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  • 2015-2019  (14)
  • Cartography and geographic base data  (14)
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  • 2015-2019  (14)
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  • Cartography and geographic base data  (14)
  • 1
    Online Resource
    Online Resource
    Seamless Upscaling of the Field-Measured Grassland Aboveground Biomass Based on Gaussian Process Regression and Gap-Filled Landsat 8 OLI Reflectance
    MDPI AG ; 2018
    In:  ISPRS International Journal of Geo-Information Vol. 7, No. 7 ( 2018-06-22), p. 242-
    Details
    In: ISPRS International Journal of Geo-Information, MDPI AG, Vol. 7, No. 7 ( 2018-06-22), p. 242-
    Type of Medium: Online Resource
    ISSN: 2220-9964
    URL: Article
    DOI: 10.3390/ijgi7070242
    Language: English
    Publisher: MDPI AG
    Publication Date: 2018
    detail.hit.zdb_id: 2655790-3
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    Online Resource
  • 2
    Online Resource
    Online Resource
    Spatial-Temporal Analysis of Human Dynamics on Urban Land Use Patterns Using Social Media Data by Gender
    MDPI AG ; 2018
    In:  ISPRS International Journal of Geo-Information Vol. 7, No. 9 ( 2018-08-29), p. 358-
    Details
    In: ISPRS International Journal of Geo-Information, MDPI AG, Vol. 7, No. 9 ( 2018-08-29), p. 358-
    Abstract: The relationship between urban human dynamics and land use types has always been an important issue in the study of urban problems in China. This paper used location data from Sina Location Microblog (commonly known as Weibo) users to study the human dynamics of the spatial-temporal characteristics of gender differences in Beijing’s Olympic Village in June 2014. We applied mathematical statistics and Local Moran’s I to analyze the spatial-temporal distribution of Sina Microblog users in 100 m × 100 m grids and land use patterns. The female users outnumbered male users, and the sex ratio ( S R varied under different land use types at different times. Female users outnumbered male users regarding residential land and public green land, but male users outnumbered female users regarding workplace, especially on weekends, as the S R on weekends ( S R was 120.5) was greater than that on weekdays ( S R was 118.8). After a Local Moran’s I analysis, we found that High–High grids are primarily distributed across education and scientific research land and residential land; these grids and their surrounding grids have more female users than male users. Low–Low grids are mainly distributed across sports centers and workplaces on weekdays; these grids and their surrounding grids have fewer female users than male users. The average number of users on Saturday was the highest value and, on weekends, the number of female and male users both increased in commercial land, but male users were more active than female users ( S R was 110).
    Type of Medium: Online Resource
    ISSN: 2220-9964
    URL: Article
    DOI: 10.3390/ijgi7090358
    Language: English
    Publisher: MDPI AG
    Publication Date: 2018
    detail.hit.zdb_id: 2655790-3
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    Online Resource
  • 3
    Online Resource
    Online Resource
    Change Detection in Coral Reef Environment Using High-Resolution Images: Comparison of Object-Based and Pixel-Based Paradigms
    MDPI AG ; 2018
    In:  ISPRS International Journal of Geo-Information Vol. 7, No. 11 ( 2018-11-12), p. 441-
    Details
    In: ISPRS International Journal of Geo-Information, MDPI AG, Vol. 7, No. 11 ( 2018-11-12), p. 441-
    Abstract: Despite increases in the spatial resolution of satellite imagery prompting interest in object-based image analysis, few studies have used object-based methods for monitoring changes in coral reefs. This study proposes a high accuracy object-based change detection (OBCD) method intended for coral reef environment, which uses QuickBird and WorldView-2 images. The proposed methodological framework includes image fusion, multi-temporal image segmentation, image differencing, random forests models, and object-area-based accuracy assessment. For validation, we applied the method to images of four coral reef study sites in the South China Sea. We compared the proposed OBCD method with a conventional pixel-based change detection (PBCD) method by implementing both methods under the same conditions. The average overall accuracy of OBCD exceeded 90%, which was approximately 20% higher than PBCD. The OBCD method was free from salt-and-pepper effects and was less prone to images misregistration in terms of change detection accuracy and mapping results. The object-area-based accuracy assessment reached a higher overall accuracy and per-class accuracy than the object-number-based and pixel-number-based accuracy assessment.
