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S.E. Vos
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1
The TU Delft has acquired a UAV LiDAR system and can be used to acquire an 3D point cloud of the terrain below the system. It is of interest how such a flight mission would be best performed and what the corresponding quality would be. Current free software provided limited data quality estimation and mission planning support for the DJI Matrice 300 RTK and Yellowscan Mapper+ UAV LiDAR system. For these reasons an open source flight planner tool has been created. This tool does require the DJI Pilot 2 application and can for this reason only be used with DJI UAVs. It is optimized for the Yellowscan Mapper+ LiDAR module.
To analyze the quality of the data, two types of point cloud quality methods have been performed: comparison of targets in the point cloud to GNSS measurements, referred to the target analysis, and based on comparisons to itself for different acquisition times on the same location, referred to as the overlap analysis. For the target analysis an automatic, LiDAR intensity based method was developed, for determining target coordinates. Furthermore, target coordinates where detected manually based on image projected RGB data in the point cloud. By comparing these target coordinates to the reference GNSS target measurements, the combined GNSS and point cloud error can be estimated separate from the target fitting errors. It was found that the combined point cloud and GNSS error is likely larger than the fitting errors in up direction up to 70m flying height. This might allow for study of the point cloud error in up direction, with this method.
The presented overlap method can be used when no other reference data is available. This method divides the data in horizontal grid cells. The data in each grid cell is divided in time groups. For each time group a PCA plane is fitted and used to estimate the height in the horizontal center of the grid cell. By comparing heights between different time groups in the same grid cell, the height precision can be studied. With this method two types of overlaps are found. Within flight strips and between flight strips. The overlaps within flight strips seem to have a strong relation with the considered time difference length. This is likely caused by a combination of IMU and scan geometry errors. The overlaps between flight strips do not seem to have such a relation. This is likely caused by a combination of strip adjustment errors and possible GNSS errors. The found estimated standard deviations, up to a flying height of 70m, are generally below 17mm. It was found that flights above 70m seemed to perform significantly worse. Furthermore, grass resulted in larger estimated standard deviations than expected for low flights. This is likely caused by the ability of the scanner to measure the 3D shape of the grass leaves for lower flying heights and not for larger flying heights.
...
To analyze the quality of the data, two types of point cloud quality methods have been performed: comparison of targets in the point cloud to GNSS measurements, referred to the target analysis, and based on comparisons to itself for different acquisition times on the same location, referred to as the overlap analysis. For the target analysis an automatic, LiDAR intensity based method was developed, for determining target coordinates. Furthermore, target coordinates where detected manually based on image projected RGB data in the point cloud. By comparing these target coordinates to the reference GNSS target measurements, the combined GNSS and point cloud error can be estimated separate from the target fitting errors. It was found that the combined point cloud and GNSS error is likely larger than the fitting errors in up direction up to 70m flying height. This might allow for study of the point cloud error in up direction, with this method.
The presented overlap method can be used when no other reference data is available. This method divides the data in horizontal grid cells. The data in each grid cell is divided in time groups. For each time group a PCA plane is fitted and used to estimate the height in the horizontal center of the grid cell. By comparing heights between different time groups in the same grid cell, the height precision can be studied. With this method two types of overlaps are found. Within flight strips and between flight strips. The overlaps within flight strips seem to have a strong relation with the considered time difference length. This is likely caused by a combination of IMU and scan geometry errors. The overlaps between flight strips do not seem to have such a relation. This is likely caused by a combination of strip adjustment errors and possible GNSS errors. The found estimated standard deviations, up to a flying height of 70m, are generally below 17mm. It was found that flights above 70m seemed to perform significantly worse. Furthermore, grass resulted in larger estimated standard deviations than expected for low flights. This is likely caused by the ability of the scanner to measure the 3D shape of the grass leaves for lower flying heights and not for larger flying heights.
...
The TU Delft has acquired a UAV LiDAR system and can be used to acquire an 3D point cloud of the terrain below the system. It is of interest how such a flight mission would be best performed and what the corresponding quality would be. Current free software provided limited data quality estimation and mission planning support for the DJI Matrice 300 RTK and Yellowscan Mapper+ UAV LiDAR system. For these reasons an open source flight planner tool has been created. This tool does require the DJI Pilot 2 application and can for this reason only be used with DJI UAVs. It is optimized for the Yellowscan Mapper+ LiDAR module.
To analyze the quality of the data, two types of point cloud quality methods have been performed: comparison of targets in the point cloud to GNSS measurements, referred to the target analysis, and based on comparisons to itself for different acquisition times on the same location, referred to as the overlap analysis. For the target analysis an automatic, LiDAR intensity based method was developed, for determining target coordinates. Furthermore, target coordinates where detected manually based on image projected RGB data in the point cloud. By comparing these target coordinates to the reference GNSS target measurements, the combined GNSS and point cloud error can be estimated separate from the target fitting errors. It was found that the combined point cloud and GNSS error is likely larger than the fitting errors in up direction up to 70m flying height. This might allow for study of the point cloud error in up direction, with this method.
The presented overlap method can be used when no other reference data is available. This method divides the data in horizontal grid cells. The data in each grid cell is divided in time groups. For each time group a PCA plane is fitted and used to estimate the height in the horizontal center of the grid cell. By comparing heights between different time groups in the same grid cell, the height precision can be studied. With this method two types of overlaps are found. Within flight strips and between flight strips. The overlaps within flight strips seem to have a strong relation with the considered time difference length. This is likely caused by a combination of IMU and scan geometry errors. The overlaps between flight strips do not seem to have such a relation. This is likely caused by a combination of strip adjustment errors and possible GNSS errors. The found estimated standard deviations, up to a flying height of 70m, are generally below 17mm. It was found that flights above 70m seemed to perform significantly worse. Furthermore, grass resulted in larger estimated standard deviations than expected for low flights. This is likely caused by the ability of the scanner to measure the 3D shape of the grass leaves for lower flying heights and not for larger flying heights.
