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  • Cartography and geographic base data  (5)
  • 1
    Online Resource
    Online Resource
    MDPI AG ; 2021
    In:  ISPRS International Journal of Geo-Information Vol. 10, No. 8 ( 2021-07-21), p. 493-
    In: ISPRS International Journal of Geo-Information, MDPI AG, Vol. 10, No. 8 ( 2021-07-21), p. 493-
    Abstract: Recently, many new studies applying computer vision (CV) to street view imagery (SVI) datasets to objectively extract the view indices of various streetscape features such as trees to proxy urban scene qualities have emerged. However, human perception (e.g., imageability) have a subtle relationship to visual elements that cannot be fully captured using view indices. Conversely, subjective measures using survey and interview data explain human behaviors more. However, the effectiveness of integrating subjective measures with SVI datasets has been less discussed. To address this, we integrated crowdsourcing, CV, and machine learning (ML) to subjectively measure four important perceptions suggested by classical urban design theory. We first collected ratings from experts on sample SVIs regarding these four qualities, which became the training labels. CV segmentation was applied to SVI samples extracting streetscape view indices as the explanatory variables. We then trained ML models and achieved high accuracy in predicting scores. We found a strong correlation between the predicted complexity score and the density of urban amenities and services points of interest (POI), which validates the effectiveness of subjective measures. In addition, to test the generalizability of the proposed framework as well as to inform urban renewal strategies, we compared the measured qualities in Pudong to other five urban cores that are renowned worldwide. Rather than predicting perceptual scores directly from generic image features using a convolution neural network, our approach follows what urban design theory has suggested and confirmed as various streetscape features affecting multi-dimensional human perceptions. Therefore, the results provide more interpretable and actionable implications for policymakers and city planners.
    Type of Medium: Online Resource
    ISSN: 2220-9964
    Language: English
    Publisher: MDPI AG
    Publication Date: 2021
    detail.hit.zdb_id: 2655790-3
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  • 2
    Online Resource
    Online Resource
    MDPI AG ; 2017
    In:  ISPRS International Journal of Geo-Information Vol. 6, No. 7 ( 2017-07-03), p. 199-
    In: ISPRS International Journal of Geo-Information, MDPI AG, Vol. 6, No. 7 ( 2017-07-03), p. 199-
    Type of Medium: Online Resource
    ISSN: 2220-9964
    Language: English
    Publisher: MDPI AG
    Publication Date: 2017
    detail.hit.zdb_id: 2655790-3
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  • 3
    In: Geocarto International, Informa UK Limited, Vol. 37, No. 26 ( 2022-12-13), p. 11846-11866
    Type of Medium: Online Resource
    ISSN: 1010-6049 , 1752-0762
    Language: English
    Publisher: Informa UK Limited
    Publication Date: 2022
    detail.hit.zdb_id: 2109550-4
    SSG: 14
    SSG: 14,1
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  • 4
    In: ISPRS International Journal of Geo-Information, MDPI AG, Vol. 12, No. 2 ( 2023-01-31), p. 47-
    Abstract: Three-dimensional city models are increasingly being used for analyses and simulations. To enable such applications, it is necessary to standardise semantically richer city models and, in some cases, to connect the models with external data sources. In this study, we describe the development of a new Swedish specification for 3D city models, denoted as 3CIM, which is a joint effort between the three largest cities in Sweden—Stockholm, Gothenburg, and Malmö. Technically, 3CIM is an extension of the OGC standard CityGML 2.0, implemented as an application domain extension (ADE). The ADE is semantically thin, mainly extending CityGML 2.0 to harmonise with national standards; in contrast, 3CIM is mainly based on linkages to external databases, registers, and operational systems for the semantic part. The current version, 3CIM 1.0, includes various themes, including Bridge, Building, Utility, City Furniture, Transportation, Tunnel, Vegetation, and Water. Three test areas were created with 3CIM data, one in each city. These data were evaluated in several use-cases, including visualisation as well as daylight, noise, and flooding simulations. The conclusion from these use-cases is that the 3CIM data, together with the linked external data sources, allow for the inclusion of the necessary information for the visualisation and simulations, but extract, transform, and load (ETL) processes are required to tailor the input data. The next step is to implement 3CIM within the three cities, which will entail several challenges, as discussed at the end of the paper.
    Type of Medium: Online Resource
    ISSN: 2220-9964
    Language: English
    Publisher: MDPI AG
    Publication Date: 2023
    detail.hit.zdb_id: 2655790-3
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  • 5
    Online Resource
    Online Resource
    MDPI AG ; 2019
    In:  ISPRS International Journal of Geo-Information Vol. 8, No. 7 ( 2019-07-16), p. 304-
    In: ISPRS International Journal of Geo-Information, MDPI AG, Vol. 8, No. 7 ( 2019-07-16), p. 304-
    Abstract: Strokes are considered an elementary unit of road networks and have been widely used in their analysis and application. However, most conventional stroke generation methods are based solely on a fixed angle threshold, which ignores road networks’ geometric and structural properties. To remedy this, this paper proposes an algorithm for generating strokes that takes into account these additional geometric and structural road network properties and that reduces the impact of stroke generation on road network quality. To this end, we introduce a model of feature-based information entropy and then utilize this model to calculate road networks’ information volume and both the elemental and neighborhood level. To make our experimental results more objective, we use the Douglas-Peucker algorithm to simplify the information change curve and to obtain the optimal angle threshold range for generating strokes for different road network structures. Finally, we apply this model to three different road networks, and the optimal threshold ranges are 54°–63° (Chicago), 61°–63° (Moscow), 45°–48° (Monaco). And taking Monaco as an example, this paper conducts stroke selection experiments. The results demonstrate that our proposed algorithm has better connectivity and wider coverage than those based on a common angle threshold (60°).
    Type of Medium: Online Resource
    ISSN: 2220-9964
    Language: English
    Publisher: MDPI AG
    Publication Date: 2019
    detail.hit.zdb_id: 2655790-3
    Location Call Number Limitation Availability
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