970 resultados para Laser-Sintern
Resumo:
Flood extent maps derived from SAR images are a useful source of data for validating hydraulic models of river flood flow. The accuracy of such maps is reduced by a number of factors, including changes in returns from the water surface caused by different meteorological conditions and the presence of emergent vegetation. The paper describes how improved accuracy can be achieved by modifying an existing flood extent delineation algorithm to use airborne laser altimetry (LiDAR) as well as SAR data. The LiDAR data provide an additional constraint that waterline (land-water boundary) heights should vary smoothly along the flooded reach. The method was tested on a SAR image of a flood for which contemporaneous aerial photography existed, together with LiDAR data of the un-flooded reach. Waterline heights of the SAR flood extent conditioned on both SAR and LiDAR data matched the corresponding heights from the aerial photo waterline significantly more closely than those from the SAR flood extent conditioned only on SAR data.
Resumo:
The Holocene estuarine silts of the Severn Estuary Levels (southwest Britain) are representative of their kind in northwest Europe. They contain two broad types of plant material: particles codeposited with mineral grains from the estuarine water body, and extraneous debris (stems of indigenous prior plants; post depositional root matter) which is difficult to remove completely by physical means. Treatment with hydrogen peroxide before laser granulometry removes all plant material regardless of kind, drastically reduces values for the mean grain size and median size relative to untreated samples, but has little effect on the mode, except for a restricted group of bimodal-platykurtic, medium-coarse silts. It is concluded that, in the case of sediments of the general kind examined, no advantages acrue from the treatment of samples with hydrogen peroxide prior to analysis. Although a discrete rather than continuous variable, values of the mode obtained from untreated sediments are suggested to be acceptable for most purposes where a measure of central tendency is required.
Resumo:
Coral growth rate can be affected by environmental parameters such as seawater temperature, depth, and light intensity. The natural reef environment is also disturbed by human influences such as anthropogenic pollutants, which in Barbados are released close to the reefs. Here we describe a relatively new method of assessing the history of pollution and explain how these effects have influenced the coral communities off the west coast of Barbados. We evaluate the relative impact of both anthropogenic pollutants and natural stresses. Sclerochronology documents framework and skeletal growth rate and records pollution history (recorded as reduced growth) for a suite of sampled Montastraea annularis coral cores. X-radiography shows annual growth band patterns of the corals extending back over several decades and indicates significantly lower growth rate in polluted sites. Results using laser-ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) on the whole sample (aragonite, organic matter, trapped particulate matter, etc.), have shown contrasting concentrations of the trace elements (Cu, Sn, Zn, and Pb) between corals at different locations and within a single coral. Deepwater corals 7 km apart, record different levels of Pb and Sn, suggesting that a current transported the metal pollution in the water. In addition, the 1995 hurricanes are associated with anomalous values for Sn and Cu from most sites. These are believed to result from dispersion of nearshore polluted water. We compared the concentrations of trace elements in the coral growth of particular years to those in the relevant contemporaneous seawater. Mean values for the concentration factor in the coral, relative to the water, ranged from 10 for Cu and Ni to 2.4 and 0.7 for Cd and Zn, respectively. Although the uncertainties are large (60-80%), the coral record enabled us to demonstrate the possibility of calculating a history of seawater pollution for these elements from the 1940s to 1997. Our values were much higher than those obtained from analysis of carefully cleaned coral aragonite; they demonstrate the incorporation of more contamination including that from particulate material as well as dissolved metals.
Resumo:
Airborne laser altimetry has the potential to make frequent detailed observations that are important for many aspects of studying land surface processes. However, the uncertainties inherent in airborne laser altimetry data have rarely been well measured. Uncertainty is often specified as generally as 20cm in elevation, and 40cm planimetric. To better constrain these uncertainties, we present an analysis of several datasets acquired specifically to study the temporal consistency of laser altimetry data, and thus assess its operational value. The error budget has three main components, each with a time regime. For measurements acquired less than 50ms apart, elevations have a local standard deviation in height of 3.5cm, enabling the local measurement of surface roughness of the order of 5cm. Points acquired seconds apart acquire an additional random error due to Differential Geographic Positioning System (DGPS) fluctuation. Measurements made up to an hour apart show an elevation drift of 7cm over a half hour. Over months, this drift gives rise to a random elevation offset between swathes, with an average of 6.4cm. The RMS planimetric error in point location was derived as 37.4cm. We conclude by considering the consequences of these uncertainties on the principle application of laser altimetry in the UK, intertidal zone monitoring.
