934 resultados para Radar remote sensing, SAR, Along Track Interferometry, Traffic, Transport geography, traffic simulation, statistical pattern recognition


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Airborne Light Detection and Ranging (LIDAR) technology has become the primary method to derive high-resolution Digital Terrain Models (DTMs), which are essential for studying Earth's surface processes, such as flooding and landslides. The critical step in generating a DTM is to separate ground and non-ground measurements in a voluminous point LIDAR dataset, using a filter, because the DTM is created by interpolating ground points. As one of widely used filtering methods, the progressive morphological (PM) filter has the advantages of classifying the LIDAR data at the point level, a linear computational complexity, and preserving the geometric shapes of terrain features. The filter works well in an urban setting with a gentle slope and a mixture of vegetation and buildings. However, the PM filter often removes ground measurements incorrectly at the topographic high area, along with large sizes of non-ground objects, because it uses a constant threshold slope, resulting in "cut-off" errors. A novel cluster analysis method was developed in this study and incorporated into the PM filter to prevent the removal of the ground measurements at topographic highs. Furthermore, to obtain the optimal filtering results for an area with undulating terrain, a trend analysis method was developed to adaptively estimate the slope-related thresholds of the PM filter based on changes of topographic slopes and the characteristics of non-terrain objects. The comparison of the PM and generalized adaptive PM (GAPM) filters for selected study areas indicates that the GAPM filter preserves the most "cut-off" points removed incorrectly by the PM filter. The application of the GAPM filter to seven ISPRS benchmark datasets shows that the GAPM filter reduces the filtering error by 20% on average, compared with the method used by the popular commercial software TerraScan. The combination of the cluster method, adaptive trend analysis, and the PM filter allows users without much experience in processing LIDAR data to effectively and efficiently identify ground measurements for the complex terrains in a large LIDAR data set. The GAPM filter is highly automatic and requires little human input. Therefore, it can significantly reduce the effort of manually processing voluminous LIDAR measurements.

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Underwater sound is very important in the field of oceanography where it is used for remote sensing in much the same way that radar is used in atmospheric studies. One way to mathematically model sound propagation in the ocean is by using the parabolic-equation method, a technique that allows range dependent environmental parameters. More importantly, this method can model sound transmission where the source emits either a pure tone or a short pulse of sound. Based on the parabolic approximation method and using the split-step Fourier algorithm, a computer model for underwater sound propagation was designed and implemented. This computer model differs from previous models in its use of the interactive mode, structured programming, modular design, and state-of-the-art graphics displays. In addition, the model maximizes the efficiency of computer time through synchronization of loosely coupled dual processors and the design of a restart capability. Since the model is designed for adaptability and for users with limited computer skills, it is anticipated that it will have many applications in the scientific community.

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Large-extent vegetation datasets that co-occur with long-term hydrology data provide new ways to develop biologically meaningful hydrologic variables and to determine plant community responses to hydrology. We analyzed the suitability of different hydrological variables to predict vegetation in two water conservation areas (WCAs) in the Florida Everglades, USA, and developed metrics to define realized hydrologic optima and tolerances. Using vegetation data spatially co-located with long-term hydrological records, we evaluated seven variables describing water depth, hydroperiod length, and number of wet/dry events; each variable was tested for 2-, 4- and 10-year intervals for Julian annual averages and environmentally-defined hydrologic intervals. Maximum length and maximum water depth during the wet period calculated for environmentally-defined hydrologic intervals over a 4-year period were the best predictors of vegetation type. Proportional abundance of vegetation types along hydrological gradients indicated that communities had different realized optima and tolerances across WCAs. Although in both WCAs, the trees/shrubs class was on the drier/shallower end of hydrological gradients, while slough communities occupied the wetter/deeper end, the distribution ofCladium, Typha, wet prairie and Salix communities, which were intermediate for most hydrological variables, varied in proportional abundance along hydrologic gradients between WCAs, indicating that realized optima and tolerances are context-dependent.

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Drillhole-determined sea-ice thickness was compared with values derived remotely using a portable small-offset loop-loop steady state electromagnetic (EM) induction device during expeditions to Fram Strait and the Siberian Arctic, under typical winter and summer conditions. Simple empirical transformation equations are derived to convert measured apparent conductivity into ice thickness. Despite the extreme seasonal differences in sea-ice properties as revealed by ice core analysis, the transformation equations vary little for winter and summer. Thus, the EM induction technique operated on the ice surface in the horizontal dipole mode yields accurate results within 5 to 10% of the drillhole determined thickness over level ice in both seasons. The robustness of the induction method with respect to seasonal extremes is attributed to the low salinity of brine or meltwater filling the extensive pore space in summer. Thus, the average bulk ice conductivity for summer multiyear sea ice derived according to Archie's law amounts to 23 mS/m compared to 3 mS/m for winter conditions. These mean conductivities cause only minor differences in the EM response, as is shown by means of 1-D modeling. However, under summer conditions the range of ice conductivities is wider. Along with the widespread occurrence of surface melt ponds and freshwater lenses underneath the ice, this causes greater scatter in the apparent conductivity/ice thickness relation. This can result in higher deviations between EM-derived and drillhole determined thicknesses in summer than in winter.

