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16 results for “maiac”
The MANVI product: MODIS (MAIAC) nadir-solar adjusted vegetation indices (EVI and NDVI) for South America
<p><strong>Title: </strong>The MANVI product: MODIS (MAIAC) nadir-solar adjusted vegetation indices (EVI and NDVI) for South America.</p> <p><strong>Authors:</strong> Dalagnol, Ricardo; Wagner, Fabien Hubert; Galvão, Lênio Soares; Aragão, Luiz Eduardo Oliveira e Cruz.</p> <p><strong>Contact:</strong> Ricardo Dalagnol (ricds@hotmail.com)</p> <p> </p> <p><strong>27 Jan 2022 - MANVI v2 was released!</strong> All data were reprocessed and improved. It is advised to re-download the whole series instead of combining v1 and v2. The dataset now covers years 2000-2021.</p> <p><strong>23 May 2019 - MANVI v1 was released.</strong> It covers years 2000-2018.</p> <p> </p> <p><strong>Data:</strong> MODIS (MAIAC) EVI and NDVI indices</p> <p><strong>Scale factor</strong>: 10000</p> <p><strong>Coverage:</strong> South America land</p> <p><strong>Time period:</strong> 2000 to 2021 (starting in 2000, Julian day 64)</p> <p><strong>Spatial resolution:</strong> 1 km</p> <p><strong>Temporal resolution:</strong> 16 days</p> <p><strong>Coordinate reference system:</strong> geographic projection, datum WGS-84</p> <p><strong>Processing details:</strong></p> <ul> <li>The original MODIS (MAIAC) data were described by Lyasputin et al. 2011 (<a href="https://doi.org/10.1029/2010JD014986">https://doi.org/10.1029/2010JD014986</a>). The daily MODIS (MAIAC) surface reflectance data from collection 6, acquired from Terra and Aqua satellites, are available from the MCD19A1 product (<a href="https://ladsweb.modaps.eosdis.nasa.gov/archive/allData/6/MCD19A1">https://ladsweb.modaps.eosdis.nasa.gov/archive/allData/6/MCD19A1</a>). The Bidirectional Reflectance Distribution Function (BRDF) model parameters are available from MCD19A3 product (<a href="https://ladsweb.modaps.eosdis.nasa.gov/archive/allData/6/MCD19A3">https://ladsweb.modaps.eosdis.nasa.gov/archive/allData/6/MCD19A3</a>)</li> <li>The daily MCD19A1 data at 1 km spatial resolution were normalized using the BRDF parameters and Ross-Thick Li-Sparse (RTLS) model considering a fixed nadir view and a 45 deg. solar zenith angle using the parameters from the MCD19A3 product</li> <li>The daily data were aggregated into 16-day composites by the pixel’s median. The 16-day composites always start from Day Of Year (DOY) 016 and end with DOY 352. Therefore, the remaining days from 352 to 365/366 were not used. This procedure was used to facilitate inter-annual comparisons</li> <li>The tiles that cover the South America were mosaicked and re-projected from sinusoidal to geographic projection</li> <li>The Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) were calculated using standard formulas. The EVI parameters were: C1 = 6, C2 = 7.5, L = 1, G = 2.5</li> </ul> <p><strong>File(s) format:</strong></p> <ul> <li>Zip files for EVI and NDVI - one per year: <ul> <li>Inside them there are raster files with ".tif" format, one per 16-day window. The filename syntax is "maiac_southamerica_DATA_YYYYDOY.tif", where YYYY is the year (e.g. 2000), and the DOY is the Julian day of the last day of the composite window, i.e. YYYYDOY for January 2005 for DOY from 001 to 016 is 2005016, from DOY 017 to 032 is 2005032, etc.</li> </ul> </li> <li>Csv files with the YYYYDOY and "real" dates for the time period</li> </ul> <p><strong>Code:</strong> <a href="https://github.com/ricds/maiac_processing">https://github.com/ricds/maiac_processing</a></p> <p><strong>Acknowledgements:</strong> This work was funded by São Paulo Research Foundation – FAPESP, Brazil, grant 2015/22987-7. We thank NASA, and especially Yujie Wang and Alexei Lyapustin, for providing the freely available MODIS (MAIAC) data.</p> <p> </p> <p><strong>Dataset usage</strong>: This dataset is a product of the first author's PhD work and lots of hours of coding and patience. It is free to use, but if you use this dataset in your work, please make sure to properly cite the repository. We also welcome users to invite us for collaboration.</p> <p> </p> <p><strong>For use of this dataset please cite:</strong></p> <p>Dalagnol, Ricardo; Wagner, Fabien Hubert; Galvão, Lênio Soares; Aragão, Luiz Eduardo Oliveira e Cruz. (2022). "The MANVI product: MODIS (MAIAC) nadir-solar adjusted vegetation indices (EVI and NDVI) for South America". (Version v2) [Data set]. Zenodo. <a href="https://doi.org/10.5281/zenodo.3159487">https://doi.org/10.5281/zenodo.3159487</a></p> <p> </p> <p><strong>More information: </strong>contact Ricardo Dalagnol (ricds@hotmail.com). We also have the MODIS (MAIAC) BRDF-corrected bands 1-8, EVI, NDVI at 1 km with 16-day and monthly aggregation composites.</p>
