ISPRS International Journal of Geo-Information

18 pages, 6796 KiB

Open AccessArticle

Integration of Spatial and Co-Existence Relationships to Improve Administrative Region Target Detection in Map Images

by Kaixuan Du, Fu Ren, Yong Wang, Xianghong Che, Jiping Liu, Jiaxin Hou and Zewei You

ISPRS Int. J. Geo-Inf. 2024, 13(6), 216; https://doi.org/10.3390/ijgi13060216 - 20 Jun 2024

Cited by 1 | Viewed by 854

Administrative regions are fundamental geographic elements on maps, thus making their detection in map images crucial to enhancing intelligent map interpretation. However, existing methods in this field primarily depend on the texture features within the images and do not account for the influence [...] Read more.

Administrative regions are fundamental geographic elements on maps, thus making their detection in map images crucial to enhancing intelligent map interpretation. However, existing methods in this field primarily depend on the texture features within the images and do not account for the influence of spatial and co-existence relationships among different targets. In this study, taking the administrative regions of the Chinese Mainland, Taiwan, Tibet, and Henan as test targets, we employed the spatial and co-existence relationships of pairs of targets to improve target detection performance. Firstly, these four regions were detected using a simple Single-Target Cascading detection model based on RetinaNet. Subsequently, the detection results were adjusted with the spatial and co-existence relationships of each pair of targets. The adjusted outcomes demonstrate a significant increase in target detection accuracy, as well as precision (from 0.62 to 0.96) and F1 score (from 0.76 to 0.88), for the Chinese Mainland target. This study contributes to the advancement of intelligent map interpretation. Full article

(This article belongs to the Topic Geocomputation and Artificial Intelligence for Mapping)

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25 pages, 6442 KiB

Open AccessArticle

Spatial and Temporal Changes and Influencing Factors of Capital Cities in Five Provinces of the Underdeveloped Regions of Northwest China

by Yuanbao Feng, Yujun Ma, Wei Jia, Sifa Shu, Hongda Li and Xiangyu Hu

ISPRS Int. J. Geo-Inf. 2024, 13(6), 215; https://doi.org/10.3390/ijgi13060215 - 19 Jun 2024

Viewed by 1139

Abstract

In recent years, China’s economy has experienced rapid development, and its cities have undergone rapid expansion; however, the development of cities in the northwest region has been relatively slow due to various geographical and economic constraints. Studying the urban expansion in these regions [...] Read more.

In recent years, China’s economy has experienced rapid development, and its cities have undergone rapid expansion; however, the development of cities in the northwest region has been relatively slow due to various geographical and economic constraints. Studying the urban expansion in these regions is of significant importance for regional planning and development. This study selected the provincial capitals of five underdeveloped provinces in northwestern China as the research sample and used Landsat TM/OLI remote-sensing imagery as the primary data, supplemented by Digital Elevation Model (DEM), meteorological, and socio-economic data, the study extracted urban impervious surfaces using the ENDISI and MNDWI indices. It analyzed the spatial and temporal characteristics of urban impervious surfaces from 1990 to 2020 using indicators such as urban expansion intensity, compactness and fractal dimension, centroid migration, and standard deviation ellipse. Furthermore, the study quantified the influencing factors using Geodetectors. The findings reveal the following: (1) From 1990 to 2020, impervious surfaces in the five cities continued to expand, with Xi’an experiencing the largest expansion area at 549.94 km² and Xining the smallest at only 132.83 km², with an expansion intensity of merely 2.99%. However, significant disparities existed in expansion intensity and area across different periods. (2) Overall, the compactness of the cities decreased by 47.6% while the overall fractal dimension increased by 2.85%, indicating a trend towards more dispersed and complex urban forms. (3) Expansion directions varied among the cities, with Xi’an and Urumqi expanding towards the northwest, Lanzhou towards the north, Yinchuan primarily towards the east, and Xining mainly towards the west. (4) Economic, demographic, and investment factors were identified as the primary influencers of urban expansion, exhibiting changes over different periods. Analyzing the similarities and differences in city development can offer valuable insights into urban construction and sustainable development in underdeveloped areas. Full article

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16 pages, 2922 KiB

Open AccessArticle

Identifying the Spatial Range of the Pearl River Delta Urban Agglomeration by Fusing Nighttime Light Data with Weibo Sign-In Data

by Yongwang Cao, Song Liu and Zaigao Yang

ISPRS Int. J. Geo-Inf. 2024, 13(6), 214; https://doi.org/10.3390/ijgi13060214 - 19 Jun 2024

Viewed by 1120

Abstract

Accurately identifying the spatial range of urban agglomerations holds significant practical importance for the precise allocation of various elements and coordinated development within urban agglomerations. However, current research predominantly focuses on the physical spaces of urban agglomerations, overlooking their sphere of influence. This [...] Read more.

Accurately identifying the spatial range of urban agglomerations holds significant practical importance for the precise allocation of various elements and coordinated development within urban agglomerations. However, current research predominantly focuses on the physical spaces of urban agglomerations, overlooking their sphere of influence. This study begins with the spatial interactions of population elements within urban agglomerations and fuses Weibo sign-in data with NTL data to identify the spatial range of urban agglomerations. It further compares and validates the results before and after the fusion of data. The results reveal that the accuracy of identifying the spatial range of urban agglomerations with the fusion of NTL data and Weibo sign-in data has improved by 7%, with a Kappa increase of 0.1766 compared to using NTL data alone, which indicates that fusing social media data can significantly enhance the accuracy of identifying the spatial range of urban agglomerations. This study proposes a novel approach for identifying the spatial range of urban agglomerations through the fusion of NTL data and social media data from a data fusion perspective. On one hand, it supplements the application of data fusion in the study of urban agglomeration spaces; on the other hand, it accurately identifies the spatial range of urban agglomerations, which holds great practical value for the sustainable development of urban agglomerations. Full article

(This article belongs to the Special Issue Application of Geographical Information System in Urban Design, Management or Evaluation)

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18 pages, 9602 KiB

Open AccessArticle

Shape Pattern Recognition of Building Footprints Using t-SNE Dimensionality Reduction Visualization

by Jingzhong Li and Kainan Mao

ISPRS Int. J. Geo-Inf. 2024, 13(6), 213; https://doi.org/10.3390/ijgi13060213 - 19 Jun 2024

Viewed by 757

Abstract

The shape pattern recognition of building footprints stands as a pivotal concern within GIS spatial cognition. In this study, we introduce a novel approach for the shape recognition of building footprints, leveraging t-distributed stochastic neighbor embedding (t-SNE) dimensionality reduction visualization. First, the Canonical [...] Read more.

