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At active volcanoes, the surface temperature and its spatial distribution can indicate changes in the underlying magmatic and hydrothermal system. Surface temperature monitoring has been widely performed using thermal remote sensing with thermal infrared (TIR) cameras. One of the drawbacks of this method is that the unknown viewing orientation of TIR images inhibits quantitative evaluations of the spatial extent and distributions of thermal anomalies. Therefore, many studies have performed 3D temperature-field reconstructions by processing TIR images photogrammetrically. However, these studies have not included the correction of TIR wave atmospheric attenuation and viewing-angle variation in emissivity in the reconstruction procedure, which can result in significant temperature misestimation. We propose a simple method that incorporates the correction into the reconstruction process, which can improve the estimation of surface temperature, especially in rugged terrains. We demonstrate our method for the active crater of Aso volcano in Japan. We create digital elevation models by applying the Structure from Motion–Multi-view Stereo algorithm to aerial visible images taken at the same time as the TIR images and then project the TIR images onto the DEM with the direct georeferencing method. The correction is carried out using the geometric parameters acquired in the process. We create 1-m resolution orthorectified thermal images of the crater on two separate dates (18 August 2020 and 16 March 2022) and calculate the heat discharge rates from steaming grounds and a volcanic lake. We find that the heat discharge rate from the fumarolic field on the south crater wall showed a sevenfold increase after the phreatic explosions that occurred on 14 and 20 October 2021.

With the advent of modern sensing technology, mapping products have begun to achieve an unprecedented precision of measurement. Considering their diverse use cases, several factors play a role in what would make the resulting measurements accurate. For light detection and ranging (LiDAR) and photogrammetry-based mapping solutions that implement vehicles outfitted with laser ranging devices, RGB cameras, and global navigation satellite system/inertial navigation system (GNSS/INS) georeferencing units, the quality of the derived mapping products is governed by the combined accuracy of the various sensors. While ranging errors associated with LiDAR systems or the imaging quality of RGB cameras are sensor-dependent and are mostly constant, the accuracy of a georeferencing unit depends on a variety of extrinsic factors, including but not limited to, availability of clear line-of-path to GNSS satellites and presence of radio interferences. The quality of the GNSS signal, in turn, is affected by the grade of hardware components used and, to a great extent, obstructions to signal reception. This document reports some of the major challenges of vehicle-based mobile mapping with regards to GNSS/INS navigation. The background of GNSS/INS positioning is discussed to build a framework for trajectory enhancement as well as improvement of LiDAR mapping products. The focus is put on using available sensor data from LiDAR and/or cameras to enhance their position/orientation quality. Some best practices in light of potential trajectory deterioration are also recommended.

More accurate snow quality predictions are needed to economically and socially support communities in a changing Arctic environment. This contrasts with the current availability of affordable and efficient snow monitoring methods. In this study, a novel approach is presented to determine spatial snow depth distribution in challenging alpine terrain that was tested during a field campaign performed in the Tarfala valley, Kebnekaise mountains, northern Sweden, in April 2019. The combination of a multispectral camera and an Unmanned Aerial Vehicle (UAV) was used to derive three-dimensional (3D) snow surface models via Structure from Motion (SfM) with direct georeferencing. The main advantage over conventional photogrammetric surveys is the utilization of accurate Real-Time Kinematic (RTK) positioning which enables direct georeferencing of the images, and therefore eliminates the need for ground control points. The proposed method is capable of producing high-resolution 3D snow-covered surface models (<7 cm/pixel) of alpine areas up to eight hectares in a fast, reliable and affordable way. The test sites’ average snow depth was 160 cm with an average standard deviation of 78 cm. The overall Root-Mean-Square Errors (RMSE) of the snow depth range from 11.52 cm for data acquired in ideal surveying conditions to 41.03 cm in aggravated light and wind conditions. Results of this study suggest that the red components in the electromagnetic spectrum, i.e., the red, red edge, and near-infrared (NIR) band, contain the majority of information used in photogrammetric processing. The experiments highlighted a significant influence of the multi-spectral imagery on the quality of the final snow depth estimation as well as a strong potential to reduce processing times and computational resources by limiting the dimensionality of the imagery through the application of a Principal Component Analysis (PCA) before the photogrammetric 3D reconstruction. The proposed method is part of clo

