992 resultados para spectral change


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A detailed analysis is presented of solar UV spectral irradiance for the period between May 2003 and August 2005, when data are available from both the Solar Ultraviolet pectral Irradiance Monitor (SUSIM) instrument (on board the pper Atmosphere Research Satellite (UARS) spacecraft) and the Solar Stellar Irradiance Comparison Experiment (SOLSTICE) instrument (on board the Solar Radiation and Climate Experiment (SORCE) satellite). The ultimate aim is to develop a data composite that can be used to accurately determine any differences between the “exceptional” solar minimum at the end of solar cycle 23 and the previous minimum at the end of solar cycle 22 without having to rely on proxy data to set the long‐term change. SUSIM data are studied because they are the only data available in the “SOLSTICE gap” between the end of available UARS SOLSTICE data and the start of the SORCE data. At any one wavelength the two data sets are considered too dissimilar to be combined into a meaningful composite if any one of three correlations does not exceed a threshold of 0.8. This criterion removes all wavelengths except those in a small range between 156 nm and 208 nm, the longer wavelengths of which influence ozone production and heating in the lower stratosphere. Eight different methods are employed to intercalibrate the two data sequences. All methods give smaller changes between the minima than are seen when the data are not adjusted; however, correcting the SUSIM data to allow for an exponentially decaying offset drift gives a composite that is largely consistent with the unadjusted data from the SOLSTICE instruments on both UARS and SORCE and in which the recent minimum is consistently lower in the wave band studied.

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Attempts to estimate photosynthetic rate or gross primary productivity from remotely sensed absorbed solar radiation depend on knowledge of the light use efficiency (LUE). Early models assumed LUE to be constant, but now most researchers try to adjust it for variations in temperature and moisture stress. However, more exact methods are now required. Hyperspectral remote sensing offers the possibility of sensing the changes in the xanthophyll cycle, which is closely coupled to photosynthesis. Several studies have shown that an index (the photochemical reflectance index) based on the reflectance at 531 nm is strongly correlated with the LUE over hours, days and months. A second hyperspectral approach relies on the remote detection of fluorescence, which is a directly related to the efficiency of photosynthesis. We discuss the state of the art of the two approaches. Both have been demonstrated to be effective, but we specify seven conditions required before the methods can become operational.

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We investigate the depositional time scale of lithological couplets (fine sandstone/siltstone-siltstone/mudstone) from two distinctive outcrops of Permo-Carboniferous glacial rhythmites in the Itarare Group (Parana Basin, Brazil). Resolving the fundamental issue of time scale for these rhythmites is important in light of recent evidence for paleosecular variation measured in these sequences. Spectral analysis and tuning of high-resolution gray scale scans of sediment core microstratigraphy, which comprises pervasive laminations, reveal a comparable spectral content at both localities, with a frequency suite interpreted as that of short-term climate variability of Recent and modern times. This evidence for decadal- to centennial-scale deposition of these lithological couplets is discussed in light of the `varvic` character, i.e., annual time scale that was previously assumed for the rhythmites.

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Submicron atmospheric particles in the Amazon Basin were characterized by a high-resolution aerosol mass spectrometer during the wet season of 2008. Patterns in the mass spectra closely resembled those of secondary-organic-aerosol (SOA) particles formed in environmental chambers from biogenic precursor gases. In contrast, mass spectral indicators of primary biological aerosol particles (PBAPs) were insignificant, suggesting that PBAPs contributed negligibly to the submicron fraction of particles during the period of study. For 40% of the measurement periods, the mass spectra indicate that in-Basin biogenic SOA production was the dominant source of the submicron mass fraction, contrasted to other periods (30%) during which out-of-Basin organic-carbon sources were significant on top of the baseline in-Basin processes. The in-Basin periods had an average organic-particle loading of 0.6 mu g m(-3) and an average elemental oxygen-to-carbon (O:C) ratio of 0.42, compared to 0.9 mu g m(-3) and 0.49, respectively, during periods of out-of-Basin influence. On the basis of the data, we conclude that most of the organic material composing submicron particles over the Basin derived from biogenic SOA production, a finding that is consistent with microscopy observations made in a concurrent study. This source was augmented during some periods by aged organic material delivered by long-range transport. Citation: Chen, Q., et al. (2009), Mass spectral characterization of submicron biogenic organic particles in the Amazon Basin, Geophys. Res. Lett., 36, L20806, doi: 10.1029/2009GL039880.