To analyze the quality of the data, two types of point cloud quality methods have been performed: comparison of targets in the point cloud to GNSS measurements, referred to the target analysis, and based on comparisons to itself for different acquisition times on the same location, referred to as the overlap analysis. For the target analysis an automatic, LiDAR intensity based method was developed, for determining target coordinates. Furthermore, target coordinates where detected manually based on image projected RGB data in the point cloud. By comparing these target coordinates to the reference GNSS target measurements, the combined GNSS and point cloud error can be estimated separate from the target fitting errors. It was found that the combined point cloud and GNSS error is likely larger than the fitting errors in up direction up to 70m flying height. This might allow for study of the point cloud error in up direction, with this method.
The presented overlap method can be used when no other reference data is available. This method divides the data in horizontal grid cells. The data in each grid cell is divided in time groups. For each time group a PCA plane is fitted and used to estimate the height in the horizontal center of the grid cell. By comparing heights between different time groups in the same grid cell, the height precision can be studied. With this method two types of overlaps are found. Within flight strips and between flight strips. The overlaps within flight strips seem to have a strong relation with the considered time difference length. This is likely caused by a combination of IMU and scan geometry errors. The overlaps between flight strips do not seem to have such a relation. This is likely caused by a combination of strip adjustment errors and possible GNSS errors. The found estimated standard deviations, up to a flying height of 70m, are generally below 17mm. It was found that flights above 70m seemed to perform significantly worse. Furthermore, grass resulted in larger estimated standard deviations than expected for low flights. This is likely caused by the ability of the scanner to measure the 3D shape of the grass leaves for lower flying heights and not for larger flying heights.
The Building with Nature approach has been gaining ground in hydraulic engineering, increasing the importance of understanding the cross-shore morphodynamic processes. The intertidal zone, where marine and aeolian processes come together, is an important link in the transport of sediment from the sea towards the dunes. The grain size distribution affects the sediment supply in the intertidal zone. This research investigates the effect of marine processes on the cross-shore variations of the grain size distribution in the intertidal zone by using a one-dimensional non linear shallow water XBeach model.
The intertidal zone is subject to shoaling, surf and swash zone processes. The grain size influences the beach slope, the initiation of motion and settling to the bed. The cross-shore sediment transport is the combination of sediment that is stirred up from the bed and subsequently transported. Breaking induced turbulence enhances stirring of sediment from the bed and keeps sediment in suspension. The amount of stirring and the transport direction depends on the wave conditions.
Input and control data for the model study was provided by the Scanex 2020 fieldwork campaign at Noordwijk, the Netherlands. The ADV velocity data combined with a pressure signal has been used for the tidal and incoming wave signal. Cross-shore profiles have been determined in Matlab based on terrestrial laser scans. Soil samples of the intertidal zone were taken with a sand scraper and analyzed with a sieve tower. For the initial grain size distribution is the average distribution of 14 samples on a transect was used. Based on wave, wind and soil sampling data a model period from 29-2-2020 02:00 to 10-3-2020 13:00 was selected.
The XBeach model used is as described by Reniers et al. (2013), but with a time-averaged turbulent kinetic energy and a different implementation of the Riemann boundary. The model consisted of a 176 x 3 grid with a grid size of dx=1 m and dy=5 m. For the initial bathymetry the laser scan of 29-2-2020 02:00 was used. The initial grain size was imposed on all the model grid cells. Additional to the standard run, runs have been performed to research the effect of a storm, the model sensitivity and the effect of aeolian transport.
The model shows a pattern of cross-shore grain size variations with coarser sediment from x=20 to x=56 m, finer sediment from x=57 to x=105 m and fluctuating grain size from x=106 to x=136 m compared to the initial grainsize. After 24 h a grain size pattern establishes with a clear deposition of fine sediment on the upper beach. The pattern remained stable for nearly the full model period. After 200 hours the fines become less prominent and move onshore. On the intratidal scale sediment becomes coarser when submerged and finer when emerged, except near the high water line where fine sediment is deposited.
The model reproduced the same pattern of grain size variations over the cross-shore as was found in the soil samples of 10-3-2020. As the cross-shore grain size pattern remained stable during the model period, processes on the spring-neap time scale or storm time scale seem to govern the cross-shore variations of the grain size. For the aeolian transport this would imply that for this model period the fine sediment supply is controlled on the same time scales. Nevertheless, considering that aeolian transport could have resulted in coarsening of the fines in the upper intertidal zone, processes over a single tide, could be more important than was visible in the model result.
...
The intertidal zone is subject to shoaling, surf and swash zone processes. The grain size influences the beach slope, the initiation of motion and settling to the bed. The cross-shore sediment transport is the combination of sediment that is stirred up from the bed and subsequently transported. Breaking induced turbulence enhances stirring of sediment from the bed and keeps sediment in suspension. The amount of stirring and the transport direction depends on the wave conditions.
Input and control data for the model study was provided by the Scanex 2020 fieldwork campaign at Noordwijk, the Netherlands. The ADV velocity data combined with a pressure signal has been used for the tidal and incoming wave signal. Cross-shore profiles have been determined in Matlab based on terrestrial laser scans. Soil samples of the intertidal zone were taken with a sand scraper and analyzed with a sieve tower. For the initial grain size distribution is the average distribution of 14 samples on a transect was used. Based on wave, wind and soil sampling data a model period from 29-2-2020 02:00 to 10-3-2020 13:00 was selected.
The XBeach model used is as described by Reniers et al. (2013), but with a time-averaged turbulent kinetic energy and a different implementation of the Riemann boundary. The model consisted of a 176 x 3 grid with a grid size of dx=1 m and dy=5 m. For the initial bathymetry the laser scan of 29-2-2020 02:00 was used. The initial grain size was imposed on all the model grid cells. Additional to the standard run, runs have been performed to research the effect of a storm, the model sensitivity and the effect of aeolian transport.
The model shows a pattern of cross-shore grain size variations with coarser sediment from x=20 to x=56 m, finer sediment from x=57 to x=105 m and fluctuating grain size from x=106 to x=136 m compared to the initial grainsize. After 24 h a grain size pattern establishes with a clear deposition of fine sediment on the upper beach. The pattern remained stable for nearly the full model period. After 200 hours the fines become less prominent and move onshore. On the intratidal scale sediment becomes coarser when submerged and finer when emerged, except near the high water line where fine sediment is deposited.
The model reproduced the same pattern of grain size variations over the cross-shore as was found in the soil samples of 10-3-2020. As the cross-shore grain size pattern remained stable during the model period, processes on the spring-neap time scale or storm time scale seem to govern the cross-shore variations of the grain size. For the aeolian transport this would imply that for this model period the fine sediment supply is controlled on the same time scales. Nevertheless, considering that aeolian transport could have resulted in coarsening of the fines in the upper intertidal zone, processes over a single tide, could be more important than was visible in the model result.
