Geoscience and Remote Sensing

Remote sensing of environment research has explored the benefits of using synthetic aperture radar imagery systems for a wide range of land and marine applications since these systems are not affected by weather conditions and therefore are operable both daytime and nighttime. The design of image processing techniques for  synthetic aperture radar applications requires tests and validation on real and synthetic images. The GRSS benchmark database supports the desing and analysis of algorithms to deal with SAR and PolSAR data.

Last Updated On: 
Tue, 02/08/2022 - 17:46
Citation Author(s): 
Nobre, R. H.; Rodrigues, F. A. A.; Rosa, R.; Medeiros, F.N.; Feitosa, R., Estevão, A.A., Barros, A.S.

A pothole dataset collected by iPhone 14 pro. Due to the lack of publicly available small-scale pothole point cloud datasets, a custom dataset was created for model performance evaluation. The data collection area is located within the Yujiaotou campus of Wuhan University of Technology and the surrounding road network in Wuhan, China. For data acquisition, an iPhone 14 Pro equipped with a LiDAR scanner was used.

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Extracting ships from complex backgrounds is the bottleneck of ship detection in high-resolution optical satellite images. In this letter, we propose a nearly closed-form ship rotated bounding box space used for ship detection and design a method to generate a small number of highly potential candidates based on this space. We first analyze the possibility of accurately covering all ships by labeling rotated bounding boxes. Moreover, to reduce search space, we construct a nearly closed-form ship rotated bounding box space.

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This dataset is the supporting simulated data for the paper titled "Hidden Border Tunnels: Research on Excavation Monitoring and Excavation Path Prediction." These data are generated through physical simulations and are used to validate the effectiveness of the algorithms proposed in the paper. The dataset includes the coordinates of simulated vibration events, as well as the prediction results of excavation events by various machine learning models, such as RNN, LSTM, GRU, Transformer, CNN_Transformer, and LSTMTransformer.

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This dataset is the supporting simulated data for the paper titled "Hidden Border Tunnels: Research on Excavation Monitoring and Excavation Path Prediction." These data are generated through physical simulations and are used to validate the effectiveness of the algorithms proposed in the paper. The dataset includes the coordinates of simulated vibration events, as well as the prediction results of excavation events by various machine learning models, such as RNN, LSTM, GRU, Transformer, CNN_Transformer, and LSTMTransformer.

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7 Views

Satellite attitude determination is critical for accurately measuring and controlling a satellite’s orientation in orbit using a variety of sensors and methods. Currently, low-low Satellite-to-Satellite Tracking (ll-SST) missions—such as GRACE(-FO)—and upcoming missions like Magic primarily rely on quaternion data from onboard star camera sensors. To enhance attitude determination, we propose a GSCF fusion method.

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This dataset includes three types: DEM, land cover data, and high-definition remote sensing images.

Among them, the DEM data has an accuracy of 30 meters and is used to calculate the slope value. The land cover data has an accuracy of 8.98 meters and is located in a field area in southern Taiwan, China, and is used to extract coarse-grained land object types. The high-definition remote sensing data is taken by drones with an accuracy of 0.03 meters and is used for unsupervised classification of land objects.

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Ecological carrying capacity (ECC) is central to assessing the sustainability of ecosystems, aiming to quantify the limits of natural systems to support human activities while maintaining biodiversity and resource regeneration. To assess ECC, earlier studies typically used the analytic hierarchy process (AHP) method for modeling.

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MapData is a globally diverse dataset spanning 233 geographic sampling points. It offers original high-resolution images ranging from 7,000×5,000 to 20,000×15,000 pixels. After rigorous cleaning, the dataset provides 121,781 aligned electronic map–visible image pairs (each standardized to 512×512 pixels) with hybrid manual-automated ground truth—addressing the scarcity of scalable multimodal benchmarks.

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47 Views

We develop a geological and geophysical forward modeling workflow from the perspective of stratigraphic forward modeling, adding fold structures, building attribute models, building seismic data. Specifically, we first use PyBadlands (Salles et al., 2018) to simulate numerous stratigraphic layers under diverse forcing conditions. Then we perform the interpolation process to obtain a stratigraphic volume and add folding structures (Wu et al., 2020).

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