arXiv AI
Jun 24
MVG-KAN: Multi-View Geo-Wind Guided KAN for PM$_{2.5}$ Forecasting
arXiv:2606. 24347v1 Announce Type: new Abstract: Accurate short-term PM$_{2.
Tracking Urban Atmospheric Pollutants using Sentinel-5P Satellite Data
arXiv:2606. 02592v1 Announce Type: cross Abstract: Urban nitrogen dioxide ($NO_2$) is a key indicator of combustion-related air pollution and exhibits strong spatial and temporal variability in cities.
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arXiv Machine Learning
Jul 7
Closing Gaps in Emissions Monitoring with Climate TRACE
arXiv:2511. 19277v2 Announce Type: replace Abstract: Global greenhouse gas emissions estimates are essential for monitoring and mitigation planning.
arXiv Machine Learning
Jul 23
Air Quality Arena: A Large-Scale Multi-Region Ground Monitoring Dataset and Benchmark for Air Quality Forecasting with Time-Series Foundation Models
arXiv:2607. 19381v1 Announce Type: new Abstract: Air pollution causes an estimated 7.
arXiv AI
6d ago
Remote Sensing and Machine Learning-Based Analysis of Land Use and Vegetation Change in Dhaka District, Bangladesh
arXiv:2608. 12001v1 Announce Type: cross Abstract: Rapid urbanization in Dhaka District, Bangladesh has triggered substantial alterations in land use and environmental conditions, necessitating systematic monitoring for informed urban planning and ecological sustainability.
arXiv AI
Aug 11
AirFlow: Context Preserving and Multi-Rate State Modeling for Air Quality Forecasting
arXiv:2608. 09775v1 Announce Type: new Abstract: Accurate air quality forecasting is essential for public health and urban environmental management, but remains challenging because pollutant channels differ in periodicity and distribution drift, while their concentration trajectories contain both multi-scale dependencies and rapid changes.
arXiv Machine Learning
Jul 21
Apeliotes: A Diffusion-Based Modeling Framework for km-scale Multi-Level Atmospheric Fields
arXiv:2607. 17037v1 Announce Type: new Abstract: High-resolution atmospheric data are required to resolve mesoscale and localized meteorological structures, however such datasets remain limited in many regions of the world.
arXiv Machine Learning
Jun 16
deFOREST: Fusing Optical and Radar satellite data for Enhanced Sensing of Tree-loss
arXiv:2510. 14092v2 Announce Type: replace-cross Abstract: In this paper we develop a deforestation detection pipeline that incorporates optical and Synthetic Aperture Radar (SAR) data.
arXiv AI
Jul 29
From Deterministic to Generative Deep Learning for Urban Air Quality Reconstruction from Sparse Observations
arXiv:2607. 25687v1 Announce Type: cross Abstract: Full-field reconstruction of air pollution is essential for evaluating pollution exposure and supporting public health decision-making.
arXiv Machine Learning
Jun 11
Urban Heat MiniCubes: An AI-Ready dataset for urban heat research
arXiv:2606. 11534v1 Announce Type: cross Abstract: Urban heat is amplified by impermeable surfaces and heterogeneous built environments, yet street-level variability remains difficult to quantify because multi-sensor observations are rarely available in consistent, analysis-ready form at the necessary spatiotemporal scales.
arXiv Machine Learning
Jul 31
Foundation-Model Earth Representations Enable Regional-Scale Forest Aboveground Biomass Monitoring Across the Northeastern United States
arXiv:2607. 27217v1 Announce Type: cross Abstract: Forest aboveground biomass (AGB) is a critical indicator of ecosystem productivity and terrestrial carbon storage, yet regional carbon monitoring remains constrained by the sparse spatial and temporal availability of field inventories and airborne structural measurements.
Hugging Face Trending Papers
Jul 30
Large scale cross-regional remote sensing flood monitoring framework for operative mapping and impact analysis
Effective flood monitoring is critical for minimizing the impacts of flood disasters on populations and infrastructure. Yet reliable remote sensing across extensive and environmentally diverse regions remains challenging, as most segmentation algorithms lack the generalisation capacity required for large-scale application, while annotated flood data are scarce and unevenly distributed.
arXiv Machine Learning
5d ago
Which Site, and When: A Free-Satellite-Data Test of Himalayan Glacial Lake Bursts, Landslides, and Ice Floods
arXiv:2608. 12422v1 Announce Type: new Abstract: Two free satellite signals carry real information about glacial-lake outburst risk in the Nepal Himalaya: radar interferometry sees a moraine dam slowly sagging, and satellite weather marks the weeks when a primed lake is under stress.