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  • Cartography and geographic base data  (4)
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  • Cartography and geographic base data  (4)
  • 1
    Online Resource
    Online Resource
    Simulating Spatio-Temporal Patterns of Terrorism Incidents on the Indochina Peninsula with GIS and the Random Forest Method
    MDPI AG ; 2019
    In:  ISPRS International Journal of Geo-Information Vol. 8, No. 3 ( 2019-03-07), p. 133-
    Details
    In: ISPRS International Journal of Geo-Information, MDPI AG, Vol. 8, No. 3 ( 2019-03-07), p. 133-
    Abstract: In recent years, various types of terrorist attacks have occurred which have caused worldwide catastrophes. The ability to proactively detect and even predict a potential terrorist risk is critically important for government agencies to react in a timely manner. In this study, a method of geospatial statistics was used to analyse the spatio-temporal evolution of terrorist attacks on the Indochina Peninsula. The machine learning random forest (RF) method was adopted to predict the potential risk of terrorist attacks on the Indochina Peninsula on a spatial scale with 15 driving factors. The RF model performed well with AUC values of 0.839 [95% confidence interval of 0.833–0.844]. The map of the potential distribution of terrorist attack risk was obtained with a 0.05×0.05-degree (approximately 5×5 km) resolution. The results indicate that Thailand is the most dangerous area for terrorist attacks, especially southern Thailand, Bangkok and its surrounding cities. Middle Cambodia and the northern and southern parts of Myanmar are also high-risk areas. Other areas are relatively low risk. This study provides the hotspots for terrorist attacks on a more fine-grained geographical unit. Meanwhile, it shows that machine learning algorithms (e.g., RF) combined with GIS have great potential for simulating the risk of terrorist attacks.
    Type of Medium: Online Resource
    ISSN: 2220-9964
    URL: Article
    DOI: 10.3390/ijgi8030133
    Language: English
    Publisher: MDPI AG
    Publication Date: 2019
    detail.hit.zdb_id: 2655790-3
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    Online Resource
  • 2
    Online Resource
    Online Resource
    The Spatiotemporal Pattern and Driving Factors of Cyber Fraud Crime in China
    MDPI AG ; 2021
    In:  ISPRS International Journal of Geo-Information Vol. 10, No. 12 ( 2021-11-30), p. 802-
    Details
    In: ISPRS International Journal of Geo-Information, MDPI AG, Vol. 10, No. 12 ( 2021-11-30), p. 802-
    Abstract: As a typical cybercrime, cyber fraud poses severe threats to civilians’ property safety and social stability. Traditional criminological theories such as routine activity theory focus mainly on the effects of individual characteristics on cybercrime victimization and ignore the impacts of macro-level environmental factors. This study aims at exploring the spatiotemporal pattern of cyber fraud crime in China and investigating the relationships between cyber fraud and environmental factors. The results showed that cyber fraud crimes were initially distributed in southeastern China and gradually spread towards the middle and northern regions; spatial autocorrelation analysis revealed that the spatial concentration trend of cyber fraud became more and more strong, and a strong distinction in cyber fraud clustering between the north and the south was identified. To further explain the formative causes of these spatial patterns, a generalized additive model (GAM) was constructed by incorporating natural and social environmental factors. The results suggested that the distribution of cyber fraud was notably affected by the regional economy and population structure. Also, the high incidence of cyber fraud crime was closely associated with a large nonagricultural population, a high proportion of tertiary industry in GDP, a large number of general college students, a longer cable length, and a large numbers of internet users.
    Type of Medium: Online Resource
    ISSN: 2220-9964
    URL: Article
    DOI: 10.3390/ijgi10120802
    Language: English
    Publisher: MDPI AG
    Publication Date: 2021
    detail.hit.zdb_id: 2655790-3
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    Online Resource
  • 3
    Online Resource
    Online Resource
    A Study on the Emergency Shelter Spatial Accessibility Based on the Adaptive Catchment Size 2SFCA Method
    MDPI AG ; 2022
    In:  ISPRS International Journal of Geo-Information Vol. 11, No. 12 ( 2022-11-26), p. 593-
    Details
    In: ISPRS International Journal of Geo-Information, MDPI AG, Vol. 11, No. 12 ( 2022-11-26), p. 593-
    Abstract: In order to access the spatial accessibility of emergency shelters, the relationship between the supply and demand of emergency shelters in the two dimensions of space and non-space must be comprehensively considered. Meanwhile, it is vital to understand the competitive relationship among emergency shelters. However, there are disadvantages when using the two-step floating catchment area (2SFCA) method and the improved 2SFCA method when addressing these issues. This study proposes the adaptive catchment size 2SFCA (A-2SFCA) method to calculate spatial accessibility values, which can work alongside the two relationships mentioned above. The analysis procedure of the A-2SFCA method has two stages. Firstly, this method adjusts the catchment size of the shelters by observing how crowded they are and repeatedly using this statistic in a service subset. At the end of this stage, every catchment area is determined. Secondly, the catchment areas are used to calculate the spatial accessibility values. The method was used to study a region in the Tianjin urban area in China. The proposed A-2SFCA and fixed-coverage-based two-step floating catchment area (FC2SFCA) methods are employed to measure and compare the spatial accessibility values. The result shows that the spatial accessibility in Tianjin urban area is unstable. The spatial accessibility result obtained from the A-2SFCA method is more reasonable than the FC2SFCA method when analyzing the reasonable catchment areas of emergency shelters. The A-2SFCA method provides a method for determining the catchment size of public service providers, which can be used for the accessibility analysis of various other public facilities.
    Type of Medium: Online Resource
    ISSN: 2220-9964
    URL: Article
    DOI: 10.3390/ijgi11120593
    Language: English
    Publisher: MDPI AG
    Publication Date: 2022
    detail.hit.zdb_id: 2655790-3
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    Online Resource
  • 4
    Online Resource
    Online Resource
    AGIM-net based subject-sensitive hashing algorithm for integrity authentication of HRRS images
    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: 10.1080/10106049.2023.2168071
    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
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