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  • Cartography and geographic base data  (13)
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  • Cartography and geographic base data  (13)
  • 1
    Online Resource
    Online Resource
    Analyzing Urban Human Mobility Patterns through a Thematic Model at a Finer Scale
    MDPI AG ; 2016
    In:  ISPRS International Journal of Geo-Information Vol. 5, No. 6 ( 2016-06-01), p. 78-
    Details
    In: ISPRS International Journal of Geo-Information, MDPI AG, Vol. 5, No. 6 ( 2016-06-01), p. 78-
    Type of Medium: Online Resource
    ISSN: 2220-9964
    URL: Article
    DOI: 10.3390/ijgi5060078
    Language: English
    Publisher: MDPI AG
    Publication Date: 2016
    detail.hit.zdb_id: 2655790-3
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    Online Resource
  • 2
    Online Resource
    Online Resource
    MSNet: multispectral semantic segmentation network for remote sensing images
    Informa UK Limited ; 2022
    In:  GIScience & Remote Sensing Vol. 59, No. 1 ( 2022-12-31), p. 1177-1198
    Details
    In: GIScience & Remote Sensing, Informa UK Limited, Vol. 59, No. 1 ( 2022-12-31), p. 1177-1198
    Type of Medium: Online Resource
    ISSN: 1548-1603 , 1943-7226
    URL: Article
    DOI: 10.1080/15481603.2022.2101728
    Language: English
    Publisher: Informa UK Limited
    Publication Date: 2022
    detail.hit.zdb_id: 2209042-3
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    Online Resource
  • 3
    Online Resource
    Online Resource
    Exploring the Connection between Urban 3D Form and Building Energy Performance and the Influencing Mechanism
    MDPI AG ; 2021
    In:  ISPRS International Journal of Geo-Information Vol. 10, No. 10 ( 2021-10-16), p. 709-
    Details
    In: ISPRS International Journal of Geo-Information, MDPI AG, Vol. 10, No. 10 ( 2021-10-16), p. 709-
    Abstract: Continuous growth of building energy consumption CO2 emission (BECCE) threatens urban sustainable development. Urban form is an important factor affecting BECCE. Compactness is a significant urban morphological characteristic. There is currently a lack of research on the effect of urban three-dimensional (3D) compactness on BECCE. To clarify the research value of 3D compactness, we investigated whether 3D compactness has a stronger impact on BECCE than two-dimensional (2D) compactness. A total of 288 buildings of the People’s Bank of China (PBOC) were divided into 5 zones according to building climate demarcation. As BECCE is affected mainly by four aspects (socioeconomic condition, building features, macroclimate, and urban form), the BECCE driven by urban form (BECCE-f) in each zone was calculated firstly using the partial least square regression model. Normalized compactness index (NCI) and normalized vertical compactness index (NVCI) were calculated with Python to quantify urban 2D and 3D compactness within a 1 km buffer of PBOC buildings. The mean NCI and NVCI values of each zone were adopted as 2D and 3D compactness of this zone. Gray correlation analysis of the five zones showed that the connection between the NVCI and BECCE-f is stronger than that between NCI and BECCE-f. Based on this, we believe that the emphasis of later research should be shifted to urban 3D form, not just 2D elements. 3D form can describe the real urban form in a more accurate and detailed manner. Emphasizing 3D morphological characteristics in studies of the relationship between urban form and building energy performance is more meaningful and valuable than only considering 2D characteristics. The impact mechanism of urban form on BECCE-f should also be analyzed from the perspective of 3D form. This study also provides beneficial solutions to building energy saving and low-carbon building construction.
    Type of Medium: Online Resource
    ISSN: 2220-9964
    URL: Article
    DOI: 10.3390/ijgi10100709
    Language: English
    Publisher: MDPI AG
    Publication Date: 2021
    detail.hit.zdb_id: 2655790-3
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    Online Resource
  • 4
    Online Resource
    Online Resource
    A Fine-Scale Mangrove Map of China Derived from 2-Meter Resolution Satellite Observations and Field Data
    MDPI AG ; 2021
    In:  ISPRS International Journal of Geo-Information Vol. 10, No. 2 ( 2021-02-20), p. 92-
    Details
    In: ISPRS International Journal of Geo-Information, MDPI AG, Vol. 10, No. 2 ( 2021-02-20), p. 92-
    Abstract: Mangrove forests are important ecosystems in the coastal intertidal zone, but China’s mangroves have experienced a large reduction in area from the 1950s, and the remaining mangrove forests are exhibiting increased fragmentation. A detailed mangrove dataset of China is crucial for mangrove ecosystem management and protection, but the fragmented mangrove patches are hardly mapped by medium resolution satellite imagery. To overcome these difficulties, we presented a fine-scale mangrove map for 2018 using the 2-meter resolution Gaofen-1 and Ziyuan-3 satellite imagery together with field data. We employed a hybrid method of object-based image analysis (OBIA), interpreter editing, and field surveying for mangrove mapping. The field survey route reached 9500 km, and 2650 patches were verified during the field work. Accuracy assessment by confusion matrix showed that the kappa coefficient reached 0.98, indicating a highly thematic accuracy of the mangrove dataset. Results showed the total area of mangrove forest in China for 2018 was 25,683.88 hectares, and approximately 91% of mangroves were found in the three provinces of Guangdong, Guangxi, and Hainan. About 64% of mangroves were distributed in or near the nature reserves established by national or local governments, which indicated that China’s mangroves were well protected in recent years. The new fine-scale mangrove dataset was freely shared together with this paper, and it can be used by local authorities and research groups for mangrove management and ecological planning.