The shape pattern recognition of building footprints stands as a pivotal concern within GIS spatial cognition. In this study, we introduce a novel approach for the shape recognition of building footprints, leveraging t-distributed stochastic neighbor embedding (t-SNE) dimensionality reduction visualization. First, the Canonical Time Warping (CTW) algorithm is employed to gauge the shape similarity distance of building footprints. Subsequently, the t-SNE model is utilized to map the building footprints, featuring varying numbers of coordinate vertices, onto points within the Cartesian coordinate system. The shape similarity distance serves as the input to the t-SNE model for parameter optimization. Lastly, building footprint shapes are identified through the inherent clustering patterns of points using a Gaussian Mixture Model (GMM). Experimental results demonstrate the method’s robustness to the translation, rotation, scaling, and mirroring of geometric objects, while effectively measuring shape similarity between building footprints. Furthermore, diverse types of building footprints are discernible through natural clustering in low-dimensional spaces, aligning closely with human visual perception. Full article

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18 pages, 5317 KiB

Open AccessArticle

Trajectory Compression with Spatio-Temporal Semantic Constraints

by Yan Zhou, Yunhan Zhang, Fangfang Zhang, Yeting Zhang and Xiaodi Wang

ISPRS Int. J. Geo-Inf. 2024, 13(6), 212; https://doi.org/10.3390/ijgi13060212 - 18 Jun 2024

Viewed by 734

Abstract

Most trajectory compression methods primarily focus on geometric similarity between compressed and original trajectories, lacking explainability of compression results due to ignoring semantic information. This paper proposes a spatio-temporal semantic constrained trajectory compression method. It constructs a new trajectory distance measurement model integrating [...] Read more.

Most trajectory compression methods primarily focus on geometric similarity between compressed and original trajectories, lacking explainability of compression results due to ignoring semantic information. This paper proposes a spatio-temporal semantic constrained trajectory compression method. It constructs a new trajectory distance measurement model integrating both semantic and spatio-temporal features. This model quantifies semantic features using information entropy and measures spatio-temporal features with synchronous Euclidean distance. The compression principle is to retain feature points with maximum spatio-temporal semantic distance from the original trajectory until the compression rate is satisfied. Experimental results show these methods closely resemble each other in maintaining geometric similarity of trajectories, but our method significantly outperforms DP, TD-TR, and CascadeSync methods in preserving semantic similarity of trajectories. This indicates that our method considers both geometric and semantic features during compression, resulting in the compressed trajectory becoming more interpretable. Full article

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23 pages, 11788 KiB

Open AccessArticle

Implementing Immersive Worlds for Metaverse-Based Participatory Design through Photogrammetry and Blockchain

by Nikolai Abramov, Havana Lankegowda, Shunwei Liu, Luigi Barazzetti, Carlo Beltracchi and Pierpaolo Ruttico

ISPRS Int. J. Geo-Inf. 2024, 13(6), 211; https://doi.org/10.3390/ijgi13060211 - 18 Jun 2024

Cited by 1 | Viewed by 999

Abstract

This paper explores participatory design methods for the interconnection of digital recording techniques, like digital photogrammetry and Gaussian splatting, with emerging domains such as the metaverse and blockchain technology. The focus lies in community engagement and the economic growth of urban and rural [...] Read more.

This paper explores participatory design methods for the interconnection of digital recording techniques, like digital photogrammetry and Gaussian splatting, with emerging domains such as the metaverse and blockchain technology. The focus lies in community engagement and the economic growth of urban and rural areas through blockchain integration, utilizing low-cost digitalization methods to create Web3 environments mirroring real settlements. Through a case study of an Italian village, the potential of participatory design and community-led development strategies in revitalizing neglected areas are explored, and the use of low-cost drone-based photogrammetry and Gaussian splatting in digitization are compared, highlighting their advantages and drawbacks considering the aim of this work, i.e., the creation of an interactive metaverse space. Ultimately, the study underscores the transformative role of digital technologies in reshaping design processes and fostering community development through a workflow, stressing collaborative decision-making and blockchain-driven economy, manufacturing, and maintenance through self-ownership models and performance-based smart contracts. Full article

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14 pages, 2504 KiB

Open AccessArticle

Traffic Flow Prediction Based on Federated Learning and Spatio-Temporal Graph Neural Networks

by Jian Feng, Cailing Du and Qi Mu

ISPRS Int. J. Geo-Inf. 2024, 13(6), 210; https://doi.org/10.3390/ijgi13060210 - 18 Jun 2024

Cited by 1 | Viewed by 1384

Abstract

In response to the insufficient consideration of spatio-temporal dependencies and traffic pattern similarity in traffic flow prediction methods based on federated learning, as well as the neglect of model heterogeneity and objective heterogeneity, a traffic flow prediction model based on federated learning and [...] Read more.

In response to the insufficient consideration of spatio-temporal dependencies and traffic pattern similarity in traffic flow prediction methods based on federated learning, as well as the neglect of model heterogeneity and objective heterogeneity, a traffic flow prediction model based on federated learning and spatio-temporal graph neural networks is proposed. The model is divided into two stages. In the road network division stage, the traffic road network is divided into subnetworks by the dynamic time warping algorithm and the K-means algorithm, to ensure the same subnetwork has the similar traffic flow pattern. The federated learning stage is divided into two sub-stages. In the local training phase, the spatio-temporal graph neural network with an attention mechanism is utilized to create personalized models and meme models to capture the spatio-temporal dependencies of each subnetwork. At the same time, deep mutual learning is utilized to address model heterogeneity and objective heterogeneity through knowledge distillation. In the global aggregation phase, a multi-factor weighted aggregation strategy is designed to measure the contribution of each local model to the global model, to enhance the fairness of aggregation. Three sets of experiments were conducted on two real datasets, and the experimental results demonstrate that the proposed model outperforms the baseline models in three common evaluation metrics. Full article

(This article belongs to the Special Issue Harnessing the Geospatial Data Revolution for Promoting Sustainable Transport Systems)

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14 pages, 29541 KiB

Open AccessArticle

A Type of Scale-Oriented Terrain Pattern Derived from Normalized Topographic Relief Layers and Its Interpretation

by Xi Nan, Ainong Li, Zhengwei He and Jinhu Bian

ISPRS Int. J. Geo-Inf. 2024, 13(6), 209; https://doi.org/10.3390/ijgi13060209 - 17 Jun 2024

Viewed by 843

Abstract

Topographic scale characteristics contain valuable information for interpreting landform structures, which is crucial for understanding the spatial differentiation of landforms across large areas. However, the absence of parameters that specifically describe the topographic scale characteristics hinders the quantitative representation of regional topography from [...] Read more.

