Land Remote Sensing and Global Environmental Change

Ramachandran, Bhaskar; Justice, Christopher O.; Abrams, Michael J.

doi:10.1007/978-1-4419-6749-7

Cited by 69 publications

(12 citation statements)

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“…Additionally, at each fire point, the MODIS Vegetation Continuous Fields (VCF) product (Collection 3 for 2001) is used to identify the density of the vegetation at each active fire location. The VCF product identifies the percent tree, non-tree vegetation, and bare cover at 500 m resolution (Hansen et al, 2003(Hansen et al, , 2005Carroll et al, 2011). The VCF data are scaled to 1 km spatial resolution to match the fire detection and LCT datasets.…”

Section: Model Descriptionmentioning

confidence: 99%

The Fire INventory from NCAR (FINN): a high resolution global model to estimate the emissions from open burning

et al. 2011

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Abstract. The Fire INventory from NCAR version 1.0 (FINNv1) provides daily, 1 km resolution, global estimates of the trace gas and particle emissions from open burning of biomass, which includes wildfire, agricultural fires, and prescribed burning and does not include biofuel use and trash burning. Emission factors used in the calculations have been updated with recent data, particularly for the non-methane organic compounds (NMOC). The resulting global annual NMOC emission estimates are as much as a factor of 5 greater than some prior estimates. Chemical speciation profiles, necessary to allocate the total NMOC emission estimates to lumped species for use by chemical transport models, are provided for three widely used chemical mechanisms: SAPRC99, GEOS-CHEM, and MOZART-4. Using these profiles, FINNv1 also provides global estimates of key organic compounds, including formaldehyde and methanol. Uncertainties in the emissions estimates arise from several of the method steps. The use of fire hot spots, assumed area burned, land cover maps, biomass consumption estimates, and emission factors all introduce error into the model estimates. The uncertainty in the FINNv1 emission estimates are about a factor of two; but, the global estimates agree reasonably well with other global inventories of biomass burning emissions for CO, CO 2 , and other species with less variable emission factors. FINNv1 emission estimates have been developed specifically for modeling atmospheric chemistry and air quality in a consistent framework at scales from local to global. The product is unique because of the high temporalCorrespondence to: C. Wiedinmyer (christin@ucar.edu) and spatial resolution, global coverage, and the number of species estimated. FINNv1 can be used for both hindcast and forecast or near-real time model applications and the results are being critically evaluated with models and observations whenever possible.

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Section: Model Descriptionmentioning

confidence: 99%

The Fire INventory from NCAR (FINN): a high resolution global model to estimate the emissions from open burning

et al. 2011

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“…These data are from the Terra and Aqua MODIS fire and thermal anomalies data provided from the official NASA MCD14ML product, Collection 5, version 1 (Giglio et al, 2003). Land cover and vegetation density was determined with the MODIS Land Cover Type product (Friedl et al, 2010) and the MODIS Vegetation Continuous Fields product (Collection 3 for 2001) (Hansen et al, 2003(Hansen et al, , 2005Carroll et al, 2011), and fuel loadings from Hoelzemann et al (2004) and Akagi et al (2011). Emission factors for mercury emissions were provided by Wiedinmyer and Friedli (2007).…”

Section: Forest Firesmentioning

confidence: 99%

Estimation of mercury emissions from forest fires, lakes, regional and local sources using measurements in Milwaukee and an inverse method

2012

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Abstract. Gaseous elemental mercury is a global pollutant that can lead to serious health concerns via deposition to the biosphere and bio-accumulation in the food chain. Hourly measurements between June 2004 and May 2005 in an urban site (Milwaukee, WI) show elevated levels of mercury in the atmosphere with numerous short-lived peaks as well as longer-lived episodes. The measurements are analyzed with an inverse model to obtain information about mercury emissions. The model is based on high resolution meteorological simulations (WRF), hourly back-trajectories (WRF-FLEXPART) and a chemical transport model (CAMx). The hybrid formulation combining back-trajectories and Eulerian simulations is used to identify potential source regions as well as the impacts of forest fires and lake surface emissions. Uncertainty bounds are estimated using a bootstrap method on the inversions. Comparison with the US Environmental Protection Agency's National Emission Inventory (NEI) and Toxic Release Inventory (TRI) shows that emissions from coal-fired power plants are properly characterized, but emissions from local urban sources, waste incineration and metal processing could be significantly under-estimated. Emissions from the lake surface and from forest fires were found to have significant impacts on mercury levels in Milwaukee, and to be underestimated by a factor of two or more.

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“…Up-to-date land cover and change information is required by resource managers and decision-makers at regional, national, or global level to support the development and implementation of policies, and to meet mandatory reporting requirements resulting from those policies (Townshend et al, 2011). Within forest environments, information to support forest inventories has historically relied on the interpretation of aerial images and forest plot data, providing a mix of cost effectiveness and information content typically required to support forest management activities at the strategic level.…”

Section: Introductionmentioning

confidence: 99%

An integrated Landsat time series protocol for change detection and generation of annual gap-free surface reflectance composites

Hermosilla

Wulder

White

et al. 2015

Remote Sensing of Environment

266

130

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Land Remote Sensing and Global Environmental Change

Cited by 69 publications

References 0 publications

The Fire INventory from NCAR (FINN): a high resolution global model to estimate the emissions from open burning

The Fire INventory from NCAR (FINN): a high resolution global model to estimate the emissions from open burning

Estimation of mercury emissions from forest fires, lakes, regional and local sources using measurements in Milwaukee and an inverse method

An integrated Landsat time series protocol for change detection and generation of annual gap-free surface reflectance composites

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