...
The Building with Nature approach has been gaining ground in hydraulic engineering, increasing the importance of understanding the cross-shore morphodynamic processes. The intertidal zone, where marine and aeolian processes come together, is an important link in the transport of sediment from the sea towards the dunes. The grain size distribution affects the sediment supply in the intertidal zone. This research investigates the effect of marine processes on the cross-shore variations of the grain size distribution in the intertidal zone by using a one-dimensional non linear shallow water XBeach model.
The intertidal zone is subject to shoaling, surf and swash zone processes. The grain size influences the beach slope, the initiation of motion and settling to the bed. The cross-shore sediment transport is the combination of sediment that is stirred up from the bed and subsequently transported. Breaking induced turbulence enhances stirring of sediment from the bed and keeps sediment in suspension. The amount of stirring and the transport direction depends on the wave conditions.
Input and control data for the model study was provided by the Scanex 2020 fieldwork campaign at Noordwijk, the Netherlands. The ADV velocity data combined with a pressure signal has been used for the tidal and incoming wave signal. Cross-shore profiles have been determined in Matlab based on terrestrial laser scans. Soil samples of the intertidal zone were taken with a sand scraper and analyzed with a sieve tower. For the initial grain size distribution is the average distribution of 14 samples on a transect was used. Based on wave, wind and soil sampling data a model period from 29-2-2020 02:00 to 10-3-2020 13:00 was selected.
The XBeach model used is as described by Reniers et al. (2013), but with a time-averaged turbulent kinetic energy and a different implementation of the Riemann boundary. The model consisted of a 176 x 3 grid with a grid size of dx=1 m and dy=5 m. For the initial bathymetry the laser scan of 29-2-2020 02:00 was used. The initial grain size was imposed on all the model grid cells. Additional to the standard run, runs have been performed to research the effect of a storm, the model sensitivity and the effect of aeolian transport.
The model shows a pattern of cross-shore grain size variations with coarser sediment from x=20 to x=56 m, finer sediment from x=57 to x=105 m and fluctuating grain size from x=106 to x=136 m compared to the initial grainsize. After 24 h a grain size pattern establishes with a clear deposition of fine sediment on the upper beach. The pattern remained stable for nearly the full model period. After 200 hours the fines become less prominent and move onshore. On the intratidal scale sediment becomes coarser when submerged and finer when emerged, except near the high water line where fine sediment is deposited.
The model reproduced the same pattern of grain size variations over the cross-shore as was found in the soil samples of 10-3-2020. As the cross-shore grain size pattern remained stable during the model period, processes on the spring-neap time scale or storm time scale seem to govern the cross-shore variations of the grain size. For the aeolian transport this would imply that for this model period the fine sediment supply is controlled on the same time scales. Nevertheless, considering that aeolian transport could have resulted in coarsening of the fines in the upper intertidal zone, processes over a single tide, could be more important than was visible in the model result.
The intertidal zone is subject to shoaling, surf and swash zone processes. The grain size influences the beach slope, the initiation of motion and settling to the bed. The cross-shore sediment transport is the combination of sediment that is stirred up from the bed and subsequently transported. Breaking induced turbulence enhances stirring of sediment from the bed and keeps sediment in suspension. The amount of stirring and the transport direction depends on the wave conditions.
Input and control data for the model study was provided by the Scanex 2020 fieldwork campaign at Noordwijk, the Netherlands. The ADV velocity data combined with a pressure signal has been used for the tidal and incoming wave signal. Cross-shore profiles have been determined in Matlab based on terrestrial laser scans. Soil samples of the intertidal zone were taken with a sand scraper and analyzed with a sieve tower. For the initial grain size distribution is the average distribution of 14 samples on a transect was used. Based on wave, wind and soil sampling data a model period from 29-2-2020 02:00 to 10-3-2020 13:00 was selected.
The XBeach model used is as described by Reniers et al. (2013), but with a time-averaged turbulent kinetic energy and a different implementation of the Riemann boundary. The model consisted of a 176 x 3 grid with a grid size of dx=1 m and dy=5 m. For the initial bathymetry the laser scan of 29-2-2020 02:00 was used. The initial grain size was imposed on all the model grid cells. Additional to the standard run, runs have been performed to research the effect of a storm, the model sensitivity and the effect of aeolian transport.
The model shows a pattern of cross-shore grain size variations with coarser sediment from x=20 to x=56 m, finer sediment from x=57 to x=105 m and fluctuating grain size from x=106 to x=136 m compared to the initial grainsize. After 24 h a grain size pattern establishes with a clear deposition of fine sediment on the upper beach. The pattern remained stable for nearly the full model period. After 200 hours the fines become less prominent and move onshore. On the intratidal scale sediment becomes coarser when submerged and finer when emerged, except near the high water line where fine sediment is deposited.
The model reproduced the same pattern of grain size variations over the cross-shore as was found in the soil samples of 10-3-2020. As the cross-shore grain size pattern remained stable during the model period, processes on the spring-neap time scale or storm time scale seem to govern the cross-shore variations of the grain size. For the aeolian transport this would imply that for this model period the fine sediment supply is controlled on the same time scales. Nevertheless, considering that aeolian transport could have resulted in coarsening of the fines in the upper intertidal zone, processes over a single tide, could be more important than was visible in the model result.
Detection of aeolian sand strips and their characteristics using terrestrial laser scanning
The dependency between aeolian sand strip development and the environmental conditions occurring at the Noordwijk beach
Master thesis
(2022)
-
K. Boomaars, S.E. Vos, C.O. van IJzendoorn, A.J.H.M. Reniers, R.C. Lindenbergh, M. Kuschnerus
Sea level rise causes more difficulties for coastal maintenance. Although hard structures were built in the past to prevent for flooding, nature based solutions are preferred more recently. For the application of nature based solutions, a better understanding of the coastal processes is desired. Dry sand is transported towards the dunes by aeolian processes, whose bedform development is understudied while knowledge on this is important. One of the most visually clear bedforms are organised dry sand over a moist beach, referred to as sand strips. In order to improve the knowledge on sand strips, this study focusses on sand strip properties and occurring environmental conditions during their presence at the Noordwijk beach, using data of a terrestrial laser scanning (TLS) device.
