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  • English  (36)
  • 2020-2024  (36)
  • Cartography and geographic base data  (36)
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  • English  (36)
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  • 2020-2024  (36)
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  • Cartography and geographic base data  (36)
  • 1
    Online Resource
    Online Resource
    A new sequential homogeneous pixel selection algorithm for distributed scatterer InSAR
    Informa UK Limited ; 2023
    In:  GIScience & Remote Sensing Vol. 60, No. 1 ( 2023-12-31)
    Details
    In: GIScience & Remote Sensing, Informa UK Limited, Vol. 60, No. 1 ( 2023-12-31)
    Type of Medium: Online Resource
    ISSN: 1548-1603 , 1943-7226
    URL: Article
    DOI: 10.1080/15481603.2023.2218261
    Language: English
    Publisher: Informa UK Limited
    Publication Date: 2023
    detail.hit.zdb_id: 2209042-3
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    Online Resource
  • 2
    Online Resource
    Online Resource
    Efficient Algorithm for Constructing Order K Voronoi Diagrams in Road Networks
    MDPI AG ; 2023
    In:  ISPRS International Journal of Geo-Information Vol. 12, No. 4 ( 2023-04-19), p. 172-
    Details
    In: ISPRS International Journal of Geo-Information, MDPI AG, Vol. 12, No. 4 ( 2023-04-19), p. 172-
    Abstract: The order k Voronoi diagram (OkVD) is an effective geometric construction to partition the geographical space into a set of Voronoi regions such that all locations within a Voronoi region share the same k nearest points of interest (POIs). Despite the broad applications of OkVD in various geographical analysis, few efficient algorithms have been proposed to construct OkVD in real road networks. This study proposes a novel algorithm consisting of two stages. In the first stage, a new one-to-all k shortest path finding procedure is proposed to efficiently determine the shortest paths to k nearest POIs for each node. In the second stage, a new recursive procedure is introduced to effectively divide boundary links within different Voronoi regions using the hierarchical tessellation property of the OkVD. To demonstrate the applicability of the proposed OkVD construction algorithm, a case study of place-based accessibility evaluation is carried out. Computational experiments are also conducted on five real road networks with different sizes, and results show that the proposed OkVD algorithm performed significantly better than state-of-the-art algorithms.
    Type of Medium: Online Resource
    ISSN: 2220-9964
    URL: Article
    DOI: 10.3390/ijgi12040172
    Language: English
    Publisher: MDPI AG
    Publication Date: 2023
    detail.hit.zdb_id: 2655790-3
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    Online Resource
  • 3
    Online Resource
    Online Resource
    A comparative study on the applicability and effectiveness of NSVI and NDVI for estimating fractional vegetation cover based on multi-source remote sensing image
    Informa UK Limited ; 2023
    In:  Geocarto International Vol. 38, No. 1 ( 2023-12-31)
    Details
    In: Geocarto International, Informa UK Limited, Vol. 38, No. 1 ( 2023-12-31)
    Type of Medium: Online Resource
    ISSN: 1010-6049 , 1752-0762
    URL: Article
    DOI: 10.1080/10106049.2023.2184501
    Language: English
    Publisher: Informa UK Limited
    Publication Date: 2023
    detail.hit.zdb_id: 2109550-4
    SSG: 14
    SSG: 14,1
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    Online Resource
  • 4
    Online Resource
    Online Resource
    EmergEventMine: End-to-End Chinese Emergency Event Extraction Using a Deep Adversarial Network
    MDPI AG ; 2022
    In:  ISPRS International Journal of Geo-Information Vol. 11, No. 6 ( 2022-06-10), p. 345-
    Details
    In: ISPRS International Journal of Geo-Information, MDPI AG, Vol. 11, No. 6 ( 2022-06-10), p. 345-
