regency, South Sumatra. This study aims to analyze the distribution pattern of land fires using GIS spatial analysis technology. Through Sentinel-2 image classification and fire intensity analysis, it had been identified focal points of dormant land fires mainly in South Indralaya, North Indralaya, and West Pemulutan sub-districts. The results of this study provide in-depth insight into the spatial distribution of land fires and the factors that influence their occurrence. This research also produced a map of the distribution of fire hotspots in unused land areas. From the research, it can be concluded that spatial analysis can map in detail and comprehensively the burning locations on unused land. The implication of this research is the need to develop more effective mitigation strategies to address the risk of land fires in the future. Therefore, this study not only makes an important contribution to the scientific literature but also offers new directions for research and policy focused on sustainable and effective land fire risk management.

The Spatiotemporal Impact of Digital Economy on High-Quality Agricultural Development: Evidence from China

China’s high-quality economic development is strongly supported by the high-quality development of agriculture, and the digital economy has emerged as a key driver for promoting shared prosperity and high-quality economic development. Against this backdrop, investigating the connection between high-quality agricultural development and the digital economy holds significant importance. This study utilized the entropy-weighted TOPSIS model to evaluate comprehensive evaluation indicators of the two according to panel data from 30 provinces in China between 2011 and 2021. Subsequently, GIS spatial analysis and exploratory spatial data analysis (ESDA) were employed to investigate the spatiotemporal evolution features and spatial correlations. Finally, the spatiotemporal geographically weighted regression (GTWR) model was constructed to examine the spatiotemporal impact of the digital economy on the advancement of high-quality agricultural growth. The results indicate that: (1) from 2011 to 2021, China’s high-quality agricultural development and digital economy both demonstrated a general increasing trend. In terms of spatial distribution, there were significant spatial variations, with a general trend of “Southeast is higher, whereas the Northwest is lower”. The regions with significant value were primarily clustered in the coastal areas in the east and several provincial capitals. (2) Both of the two exhibited significant global spatial self-correlation, and there were also significant spatiotemporal clustering effects in high-quality agricultural growth, gradually forming a high-value cluster centered around Shanghai and a low-value cluster centered around western provinces. (3) The digital economy positively influences the enhancement of high-quality agricultural development, demonstrating notable spatial and temporal heterogeneity. In contrast to the southeastern areas, the influence is more pronounced in the northern and central-western areas.

DISTRIBUTION AND VARIATION OF NET PRIMARY PRODUCTIVITY IN FORESTLAND AND GRASSLAND OF CHINA

Net primary productivity (NPP) can characterize the state and service functions of terrestrial ecosystems and reflect the responses of plants to climate fluctuations and human disturbances. Many studies have analysed changes in NPP and its influencing factors in some parts of China, but few studies have made in-depth comparisons between different regions, decades, and land cover types across China. Based on uniform NPP products and land cover data, the distribution, difference and variation of NPP in forestland and grassland in China were investigated with GIS spatial analysis and least-squares regression methods, and results indicated that average NPP increased gradually from northwest to southeast, and the regions with average NPP of 1-200 gC m-2 yr-1 occupied the largest proportion. During 1981–2018, the regions where decadal average NPP increased were larger than those where NPP decreased, and the areas with inter-decadal difference of 1-50 gC m-2 yr-1 were the largest. In different land cover types or regions, NPP generally exhibited a rapid rising trend in the 1990s and a slow or declining trend in the 2000s. Annual NPP increased at a rate of 13.2 gC m-2 decade-1 in the entire study area during 1981–2018, and the NPP in forestland and grassland increased at a speed of 15.6 and 11.1 gC m-2 decade-1, respectively. Spatially, NPP increased at a rate of 1-100 gC m-2 decade-1 in most areas, and the increasing trend was statistically significant in Qinghai-Tibetan Plateau, most of Northwest China and eastern Northeast China. The area with a significant increase in NPP over the past 38 years accounted for 21.0% of the total study area. Our results highlight the consistent and upward variation of NPP in general, but there are some distinctions among different land cover types and different regions of China, and higher quality datasets and more reliable methods should be fully explored in further studies. Keywords: Net primary productivity, spatial distribution, linear trend, forestland and grassland, China.

Assessment of supply-demand relationships considering the interregional flow of ecosystem services.