More accurate snow quality predictions are needed to economically and socially support communities in a changing Arctic environment. This contrasts with the current availability of affordable and efficient snow monitoring methods. In this study, a novel approach is presented to determine spatial snow depth distribution in challenging alpine terrain that was tested during a field campaign performed in the Tarfala valley, Kebnekaise mountains, northern Sweden, in April 2019. The combination of a multispectral camera and an Unmanned Aerial Vehicle (UAV) was used to derive three-dimensional (3D) snow surface models via Structure from Motion (SfM) with direct georeferencing. The main advantage over conventional photogrammetric surveys is the utilization of accurate Real-Time Kinematic (RTK) positioning which enables direct georeferencing of the images, and therefore eliminates the need for ground control points. The proposed method is capable of producing high -resolution 3D snow-covered surface models (<7 cm/pixel) of alpine areas up to eight hectares in a fast, reli-able and affordable way. The test sites' average snow depth was 160 cm with an average standard deviation of 78 cm. The overall Root-Mean-Square Errors (RMSE) of the snow depth range from 11.52 cm for data acquired in ideal surveying conditions to 41.03 cm in aggravated light and wind conditions. Results of this study suggest that the red components in the electromagnetic spectrum, i.e., the red, red edge, and near-infrared (NIR) band, contain the majority of information used in photogrammetric processing. The experiments highlighted a sig-nificant influence of the multi-spectral imagery on the quality of the final snow depth estimation as well as a strong potential to reduce processing times and computational resources by limiting the dimensionality of the imagery through the application of a Principal Component Analysis (PCA) before the photogrammetric 3D reconstruction. The proposed method is part of

More accurate snow quality predictions are needed to economically and socially support communities in a changing Arctic environment. This contrasts with the current availability of affordable and efficient snow monitoring methods. In this study, a novel approach is presented to determine spatial snow depth distribution in challenging alpine terrain that was tested during a field campaign performed in the Tarfala valley, Kebnekaise mountains, northern Sweden, in April 2019. The combination of a multispectral camera and an Unmanned Aerial Vehicle (UAV) was used to derive three-dimensional (3D) snow surface models via Structure from Motion (SfM) with direct georeferencing. The main advantage over conventional photogrammetric surveys is the utilization of accurate Real-Time Kinematic (RTK) positioning which enables direct georeferencing of the images, and therefore eliminates the need for ground control points. The proposed method is capable of producing high -resolution 3D snow-covered surface models (<7 cm/pixel) of alpine areas up to eight hectares in a fast, reli-able and affordable way. The test sites' average snow depth was 160 cm with an average standard deviation of 78 cm. The overall Root-Mean-Square Errors (RMSE) of the snow depth range from 11.52 cm for data acquired in ideal surveying conditions to 41.03 cm in aggravated light and wind conditions. Results of this study suggest that the red components in the electromagnetic spectrum, i.e., the red, red edge, and near-infrared (NIR) band, contain the majority of information used in photogrammetric processing. The experiments highlighted a sig-nificant influence of the multi-spectral imagery on the quality of the final snow depth estimation as well as a strong potential to reduce processing times and computational resources by limiting the dimensionality of the imagery through the application of a Principal Component Analysis (PCA) before the photogrammetric 3D reconstruction. The proposed method is part of

GNSS/INS applications are being developed, especially for direct georeferencing in airborne photogrammetry. Achieving accurately georeferenced products from the integration of GNSS and INS requires removing systematic errors in the mobile mapping systems. The INS sensor's uncertainty is decreasing; therefore, the influence of the deflection of verticals (DOV, the angle between the plumb line and normal to the ellipsoid) should be considered in the direct georeferencing. Otherwise, an error is imposed for calculating the exterior orientation parameters of the aerial images and aerial laser scanning. This study determines the DOV using the EGM2008 model and gravity data in Sweden. The impact of the DOVs on horizontal and vertical coordinates, considering different flight altitudes and camera field of view, is assessed. The results confirm that the calculated DOV components using the EGM2008 model are sufficiently accurate for aerial mapping system purposes except for mountainous areas because the topographic signal is not modelled correctly.

