311 resultados para MODIS


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Since 1999, the National Commission for the Knowledge and Use of the Biodiversity (CONABIO) in Mexico has been developing and managing the “Operational program for the detection of hot-spots using remote sensing techniques”. This program uses images from the MODerate resolution Imaging Spectroradiometer (MODIS) onboard the Terra and Aqua satellites and from the Advanced Very High Resolution Radiometer of the National Oceanic and Atmospheric Administration (NOAA-AVHRR), which are operationally received through the Direct Readout station (DR) at CONABIO. This allows the near-real time monitoring of fire events in Mexico and Central America. In addition to the detection of active fires, the location of hot spots are classified with respect to vegetation types, accessibility, and risk to Nature Protection Areas (NPA). Besides the fast detection of fires, further analysis is necessary due to the considerable effects of forest fires on biodiversity and human life. This fire impact assessment is crucial to support the needs of resource managers and policy makers for adequate fire recovery and restoration actions. CONABIO attempts to meet these requirements, providing post-fire assessment products as part of the management system in particular for satellite-based burnt area mapping. This paper provides an overview of the main components of the operational system and will present an outlook to future activities and system improvements, especially the development of a burnt area product. A special focus will also be placed on the fire occurrence within NPAs of Mexico

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Accurate knowledge of ice-production rates within the marginal ice zones of the Arctic Ocean requires monitoring of the thin-ice distribution within polynyas. The thickness of the ice layer controls the heat loss and hence the new-ice formation. An established thinice algorithm using high-resolution MODIS data allows deriving the ice-thickness distribution within polynyas. The average uncertainty is ±4.7 cm for ice thicknesses below 0.2 m. In this study, the ice-thickness distributions within the Laptev Sea polynya for the two winter seasons 2007/08 and 2008/09 are calculated. Then, a new method is applied to determine a daily MODIS thin-ice product.

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This paper presents an analysis of ground-based Aerosol Optical Depth (AOD) observations by the Aerosol Robotic Network (AERONET) in South America from 2001 to 2007 in comparison with the satellite AOD product of Moderate Resolution Imaging Spectroradiometer (MODIS), aboard TERRA and AQUA satellites. Data of 12 observation sites were used with primary interest in AERONET sites located in or downwind of areas with high biomass burning activity and with measurements available for the full time range. Fires cause the predominant carbonaceous aerosol emission signal during the dry season in South America and are therefore a special focus of this study. Interannual and seasonal behavior of the observed AOD at different sites were investigated, showing clear differences between purely fire and urban influenced sites. An intercomparison of AERONET and MODIS AOD annual correlations revealed that neither an interannual long-term trend may be observed nor that correlations differ significantly owing to different overpass times of TERRA and AQUA. Individual anisotropic representativity areas for each AERONET site were derived by correlating daily AOD of each site for all years with available individual MODIS AOD pixels gridded to 1 degrees x 1 degrees. Results showed that for many sites a good AOD correlation (R(2) > 0.5) persists for large, often strongly anisotropic, areas. The climatological areas of common regional aerosol regimes often extend over several hundreds of kilometers, sometimes far across national boundaries. As a practical application, these strongly inhomogeneous and anisotropic areas of influence are being implemented in the tropospheric aerosol data assimilation system of the Coupled Chemistry-Aerosol-Tracer Transport Model coupled to the Brazilian Regional Atmospheric Modeling System (CCATT-BRAMS) at the Brazilian National Institute for Space Research (INPE). This new information promises an improved exploitation of local site sampling and, thus, chemical weather forecast.

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[1] The retrieval of aerosol optical depth (Ta) over land by satellite remote sensing is still a challenge when a high spatial resolution is required. This study presents a tool that uses satellite measurements to dynamically identify the aerosol optical model that best represents the optical properties of the aerosol present in the atmosphere. We use aerosol critical reflectance to identify the single scattering albedo of the aerosol layer. Two case studies show that the Sao Paulo region can have different aerosol properties and demonstrates how the dynamic methodology works to identify those differences to obtain a better T a retrieval. The methodology assigned the high single scattering albedo aerosol model (pi o( lambda = 0.55) = 0.90) to the case where the aerosol source was dominated by biomass burning and the lower pi(o) model (pi(o) (lambda = 0.55) = 0.85) to the case where the local urban aerosol had the dominant influence on the region, as expected. The dynamic methodology was applied using cloud-free data from 2002 to 2005 in order to retrieve Ta with Moderate Resolution Imaging Spectroradiometer ( MODIS). These results were compared with collocated data measured by AERONET in Sao Paulo. The comparison shows better results when the dynamic methodology using two aerosol optical models is applied (slope 1.06 +/- 0.08 offset 0.01 +/- 0.02 r(2) 0.6) than when a single and fixed aerosol model is used (slope 1.48 +/- 0.11 and offset - 0.03 +/- 0.03 r(2) 0.6). In conclusion the dynamical methodology is shown to work well with two aerosol models. Further studies are necessary to evaluate the methodology in other regions and under different conditions.

