Moderate-Resolution Imaging Spectroradiometer
PulseAugur coverage of Moderate-Resolution Imaging Spectroradiometer — every cluster mentioning Moderate-Resolution Imaging Spectroradiometer across labs, papers, and developer communities, ranked by signal.
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New RNN Maxent model improves ecological forecasting by learning nonlinear time-series relationships
Researchers have developed RNN Maxent, a novel extension of the Maxent framework that integrates a Gated Recurrent Unit (GRU) neural network to capture nonlinear, temporal relationships in ecological data. This new meth…
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New MODIS framework integrates multi-omics data for rare diseases
Researchers have developed MODIS, a novel semi-supervised framework designed to integrate multi-omics data, particularly for small and unpaired datasets common in rare disease studies. The framework addresses challenges…
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Deep learning enhances satellite cloud mask resolution with new dataset
Researchers have developed two deep learning models, SpatialCNN and SpatialGAN, to improve the spatial resolution of satellite cloud mask products. These models are designed to downscale SEVIRI cloud mask data, achievin…
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New AI framework models power-line risk using remote sensing data
A new probability-of-failure (PoF) modeling framework has been developed for electric power grid asset management, integrating remote sensing data to predict risks from lightning and vegetation. This modular and explain…
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New technique aligns satellite data for improved Antarctic sea ice labeling
Researchers have developed a new method to align multimodal satellite imagery, specifically from Sentinel-1 and MODIS platforms, to improve the labeling of Antarctic sea ice. This approach addresses the challenge of spa…
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New framework reconstructs NDVI time-series data using self-supervised learning
Researchers have developed GloSSR, a novel self-supervised spatiotemporal learning framework designed to reconstruct Normalized Difference Vegetation Index (NDVI) time series data. This method addresses the challenge of…
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New ML framework accurately detects clouds using infrared data
Researchers have developed a new machine learning framework called the Cloud Identification Support Vector Machine (CISVM) for detecting clouds using infrared atmospheric sounding data. This supervised approach exclusiv…
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New CanadaFireSat dataset enables high-resolution wildfire forecasting
Researchers have developed a new benchmark dataset called CanadaFireSat to improve high-resolution wildfire forecasting. This dataset utilizes multi-modal data, including high-resolution satellite imagery from Sentinel-…
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Vision Transformers Enhance Coastal Algal Bloom Mapping
Researchers have developed a new method for mapping coastal algal blooms using vision transformers, a type of deep learning model. This approach leverages high-resolution imagery from Landsat-8/9 and Sentinel-2 satellit…
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Houston clouds align with interstate roads, showing urban heat effect
New satellite imagery from Houston, Texas, has revealed clouds forming in perfect alignment with the city's interstate roads. This phenomenon, observed by meteorologists, provides compelling visual evidence for the "urb…
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AI model quantifies CO2 using satellite weather data
Researchers have developed a physics-guided neural network capable of quantifying atmospheric carbon dioxide ($XCO_2$) using data from the Geostationary Operational Environmental Satellite (GOES-East). This model levera…
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New GDS-Mamba model enhances tree species classification with graph and sparse tokens
Researchers have developed a new model called GDS-Mamba to improve the classification of tree species using MODIS satellite time series data. This model addresses challenges like subtle species differences and the coupl…
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New satellite system uses AI for real-time wildfire detection under strict constraints
Researchers have developed a real-time wildfire detection system for use on satellites, designed to operate under strict on-board constraints. The system utilizes a lightweight dense representation learning approach, sp…
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Earth System Foundation Model integrates diverse data for climate forecasting
Researchers have developed the Earth System Foundation Model (ESFM), an open-source framework designed to integrate and forecast using diverse Earth system data. ESFM builds upon the Aurora model's architecture and inco…