Sand strips are detected with the Fourier transform. Since surface moisture can be derived from the reflectance intensity of the TLS-data, and due to the different moisture content of the sand strips compared to the surrounding beach, the Fourier transform is applied on the reflectance intensity. Sand strips are detected based on the energy in the variance density spectrum for a wavenumber-range corresponding to sand strips. The detected sand strips were oriented alongshore to oblique-alongshore with a mean wavelength and height of 13.2 m and 4.0 cm respectively, which is in correspondence with similar sand strip-related studies.
According to sand samples of the beach the grain size varies in transverse direction of the sand strips, comparable with the grain size variation of aeolian sand ripples. The coarser grains were located at the crest and the finer grains at the lee-side. Additionally, the samples also showed a significant difference in gravimetric moisture content between the sand strips and surrounding beach, as expected due to the reflectance-based detection. At the sand strips, the maximum moisture content was 5.3%, while the minimum determined moisture content at the surrounding beach was 6.0%. The mean values were equal to 2.6% and 9.4% for the sand strips and surrounding beach respectively.
In addition, sand strips mainly occurred during (almost) alongshore wind events with a wind velocity in excess of 8 m/s. However, the threshold wind velocity for sand strip formation is determined at 10 m/s. Due to the significant height difference that can remain present during precipitation events, these events are not necessarily restrictive factors for sand strip development, although the reflectance intensity suggests different. Furthermore, sand strips mostly formed during falling tide and they were mostly destroyed during rising tide.
The one life cycle of the sand strips that is analysed showed dynamic sand strip behaviour. The migration rate of the sand strips varied over the width of the beach, causing more inland oriented sand strips. This dynamic behaviour cannot be related to weather conditions since they remained constant, however it could be related to topographic steering caused by the dune. Nevertheless, the results of the dynamic properties are only indicative and encourage further study of dynamic sand strip properties. ...
Sand strips are detected with the Fourier transform. Since surface moisture can be derived from the reflectance intensity of the TLS-data, and due to the different moisture content of the sand strips compared to the surrounding beach, the Fourier transform is applied on the reflectance intensity. Sand strips are detected based on the energy in the variance density spectrum for a wavenumber-range corresponding to sand strips. The detected sand strips were oriented alongshore to oblique-alongshore with a mean wavelength and height of 13.2 m and 4.0 cm respectively, which is in correspondence with similar sand strip-related studies.
According to sand samples of the beach the grain size varies in transverse direction of the sand strips, comparable with the grain size variation of aeolian sand ripples. The coarser grains were located at the crest and the finer grains at the lee-side. Additionally, the samples also showed a significant difference in gravimetric moisture content between the sand strips and surrounding beach, as expected due to the reflectance-based detection. At the sand strips, the maximum moisture content was 5.3%, while the minimum determined moisture content at the surrounding beach was 6.0%. The mean values were equal to 2.6% and 9.4% for the sand strips and surrounding beach respectively.
In addition, sand strips mainly occurred during (almost) alongshore wind events with a wind velocity in excess of 8 m/s. However, the threshold wind velocity for sand strip formation is determined at 10 m/s. Due to the significant height difference that can remain present during precipitation events, these events are not necessarily restrictive factors for sand strip development, although the reflectance intensity suggests different. Furthermore, sand strips mostly formed during falling tide and they were mostly destroyed during rising tide.
The one life cycle of the sand strips that is analysed showed dynamic sand strip behaviour. The migration rate of the sand strips varied over the width of the beach, causing more inland oriented sand strips. This dynamic behaviour cannot be related to weather conditions since they remained constant, however it could be related to topographic steering caused by the dune. Nevertheless, the results of the dynamic properties are only indicative and encourage further study of dynamic sand strip properties. ...
Sea level rise causes more difficulties for coastal maintenance. Although hard structures were built in the past to prevent for flooding, nature based solutions are preferred more recently. For the application of nature based solutions, a better understanding of the coastal processes is desired. Dry sand is transported towards the dunes by aeolian processes, whose bedform development is understudied while knowledge on this is important. One of the most visually clear bedforms are organised dry sand over a moist beach, referred to as sand strips. In order to improve the knowledge on sand strips, this study focusses on sand strip properties and occurring environmental conditions during their presence at the Noordwijk beach, using data of a terrestrial laser scanning (TLS) device.
Sand strips are detected with the Fourier transform. Since surface moisture can be derived from the reflectance intensity of the TLS-data, and due to the different moisture content of the sand strips compared to the surrounding beach, the Fourier transform is applied on the reflectance intensity. Sand strips are detected based on the energy in the variance density spectrum for a wavenumber-range corresponding to sand strips. The detected sand strips were oriented alongshore to oblique-alongshore with a mean wavelength and height of 13.2 m and 4.0 cm respectively, which is in correspondence with similar sand strip-related studies.
According to sand samples of the beach the grain size varies in transverse direction of the sand strips, comparable with the grain size variation of aeolian sand ripples. The coarser grains were located at the crest and the finer grains at the lee-side. Additionally, the samples also showed a significant difference in gravimetric moisture content between the sand strips and surrounding beach, as expected due to the reflectance-based detection. At the sand strips, the maximum moisture content was 5.3%, while the minimum determined moisture content at the surrounding beach was 6.0%. The mean values were equal to 2.6% and 9.4% for the sand strips and surrounding beach respectively.
In addition, sand strips mainly occurred during (almost) alongshore wind events with a wind velocity in excess of 8 m/s. However, the threshold wind velocity for sand strip formation is determined at 10 m/s. Due to the significant height difference that can remain present during precipitation events, these events are not necessarily restrictive factors for sand strip development, although the reflectance intensity suggests different. Furthermore, sand strips mostly formed during falling tide and they were mostly destroyed during rising tide.
The one life cycle of the sand strips that is analysed showed dynamic sand strip behaviour. The migration rate of the sand strips varied over the width of the beach, causing more inland oriented sand strips. This dynamic behaviour cannot be related to weather conditions since they remained constant, however it could be related to topographic steering caused by the dune. Nevertheless, the results of the dynamic properties are only indicative and encourage further study of dynamic sand strip properties.
