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Are the Poor Digitally Left Behind? Indications of Urban Divides Based on Remote Sensing and Twitter Data.

, , , , , and . ISPRS Int. J. Geo Inf., 7 (8): 304 (2018)

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Automated building characterization for seismic risk assessment using street-level imagery and deep learning, , , , , and . ISPRS Journal of Photogrammetry and Remote Sensing, (2021)Deep Relearning in the Geospatial Domain for Semantic Remote Sensing Image Segmentation., , , , , and . IEEE Geosci. Remote. Sens. Lett., (2022)Disaster Intensity-Based Selection of Training Samples for Remote Sensing Building Damage Classification., , , , , and . IEEE Trans. Geosci. Remote. Sens., 59 (10): 8288-8304 (2021)Remote monitoring to predict bridge scour failure using Interferometric Synthetic Aperture Radar (InSAR) stacking techniques., , , , and . Int. J. Appl. Earth Obs. Geoinformation, (2018)Image super-resolution with dense-sampling residual channel-spatial attention networks for multi-temporal remote sensing image classification., , and . Int. J. Appl. Earth Obs. Geoinformation, (2021)LSTM models for spatiotemporal extrapolation of population data., , , and . JURSE, page 1-4. IEEE, (2023)Stability Characterization of the Response of White Storks' Foraging Behavior to Vegetation Dynamics Retrieved from Landsat Time Series., , , , , and . IGARSS, page 4799-4802. IEEE, (2020)Automatic Training Set Compilation With Multisource Geodata for DTM Generation From the TanDEM-X DSM., , , , and . IEEE Geosci. Remote. Sens. Lett., 17 (3): 456-460 (2020)Large-Area Characterization of Urban Morphology: Mapping Built-Up Height and Density with the TanDEM-X Mission and Sentinel-2, , , , , , , , , and . IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 12 (8): 2912--2927 (August 2019)Are the Poor Digitally Left Behind? Indications of Urban Divides Based on Remote Sensing and Twitter Data., , , , , and . ISPRS Int. J. Geo Inf., 7 (8): 304 (2018)