N: 90 S: -90 E: 180 W: -180
Description
The MCD19A2 Version 6 data product was decommissioned on July 31, 2023. Users are encouraged to use the MCD19A2 Version 6.1 data product.
The MCD19A2 Version 6 data product is a Moderate Resolution Imaging Spectroradiometer (MODIS) Terra and Aqua combined Multi-angle Implementation of Atmospheric Correction (MAIAC) Land Aerosol Optical Depth (AOD) gridded Level 2 product produced daily at 1 kilometer (km) pixel resolution. The MCD19A2 product provides the atmospheric properties and view geometry used to calculate the MAIAC Land Surface Bidirectional Reflectance Factor (BRF) or surface reflectance, MCD19A1 product.
The MCD19A2 AOD data product contains the following Science Dataset (SDS) layers: blue band AOD at 0.47 µm, green band AOD at 0.55 µm, AOD uncertainty, fine mode fraction over water, column water vapor over land and clouds (in cm), smoke injection height (m above ground), AOD QA, AOD model at 1km, cosine of solar zenith angle, cosine of view zenith angle, relative azimuth angle, scattering angle, and glint angle at 5km. A low-resolution browse image is also included showing AOD of the blue band at 0.47 µm created using a composite of all available orbits.
Each SDS layer within each MCD19A2 Hierarchical Data Format 4 (HDF4) file contains a third dimension that represents the number of orbit overpasses. This factor could affect the total number of bands for each SDS layer.
Known Issues
- The longname in the internal metadata is provided incorrectly. The correct longname is "MODIS/Terra and Aqua MAIAC Land Aerosol Optical Depth Daily L2G 1 km SIN Grid."
- Additional known issues are described on page 14 of the User Guide.
- For complete information about known issues please refer to the MODIS/VIIRS Land Quality Assessment website.
Product Summary
Citation
Citation is critically important for dataset documentation and discovery. This dataset is openly shared, without restriction, in accordance with the EOSDIS Data Use and Citation Guidance.
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File Naming Convention
The file name begins with the Product Short Name (MCD19A2) followed by the Julian Date of Acquisition formatted as AYYYYDDD (A2002281), the Tile Identifier which is horizontal tile and vertical tile provided as hXXvYY (h33v11), the Version of the data collection (006), the Julian Date and Time of Production designated as YYYYDDDHHMMSS (2018017104530), and the Data Format (hdf).
Documents
USER'S GUIDE
ALGORITHM THEORETICAL BASIS DOCUMENT (ATBD)
DATA PRODUCT SPECIFICATION
Publications Citing This Dataset
| Title | Year Sort ascending | Author | Topic |
|---|---|---|---|
| Characteristics of Remotely Sensed Urban Pollution Island (UPI) & its Linkage with Surface Urban Heat Island (SUHI) over Eastern India | Barat, Archisman, Parth Sarthi, P. | Aerosol Optical Depth/Thickness, Land Surface Temperature, Emissivity, Aerosol Backscatter, Aerosol Extinction, Angstrom Exponent, Aerosol Particle Properties, Aerosol Radiance, Carbonaceous Aerosols, Dust/Ash/Smoke, Nitrate Particles, Organic Particles, Particulate Matter, Sulfate Particles, Optical Depth/Thickness, Radiative Flux, Reflectance | |
| Changes in air pollution, land surface temperature, and urban heat islands during the COVID-19 lockdown in three Chinese urban agglomerations | Feng, Zihao, Wang, Xuhong, Yuan, Jiaxin, Zhang, Ying, Yu, Mengqianxi | Land Surface Temperature, Emissivity, Aerosol Optical Depth/Thickness, Vegetation Index, Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI) | |
| Burned agricultural biomass, air pollution and crime | Ayesh, Abubakr | Aerosol Optical Depth/Thickness | |