Sand strips are detected with the Fourier transform. Since surface moisture can be derived from the reflectance intensity of the TLS-data, and due to the different moisture content of the sand strips compared to the surrounding beach, the Fourier transform is applied on the reflectance intensity. Sand strips are detected based on the energy in the variance density spectrum for a wavenumber-range corresponding to sand strips. The detected sand strips were oriented alongshore to oblique-alongshore with a mean wavelength and height of 13.2 m and 4.0 cm respectively, which is in correspondence with similar sand strip-related studies.
According to sand samples of the beach the grain size varies in transverse direction of the sand strips, comparable with the grain size variation of aeolian sand ripples. The coarser grains were located at the crest and the finer grains at the lee-side. Additionally, the samples also showed a significant difference in gravimetric moisture content between the sand strips and surrounding beach, as expected due to the reflectance-based detection. At the sand strips, the maximum moisture content was 5.3%, while the minimum determined moisture content at the surrounding beach was 6.0%. The mean values were equal to 2.6% and 9.4% for the sand strips and surrounding beach respectively.
In addition, sand strips mainly occurred during (almost) alongshore wind events with a wind velocity in excess of 8 m/s. However, the threshold wind velocity for sand strip formation is determined at 10 m/s. Due to the significant height difference that can remain present during precipitation events, these events are not necessarily restrictive factors for sand strip development, although the reflectance intensity suggests different. Furthermore, sand strips mostly formed during falling tide and they were mostly destroyed during rising tide.
The one life cycle of the sand strips that is analysed showed dynamic sand strip behaviour. The migration rate of the sand strips varied over the width of the beach, causing more inland oriented sand strips. This dynamic behaviour cannot be related to weather conditions since they remained constant, however it could be related to topographic steering caused by the dune. Nevertheless, the results of the dynamic properties are only indicative and encourage further study of dynamic sand strip properties.
In order to understand the long term behavior of intertidal ridge-runnel systems high resolution spatial and temporal data covering extended periods of time is needed. Such datasets are still rare but are becoming more available through the usage of remote sensing technologies such as Argus and Terrestrial Laser Scanning. A three month period (Feb – April 2020) with data obtained by laser scanning at the beach of Noordwijk, the Netherlands, has been analysed to evaluate the longshore variability of rip channels. During this period varying weather conditions occurred. The timeseries consist out of snapshots taken around the occurrence of the lowest tidal water level each day, containing elevation data of an 1km alongshore section of the beach. Each scan in this timeseries is processed in order to remove noise, objects and correct for time dependent rotations. The spatial gaps in the scans present in the data as the result of flowing or standing water are interpolated using a 2D grid interpolation method. The analysis is done using two different methods: a 1D-method using longshore elevation transacts, and a more advanced 4D-Object-by-Change based upon elevation changes over time. The 1D-method detected 44 rip channels that existed for multiple days, with an average alongshore migration rate of 1.55 m/day. The average spacing between rip channels was found to be 131 meters. The 4D-OBC detected less rip channel when compared to the 1D-method but did capture other morphological features such a runnels. A comparison of the alongshore migration rates and the dominant wave and wind directions that during this period showed a correlation between wind and wave direction and the direction of the alongshore migration direction, however some exceptions are visible. Comparing this research to similar research and literature did show differences in the migration rates and rip spacing. These are explained by the different nature of both datasets (2D vs 3D) and methodology used in the detection of rip channels.
...
In order to understand the long term behavior of intertidal ridge-runnel systems high resolution spatial and temporal data covering extended periods of time is needed. Such datasets are still rare but are becoming more available through the usage of remote sensing technologies such as Argus and Terrestrial Laser Scanning. A three month period (Feb – April 2020) with data obtained by laser scanning at the beach of Noordwijk, the Netherlands, has been analysed to evaluate the longshore variability of rip channels. During this period varying weather conditions occurred. The timeseries consist out of snapshots taken around the occurrence of the lowest tidal water level each day, containing elevation data of an 1km alongshore section of the beach. Each scan in this timeseries is processed in order to remove noise, objects and correct for time dependent rotations. The spatial gaps in the scans present in the data as the result of flowing or standing water are interpolated using a 2D grid interpolation method. The analysis is done using two different methods: a 1D-method using longshore elevation transacts, and a more advanced 4D-Object-by-Change based upon elevation changes over time. The 1D-method detected 44 rip channels that existed for multiple days, with an average alongshore migration rate of 1.55 m/day. The average spacing between rip channels was found to be 131 meters. The 4D-OBC detected less rip channel when compared to the 1D-method but did capture other morphological features such a runnels. A comparison of the alongshore migration rates and the dominant wave and wind directions that during this period showed a correlation between wind and wave direction and the direction of the alongshore migration direction, however some exceptions are visible. Comparing this research to similar research and literature did show differences in the migration rates and rip spacing. These are explained by the different nature of both datasets (2D vs 3D) and methodology used in the detection of rip channels.
Cross-shore morphodynamics of intertidal bars
A conceptual model, empirical evidence and numerical modelling
The beach recovery process determines the resilience of a sandy coast and is an important aspect of the coastal safety. Sediment stored underwater due to storms is transported onshore by the migration of subtidal and intertidal bars under mild wave conditions. The intertidal zone is an im-portant interface, connecting the marine and aeolian zone and facilitating the transition of hydro-dynamic to aeolian sediment transport. The aim of this study is to investigate the cross-shore mor-phodynamics of intertidal sandbars. The dominant cross-shore sediment transport processes can mainly be divided into surf zone and swash zone processes. The surf zone processes are primarily determined by the balance of wave nonlinearities, undertow and infra-gravity waves. In the swash zone, the cross-shore sediment transport is determined by the balance between the turbulent uprush and the gravity induced backwash. A recent terrestrial laser scanning (TLS) measuring campaign conducted at Kijkduin, the Nether-lands, provided new insight in the intertidal bar behavior. The results of one cross section are ana-lyzed. In a period of 6 weeks, two distinctive intertidal bars formed, grew and migrated onshore during mild wave conditions and eventually eroded again during a storm. Within 5 days, the upper intertidal bar migrated onshore over a distance of 25m and grew with a height of 0.3m, attributed to swash zone processes. Onshore sediment transport fluxes reached values of nearly 2 m3 per meter width in one tidal cycle.