AnisoVeg: Anisotropy and Nadir-normalized MODIS MAIAC datasets for satellite vegetation studies in South America
<p><strong>Dataset paper under review.</strong></p> <p><strong>Contact Ricardo Dalagnol (ricds@hotmail.com) for more information.</strong></p> <p> </p> <p><strong>Data:</strong> AnisoVeg: Anisotropy and Nadir-normalized MODIS MAIAC datasets for satellite vegetation studies in South America</p> <p><strong>Scale factor</strong>: 10000</p> <p><em>obs: the no_samples layer does not have scale.</em></p> <p><strong>Coverage:</strong> South America land</p> <p><strong>Time period:</strong> 2000 to 2021 (starting in March 2000)</p> <p><strong>Spatial resolution:</strong> 0.009107388 degree equivalent to ~1 km</p> <p><strong>Temporal resolution:</strong> Monthly</p> <p><strong>Coordinate reference system:</strong> geographic projection, datum WGS-84</p> <p><strong>Processing details summary (more detailed explanation in the paper):</strong></p> <ul> <li>The original MODIS (MAIAC) data were described by Lyasputin et al. 2011 (<a href="https://doi.org/10.1029/2010JD014986">https://doi.org/10.1029/2010JD014986</a>). The daily MODIS (MAIAC) surface reflectance data from collection 6, acquired from Terra and Aqua satellites, are available from the MCD19A1 product (<a href="https://ladsweb.modaps.eosdis.nasa.gov/archive/allData/6/MCD19A1">https://ladsweb.modaps.eosdis.nasa.gov/archive/allData/6/MCD19A1</a>). The Bidirectional Reflectance Distribution Function (BRDF) model parameters are available from MCD19A3 product (<a href="https://ladsweb.modaps.eosdis.nasa.gov/archive/allData/6/MCD19A3">https://ladsweb.modaps.eosdis.nasa.gov/archive/allData/6/MCD19A3</a>)</li> <li>The daily MCD19A1 data at 1 km spatial resolution were normalized using the BRDF parameters and Ross-Thick Li-Sparse (RTLS) model considering (1) a fixed nadir view and a 45 deg. solar zenith angle using the parameters from the MCD19A3 product; and (2) backward and forward scattering. For the nadir (NAD) product, the nadir normalization was taken. For the anisotropy (ANI) product, we calculated the backward minus forward surfaces for each layer, resulting in the ANI product.</li> <li>The daily data were aggregated into monthly composites by the pixel’s median.</li> <li>The tiles that cover the South America were mosaicked and re-projected from sinusoidal to geographic projection</li> <li>The Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) were calculated using standard formulas. The EVI parameters were: C1 = 6, C2 = 7.5, L = 1, G = 2.5</li> </ul> <p><strong>File(s) format:</strong></p> <ul> <li>Zip files - one per year. NAD are the nadir-normalized products and ANI the anisotropy. Inside zip files there are raster files with ".tif" format, one per month window.</li> <li>The filename syntax is "maiac_southamerica_month_PRODUCT_YYYY_MM_LAYER_latlon.tif", where YYYY is the year (e.g. 2000), MM is the month with two digits (e.g. 03 for March), PRODUCT is either nadir or anisotropy, and LAYER can be bands 1-8, EVI and NDVI.</li> <li>There is also the number of samples (no_samples) layers for each date, which can be used to filter composites with a minimum desirable number of daily observations. </li> </ul> <p> </p> <p><strong>Code:</strong> <a href="https://github.com/ricds/maiac_processing">https://github.com/ricds/maiac_processing</a></p> <p> </p> <p><strong>Acknowledgements:</strong> R.D. was supported by Sao Paulo Research Foundation (FAPESP) grants 2015/22987-7 and 2019/21662-8. FHW was supported by FAPESP grant 2015/50484-0. Part of this work was carried out at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration (NASA). The funders had no role in the study design, data collection and analysis, including the decision to publish or prepare the manuscript. We thank the MODIS MAIAC team from NASA for providing the freely available MODIS (MAIAC) daily dataset.