A5021452248- Atmospheric aerosols and clouds
- Atmospheric chemistry and aerosols
- Atmospheric Ozone and Climate
- Atmospheric and Environmental Gas Dynamics
- Remote Sensing in Agriculture
- Air Quality and Health Impacts
- Air Quality Monitoring and Forecasting
- Calibration and Measurement Techniques
- Remote Sensing and LiDAR Applications
- Remote Sensing and Land Use
- Land Use and Ecosystem Services
- Fire effects on ecosystems
- Plant Water Relations and Carbon Dynamics
- Urban Heat Island Mitigation
- Meteorological Phenomena and Simulations
- Climate Change and Health Impacts
- Geophysics and Gravity Measurements
- Geochemistry and Geologic Mapping
- Aeolian processes and effects
- Cryospheric studies and observations
- Vehicle emissions and performance
- Satellite Image Processing and Photogrammetry
- Water Systems and Optimization
- Flow Measurement and Analysis
- Advanced Sensor Technologies Research
Goddard Space Flight Center
2016-2025
National Aeronautics and Space Administration
2013-2024
University of Maryland, College Park
2023
University of Iowa
2023
Harvard University
2023
Washington University in St. Louis
2023
Southern University of Science and Technology
2023
Peking University
2023
University of Oklahoma
2021
Ministry of Ecology and Environment
2021
Abstract. The Aerosol Robotic Network (AERONET) has provided highly accurate, ground-truth measurements of the aerosol optical depth (AOD) using Cimel Electronique Sun–sky radiometers for more than 25 years. In Version 2 (V2) AERONET database, near-real-time AOD was semiautomatically quality controlled utilizing mainly cloud-screening methodology, while additional data contaminated by clouds or affected instrument anomalies were removed manually before attaining quality-assured status (Level...
We estimated global fine particulate matter (PM2.5) concentrations using information from satellite-, simulation- and monitor-based sources by applying a Geographically Weighted Regression (GWR) to geophysically based satellite-derived PM2.5 estimates. Aerosol optical depth multiple satellite products (MISR, MODIS Dark Target, SeaWiFS Deep Blue, MAIAC) was combined with simulation (GEOS-Chem) upon their relative uncertainties as determined ground-based sun photometer (AERONET) observations...
Abstract. This paper describes the latest version of algorithm MAIAC used for processing MODIS Collection 6 data record. Since initial publication in 2011–2012, has changed considerably to adapt global and improve cloud/snow detection, aerosol retrievals atmospheric correction data. The main changes include (1) transition from a 25 1 km scale retrieval spectral regression coefficient (SRC) which helped remove occasional blockiness at optical depth (AOD) surface reflectance, (2) continuous...
Exposure to outdoor fine particulate matter (PM2.5) is a leading risk factor for mortality. We develop global estimates of annual PM2.5 concentrations and trends 1998-2018 using advances in satellite observations, chemical transport modeling, ground-based monitoring. Aerosol optical depths (AODs) from advanced products including finer resolution, increased coverage, improved long-term stability are combined related surface geophysical relationships between AOD simulated by the GEOS-Chem...
[1] An aerosol component of a new multiangle implementation atmospheric correction (MAIAC) algorithm is presented. MAIAC generic developed for the Moderate Resolution Imaging Spectroradiometer (MODIS), which performs retrievals and over both dark vegetated surfaces bright deserts based on time series analysis image-based processing. The look-up tables explicitly include surface bidirectional reflectance. derives spectral regression coefficient (SRC) relating reflectance in blue (0.47 μm)...
Various approaches have been proposed to model PM
A strong positive correlation between vegetation canopy bidirectional reflectance factor (BRF) in the near infrared (NIR) spectral region and foliar mass-based nitrogen concentration (%N) has been reported some temperate boreal forests. This relationship, if true, would indicate an additional role for climate system via its influence on surface albedo may offer a simple approach monitoring using satellite data. We report, however, that previously is artifact--it consequence of variations...
Annual global satellite-based estimates of fine particulate matter (PM2.5) are widely relied upon for air-quality assessment. Here, we develop and apply a methodology monthly uncertainties during the period 1998–2019, which combines satellite retrievals aerosol optical depth, chemical transport modeling, ground-based measurements to allow characterization seasonal episodic exposure, as well aid management. Many densely populated regions have their highest PM2.5 concentrations in winter,...