Accurate assessment of ecosystem service (ES) supply, demand, and flow is essential for identifying and enhancing the ES supply-demand relationship and promoting regional sustainable development. Based on the InVEST model, supply-demand ratio, coupling coordination analysis, breakpoint and field strength model, and GIS spatial analysis method, we evaluated the supply and demand of water yield, food supply, carbon storage, and soil conservation service in the Loess Plateau in 2000 and 2020 and analyzed the supply-demand relationship before and after considering the interregional ecosystem service flow (ESF). The results showed that (1) from 2000 to 2020, the supply and demand of the four types of ESs in the Loess Plateau increased. Before considering ESF, the surplus degree in water yield, food supply, and soil conservation increased, and carbon storage decreased. In most counties, the coupling coordination between the supply and demand of the soil conservation is mostly extreme incoordination and moderate incoordination, and other types of ESs are mostly reluctant coordination and moderate incoordination. The degree of incoordination in water yield and soil conservation have eased, while food supply and carbon storage have strengthened. For the comprehensive supply-demand relationship of ES, the degree of surplus and coordination increased, with most counties were in a state of surplus and coordination. (2) Water yield and soil conservation services flow primarily to the western and northwestern portions of the Loess Plateau, with a decrease in the number of flow paths but an increase in the total flow rate for the former and a decrease in flow paths and total flow rate for the latter. The food supply and carbon storage flow in all directions and the total flow rate increases, with a significant increase in the number of flow paths for carbon storage. (3) After considering ESF, the supply-demand relationship of each type of ES and the comprehensive ES supply-demand relationship are changed, in which the degree of surplus and coordination of deficit counties are significantly improved, and some counties even become surplus or improve the level of coordination. After considering ESF, the supply-demand ratio changes even more relative to the degree of coupling coordination. This study is of great significance for identifying the cross-regional transfer pattern of ES, understanding in-depth the dynamic supply-demand relationship of ES, and mitigating the mismatch between supply and demand of ES. It provides a scientific and objective theoretical basis for promoting regional sustainable development.

Contrary to expectation: The surface urban heat island intensity is increasing in population shrinking region while decreasing in population growing region-A comparative analysis from China.

Exploring the complex relationship between population change and surface urban heat island (SUHI) effect has important practical significance for the ecological transformation development of shrinking cities in the context of the prevalence of urban shrinkage and the global climate change. This paper compares the population change and SUHI effect between population shrinking region (Northeast Region, NR) and population growing region (Yangtze River Delta, YRD) in China, and explores their differences in driving mechanisms, using GIS spatial analysis and Geodetector model. Our results indicated that there are significant differences in population changes and SUHI intensity between these two regions. About 72.22% of the cities in the NR were shrinking, while their SUHI intensities increased by an average of 1.69°C. On the contrary, the urban population in the YRD shows a linear growth trend, while their SUHI intensities decreased by 0.11°C on average. The results of bivariate Moran's I index also indicated that the spatial correlation between the urban population changes and the SUHI intensity changes are not significant in the above regions. Furthermore, there are significant differences in the primary drivers of SUHI variations between these two regions. In the NR, underlying surface changes, including the changes of green coverage and built-up areas, are the most important driving factors. However, atmospheric environment changes, such as carbon dioxide emission and sulfur dioxide emission, are the key drivers in the YRD. Northam's theory of three-stage urbanization and environmental Kuznets curve hypothesis are powerful to explain these differences.

Spatial–Temporal Differentiation and Trend Prediction of Coupling Coordination Degree of Port Environmental Efficiency and Urban Economy: A Case Study of the Yangtze River Delta

Green development is a primary path for ports and cities to achieve a low-carbon transition under the Sustainable Development Goals and a powerful driving force to elevate regional port–city relations to a high level of coordination. In this paper, twenty port cities in the Yangtze River Delta (YRD) were selected and port environmental efficiency (PEE) was calculated through the window SBM model, while the EW-TOPSIS model was used to evaluate high-quality urban economic development (HED). The coupling coordination degree (CCD) model, the kernel density model, GIS spatial analysis, and the grey prediction model were used to further explore the spatial–temporal dynamic evolution and prediction of the CCD between PEE and HED. The results suggested that: (1) PEE fluctuation in the YRD is increasing, with a trend of seaports achieving higher PEE than river ports; (2) HED in the YRD shows upward trends, and the polarization of individual cities is obvious; (3) Temporally, the CCD in the YRD has risen from 0.438 to 0.518. Shanghai consistently maintains intermediate coordination, and Jiangsu has experienced the most significant increase in CCD. Spatially, CCD is led by Lianyungang, Suzhou, Shanghai, and Ningbo-Zhoushan, displaying a decreasing distribution pattern from east to west. The projection for 2026 suggests that all port cities within the YRD will have transitioned to a phase of orderly development. To enhance the coordination level in the YRD, policymakers should consider the YRD as a whole to position the ports functionally and manage them hierarchically, utilize the ports to break down resource boundaries to promote the synergistic division of labor among cities, and then tilt the resources towards Anhui.