</p> <p> </p> <p><strong>Auxiliary data of AnisoVeg:</strong></p> <ul> <li>Backscattering data of AnisoVeg: <a href="https://doi.org/10.5281/zenodo.6040299">https://doi.org/10.5281/zenodo.6040299</a> and <a href="https://doi.org/10.5281/zenodo.6040790">https://doi.org/10.5281/zenodo.6040790</a></li> <li>Forward scattering data of AnisoVeg: <a href="https://doi.org/10.5281/zenodo.6048784">https://doi.org/10.5281/zenodo.6048784</a> and <a href="https://doi.org/10.5281/zenodo.6048793">https://doi.org/10.5281/zenodo.6048793</a></li> </ul> <p> </p> <p><strong>Layers available at Google Earth Engine (GEE):</strong></p> <ul> <li>EVI Anisotropy: <a href="https://code.earthengine.google.com/?asset=projects/anisoveg/assets/evi_anisotropy">https://code.earthengine.google.com/?asset=projects/anisoveg/assets/evi_anisotropy</a></li> <li>EVI Nadir: <a href="https://code.earthengine.google.com/?asset=projects/anisoveg/assets/evi_nadir">https://code.earthengine.google.com/?asset=projects/anisoveg/assets/evi_nadir</a></li> </ul> <p>Obs: these require a (free) google earth engine account.</p> <p> </p> <p><strong>Dataset usage</strong>: This dataset is a product of hundreds of hours of coding starting in 2016 with the first author PhD work and then into his Postdoc, and many more hundreds hours of data processing. Data is free to use, but if you use this dataset, please cite the dataset paper or this repository (while paper is under review). Invitation for collaboration are welcomed.</p> <ul> </ul> <p> </p> <p><strong>While the paper is under review, for use of this dataset please cite:</strong></p> <p>Dalagnol, Ricardo; Galvão, Lênio Soares; Wagner, Fabien Hubert; Moura, Yhasmin Mendes; Gonçalves, Nathan; Wang, Yujie; Lyapustin, Alexei; Yang, Yan; Saatchi, Sassan; Aragão, Luiz Eduardo Oliveira e Cruz. (2022). "AnisoVeg: Anisotropy and Nadir-normalized MODIS MAIAC datasets for satellite vegetation studies in South America". (Version v1) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.3878879</p>
A novel big data mining framework for reconstructing large-scale daily MAIAC AOD across China from 2000 to 2020
<p>This dataset contains the mean reconstructed MAIAC AOD and mean percentage of coverage of reconstructed MAIAC AOD across China from 2000 to 2020. </p>
Remaining bands of Back scattering data of AnisoVeg: Anisotropy and Nadir-normalized MODIS MAIAC datasets for satellite vegetation studies in South America
<p><strong>Title: Remaining bands of Back scattering data of AnisoVeg: Anisotropy and Nadir-normalized MODIS MAIAC datasets for satellite vegetation studies in South America</strong></p> <p>Ricardo Dalagnol (ricds@hotmail.com)</p> <p> </p> <p><strong>This dataset is associated with the dataset found in the Zenodo repository below and a paper under review. Feel free to use this dataset, but please cite the repository below (while the paper is under review).</strong></p> <p>Dalagnol, Ricardo; Galvão, Lênio Soares; Wagner, Fabien Hubert; Moura, Yhasmin Mendes; Gonçalves, Nathan; Wang, Yujie; Lyapustin, Alexei; Yang, Yan; Saatchi, Sassan; Aragão, Luiz Eduardo Oliveira e Cruz. (2022). "AnisoVeg: Anisotropy and Nadir-normalized MODIS MAIAC datasets for satellite vegetation studies in South America". (Version v1) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.3878879</p>
Back scattering data of AnisoVeg: Anisotropy and Nadir-normalized MODIS MAIAC datasets for satellite vegetation studies in South America
<p><strong>Title: Back scattering data of AnisoVeg: Anisotropy and Nadir-normalized MODIS MAIAC datasets for satellite vegetation studies in South America</strong></p> <p>Ricardo Dalagnol (ricds@hotmail.com)</p> <p> </p> <p><strong>This dataset is associated with the dataset found in the Zenodo repository below and a paper under review. Feel free to use this dataset, but please cite the repository below (while the paper is under review).</strong></p> <p>Dalagnol, Ricardo; Galvão, Lênio Soares; Wagner, Fabien Hubert; Moura, Yhasmin Mendes; Gonçalves, Nathan; Wang, Yujie; Lyapustin, Alexei; Yang, Yan; Saatchi, Sassan; Aragão, Luiz Eduardo Oliveira e Cruz. (2022). "AnisoVeg: Anisotropy and Nadir-normalized MODIS MAIAC datasets for satellite vegetation studies in South America". (Version v1) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.3878879</p>