GNSS/INS applications are being developed, especially for direct georeferencing in airborne photogrammetry. Achieving accurately georeferenced products from the integration of GNSS and INS requires removing systematic errors in the mobile mapping systems. The INS sensor's uncertainty is decreasing; therefore, the influence of the deflection of verticals (DOV, the angle between the plumb line and normal to the ellipsoid) should be considered in the direct georeferencing. Otherwise, an error is imposed for calculating the exterior orientation parameters of the aerial images and aerial laser scanning. This study determines the DOV using the EGM2008 model and gravity data in Sweden. The impact of the DOVs on horizontal and vertical coordinates, considering different flight altitudes and camera field of view, is assessed. The results confirm that the calculated DOV components using the EGM2008 model are sufficiently accurate for aerial mapping system purposes except for mountainous areas because the topographic signal is not modelled correctly.

More accurate snow quality predictions are needed to economically and socially support communities in a changing Arctic environment. This contrasts with the current availability of affordable and efficient snow monitoring methods. In this study, a novel approach is presented to determine spatial snow depth distribution in challenging alpine terrain that was tested during a field campaign performed in the Tarfala valley, Kebnekaise mountains, northern Sweden, in April 2019. The combination of a multispectral camera and an Unmanned Aerial Vehicle (UAV) was used to derive three-dimensional (3D) snow surface models via Structure from Motion (SfM) with direct georeferencing. The main advantage over conventional photogrammetric surveys is the utilization of accurate Real-Time Kinematic (RTK) positioning which enables direct georeferencing of the images, and therefore eliminates the need for ground control points. The proposed method is capable of producing high -resolution 3D snow-covered surface models (<7 cm/pixel) of alpine areas up to eight hectares in a fast, reli-able and affordable way. The test sites' average snow depth was 160 cm with an average standard deviation of 78 cm. The overall Root-Mean-Square Errors (RMSE) of the snow depth range from 11.52 cm for data acquired in ideal surveying conditions to 41.03 cm in aggravated light and wind conditions. Results of this study suggest that the red components in the electromagnetic spectrum, i.e., the red, red edge, and near-infrared (NIR) band, contain the majority of information used in photogrammetric processing. The experiments highlighted a sig-nificant influence of the multi-spectral imagery on the quality of the final snow depth estimation as well as a strong potential to reduce processing times and computational resources by limiting the dimensionality of the imagery through the application of a Principal Component Analysis (PCA) before the photogrammetric 3D reconstruction. The proposed method is part of

In this study, three different procedures: checkpoint RMS of residuals, statistical evaluation of AT results using t-test, and comparison of a photogrammetric digital surface model (DSM) and LiDAR data are used to analyse the effect of IMU and GNSS uncertainties on the final adjusted results. The outcome suggests that the method of block-wise GNSS shift correction is the better method for aerial triangulation and one should use appropriate observable weights in AT. The comparison of checkpoint RMS residuals between the two methods shows that the block-wise solution is on average 6cm more accurate than the strip-wise solution.

In this study, three different procedures: checkpoint RMS of residuals, statistical evaluation of AT results using t-test, and comparison of a photogrammetric digital surface model (DSM) and LiDAR data are used to analyse the effect of IMU and GNSS uncertainties on the final adjusted results. The outcome suggests that the method of block-wise GNSS shift correction is the better method for aerial triangulation and one should use appropriate observable weights in AT. The comparison of checkpoint RMS residuals between the two methods shows that the block-wise solution is on average 6cm more accurate than the strip-wise solution.