Mapping and Spatial Analysis to Expand Rural Broadband Access

High-speed broadband internet access is a critically important issue for many aspects of daily life, yet populations in rural areas are often unserved or underserved with reliable internet connectivity. Expanding broadband internet coverage in rural areas may have significant economic potential, especially since it enables precision farming which in turn increases yields, particularly for row crops such as corn and soybeans. This paper introduces methods that utilize GIS spatial analysis and remote sensing to assist in efforts to expand rural broadband access using case study counties in Illinois. Specifically, the methods presented here: (1) quantify current cropland production as well as future potential production in currently unserved or underserved rural areas; and (2) automate mapping of vertical assets from Light Detection and Ranging (LiDAR) data that may be utilized as high points to expand broadband coverage. Collectively, these methodologies may be used for policy advocacy and to inform the decision-making process as future broadband expansion initiatives are considered in rural areas.

Assessment of Unmanned Aerial System Flight Plans for Data Acquisition from Erosional Terrain

Accurate data mapping and visualization are of crucial importance for the detection and monitoring of slope morphodynamics, including erosion processes and studying small erosional landforms (rills and gullies). The purpose of the current research is to examine how the flight geometry of unmanned aerial systems (UASs) could affect the accuracy of photogrammetric processing products, concerning small erosion landforms that are a result of slope wash and temporary small streams formed by rain. In October 2021, three UAS flights with a different geometry were carried out in a hilly to a low-mountain area with an average altitude of about 650 m where erosion processes are observed. UAS imagery processing was carried out using structure-from-motion (SfM) photogrammetry. High-resolution products such as photogrammetric-based point clouds, digital surface models (DSMs) and orthophotos were generated. The obtained data were compared and evaluated by the root mean square error (RMSE), length measurement, cloud-to-cloud comparison, and 3D spatial GIS analysis of DSMs. The results show small differences between the considered photogrammetric products generated by nadir-viewing and oblique-viewing (45°—single strip and 60°—cross strips) geometry. The complex analysis of the obtained photogrammetric products gives an advantage to the 60°—cross strips imagery, in studying erosional terrains with slow slope morphodynamics.

Effects of Land Use Types on Water Quality at Different Buffer Scales: Tianjin Section of the Haihe River Basin as an Example

It is important to explore the relationship between land use types and water quality to improve the surface water environment. Based on monthly water quality monitoring data from 16 nationally controlled surface water quality monitoring stations in Tianjin and land use data in 2021, GIS spatial analysis and mathematical and statistical methods were used to study the influence of land use types on surface water quality in buffer zones at different scales. The results showed that:① the land use types in the study area were mainly construction land, farmland, and water areas, which had significant effects on river water quality. Except for water temperature (WT) and pH, the farmland, construction land, and water areas were negatively correlated with each water quality indicator; forest land and grassland were positively correlated with dissolved oxygen (DO) and total nitrogen (TN) and negatively correlated with other water quality indicators. ② The water quality indicators showed obvious spatial differences in different seasons. The pH, DO and TN concentrations were higher in the dry season, whereas the permanganate index, ammonia nitrogen (NH4+-N), and total phosphorus (TP) concentrations were higher in the rainy season. ③ The results of the RDA analysis showed that the 800 m buffer zone land use had the greatest explanatory power for water quality changes in the dry season (50.4%), whereas the 3 000 m buffer zone land use could explain the water quality changes in the rainy season to the greatest extent (49.6%); from the average explanation rate of the dry and rainy seasons, the 3 000 m buffer zone was the best impact scale (50.0%) on water quality indicators in Tianjin. ④ The partial least squares regression (PLSR) analysis showed that the most important variables affecting surface water quality changes were construction land, farmland, and water areas. The predictive ability of the PLSR model of most water quality indicators was stronger in the dry season than that in the rainy season. In the dry season, all water quality indicators, except WT and pH, were most influenced by farmland. In the rainy season, construction land had the greatest influence on WT and NH4+-N concentrations, and the most important influencing factor for the remaining water quality indicators was still farmland. This study showed that the rational planning of land use types within 3 000 m of rivers or lakes was beneficial to improving the water quality of surface water.