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Underwater photo-transect surveys were conducted on September 23-27, 2007 at different sections of the reef flat, reef crest and reef slope in Heron Reef. This survey was done by swimming along pre-defined transect sites and taking a picture of the bottom substrate parallel to the bottom at constant vertical distance (30cm) every two to three metres. A total of 3,586 benthic photos were taken. A floating GPS setup connected to the swimmer/diver by a line enabled recording of coordinates of transect surveys. Approximation of the coordinates for each benthic photo was based on the photo timestamp and GPS coordinate time stamp, using GPS Photo Link Software. Coordinates of each photo were interpolated by finding the the gps coordinates that were logged at a set time before and after the photo was captured. The output of this process was an ArcMap point shapefile, a Google Earth KML file and a thumbnail of each benthic photo taken. The data in the ArcMap shapefile and in the Google Earth KML file consisted of the approximated coordinate of each benthic photo taken during the survey. Using the GPS Photo Link extension within the ArcMap environment, opening the ArcMap shapefile will enable thumbnail to be displayed on the associated benthic cover photo whenever hovering with the mouse over a point on the transect. By downloading the GPSPhotoLink software from the www.geospatialexperts.com, and installing it as a trial version the ArcMap exstension will be installed in the ArcMap environment.

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Underwater georeferenced photo-transect surveys were conducted on December 10-15, 2011 at various sections of the reef at Lizard Island, Great Barrier Reef. For this survey a snorkeler or diver swam over the bottom while taking photos of the benthos at a set height using a standard digital camera and towing a GPS in a surface float which logged the track every five seconds. A standard digital compact camera was placed in an underwater housing and fitted with a 16 mm lens which provided a 1.0 m x 1.0 m footprint, at 0.5 m height above the benthos. Horizontal distance between photos was estimated by three fin kicks of the survey diver/snorkeler, which corresponded to a surface distance of approximately 2.0 - 4.0 m. The GPS was placed in a dry-bag and logged the position as it floated at the surface while being towed by the photographer. A total of 5,735 benthic photos were taken. A floating GPS setup connected to the swimmer/diver by a line enabled recording of coordinates of each benthic photo (Roelfsema 2009). Approximation of coordinates of each benthic photo was conducted based on the photo timestamp and GPS coordinate time stamp, using GPS Photo Link Software (www.geospatialexperts.com). Coordinates of each photo were interpolated by finding the GPS coordinates that were logged at a set time before and after the photo was captured. Benthic or substrate cover data was derived from each photo by randomly placing 24 points over each image using the Coral Point Count for Microsoft Excel program (Kohler and Gill, 2006). Each point was then assigned to 1 of 78 cover types, which represented the benthic feature beneath it. Benthic cover composition summary of each photo scores was generated automatically using CPCE program. The resulting benthic cover data of each photo was linked to GPS coordinates, saved as an ArcMap point shapefile, and projected to Universal Transverse Mercator WGS84 Zone 55 South.

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Underwater georeferenced photo-transect surveys were conducted on October 3-7, 2012 at various sections of the reef and lagoon at Lizard Island, Great Barrier Reef. For this survey a snorkeler swam while taking photos of the benthos at a set distance from the benthos using a standard digital camera and towing a GPS in a surface float which logged the track every five seconds. A Canon G12 digital camera was placed in a Canon underwater housing and photos were taken at 1 m height above the benthos. Horizontal distance between photos was estimated by three fin kicks of the survey snorkeler, which corresponded to a surface distance of approximately 2.0 - 4.0 m. The GPS was placed in a dry bag and logged the position at the surface while being towed by the photographer (Roelfsema, 2009). A total of 1,265 benthic photos were taken. Approximation of coordinates of each benthic photo was conducted based on the photo timestamp and GPS coordinate time stamp, using GPS Photo Link Software (www.geospatialexperts.com). Coordinates of each photo were interpolated by finding the GPS coordinates that were logged at a set time before and after the photo was captured. Benthic or substrate cover data was derived from each photo by randomly placing 24 points over each image using the Coral Point Count for Microsoft Excel program (Kohler and Gill, 2006). Each point was then assigned to 1 of 79 cover types, which represented the benthic feature beneath it. Benthic cover composition summary of each photo scores was generated automatically using CPCE program. The resulting benthic cover data of each photo was linked to GPS coordinates, saved as an ArcMap point shapefile, and projected to Universal Transverse Mercator WGS84 Zone 55 South.