| Assessment of urban sprawls, amenities, and indifferences of LST and AOD in sub-urban area: a case study of Jammu | Varade, Divyesh, Singh, Hemant, Singh, Abhinav Pratap, Awasthi, Shubham | Aerosol Optical Depth/Thickness, Land Surface Temperature, Emissivity | |
| Diurnal to seasonal variability of aerosols above the Mediterranean | Kaskaoutis, Dimitris G., Stavroulas, Iasonas, Bougiatioti, Aikaterini, Gerasopoulos, Evangelos, Mihalopoulos, Nikolaos, Alastuey, Andres, Minguillon, Maria Cruz, Rashki, Alireza, Sciare, Jean, Titos, Gloria | Aerosol Optical Depth/Thickness | |
| Downwind Ozone Changes of the 2019 Williams Flats Wildfire: Insights | Pouyaei, Arman, Mizzi, Arthur P., Choi, Yunsoo, Mousavinezhad, Seyedali, Khorshidian, Nima | Carbon And Hydrocarbon Compounds, Nitrogen Dioxide, Aerosol Optical Depth/Thickness, Aerosol Backscatter, Aerosol Extinction, Angstrom Exponent, Aerosol Particle Properties, Aerosol Radiance, Carbonaceous Aerosols, Cloud Condensation Nuclei, Dust/Ash/Smoke, Nitrate Particles, Organic Particles, Particulate Matter, Sulfate Particles, Optical Depth/Thickness, Radiative Flux, Reflectance | |
| Machine learning-based spatial data development for optimizing | Sakti, Anjar Dimara, Zakiar, Muhammad Rizky, Santoso, Cokro, Windasari, Nila Armelia, Jaelani, Anton Timur, Damayanti, Seny, Anggraini, Tania Septi, Putri, Anissa Dicky, Hudalah, Delik, Deliar, Albertus | Aerosol Optical Depth/Thickness | |
| Prediction of abnormal proliferation risk of Phaeocystis globosa based on correlation mining of PC concentration indicator and meteorological factors along ... | Chen, Huaquan, Yao, Huanmei, Liao, Pengren, Wen, Ke, Huang, Yi, Zhong, Weiping | Aerosol Optical Depth/Thickness | |
| Modeling the Air Pollution and Weather Feedback from Wildfire Emissions with WRFChem over Greece | Rovithakis, Anastasios, Voulgarakis, Apostolos | Aerosol Optical Depth/Thickness | |
| Saharan dust and childhood respiratory symptoms in Benin | McElroy, Sara, Dimitrova, Anna, Evan, Amato, Benmarhnia, Tarik | Aerosol Optical Depth/Thickness, Reflectance | |
| The environmental story during the COVID-19 lockdownHow human activities affect PM2.5 concentration in China? | Tan, Zhenyu, Li, Xinghua, Gao, Meiling, Jiang, Liangcun | Aerosol Optical Depth/Thickness | |
| Synergy between the Urban Heat Island and the Urban Pollution Island in | Mendez-Astudillo, Jorge, Caetano, Ernesto, Pereyra-Castro, Karla | Aerosol Optical Depth/Thickness | |
| Temporal and spatial distribution mapping of particulate matter in southwest of Iran using remote sensing, GIS, and statistical techniques | Soleimany, Arezoo, Solgi, Eisa, Ashrafi, Khosro, Jafari, Reza, Grubliauskas, Raimondas | Aerosol Optical Depth/Thickness | |
| Spatiotemporal distributions of PM2.5 concentrations in the Beijing-Tianjin-Hebei region from 2013 to 2020 | Yang, Xiaohui, Xiao, Dengpan, Bai, Huizi, Tang, Jianzhao, Wang, Wei | Aerosol Optical Depth/Thickness | |
| Spatiotemporal pattern and long-term trend of global surface urban heat islands characterized by dynamic urban-extent method and MODIS data | Si, Menglin, Li, Zhao-Liang, Nerry, Francoise, Tang, Bo-Hui, Leng, Pei, Wu, Hua, Zhang, Xia, Shang, Guofei | Aerosol Optical Depth/Thickness, Vegetation Index, Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Land Surface Temperature, Emissivity, Land Use/Land Cover Classification, Albedo, Anisotropy | |
| Spatiotemporal PM2.5 estimations in China from 2015 to 2020 using an improved gradient boosting decision tree | He, Weihuan, Meng, Huan, Han, Jie, Zhou, Gaohui, Zheng, Hui, Zhang, Songlin | Land Use/Land Cover Classification, Aerosol Optical Depth/Thickness, Vegetation Index, Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI) | |
