ArticleRemote sensing of environment2019
Impacts of snow and cloud covers on satellite-derived PM
Article in Remote sensing of environment, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
24 citing papers in PubMed.
- A Hybrid Transfer Learning Approach for Ambient PMACS ES&T air · 2026Article
- Environmental exposure to air pollution and climate: Intersecting the impact on ear and nose health and chemosensory function (Review).International journal of molecular medicine · 2026Review
- Ambient PMCurrent environmental health reports · 2026Review
- Aerosol optical depth trends and variability over the Middle East from MODIS, MISR, OMI, and AERONET observations.Scientific reports · 2025Article
- Development of longitudinal datasets (2000-2020) with high spatiotemporal resolution for air pollution exposure assessment in Canada.Data in brief · 2025Article
- Estimating PMToxics · 2025Article
- Machine learning-based quantification and separation of emissions and meteorological effects on PMScientific reports · 2025Article
- Utility of low-cost sensor measurement for predicting ambient PMEnvironmental science: atmospheres · 2025Article
- Application of multi-angle spaceborne observations in characterizing the long-term particulate organic carbon pollution in China.The Science of the total environment · 2025Article
- Reconstructing aerosol optical depth using spatiotemporal Long Short-Term Memory convolutional autoencoder.Scientific data · 2023Article
- Generating High Spatial Resolution Exposure Estimates from Sparse Regulatory Monitoring Data.Atmospheric environment (Oxford, England : 1994) · 2023Article
- Efficacy of Low-Cost Sensor Networks at Detecting Fine-Scale Variations in Particulate Matter in Urban Environments.International journal of environmental research and public health · 2023Article
- Within-City Variation in Ambient Carbon Monoxide Concentrations: Leveraging Low-Cost Monitors in a Spatiotemporal Modeling Framework.Environmental health perspectives · 2022Article
- Application of geostationary satellite and high-resolution meteorology data in estimating hourly PMRemote sensing of environment · 2022Article
- Estimating 2013-2019 NOEnvironmental pollution (Barking, Essex : 1987) · 2022Article
- Robust prediction of hourly PMNational science review · 2021Article
- Short-term PMEnvironmental health : a global access science source · 2021Article
- Estimating PMRemote sensing of environment · 2021Article
- Contribution of low-cost sensor measurements to the prediction of PMEnvironmental research · 2020Article
- Methods, availability, and applications of PMJournal of the Air & Waste Management Association (1995) · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
Satellite aerosol optical depth (AOD) has been widely employed to evaluate ground fine particle (PM
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.