LiDAR mapping of tidal marshes for ecogeomorphological modelling in the TIDE project

The European research project TIDE (Tidal Inlets Dynamics and Environment) is developing and validating coupled models describing the morphological, biological and ecological evolution of tidal environments. The interactions between the physical and biological processes occurring in these regions requires that the system be studied as a whole rather than as separate parts. Extensive use of remote sensing including LiDAR is being made to provide validation data for the modelling. This paper describes the different uses of LiDAR within the project and their relevance to the TIDE science objectives. LiDAR data have been acquired from three different environments, the Venice Lagoon in Italy, Morecambe Bay in England, and the Eden estuary in Scotland. LiDAR accuracy at each site has been evaluated using ground reference data acquired with differential GPS. A semi-automatic technique has been developed to extract tidal channel networks from LiDAR data either used alone or fused with aerial photography. While the resulting networks may require some correction, the procedure does allow network extraction over large areas using objective criteria and reduces fieldwork requirements. The networks extracted may subsequently be used in geomorphological analyses, for example to describe the drainage patterns induced by networks and to examine the rate of change of networks. Estimation of the heights of the low and sparse vegetation on marshes is being investigated by analysis of the statistical distribution of the measured LiDAR heights. Species having different mean heights may be separated using the first-order moments of the height distribution.

Modelling convective processes during the suppressed phase of the a Madden-Julian Oscillation: Comparing single-column models with cloud resolving models

The role of convective processes in moistening the atmosphere during suppressed periods of the suppressed phase of a Madden-Julian oscillation is investigated in cloud-resolving model (CRM) simulations, and the impact of moistening on the subsequent evolution of convection is assessed as part of a Global Energy and Water Cycle Experiment Cloud System Study (GCSS) intercomparison project. The ability of single-column model (SCM) versions of a number of state-of-the-art climate and numerical weather prediction models to capture these convective processes is also evaluated. During the suppressed periods, the CRMs are found to simulate a maximum moistening around 3 km, which is associated with a predominance of shallow convection. All SCMs produce adequate amounts of shallow convection during the suppressed periods, comparable to that seen in CRMs, but the relatively drier SCMs have higher precipitation rates than the relatively wetter SCMs and CRMs. The relatively drier SCMs dry, rather than moisten, the lower troposphere below the melting level. During the transition periods, convective processes act to moisten the atmosphere above the level at which mean advection changes from moistening to drying, despite an overall drying effect for the column. The SCMs capture some essence of this moistening at upper levels. A gradual transition from shallow to deep convection is simulated by the CRMs and the wetter SCMs during the transition periods, but the onset of deep convection is delayed in the drier SCMs. This results in lower precipitation rates for these SCMs during the active periods, although much better agreement exists between the models at this time.

Uses of airborne scanning laser altimetry for river flood modelling and coastal geomorphology

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.

Biogenic nitric oxide emissions from soils: impact on NOx and ozone over West Africa during AMMA (African Monsoon Multidisciplinary Analysis) - Modelling study

Nitrogen oxide biogenic emissions from soils are driven by soil and environmental parameters. The relationship between these parameters and NO fluxes is highly non linear. A new algorithm, based on a neural network calculation, is used to reproduce the NO biogenic emissions linked to precipitations in the Sahel on the 6 August 2006 during the AMMA campaign. This algorithm has been coupled in the surface scheme of a coupled chemistry dynamics model (MesoNH Chemistry) to estimate the impact of the NO emissions on NOx and O3 formation in the lower troposphere for this particular episode. Four different simulations on the same domain and at the same period are compared: one with anthropogenic emissions only, one with soil NO emissions from a static inventory, at low time and space resolution, one with NO emissions from neural network, and one with NO from neural network plus lightning NOx. The influence of NOx from lightning is limited to the upper troposphere. The NO emission from soils calculated with neural network responds to changes in soil moisture giving enhanced emissions over the wetted soil, as observed by aircraft measurements after the passing of a convective system. The subsequent enhancement of NOx and ozone is limited to the lowest layers of the atmosphere in modelling, whereas measurements show higher concentrations above 1000 m. The neural network algorithm, applied in the Sahel region for one particular day of the wet season, allows an immediate response of fluxes to environmental parameters, unlike static emission inventories. Stewart et al (2008) is a companion paper to this one which looks at NOx and ozone concentrations in the boundary layer as measured on a research aircraft, examines how they vary with respect to the soil moisture, as indicated by surface temperature anomalies, and deduces NOx fluxes. In this current paper the model-derived results are compared to the observations and calculated fluxes presented by Stewart et al (2008).

The modelling of electrical current NDT methods and its application to weld testing

Discussion of the numerical modeling of NDT methods based on the potential drop and the disruption of power lines to describe the nature, importance and application of modeling. La 1ère partie est consacrée aux applications aux contrôles par courants de Foucault. The first part is devoted to applications for inspection by eddy currents.