Extraction of tidal channel networks from aerial photographs alone and combined with laser altimetry
Resumo:
Tidal channel networks play an important role in the intertidal zone, exerting substantial control over the hydrodynamics and sediment transport of the region and hence over the evolution of the salt marshes and tidal flats. The study of the morphodynamics of tidal channels is currently an active area of research, and a number of theories have been proposed which require for their validation measurement of channels over extensive areas. Remotely sensed data provide a suitable means for such channel mapping. The paper describes a technique that may be adapted to extract tidal channels from either aerial photographs or LiDAR data separately, or from both types of data used together in a fusion approach. Application of the technique to channel extraction from LiDAR data has been described previously. However, aerial photographs of intertidal zones are much more commonly available than LiDAR data, and most LiDAR flights now involve acquisition of multispectral images to complement the LiDAR data. In view of this, the paper investigates the use of multispectral data for semiautomatic identification of tidal channels, firstly from only aerial photographs or linescanner data, and secondly from fused linescanner and LiDAR data sets. A multi-level, knowledge-based approach is employed. The algorithm based on aerial photography can achieve a useful channel extraction, though may fail to detect some of the smaller channels, partly because the spectral response of parts of the non-channel areas may be similar to that of the channels. The algorithm for channel extraction from fused LiDAR and spectral data gives an increased accuracy, though only slightly higher than that obtained using LiDAR data alone. The results illustrate the difficulty of developing a fully automated method, and justify the semi-automatic approach adopted.
Resumo:
The study of the morphodynamics of tidal channel networks is important because of their role in tidal propagation and the evolution of salt-marshes and tidal flats. Channel dimensions range from tens of metres wide and metres deep near the low water mark to only 20-30cm wide and 20cm deep for the smallest channels on the marshes. The conventional method of measuring the networks is cumbersome, involving manual digitising of aerial photographs. This paper describes a semi-automatic knowledge-based network extraction method that is being implemented to work using airborne scanning laser altimetry (and later aerial photography). The channels exhibit a width variation of several orders of magnitude, making an approach based on multi-scale line detection difficult. The processing therefore uses multi-scale edge detection to detect channel edges, then associates adjacent anti-parallel edges together to form channels using a distance-with-destination transform. Breaks in the networks are repaired by extending channel ends in the direction of their ends to join with nearby channels, using domain knowledge that flow paths should proceed downhill and that any network fragment should be joined to a nearby fragment so as to connect eventually to the open sea.
Resumo:
Two ongoing projects at ESSC that involve the development of new techniques for extracting information from airborne LiDAR data and combining this information with environmental models will be discussed. The first project in conjunction with Bristol University is aiming to improve 2-D river flood flow models by using remote sensing to provide distributed data for model calibration and validation. Airborne LiDAR can provide such models with a dense and accurate floodplain topography together with vegetation heights for parameterisation of model friction. The vegetation height data can be used to specify a friction factor at each node of a model’s finite element mesh. A LiDAR range image segmenter has been developed which converts a LiDAR image into separate raster maps of surface topography and vegetation height for use in the model. Satellite and airborne SAR data have been used to measure flood extent remotely in order to validate the modelled flood extent. Methods have also been developed for improving the models by decomposing the model’s finite element mesh to reflect floodplain features such as hedges and trees having different frictional properties to their surroundings. Originally developed for rural floodplains, the segmenter is currently being extended to provide DEMs and friction parameter maps for urban floods, by fusing the LiDAR data with digital map data. The second project is concerned with the extraction of tidal channel networks from LiDAR. These networks are important features of the inter-tidal zone, and play a key role in tidal propagation and in the evolution of salt-marshes and tidal flats. The study of their morphology is currently an active area of research, and a number of theories related to networks have been developed which require validation using dense and extensive observations of network forms and cross-sections. The conventional method of measuring networks is cumbersome and subjective, involving manual digitisation of aerial photographs in conjunction with field measurement of channel depths and widths for selected parts of the network. A semi-automatic technique has been developed to extract networks from LiDAR data of the inter-tidal zone. A multi-level knowledge-based approach has been implemented, whereby low level algorithms first extract channel fragments based mainly on image properties then a high level processing stage improves the network using domain knowledge. The approach adopted at low level uses multi-scale edge detection to detect channel edges, then associates adjacent anti-parallel edges together to form channels. The higher level processing includes a channel repair mechanism.