Remaining bands of Forward scattering data of AnisoVeg: Anisotropy and Nadir-normalized MODIS MAIAC datasets for satellite vegetation studies in South America
<p><strong>Title: Remaining bands of Forward scattering data of AnisoVeg: Anisotropy and Nadir-normalized MODIS MAIAC datasets for satellite vegetation studies in South America</strong></p> <p>Ricardo Dalagnol (ricds@hotmail.com)</p> <p> </p> <p><strong>This dataset is associated with the dataset found in the Zenodo repository below and a paper under review. Feel free to use this dataset, but please cite the repository below (while the paper is under review).</strong></p> <p>Dalagnol, Ricardo; Galvão, Lênio Soares; Wagner, Fabien Hubert; Moura, Yhasmin Mendes; Gonçalves, Nathan; Wang, Yujie; Lyapustin, Alexei; Yang, Yan; Saatchi, Sassan; Aragão, Luiz Eduardo Oliveira e Cruz. (2022). "AnisoVeg: Anisotropy and Nadir-normalized MODIS MAIAC datasets for satellite vegetation studies in South America". (Version v1) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.3878879</p>
Forward scattering data of AnisoVeg: Anisotropy and Nadir-normalized MODIS MAIAC datasets for satellite vegetation studies in South America
<p><strong>Title: Forward scattering data of AnisoVeg: Anisotropy and Nadir-normalized MODIS MAIAC datasets for satellite vegetation studies in South America</strong></p> <p>Ricardo Dalagnol (ricds@hotmail.com)</p> <p> </p> <p><strong>This dataset is associated with the dataset found in the Zenodo repository below and a paper under review. Feel free to use this dataset, but please cite the repository below (while the paper is under review).</strong></p> <p>Dalagnol, Ricardo; Galvão, Lênio Soares; Wagner, Fabien Hubert; Moura, Yhasmin Mendes; Gonçalves, Nathan; Wang, Yujie; Lyapustin, Alexei; Yang, Yan; Saatchi, Sassan; Aragão, Luiz Eduardo Oliveira e Cruz. (2022). "AnisoVeg: Anisotropy and Nadir-normalized MODIS MAIAC datasets for satellite vegetation studies in South America". (Version v1) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.3878879</p>
DSCOVR EPIC L2 Multi-Angle Implementation of Atmospheric Correction (MAIAC) Version 02
DSCOVR_EPIC_L2_MAIAC_02 is the DSCOVR EPIC L2 Multi-Angle Implementation of Atmospheric Correction (MAIAC) Version 02 data product. Data collection for this product is ongoing. Level 2 Multi-Angle Implementation of Atmospheric Correction (MAIAC) provides an interdisciplinary suite of products for the Deep Space Climate Observatory (DSCOVR) Earth Polychromatic Imaging Camera (EPIC). The current version 2 reports the following products: a) Atmosphere: cloud mask, global aerosol optical depth at 443nm and 551nm, fine mode fraction (over ocean) and spectral aerosol absorption for detected biomass burning or mineral dust aerosols. The absorption information includes single scattering albedo at 443nm, imaginary refractive index at 680nm, and Absorption Angstrom Exponent (AAE) characterizing spectral increase of imaginary refractive index at Vis-UV wavelengths. The absorption information is provided for two effective aerosol layer heights of 1km and 4km generally representing boundary layer and transport mode. b) Land: atmospherically corrected spectral bidirectional reflectance factors (BRF) along with Lambertian surface reflectance, and bidirectional reflectance distribution function (BRDF) for the backscattering view geometries of EPIC. The BRDF is represented by 3 parameters of the Ross-Thick Li-Sparse model. c) Ocean: Water leaving reflectance (non-dimensional) at Ultraviolet-Visible (UV-Vis) bands.The parameters are distributed at 10 km rotated sinusoidal grid and 1 to 2-hour temporal frequency. MAIAC version 02 also provides gap-filled global composite products for Normalized Difference Vegetation Index (NDVI) over land, and water leaving reflectance in 5 UV-Vis bands over global ocean. The composite products represent a weighted running average where the weight of the latest observation is maximized towards the local noon and low aerosol conditions.