The findings are compared with two XBeach models (surf beat model and hydrostatic swash model) which are used to reproduce the observed morphological behavior of the upper intertidal bar. Both models partly reproduce the onshore migration but show deviating results regarding the final growth of the intertidal bar. In contrast to the surf beat model, the morphological changes in the hydrostatic swash model are primarily induced by swash zone processes, which is comparable to the processes in the TLS measurements. Finally, a conceptual model is developed in which four intertidal bar regimes are classified based on the tidal water level. The distinction determines the dominant cross-shore processes for the for-mation, migration, growth and destruction of intertidal bars. The model shows that the swash zone processes are dominant for the onshore migration and growth of intertidal bars in the overwash regime, while the surf zone processes are dominant in the submersion regime. The findings presented in this study provide a better understanding of the intertidal bar behavior. Although the XBeach models did not reproduce the observed behavior completely, there are some pronounced similarities. Further research is required to increase the knowledge of intertidal bar behavior at a variety of sandy coasts and to improve the performance of rocesses-based models like XBeach.
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The findings are compared with two XBeach models (surf beat model and hydrostatic swash model) which are used to reproduce the observed morphological behavior of the upper intertidal bar. Both models partly reproduce the onshore migration but show deviating results regarding the final growth of the intertidal bar. In contrast to the surf beat model, the morphological changes in the hydrostatic swash model are primarily induced by swash zone processes, which is comparable to the processes in the TLS measurements. Finally, a conceptual model is developed in which four intertidal bar regimes are classified based on the tidal water level. The distinction determines the dominant cross-shore processes for the for-mation, migration, growth and destruction of intertidal bars. The model shows that the swash zone processes are dominant for the onshore migration and growth of intertidal bars in the overwash regime, while the surf zone processes are dominant in the submersion regime. The findings presented in this study provide a better understanding of the intertidal bar behavior. Although the XBeach models did not reproduce the observed behavior completely, there are some pronounced similarities. Further research is required to increase the knowledge of intertidal bar behavior at a variety of sandy coasts and to improve the performance of rocesses-based models like XBeach.
...
The beach recovery process determines the resilience of a sandy coast and is an important aspect of the coastal safety. Sediment stored underwater due to storms is transported onshore by the migration of subtidal and intertidal bars under mild wave conditions. The intertidal zone is an im-portant interface, connecting the marine and aeolian zone and facilitating the transition of hydro-dynamic to aeolian sediment transport. The aim of this study is to investigate the cross-shore mor-phodynamics of intertidal sandbars. The dominant cross-shore sediment transport processes can mainly be divided into surf zone and swash zone processes. The surf zone processes are primarily determined by the balance of wave nonlinearities, undertow and infra-gravity waves. In the swash zone, the cross-shore sediment transport is determined by the balance between the turbulent uprush and the gravity induced backwash. A recent terrestrial laser scanning (TLS) measuring campaign conducted at Kijkduin, the Nether-lands, provided new insight in the intertidal bar behavior. The results of one cross section are ana-lyzed. In a period of 6 weeks, two distinctive intertidal bars formed, grew and migrated onshore during mild wave conditions and eventually eroded again during a storm. Within 5 days, the upper intertidal bar migrated onshore over a distance of 25m and grew with a height of 0.3m, attributed to swash zone processes. Onshore sediment transport fluxes reached values of nearly 2 m3 per meter width in one tidal cycle.
The findings are compared with two XBeach models (surf beat model and hydrostatic swash model) which are used to reproduce the observed morphological behavior of the upper intertidal bar. Both models partly reproduce the onshore migration but show deviating results regarding the final growth of the intertidal bar. In contrast to the surf beat model, the morphological changes in the hydrostatic swash model are primarily induced by swash zone processes, which is comparable to the processes in the TLS measurements. Finally, a conceptual model is developed in which four intertidal bar regimes are classified based on the tidal water level. The distinction determines the dominant cross-shore processes for the for-mation, migration, growth and destruction of intertidal bars. The model shows that the swash zone processes are dominant for the onshore migration and growth of intertidal bars in the overwash regime, while the surf zone processes are dominant in the submersion regime. The findings presented in this study provide a better understanding of the intertidal bar behavior. Although the XBeach models did not reproduce the observed behavior completely, there are some pronounced similarities. Further research is required to increase the knowledge of intertidal bar behavior at a variety of sandy coasts and to improve the performance of rocesses-based models like XBeach.
The findings are compared with two XBeach models (surf beat model and hydrostatic swash model) which are used to reproduce the observed morphological behavior of the upper intertidal bar. Both models partly reproduce the onshore migration but show deviating results regarding the final growth of the intertidal bar. In contrast to the surf beat model, the morphological changes in the hydrostatic swash model are primarily induced by swash zone processes, which is comparable to the processes in the TLS measurements. Finally, a conceptual model is developed in which four intertidal bar regimes are classified based on the tidal water level. The distinction determines the dominant cross-shore processes for the for-mation, migration, growth and destruction of intertidal bars. The model shows that the swash zone processes are dominant for the onshore migration and growth of intertidal bars in the overwash regime, while the surf zone processes are dominant in the submersion regime. The findings presented in this study provide a better understanding of the intertidal bar behavior. Although the XBeach models did not reproduce the observed behavior completely, there are some pronounced similarities. Further research is required to increase the knowledge of intertidal bar behavior at a variety of sandy coasts and to improve the performance of rocesses-based models like XBeach.
Sediment transport during the execution of the pilot nourishment Ameland Inlet
Development of a tool for analysing bathymetric surveys, applied on the pilot nourishment Ameland inlet
Master thesis
(2019)
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Thijs van Rhijn, Zhengbing Wang, Bram van Prooijen, Sander Vos, Harry de Looff, Pieter Koen Tonnon, Erik van Dijk
Within the KustGenese 2.0 research project a 5Mm3 pilot nourishment is created on the ebb-tidal delta of Ameland. For this thesis I was involved in the parties; Van den Herik, the contractor who executed the work, Deltares and Rijkswaterstaat. A tool is created to quickly analyse new surveys in combination with the ships deposit data. The tool is applicable for any other dredging project.