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Surveying habitats critical to the survival of grey nurse sharks in South-East Queensland has mapped critical habitats, gathered species inventories and developed protocols for ecological monitoring of critical habitats in southern Queensland. This information has assisted stakeholders with habitat definition and effective management. In 2002 members of UniDive applied successfully for World Wide Fund for Nature, Threatened Species Network funds to map the critical Grey Nurse Shark Habitats in south east Queensland. UniDive members used the funding to survey, from the boats of local dive operators, Wolf Rock at Double Island Point, Gotham, Cherub's Cave, Henderson's Rock and China Wall at North Moreton and Flat Rock at Point Look Out during 2002 and 2003. These sites are situated along the south east Queensland coast and are known to be key Grey Nurse Shark aggregation sites. During the project UniDive members were trained in mapping and survey techniques that include identification of fish, invertebrates and substrate types. Training was conducted by experts from the University of Queensland (Centre of Marine Studies, Biophysical Remote Sensing) and the Queensland Parks and Wildlife Service who are also UniDive members. The monitoring methods (see methods) are based upon results of the UniDive Coastcare project from 2002, the international established Reef Check program and research conducted by Biophysical Remote Sensing and the Centre of Marine Studies. Habitats were mapped using a combination of towed GPS photo transects, aerial photography, bathymetry surveys and expert knowledge. This data provides georeferenced information regarding the major features of each of Sites mapped including Wolf Rock

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Transects of a Remotely Operated Vehicle (ROV) providing sea-bed videos and photographs were carried out during POLARSTERN expedition ANT-XVII/3 focussing on the ecology of benthic assemblages on the Antarctic shelf in the South-Eastern Weddell Sea. The ROV-system sprint 103 was equiped with two video- and one still camera, lights, flash-lights, compass, and parallel lasers providing a scale in the images, a tether-management system (TMS), a winch, and the board units. All cameras used the same main lense and could be tilted. Videos were recorded in Betacam-format and (film-)slides were made by decision of the scientific pilot. The latter were mainly made under the aspect to improve the identification of organisms depicted in the videos because the still photographs have a much higher optical resolution than the videos. In the photographs species larger than 3 mm, in the videos larger than 1 cm are recognisable and countable. Under optimum conditions the transects were strait; the speed and direction of the ROV were determined by the drift of the ship in the coastal current, since both, the ship and the ROV were used as a drifting system; the option to operate the vehicle actively was only used to avoide obstacles and to reach at best a distance of only approximately 30 cm to the sea-floor. As a consequence the width of the photographs in the foreground is approximately 50 cm. Deviations from this strategy resulted mainly from difficult ice- and weather conditions but also from high current velocity and local up-welling close to the sea-bed. The sea-bed images provide insights into the general composition of key species, higher systematic groups and ecological guilds. Within interdisciplinary approaches distributions of assemblages can be attributed to environmental conditions such as bathymetry, sediment characteristics, water masses and current regimes. The images also contain valuable information on how benthic species are associated to each other. Along the transects, small- to intermediate-scaled disturbances, e.g. by grounding icebergs were analysed and further impact to the entire benthic system by local succession of recolonisation was studied. This information can be used for models predicting the impact of climate change to benthic life in the Southern Ocean. All these approaches contribute to a better understanding of the fiunctioning of the benthic system and related components of the entire Antarctic marine ecosystem. Despite their scientific value the imaging methods meet concerns about the protection of sensitive Antarctic benthic systems since they are non-invasive and they also provide valuable material for education and outreach purposes.

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Seagrass meadows are important marine carbon sinks, yet they are threatened and declining worldwide. Seagrass management and conservation requires adequate understanding of the physical and biological factors determining carbon content in seagrass sediments. Here, we identified key factors that influence carbon content in seagrass meadows across several environmental gradients in Moreton Bay, SE Queensland. Sampling was conducted in two regions: (1) Canopy Complexity, 98 sites on the Eastern Banks, where seagrass canopy structure and species composition varied while turbidity was consistently low; and (2) Turbidity Gradient, 11 locations across the entire bay, where turbidity varied among sampling locations. Sediment organic carbon content and seagrass structural complexity (shoot density, leaf area, and species specific characteristics) were measured from shallow sediment and seagrass biomass cores at each location, respectively. Environmental data were obtained from empirical measurements (water quality) and models (wave height). The key factors influencing carbon content in seagrass sediments were seagrass structural complexity, turbidity, water depth, and wave height. In the Canopy Complexity region, carbon content was higher for shallower sites and those with higher seagrass structural complexity. When turbidity varied along the Turbidity Gradient, carbon content was higher at sites with high turbidity. In both regions carbon content was consistently higher in sheltered areas with lower wave height. Seagrass canopy structure, water depth, turbidity, and hydrodynamic setting of seagrass meadows should therefore be considered in conservation and management strategies that aim to maximize sediment carbon content.