ABoVE: Light-Curve Modelling of Gridded GPP Using MODIS MAIAC and Flux Tower Data
This dataset contains gridded estimations of daily ecosystem Gross Primary Production (GPP) in grams of carbon per day at a 1 km2 spatial resolution over Alaska and Canada from 2000-01-01 to 2018-01-01. Daily estimates of GPP were derived from a light-curve model that was fitted and validated over a network of ABoVE domain Ameriflux flux towers then upscaled using MODIS Multi-Angle Implementation of Atmospheric Correction (MAIAC) data to span the extended ABoVE domain. In general, the methods involved three steps; the first step involved collecting and processing mainly carbon-flux site-level data, the second step involved the analysis and correction of site-level MAIAC data, and the final step developed a framework to produce large-scale estimates of GPP. The light-curve parameter model was generated by upscaling from flux tower sub-daily temporal resolution by deconvolving the GPP variable into 3 components: the absorbed photosynthetically active radiation (aPAR), the maximum GPP or maximum photosynthetic capacity (GPPmax), and the photosynthetic limitation or amount of light needed to reach maximum capacity (PPFDmax). GPPmax and PPFDmax were related to satellite reflectance measurements sampled at the daily scale. GPP over the extended ABoVE domain was estimated at a daily resolution from the light-curve parameter model using MODIS MAIAC daily reflectance as input. This framework allows large-scale estimates of phenology and evaluation of ecosystem sensitivity to climate change.
MAIAC Daily V01
DSOCVR EPIC_L2 MAIAC-Daily_01 contains plots of data generated from DSCOVR_EPIC_L2_MAIAC_03, the DSCOVR EPIC L2 Multi-Angle Implementation of Atmospheric Correction (MAIAC) Version 03 data product. Data collection for this product is ongoing.The datasets visualized include Aerosol Layer Height (ALH), Aerosol Optical Depth, and Single Scattering Albedo at 340nm, 388nm, 443nm, 551 nm, 680nm, and 780nm.Level 2 Multi-Angle Implementation of Atmospheric Correction (MAIAC) provides an interdisciplinary suite of products for the Deep Space Climate Observatory (DSCOVR) Earth Polychromatic Imaging Camera (EPIC). The current version 3 reports the following products:a) Atmosphere: cloud mask, global aerosol optical depth at 443nm and 551nm, fine mode fraction (over the ocean), aerosol layer height (ALH) globally, and spectral aerosol absorption for detected biomass burning or mineral dust aerosols. The absorption information includes single scattering albedo at 340-780nm range, imaginary refractive index at 680nm (k0), and Spectral Absorption Exponent (SAE) characterizing spectral increase of imaginary refractive index from Red towards UV wavelengths. The aerosol optical properties {AOD, ALH, k0, SAE} are retrieved simultaneously by matching EPIC measurements in the UV-NIR range, including atmospheric oxygen A- and B-bands.b) Land: atmospherically corrected spectral bidirectional reflectance factors (BRF) along with Lambertian surface reflectance and bidirectional reflectance distribution function (BRDF) for the backscattering view geometries of EPIC. The BRDF is represented by three parameters of the Ross-Thick Li-Sparse model.c) Ocean: Water leaving reflectance (non-dimensional) at Ultraviolet-Visible (UV-Vis) bands.The parameters are provided at 10 km resolution on a zonal sinusoidal grid with a 1—to 2-hour temporal frequency. MAIAC version 03 also provides gap-filled global composite products for the Normalized Difference Vegetation Index (NDVI) over land and water, leaving reflectance in 5 UV-Vis bands over the global ocean. The composite products represent a weighted running average where the weight of the latest observation is maximized towards the local noon and low aerosol conditions.