Topographic scale characteristics contain valuable information for interpreting landform structures, which is crucial for understanding the spatial differentiation of landforms across large areas. However, the absence of parameters that specifically describe the topographic scale characteristics hinders the quantitative representation of regional topography from the perspective of spatial scales. In this study, false-color composite images were generated using normalized topographic relief data, showing a type of scale-oriented terrain pattern. Subsequent analysis indicated a direct correlation between the luminance of the patterns and the normalized topographic relief. Additionally, a linear correlation exists between the color of the patterns and the change rate in normalized topographic relief. Based on the analysis results, the issue of characterizing topographic scale effects was transformed into a problem of interpreting terrain patterns. The introduction of two parameters, flux and curl of topographic field, allowed for the interpretation of the terrain patterns. The assessment indicated that the calculated values of topographic field flux are equivalent to the luminance of the terrain patterns and the variations in the topographic field curl correspond with the spatial differentiation of colors in the terrain patterns. This study introduced a new approach to analyzing topographic scale characteristics, providing a pathway for quantitatively describing scale effects and automatically classifying landforms at a regional scale. Through exploratory analysis on artificially constructed simple DEMs and verification in four typical geomorphological regions of real terrain, it was shown that the terrain pattern method has better intuitiveness than the scale signature approach. It can reflect the scale characteristics of terrain in continuous space. Compared to the MTPCC image, the terrain parameters derived from the terrain pattern method further quantitatively describe the scale effects of the terrain. Full article

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26 pages, 36248 KiB

Open AccessArticle

Agent-Based Modeling of COVID-19 Transmission: A Case Study of Housing Densities in Sankalitnagar, Ahmedabad

by Molly French, Amit Patel, Abid Qureshi, Deepak Saxena and Raja Sengupta

ISPRS Int. J. Geo-Inf. 2024, 13(6), 208; https://doi.org/10.3390/ijgi13060208 - 17 Jun 2024

Viewed by 1247

Abstract

The differential transmission of COVID-19 depending on the socio-economic status of a neighborhood is well established. For example, several studies have shown that COVID-19 transmission was higher in poorer and denser neighborhoods than in wealthier ones. However, what is less well known is [...] Read more.

The differential transmission of COVID-19 depending on the socio-economic status of a neighborhood is well established. For example, several studies have shown that COVID-19 transmission was higher in poorer and denser neighborhoods than in wealthier ones. However, what is less well known is how this varied rate of transmission interacted with established health measures, i.e., face masks and lockdowns, in the context of developing countries to reduce pandemic cases and hence resulted in fewer deaths. This study uses an Agent-Based Model (ABM) simulation to examine the context and impacts of COVID-19 mitigation efforts (i.e., lockdowns combined with masks) on the transmission of COVID-19 across a single neighborhood in Ahmedabad, a city in the state of Gujarat, India. The model is parameterized using real-world population data, which allows us to simulate the spread of COVID-19 to find conditions that most closely match the realities of COVID-19 in the spring of 2020. Consequently, the simulation can be used to understand the impact of nation-wide lockdown on the spread of COVID cases across Ahmedabad as a function of housing density. Thus, invaluable insight into the effectiveness of a lockdown as a mitigation measure can be derived. Further information about how the effectiveness of the lockdown varied by neighborhood, as well as other factors that impacted it, can be ascertained. Full article

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14 pages, 9686 KiB

Open AccessFeature PaperArticle

Web Publication of Schmitt’s Map of Southern Germany (1797)—The Projection of the Map Based on Archival Documents and Geospatial Analysis

by Gábor Timár and Eszter Kiss

ISPRS Int. J. Geo-Inf. 2024, 13(6), 207; https://doi.org/10.3390/ijgi13060207 - 17 Jun 2024

Cited by 1 | Viewed by 3269

Abstract

This work shows the original projection of a 1:57,600 scale map of southern Germany at the end of the 18th century, produced under the direction of Karl-Heinrich von Schmitt (1743–1805). The sections of the map were scanned and georeferenced as part of the [...] Read more.

This work shows the original projection of a 1:57,600 scale map of southern Germany at the end of the 18th century, produced under the direction of Karl-Heinrich von Schmitt (1743–1805). The sections of the map were scanned and georeferenced as part of the MAPIRE project, and the results are publicly available. In the present work, we use contemporary documents, in particular the books of César-Francois Cassini de Thury and manuscript sketches of the map found in the Military Archive of Vienna, to show that the overall projection of the map is identical to that used in Cassini’s survey of France (first half of the 18th century). In the archive, we managed to find the overview sheet on which—in addition to the Paris Cassini coordinate system—the section grid of the Schmitt map was also constructed. This sketch served as the basis for the compilation and copying work, wherein the existing map works and survey sketches were inserted into 197 sections of the Schmitt map. Thus, the map coordinate system can be modeled in GIS systems using the Cassini (or Cassini-Soldner) projection, with the Paris Observatory as the projection origin. The georeferencing accuracy of using the pure Cassini projection is around 1–1.3 km (at the extremes, around 5 km), which is much more inaccurate than the one used in later topographic surveys. It is considered a combined result of the compilation of the different maps, presumably surveyed by graphic triangulation with measuring tables. Full article

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19 pages, 4817 KiB

Open AccessArticle

Land Cover Disaggregated Fire Occurrence and Particulate Matter_2.5 Relationship in the Mekong Region: A Comprehensive Study

by Nektaria Adaktylou, Dimitris Stratoulias, Julia Borgman, Sangwoo Cha, Devara P. Adiningrat and Narissara Nuthammachot

ISPRS Int. J. Geo-Inf. 2024, 13(6), 206; https://doi.org/10.3390/ijgi13060206 - 17 Jun 2024

Viewed by 909

Abstract

Air pollution has become an increasing concern in the Mekong region due to seasonal vegetative burning triggered by related anthropogenic activities and climate change. While the assumption of a correlation between agriculture burning and air pollution is a common postulation, little evidence exists [...] Read more.

Air pollution has become an increasing concern in the Mekong region due to seasonal vegetative burning triggered by related anthropogenic activities and climate change. While the assumption of a correlation between agriculture burning and air pollution is a common postulation, little evidence exists on the association between fire incidents and air pollution concentrations. The current study explores the relationship between satellite-derived fire occurrence, land surface characteristics, and particulate matter 2.5 (PM_2.5) concentrations for the five Lower Mekong countries, namely Cambodia, Laos, Myanmar, Thailand, and Vietnam, in an effort to gain new insights into fire distributions related to air quality. Publicly available daily active fire hotspots from the VIIRS satellite instrument, annual land cover products from the MODIS satellite, and mean monthly ground-level PM_2.5 estimates from the V5.GL.04 database were analyzed in two relational assessments; first, the distribution of VIIRS active fire counts and fire radiative power (FRP) temporally and spatially and secondly, the correlations between the monthly VIIRS active fire counts, cumulative monthly FRP and mean monthly PM_2.5 estimates per country and land cover type. The results suggest a statistically significant positive correlation between monthly fire counts, cumulative FRP, and PM_2.5 estimates for each country, which differ based on land cover. The strongest correlation between monthly fire incidences and PM_2.5 estimates was found in the case of Myanmar. For all countries combined, fires detected in forests displayed the highest correlation with monthly PM_2.5 estimates. This study demonstrates the use of the VIIRS active fire product and provides important insights into temporal and spatial fire distributions as baseline information for fire prevention and mitigation strategies in the Mekong region. Full article

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23 pages, 9797 KiB

Open AccessArticle

Identification of Typhoon-Vulnerable Areas and Countermeasures in High-Density Coastal Cities: The Case of Macau

by Ziyi Chen, Long Zhou, Wenrui Li and Binglin Martin Tang

ISPRS Int. J. Geo-Inf. 2024, 13(6), 205; https://doi.org/10.3390/ijgi13060205 - 17 Jun 2024

Viewed by 1171

Abstract

Typhoons are extremely severe weather events which seriously threaten the safety of people’s lives and properties. Therefore, identifying and controlling typhoon disaster hazards have become important research topics. The spatial–temporal characteristics of typhoons are analysed using the typhoon disaster data in Macau from [...] Read more.