Direct georeferencing of airborne mobile mapping systems is developing with unprecedented speed using GNSS/INS integration. Removal of systematic errors is required for achieving a high accurate georeferenced product in mobile mapping platforms with integrated GNSS/INS sensors. It is crucial to consider the deflection of verticals (DOV) in direct georeferencing due to the recently improved INS sensor accuracy. This study determines the DOV using Sweden's EGM2008 model and gravity data. The influence of the DOVs on horizontal and vertical coordinates and considering different flight heights is assessed. The results confirm that the calculated DOV components using the EGM2008 model are sufficiently accurate for aerial photogrammetry purposes except for the mountainous areas because the topographic signal is not modeled correctly., QC 20220914

More accurate snow quality predictions are needed to economically and socially support communities in a changing Arctic environment. This contrasts with the current availability of affordable and efficient snow monitoring methods. In this study, a novel approach is presented to determine spatial snow depth distribution in challenging alpine terrain that was tested during a field campaign performed in the Tarfala valley, Kebnekaise mountains, northern Sweden, in April 2019. The combination of a multispectral camera and an Unmanned Aerial Vehicle (UAV) was used to derive three-dimensional (3D) snow surface models via Structure from Motion (SfM) with direct georeferencing. The main advantage over conventional photogrammetric surveys is the utilization of accurate Real-Time Kinematic (RTK) positioning which enables direct georeferencing of the images, and therefore eliminates the need for ground control points. The proposed method is capable of producing high -resolution 3D snow-covered surface models (<7 cm/pixel) of alpine areas up to eight hectares in a fast, reli-able and affordable way. The test sites' average snow depth was 160 cm with an average standard deviation of 78 cm. The overall Root-Mean-Square Errors (RMSE) of the snow depth range from 11.52 cm for data acquired in ideal surveying conditions to 41.03 cm in aggravated light and wind conditions. Results of this study suggest that the red components in the electromagnetic spectrum, i.e., the red, red edge, and near-infrared (NIR) band, contain the majority of information used in photogrammetric processing. The experiments highlighted a sig-nificant influence of the multi-spectral imagery on the quality of the final snow depth estimation as well as a strong potential to reduce processing times and computational resources by limiting the dimensionality of the imagery through the application of a Principal Component Analysis (PCA) before the photogrammetric 3D reconstruction. The proposed method is part of, QC 20220429

GNSS/INS applications are being developed, especially for direct georeferencing in airborne photogrammetry. Achieving accurately georeferenced products from the integration of GNSS and INS requires removing systematic errors in the mobile mapping systems. The INS sensor's uncertainty is decreasing; therefore, the influence of the deflection of verticals (DOV, the angle between the plumb line and normal to the ellipsoid) should be considered in the direct georeferencing. Otherwise, an error is imposed for calculating the exterior orientation parameters of the aerial images and aerial laser scanning. This study determines the DOV using the EGM2008 model and gravity data in Sweden. The impact of the DOVs on horizontal and vertical coordinates, considering different flight altitudes and camera field of view, is assessed. The results confirm that the calculated DOV components using the EGM2008 model are sufficiently accurate for aerial mapping system purposes except for mountainous areas because the topographic signal is not modelled correctly., QC 20230421

GNSS/INS applications are being developed, especially for direct georeferencing in airborne photogrammetry. Achieving accurately georeferenced products from the integration of GNSS and INS requires removing systematic errors in the mobile mapping systems. The INS sensor's uncertainty is decreasing; therefore, the influence of the deflection of verticals (DOV, the angle between the plumb line and normal to the ellipsoid) should be considered in the direct georeferencing. Otherwise, an error is imposed for calculating the exterior orientation parameters of the aerial images and aerial laser scanning. This study determines the DOV using the EGM2008 model and gravity data in Sweden. The impact of the DOVs on horizontal and vertical coordinates, considering different flight altitudes and camera field of view, is assessed. The results confirm that the calculated DOV components using the EGM2008 model are sufficiently accurate for aerial mapping system purposes except for mountainous areas because the topographic signal is not modelled correctly.