MODIS/Terra+Aqua Surface Reflectance (Bands 8-12) from MAIAC, Daily L3 Global 0.05Deg CMG V061
The MCD19A1CMGO Version 6.1 data product is a Moderate Resolution Imaging Spectroradiometer (MODIS) Terra and Aqua combined Multi-Angle Implementation of Atmospheric Correction (MAIAC) Surface Reflectance Level 3 (Bands 8-12) product produced daily in a 0.05 degree (5,600 meters at the equator) Climate Modeling Grid (CMG). The MCD19A1CMGO product is corrected for atmospheric gases and aerosols using a new MAIAC algorithm that is based on a time series analysis and a combination of pixel- and image-based processing. The MODIS MAIAC products provide an estimate of the surface spectral reflectance, also referred to as Bidirectional Reflectance Factor (BRF), as it would be measured at ground-level in the absence of atmospheric scattering or absorption. The Surface Reflectance dataset includes BRF, BRF normalized to a fixed geometry of solar zenith angle at 45° and nadir view, and Nadir Bidirectional Reflectance Distribution Function (BRDF)-Adjusted Reflectance (NBAR) normalized to the nadir view and local sun angle at 1:30 pm.The MCD19A1CMGO MAIAC Surface Reflectance product for ocean bands includes 19 Science Dataset (SDS) layers: BRF for bands 8-12, BRF normalized to a fixed geometry for bands 8-12, NBAR for bands 8-12, Quality Assessment (QA) bits, cosine of solar zenith angle, cosine of view zenith angle, and relative azimuth angle. A low-resolution browse is also included.Known Issues* Known issues are described in Section 6 of the User Guide.* For complete information about known issues please refer to the [MODIS/VIIRS Land Quality Assessment website](https://landweb.modaps.eosdis.nasa.gov/knownissue?sensor=MODIS&sat=TerraAqua&as=61).
MODIS/Terra+Aqua Surface Reflectance (Bands 1-7) from MAIAC, Daily L3 Global 0.05Deg CMG V061
The MCD19A1CMGL Version 6.1 data product is a Moderate Resolution Imaging Spectroradiometer (MODIS) Terra and Aqua combined Multi-Angle Implementation of Atmospheric Correction (MAIAC) Surface Reflectance Level 3 (Bands 1-7) product produced daily in a 0.05 degree (5,600 meters at the equator) Climate Modeling Grid (CMG). The MCD19A1CMGL product is corrected for atmospheric gases and aerosols using a new MAIAC algorithm that is based on a time series analysis and a combination of pixel- and image-based processing. The MODIS MAIAC products provide an estimate of the surface spectral reflectance, also referred to as Bidirectional Reflectance Factor (BRF), as it would be measured at ground-level in the absence of atmospheric scattering or absorption. The Surface Reflectance dataset includes BRF, BRF normalized to a fixed geometry of solar zenith angle at 45° and nadir view, and Nadir Bidirectional Reflectance Distribution Function (BRDF)-Adjusted Reflectance (NBAR) normalized to the nadir view and local sun angle at 1:30 pm.The MCD19A1CMGL MAIAC Surface Reflectance product for land bands includes 25 Science Dataset (SDS) layers: BRF for bands 1-7, BRF normalized to a fixed geometry for bands 1-7, NBAR for bands 1-7, Quality Assessment (QA) bits, cosine of solar zenith angle, cosine of view zenith angle, and relative azimuth angle. A low-resolution browse is also included.Known Issues* Known issues are described in Section 6 of the User Guide.* For complete information about known issues please refer to the [MODIS/VIIRS Land Quality Assessment website](https://landweb.modaps.eosdis.nasa.gov/knownissue?sensor=MODIS&sat=TerraAqua&as=61).
