995 resultados para Surface Reflectance
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We develop a method to derive aerosol properties over land surfaces using combined spectral and angular information, such as available from ESA Sentinel-3 mission, to be launched in 2015. A method of estimating aerosol optical depth (AOD) using only angular retrieval has previously been demonstrated on data from the ENVISAT and PROBA-1 satellite instruments, and is extended here to the synergistic spectral and angular sampling of Sentinel-3. The method aims to improve the estimation of AOD, and to explore the estimation of fine mode fraction (FMF) and single scattering albedo (SSA) over land surfaces by inversion of a coupled surface/atmosphere radiative transfer model. The surface model includes a general physical model of angular and spectral surface reflectance. An iterative process is used to determine the optimum value of the aerosol properties providing the best fit of the corrected reflectance values to the physical model. The method is tested using hyperspectral, multi-angle Compact High Resolution Imaging Spectrometer (CHRIS) images. The values obtained from these CHRIS observations are validated using ground-based sun photometer measurements. Results from 22 image sets using the synergistic retrieval and improved aerosol models show an RMSE of 0.06 in AOD, reduced to 0.03 over vegetated targets.
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Imagens CCD/CBERS-2, nas bandas espectrais CCD2, CCD3 e CCD4, dos anos de 2004 e 2005, de Mirante do Paranapanema - SP, foram transformadas em reflectância de superfície usando o modelo 5S de correção atmosférica e normalizadas radiometricamente. O objetivo principal foi caracterizar espectralmente áreas de pastagens de Brachiaria brizantha em fase de florescimento, isentas e infectadas com a doença mela-das-sementes da braquiária, possibilitando a sua detecção por meio da comparação entre os valores de reflectância de superfície denominada de Fator de Reflectância Bidirecional de Superfície (FRBS). Teve-se, também, o objetivo de avaliar a eficácia das imagens CCD/CBERS-2 para a obtenção de respostas espectrais de pastagens. Os dosséis sadios e doentes da Brachiaria brizantha foram identificados por meio da análise dos valores de reflectância e dos dados observados no Índice de Estresse Hídrico Acumulativo Relativo da Cultura (ACWSI) obtidos na área de estudo. Os resultados indicaram que as principais diferenças foram a diminuição da reflectância na banda CCD3 e o aumento da reflectância na banda CCD4 nas áreas doentes. A metodologia empregada com o uso de dados do sensor CCD/CBERS-2, associados ao ACWSI, mostrou-se eficaz para discriminar dosséis infectados com a mela-das-sementes da braquiária.
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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The Amazon River floodplain is an important source of atmospheric CO2 and CH4. Aquatic herbaceous vegetation (macrophytes) have been shown to contribute significantly to floodplain net primary productivity (NPP) and methane emission in the region. Their fast growth rates under both flooded and dry conditions make herbaceous vegetation the most variable element in the Amazon floodplain NPP budget, and the most susceptible to environmental changes. The present study combines multitemporal Radarsat-1 and MODIS images to monitor spatial and temporal changes in herbaceous vegetation cover in the Amazon floodplain. Radarsat-1 images were acquired from Dec/2003 to Oct/2005, and MODIS daily surface reflectance products were acquired for the two cloud-free dates closest to each Radarsat-1 acquisition. An object-based, hierarchical algorithm was developed using the temporal SAR information to discriminate Permanent Open Water (OW), Floodplain (FP) and Upland (UL) classes at Level 1, and then subdivide the FP class into Woody Vegetation (WV) and Possible Macrophytes (PM) at Level 2. At Level 3, optical and SAR information were combined to discriminate actual herbaceous cover at each date. The resulting maps had accuracies ranging from 80% to 90% for Level 1 and 2 classifications, and from 60% to 70% for Level 3 classifications, with kappa values ranging between 0.7 and 0.9 for Levels 1 and 2 and between 0.5 and 0.6 for Level 3. All study sites had noticeable variations in the extent of herbaceous cover throughout the hydrological year, with maximum areas up to four times larger than minimum areas. The proposed classification method was able to capture the spatial pattern of macrophyte growth and development in the studied area, and the multitemporal information was essential for both separating vegetation cover types and assessing monthly variation in herbaceous cover extent.