The tool is applied on the 4-6 weekly surveys during the execution of the pilot nourishment. An analyse with the tool gives insight into the morphodynamics of the ebb tidal delta and the location of the pilot nourishment. The sediment transport on the nourishment location is wave dominated, as the sediment transport is limited during calm wave conditions. The sediment transport on the second ebb shield is however tide dominated. During the January 2019 storms an increase in sediment transport is seen on both tidal and wave dominated parts. ...
The tool is applied on the 4-6 weekly surveys during the execution of the pilot nourishment. An analyse with the tool gives insight into the morphodynamics of the ebb tidal delta and the location of the pilot nourishment. The sediment transport on the nourishment location is wave dominated, as the sediment transport is limited during calm wave conditions. The sediment transport on the second ebb shield is however tide dominated. During the January 2019 storms an increase in sediment transport is seen on both tidal and wave dominated parts. ...
Within the KustGenese 2.0 research project a 5Mm3 pilot nourishment is created on the ebb-tidal delta of Ameland. For this thesis I was involved in the parties; Van den Herik, the contractor who executed the work, Deltares and Rijkswaterstaat. A tool is created to quickly analyse new surveys in combination with the ships deposit data. The tool is applicable for any other dredging project.
The tool is applied on the 4-6 weekly surveys during the execution of the pilot nourishment. An analyse with the tool gives insight into the morphodynamics of the ebb tidal delta and the location of the pilot nourishment. The sediment transport on the nourishment location is wave dominated, as the sediment transport is limited during calm wave conditions. The sediment transport on the second ebb shield is however tide dominated. During the January 2019 storms an increase in sediment transport is seen on both tidal and wave dominated parts.
The tool is applied on the 4-6 weekly surveys during the execution of the pilot nourishment. An analyse with the tool gives insight into the morphodynamics of the ebb tidal delta and the location of the pilot nourishment. The sediment transport on the nourishment location is wave dominated, as the sediment transport is limited during calm wave conditions. The sediment transport on the second ebb shield is however tide dominated. During the January 2019 storms an increase in sediment transport is seen on both tidal and wave dominated parts.
Mapping sub-annual beach growth using terrestrial laser scanning
A study on the application of terrestrial laser scanning on small scale beach variability, to quantify beach resilience on sub-annual time scale
Master thesis
(2018)
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Rik Hobbelen, Stefan Aarninkhof, Sander Vos, Sierd de Vries, Roderik Lindenbergh
This thesis presents a case study on beach growth of a South Holland beach located slightly north of the Sand Motor over the course of six months, which was measured using a terrestrial laser scanner (TLS). This device was set up to continuously take hourly full coverage measurements of a one kilometre stretch of beach from a hotel rooftop.
As sea-levels rise, interest in the morphological processes that take place on beaches is growing, so that coastal safety can be continued to be guaranteed in the future. As a result, it becomes increasingly relevant to understand the transport of sediment towards the beach. Existing studies on the subject focus on timescales of years to decades, often making use of GPS measurements. However, no thorough research has been performed on sub-annual timescales in over a decade, leading to the following main research question for this thesis: How is beach volume growth distributed on sub-annual time scale, both in spatial and temporal dimensions?
To validate the data obtained by the TLS, an accuracy check was performed which proved the standard deviation of the measurements to be much smaller than the observed morphological change. A rotational instability of the scanning device was discovered and corrected, however a higher measurement accuracy could be obtained by developing a more detailed correction method. The applied correction method did however no longer allow for the study of smaller fluxes such as aeolian transport, as they are overruled by it. It was investigated how the raw 3D data obtained from the TLS should be processed to obtain a clean timeseries of cross-sections. A framework is presented that includes noise detection and removal, object filtering, interpolation and subsampling. Subsequently, timeseries of 132 cross-sections were extracted from the data by selecting a daily low tide scan for 132 days along 4 different transects.
The resulting timeseries clearly display morphological activity such as intertidal bar migration and storm erosion, and volumetric computations have displayed periods of beach growth. These periods generally occur between storms, during calm wind and wave conditions. The main driver for this growth is the onshore migration of intertidal bars. As bars enter the intertidal zone, they migrate onshore and grow, increasing the volume of the beach. A swash bar that formed high in the intertidal zone during neap tide was found to migrate at increased rate during the neap-spring tidal cycle and welded to the beach, as compared to a different bar which migrated during the springneap cycle. Following spring tide, the bar ceased onshore migration and an offshore expansion occurred. This offshore expansion had a great effect on the volumetric growth of the total beach profile and showcases the influence of tide in the migration of swash bars. However, due to the great number of factors that influence beach growth, only few significant correlations were found between beach volume changes and boundary conditions such as tide, and wave and wind forcing.
Over the entire research period, only limited growth of the beach has occurred (2.6 m3 over all transects). Periods of growth (up to 20 m3 in under a month) were followed by storms, which eroded the gained volume. No general linear trend in growth was observed, indicating the dominance of variability over trend on the regarded time scale. This result contradicts findings of studies that use monthly or yearly data. When regarding daily data for several months, the beach volume is very much influenced by bar migration and storm erosion which lead to much more variation in the volumetric signal. ...
As sea-levels rise, interest in the morphological processes that take place on beaches is growing, so that coastal safety can be continued to be guaranteed in the future. As a result, it becomes increasingly relevant to understand the transport of sediment towards the beach. Existing studies on the subject focus on timescales of years to decades, often making use of GPS measurements. However, no thorough research has been performed on sub-annual timescales in over a decade, leading to the following main research question for this thesis: How is beach volume growth distributed on sub-annual time scale, both in spatial and temporal dimensions?
To validate the data obtained by the TLS, an accuracy check was performed which proved the standard deviation of the measurements to be much smaller than the observed morphological change. A rotational instability of the scanning device was discovered and corrected, however a higher measurement accuracy could be obtained by developing a more detailed correction method. The applied correction method did however no longer allow for the study of smaller fluxes such as aeolian transport, as they are overruled by it. It was investigated how the raw 3D data obtained from the TLS should be processed to obtain a clean timeseries of cross-sections. A framework is presented that includes noise detection and removal, object filtering, interpolation and subsampling. Subsequently, timeseries of 132 cross-sections were extracted from the data by selecting a daily low tide scan for 132 days along 4 different transects.