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This study includes the results of the analysis of areas susceptible to degradation by remote sensing in semi-arid region, which is a matter of concern and affects the whole population and the catalyst of this process occurs by the deforestation of the savanna and improper practices by the use of soil. The objective of this research is to use biophysical parameters of the MODIS / Terra and images TM/Landsat-5 to determine areas susceptible to degradation in semi-arid Paraiba. The study area is located in the central interior of Paraíba, in the sub-basin of the River Taperoá, with average annual rainfall below 400 mm and average annual temperature of 28 ° C. To draw up the map of vegetation were used TM/Landsat-5 images, specifically, the composition 5R4G3B colored, commonly used for mapping land use. This map was produced by unsupervised classification by maximum likelihood. The legend corresponds to the following targets: savanna vegetation sparse and dense, riparian vegetation and exposed soil. The biophysical parameters used in the MODIS were emissivity, albedo and vegetation index for NDVI (NDVI). The GIS computer programs used were Modis Reprojections Tools and System Information Processing Georeferenced (SPRING), which was set up and worked the bank of information from sensors MODIS and TM and ArcGIS software for making maps more customizable. Initially, we evaluated the behavior of the vegetation emissivity by adapting equation Bastiaanssen on NDVI for spatialize emissivity and observe changes during the year 2006. The albedo was used to view your percentage of increase in the periods December 2003 and 2004. The image sensor of Landsat TM were used for the month of December 2005, according to the availability of images and in periods of low emissivity. For these applications were made in language programs for GIS Algebraic Space (LEGAL), which is a routine programming SPRING, which allows you to perform various types of algebras of spatial data and maps. For the detection of areas susceptible to environmental degradation took into account the behavior of the emissivity of the savanna that showed seasonal coinciding with the rainy season, reaching a maximum emissivity in the months April to July and in the remaining months of a low emissivity . With the images of the albedo of December 2003 and 2004, it was verified the percentage increase, which allowed the generation of two distinct classes: areas with increased variation percentage of 1 to 11.6% and the percentage change in areas with less than 1 % albedo. It was then possible to generate the map of susceptibility to environmental degradation, with the intersection of the class of exposed soil with varying percentage of the albedo, resulting in classes susceptibility to environmental degradation

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The municipality of Petrolina, located in the semi-arid region of Brazil, is highlighted as an important agricultural growing region, however the irrigated areas have cleared natural vegetation inducing a loss of biodiversity. To analyze the contrast between these two ecosystems the large scale values of biomass production (BIO), evapotranspiration (ET) and water productivity (WP) were quantified. Monteithś equation was applied for estimating the absorbed photosynthetically active radiation (APAR), while the new SAFER (Simple Algorithm For Evapotranspiration Retrieving) algorithm was used to retrieve ET. The water productivity (WP) was analysed by the ratio of BIO by ET at monthly time scale with four bands of MODIS satellite images together with agrometeorological data for the year of 2011. The period with the highest water productivity values were from March to April in the rainy period for both irrigated and not irrigated conditions. However the largest ET rates were in November for irrigated crops and April for natural vegetation. More uniformity of the vegetation and water variables occurs in natural vegetation, evidenced by the lower values of standard deviation when comparing to irrigated crops, due to the different crop stages, cultural and irrigation managements. The models applied with MODIS satellite images on a large scale are considered to be suitable for water productivity assessments and for quantifying the effects of increasing irrigated areas over natural vegetation on regional water consumption in situations of quick changing land use pattern. © 2012 SPIE.

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In this work we investigate the cold front passage effects on sensible and latent heat flux in a tropical hydroelectric reservoir. The study area, Itumbiara reservoir (Goiás State/Brazil) at the beginning of the austral winter, is characterized by the presence of a weak thermal stratification and the passage of several cold fronts from higher latitudes of South America. Sensible and latent heat fluxes were estimated considering the atmospheric boundary layer stability. In situ and MODIS water surface temperature data were used to adjust the coefficients for momentum and heat exchanges between water and atmosphere and spatialize the sensible and latent heat fluxes. The results showed that during a cold front event the sensible heat flux can be up to five times greater than the flux observed before. The latent heat flux tends to decrease during the cold front but increase again after the passage. The highest values of heat loss were observed at littoral zone and some Reservoir's embayment. The heat loss intensification can be separated in two moments: first, during the cold front passage, when the wind speed increases and the air temperature decreases; second, after the cold front passage, with air humidity decreasing. This can be considered a key process to understanding the heat loss in the Itumbiara reservoir. © 2013 COSPAR. Published by Elsevier Ltd. All rights reserved.

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The objective of this study was to define a method for estimating soybean crop area in the Northern Rio Grande do Sul state (Brazil). Overall, six different remote sensing methods were proposed based on spectral-temporal profile and minimum and maximum values of NDVI/MODIS related to the stages of sowing, maximum development and harvesting of soybean areas. The resulting estimates were compared to official crop area data provided by the Brazilian government, using statistical analysis and the fuzzy similarity method. The performance of each method depended on information such as crop size, type of crop management, and sowing/harvesting dates. Regression coefficients of determination and fuzzy agreement values were above 0.8 and 0.45, respectively, for all methods. For operational monitoring of soybean crop area, the empirical threshold applied to the image difference with inclusion of harvest image method was the most effective, producing estimates that matched closely the official data. For spatial analysis the application of multitemporal images classification method is recommended that generated a map of better quality. The efficiency of these methods should be evaluated in the areas of soybean expansion in the state.

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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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.

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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.