Typhoons are extremely severe weather events which seriously threaten the safety of people’s lives and properties. Therefore, identifying and controlling typhoon disaster hazards have become important research topics. The spatial–temporal characteristics of typhoons are analysed using the typhoon disaster data in Macau from 2000 to 2020. Computational fluid dynamics (CFD) numerical simulation is adopted to understand the 3D urban wind environment. Moreover, the ‘exposure, sensitivity and adaptation’ evaluation model is applied to construct the study framework. To calculate urban disaster vulnerability, the Create Fishnet tool is used to divide the city of Macau into 470 grids. The principal component analysis method is used to reveal the factors that significantly affect the typhoon’s vulnerable areas. Result shows that 31.27% of grids are severely vulnerable. In addition, six principal components are identified, including indicators such as population density, building area ratio, mean elevation and wind speed. This study verifies the feasibility of wind speed data obtained by CFD in the typhoon evaluation model. Moreover, it provides a reliable reference guide for future urban microlevel studies. Full article

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28 pages, 112056 KiB

Open AccessArticle

Spatiotemporal Analysis of Ecological Security Based on Landscape Patterns

by Huaidan Zhang, Ke Nie and Xueling Wu

ISPRS Int. J. Geo-Inf. 2024, 13(6), 204; https://doi.org/10.3390/ijgi13060204 - 16 Jun 2024

Viewed by 835

Abstract

With rapid urbanization, environmental problems such as soil erosion and resource shortages have emerged. Ecological environmental quality is decreasing, and ecological security issues are becoming increasingly prominent; thus, relevant research is particularly urgent. The ecological security issue is complex due to many influencing [...] Read more.

With rapid urbanization, environmental problems such as soil erosion and resource shortages have emerged. Ecological environmental quality is decreasing, and ecological security issues are becoming increasingly prominent; thus, relevant research is particularly urgent. The ecological security issue is complex due to many influencing factors. The transformation of landscape type is the most important factor affecting ecological security. Therefore, there is an urgent need to optimize and screen for the indicator factors that affect ecological security, carry out a dynamic evaluation of ecological security based on landscape pattern analysis, and analyze the driving forces behind ecological security changes. Song County is located in the ecological core area of the Funiu Mountains in western Henan, with complex topography and geomorphology; large changes in landscape patterns in recent years; frequent geological disasters, which have posed a greater threat to people’s life and property safety; and significant ecological security problems. This paper takes Song County as the research area, using the decision tree model to obtain the land use classification results of four periods in Song County in 2005, 2010, 2015, and 2020 based on remote sensing images. Landscape pattern analysis is conducted from two aspects: patch level and landscape level. On this basis, ecological security evaluation indicators are constructed from three levels: pressure, state, and response, and the comprehensive index model is used to obtain the results of four ecological security evaluations. Exploratory spatial data analysis (ESDA) is used to conduct research and prediction on spatiotemporal differentiation. Finally, the spatial heterogeneity relationship between the ecological security level and its driving factors in Song County is quantitatively analyzed using a geographic detector model. The results clearly show that the overall landscape form gradually tends to develop in the direction of complex irregularity. Due to frequent geological disasters and strong human engineering activities near the core areas of the Luhun Reservoir and Yi River basin, as well as Baihejie Village in Baihe Township and Che Village in Muzhijie Township, the landscape pattern is changing considerably. The self-restoration ability of the land’s ecosystem is gradually weakening, and the degree of ecological damage is gradually accelerating. The ecological security level is unsafe, the area of unsafe security is gradually increasing, and the ecological security index (ESI) will continue to decrease in the future. To improve ecological security, we recommend paying attention to land conservation and rational utilization while pursuing economic development. Full article

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19 pages, 4591 KiB

Open AccessArticle

Generating Urban Road Networks with Conditional Diffusion Models

by Xiaoyan Gu, Mengmeng Zhang, Jinxin Lyu and Quansheng Ge

ISPRS Int. J. Geo-Inf. 2024, 13(6), 203; https://doi.org/10.3390/ijgi13060203 - 16 Jun 2024

Viewed by 1188

Abstract

The auto-generation of urban roads can greatly improve efficiency and productivity in urban planning and designing. However, it has also raised concerns amongst researchers over the past decade. In this paper, we present an image-based urban road network generation framework using conditional diffusion [...] Read more.

The auto-generation of urban roads can greatly improve efficiency and productivity in urban planning and designing. However, it has also raised concerns amongst researchers over the past decade. In this paper, we present an image-based urban road network generation framework using conditional diffusion models. We first trained a diffusion model capable of generating road images with similar characteristics to the ground truth using four context factors. Then, we used the trained model as the generator to synthesize road images conditioned in a geospatial context. Finally, we converted the generated road images into road networks with several post-processes. The experiments conducted in five cities of the United States showed that our model can generate reasonable road networks, maintaining the layouts and styles of real examples. Moreover, our model has the ability to show the obstructive effect of geographic barriers on urban roads. By comparing models with different context factors as input, we find that the model that considers all four factors generally performs the best. The most important factor in guiding the shape of road networks is intersections, implying that the development of urban roads is not only restricted by the natural environment but is more strongly influenced by human design. Full article

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29 pages, 15331 KiB

Open AccessArticle

Dynamic Construction of Spherical Raster Voronoi Diagrams Based on Ordered Dilation

by Qingping Liu, Xuesheng Zhao, Yuanzheng Duan, Mengmeng Qin, Wenlan Xie and Wenbin Sun

ISPRS Int. J. Geo-Inf. 2024, 13(6), 202; https://doi.org/10.3390/ijgi13060202 - 14 Jun 2024

Viewed by 1315

Abstract

The Voronoi diagram on the Earth’s surface is a significant data model, characterized by natural proximity and dynamic stability, which has emerged as one of the most promising solutions for global spatial dynamic management and analysis. However, traditional algorithms for generating spherical raster [...] Read more.