    Type of Medium: Online Resource
    ISSN: 2220-9964
    URL: Article
    DOI: 10.3390/ijgi7110441
    Language: English
    Publisher: MDPI AG
    Publication Date: 2018
    detail.hit.zdb_id: 2655790-3
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    Online Resource
  • 4
    Online Resource
    Online Resource
    Comparative Analysis on Two Schemes for Synthesizing the High Temporal Landsat-like NDVI Dataset Based on the STARFM Algorithm
    MDPI AG ; 2015
    In:  ISPRS International Journal of Geo-Information Vol. 4, No. 3 ( 2015-08-17), p. 1423-1441
    Details
    In: ISPRS International Journal of Geo-Information, MDPI AG, Vol. 4, No. 3 ( 2015-08-17), p. 1423-1441
    Type of Medium: Online Resource
    ISSN: 2220-9964
    URL: Article
    DOI: 10.3390/ijgi4031423
    Language: English
    Publisher: MDPI AG
    Publication Date: 2015
    detail.hit.zdb_id: 2655790-3
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  • 5
    Online Resource
    Online Resource
    A Dual-Path and Lightweight Convolutional Neural Network for High-Resolution Aerial Image Segmentation
    MDPI AG ; 2019
    In:  ISPRS International Journal of Geo-Information Vol. 8, No. 12 ( 2019-12-12), p. 582-
    Details
    In: ISPRS International Journal of Geo-Information, MDPI AG, Vol. 8, No. 12 ( 2019-12-12), p. 582-
    Abstract: Semantic segmentation on high-resolution aerial images plays a significant role in many remote sensing applications. Although the Deep Convolutional Neural Network (DCNN) has shown great performance in this task, it still faces the following two challenges: intra-class heterogeneity and inter-class homogeneity. To overcome these two problems, a novel dual-path DCNN, which contains a spatial path and an edge path, is proposed for high-resolution aerial image segmentation. The spatial path, which combines the multi-level and global context features to encode the local and global information, is used to address the intra-class heterogeneity challenge. For inter-class homogeneity problem, a Holistically-nested Edge Detection (HED)-like edge path is employed to detect the semantic boundaries for the guidance of feature learning. Furthermore, we improve the computational efficiency of the network by employing the backbone of MobileNetV2. We enhance the performance of MobileNetV2 with two modifications: (1) replacing the standard convolution in the last four Bottleneck Residual Blocks (BRBs) with atrous convolution; and (2) removing the convolution stride of 2 in the first layer of BRBs 4 and 6. Experimental results on the ISPRS Vaihingen and Potsdam 2D labeling dataset show that the proposed DCNN achieved real-time inference speed on a single GPU card with better performance, compared with the state-of-the-art baselines.
    Type of Medium: Online Resource
    ISSN: 2220-9964
    URL: Article
    DOI: 10.3390/ijgi8120582
    Language: English
    Publisher: MDPI AG
    Publication Date: 2019
    detail.hit.zdb_id: 2655790-3
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    Online Resource
  • 6
    Online Resource
    Online Resource
    A Dynamic Indoor Field Model for Emergency Evacuation Simulation
    MDPI AG ; 2017
    In:  ISPRS International Journal of Geo-Information Vol. 6, No. 4 ( 2017-03-30), p. 104-
    Details
    In: ISPRS International Journal of Geo-Information, MDPI AG, Vol. 6, No. 4 ( 2017-03-30), p. 104-
    Type of Medium: Online Resource
    ISSN: 2220-9964
    URL: Article
    DOI: 10.3390/ijgi6040104
    Language: English
    Publisher: MDPI AG
    Publication Date: 2017
    detail.hit.zdb_id: 2655790-3
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  • 7
    Online Resource
    Online Resource
    Method for the Analysis and Visualization of Similar Flow Hotspot Patterns between Different Regional Groups
    MDPI AG ; 2018
    In:  ISPRS International Journal of Geo-Information Vol. 7, No. 8 ( 2018-08-15), p. 328-
    Details
    In: ISPRS International Journal of Geo-Information, MDPI AG, Vol. 7, No. 8 ( 2018-08-15), p. 328-
    Abstract: Interaction among different regions can be illustrated in the form of a stream. For example, the interaction between the flows of people and information among different regions can reflect city network structures, as well as city functions and interconnections. The popularization of big data has facilitated the acquisition of flow data for various types of individuals. The application of the regional interaction model, which is based on the summary level of individual flow data mining, is currently a hot research topic. Thus far, however, previous research on spatial interaction methods has mainly focused on point-to-point and area-to-area interaction patterns, and investigations on the patterns of interaction hotspots between two regional groups with predefined neighborhood relationships, that being with two regions, remain scarce. In this study, a method for the identification of similar interaction hotspot patterns between two regional groups is proposed, and geo-information Tupu methods are applied to visualize interaction patterns. China’s air traffic flow data are used as an example to illustrate the performance of the proposed method to identify and analyze interaction hotspot patterns between regional groups with adjoining relationships across China. Research results indicate that the proposed method efficiently identifies the patterns of interaction flow hotspots between regional groups. Moreover, it can be applied to analyze any flow space in the excavation of the patterns of regional group interaction hotspots.