    Abstract: With the rapid development of the internet and social media, extracting emergency events from online news reports has become an urgent need for public safety. However, current studies on the text mining of emergency information mainly focus on text classification and event recognition, only obtaining a general and conceptual cognition about an emergency event, which cannot effectively support emergency risk warning, etc. Existing event extraction methods of other professional fields often depend on a domain-specific, well-designed syntactic dependency or external knowledge base, which can offer high accuracy in their professional fields, but their generalization ability is not good, and they are difficult to directly apply to the field of emergency. To address these problems, an end-to-end Chinese emergency event extraction model, called EmergEventMine, is proposed using a deep adversarial network. Considering the characteristics of Chinese emergency texts, including small-scale labelled corpora, relatively clearer syntactic structures, and concentrated argument distribution, this paper simplifies the event extraction with four subtasks as a two-stage task based on the goals of subtasks, and then develops a lightweight heterogeneous joint model based on deep neural networks for realizing end-to-end and few-shot Chinese emergency event extraction. Moreover, adversarial training is introduced into the joint model to alleviate the overfitting of the model on the small-scale labelled corpora. Experiments on the Chinese emergency corpus fully prove the effectiveness of the proposed model. Moreover, this model significantly outperforms other existing state-of-the-art event extraction models.
    Type of Medium: Online Resource
    ISSN: 2220-9964
    URL: Article
    DOI: 10.3390/ijgi11060345
    Language: English
    Publisher: MDPI AG
    Publication Date: 2022
    detail.hit.zdb_id: 2655790-3
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  • 5
    Online Resource
    Online Resource
    Analysis of the Spatial Distribution and Associated Factors of the Transmission Locations of COVID-19 in the First Four Waves in Hong Kong
    MDPI AG ; 2023
    In:  ISPRS International Journal of Geo-Information Vol. 12, No. 3 ( 2023-03-06), p. 111-
    Details
    In: ISPRS International Journal of Geo-Information, MDPI AG, Vol. 12, No. 3 ( 2023-03-06), p. 111-
    Abstract: Understanding the space–time pattern of the transmission locations of COVID-19, as well as the relationship between the pattern, socioeconomic status, and environmental factors, is important for pandemic prevention. Most existing research mainly analyzes the locations resided in or visited by COVID-19 cases, while few studies have been undertaken on the space–time pattern of the locations at which the transmissions took place and its associated influencing factors. To fill this gap, this study focuses on the space–time distribution patterns of COVID-19 transmission locations and the association between such patterns and urban factors. With Hong Kong as the study area, transmission chains of the four waves of COVID-19 outbreak in Hong Kong during the time period of January 2020 to June 2021 were reconstructed from the collected case information, and then the locations of COVID-19 transmission were inferred from the transmission chains. Statistically significant clusters of COVID-19 transmission locations at the level of tertiary planning units (TPUs) were detected and compared among different waves of COVID-19 outbreak. The high-risk areas and the associated influencing factors of different waves were also investigated. The results indicate that COVID-19 transmission began with the Hong Kong Island, further moved northward towards the New Territories, and finally shifted to the south Hong Kong Island, and the transmission population shows a difference between residential locations and non-residential locations. The research results can provide health authorities and policy-makers with useful information for pandemic prevention, as well as serve as a guide to the public in the avoidance of activities and places with a high risk of contagion.
