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Earth Observation

Earth Observation (EO) refers to the use of remote sensing technologies to monitor land, marine (seas, rivers, lakes) and atmosphere. Satellite-based EO relies on the use of satellite-mounted payloads to gather imaging data about the Earth’s characteristics. The images are then processed and analyzed in order to extract different types of information that can serve a very wide range of applications and industries.

Papers

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Showing 276–300 of 518 papers

TitleStatusHype
Get Your Embedding Space in Order: Domain-Adaptive Regression for Forest MonitoringCode0
GeoLLM-Engine: A Realistic Environment for Building Geospatial Copilots—0
Equivariant Imaging for Self-supervised Hyperspectral Image Inpainting—0
Detecting Out-Of-Distribution Earth Observation Images with Diffusion Models—0
Bridging Data Islands: Geographic Heterogeneity-Aware Federated Learning for Collaborative Remote Sensing Semantic Segmentation—0
Uncertainty Aware Tropical Cyclone Wind Speed Estimation from Satellite DataCode0
Automated National Urban Map Extraction—0
Onboard Processing of Hyperspectral Imagery: Deep Learning Advancements, Methodologies, Challenges, and Emerging Trends—0
Deep Learning for Satellite Image Time Series Analysis: A Review—0
Neural Embedding Compression For Efficient Multi-Task Earth Observation ModellingCode0
SatSynth: Augmenting Image-Mask Pairs through Diffusion Models for Aerial Semantic Segmentation—0
Impact Assessment of Missing Data in Model Predictions for Earth Observation ApplicationsCode0
Early Flood Warning Using Satellite-Derived Convective System and Precipitation Data -- A Retrospective Case Study of Central Vietnam—0
Assimilation of SWOT Altimetry and Sentinel-1 Flood Extent Observations for Flood Reanalysis -- A Proof-of-Concept—0
Local Binary and Multiclass SVMs Trained on a Quantum AnnealerCode0
A Geospatial Approach to Predicting Desert Locust Breeding Grounds in Africa—0
Impacts of Color and Texture Distortions on Earth Observation Data in Deep Learning—0
Portraying the Need for Temporal Data in Flood Detection via Sentinel-1—0
From Spectra to Biophysical Insights: End-to-End Learning with a Biased Radiative Transfer ModelCode0
Toward Autonomous Cooperation in Heterogeneous Nanosatellite Constellations Using Dynamic Graph Neural Networks—0
Quick unsupervised hyperspectral dimensionality reduction for earth observation: a comparison—0
ViGEO: an Assessment of Vision GNNs in Earth ObservationCode0
Solid Waste Detection, Monitoring and Mapping in Remote Sensing Images: A Survey—0
Large Language Models for Captioning and Retrieving Remote Sensing Images—0
Ai4Fapar: How artificial intelligence can help to forecast the seasonal earth observation signal—0
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