9 resultados para Optical fiber sensing
em Publishing Network for Geoscientific
Resumo:
Thawing-induced cliff top retreat in permafrost landscapes is mainly due to thermo-erosion. Ground-ice-rich permafrost landscapes are specifically vulnerable to thermo-erosion and may show high degradation rates. Within the HGF Alliance Remote Sensing and the FP7 PAGE21 permafrost programs we investigated how SAR and optical remote sensing can contribute to the monitoring of erosion rates of ice-rich cliffs in Arctic Siberia (Lena Delta, Russia). We produced two different vector products: i) Intra-annual cliff top retreat based on TerraSAR-X (TSX) satellite data (2012-2014): High-temporal resolution time series of TSX satellite data allow the inter-annual and intra-annual monitoring of the upper cliff-line retreat also under bad weather conditions and continuous cloud coverage. This published SAR product contains the retreating upper cliff lines of a 1.5 km long part of eroding ice-rich coast of Kurungnakh Island in the central Lena Delta. The upper cliff line was mapped using a thresholding approach for images acquired in the years 2012, 2013 and 2014 for the months June (2013, 2014), July (2013, 2014), August (2012, 2013, 2014) and September (2013, 2014). The cliff top retreat vector product is called 'upper_cliff_TerraSAR-X'. While the 2014 cliff lines show a clear retreat of 2 to 3 m/month, the cliff top lines for 2012 and 2013 are not chronologically ordered. However, lines from the end of the season of a year are always close to the lines from the beginning of the next summer season, indicating low cliff retreat in winter. ii) 4-year cliff top retreat based on optical satellite data (2010-2014): Long-term cliff top retreat could be assessed with two high-spatial resolution optical satellite images (GeoEye-1, 2010-08-05 and Worldview-1, 2014-08-19). The cliff top retreat vector product is called 'upper_cliff_optical'. Results: The long-term cliff top retreat derived from optical satellite data are 35 m cliff retreat within 4 years. The higher-temporal resolution SAR data equivalently show long-term rates of 18 m within 2 years and nearly now degradation activities in winter but maximum erosion rates in summer months.The Intra-seasonal cliff top retreat lines from 2014 show a rate of 2 to 3 m per month.
Resumo:
The Aral Sea is located in an arid region with much sand and salt deposits in the surrounding barren open land. Hence, significant displacements of sediments into the lakebed by the action of wind, water, gravity, or snow are likely. The bathymetry of the lake was last observed in the 1960s, and within the last half century, the structure of the lakebed has changed. Based on satellite observations of the temporal changes of shoreline (Landsat optical remote sensing) and water level (multi-mission satellite altimetry) over more than one decade an updated bathymetric chart for the East Basin of the Aral Sea has been generated. During this time, the geometry of the shallow East Basin experienced strong fluctuations due to the occurrence of periods of drying and strong inflow. By the year 2014 the East Basin fell dry. The dynamic behavior of the basin allowed for estimating the lake's bathymetry from a series of satellite-based information. The river mouth made its impression in the present East Aral Sea, because its shrinking led to the inflow of much sediment into the lake's interior. In addition, salt deposits along the shorelines increased the corresponding elevation, a phenomenon that is more pronounced in the reduced lakebed because of increased salinity. It must be noted that height estimates from satellite altimetry were only possible down to a minimum elevation of 27 m above sea level due to a lack of reliable altimetry data over the largely reduced water surface. In order to construct a complete bathymetric chart of the lakebed of the East Aral Sea heights below 27 m were obtained solely from Landsat optical images following the SRB (Selected Region Boundary) approach as described by Singh et al. (2015).
Resumo:
This airborne hyperspectral (19 bands) image data of Heron Reef, Great Barrier Reef, Australia is derived from Compact Airborne Spectrographic Imager (CASI) data acquired on 1st and 3rd of July 2002, latitude -23.45, longitude 151.92. Processing and correction to at-surface data was completed by Karen Joyce (Joyce, 2004). Raw imagery consisted several images corresponding to the number of flight paths taken to cover the entire Heron Reef. Spatial resolution is one meter. Radiometric corrections converted the at-sensor digital number values to at surface spectral radiance values using sensor specific calibration coefficients and CSIRO's c-WomBat-c atmospheric correction software. Geometric corrections were done using field collected coordinates of features identified in the image. Projection used was Universal Transverse Mercator Zone 56 South and Datum used was WGS 84. Image data is in TIFF format.
Resumo:
Hydrographers have traditionally referred to the nearshore area as the "white ribbon" area due to the challenges associated with the collection of elevation data in this highly dynamic transitional zone between terrestrial and marine environments. Accordingly, available information in this zone is typically characterised by a range of datasets from disparate sources. In this paper we propose a framework to 'fill' the white ribbon area of a coral reef system by integrating multiple elevation and bathymetric datasets acquired by a suite of remote-sensing technologies into a seamless digital elevation model (DEM). A range of datasets are integrated, including field-collected GPS elevation points, terrestrial and bathymetric LiDAR, single and multibeam bathymetry, nautical chart depths and empirically derived bathymetry estimations from optical remote sensing imagery. The proposed framework ranks data reliability internally, thereby avoiding the requirements to quantify absolute error and results in a high resolution, seamless product. Nested within this approach is an effective spatially explicit technique for improving the accuracy of bathymetry estimates derived empirically from optical satellite imagery through modelling the spatial structure of residuals. The approach was applied to data collected on and around Lizard Island in northern Australia. Collectively, the framework holds promise for filling the white ribbon zone in coastal areas characterised by similar data availability scenarios. The seamless DEM is referenced to the horizontal coordinate system MGA Zone 55 - GDA 1994, mean sea level (MSL) vertical datum and has a spatial resolution of 20 m.