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Large conurbations are a significant source of the anthropogenic pollution and demographic differences between cities that result in a different pollution burden. The metropolitan area of Sao Paulo (MASP, population 20 million) accounts for one fifth of the Brazilian vehicular fleet. A feature of MASP is the amount of ethanol used by the vehicular fleet, known to exacerbate air quality. The study describes the diurnal behaviour of the submicron aerosol and relies on total particle number concentration, particle number size distribution, light scattering and light absorption measurements. Modelled planetary boundary layer (PBL) depth and air mass movement data were used to aid the interpretation. During morning rush-hour, stagnant air and a shallow PBL height favour the accumulation of aerosol pollution. During clear-sky conditions, there was a wind shift towards the edge of the city indicating a heat island effect with implications on particulate pollution levels at the site. The median total particle number concentration for the submicron aerosol typically varied in the range 1.6 x 10(4)-3.2 x 10(4) cm(-3) frequently exceeding 4 x 10(4) cm-3 during the day. During weekdays, nucleation-mode particles are responsible for most of the particles by numbers. The highest concentrations of total particle number concentrations and black carbon (BC) were observed on Fridays. Median diurnal values for light absorption and light scattering (at 637 nm wavelength) varied in the range 12-33 Mm(-1) and 21-64 Mm(-1), respectively. The former one is equal to 1.8-5.0 mu g m(-3) of BC. The growth of the PBL, from the morning rush-hour until noon, is consistent with the diurnal cycle of BC mass concentrations. Weekday hourly median single-scattering albedo (omega(0)) varied in the range 0.59-0.76. Overall, this suggests a top of atmosphere (TOA) warming effect. However, considering the low surface reflectance of urban areas, for the given range of omega(0), the TOA radiative forcing can be either positive or negative for the sources within the MASP. On the average, weekend omega(0) values were 0.074 higher than during weekdays. During 11% of the days, new particle formation (NPF) events occurred. The analysed events growth rates ranged between 9 and 25 nm h(-1). Sulphuric acid proxy concentrations calculated for the site were less than 5% of the concentration needed to explain the observed growth. Thus, other vapours are likely contributors to the observed growth.
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The spectral reflectance of the sea surface recorded using ocean colour satellite sensors has been used to estimate chlorophyll-a concentrations for decades. However, in bio-optically complex coastal waters, these estimates are compromised by the presence of several other coloured components besides chlorophyll, especially in regions affected by low-salinity waters. The present work aims to (a) describe the influence of the freshwater plume from the La Plata River on the variability of in situ remote sensing reflectance and (b) evaluate the performance of operational ocean colour chlorophyll algorithms applied to Southwestern Atlantic waters, which receive a remarkable seasonal contribution from La Plata River discharges. Data from three oceanographic cruises are used, in addition to a historical regional bio-optical dataset. Deviations found between measured and estimated concentrations of chlorophyll-a are examined in relation to surface water salinity and turbidity gradients to investigate the source of errors in satellite estimates of pigment concentrations. We observed significant seasonal variability in surface reflectance properties that are strongly driven by La Plata River plume dynamics and arise from the presence of high levels of inorganic suspended solids and coloured dissolved materials. As expected, existing operational algorithms overestimate the concentration of chlorophyll-a, especially in waters of low salinity (S<33.5) and high turbidity (Rrs(670)>0.0012 sr−1). Additionally, an updated version of the regional algorithm is presented, which clearly improves the chlorophyll estimation in those types of coastal environment. In general, the techniques presented here allow us to directly distinguish the bio-optical types of waters to be considered in algorithm studies by the ocean colour community.
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The Advanced Very High Resolution Radiometer (AVHRR) carried on board the National Oceanic and Atmospheric Administration (NOAA) and the Meteorological Operational Satellite (MetOp) polar orbiting satellites is the only instrument offering more than 25 years of satellite data to analyse aerosols on a daily basis. The present study assessed a modified AVHRR aerosol optical depth τa retrieval over land for Europe. The algorithm might also be applied to other parts of the world with similar surface characteristics like Europe, only the aerosol properties would have to be adapted to a new region. The initial approach used a relationship between Sun photometer measurements from the Aerosol Robotic Network (AERONET) and the satellite data to post-process the retrieved τa. Herein a quasi-stand-alone procedure, which is more suitable for the pre-AERONET era, is presented. In addition, the estimation of surface reflectance, the aerosol model, and other processing steps have been adapted. The method's cross-platform applicability was tested by validating τa from NOAA-17 and NOAA-18 AVHRR at 15 AERONET sites in Central Europe (40.5° N–50° N, 0° E–17° E) from August 2005 to December 2007. Furthermore, the accuracy of the AVHRR retrieval was related to products from two newer instruments, the Medium Resolution Imaging Spectrometer (MERIS) on board the Environmental Satellite (ENVISAT) and the Moderate Resolution Imaging Spectroradiometer (MODIS) on board Aqua/Terra. Considering the linear correlation coefficient R, the AVHRR results were similar to those of MERIS with even lower root mean square error RMSE. Not surprisingly, MODIS, with its high spectral coverage, gave the highest R and lowest RMSE. Regarding monthly averaged τa, the results were ambiguous. Focusing on small-scale structures, R was reduced for all sensors, whereas the RMSE solely for MERIS substantially increased. Regarding larger areas like Central Europe, the error statistics were similar to the individual match-ups. This was mainly explained with sampling issues. With the successful validation of AVHRR we are now able to concentrate on our large data archive dating back to 1985. This is a unique opportunity for both climate and air pollution studies over land surfaces.
