65 resultados para Coastal Monitoring. Geodesy. DEM. LiDAR
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:
A circumpolar representative and consistent wetland map is required for a range of applications ranging from upscaling of carbon fluxes and pools to climate modelling and wildlife habitat assessment. Currently available data sets lack sufficient accuracy and/or thematic detail in many regions of the Arctic. Synthetic aperture radar (SAR) data from satellites have already been shown to be suitable for wetland mapping. Envisat Advanced SAR (ASAR) provides global medium-resolution data which are examined with particular focus on spatial wetness patterns in this study. It was found that winter minimum backscatter values as well as their differences to summer minimum values reflect vegetation physiognomy units of certain wetness regimes. Low winter backscatter values are mostly found in areas vegetated by plant communities typically for wet regions in the tundra biome, due to low roughness and low volume scattering caused by the predominant vegetation. Summer to winter difference backscatter values, which in contrast to the winter values depend almost solely on soil moisture content, show expected higher values for wet regions. While the approach using difference values would seem more reasonable in order to delineate wetness patterns considering its direct link to soil moisture, it was found that a classification of winter minimum backscatter values is more applicable in tundra regions due to its better separability into wetness classes. Previous approaches for wetland detection have investigated the impact of liquid water in the soil on backscatter conditions. In this study the absence of liquid water is utilized. Owing to a lack of comparable regional to circumpolar data with respect to thematic detail, a potential wetland map cannot directly be validated; however, one might claim the validity of such a product by comparison with vegetation maps, which hold some information on the wetness status of certain classes. It was shown that the Envisat ASAR-derived classes are related to wetland classes of conventional vegetation maps, indicating its applicability; 30% of the land area north of the treeline was identified as wetland while conventional maps recorded 1-7%.
Resumo:
Requirements for space based monitoring of permafrost features had been already defined within the IGOS Cryosphere Theme Report at the start of the IPY in 2007 (IGOS, 2007). The WMO Polar Space Task Group (PSTG, http://www.wmo.int/pages/prog/sat/pstg_en.php) identified the need to review the requirements for permafrost monitoring and to update these requirements in 2013. Relevant surveys with focus on satellite data are already available from the ESA DUE Permafrost User requirements survey (2009), the United States National Research Council (2014) and the ESA - CliC - IPA - GTN -P workshop in February 2014. These reports have been reviewed and specific needs discussed within the community and a white paper submitted to the WMO PSTG. Acquisition requirements for monitoring of especially terrain changes (incl. rock glaciers and coastal erosion) and lakes (extent, ice properties etc.) with respect to current satellite missions have been specified. About 50 locations ('cold spots') where permafrost (Arctic and Antarctic) in situ monitoring has been taking place for many years or where field stations are currently established have been identified. These sites have been proposed to the WMO Polar Space Task Group as focus areas for future monitoring by high resolution satellite data. The specifications of these sites including meta-data on site instrumentation have been published as supplement to the white paper (Bartsch et al. 2014, doi:10.1594/PANGAEA.847003). The representativity of the 'cold spots' around the arctic has been in the following assessed based on a landscape units product which has been developed as part of the FP7 project PAGE21. The ESA DUE Permafrost service has been utilized to produce a pan-arctic database (25km, 2000-2014) comprising Mean Annual Surface Temperature, Annual and summer Amplitude of Surface Temperature, Mean Summer (July-August) Surface Temperature. Surface status (frozen/unfrozen) related products have been also derived from the ESA DUE Permafrost service. This includes the length of unfrozen period, first unfrozen day and first frozen day. In addition, SAR (ENVISAT ASAR GM) statistics as well as topographic parameters have been considered. The circumpolar datasets have been assessed for their redundancy in information content. 12 distinct units could be derived. The landscape units reveal similarities between North Slope Alaska and the region from the Yamal Peninsula to the Yenisei estuary. Northern Canada is characterized by the same landscape units like western Siberia. North-eastern Canada shows similarities to the Laptev coast region. This paper presents the result of this assessment and formulates recommendations for extensions of the in situ monitoring networks and categorizes the sites by satellite data requirements (specifically Sentinels) with respect to the landscape type and related processes.
Resumo:
We have generated a new digital elevation model for entire King George Island, Antarctica, using summer TanDEM-X bistatic SAR satellite data. The data was processed using differential SAR interferometry with an older DEM as reference. 4 TanDEM-X scenes from January 2012 were used as input. The new DEM was referenced to and validated against DGPS measurements. Height values are given in reference to ellipsoid (WGS84).
Resumo:
In this study, high-throughput sequencing (HTS) metabarcoding was applied for the surveillance of plankton communities within the southeastern (SE) Baltic Sea coastal zone. These results were compared with those from routine monitoring survey and morphological analyses. Four of five nonindigenous species found in the samples were identified exclusively by metabarcoding. All of them are considered as invasive in the Baltic Sea with reported impact on the ecosystem and biodiversity. This study indicates that, despite some current limitations, HTS metabarcoding can provide information on the presence of exotic species and advantageously complement conventional approaches, only requiring the same monitoring effort as before. Even in the currently immature status of HTS, this combination of HTS metabarcoding and observational records is recommended in the early detection of marine pests and delivery of the environmental status metrics of nonindigenous species.