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A new class of doubletalk detector based on exploiting a spectral slit is proposed. This is achieved by spectrally deleting a frequency band in the far-end signal such that when the near-end signal is present, only the near-end spectral information is present. The proposed method relies solely on the detection of speech activity period in the slit area, and significantly, it requires no estimation of the echo path. Evaluation in typical acoustic echo setups shows that the proposed method outperforms other conventional doubletalk detectors in terms of probability of miss detection even under poor echo-to-noise ratio (ENR), low echo-to-far-end ratio (EFR) conditions, and echo path change.

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Building on a habitat mapping project completed in 2011, Deakin University was commissioned by Parks Victoria (PV) to apply the same methodology and ground-truth data to a second, more recent and higher resolution satellite image to create habitat maps for areas within the Corner Inlet and Nooramunga Marine and Coastal Park and Ramsar area. A ground-truth data set using in situ video and still photographs was used to develop and assess predictive models of benthic marine habitat distributions incorporating data from both RapidEye satellite imagery (corrected for atmospheric and water column effects by CSIRO) and LiDAR (Light Detection and Ranging) bathymetry. This report describes the results of the mapping effort as well as the methodology used to produce these habitat maps.

Overall accuracies of habitat classifications were good, with error rates similar to or better than the earlier classification (>73 % and kappa values > 0.58 for both study localities). The RapidEye classification failed to accurately detect Pyura and reef habitat classes at the Corner Inlet locality, possibly due to differences in spectral frequencies. For comparison, these categories were combined into a ‘non-seagrass’ category, similar to the one used at the Nooramunga locality in the original classification. Habitats predicted with highest accuracies differed from the earlier classification and were Posidonia in Corner Inlet (89%), and bare sediment (no-visible seagrass class) in Nooramunga (90%). In the Corner Inlet locality reef and Pyura habitat categories were not distinguishable in the repeated classification and so were combined with bare sediments. The majority of remaining classification errors were due to the misclassification of Zosteraceae as bare sediment and vice versa. Dominant habitats were the same as those from the 2011 classification with some differences in extent. For the Corner Inlet study locality the no-visible seagrass category remained the most extensive (9059 ha), followed by Posidonia (5,513 ha) and Zosteraceae (5,504 ha). In Nooramunga no-visible seagrass (6,294 ha), Zosteraceae (3,122 ha) and wet saltmarsh (1,562 ha) habitat classes were most dominant.

Change detection analyses between the 2009 and 2011 imagery were undertaken as part of this project, following the analyses presented in Monk et al. (2011) and incorporating error estimates from both classifications. These analyses indicated some shifts in classification between Posidonia and Zosteraceae as well as a general reduction in the area of Zosteraceae. Issues with classification of mixed beds were apparent, particularly in the main Posidonia bed at Nooramunga where a mosaic of Zosteraceae and Posidonia was seen that was not evident in the ALOS classification. Results of a reanalysis of the 1998-2009 change detection illustrating effects of binning of mixed beds is also provided as an appendix.

This work has been successful in providing baseline maps at an improved level of detail using a repeatable method meaning that any future changes in intertidal and shallow water marine habitats may be assessed in a consistent way with quantitative error assessments. In wider use, these maps should also allow improved conservation planning, advance fisheries and catchment management, and progress infrastructure planning to limit impacts on the Inlet environment.

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We study a model for dynamical localization of topology using ideas from non-commutative geometry and topology in quantum mechanics. We consider a collection X of N one-dimensional manifolds and the corresponding set of boundary conditions (self-adjoint extensions) of the Dirac operator D. The set of boundary conditions encodes the topology and is parameterized by unitary matrices g. A particular geometry is described by a spectral triple x(g) = (A X, script H sign X, D(g)). We define a partition function for the sum over all g. In this model topology fluctuates but the dimension is kept fixed. We use the spectral principle to obtain an action for the set of boundary conditions. Together with invariance principles the procedure fixes the partition function for fluctuating topologies. The model has one free-parameter β and it is equivalent to a one plaquette gauge theory. We argue that topology becomes localized at β = ∞ for any value of N. Moreover, the system undergoes a third-order phase transition at β = 1 for large-N. We give a topological interpretation of the phase transition by looking how it affects the topology. © SISSA/ISAS 2004.