    Type of Medium: Online Resource
    ISSN: 2220-9964
    URL: Article
    DOI: 10.3390/ijgi10020092
    Language: English
    Publisher: MDPI AG
    Publication Date: 2021
    detail.hit.zdb_id: 2655790-3
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  • 5
    Online Resource
    Online Resource
    Spatio-Temporal Relevance Classification from Geographic Texts Using Deep Learning
    MDPI AG ; 2023
    In:  ISPRS International Journal of Geo-Information Vol. 12, No. 9 ( 2023-09-01), p. 359-
    Details
    In: ISPRS International Journal of Geo-Information, MDPI AG, Vol. 12, No. 9 ( 2023-09-01), p. 359-
    Abstract: The growing proliferation of geographic information presents a substantial challenge to the traditional framework of a geographic information analysis and service. The dynamic integration and representation of geographic knowledge, such as triples, with spatio-temporal information play a crucial role in constructing a comprehensive spatio-temporal knowledge graph and facilitating the effective utilization of spatio-temporal big data for knowledge-driven service applications. The existing knowledge graph (or geographic knowledge graph) takes spatio-temporal as the attribute of entity, ignoring the role of spatio-temporal information for accurate retrieval of entity objects and adaptive expression of entity objects. This study approaches the correlation between geographic knowledge and spatio-temporal information as a text classification problem, with the aim of addressing the challenge of establishing meaningful connections among spatio-temporal data using advanced deep learning techniques. Specifically, we leverage Wikipedia as a valuable data source for collecting and filtering geographic texts. The Open Information Extraction (OpenIE) tool is employed to extract triples from each sentence, followed by manual annotation of the sentences’ spatio-temporal relevance. This process leads to the formation of quadruples (time relevance/space relevance) or quintuples (spatio-temporal relevance). Subsequently, a comprehensive spatio-temporal classification dataset is constructed for experiment verification. Ten prominent deep learning text classification models are then utilized to conduct experiments covering various aspects of time, space, and spatio-temporal relationships. The experimental results demonstrate that the Bidirectional Encoder Representations from Transformer-Region-based Convolutional Neural Network (BERT-RCNN) model exhibits the highest performance among the evaluated models. Overall, this study establishes a foundation for future knowledge extraction endeavors.
    Type of Medium: Online Resource
    ISSN: 2220-9964
    URL: Article
    DOI: 10.3390/ijgi12090359
    Language: English
    Publisher: MDPI AG
    Publication Date: 2023
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  • 6
    Online Resource
    Online Resource
    Influential Factor Detection for Tourism on the Qinghai-Tibet Plateau Based on Social Media Data
    MDPI AG ; 2021
    In:  ISPRS International Journal of Geo-Information Vol. 10, No. 9 ( 2021-08-27), p. 579-
    Details
    In: ISPRS International Journal of Geo-Information, MDPI AG, Vol. 10, No. 9 ( 2021-08-27), p. 579-
    Abstract: Tourism is playing an important role in the economic development of the Qinghai-Tibet Plateau (QTP). To better develop tourism in this region, the spatial heterogeneity of influencing factors on tourism needs to be studied. Using the spatial distribution of tourism potential from social media data, this paper analyzes the influencing factors of tourism on the QTP from the perspective of spatial heterogeneity. We extract microblogs related to travel topics connected to the QTP in 2017 from Sina Weibo to capture tourism potential. Then, factors considered from six aspects (tourism resources, amenities, transportation, geography, population, and the economy) are selected, and a geographic detector (Geodetector) is employed to detect the explanatory power of these factors for tourism potential. The results indicate different influential tourism factors in Qinghai and Tibet. In Qinghai, the main factors are hotels, tourist attractions, and road network density, and the explanatory power of the factors mainly comes from eastern and western Qinghai. In Tibet, the main factors are road network density, regional GDP (Gross Domestic Product), and urban land. It is suggested that tourism in the central region of Qinghai can be improved by enhancing the publicity and utilization of tourism resources, and Tibet should enhance tourism resource utilization and improve tourism amenities and infrastructure.