The Voronoi diagram on the Earth’s surface is a significant data model, characterized by natural proximity and dynamic stability, which has emerged as one of the most promising solutions for global spatial dynamic management and analysis. However, traditional algorithms for generating spherical raster Voronoi diagrams find it challenging to dynamically adjust the Voronoi diagram while maintaining precision and efficiency. The efficient and accurate construction of the spherical Voronoi diagram has become one of the bottleneck issues limiting its further large-scale application. To this end, this paper proposes a dynamic construction scheme for the spherical Voronoi diagram based on the QTM (Quaternary Triangular Mesh) system, with the aim of enabling efficient generation, local updates, and multi-scale visualization of the spherical Voronoi diagrams. In this paper, canonical ordering is introduced. Tailored for the properties of the spherical triangular grid, it constructs a unified and standardized sorting strategy for the dilation of the spherical grids. The construction and updating of the spherical Voronoi diagram are achieved through the ordered dilation of sites. Furthermore, the multi-scale visualization of the spherical Voronoi diagram is realized through the hierarchical structure of the QTM. The paper presents our algorithm intuitively through pseudocode, conducts comparative experiments on the feasibility and efficiency, and designs an experiment for the dynamic navigation and management of ocean-going vessels based on the global multi-resolution Voronoi diagram. The experimental results demonstrate that our algorithm effectively controls the error of the generation of the raster Voronoi diagram and has a significant efficiency advantage when processing dynamic environments. Full article

(This article belongs to the Topic Technological Innovation and Emerging Operational Applications in Digital Earth)

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20 pages, 5055 KiB

Open AccessArticle

Automatic Extraction and Cluster Analysis of Natural Disaster Metadata Based on the Unified Metadata Framework

by Zongmin Wang, Xujie Shi, Haibo Yang, Bo Yu and Yingchun Cai

ISPRS Int. J. Geo-Inf. 2024, 13(6), 201; https://doi.org/10.3390/ijgi13060201 - 14 Jun 2024

Viewed by 927

Abstract

The development of information technology has led to massive, multidimensional, and heterogeneously sourced disaster data. However, there’s currently no universal metadata standard for managing natural disasters. Common pre-training models for information extraction requiring extensive training data show somewhat limited effectiveness, with limited annotated [...] Read more.

The development of information technology has led to massive, multidimensional, and heterogeneously sourced disaster data. However, there’s currently no universal metadata standard for managing natural disasters. Common pre-training models for information extraction requiring extensive training data show somewhat limited effectiveness, with limited annotated resources. This study establishes a unified natural disaster metadata standard, utilizes self-trained universal information extraction (UIE) models and Python libraries to extract metadata stored in both structured and unstructured forms, and analyzes the results using the Word2vec-Kmeans cluster algorithm. The results show that (1) the self-trained UIE model, with a learning rate of 3 × 10⁻⁴ and a batch_size of 32, significantly improves extraction results for various natural disasters by over 50%. Our optimized UIE model outperforms many other extraction methods in terms of precision, recall, and F1 scores. (2) The quality assessments of consistency, completeness, and accuracy for ten tables all exceed 0.80, with variances between the three dimensions being 0.04, 0.03, and 0.05. The overall evaluation of data items of tables also exceeds 0.80, consistent with the results at the table level. The metadata model framework constructed in this study demonstrates high-quality stability. (3) Taking the flood dataset as an example, clustering reveals five main themes with high similarity within clusters, and the differences between clusters are deemed significant relative to the differences within clusters at a significance level of 0.01. Overall, this experiment supports effective sharing of disaster data resources and enhances natural disaster emergency response efficiency. Full article

(This article belongs to the Special Issue Unlocking the Power of Geospatial Data: Semantic Information Extraction, Ontology Engineering, and Deep Learning for Knowledge Discovery)

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16 pages, 7662 KiB

Open AccessArticle

Exploring the Influence of Terrain Blockage on Spatiotemporal Variations in Land Surface Temperature from the Perspective of Heat Energy Redistribution

by Hong Gao, Yong Dong, Liang Zhou and Xi Wang

ISPRS Int. J. Geo-Inf. 2024, 13(6), 200; https://doi.org/10.3390/ijgi13060200 - 14 Jun 2024

Viewed by 821

Abstract

Land surface temperature (LST) is a critical indicator of the earth’s surface environment, which has significant implications for research on the ecological environment and climate change. The influence of terrain on LST is complex due to its rugged and varied surface topography. The [...] Read more.

Land surface temperature (LST) is a critical indicator of the earth’s surface environment, which has significant implications for research on the ecological environment and climate change. The influence of terrain on LST is complex due to its rugged and varied surface topography. The relationship between traditional terrain features and LST has been comprehensively discussed in the literature; however, terrain blockage has received less attention and could influence LST by hindering the redistribution of heat energy in mountain regions. Here, we investigate the influence of terrain blockage on the spatiotemporal variation in LST in mountain regions. We first propose a terrain feature framework to characterize the effect of terrain blockage from the perspective of heat energy redistribution and then adopt a random forest model to analyze the relationship between terrain blockage features and LST over a whole year. The results show that terrain blockage significantly influences the spatial heterogeneity of LST, which can be effectively simulated based on terrain blockage features, with a mean deviation of less than 0.15 K. Terrain blockage has a more pronounced influence on LST during the four months from June to September. This influence is also more evident during nighttime than daytime. Regarding LST in mountain regions, local terrain blockage features have a greater influence than global terrain blockage features. In spatial terms, the influence of terrain blockage on LST is uniform. Moreover, the diurnal variation in LST can also be effectively simulated based on terrain blockage. The contribution of this study lies in the finding that terrain blockage can influence the spatiotemporal variation in LST through the process of heat energy redistribution. The terrain blockage features proposed in this study may be useful for other studies of the ecological environment in mountain regions. Full article

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23 pages, 4085 KiB

Open AccessArticle

Effectiveness of Adjacent and Bivariate Maps in Communicating Global Sensitivity Analysis for Geodiversity Assessment

by Piotr Jankowski, Seda Şalap-Ayça, Alicja Najwer, Arika Ligmann-Zielińska and Zbigniew Zwoliński

ISPRS Int. J. Geo-Inf. 2024, 13(6), 199; https://doi.org/10.3390/ijgi13060199 - 13 Jun 2024

Viewed by 912

Abstract

This study compares adjacent and bivariate maps in communicating variance-based global sensitivity analysis (GSA) results for a geodiversity assessment spatial multi-criteria model and examines the influence of prior exposure to geodiversity and map reading skills on interpretation. It analyzes the quality of map [...] Read more.

This study compares adjacent and bivariate maps in communicating variance-based global sensitivity analysis (GSA) results for a geodiversity assessment spatial multi-criteria model and examines the influence of prior exposure to geodiversity and map reading skills on interpretation. It analyzes the quality of map interpretation, confidence levels, and map communication effectiveness. The findings indicate that there is no significant difference in the quality of map interpretation or confidence levels between the two map types. However, there are nuanced differences in interpretive patterns, suggesting the need for further investigation into factors affecting map interpretation. Adjacent maps are more effective in identifying factors linked to uncertainty in high geodiversity values, while bivariate maps excel in understanding spatial variability. Prior exposure to geodiversity and map reading skills do not significantly impact interpretation quality or confidence levels. Future research could explore other factors influencing map effectiveness and explore the cognitive processes underlying map interpretation. Understanding these processes could lead to more effective strategies for communicating the results of a GSA for spatial models through maps. Full article

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18 pages, 18337 KiB

Open AccessArticle

A Novel Approach to Urban Village Extraction and Generalization from Digital Line Graphics Using the Computational Geometric Method and the Modified Hausdorff Distance

by Xiaorong Gao, Haowen Yan, Xiaomin Lu, Xiaolong Wang and Rong Wang

ISPRS Int. J. Geo-Inf. 2024, 13(6), 198; https://doi.org/10.3390/ijgi13060198 - 13 Jun 2024

Viewed by 1002

Abstract

Urban villages represent informal residential areas emerging since China’s rapid urbanization process. Scientific map generalization of urban villages with scientific maps aids readers in discerning their distribution and making informed decisions concerning them. However, there is still a scarcity of research on the [...] Read more.