Risk Assessment of Water Inrush from Coal Seam Roof Based on the Combined Weighting of the Geographic Information System and Game Theory: A Case Study of Dananhu Coal Mine No. 7, China

Coal mines’ water inrush is one of the five major disasters that affect the safety of coal mine production. The assessment of coal mines’ water inrush is a prerequisite for preventing and controlling coal mines’ water inrush. To objectively and effectively evaluate the risk of water inrush in the coal seam roof and overcome the shortage of single assignment methods, two methods, the analytic hierarchy process and the entropy method, are used in this paper to determine each evaluation factor’s subjective and objective consequences. Game theory is applied to obtain the combined weights of each influencing factor to make up for the lack of a single assignment method. Taking the roof of Coal Seam No. 7 in mining Areas I and II of Dananhu Coal Mine No. 7 as an example, six primary evaluation indexes are created to control water inrush in the coal seam roof. The comprehensive weights of each index is determined; a vulnerability index evaluation model is established; and the results of the water inrush risk zone in the coal seam roof of Dananhu Coal Mine No. 7 are obtained using the GIS spatial analysis function. The results show that the discriminatory effects of the zoning model have a high accuracy and can provide a reference basis for future coal seam mining control work in this mine.

Urban space use for outing before and during the pandemic: A case study of Daejeon, South Korea using social media posts

This study aims to investigate the popularly visited places and their spatial characteristics during the pandemic. To achieve this objective, semantic network analysis (SNA) and GIS spatial analysis were conducted using place-based words collected from Instagram posts from 2018 to June 2021 with the hashtag ‘Daejeon Nadri.’ The findings indicate that during the pandemic, the eigenvector centrality of words related to city centers decreased significantly, while words related to suburban areas increased. Before the pandemic, there was approximately a 10 km distance from the central node to the farthest node in the same modularity class. However, during the pandemic, the visited places were limited to their neighboring areas in the same modularity class. This study found that visited places during the pandemic were predominantly located in suburban areas, particularly around stream and forest areas. Green areas situated in city centers did not show a significant increase in visits during the pandemic. This indicates that people tended to visit less crowded green areas in suburban areas and showed a tendency to visit nearby places during the pandemic. These changes suggest that suburban green areas are also crucial for cities, not just for green areas in cities. In planning for future epidemics, easy access to green areas is crucial. Such accessibility can be made by allocating small green areas, creating linear green belts to link main greens, and strengthening public transport links to suburban areas. Management implicationsThe results of this study imply that individuals tend to prefer natural green spaces with low population density for their outings amid the COVID-19 crisis. This finding underscores the significance of green spaces that accommodate urban residents' leisure activities during specific circumstances such as epidemics. It is worth considering appropriate allocation of green spaces within the city to ensure equal access to public green in urban planning. Another challenge is to enhance the public transportation network to connect major green spaces in the outskirts and suburbs of the metropolitan region.

Geomorphological assessment as basic complement of InSAR analysis for landslide processes understanding

Landslide research has benefited greatly from advances in remote sensing techniques. However, the recent increase in available data on land surface movement provided by InSAR techniques can lead to identifying only those areas that were active during data acquisition as hazardous, overlooking other potentially unsafe areas or neglecting landslide-specific geological settings in hazard assessments. Here, we present a case study that serves as a reminder for landslide researchers to carefully consider the geology and geomorphology of study areas where complex active movements are detected using InSAR technology. In an area extensively studied using InSAR and UAV-related techniques, we provide new insights by applying classical approaches. The area is the coastal stretch of La Herradura, and its importance lies in the fact that it has served as an illustrative example in the Product User Manual of the European Ground Motion Service, a platform that provides ground motion data on a European scale. Our approach is to revisit the area and carry out qualitative geological and geomorphological assessments supported by UAV surveys and GIS spatial analysis on a broader scale than previously published investigations. Our classical approach has yielded the following new observations, crucial for risk assessment and land management: active landslides identified by InSAR techniques since 2015 are bodies nested within large mass movements that affect entire slopes. A variety of processes contribute to slope dynamics, such as large slumps, marble rock spreading and block sliding, and surface rock falls and topples. The revised delineation of the landslide bodies reveals an area almost five times larger than previously mapped. These new findings in a well-known area highlight (1) the importance of updating and downscaling previous maps and (2) the ongoing importance of classical fieldwork and desk studies as basic complements to modern InSAR analyses.