| Spatiotemporal variation and provincial scale differences of the AOD across China during 20002021 | de Leeuw, Gerrit, Fan, Cheng, Li, Zhengqiang, Dong, Jiantao, Li, Yinna, Ou, Yang, Zhu, Sifeng | Aerosol Optical Depth/Thickness, Land Surface Temperature, Emissivity | |
| SmokeDriven Changes in Photosynthetically Active Radiation During the US Agricultural Growing Season | Corwin, Kimberley A., Corr, Chelsea A., Burkhardt, Jesse, Fischer, Emily V. | Aerosol Optical Depth/Thickness, Aerosol Backscatter, Aerosol Extinction, Angstrom Exponent, Aerosol Particle Properties, Aerosol Radiance, Carbonaceous Aerosols, Cloud Condensation Nuclei, Dust/Ash/Smoke, Nitrate Particles, Organic Particles, Particulate Matter, Sulfate Particles, Trace Gases/Trace Species, Atmospheric Emitted Radiation, Emissivity, Optical Depth/Thickness, Radiative Flux, Reflectance, Transmittance, Atmospheric Stability, Humidity, Total Precipitable Water, Water Vapor Profiles, Cloud Condensation Nuclei, Cloud Droplet Concentration/Size, Cloud Liquid Water/Ice, Cloud Optical Depth/Thickness, Cloud Asymmetry, Cloud Ceiling, Cloud Frequency, Cloud Height, Cloud Top Pressure, Cloud Top Temperature, Cloud Vertical Distribution, Cloud Emissivity, Cloud Radiative Forcing, Cloud Reflectance, Rain Storms, Atmospheric Ozone | |
| Recent trends of land surface temperature in relation to the influencing factors using Google Earth Engine platform and time series products in megacities of India | Bera, Dipankar, Chatterjee, Nilanjana Das, Ghosh, Subrata, Dinda, Santanu, Bera, Sudip | Reflectance, Aerosol Optical Depth/Thickness, Land Surface Temperature, Emissivity, Albedo, Anisotropy | |
| UrbanRural Gradient in Urban Heat Island Variations Responsive to LargeScale Human Activity Changes During Chinese New Year Holiday | Zhan, Wenfeng, Liu, Zihan, Bechtel, Benjamin, Li, Jiufeng, Lai, Jiameng, Fu, Huyan, Li, Long, Huang, Fan, Wang, Chunli, Chen, Yangyi | Albedo, Anisotropy, Vegetation Index, Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Land Surface Temperature, Emissivity, Plant Phenology, Land Use/Land Cover Classification, Aerosol Optical Depth/Thickness, Surface Pressure, Heat Flux, Longwave Radiation, Shortwave Radiation, Air Temperature, Specific Humidity, Evapotranspiration, Wind Speed, Rain, Snow, Soil Moisture/Water Content, Soil Temperature, Snow Cover, Snow Depth, Snow Water Equivalent, Runoff | |
| Vegetation activity enhanced in India during the COVID-19 lockdowns: evidence from satellite data | Ranjan, Avinash Kumar, Dash, Jadunandan, Xiao, Jingfeng, Gorai, Amit Kumar | Land Use/Land Cover Classification, Vegetation Index, Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Aerosol Optical Depth/Thickness | |
| Wildfire-induced pollution and its short-term impact on COVID-19 cases and mortality in California | Naqvi, Hasan Raja, Mutreja, Guneet, Shakeel, Adnan, Singh, Karan, Abbas, Kumail, Naqvi, Darakhsha Fatma, Chaudhary, Anis Ahmad, Siddiqui, Masood Ahsan, Gautam, Alok Sagar, Gautam, Sneha, Naqvi, Afsar Raza | Aerosol Optical Depth/Thickness | |
| Gap-filling MODIS daily aerosol optical depth products by developing a spatiotemporal fitting algorithm | Zhang, Tao, Zhou, Yuyu, Zhao, Kaiguang, Zhu, Zhengyuan, Asrar, Ghassem R., Zhao, Xia | Aerosol Optical Depth/Thickness | |
| Estimation of aerosol optical depth at 30 m resolution using Landsat imagery and machine learning | Liang, Tianchen, Liang, Shunlin, Zou, Linqing, Sun, Lin, Li, Bing, Lin, Hao, He, Tao, Tian, Feng | Aerosol Optical Depth/Thickness, Terrain Elevation, RADAR IMAGERY, Topographical Relief Maps | |
| Evaluation of trophic state for inland waters through combining | Liu, Yongxin, Wu, Huan, Wang, Shenglei, Chen, Xiuwan, Kimball, John S., Zhang, Chenlu, Gao, Han, Guo, Peng | Aerosol Optical Depth/Thickness |