More accurate snow quality predictions are needed to economically and socially support communities in a changing Arctic environment. This contrasts with the current availability of affordable and efficient snow monitoring methods. In this study, a novel approach is presented to determine spatial snow depth distribution in challenging alpine terrain that was tested during a field campaign performed in the Tarfala valley, Kebnekaise mountains, northern Sweden, in April 2019. The combination of a multispectral camera and an Unmanned Aerial Vehicle (UAV) was used to derive three-dimensional (3D) snow surface models via Structure from Motion (SfM) with direct georeferencing. The main advantage over conventional photogrammetric surveys is the utilization of accurate Real-Time Kinematic (RTK) positioning which enables direct georeferencing of the images, and therefore eliminates the need for ground control points. The proposed method is capable of producing high -resolution 3D snow-covered surface models (<7 cm/pixel) of alpine areas up to eight hectares in a fast, reli-able and affordable way. The test sites' average snow depth was 160 cm with an average standard deviation of 78 cm. The overall Root-Mean-Square Errors (RMSE) of the snow depth range from 11.52 cm for data acquired in ideal surveying conditions to 41.03 cm in aggravated light and wind conditions. Results of this study suggest that the red components in the electromagnetic spectrum, i.e., the red, red edge, and near-infrared (NIR) band, contain the majority of information used in photogrammetric processing. The experiments highlighted a sig-nificant influence of the multi-spectral imagery on the quality of the final snow depth estimation as well as a strong potential to reduce processing times and computational resources by limiting the dimensionality of the imagery through the application of a Principal Component Analysis (PCA) before the photogrammetric 3D reconstruction. The proposed method is part of

With the advent of modern sensing technology, mapping products have begun to achieve an unprecedented precision of measurement. Considering their diverse use cases, several factors play a role in what would make the resulting measurements accurate. For light detection and ranging (LiDAR) and photogrammetry-based mapping solutions that implement vehicles outfitted with laser ranging devices, RGB cameras, and global navigation satellite system/inertial navigation system (GNSS/INS) georeferencing units, the quality of the derived mapping products is governed by the combined accuracy of the various sensors. While ranging errors associated with LiDAR systems or the imaging quality of RGB cameras are sensor-dependent and are mostly constant, the accuracy of a georeferencing unit depends on a variety of extrinsic factors, including but not limited to, availability of clear line-of-path to GNSS satellites and presence of radio interferences. The quality of the GNSS signal, in turn, is affected by the grade of hardware components used and, to a great extent, obstructions to signal reception. This document reports some of the major challenges of vehicle-based mobile mapping with regards to GNSS/INS navigation. The background of GNSS/INS positioning is discussed to build a framework for trajectory enhancement as well as improvement of LiDAR mapping products. The focus is put on using available sensor data from LiDAR and/or cameras to enhance their position/orientation quality. Some best practices in light of potential trajectory deterioration are also recommended.

GNSS/INS applications are being developed, especially for direct georeferencing in airborne photogrammetry. Achieving accurately georeferenced products from the integration of GNSS and INS requires removing systematic errors in the mobile mapping systems. The INS sensor's uncertainty is decreasing; therefore, the influence of the deflection of verticals (DOV, the angle between the plumb line and normal to the ellipsoid) should be considered in the direct georeferencing. Otherwise, an error is imposed for calculating the exterior orientation parameters of the aerial images and aerial laser scanning. This study determines the DOV using the EGM2008 model and gravity data in Sweden. The impact of the DOVs on horizontal and vertical coordinates, considering different flight altitudes and camera field of view, is assessed. The results confirm that the calculated DOV components using the EGM2008 model are sufficiently accurate for aerial mapping system purposes except for mountainous areas because the topographic signal is not modelled correctly.

GNSS/INS applications are being developed, especially for direct georeferencing in airborne photogrammetry. Achieving accurately georeferenced products from the integration of GNSS and INS requires removing systematic errors in the mobile mapping systems. The INS sensor's uncertainty is decreasing; therefore, the influence of the deflection of verticals (DOV, the angle between the plumb line and normal to the ellipsoid) should be considered in the direct georeferencing. Otherwise, an error is imposed for calculating the exterior orientation parameters of the aerial images and aerial laser scanning. This study determines the DOV using the EGM2008 model and gravity data in Sweden. The impact of the DOVs on horizontal and vertical coordinates, considering different flight altitudes and camera field of view, is assessed. The results confirm that the calculated DOV components using the EGM2008 model are sufficiently accurate for aerial mapping system purposes except for mountainous areas because the topographic signal is not modelled correctly.