Study The Spread of Cancerous Diseases Throughout Iraq Using Geographic Information Systems (GIS)

GIS science is considered one of the modern sciences that intertwine with various disciplines and scientific branches in order to solve or present a specific problem. Understanding the wider picture of public health has been greatly aided by the development of Medical GIS. In this paper, the spatial analysis of GIS was used to prepare maps for the distribution of the number of cancer cases in some central and southern governorates of Iraq for several years. It was clearly noted that most of the injuries are in southern Iraq. In this paper was used the Arc-GIS software V. 10.3 and data collected by the ministry of health department of statistics were used.

Research on Urban Storm Flood Simulation by Coupling K-means Machine Learning Algorithm and GIS Spatial Analysis Technology into SWMM Model

Research on Urban Storm Flood Simulation by Coupling K-means Machine Learning Algorithm and GIS Spatial Analysis Technology into SWMM Model

Importance of ecosystem services and ecological security patterns on Hainan Island, China

The identification and restoration of damaged ecosystems are key to achieving ecological conservation and sustainable. Hainan Island is experiencing a serious crisis of biodiversity and habitat degradation. Therefore, its ecological conservation has become a priority and challenge for China. This study aimed to construct a multi-level ecological security pattern (ESP) based on the synergy of multiple ecosystem service functions and identify important ecological elements and ecological restoration areas. Based on the InVEST model, the circuit theory model, and a series of GIS spatial analysis methods, the importance of ecosystem functions (biodiversity maintenance, water conservation, carbon sequestration, and soil conservation) was evaluated, and ecological sources, ecological corridors, ecological pinch points, and ecological barrier points were identified. The results are as follows: 1) The best habitats in Hainan Island were distributed in the central mountainous area with diverse ecosystems, with an area of 10982.5 km2, accounting for 34.25% of the total suitable habitats. Low-level habitats are mainly distributed on tableland and coastal zones. Human disturbance is the direct cause of landscape patch fragmentation in low-level habitat areas. 2) A total of 65 large ecological sources with a total area of 8238.23 km2 were identified, which were concentrated in the biodiversity and water conservation areas in the central part of the island. 3) Crucial areas in Hainan Island mainly comprised forests and water bodies. Ecological corridors radiated across the entire area in the form of a spider web and connected all important ecological patches, including 138 ecological corridors (73 primary ecological corridors and 65 secondary ecological corridors), 222 ecological pinch points, and 198 ecological barrier points. In addition, the identified areas for restoration are primary areas in urgent need of protection and restoration. In general, the ecological pinch points are natural conservation areas supplemented by anthropogenic restoration, and the ecological barrier points demand equal attention for anthropogenic restoration and nature conservation. The ecosystem protection plan developed in this study will enrich the theoretical achievements of territorial spatial ecological planning in Hainan Island, and provides clear guidance for alleviating the contradiction between land use and economic development in Hainan Island.

Investigating Temporal and Spatial Variations of Nutrient and Trace Metal Loading in Utah Lake (Utah, USA)

Utah Lake is one of the largest freshwater bodies in the West and a valuable resource for agricultural and recreational activities in the region. However, it has suffered elevated trace metal and nutrient levels since the pioneer settlement in 1847. The objectives of this project were as follows: (1) investigate the temporal and spatial variations of trace metal and nutrient concentrations in Utah Lake and its tributaries; (2) model trace metal and nutrient concentrations across the lake using GIS spatial analysis techniques. We collected floc layer sediment samples quarterly as well as monthly water samples for trace metal and nutrient analyses at designated sites. GIS spatial analysis techniques were used to model the trace metal and nutrient concentrations in the lake. Elevated trace metal concentrations in river and lake water samples have been detected, especially in the month of June. The GIS modeling revealed that the highest trace metal and nutrient concentrations were located at the deepest part of the lake and near the Spanish Fork River inlet, respectively. Moreover, the results indicate that Utah Lake is not well mixed horizontally but well mixed vertically. Our findings can help state agencies address issues in water quality and management related to human–environment interactions.