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This article presents and technically describes a new field spectro-goniometer system for the ground-based characterization of the surface reflectance anisotropy under natural illumination conditions developed at the Alfred Wegener Institute (AWI). The spectro-goniometer consists of a Manual Transportable Instrument platform for ground-based Spectro-directional observations (ManTIS), and a hyperspectral sensor system. The presented measurement strategy shows that the AWI ManTIS field spectro-goniometer can deliver high quality hemispherical conical reflectance factor (HCRF) measurements with a pointing accuracy of ±6 cm within the constant observation center. The sampling of a ManTIS hemisphere (up to 30° viewing zenith, 360° viewing azimuth) needs approx. 18 min. The developed data processing chain in combination with the software used for the semi-automatic control provides a reliable method to reduce temporal effects during the measurements. The presented visualization and analysis approaches of the HCRF data of an Arctic low growing vegetation showcase prove the high quality of spectro-goniometer measurements. The patented low-cost and lightweight ManTIS instrument platform can be customized for various research needs and is available for purchase.
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Identifying cloud interference in satellite-derived data is a critical step toward developing useful remotely sensed products. Most MODIS land products use a combination of the MODIS (MOD35) cloud mask and the 'internal' cloud mask of the surface reflectance product (MOD09) to mask clouds, but there has been little discussion of how these masks differ globally. We calculated global mean cloud frequency for both products, for 2009, and found that inflated proportions of observations were flagged as cloudy in the Collection 5 MOD35 product. These erroneously categorized areas were spatially and environmentally non-random and usually occurred over high-albedo land-cover types (such as grassland and savanna) in several regions around the world. Additionally, we found that spatial variability in the processing path applied in the Collection 5 MOD35 algorithm affects the likelihood of a cloudy observation by up to 20% in some areas. These factors result in abrupt transitions in recorded cloud frequency across landcover and processing-path boundaries impeding their use for fine-scale spatially contiguous modeling applications. We show that together, these artifacts have resulted in significantly decreased and spatially biased data availability for Collection 5 MOD35-derived composite MODIS land products such as land surface temperature (MOD11) and net primary productivity (MOD17). Finally, we compare our results to mean cloud frequency in the new Collection 6 MOD35 product, and find that landcover artifacts have been reduced but not eliminated. Collection 6 thus increases data availability for some regions and land cover types in MOD35-derived products but practitioners need to consider how the remaining artifacts might affect their analysis.
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The impact of ambient ultraviolet (UV)-B radiation on the endemic bryophyte, Grimmia antarctici, was studied over 14 months in East Antarctica. Over recent decades, Antarctic plants have been exposed to the largest relative increase in UV-B exposure as a result of ozone depletion. We investigated the effect of reduced UV and visible radiation on the pigment concentrations, surface reflectance and physiological and morphological parameters of this moss. Plexiglass screens were used to provide both reduced UV levels (77%) and a 50% decrease in total radiation. The screen combinations were used to separate UV photoprotective from visible photoprotective strategies, because these bryophytes are growing in relatively high light environments compared with many mosses. G. antarctici was affected negatively by ambient levels of UV radiation. Chlorophyll content was significantly lower in plants grown under near-ambient UV, while the relative proportions of photoprotective carotenoids, especially beta-carotene and zeaxanthin, increased. However, no evidence for the accumulation of UV-B-absorbing pigments in response to UV radiation was observed. Although photosynthetic rates were not affected, there was evidence of UV effects on morphology. Plants that were shaded showed fewer treatment responses and these were similar to the natural variation observed between moss growing on exposed microtopographical ridges and in more sheltered valleys within the turf. Given that other Antarctic bryophytes possess UV-B-absorbing pigments which should offer better protection under ambient UV-B radiation, these findings suggest that G. antarctici may be disadvantaged in some settings under a climate with continuing high levels of springtime UV-B radiation.