In this study, three different procedures: checkpoint RMS of residuals, statistical evaluation of AT results using t-test, and comparison of a photogrammetric digital surface model (DSM) and LiDAR data are used to analyse the effect of IMU and GNSS uncertainties on the final adjusted results. The outcome suggests that the method of block-wise GNSS shift correction is the better method for aerial triangulation and one should use appropriate observable weights in AT. The comparison of checkpoint RMS residuals between the two methods shows that the block-wise solution is on average 6cm more accurate than the strip-wise solution.

More accurate snow quality predictions are needed to economically and socially support communities in a changing Arctic environment. This contrasts with the current availability of affordable and efficient snow monitoring methods. In this study, a novel approach is presented to determine spatial snow depth distribution in challenging alpine terrain that was tested during a field campaign performed in the Tarfala valley, Kebnekaise mountains, northern Sweden, in April 2019. The combination of a multispectral camera and an Unmanned Aerial Vehicle (UAV) was used to derive three-dimensional (3D) snow surface models via Structure from Motion (SfM) with direct georeferencing. The main advantage over conventional photogrammetric surveys is the utilization of accurate Real-Time Kinematic (RTK) positioning which enables direct georeferencing of the images, and therefore eliminates the need for ground control points. The proposed method is capable of producing high -resolution 3D snow-covered surface models (<7 cm/pixel) of alpine areas up to eight hectares in a fast, reli-able and affordable way. The test sites' average snow depth was 160 cm with an average standard deviation of 78 cm. The overall Root-Mean-Square Errors (RMSE) of the snow depth range from 11.52 cm for data acquired in ideal surveying conditions to 41.03 cm in aggravated light and wind conditions. Results of this study suggest that the red components in the electromagnetic spectrum, i.e., the red, red edge, and near-infrared (NIR) band, contain the majority of information used in photogrammetric processing. The experiments highlighted a sig-nificant influence of the multi-spectral imagery on the quality of the final snow depth estimation as well as a strong potential to reduce processing times and computational resources by limiting the dimensionality of the imagery through the application of a Principal Component Analysis (PCA) before the photogrammetric 3D reconstruction. The proposed method is part of

In this study, three different procedures: checkpoint RMS of residuals, statistical evaluation of AT results using t-test, and comparison of a photogrammetric digital surface model (DSM) and LiDAR data are used to analyse the effect of IMU and GNSS uncertainties on the final adjusted results. The outcome suggests that the method of block-wise GNSS shift correction is the better method for aerial triangulation and one should use appropriate observable weights in AT. The comparison of checkpoint RMS residuals between the two methods shows that the block-wise solution is on average 6cm more accurate than the strip-wise solution.

In this study, three different procedures: checkpoint RMS of residuals, statistical evaluation of AT results using t-test, and comparison of a photogrammetric digital surface model (DSM) and LiDAR data are used to analyse the effect of IMU and GNSS uncertainties on the final adjusted results. The outcome suggests that the method of block-wise GNSS shift correction is the better method for aerial triangulation and one should use appropriate observable weights in AT. The comparison of checkpoint RMS residuals between the two methods shows that the block-wise solution is on average 6cm more accurate than the strip-wise solution.

In this study, three different procedures: checkpoint RMS of residuals, statistical evaluation of AT results using t-test, and comparison of a photogrammetric digital surface model (DSM) and LiDAR data are used to analyse the effect of IMU and GNSS uncertainties on the final adjusted results. The outcome suggests that the method of block-wise GNSS shift correction is the better method for aerial triangulation and one should use appropriate observable weights in AT. The comparison of checkpoint RMS residuals between the two methods shows that the block-wise solution is on average 6cm more accurate than the strip-wise solution., QC 20210518