Abstract. Fine particulate matter with aerodynamic diameters ≤2.5 µm (PM2.5) has adverse effects on human health and the atmospheric environment. The estimation of surface PM2.5 concentrations made intensive use satellite-derived aerosol products. However, it been a great challenge to obtain high-quality high-resolution data from both ground satellite observations, which is essential monitor air pollution over small-scale areas such as metropolitan regions. Here, space–time extremely...
Abstract Mapping aboveground forest biomass is central for assessing the global carbon balance. However, current large-scale maps show strong disparities, despite good validation statistics of their underlying models. Here, we attribute this contradiction to a flaw in methods, which ignore spatial autocorrelation (SAC) data, leading overoptimistic assessment model predictive power. To illustrate issue, reproduce approach mapping studies using massive inventory dataset 11.8 million trees...
A number of models have been developed to estimate PM2.5 exposure, including satellite-based aerosol optical depth (AOD) models, land-use regression, or chemical transport model simulation, all with both strengths and weaknesses. Variables like normalized difference vegetation index (NDVI), surface reflectance, absorbing index, meteoroidal fields are also informative about concentrations. Our objective is establish a hybrid which incorporates multiple approaches input variables improve...
Since 1972, the Landsat program has been continually monitoring Earth, to now provide 50 years of digital, multispectral, medium spatial resolution observations. Over this time, data were crucial for many scientific and technical advances. Prior program, detailed, synoptic depictions Earth's surface rare, ability acquire work with large datasets was limited. The early delivered a series technological breakthroughs, pioneering new methods, demonstrating capacity digital satellite imagery,...
Particulate matter (PM) air pollution is one of the major causes death worldwide, with demonstrated adverse effects from both short-term and long-term exposure. Most epidemiological studies have been conducted in cities because lack reliable spatiotemporal estimates particles exposure nonurban settings. The objective this study to estimate daily PM10 (PM < 10 μm), fine 2.5 μm, PM2.5) coarse between PM2.5–10) at 1-km2 grid for 2013–2015 using a machine learning approach, Random Forest (RF)....
Abstract [1] This paper describes a radiative transfer basis of the algorithm MAIAC which performs simultaneous retrievals atmospheric aerosol and bidirectional surface reflectance from Moderate Resolution Imaging Spectroradiometer (MODIS). The are based on an accurate semianalytical solution for top-of-atmosphere expressed as explicit function three parameters Ross–Thick Li–Sparse model reflectance. depends certain functions properties geometry precomputed in look-up table (LUT). further...
Abstract. The Aerosol Robotic Network (AERONET) Version 3 (V3) aerosol retrieval algorithm is described, which based on the 2 (V2) with numerous updates. Comparisons of V3 retrievals to those V2 are presented, along a new approach estimate uncertainties in many retrieved parameters. Changes include (1) polarized radiative transfer code (RTC), replaced scalar RTC V2, (2) detailed characterization gas absorption by adding NO2 and H2O specify total atmospheric column, specification vertical...
We show that the vegetation canopy of Amazon rainforest is highly sensitive to changes in precipitation patterns and reduction rainfall since 2000 has diminished greenness across large parts Amazonia. Large-scale directional declines may indicate decreases carbon uptake substantial energy balance Amazon. use improved estimates surface reflectance from satellite data a close link between reductions annual precipitation, El Niño southern oscillation events, photosynthetic activity tropical...
The Mongolian Steppe is one of the largest remaining grassland ecosystems. Recent studies have reported widespread decline vegetation across steppe and about 70% this ecosystem now considered degraded. Among scientific community there has been an active debate whether observed degradation related to climate, or over-grazing, both. Here, we employ a new atmospheric correction cloud screening algorithm (MAIAC) investigate trends in satellite phenology. We relate these changes climate domestic...
NO2 is a combustion byproduct that has been associated with multiple adverse health outcomes. To assess levels high accuracy, we propose the use of an ensemble model to integrate machine learning algorithms, including neural network, random forest, and gradient boosting, variety predictor variables, chemical transport models. This covers entire contiguous U.S. daily predictions on 1-km-level grid cells from 2000 2016. The produced cross-validated R2 0.788 overall, spatial 0.844, temporal...