The resulting timeseries clearly display morphological activity such as intertidal bar migration and storm erosion, and volumetric computations have displayed periods of beach growth. These periods generally occur between storms, during calm wind and wave conditions. The main driver for this growth is the onshore migration of intertidal bars. As bars enter the intertidal zone, they migrate onshore and grow, increasing the volume of the beach. A swash bar that formed high in the intertidal zone during neap tide was found to migrate at increased rate during the neap-spring tidal cycle and welded to the beach, as compared to a different bar which migrated during the springneap cycle. Following spring tide, the bar ceased onshore migration and an offshore expansion occurred. This offshore expansion had a great effect on the volumetric growth of the total beach profile and showcases the influence of tide in the migration of swash bars. However, due to the great number of factors that influence beach growth, only few significant correlations were found between beach volume changes and boundary conditions such as tide, and wave and wind forcing.
Over the entire research period, only limited growth of the beach has occurred (2.6 m3 over all transects). Periods of growth (up to 20 m3 in under a month) were followed by storms, which eroded the gained volume. No general linear trend in growth was observed, indicating the dominance of variability over trend on the regarded time scale. This result contradicts findings of studies that use monthly or yearly data. When regarding daily data for several months, the beach volume is very much influenced by bar migration and storm erosion which lead to much more variation in the volumetric signal. ...
This thesis presents a case study on beach growth of a South Holland beach located slightly north of the Sand Motor over the course of six months, which was measured using a terrestrial laser scanner (TLS). This device was set up to continuously take hourly full coverage measurements of a one kilometre stretch of beach from a hotel rooftop.
As sea-levels rise, interest in the morphological processes that take place on beaches is growing, so that coastal safety can be continued to be guaranteed in the future. As a result, it becomes increasingly relevant to understand the transport of sediment towards the beach. Existing studies on the subject focus on timescales of years to decades, often making use of GPS measurements. However, no thorough research has been performed on sub-annual timescales in over a decade, leading to the following main research question for this thesis: How is beach volume growth distributed on sub-annual time scale, both in spatial and temporal dimensions?
To validate the data obtained by the TLS, an accuracy check was performed which proved the standard deviation of the measurements to be much smaller than the observed morphological change. A rotational instability of the scanning device was discovered and corrected, however a higher measurement accuracy could be obtained by developing a more detailed correction method. The applied correction method did however no longer allow for the study of smaller fluxes such as aeolian transport, as they are overruled by it. It was investigated how the raw 3D data obtained from the TLS should be processed to obtain a clean timeseries of cross-sections. A framework is presented that includes noise detection and removal, object filtering, interpolation and subsampling. Subsequently, timeseries of 132 cross-sections were extracted from the data by selecting a daily low tide scan for 132 days along 4 different transects.
The resulting timeseries clearly display morphological activity such as intertidal bar migration and storm erosion, and volumetric computations have displayed periods of beach growth. These periods generally occur between storms, during calm wind and wave conditions. The main driver for this growth is the onshore migration of intertidal bars. As bars enter the intertidal zone, they migrate onshore and grow, increasing the volume of the beach. A swash bar that formed high in the intertidal zone during neap tide was found to migrate at increased rate during the neap-spring tidal cycle and welded to the beach, as compared to a different bar which migrated during the springneap cycle. Following spring tide, the bar ceased onshore migration and an offshore expansion occurred. This offshore expansion had a great effect on the volumetric growth of the total beach profile and showcases the influence of tide in the migration of swash bars. However, due to the great number of factors that influence beach growth, only few significant correlations were found between beach volume changes and boundary conditions such as tide, and wave and wind forcing.
Over the entire research period, only limited growth of the beach has occurred (2.6 m3 over all transects). Periods of growth (up to 20 m3 in under a month) were followed by storms, which eroded the gained volume. No general linear trend in growth was observed, indicating the dominance of variability over trend on the regarded time scale. This result contradicts findings of studies that use monthly or yearly data. When regarding daily data for several months, the beach volume is very much influenced by bar migration and storm erosion which lead to much more variation in the volumetric signal.
As sea-levels rise, interest in the morphological processes that take place on beaches is growing, so that coastal safety can be continued to be guaranteed in the future. As a result, it becomes increasingly relevant to understand the transport of sediment towards the beach. Existing studies on the subject focus on timescales of years to decades, often making use of GPS measurements. However, no thorough research has been performed on sub-annual timescales in over a decade, leading to the following main research question for this thesis: How is beach volume growth distributed on sub-annual time scale, both in spatial and temporal dimensions?
To validate the data obtained by the TLS, an accuracy check was performed which proved the standard deviation of the measurements to be much smaller than the observed morphological change. A rotational instability of the scanning device was discovered and corrected, however a higher measurement accuracy could be obtained by developing a more detailed correction method. The applied correction method did however no longer allow for the study of smaller fluxes such as aeolian transport, as they are overruled by it. It was investigated how the raw 3D data obtained from the TLS should be processed to obtain a clean timeseries of cross-sections. A framework is presented that includes noise detection and removal, object filtering, interpolation and subsampling. Subsequently, timeseries of 132 cross-sections were extracted from the data by selecting a daily low tide scan for 132 days along 4 different transects.
The resulting timeseries clearly display morphological activity such as intertidal bar migration and storm erosion, and volumetric computations have displayed periods of beach growth. These periods generally occur between storms, during calm wind and wave conditions. The main driver for this growth is the onshore migration of intertidal bars. As bars enter the intertidal zone, they migrate onshore and grow, increasing the volume of the beach. A swash bar that formed high in the intertidal zone during neap tide was found to migrate at increased rate during the neap-spring tidal cycle and welded to the beach, as compared to a different bar which migrated during the springneap cycle. Following spring tide, the bar ceased onshore migration and an offshore expansion occurred. This offshore expansion had a great effect on the volumetric growth of the total beach profile and showcases the influence of tide in the migration of swash bars. However, due to the great number of factors that influence beach growth, only few significant correlations were found between beach volume changes and boundary conditions such as tide, and wave and wind forcing.
Over the entire research period, only limited growth of the beach has occurred (2.6 m3 over all transects). Periods of growth (up to 20 m3 in under a month) were followed by storms, which eroded the gained volume. No general linear trend in growth was observed, indicating the dominance of variability over trend on the regarded time scale. This result contradicts findings of studies that use monthly or yearly data. When regarding daily data for several months, the beach volume is very much influenced by bar migration and storm erosion which lead to much more variation in the volumetric signal.