12 resultados para GPS Based Aerial Triangulation

em Publishing Network for Geoscientific


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An autonomous vessel, the Offshore Sensing Sailbuoy, was used for wave measurements near the Ekofisk oil platform complex in the North Sea (56.5 N, 3.2 E, operated by ConocoPhilllips) from 6 to 20 November 2015. Being 100% wind propelled, the Sailbuoy has two-way communication via the Iridium network and has the capability for missions of six months or more. It has previously been deployed in the Arctic, Norwegian Sea and the Gulf of Mexico, but this was the first real test for wave measurements. During the campaign it held position about 20km northeast of Ekofisk (on the lee side) during rough conditions. Mean wind speed measured at Ekofisk during the campaign was near 9.8m/s, with a maximum of 20.4m/s, with wind mostly from south and south west. A Datawell MOSE G1000 GPS based 2Hz wave sensor was mounted on the Sailbuoy. Mean significant wave height (Hs 1hr) measured was 3m, whereas maximum Hs was 6m. Mean wave period was 7.7s, while maximum wave height, Hmax, was 12.6m. These measurements have been compared with non-directional Waverider observations at the Ekofisk complex. Mean Hs at Ekofisk was 3.1m, while maximum Hs was 6.5m. Nevertheless, the correlation between the two measurements was high (97%). Spectra comparison was also good, except for low Hs (~1m), where the motion of the vessel seemed to influence the measurements. Nevertheless, the Sailbuoy performed well during this campaign, and results suggests that it is a suitable platform for wave measurements in rather rough sea conditions.

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We analyze 2006-2009 data from four continuous Global Positioning System (GPS) receivers located between 5 and 150 km from the glacier Jakobshavn Isbrae, West Greenland. The GPS stations were established on bedrock to determine the vertical crustal motion due to the unloading of ice from Jakobshavn Isbrae. All stations experienced uplift, but the uplift rate at Kangia North, only 5 km from the glacier front, was about 10 mm/yr larger than the rate at Ilulissat, located only ~45 km further away. This suggests that most of the uplift is due to the unloading of the Earth's surface as Jakobshavn thins and loses mass. Our estimate of Jakobshavn's contribution to uplift rates at Kangia North and Ilulissat are 14.6 ± 1.7 mm/yr and 4.9 ± 1.1 mm/yr, respectively. The observed rates are consistent with a glacier thinning model based on repeat altimeter surveys from NASA's Airborne Topographic Mapper (ATM), which shows that Jakobshavn lost mass at an average rate of 22 ± 2 km**3/yr between 2006 and 2009. At Kangia North and Ilulissat, the predicted uplift rates computed using thinning estimates from the ATM laser altimetry are 12.1 ± 0.9 mm/yr and 3.2 ± 0.3 mm/yr, respectively. The observed rates are slightly larger than the predicted rates. The fact that the GPS uplift rates are much larger closer to Jakobshavn than further away, and are consistent with rates inferred using the ATM-based glacier thinning model, shows that GPS measurements of crustal motion are a potentially useful method for assessing ice-mass change models.

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As part of the CryoSat Cal/Val activities and the pre-site survey for an ice core drilling contributing to the International Partnerships in Ice Core Sciences (IPICS), ground based kinematic GPS measurements were conducted in early 2007 in the vicinity of the German overwintering station Neumayer (8.25° W and 70.65° S). The investigated area comprises the regions of the ice tongues Halvfarryggen and Søråsen, which rise from the Ekströmisen to a maximum of about 760 m surface elevation, and have an areal extent of about 100 km x 50 km each. Available digital elevation models (DEMs) from radar altimetry and the Antarctic Digital Database show elevation differences of up to hundreds of meters in this region, which necessitated an accurate survey of the conditions on-site. An improved DEM of the Ekströmisen surroundings is derived by a combination of highly accurate ground based GPS measurements, satellite derived laser altimetry data (ICESat), airborne radar altimetry (ARA), and radio echo sounding (RES). The DEM presented here achieves a vertical accuracy of about 1.3 m and can be used for improved ice dynamic modeling and mass balance studies.

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Interpretation of ice-core records requires accurate knowledge of the past and present surface topography and stress-strain fields. The European Project for Ice Coring in Antarctica (EPICA) drilling site (0.0684° E and 75.0025° S, 2891.7 m) in Dronning Maud Land, Antarctica, is located in the immediate vicinity of a transient and splitting ice divide. A digital elevation model is determined from the combination of kinematic GPS measurements with the GLAS12 data sets from the ICESat satellite. Based on a network of stakes, surveyed with static GPS, the velocity field around the EDML drilling site is calculated. The annual mean velocity magnitude of 12 survey points amounts to 0.74 m/a. Flow directions mainly vary according to their distance from the ice divide. Surface strain rates are determined from a pentagon-shaped stake network with one center point, close to the drilling site. The strain field is characterised by along flow compression, lateral dilatation, and vertical layer thinning.

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The knowledge of ice sheet surface topography and the location of the ice divides are essential for ice dynamic modeling. An improved digital elevation model (DEM) of Dronning Maud Land (DML), Antarctica, is presented in this paper. It is based on ground-based kinematic GPS profiles, airborne radar altimetry, and data of the airborne radio-echo sounding system, as well as spaceborne laser altimetry from NASA's Ice, Cloud and land Elevation Satellite (ICESat). The accuracy of ICESat ice sheet altimetry data in the area of investigation is discussed. The location of the ice divides is derived from aspect calculation of the topography and is verified with several velocity data derived from repeated static GPS measurements.

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Approximately 18,400 km**2 of seagrass habitat has been mapped within the coastal waters (<15 m) of Queensland (Australia) between November 1984 and June 2010. The total seagrass meadow distribution was calculated by merging maps from 115 separate mapping surveys (varying locations and dates). Due to tropical seagrass dynamism, meadow distribution can change seasonally and between years, and as a consequence, the composite represents the maximum area of seabed where seagrass has been observed/recorded. Mapping survey methodologies followed standardised global seagrass research methods (McKenzie et al. 2001) where the presence of seagrass was determined from in situ visual assessment of the seabed by either divers or drop cameras at GPS marked positions. Seagrass meadow boundaries were determined based on the positions of survey sites and the presence of seagrass, coupled with depth contours and remote sensing (e.g. aerial photography) where available. The merged meadow boundary accuracy was dependent on the original survey maps and varied from 10-100 m. The resulting composite seagrass distribution was saved as an ArcMap polygon shapefile, and projected to Geocentric Datum of Australia GDA94.

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Monitoring the impact of sea storms on coastal areas is fundamental to study beach evolution and the vulnerability of low-lying coasts to erosion and flooding. Modelling wave runup on a beach is possible, but it requires accurate topographic data and model tuning, that can be done comparing observed and modeled runup. In this study we collected aerial photos using an Unmanned Aerial Vehicle after two different swells on the same study area. We merged the point cloud obtained with photogrammetry with multibeam data, in order to obtain a complete beach topography. Then, on each set of rectified and georeferenced UAV orthophotos, we identified the maximum wave runup for both events recognizing the wet area left by the waves. We then used our topography and numerical models to simulate the wave runup and compare the model results to observed values during the two events. Our results highlight the potential of the methodology presented, which integrates UAV platforms, photogrammetry and Geographic Information Systems to provide faster and cheaper information on beach topography and geomorphology compared with traditional techniques without losing in accuracy. We use the results obtained from this technique as a topographic base for a model that calculates runup for the two swells. The observed and modeled runups are consistent, and open new directions for future research.

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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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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