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PURPOSE. To study changes in lamina cribrosa position and prelaminar tissue thickness (PTT) after surgical IOP reduction in glaucoma patients. METHODS. Twenty-two patients (mean age, 71.4 years) were imaged with spectral domain optical coherence tomography (SD-OCT; 24 radial B-scans centered on the optic nerve head [ONH]) before trabeculectomy or tube shunt implantation. Follow up images were acquired 1 week, 1 month, 3 months, and 6 months postsurgery. Bruch's membrane opening (BMO), the internal limiting membrane (ILM) and the anterior laminar surface (ALS) were segmented in each radial scan with custom software. Surfaces were fitted to the ILM and ALS with the extracted three-dimesional coordinates. PTT was the distance between the ILM and ALS, perpendicular to a BMO reference plane. Serial postsurgical laminar displacement (LD), relative to the BMO reference plane, and changes in PTT were measured. Positive values indicated anterior LD. RESULTS. Mean (SD) presurgery IOP was 18.1 (6.5) mm Hg, and reduced by 4.7 (5.5), 2.4 (7.7), 7.0 (6.2), and 6.8 (7.5) mm Hg at 1 week, 1 month, 3 months, and 6 months postsurgery, respectively. At the four postsurgery time points, there was significant anterior LD (1.8 [9.5], -1.1 [8.9], 8.8 [20.2], and 17.9 [25.8] mu m) and PTT increase (1.7 [13.3], 2.4 [11.9], 17.4 [13.7], and 13.9 [18.6] mu m). LD was greater in ONHs with larger BMO area (P = 0.01) and deeper ALS (P = 0.04); however, PTT was not associated with any of the tested independent variables. CONCLUSIONS. Both anterior LD and thickening of prelaminar tissue occur after surgical IOP reduction in patients with glaucoma. (Invest Ophthalmol Vis Sci. 2012;53:5819-5826) DOI:10.1167/iovs.12-9924

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Urban agriculture is a phenomenon that can be observed world-wide, particularly in cities of devel- oping countries. It is contributing significantly to food security and food safety and has sustained livelihood of the urban and peri-urban low income dwe llers in developing countries for many years. Population increase due to rural-urban migration and natural - formal as well as informal - urbani- sation are competing with urban farming for available space and scarce water resources. A mul- titemporal and multisensoral urban change analysis over the period of 25 years (1982-2007) was performed in order to measure and visualise the urban expansion along the Kizinga and Mzinga valley in the south of Dar Es Salaam. Airphotos and VHR satellite data were analysed by using a combination of a composition of anisotropic textural measures and spectral information. The study revealed that unplanned built-up area is expanding continuously, and vegetation covers and agricultural lands decline at a fast rate. The validation showed that the overall classification accuracy varied depending on the database. The extracted built-up areas were used for visual in- terpretation mapping purposes and served as information source for another research project. The maps visualise an urban congestion and expansion of nearly 18% of the total analysed area that had taken place in the Kizinga valley between 1982 and 2007. The same development can be ob- served in the less developed and more remote Mzinga valley between 1981 and 2002. Both areas underwent fast changes where land prices still tend to go up and an influx of people both from rural and urban areas continuously increase the density with the consequence of increasing multiple land use interests.

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The Zagros oak forests in Western Iran are critically important to the sustainability of the region. These forests have undergone dramatic declines in recent decades. We evaluated the utility of the non-parametric Random Forest classification algorithm for land cover classification of Zagros landscapes, and selected the best spatial and spectral predictive variables. The algorithm resulted in high overall classification accuracies (>85%) and also equivalent classification accuracies for the datasets from the three different sensors. We evaluated the associations between trends in forest area and structure with trends in socioeconomic and climatic conditions, to identify the most likely driving forces creating deforestation and landscape structure change. We used available socioeconomic (urban and rural population, and rural income), and climatic (mean annual rainfall and mean annual temperature) data for two provinces in northern Zagros. The most correlated driving force of forest area loss was urban population, and climatic variables to a lesser extent. Landscape structure changes were more closely associated with rural population. We examined the effects of scale changes on the results from spatial pattern analysis. We assessed the impacts of eight years of protection in a protected area in northern Zagros at two different scales (both grain and extent). The effects of protection on the amount and structure of forests was scale dependent. We evaluated the nature and magnitude of changes in forest area and structure over the entire Zagros region from 1972 to 2009. We divided the Zagros region in 167 Landscape Units and developed two measures— Deforestation Sensitivity (DS) and Connectivity Sensitivity (CS) — for each landscape unit as the percent of the time steps that forest area and ECA experienced a decrease of greater than 10% in either measure. A considerable loss in forest area and connectivity was detected, but no sudden (nonlinear) changes were detected at the spatial and temporal scale of the study. Connectivity loss occurred more rapidly than forest loss due to the loss of connecting patches. More connectivity was lost in southern Zagros due to climatic differences and different forms of traditional land use.