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The pattern of illumination on an undulating surface can be used to infer its 3-D form (shape-from-shading). But the recovery of shape would be invalid if the luminance changes actually arose from changes in reflectance. So how does vision distinguish variation in illumination from variation in reflectance to avoid illusory depth? When a corrugated surface is painted with an albedo texture, the variation in local mean luminance (LM) due to shading is accompanied by a similar modulation in local luminance amplitude (AM). This is not so for reflectance variation, nor for roughly textured surfaces. We used depth mapping and paired comparison methods to show that modulations of local luminance amplitude play a role in the interpretation of shape-from-shading. The shape-from-shading percept was enhanced when LM and AM co-varied (in-phase) and was disrupted when they were out of phase or (to a lesser degree) when AM was absent. The perceptual differences between cue types (in-phase vs out-of-phase) were enhanced when the two cues were present at different orientations within a single image. Our results suggest that when LM and AM co-vary (in-phase) this indicates that the source of variation is illumination (caused by undulations of the surface), rather than surface reflectance. Hence, the congruence of LM and AM is a cue that supports a shape-from-shading interpretation. © 2006 Elsevier Ltd. All rights reserved.
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Thesis (Ph.D.)--University of Washington, 2016-08
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Dissertação (mestrado)—Universidade de Brasília, Instituto de Ciências Humanas, Departamento de Geografia, Programa de Pós-Graduação em Geografia, 2015.
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Executing a cloud or aerosol physical properties retrieval algorithm from controlled synthetic data is an important step in retrieval algorithm development. Synthetic data can help answer questions about the sensitivity and performance of the algorithm or aid in determining how an existing retrieval algorithm may perform with a planned sensor. Synthetic data can also help in solving issues that may have surfaced in the retrieval results. Synthetic data become very important when other validation methods, such as field campaigns,are of limited scope. These tend to be of relatively short duration and often are costly. Ground stations have limited spatial coverage whilesynthetic data can cover large spatial and temporal scales and a wide variety of conditions at a low cost. In this work I develop an advanced cloud and aerosol retrieval simulator for the MODIS instrument, also known as Multi-sensor Cloud and Aerosol Retrieval Simulator (MCARS). In a close collaboration with the modeling community I have seamlessly combined the GEOS-5 global climate model with the DISORT radiative transfer code, widely used by the remote sensing community, with the observations from the MODIS instrument to create the simulator. With the MCARS simulator it was then possible to solve the long standing issue with the MODIS aerosol optical depth retrievals that had a low bias for smoke aerosols. MODIS aerosol retrieval did not account for effects of humidity on smoke aerosols. The MCARS simulator also revealed an issue that has not been recognized previously, namely,the value of fine mode fraction could create a linear dependence between retrieved aerosol optical depth and land surface reflectance. MCARS provided the ability to examine aerosol retrievals against “ground truth” for hundreds of thousands of simultaneous samples for an area covered by only three AERONET ground stations. Findings from MCARS are already being used to improve the performance of operational MODIS aerosol properties retrieval algorithms. The modeling community will use the MCARS data to create new parameterizations for aerosol properties as a function of properties of the atmospheric column and gain the ability to correct any assimilated retrieval data that may display similar dependencies in comparisons with ground measurements.
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Time Series Analysis of multispectral satellite data offers an innovative way to extract valuable information of our changing planet. This is now a real option for scientists thanks to data availability as well as innovative cloud-computing platforms, such as Google Earth Engine. The integration of different missions would mitigate known issues in multispectral time series construction, such as gaps due to clouds or other atmospheric effects. With this purpose, harmonization among Landsat-like missions is possible through statistical analysis. This research offers an overview of the different instruments from Landsat and Sentinel missions (TM, ETM, OLI, OLI-2 and MSI sensors) and products levels (Collection-2 Level-1 and Surface Reflectance for Landsat and Level-1C and Level-2A for Sentinel-2). Moreover, a cross-sensors comparison was performed to assess the interoperability of the sensors on-board Landsat and Sentinel-2 constellations, having in mind a possible combined use for time series analysis. Firstly, more than 20,000 pairs of images almost simultaneously acquired all over Europe were selected over a period of several years. The study performed a cross-comparison analysis on these data, and provided an assessment of the calibration coefficients that can be used to minimize differences in the combined use. Four of the most popular vegetation indexes were selected for the study: NDVI, EVI, SAVI and NDMI. As a result, it is possible to reconstruct a longer and denser harmonized time series since 1984, useful for vegetation monitoring purposes. Secondly, the spectral characteristics of the recent Landsat-9 mission were assessed for a combined use with Landsat-8 and Sentinel-2. A cross-sensor analysis of common bands of more than 3,000 almost simultaneous acquisitions verified a high consistency between datasets. The most relevant discrepancy has been observed in the blue and SWIRS bands, often used in vegetation and water related studies. This analysis was supported with spectroradiometer ground measurements.