Urban villages represent informal residential areas emerging since China’s rapid urbanization process. Scientific map generalization of urban villages with scientific maps aids readers in discerning their distribution and making informed decisions concerning them. However, there is still a scarcity of research on the automatic extraction and generalization of urban villages from vector data, which needs to be studied to further improve the expression of maps. To address this problem, this paper presents a methodology for the extraction and generalization of urban villages from Digital Line Graphics. Firstly, a heuristic approach is employed to analyze the atypical morphological characteristics of urban villages. Then, indices based on computational geometry and the modified Hausdorff distance are utilized to quantify these traits. Lastly, an automatic generalization principle for urban villages is offered. The approach was tested in experimental blocks and proved to be effective. It offers a novel method for the automatic extraction and cartography of urban villages. Full article

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22 pages, 4281 KiB

Open AccessArticle

Non-Uniform Spatial Partitions and Optimized Trajectory Segments for Storage and Indexing of Massive GPS Trajectory Data

by Yuqi Yang, Xiaoqing Zuo, Kang Zhao and Yongfa Li

ISPRS Int. J. Geo-Inf. 2024, 13(6), 197; https://doi.org/10.3390/ijgi13060197 - 12 Jun 2024

Cited by 1 | Viewed by 971

Abstract

The presence of abundant spatio-temporal information based on the location of mobile objects in publicly accessible GPS mobile devices makes it crucial to collect, analyze, and mine such information. Therefore, it is necessary to index a large volume of trajectory data to facilitate [...] Read more.

The presence of abundant spatio-temporal information based on the location of mobile objects in publicly accessible GPS mobile devices makes it crucial to collect, analyze, and mine such information. Therefore, it is necessary to index a large volume of trajectory data to facilitate efficient trajectory retrieval and access. It is difficult for existing indexing methods that primarily rely on data-driven indexing structures (such as R-Tree) or space-driven indexing structures (such as Quadtree) to support efficient analysis and computation of data based on spatio-temporal range queries as a service basis, especially when applied to massive trajectory data. In this study, we propose a massive GPS data storage and indexing method based on uneven spatial segmentation and trajectory optimization segmentation. Primarily, the method divides GPS trajectories in a large spatio-temporal data space into multiple MBR sequences by greedy algorithm. Then, a hybrid indexing model for segmented trajectories is constructed to form a global spatio-temporal segmentation scheme, called HHBITS index, to achieve hierarchical organization of trajectory data. Eventually, a spatio-temporal range query processing method is proposed based on this index. This paper implements and evaluates the index in MongoDB and compares it with two other spatio-temporal composite indexes for performing spatio-temporal range queries efficiently. The experimental results show that the method in this paper has high performance in responding to spatio-temporal queries on large-scale trajectory data. Full article

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33 pages, 10982 KiB

Open AccessReview

Assessing Contamination in Transitional Waters Using Geospatial Technologies: A Review

by Itzel Arroyo-Ortega, Yaselda Chavarin-Pineda and Eduardo Torres

ISPRS Int. J. Geo-Inf. 2024, 13(6), 196; https://doi.org/10.3390/ijgi13060196 - 12 Jun 2024

Viewed by 1484

Abstract

Transitional waters (TWs) are relevant ecological and economical ecosystems that include estuaries, deltas, bays, wetlands, marshes, coastal lakes, and coastal lagoons and play a central role in providing food, protecting coastal environments, and regulating nutrients. However, human activities such as industrialization, urbanization, tourism, [...] Read more.

Transitional waters (TWs) are relevant ecological and economical ecosystems that include estuaries, deltas, bays, wetlands, marshes, coastal lakes, and coastal lagoons and play a central role in providing food, protecting coastal environments, and regulating nutrients. However, human activities such as industrialization, urbanization, tourism, and agriculture are threatening these ecosystems, which results in contamination and habitat degradation. Therefore, it is essential to evaluate contamination in TW to develop effective management and protection strategies. This study analyses the application of geospatial technologies (GTS) for monitoring and predicting contaminant distribution in TW. Cartography, interpolation, complex spatial methods, and remote sensing were applied to assess contamination profiles by heavy metals, and persistent organic compounds, and analyze contamination indices or some physicochemical water parameters. It is concluded that integrating environmental and demographic data with GTS would help to identify critical points of contamination and promote ecosystem resilience to ensure long-term health and human well-being. This review comprehensively analyzes the methods, indicators, and indices used to assess contamination in transitional waters in conjunction with GTS. It offers a valuable foundation for planning future research on pollution in these types of waters or other similar water bodies worldwide. Full article

(This article belongs to the Special Issue HealthScape: Intersections of Health, Environment, and GIS&T)

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14 pages, 5867 KiB

Open AccessArticle

Identifying Editions of the Ptolemy of Rome Maps (1478/90–1507/08) by Copper Plates Changes

by Marcos F. Pavo-López and José-Lázaro Amaro-Mellado

ISPRS Int. J. Geo-Inf. 2024, 13(6), 195; https://doi.org/10.3390/ijgi13060195 - 12 Jun 2024

Viewed by 917

Abstract

Traditionally, it has been considered that the Ptolemaic or classical maps from the four editions of Ptolemy’s Geography published in Rome (1478, 1490, 1507, and 1508) are apparently indistinguishable at first glance because they have been printed from the same plates. This poses [...] Read more.

Traditionally, it has been considered that the Ptolemaic or classical maps from the four editions of Ptolemy’s Geography published in Rome (1478, 1490, 1507, and 1508) are apparently indistinguishable at first glance because they have been printed from the same plates. This poses a problem for antiquarians, collectors, and curators who wish to accurately date their copies. Recently, two very comprehensive articles have been published on the different paper watermarks associated with each edition, which would allow for the correct identification of each one. However, there are occasions when the maps do not display watermarks. This article aims to provide some keys to distinguish between the incunabula editions (1478, 1490) and those of 1507–1508 in cases of the absence of watermarks. In this process of detecting differences, we have used digitized images of the maps. The results show small modifications in the copper plates made between the editions of 1490 and 1507/08. Our findings reveal that seven previously unknown reworked maps have been identified. Full article

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17 pages, 297 KiB

Open AccessArticle

The Relationship between the Construction of Transportation Infrastructure and the Development of New Urbanization

by Jia Shen, Xiaohong Ren, Honglin Wu and Zhitao Feng

ISPRS Int. J. Geo-Inf. 2024, 13(6), 194; https://doi.org/10.3390/ijgi13060194 - 12 Jun 2024

Viewed by 1067

Abstract

Transport infrastructure plays a crucial role in facilitating the high-quality development of new urbanization. Based on the provincial panel data of 31 provinces in China from 2013 to 2020, this study empirically analyzed the impact and mechanism of transportation infrastructure on the high-quality [...] Read more.