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External forcing and internal dynamics result in climate system variability ranging from sub-daily weather to multi-centennial trends and beyond1, 2. State-of-the-art palaeoclimatic methods routinely use hydroclimatic proxies to reconstruct temperature (for example, refs 3, 4), possibly blurring differences in the variability continuum of temperature and precipitation before the instrumental period. Here, we assess the spectral characteristics of temperature and precipitation fluctuations in observations, model simulations and proxy records across the globe. We find that whereas an ensemble of different general circulation models represents patterns captured in instrumental measurements, such as land–ocean contrasts and enhanced low-frequency tropical variability, the tree-ring-dominated proxy collection does not. The observed dominance of inter-annual precipitation fluctuations is not reflected in the annually resolved hydroclimatic proxy records. Likewise, temperature-sensitive proxies overestimate, on average, the ratio of low- to high-frequency variability. These spectral biases in the proxy records seem to propagate into multi-proxy climate reconstructions for which we observe an overestimation of low-frequency signals. Thus, a proper representation of the high- to low-frequency spectrum in proxy records is needed to reduce uncertainties in climate reconstruction efforts.

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Urban agriculture is a phenomenon that can be observed world-wide, particularly in cities of devel-oping countries. It is contributing significantly to food security and food safety and has sustained livelihood of the urban and peri-urban low income dwellers in developing countries for many years. Population increase due to rural-urban migration and natural, coupled with formal as well as infor-mal urbanization are competing with urban farming for available space and scarce water resources. A multitemporal multisensoral urban change analysis over the period of 25 years (1982-2007) was performed in order to measure and visualize the urban expansion along the Kizinga and Mzinga valley in the South of Dar es Salaam. Airphotos and VHR satellite data were analyzed by using a combination of a composition of anisotropic textural measures and spectral information. The study revealed that unplanned built-up area is expanding continuously and vegetation covers and agricultural lands decline at a fast rate. The validation showed that the overall classification accuracy varied depending on the database. The extracted built-up areas were used for visual in-terpretation mapping purposes and served as information source for another research project. The maps visualize an urban congestion and expansion of nearly 18% of the total analyzed area that had taken place in the Kizinga valley between 1982 and 2007. The same development can be ob-served in the less developed and more remote Mzinga valley between 1981 and 2002. Both areas underwent fast changes where land prices still tend to go up and an influx of people both from rural and urban areas continuously increase density with the consequence of increasing multiple land use interests.

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Landcover is subject to continuous changes on a wide variety of temporal and spatial scales. Those changes produce significant effects in human and natural activities. Maintaining an updated spatial database with the occurred changes allows a better monitoring of the Earth?s resources and management of the environment. Change detection (CD) techniques using images from different sensors, such as satellite imagery, aerial photographs, etc., have proven to be suitable and secure data sources from which updated information can be extracted efficiently, so that changes can also be inventoried and monitored. In this paper, a multisource CD methodology for multiresolution datasets is applied. First, different change indices are processed, then different thresholding algorithms for change/no_change are applied to these indices in order to better estimate the statistical parameters of these categories, finally the indices are integrated into a change detection multisource fusion process, which allows generating a single CD result from several combination of indices. This methodology has been applied to datasets with different spectral and spatial resolution properties. Then, the obtained results are evaluated by means of a quality control analysis, as well as with complementary graphical representations. The suggested methodology has also been proved efficiently for identifying the change detection index with the higher contribution.

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In this letter, we propose a novel method for unsupervised change detection (CD) in multitemporal Erreur Relative Globale Adimensionnelle de Synthese (ERGAS) satellite images by using the relative dimensionless global error in synthesis index locally. In order to obtain the change image, the index is calculated around a pixel neighborhood (3x3 window) processing simultaneously all the spectral bands available. With the objective of finding the binary change masks, six thresholding methods are selected. A comparison between the proposed method and the change vector analysis method is reported. The accuracy CD showed in the experimental results demonstrates the effectiveness of the proposed method.