Resumo:
In this study four data quality flags are presented for automated and unmanned above-water hyperspectral optical measurements collected underway in the North Sea, The Minch, Irish Sea and Celtic Sea in April/May 2009. Coincident to these optical measurements a DualDome D12 (Mobotix, Germany) camera system was used to capture sea surface and sky images. The first three flags are based on meteorological conditions, to select erroneous incoming solar irradiance (ES) taken during dusk, dawn, before significant incoming solar radiation could be detected or under rainfall. Furthermore, the relative azimuthal angle of the optical sensors to the sun is used to identify possible sunglint free sea surface zones. A total of 629 spectra remained after applying the meteorological masks (first three flags). Based on this dataset, a fourth flag for sunglint was generated by analysing and evaluating water leaving radiance (LW) and remote sensing reflectance (RRS) spectral behaviour in the presence and absence of sunglint salient in the simultaneously available sea surface images. Spectra conditions satisfying "mean LW (700-950 nm) < 2 mW/m**2/nm/Sr" or alternatively "minimum RRS (700-950 nm) < 0.010/Sr", mask the most measurements affected by sunglint, providing efficient flagging of sunglint in automated quality control. It is confirmed that valid optical measurements can be performed 0° <= theta <= 360° although 90° <= theta <= 135° is recommended.
Resumo:
Nutrient supply in the area off Northwest Africa is mainly regulated by two processes, coastal upwelling and deposition of Saharan dust. In the present study, both processes were analyzed and evaluated by different methods, including cross-correlation, multiple correlation, and event statistics, using remotely sensed proxies of the period from 2000 to 2008 to investigate their influence on the marine environment. The remotely sensed chlorophyll-a concentration was used as a proxy for the phytoplankton biomass stimulated by nutrient supply into the euphotic zone from deeper water layers and from the atmosphere. Satellite-derived alongshore wind stress and sea-surface temperature were applied as proxies for the strength and reflection of coastal upwelling processes. The westward wind and the dust component of the aerosol optical depth describe the transport direction of atmospheric dust and the atmospheric dust column load. Alongshore wind stress and induced upwelling processes were most significantly responsible for the surface chlorophyll-a variability, accounting for about 24% of the total variance, mainly in the winter and spring due to the strong north-easterly trade winds. The remotely sensed proxies allowed determination of time lags between biological response and its forcing processes. A delay of up to 16 days in the surface chlorophyll-a concentration due to the alongshore wind stress was determined in the northern winter and spring. Although input of atmospheric iron by dust storms can stimulate new phytoplankton production in the study area, only 5% of the surface chlorophyll-a variability could be ascribed to the dust component in the aerosol optical depth. All strong desert storms were identified by an event statistics in the time period from 2000 to 2008. The 57 strong storms were studied in relation to their biological response. Six events were clearly detected in which an increase of chlorophyll-a was caused by Saharan dust input and not by coastal upwelling processes. Time lags of <8 days, 8 days, and 16 days were determined. An increase in surface chlorophyll-a concentration of up to 2.4 mg m**3 after dust storms in which the dust component of the aerosol optical depth was up to 0.9 was observed.
Resumo:
In this paper, modernized shipborne procedures are presented to collect and process above-water radiometry for remote sensing applications. A setup of five radiometers and a bidirectional camera system, which provides panoramic sea surface and sky images, is proposed for the collection of high-resolution radiometric quantities. Images from the camera system can be used to determine sky state and potential glint, whitecaps, or foam contamination. A peak in the observed remote sensing reflectance RRS spectra between 750-780 nm was typically found in spectra with relatively high surface reflected glint (SRG), which suggests this waveband could be a useful SRG indicator. Simplified steps for computing uncertainties in SRG corrected RRS are proposed and discussed. The potential of utilizing "unweighted multimodel averaging," which is the average of four or more common SRG correction models, is examined to determine the best approximation RRS. This best approximation RRS provides an estimate of RRS based on various SRG correction models established using radiative transfer simulations and field investigations. Applying the average RRS provides a measure of the inherent uncertainties or biases that result from a user subjectively choosing any one SRG correction model. Comparisons between inherent and apparent optical property derived observations were used to assess the robustness of the SRG multimodel averaging ap- proach. Correlations among the standard SRG models were completed to determine the degree of association or similarities between the SRG models. Results suggest that the choice of glint models strongly affects derived RRS values and can also influence the blue to green band ratios used for modeling biogeochemical parameters such as for chlorophyll a. The objective here is to present a uniform and traceable methodology for determining ship- borne RRS measurements and its associated errors due to glint correction and to ensure the direct comparability of these measurements in future investigations. We encourage the ocean color community to publish radiometric field measurements with matching and complete metadata in open access repositories.