Transport infrastructure plays a crucial role in facilitating the high-quality development of new urbanization. Based on the provincial panel data of 31 provinces in China from 2013 to 2020, this study empirically analyzed the impact and mechanism of transportation infrastructure on the high-quality development of new urbanization from multiple perspectives. The results showed that transportation infrastructure can significantly promote the development of new urbanization, and the promoting effect was significantly positive in the eastern and western regions, while it was positive but not significant in the central region. Transportation infrastructure can promote the development of new urbanization by promoting industrial agglomeration. When the population density is lower than the corresponding threshold value, the transport infrastructure can significantly promote the development of new urbanization; when the population density is higher than the corresponding threshold value, the transport infrastructure will significantly hinder the development of new urbanization. Transport infrastructure has a significant positive spatial spillover effect on the development of new urbanization, and the positive spatial spillover effect has been significant in the eastern, central and western regions. Full article

(This article belongs to the Special Issue Application of Geographical Information System in Urban Design, Management or Evaluation)

14 pages, 3735 KiB

Open AccessArticle

Learning Effective Geometry Representation from Videos for Self-Supervised Monocular Depth Estimation

by Hailiang Zhao, Yongyi Kong, Chonghao Zhang, Haoji Zhang and Jiansen Zhao

ISPRS Int. J. Geo-Inf. 2024, 13(6), 193; https://doi.org/10.3390/ijgi13060193 - 11 Jun 2024

Viewed by 1070

Abstract

Recent studies on self-supervised monocular depth estimation have achieved promising results, which are mainly based on the joint optimization of depth and pose estimation via high-level photometric loss. However, how to learn the latent and beneficial task-specific geometry representation from videos is still [...] Read more.

Recent studies on self-supervised monocular depth estimation have achieved promising results, which are mainly based on the joint optimization of depth and pose estimation via high-level photometric loss. However, how to learn the latent and beneficial task-specific geometry representation from videos is still far from being explored. To tackle this issue, we propose two novel schemes to learn more effective representation from monocular videos: (i) an Inter-task Attention Model (IAM) to learn the geometric correlation representation between the depth and pose learning networks to make structure and motion information mutually beneficial; (ii) a Spatial-Temporal Memory Module (STMM) to exploit long-range geometric context representation among consecutive frames both spatially and temporally. Systematic ablation studies are conducted to demonstrate the effectiveness of each component. Evaluations on KITTI show that our method outperforms current state-of-the-art techniques. Full article

(This article belongs to the Topic 3D Computer Vision and Smart Building and City, 2nd Volume)

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28 pages, 5442 KiB

Open AccessArticle

Research on the Geographical Pattern, Evolution Model, and Driving Mechanism of Carbon Emission Density from Urban Industrial Land in the Yangtze River Economic Belt of China

by Fei Xie, Shuaibing Zhang, Qipeng Zhang, Sidong Zhao and Min Lai

ISPRS Int. J. Geo-Inf. 2024, 13(6), 192; https://doi.org/10.3390/ijgi13060192 - 8 Jun 2024

Cited by 2 | Viewed by 1627

Abstract

To achieve the goals of “carbon peaking and carbon neutrality”, this paper puts forward the connotation and measurement method for the carbon emission intensity of urban industrial land and conducts an empirical study with the Yangtze River Economic Belt (YREB) as an example. [...] Read more.

To achieve the goals of “carbon peaking and carbon neutrality”, this paper puts forward the connotation and measurement method for the carbon emission intensity of urban industrial land and conducts an empirical study with the Yangtze River Economic Belt (YREB) as an example. We defined the carbon intensity of urban industrial land as the industrial carbon emissions per unit area of land, which is a spatial mapping of urban industrial economic development and carbon spillover and a key indicator for urban and territorial spatial planning oriented towards the “dual carbon” goal. Findings: The carbon emission density of industrial land in the YREB varied greatly between cities and exhibited significant positive spatial autocorrelation. In addition, the geographical pattern and spatio-temporal evolution model of the urban industrial land carbon emission density had a very complex driving mechanism, and different factors had significant synergistic effects. Therefore, it is suggested that while striving towards the goal of “dual carbon”, the government should incorporate the carbon emission density indicator of urban industrial land into the urban and territorial spatial planning system, and based on the threshold of the medium suitable density, they should design differentiated management policies according to concrete urban policies and encourage cooperation among cities to jointly promote carbon emission management of urban industrial land. In policy design, emphasis should also be placed on highlighting the interactive effects of foreign direct investment, fiscal expenditure, and the number of patent authorizations as well as constructing a combination of policies centered around them to better leverage the impacts of globalization, government intervention, and innovation. Full article

(This article belongs to the Special Issue Geographic Information Systems and Cartography for a Sustainable World)

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23 pages, 7330 KiB

Open AccessArticle

Dry–Wet Changes in a Typical Agriculture and Pasture Ecotone in China between 1540 and 2019

by Xiaodong Wang, Yujia Song, Yu An, Xiaohui Liu and Xiaoqiang Li

ISPRS Int. J. Geo-Inf. 2024, 13(6), 191; https://doi.org/10.3390/ijgi13060191 - 7 Jun 2024

Viewed by 952

Abstract

Exploring periodic dry–wet changes is an important topic in climate change research due to its impact on drought and flood disasters. The purpose of this research was to determine the occurrence law of dry–wet changes in China on a scale of several hundred [...] Read more.

Exploring periodic dry–wet changes is an important topic in climate change research due to its impact on drought and flood disasters. The purpose of this research was to determine the occurrence law of dry–wet changes in China on a scale of several hundred years, using the example of transitional zones. In this study, we analyzed typical areas of the ecotone between agricultural land and pasture along the Great Wall of China. The ring width index of Carya cathayensis was fitted with the March–August Palmer drought severity index (PDSI₃₈). The PDSI₃₈ was divided into different periods using the stepwise function fitting method. The results indicated that there were two dry periods and one wet period in the region from 1543 to 2019. In each dry and wet period, there were also different temporal periods, including long (decades), intermediate (ten years), and short periods (several years). Drought represents a significant threat to agricultural production in China. In the first dry period (1543–1756), four periods with low PDSI₃₈ values (1633–1635, PDSI₃₈ = −1.71; 1636–1939, PDSI₃₈ = −3.35; 1640–1642, PDSI₃₈ = −4.68; and 1643–1645, PDSI₃₈ = −2.92) occurred, during which severe droughts (PDSI₃₈ < −4) lasted for 13 years. The dry–wet change showed the characteristics of a 12-year or multiple 12-year cycle. The results can be used to prepare to effectively address extreme drought scenarios worldwide in the future. Full article

(This article belongs to the Topic Climate Change Impacts and Adaptation: Interdisciplinary Perspectives)

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20 pages, 8983 KiB

Open AccessArticle

Analysing the Spatio-Temporal Variations of Urban Street Summer Solar Radiation through Historical Street View Images: A Case Study of Shanghai, China

by Lei Wang, Longhao Zhang and Jie He

ISPRS Int. J. Geo-Inf. 2024, 13(6), 190; https://doi.org/10.3390/ijgi13060190 - 7 Jun 2024

Viewed by 989

Abstract

Understanding solar radiation in urban street spaces is crucial for comprehending residents’ environmental experiences and enhancing their quality of life. However, existing studies rarely focus on the patterns of urban street solar radiation over time and across different urban and suburban areas. In [...] Read more.

