Next Generation Network Real-Time Kinematic Interpolation Segment to Improve the User Accuracy

Ouassou, Mohammed; Jensen, Arne Skov; Gjevestad, Jon Glenn Omholt; Kristiansen, Oddgeir

doi:10.1155/2015/346498

Cited by 8 publications

(8 citation statements)

References 18 publications

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“…An adjustment of baselines and 3-D positions of individual benchmarks was used to compute final heights with typical standard errors of less than 1 cm. The second dataset consists of 132 points observed with the Norwegian real-time kinematic GNSS network service, known as CPOS (Ouassou et al, 2015). The test field covered an area of approximately 0.2 km 2 and was located in typical Norwegian coastal terrain including exposed bedrock, slopes, and beaches covered with boulders.…”

Section: Accuracy Of the Demmentioning

confidence: 99%

High-accuracy coastal flood mapping for Norway using lidar data

Breili

Simpson

Klokkervold

et al. 2020

Nat. Hazards Earth Syst. Sci.

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Abstract. Using new high-accuracy light detection and ranging (lidar) elevation data we generate coastal flooding maps for Norway. Thus far, we have mapped ∼80 % of the coast, for which we currently have data of sufficient accuracy to perform our analysis. Although Norway is generally at low risk from sea level rise largely owing to its steep topography and land uplift due to glacial isostatic adjustment, the maps presented here show that, on local scales, many parts of the coast are potentially vulnerable to flooding. There is a considerable amount of infrastructure at risk along the relatively long and complicated coastline. Nationwide we identify a total area of 400 km2, 105 000 buildings, and 510 km of roads that are at risk of flooding from a 200-year storm surge event at present. These numbers will increase to 610 km2, 137 000, and 1340 km with projected sea level rise to 2090 (95th percentile of RCP8.5 as recommended in planning). We find that some of our results are likely biased high owing to erroneous mapping (at least for lower water levels close to the tidal datum which delineates the coastline). A comparison of control points from different terrain types indicates that the elevation model has a root-mean-square error of 0.26 m and is the largest source of uncertainty in our mapping method. The coastal flooding maps and associated statistics are freely available, and alongside the development of coastal climate services, will help communicate the risks of sea level rise and storm surge to stakeholders. This will in turn aid coastal management and climate adaptation work in Norway.

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Section: Accuracy Of the Demmentioning

confidence: 99%

High-accuracy coastal flood mapping for Norway using lidar data

Breili

Simpson

Klokkervold

et al. 2020

Nat. Hazards Earth Syst. Sci.

View full text Add to dashboard Cite

show abstract

“…An adjustment of baselines and 3D positions of individual benchmarks was used to compute final heights with typical standard errors of less than 1 cm. The second data 380 set consists of 132 points observed with the Norwegian real time kinematic GNSS network service, known as CPOS (Ouassou et al, 2015). The test field covered an area of approximately 0.2 km 2 and was located in typical Norwegian coastal terrain including solid bedrock, slopes, and beaches covered with boulders.…”

Section: Accuracy Of the Dem 370mentioning

confidence: 99%

High accuracy coastal flood mapping for Norway using LiDAR data

Breili¹,

Simpson²,

Klokkervold³

et al. 2019

Preprint

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Using new high accuracy Light Detection and Ranging elevation data we generate coastal flooding maps for Norway.Thus far, we have mapped ∼80% of the coast, for which we currently have data of sufficient accuracy to perform our analysis.Although Norway is generally at low risk from sea-level rise largely owing to its steep topography, the maps presented here show that on local scales, many parts of the coast are potentially vulnerable to flooding. There is a considerable amount of infrastructure at risk along the relatively long and complicated coastline. Nationwide we identify a total area of 400 km 2 , 5 105,000 buildings, and 510 km of roads that are at risk of flooding from a 200 year storm-surge event at present. These numbers will increase to 610 km 2 , 137,000, and 1340 km with projected sea-level rise to 2090 (95th percentile of RCP8.5 as recommended in planning). We find that some of our results are likely biased high owing to erroneous mapping (at least for lower water levels close to the tidal datum which delineates the coastline). A comparison of control points from different terrain types indicates that the elevation model has a root mean square error of 0.26 m and is the largest source of uncertainty in 10 our mapping method. The coastal flooding maps and associated statistics are freely available, and alongside the development of coastal climate services, will help communicate the risks of sea-level rise and storm surge to stakeholders. This will in turn aid coastal management and climate adaption work in Norway. Introduction 15Higher sea levels driven by anthropogenic climate change present a large challenge for many coastal communities. There are numerous negative consequences of sea-level rise, i.e., flooding, loss of life and land, damage and loss of buildings and infrastructure, increased erosion, saltwater intrusion, changing ecosystems, and reduced biodiversity (see e.g., Nicholls, 2010;Nicholls and Cazenave, 2010). The consequences of increasing sea level are large and many because the coastal zones are densely populated areas, have a large population growth, and are economically important. 20Compared to many other coastal nations, Norway is at relatively low physical vulnerability to accelerating sea-level rise (Aunan and Romstad, 2008). Norway has a very rugged coast with fjords, inlets, and many thousands of islands. The coastline 1 https://doi.is relatively long being around 103,000 km in length (Kartverket, 2019a) and is largely characterized by steep topography and an exposed bedrock that is resistant to erosion. An important component of sea-level change for Norway is vertical land motion (VLM) due to glacial isostatic adjustment. Regional differences in VLM essentially explain differences in observed sea-level 25 changes along the coast. Observations from Norway's tide gauge network show that relative sea level fell over the recent period 1984-2014 around Oslo and in the middle of Norway, where VLM is largest. Whereas other parts of the coast experienced a limited sea-level rise (Br...

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“…Then an interpolation/smoothing scheme is applied to generate the NRTK corrections for the user location. For information on how to avoid loss of information under interpolation of NRTK data, the interested reader is referred to [19]. The NRTK corrections are then transmitted to users who can perform real-time positioning with an accuracy at the cm-level [20].…”

Section: Introductionmentioning

confidence: 99%

Network real-time kinematic data screening by means of multivariate statistical analysis

Ouassou

Jensen

2019

SN Appl. Sci.

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We introduce a novel approach to the computation of network real-time kinematic (NRTK) data integrity, which can be used to improve the position accuracy for a rover receiver in the field. Our approach is based on multivariate statistical analysis and stochastic generalized linear model (SGLM). The new approach has an important objective of alarming GNSS network RTK carrier-phase users in case of an error by introducing a multi-layered approach. The network average error corrections and the corresponding variance fields are computed from the data, while the squared Mahalanobis distance (SMD) and Mahalanobis depth (MD) are used as test statistics to detect and remove data from satellites that supply inaccurate data. The variance-covariance matrices are also inspected and monitored to avoid the Heywood effect, i.e. negative variance generated by the processing filters. The quality checks were carried out at both the system and user levels in order to reduce the impact of extreme events on the rover position estimates. The SGLM is used to predict the user carrier-phase and code error statistics. Finally, we present analyses of real-world data sets to establish the practical viability of the proposed methods.

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Next Generation Network Real-Time Kinematic Interpolation Segment to Improve the User Accuracy

Cited by 8 publications

References 18 publications

High-accuracy coastal flood mapping for Norway using lidar data

High-accuracy coastal flood mapping for Norway using lidar data

High accuracy coastal flood mapping for Norway using LiDAR data

Network real-time kinematic data screening by means of multivariate statistical analysis

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