    Type of Medium: Online Resource
    ISSN: 2220-9964
    URL: Article
    DOI: 10.3390/ijgi7080328
    Language: English
    Publisher: MDPI AG
    Publication Date: 2018
    detail.hit.zdb_id: 2655790-3
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    Online Resource
  • 8
    Online Resource
    Online Resource
    Semantic 3D Modeling Based on CityGML for Ancient Chinese-Style Architectural Roofs of Digital Heritage
    MDPI AG ; 2017
    In:  ISPRS International Journal of Geo-Information Vol. 6, No. 5 ( 2017-04-27), p. 132-
    Details
    In: ISPRS International Journal of Geo-Information, MDPI AG, Vol. 6, No. 5 ( 2017-04-27), p. 132-
    Type of Medium: Online Resource
    ISSN: 2220-9964
    URL: Article
    DOI: 10.3390/ijgi6050132
    Language: English
    Publisher: MDPI AG
    Publication Date: 2017
    detail.hit.zdb_id: 2655790-3
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  • 9
    Online Resource
    Online Resource
    Using Landsat OLI and Random Forest to Assess Grassland Degradation with Aboveground Net Primary Production and Electrical Conductivity Data
    MDPI AG ; 2019
    In:  ISPRS International Journal of Geo-Information Vol. 8, No. 11 ( 2019-11-12), p. 511-
    Details
    In: ISPRS International Journal of Geo-Information, MDPI AG, Vol. 8, No. 11 ( 2019-11-12), p. 511-
    Abstract: Grassland coverage, aboveground net primary production (ANPP), and species composition are used as indicators of grassland degradation. However, soil salinization deficiency, which is also a factor of grassland degradation, is rarely used in grassland degradation assessment in semiarid regions. We assessed grassland degradation by its quality, quantity, and spatial pattern over semiarid west Jilin, China. Considering soil salinization in west Jilin, electrical conductivity (EC) is used as an index with ANPP to assess grassland degradation. First, the spatial distribution of the grassland was measured with information mined from multi-temporal remote sensing images using an object-based image analysis combined with classification and decision tree methods. Second, with 166 field samples, we utilized the random forest (RF) algorithm as the variable selection and regression method for predicting EC and ANPP. Finally, we created a new grassland degradation model (GDM) based on ANPP and EC. The results showed the R2 (0.91) and RMSE (0.057 mS/cm) of the EC model were generally highest and lowest when the ntree was 400; the ANPP model was optimal (R2 = 0.85 and RMSE = 15.81 gC/m2) when the ntree was 600. Grassland area of west Jilin was 609.67 × 103 ha in 2017, there were 373.79 × 103 ha of degraded grassland, with 210.47 × 103 ha being intensively degraded. This paper surpasses past limitations of excessive reliance on vegetation index to construct a grassland degradation model which considers the characteristics of the study area and soil salinity. The results confirm the positive influence of the ecological conservation projects sponsored by the government. The research outcome could offer supporting data for decision making to help alleviate grassland degradation and promote the rehabilitation of grassland vegetation.
    Type of Medium: Online Resource
    ISSN: 2220-9964
    URL: Article
    DOI: 10.3390/ijgi8110511
    Language: English
    Publisher: MDPI AG
    Publication Date: 2019
    detail.hit.zdb_id: 2655790-3
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    Online Resource
  • 10
    Online Resource
    Online Resource
    Impact of High-Resolution Topographic Mapping on Beach Morphological Analyses Based on Terrestrial LiDAR and Object-Oriented Beach Evolution
    MDPI AG ; 2017
    In:  ISPRS International Journal of Geo-Information Vol. 6, No. 5 ( 2017-05-09), p. 147-
    Details
    In: ISPRS International Journal of Geo-Information, MDPI AG, Vol. 6, No. 5 ( 2017-05-09), p. 147-
    Type of Medium: Online Resource
    ISSN: 2220-9964
    URL: Article
    DOI: 10.3390/ijgi6050147
    Language: English
    Publisher: MDPI AG
    Publication Date: 2017
    detail.hit.zdb_id: 2655790-3
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