Understanding solar radiation in urban street spaces is crucial for comprehending residents’ environmental experiences and enhancing their quality of life. However, existing studies rarely focus on the patterns of urban street solar radiation over time and across different urban and suburban areas. In this study, street view images from the summers of 2013 and 2019 in Shanghai were used to calculate solar radiation in urban street spaces. The results show a general decrease in street solar radiation in 2019 compared to 2013, with an average drop of 12.34%. The decrease was most significant in October (13.47%) and least in May (11.71%). In terms of solar radiation data gathered from street view sampling points, 76.57% showed a decrease, while 23.43% showed an increase. Spatially, solar radiation decreased by 79.66% for every additional 1.5 km from the city centre. In summary, solar radiation generally shows a decreasing trend, with significant variations between different areas. These findings are vitally important for guiding urban planning, optimising green infrastructure, and enhancing the urban ecological environment, further promoting sustainable urban development and improving residents’ quality of life. Full article

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21 pages, 6726 KiB

Open AccessArticle

Research on Rural Environments’ Effects on Well-Being: The Huizhou Area in China

by Xingmeng Ma, Xin Su, Yanlong Guo and Linfu Zhang

ISPRS Int. J. Geo-Inf. 2024, 13(6), 189; https://doi.org/10.3390/ijgi13060189 - 6 Jun 2024

Cited by 1 | Viewed by 1203

Abstract

The Huizhou region is an important area of traditional Chinese culture, and currently, the state of the village’s surroundings in this area is still not perfect. In this study, seven districts (counties) in the Huizhou region were selected for research. The Rural Habitat [...] Read more.

The Huizhou region is an important area of traditional Chinese culture, and currently, the state of the village’s surroundings in this area is still not perfect. In this study, seven districts (counties) in the Huizhou region were selected for research. The Rural Habitat Environment (RHES) Indicator Program is based on the concept of Socio-Economic-Natural Complex Ecosystems (SENCE) and constructs 18 metrics in three dimensions. Trends and influencing factors were analyzed using entropy weight TOPSIS and a Grey Relational Analysis (GRA) for the years 2013–2022, and spatial and temporal evolution was measured using Geographic Information Systems (GISs). The findings show that the composite index for the Huizhou region grew from 2013 (0.3197) to 2022 (0.6806). Second, the Tunxi District belongs to the high index–high economy category. The Shexian, Xiuning, and Qimen counties belong to the high index–low economy category. Huizhou District and Huangshan District belong to the low index–high economy category. Yixian County belongs to the low index–low economy category. Third, all districts (counties) show an upward trend, and Huangshan District has the best RHES condition. Shexian County ranks relatively low in the comprehensive index. Full article

(This article belongs to the Topic Advances in Multi-Scale Geographic Environmental Monitoring: Theory, Methodology and Applications)

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20 pages, 21478 KiB

Open AccessArticle

Identifying the Hierarchical Structure of Nighttime Economic Agglomerations Based on the Fusion of Multisource Data

by Weijie Wan, Hongfei Chen, Xiping Yang, Renda Li, Yuzheng Cui and Yiyang Hu

ISPRS Int. J. Geo-Inf. 2024, 13(6), 188; https://doi.org/10.3390/ijgi13060188 - 6 Jun 2024

Viewed by 935

Abstract

Nighttime economic development is an important driving force in urban economic development, and identification of the levels and boundary ranges of nighttime economic agglomerations is an important part of the management of the nighttime economy. Previous studies have been limited by the use [...] Read more.

Nighttime economic development is an important driving force in urban economic development, and identification of the levels and boundary ranges of nighttime economic agglomerations is an important part of the management of the nighttime economy. Previous studies have been limited by the use of a single data source to identify nighttime economic agglomerations. To address this limitation, multisource data fusion was used in this study to integrate nighttime lighting data, point of interest data, and check-in data and to assess the nighttime economy more comprehensively from the perspectives of both providers and receivers in the nighttime economy. To identify the hierarchical structure and boundaries of nighttime economic agglomerations accurately, a two-step method was used to identify local hotspots of the nighttime economy, divide the nighttime economic agglomerations into levels, and explore the spatial distribution and functional characteristics of different levels of nighttime economic zones. Comparative experiments showed the method used in this study to be rational and accurate. The methods and results of this study can provide a more comprehensive approach to the precise identification of nighttime economic agglomerations and guidance for the future planning, rational development, and management of nighttime economic agglomerations. Full article

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20 pages, 7840 KiB

Open AccessArticle

Simplifying Land Cover-Geoprocessing-Model Migration with a PAMC-LC Containerization Strategy in the Open Web Environment

by Huaqiao Xing, Haihang Wang, Denghai Gao, Dongyang Hou and Huayi Wu

ISPRS Int. J. Geo-Inf. 2024, 13(6), 187; https://doi.org/10.3390/ijgi13060187 - 3 Jun 2024

Viewed by 940

Abstract

Land cover and its changes over time are significant for better understanding the Earth’s fundamental characteristics and processes, such as global climate change, hydrology, and the carbon cycle. A number of land cover-geoprocessing models have been proposed for land cover-data production with different [...] Read more.

Land cover and its changes over time are significant for better understanding the Earth’s fundamental characteristics and processes, such as global climate change, hydrology, and the carbon cycle. A number of land cover-geoprocessing models have been proposed for land cover-data production with different spatial and temporal resolutions. With the massive growth in land cover data and the increasing demand for efficient model utilization, developing efficient and convenient land cover-geoprocessing models has become a formidable challenge. Although some model-migration methods have been proposed for handling the massive data, the intricacy of land cover-data and -heterogeneity models frequently prevent current strategies from directly meeting demand. In this paper, we propose the PAMC-LC-containerization approach to overcome the difficulties associated with moving existing land cover models in the open web environment. Based on the idea of model migration, we design a standardized model description and hierarchical encapsulation strategy for land cover models, and develop migration and deployment methods. Furthermore, we assess the viability and efficacy of the proposed approach by using coupled workflows for model migration and the introduction of visualization on the Mts-WH dataset and the Google dataset. The experimental results show that the PAMC-LC approach can simplify and streamline the model migration process, with important ramifications for increasing productivity, reusing models, and lowering additional data-transmission costs. Full article

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ISPRS Int. J. Geo-Inf., Volume 13, Issue 6 (June 2024) – 49 articles

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