Calibration of a Species-Specific Spectral Vegetation Index for Leaf Area Index (LAI) Monitoring: Example with MODIS Reflectance Time-Series on Eucalyptus Plantations

The leaf area index (LAI) is a key characteristic of forest ecosystems. Estimations of LAI from satellite images generally rely on spectral vegetation indices (SVIs) or radiative transfer model (RTM) inversions. We have developed a new and precise method suitable for practical application, consisting of building a species-specific SVI that is best-suited to both sensor and vegetation characteristics. Such an SVI requires calibration on a large number of representative vegetation conditions. We developed a two-step approach: (1) estimation of LAI on a subset of satellite data through RTM inversion; and (2) the calibration of a vegetation index on these estimated LAI. We applied this methodology to Eucalyptus plantations which have highly variable LAI in time and space. Previous results showed that an RTM inversion of Moderate Resolution Imaging Spectroradiometer (MODIS) near-infrared and red reflectance allowed good retrieval performance (R-2 = 0.80, RMSE = 0.41), but was computationally difficult. Here, the RTM results were used to calibrate a dedicated vegetation index (called "EucVI") which gave similar LAI retrieval results but in a simpler way. The R-2 of the regression between measured and EucVI-simulated LAI values on a validation dataset was 0.68, and the RMSE was 0.49. The additional use of stand age and day of year in the SVI equation slightly increased the performance of the index (R-2 = 0.77 and RMSE = 0.41). This simple index opens the way to an easily applicable retrieval of Eucalyptus LAI from MODIS data, which could be used in an operational way.

A MODIS-Based Energy Balance to Estimate Evapotranspiration for Clear-Sky Days in Brazilian Tropical Savannas

Evapotranspiration (ET) plays an important role in global climate dynamics and in primary production of terrestrial ecosystems; it represents the mass and energy transfer from the land to atmosphere. Limitations to measuring ET at large scales using ground-based methods have motivated the development of satellite remote sensing techniques. The purpose of this work is to evaluate the accuracy of the SEBAL algorithm for estimating surface turbulent heat fluxes at regional scale, using 28 images from MODIS. SEBAL estimates are compared with eddy-covariance (EC) measurements and results from the hydrological model MGB-IPH. SEBAL instantaneous estimates of latent heat flux (LE) yielded r(2) = 0.64 and r(2) = 0.62 over sugarcane croplands and savannas when compared against in situ EC estimates. At the same sites, daily aggregated estimates of LE were r(2) = 0.76 and r(2) = 0.66, respectively. Energy balance closure showed that turbulent fluxes over sugarcane croplands were underestimated by 7% and 9% over savannas. Average daily ET from SEBAL is in close agreement with estimates from the hydrological model for an overlay of 38,100 km(2) (r(2) = 0.88). Inputs to which the algorithm is most sensitive are vegetation index (NDVI), gradient of temperature (dT) to compute sensible heat flux (H) and net radiation (Re). It was verified that SEBAL has a tendency to overestimate results both at local and regional scales probably because of low sensitivity to soil moisture and water stress. Nevertheless the results confirm the potential of the SEBAL algorithm, when used with MODIS images for estimating instantaneous LE and daily ET from large areas.

Recent shift from forest to savanna burning in the Amazon Basin observed by satellite

The numbers of fires detected on forest, savanna and transition lands during the 2002-10 biomass burning seasons in Amazonia are shown using fire count data and co-located land cover classifications from the Moderate Resolution Imaging Spectroradiometer (MODIS). The ratio of forest fires to savanna fires has varied substantially over the study period, with a maximum ratio of 0.65:1 in 2005 and a minimum ratio of 0.27:1 in 2009, with the four lowest years occurring in 2007-10. The burning during the droughts of 2007 and 2010 is attributed to a higher number of savanna fires relative to the drought of 2005. A decrease in the regional mean single scattering albedo of biomass burning aerosols, consistent with the shift from forest to savanna burning, is also shown. During the severe drought of 2010, forest fire detections were lower in many areas compared with 2005, even though the drought was more severe in 2010. This result suggests that improved fire management practices, including stricter burning regulations as well as lower deforestation burning, may have reduced forest fires in 2010 relative to 2005 in some areas of the Amazon Basin.