MODIS/Terra+Aqua AOD and Water Vapor from MAIAC, Daily L3 Global 0.05Deg CMG V061
The MCD19A2CMG Version 6.1 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) and Water Vapor Level 3 product produced daily in a 0.05 degree (5,600 meters at the equator) Climate Modeling Grid (CMG). The MCD19A2CMG product provides the atmospheric properties and view geometry used to calculate the MAIAC Surface Reflectance data products ([MCD19A1CMGL](https://doi.org/10.5067/MODIS/MCD19A1CMGL.061) and [MCD19A1CMGO](https://doi.org/10.5067/MODIS/MCD19A1CMGO.061)). The MCD19A2CMG 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, column water vapor for Terra, column water vapor for Aqua, average cloud fraction, available AOD, satellite overpass times, line and sample number, offset, and number of AOD records. 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. Known Issues* Known issues are described in Section 6 of the User Guide.* For complete information about known issues please refer to the [MODIS/VIIRS Land Quality Assessment website](https://landweb.modaps.eosdis.nasa.gov/knownissue?sensor=MODIS&sat=TerraAqua&as=61).
MODIS/Terra+Aqua Vegetation Index from MAIAC, Daily L3 Global 0.05Deg CMG V061
The MCD19A3CMG Version 6.1 data product is a Moderate Resolution Imaging Spectroradiometer (MODIS) Terra and Aqua combined Multi-Angle Implementation of Atmospheric Correction (MAIAC) Vegetation Index Level 3 product produced daily in a 0.05 degree (5,600 meters at the equator) Climate Modeling Grid (CMG). The MCD19A3CMG product provides Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) at ground level in the absence of atmospheric scattering or absorption. The MCD19A3CMG Vegetation Index data product contains the following Science Dataset (SDS) layers: NDVI, NDVI normalized to a fixed geometry of solar zenith angle at 45° and nadir view, gap-filled NDVI, EVI, and EVI normalized to a fixed geometry of solar zenith angle at 45° and nadir view. A low-resolution browse image is also included showing NDVI created using a composite of all available orbits. Known Issues* Known issues are described in Section 6 of the User Guide. * An artifact was discovered in the EVI, NDVI, and NDVI_gapfill layers over the entire swath of southern polar region. The affected region shows false retrieval of data during the summer months. The artifacts occurred over permanently snow-covered areas where no meaningful NDVI retrieval is expected. A software fix was implemented for forward processing in June 2023. Existing data products will not be reprocessed. Affected dates are listed on the [Land Data Operational Products Evaluation Quality Assessment note](https://landweb.modaps.eosdis.nasa.gov/displayissue?id=187).* For complete information about known issues please refer to the [MODIS/VIIRS Land Quality Assessment website](https://landweb.modaps.eosdis.nasa.gov/knownissue?sensor=MODIS&sat=TerraAqua&as=61).
ABoVE: Corrected MODIS MAIAC Reflectance at Tower Sites, Alaska and Canada, 2000-2016
This dataset provides angular corrections of MODIS Multi-Angle Implementation of Atmospheric Correction algorithm (MAIAC) surface reflectances by two methods at each of 62 flux tower sites (1 km x 1 km area) across the ABoVE domain in Alaska and western Canada from 2000 to 2015/2016. The original MAIAC reflectance data were corrected to consistent view and illumination angles (0 degree view zenith angle and 45 degree of sun zenith angle) using two independent algorithms: the first based on the original BRDF (Bidirectional Reflectance Distribution Function) parameters provided by the MAIAC team, and the second based on a machine learning approach (random forests). The corrected data preserve the original MAIAC data's sub-daily temporal resolution and 1 km spatial resolution with seven land bands (bands 1-7) and five ocean bands (bands 8-12). The resulting tower site sub-daily timeseries of angular corrected surface reflectances are suitable for long-term studies on patterns, processes, and dynamics of surface phenomena.
ABoVE: Angular-corrected MODIS MAIAC Reflectance across Alaska and Canada, 2000-2017
This dataset provides angular corrections of MODIS Multi-Angle Implementation of Atmospheric Correction algorithm (MAIAC) surface reflectances across the ABoVE domain in Alaska and western Canada from 2000 to 2017. Using random forests (RF), a machine-learning approach, the original MAIAC reflectance data were corrected to consistent view and illumination angles (0 degree view zenith angle and 45 degree of sun zenith angle) to reduce artifacts and variability due to angular effects. The original MAIAC data's sub-daily temporal resolution and 1 km spatial resolution with seven land bands (bands 1-7) and five ocean bands (bands 8-12) were preserved. The resulting surface reflectance data are suitable for long-term studies on patterns, processes, and dynamics of surface phenomena. The data cover 11 different Terra and Aqua satellite MODIS MAIAC tiles.
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Allen Brain Atlas
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