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Over 50% of the world's population live within 3. km of rivers and lakes highlighting the on-going importance of freshwater resources to human health and societal well-being. Whilst covering c. 3.5% of the Earth's non-glaciated land mass, trends in the environmental quality of the world's standing waters (natural lakes and reservoirs) are poorly understood, at least in comparison with rivers, and so evaluation of their current condition and sensitivity to change are global priorities. Here it is argued that a geospatial approach harnessing existing global datasets, along with new generation remote sensing products, offers the basis to characterise trajectories of change in lake properties e.g., water quality, physical structure, hydrological regime and ecological behaviour. This approach furthermore provides the evidence base to understand the relative importance of climatic forcing and/or changing catchment processes, e.g. land cover and soil moisture data, which coupled with climate data provide the basis to model regional water balance and runoff estimates over time. Using examples derived primarily from the Danube Basin but also other parts of the World, we demonstrate the power of the approach and its utility to assess the sensitivity of lake systems to environmental change, and hence better manage these key resources in the future.

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Permanent water bodies not only store dissolved CO2 but are essential for the maintenance of wetlands in their proximity. From the viewpoint of greenhouse gas (GHG) accounting wetland functions comprise sequestration of carbon under anaerobic conditions and methane release. The investigated area in central Siberia covers boreal and sub-arctic environments. Small inundated basins are abundant on the sub-arctic Taymir lowlands but also in parts of severe boreal climate where permafrost ice content is high and feature important freshwater ecosystems. Satellite radar imagery (ENVISAT ScanSAR), acquired in summer 2003 and 2004, has been used to derive open water surfaces with 150 m resolution, covering an area of approximately 3 Mkm**2. The open water surface maps were derived using a simple threshold-based classification method. The results were assessed with Russian forest inventory data, which includes detailed information about water bodies. The resulting classification has been further used to estimate the extent of tundra wetlands and to determine their importance for methane emissions. Tundra wetlands cover 7% (400,000 km**2) of the study region and methane emissions from hydromorphic soils are estimated to be 45,000 t/d for the Taymir peninsula.

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This work represents an original contribution to the methodology for ecosystem models' development as well as the rst attempt of an end-to-end (E2E) model of the Northern Humboldt Current Ecosystem (NHCE). The main purpose of the developed model is to build a tool for ecosystem-based management and decision making, reason why the credibility of the model is essential, and this can be assessed through confrontation to data. Additionally, the NHCE exhibits a high climatic and oceanographic variability at several scales, the major source of interannual variability being the interruption of the upwelling seasonality by the El Niño Southern Oscillation, which has direct e ects on larval survival and sh recruitment success. Fishing activity can also be highly variable, depending on the abundance and accessibility of the main shery resources. This context brings the two main methodological questions addressed in this thesis, through the development of an end-to-end model coupling the high trophic level model OSMOSE to the hydrodynamics and biogeochemical model ROMS-PISCES: i) how to calibrate ecosystem models using time series data and ii) how to incorporate the impact of the interannual variability of the environment and shing. First, this thesis highlights some issues related to the confrontation of complex ecosystem models to data and proposes a methodology for a sequential multi-phases calibration of ecosystem models. We propose two criteria to classify the parameters of a model: the model dependency and the time variability of the parameters. Then, these criteria along with the availability of approximate initial estimates are used as decision rules to determine which parameters need to be estimated, and their precedence order in the sequential calibration process. Additionally, a new Evolutionary Algorithm designed for the calibration of stochastic models (e.g Individual Based Model) and optimized for maximum likelihood estimation has been developed and applied to the calibration of the OSMOSE model to time series data. The environmental variability is explicit in the model: the ROMS-PISCES model forces the OSMOSE model and drives potential bottom-up e ects up the foodweb through plankton and sh trophic interactions, as well as through changes in the spatial distribution of sh. The latter e ect was taken into account using presence/ absence species distribution models which are traditionally assessed through a confusion matrix and the statistical metrics associated to it. However, when considering the prediction of the habitat against time, the variability in the spatial distribution of the habitat can be summarized and validated using the emerging patterns from the shape of the spatial distributions. We modeled the potential habitat of the main species of the Humboldt Current Ecosystem using several sources of information ( sheries, scienti c surveys and satellite monitoring of vessels) jointly with environmental data from remote sensing and in situ observations, from 1992 to 2008. The potential habitat was predicted over the study period with monthly resolution, and the model was validated using quantitative and qualitative information of the system using a pattern oriented approach. The nal ROMS-PISCES-OSMOSE E2E ecosystem model for the NHCE was calibrated using our evolutionary algorithm and a likelihood approach to t monthly time series data of landings, abundance indices and catch at length distributions from 1992 to 2008. To conclude, some potential applications of the model for shery management are presented and their limitations and perspectives discussed.