Aerosols in Amazonia: Natural Biogenic Particles and Large Scale Biomass Burning Impacts.

The Large Scale Biosphere Atmosphere Experiment in Amazonia (LBA) is a long term (20 years) research effort aimed at the understanding of the functioning of the Amazonian ecosystem. In particular, the strong biosphere-atmosphere interaction is a key component looking at the exchange processes between vegetation and the atmosphere, focusing on aerosol particles. Two aerosol components are the most visible: The natural biogenic emissions of aerosols and VOCs, and the biomass burning emissions. A large effort was done to characterize natural biogenic aerosols that showed detailed organic characterization and optical properties. The biomass burning component in Amazonia is important in term of aerosol and trace gases emissions, with deforestation rates decreasing, from 27,000 Km2 in 2004 to about 5,000 Km2 in 2011. Biomass burning emissions in Amazonia increases concentrations of aerosol particles, CO, ozone and other species, and also change the surface radiation balance in a significant way. Long term monitoring of aerosols and trace gases were performed in two sites: a background site in Central Amazonia, 55 Km North of Manaus (called ZF2 ecological reservation) and a monitoring station in Porto Velho, Rondonia state, a site heavily impacted by biomass burning smoke. Several instruments were operated to measured aerosol size distribution, optical properties (absorption and scattering at several wavelengths), composition of organic (OC/EC) and inorganic components among other measurements. AERONET and MODIS measurements from 5 long term sites show a large year-to year variability due to climatic and socio-economic issues. Aerosol optical depths of more than 4 at 550nm was observed frequently over biomass burning areas. In the pristine Amazonian atmosphere, aerosol scattering coefficients ranged between 1 and 200 Mm-1 at 450 nm, while absorption ranged between 1 and 20 Mm-1 at 637 nm. A strong seasonal behavior was observed, with greater aerosol loadings during the dry season (Jul-Nov) as compared to the wet season (Dec-Jun). During the wet season in Manaus, aerosol scattering (450 nm) and absorption (637 nm) coefficients averaged, respectively, 14 and 0.9 Mm-1. Angstrom exponents for scattering were lower during the wet season (1.6) in comparison to the dry season (1.9), which is consistent with the shift from biomass burning aerosols, predominant in the fine mode, to biogenic aerosols, predominant in the coarse mode. Single scattering albedo, calculated at 637 nm, did not show a significant seasonal variation, averaging 0.86. In Porto Velho, even in the wet season it was possible to observe an impact from anthropogenic aerosol. Black Carbon was measured at a high 20 ug/m³ in the dry season, showing strong aerosol absorption. This work presents a general description of the aerosol optical properties in Amazonia, both during the Amazonian wet and dry seasons.

Heat island simulations in Londrina city, Brazil

This work aims to study the urban heat island on North region of Parana state, Brazil and the influence of land use and urban settlements on the intensity and frequency of occurrence of these events. Through atmospheric modeling whith WRF/Chem model two simulations were made with different land and use files, one with the original land use another obtained from a composition of MODIS-Landsat imagery. The simulations showed good skills compared to observed data. Urban areas presented higher temperatures. Landsat land use has represented better urban heat islands (UHI), the gradient between urban and rural areas was well demonstrated and the correlation coefficient was above 0.92. The model underestimated the maximum values and overestimated the minimum compared with observed data in both simulations.

Air quality simulations for Londrina region, Brazil

The objective of this work were apply and provide a preliminary evaluation of the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) performance, for Londrina region. We performed comparison with measurements obtained in meteorological stations. The model was configured to run with three domains with 27,9 and 3 km of grid resolution, using the ndown program and also was realized a simulation with the model configured to run with a single domain using a land use file based in a classified image for region of MODIS sensor. The emission files to supply the chemistry run were generated based in the work of Martins et al., 2012. RADM2 chemical mechanism and MADE/SORGAM modal aerosol models were used in the simulations. The results demonstrated that model was able to represent coherently the formation and dispersion of the pollution in Metropolitan Region of Londrina and also the importance of using the appropriate land use file for the region.