    Type of Medium: Online Resource
    ISSN: 2220-9964
    URL: Article
    DOI: 10.3390/ijgi10090579
    Language: English
    Publisher: MDPI AG
    Publication Date: 2021
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  • 7
    Online Resource
    Online Resource
    Urban Link Travel Time Prediction Based on a Gradient Boosting Method Considering Spatiotemporal Correlations
    MDPI AG ; 2016
    In:  ISPRS International Journal of Geo-Information Vol. 5, No. 11 ( 2016-11-04), p. 201-
    Details
    In: ISPRS International Journal of Geo-Information, MDPI AG, Vol. 5, No. 11 ( 2016-11-04), p. 201-
    Type of Medium: Online Resource
    ISSN: 2220-9964
    URL: Article
    DOI: 10.3390/ijgi5110201
    Language: English
    Publisher: MDPI AG
    Publication Date: 2016
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  • 8
    Online Resource
    Online Resource
    Prediction of Suspect Location Based on Spatiotemporal Semantics
    MDPI AG ; 2017
    In:  ISPRS International Journal of Geo-Information Vol. 6, No. 7 ( 2017-06-23), p. 185-
    Details
    In: ISPRS International Journal of Geo-Information, MDPI AG, Vol. 6, No. 7 ( 2017-06-23), p. 185-
    Type of Medium: Online Resource
    ISSN: 2220-9964
    URL: Article
    DOI: 10.3390/ijgi6070185
    Language: English
    Publisher: MDPI AG
    Publication Date: 2017
    detail.hit.zdb_id: 2655790-3
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  • 9
    Online Resource
    Online Resource
    Using an Optimized Chinese Address Matching Method to Develop a Geocoding Service: A Case Study of Shenzhen, China
    MDPI AG ; 2016
    In:  ISPRS International Journal of Geo-Information Vol. 5, No. 5 ( 2016-05-13), p. 65-
    Details
    In: ISPRS International Journal of Geo-Information, MDPI AG, Vol. 5, No. 5 ( 2016-05-13), p. 65-
    Type of Medium: Online Resource
    ISSN: 2220-9964
    URL: Article
    DOI: 10.3390/ijgi5050065
    Language: English
    Publisher: MDPI AG
    Publication Date: 2016
    detail.hit.zdb_id: 2655790-3
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  • 10
    Online Resource
    Online Resource
    Visualization and Analysis of Transport Accessibility Changes Based on Time Cartograms
    MDPI AG ; 2022
    In:  ISPRS International Journal of Geo-Information Vol. 11, No. 8 ( 2022-08-01), p. 432-
    Details
    In: ISPRS International Journal of Geo-Information, MDPI AG, Vol. 11, No. 8 ( 2022-08-01), p. 432-
    Abstract: Visualization of the spatial distribution pattern of transport accessibility and its changes can be crucial for understanding and assessing the performance of transportation systems. Compared to traditional maps representing geographic space, time cartograms modify geographic locations and spatial relationships to suit travelling times and thereby emphasize time–distance relationships in time-space. This study aims to facilitate a better understanding of the evolution of the spatial distribution pattern of accessibility by presenting a novel visualization and analysis methodology based on time cartograms. This is achieved by combining a visual qualitative display with a quantitative indicator analysis from multiple perspectives to show transport accessibility changes. Two indicators, namely, the shortest railway travel time (STRT) and spatiotemporal con-version parameter (STCP), are proposed to measure accessibility changes. Our work consists of the construction of time cartograms, the analysis of indicators, and the use of multiple views to show changes in transportation accessibility from multiple perspectives. The methodology is applied on the railway data of Beijing and selected 226 cities in China and to analyze changes in railway accessibility in 1996, 2003, 2009 and 2016. The results show that the development of transportation technology has continuously shortened the travel time, the time-space is gradually compressed, However, the difference in transport accessibility is getting bigger and bigger because of the uneven transportation development speeds between the regions.
    Type of Medium: Online Resource
    ISSN: 2220-9964
    URL: Article
    DOI: 10.3390/ijgi11080432
    Language: English
    Publisher: MDPI AG
    Publication Date: 2022
    detail.hit.zdb_id: 2655790-3
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