    Type of Medium: Online Resource
    ISSN: 2220-9964
    URL: Article
    DOI: 10.3390/ijgi12030111
    Language: English
    Publisher: MDPI AG
    Publication Date: 2023
    detail.hit.zdb_id: 2655790-3
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    Online Resource
  • 6
    Online Resource
    Online Resource
    Abnormal-Trajectory Detection Method Based on Variable Grid Partitioning
    MDPI AG ; 2023
    In:  ISPRS International Journal of Geo-Information Vol. 12, No. 2 ( 2023-01-28), p. 40-
    Details
    In: ISPRS International Journal of Geo-Information, MDPI AG, Vol. 12, No. 2 ( 2023-01-28), p. 40-
    Abstract: Abnormal-trajectory detection can be used to detect fraudulent behavior by taxi drivers when carrying passengers. Existing methods usually detect abnormal trajectories based on the characteristics of “few and different”, which require large data sets and, therefore, may identify “few and near” trajectories chosen by drivers according to their driving experience as abnormal situations. This study proposed an abnormal-trajectory detection method based on a variable grid to address this problem. First, the urban road network was divided into three regions: high-, medium-, and low-density road network regions using a kernel density analysis method. Second, grids with different sizes were set for different types of road network regions; trajectory tuples were obtained based on the grid division results, and the abnormality rate of the trajectory was calculated. Finally, a trajectory-abnormality probability function was developed to calculate the deviation of each trajectory from the benchmark trajectory to detect abnormal trajectories. Experimental results on a real taxi trajectory dataset demonstrated that the proposed method achieved a higher accuracy in detecting abnormal trajectories than similar methods.
    Type of Medium: Online Resource
    ISSN: 2220-9964
    URL: Article
    DOI: 10.3390/ijgi12020040
    Language: English
    Publisher: MDPI AG
    Publication Date: 2023
    detail.hit.zdb_id: 2655790-3
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    Online Resource
  • 7
    Online Resource
    Online Resource
    Driving Factors and Scale Effects of Residents’ Willingness to Pay for Environmental Protection under the Impact of COVID-19
    MDPI AG ; 2023
    In:  ISPRS International Journal of Geo-Information Vol. 12, No. 4 ( 2023-04-11), p. 163-
    Details
    In: ISPRS International Journal of Geo-Information, MDPI AG, Vol. 12, No. 4 ( 2023-04-11), p. 163-
    Abstract: In recent years, environmental degradation and the COVID-19 pandemic have seriously affected economic development and social stability. Addressing the impact of major public health events on residents’ willingness to pay for environmental protection (WTPEP) and analyzing the drivers are necessary for improving human well-being and environmental sustainability. We designed a questionnaire to analyze the change in residents’ WTPEP before and during COVID-19 and an established ordinary least squares (OLS), spatial lag model (SLM), spatial error model (SEM), geographically weighted regression (GWR), and multiscale GWR to explore driver factors and scale effects of WTPEP based on the theory of environment Kuznets curve (EKC). The results show that (1) WTPEP is 0–20,000 yuan before COVID-19 and 0–50,000 yuan during COVID-19. Residents’ WTPEP improved during COVID-19, which indicates that residents’ demand for an ecological environment is increasing; (2) The shapes and inflection points of the relationships between income and WTPEP are spatially heterogeneous before and during COVID-19, but the northern WTPEP is larger than southern, which indicates that there is a spatial imbalance in WTPEP; (3) Environmental degradation, health, environmental quality, and education are WTPEP’s significant macro-drivers, whereas income, age, and gender are significant micro-drivers. Those factors can help policymakers better understand which factors are more suitable for macro or micro environmental policy-making and what targeted measures could be taken to solve the contradiction between the growing ecological environment demand of residents and the spatial imbalance of WTPEP in the future.
