Geoscience and Remote Sensing
Radar data and Pluviometric data for Sardinia (Italy)
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The dataset contains UAV imagery and fracture interpretation of rock outcrops acquired in Praia das Conchas, Cabo Frio, Rio de Janeiro, Brazil. Along with georeferenced .geotiff images, the dataset contains filtered 500 x 500 .png tiles containing only scenes with fracture data, along with .png binary masks for semantic segmentation and original georeferenced shapefile annotations. This data can be useful for segmentation and extraction of geological structures from UAV imagery, for evaluating computer vision methodologies or machine learning techniques.
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Here, a dataset used in manuscript "Wide-Area Land Cover Mapping with Sentinel-1 Imagery using Deep Learning Semantic Segmentation Models" Scepanovic et al. (https://doi.org/10.1109/JSTARS.2021.3116094) is published. The data contains preprocessed SAR backscatter digital numbers as 7000 geotiff image patches of size 512x512 (about 10 km x 10 km size) sampled from several wide-area SAR mosaics compiled from all summer Sentinel-1A images acquired over Finland in the summer of 2018.
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Targeting the Huangnibazi Landslide located in the southwestern mountainous region of China, which is mainly induced by the heavy rainfall and the Jiuzhaigou earthquake, we implement the self-potential (SP) monitoring system and global navigation satellite system (GNSS) on the slope. The SP and GNSS data monitored at the slow-moving stage of the landslide are supplied.
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This dataset is the model data required in the manuscript for IEEE Transactions on geoscience and remote sensing.
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The dataset contains hurricane Maria-induced outage duration at the barrio level derived from nighttime lights, along with the values of cofactors from socioeconomic and physical factors that influenced the recovery process.
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