Exploring the Impact of Land Use Scales on Water Quality Based on the Random Forest Model: A Case Study of the Shaying River Basin, China

Optimizing the land use structure is one of the most effective means of improving the surface water aquatic environment. The relationship between land use patterns and water quality is complex due to the influence of dams and sluices. To further investigate the impact of land use patterns on water quality in different basins, we use the Shaying River as an example, which is a typical tributary of the Huai River Basin. Utilizing 2020 land use data and surface water quality monitoring data from two periods, this study employs GIS spatial analysis, the Random Forest Model, redundancy analysis, and Partial Least-Squares Regression to quantitatively explore how different-scale buffer zone land use patterns impact surface water quality. The key findings include: (1) notable seasonal differences in water quality indicators within the basin. The Water Quality Index (WQI) is significantly better in the non-flood season compared to the flood season, with water quality deteriorating towards the lower reaches. Key indicators affecting water quality include dissolved oxygen (DO), ammonia nitrogen (NH3-N), total phosphorus (TP), and turbidity (Tur) in the flood season and NH3-N, permanganate index (CODMn), and electrical conductivity (EC) in the non-flood season. (2) Cultivated land and construction land are the main land uses in the basin. The sub-basin buffer zone was identified as the most effective scale for land use impact on water quality indicators in the Shaying River. (3) Partial Least-Squares Regression (PLSR) analysis revealed that cultivated land, construction land, and grass are the primary land use types influencing surface water quality changes, and the PLSR model is better during the non-flood season. Cultivated and construction lands show a positive correlation with most water quality indicators, while forest land, water bodies, and grasslands correlate positively with DO and negatively with other indicators. The study underscores that rational land use planning in the sub-basin is crucial for enhancing the quality of the surface water environment.

Parallel algorithm for multi-viewpoint viewshed analysis on the GPU grounded in target cluster segmentation

ABSTRACT Viewshed analysis is a significant method for GIS spatial analysis. The needed computational resources rise sharply with the increase in the number of viewpoints, making viewshed analysis inefficient in multi-viewpoint scenes. Building on the shadow map algorithm, a parallel algorithm for multi-viewpoint viewshed analysis based on target cluster segmentation for large-scale, multi-viewpoint complex three-dimensional scenes was proposed. Target cluster segmentation was achieved using uniform grid division and K-means spatial clustering, and visibility was determined by comparing the depths. The customized graphics processing unit (GPU) rendering pipeline was adopted to execute the algorithm efficiently and in parallel. The experimental results indicated that the efficiency of the proposed algorithm improves by 6.252%, 8.280%, and 9.047% on average for viewshed analysis with 150, 300, and 600 viewpoints, respectively, compared to the algorithm based solely on shadow map. It is also able to eliminate the majority of shadow acne, thus clearly improving accuracy. The algorithm is compatible with the terrain and features while fully utilizing the parallel computational capability of the GPU and avoiding the interpolation of the digital elevation model (DEM). It significantly improves the efficiency of analysis in large-scale and multi-viewpoint scenes.

Research on the Spatial and Temporal Distribution Evolution and Sustainable Development Mechanism of Smart Health and Elderly Care Demonstration Bases Based on GIS

Utilizing GIS technology and spatial analysis methodologies, this study endeavours to delve into and grasp the localized attributes of the regional units under investigation from a geographical vantage point, as well as the interrelationships among these units. This endeavour encompasses the identification and quantification of developmental patterns, the assessment of trends, and the resolution of any intricate issues about geographical location to make prognostications and informed decisions. Classic spatial analysis techniques such as the geographic concentration index, kernel density analysis, Thiessen polygons, and spatial autocorrelation analysis (Moran’s I index) are employed in this inquiry. Initially, the study utilized the nearest neighbour index and geographic concentration index to gauge the equilibrium, proximity, and concentration of the spatiotemporal distribution of smart health elderly care demonstration bases across 31 provinces in China. Upon confirming the spatial clustering and imbalance of the distribution of elderly care demonstration bases in China, kernel density analysis was applied to compute the density of point features surrounding each output raster cell and to visually represent the spatiotemporal distribution status of the bases. Finally, Thiessen polygons and spatial autocorrelation analysis (Moran’s I index) were introduced to further elucidate and validate the spatial distribution patterns of the elderly care demonstration bases. The findings of the research reveal that smart health and elderly care bases in China manifest spatial clustering, predominantly concentrated in the central and eastern regions of the country. The overarching pattern embodies a spatial model characterized by a “concentration in three poles with multiple cores surrounding”. Ultimately, the study offers recommendations for the nexus between three principal mechanisms: market-driven development mechanisms, policy-driven development mechanisms, and technology-driven development mechanisms, advocating for the further progression of intelligent construction to attain the sustainable development of demonstration bases. This research furnishes a scientific foundation for the planning and industrial advancement of pertinent departments.