    Type of Medium: Online Resource
    ISSN: 2220-9964
    URL: Article
    DOI: 10.3390/ijgi12040163
    Language: English
    Publisher: MDPI AG
    Publication Date: 2023
    detail.hit.zdb_id: 2655790-3
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  • 8
    Online Resource
    Online Resource
    Increased precipitation weakenes the positive effect of vegetation greening on erosion
    Informa UK Limited ; 2023
    In:  Geocarto International
    Details
    In: Geocarto International, Informa UK Limited
    Type of Medium: Online Resource
    ISSN: 1010-6049 , 1752-0762
    URL: Article
    DOI: 10.1080/10106049.2023.2172216
    Language: English
    Publisher: Informa UK Limited
    Publication Date: 2023
    detail.hit.zdb_id: 2109550-4
    SSG: 14
    SSG: 14,1
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    Online Resource
  • 9
    Online Resource
    Online Resource
    Multi-Scale Massive Points Fast Clustering Based on Hierarchical Density Spanning Tree
    MDPI AG ; 2023
    In:  ISPRS International Journal of Geo-Information Vol. 12, No. 1 ( 2023-01-14), p. 24-
    Details
    In: ISPRS International Journal of Geo-Information, MDPI AG, Vol. 12, No. 1 ( 2023-01-14), p. 24-
    Abstract: Spatial clustering is dependent on spatial scales. With the widespread use of web maps, a fast clustering method for multi-scale spatial elements has become a new requirement. Therefore, to cluster and display elements rapidly at different spatial scales, we propose a method called Multi-Scale Massive Points Fast Clustering based on Hierarchical Density Spanning Tree. This study refers to the basic principle of Clustering by Fast Search and Find of Density Peaks aggregation algorithm and introduces the concept of a hierarchical density-based spanning tree, combining the spatial scale with the tree links of elements to propose the corresponding pruning strategy, and finally realizes the fast multi-scale clustering of elements. The first experiment proved the time efficiency of the method in obtaining clustering results by the distance-scale adjustment of parameters. Accurate clustering results were also achieved. The second experiment demonstrated the feasibility of the method at the aggregation point element and showed its visual effect. This provides a further explanation for the application of tree-link structures.
    Type of Medium: Online Resource
    ISSN: 2220-9964
    URL: Article
    DOI: 10.3390/ijgi12010024
    Language: English
    Publisher: MDPI AG
    Publication Date: 2023
    detail.hit.zdb_id: 2655790-3
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  • 10
    Online Resource
    Online Resource
    Application of AHP-ICM and AHP-EWM in Collapse Disaster Risk Mapping in Huinan County
    MDPI AG ; 2023
    In:  ISPRS International Journal of Geo-Information Vol. 12, No. 10 ( 2023-09-28), p. 395-
    Details
    In: ISPRS International Journal of Geo-Information, MDPI AG, Vol. 12, No. 10 ( 2023-09-28), p. 395-
    Abstract: Collapses are one of the most common geological disasters in mountainous areas, which easily damage buildings and infrastructures and bring huge property losses to people’s production and life. This paper uses Huinan County as the study area, and with the help of a geographic information system (GIS) based on the formation principle of natural disaster risk, the information content method (ICM), the analytical hierarchy process (AHP), and the analytical hierarchy process–information content method (AHP-ICM) model are applied to hazard mapping, and the analytical hierarchy process-entropy weight method (AHP-EWM) model is applied to exposure, vulnerability and emergency responses, and recovery capability mapping. A risk mapping model for collapse disasters was also constructed using these four elements. Firstly, an inventory map of 52 landslides was compiled using remote sensing interpretation, field verification, and comprehensive previous survey data. Then, the study area mapping units were delineated using the curvature watershed method in the slope unit, and 21 indicators were used to draw the collapse disaster risk zoning map by considering the four elements of geological disaster risk. The prediction accuracy of the three hazard mapping models was verified using the receiver operating characteristic (ROC) curve, and the area under the curve (AUC) results of the AHP, ICM, and AHP-ICM models were 80%, 85.7%, and 87.4%, respectively. After a comprehensive comparison, the AHP-ICM model is the best of the three models in terms of collapse hazard mapping, and it was applied to collapse risk mapping with the AHP-EWM model to produce a reasonable and reliable collapse risk zoning map, which provides a basis for collapse management and decision making.
    Type of Medium: Online Resource
    ISSN: 2220-9964
    URL: Article
    DOI: 10.3390/ijgi12100395
    Language: English
    Publisher: MDPI AG
    Publication Date: 2023
    detail.hit.zdb_id: 2655790-3
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