This article presents unmanned aerial system (UAS)-based photogrammetry as an efficient method for the estimation of snow-field parameters, including snow depth, volume, and~snow-covered area. Unlike~similar studies employing UASs, this method benefits from the rapid development of compact, high-accuracy global navigation satellite system (GNSS) receivers. Our custom-built, multi-sensor system for UAS photogrammetry facilitates attaining centimeter- to decimeter-level object accuracy without deploying ground control points; this technique is generally known as direct georeferencing. The method was demonstrated at Mapa Republiky, a snow field located in the Krkonose, a mountain range in the Czech Republic. The location has attracted the interest of scientists due to its specific characteristics; multiple approaches to snow-field parameter estimation have thus been employed in that area to date. According to the results achieved within this study, the proposed method can be considered the optimum solution since it not only attains superior density and spatial object accuracy (approximately one decimeter) but also significantly reduces the data collection time and, above all, eliminates field work to markedly reduce the health risks associated with avalanches.

This article presents unmanned aerial system (UAS)-based photogrammetry as an efficient method for the estimation of snow-field parameters, including snow depth, volume, and~snow-covered area. Unlike~similar studies employing UASs, this method benefits from the rapid development of compact, high-accuracy global navigation satellite system (GNSS) receivers. Our custom-built, multi-sensor system for UAS photogrammetry facilitates attaining centimeter- to decimeter-level object accuracy without deploying ground control points; this technique is generally known as direct georeferencing. The method was demonstrated at Mapa Republiky, a snow field located in the Krkonose, a mountain range in the Czech Republic. The location has attracted the interest of scientists due to its specific characteristics; multiple approaches to snow-field parameter estimation have thus been employed in that area to date. According to the results achieved within this study, the proposed method can be considered the optimum solution since it not only attains superior density and spatial object accuracy (approximately one decimeter) but also significantly reduces the data collection time and, above all, eliminates field work to markedly reduce the health risks associated with avalanches.

This article presents unmanned aerial system (UAS)-based photogrammetry as an efficient method for the estimation of snow-field parameters, including snow depth, volume, and~snow-covered area. Unlike~similar studies employing UASs, this method benefits from the rapid development of compact, high-accuracy global navigation satellite system (GNSS) receivers. Our custom-built, multi-sensor system for UAS photogrammetry facilitates attaining centimeter- to decimeter-level object accuracy without deploying ground control points; this technique is generally known as direct georeferencing. The method was demonstrated at Mapa Republiky, a snow field located in the Krkonose, a mountain range in the Czech Republic. The location has attracted the interest of scientists due to its specific characteristics; multiple approaches to snow-field parameter estimation have thus been employed in that area to date. According to the results achieved within this study, the proposed method can be considered the optimum solution since it not only attains superior density and spatial object accuracy (approximately one decimeter) but also significantly reduces the data collection time and, above all, eliminates field work to markedly reduce the health risks associated with avalanches.

This article presents unmanned aerial system (UAS)-based photogrammetry as an efficient method for the estimation of snow-field parameters, including snow depth, volume, and~snow-covered area. Unlike~similar studies employing UASs, this method benefits from the rapid development of compact, high-accuracy global navigation satellite system (GNSS) receivers. Our custom-built, multi-sensor system for UAS photogrammetry facilitates attaining centimeter- to decimeter-level object accuracy without deploying ground control points; this technique is generally known as direct georeferencing. The method was demonstrated at Mapa Republiky, a snow field located in the Krkonose, a mountain range in the Czech Republic. The location has attracted the interest of scientists due to its specific characteristics; multiple approaches to snow-field parameter estimation have thus been employed in that area to date. According to the results achieved within this study, the proposed method can be considered the optimum solution since it not only attains superior density and spatial object accuracy (approximately one decimeter) but also significantly reduces the data collection time and, above all, eliminates field work to markedly reduce the health risks associated with avalanches.

This article presents unmanned aerial system (UAS)-based photogrammetry as an efficient method for the estimation of snow-field parameters, including snow depth, volume, and~snow-covered area. Unlike~similar studies employing UASs, this method benefits from the rapid development of compact, high-accuracy global navigation satellite system (GNSS) receivers. Our custom-built, multi-sensor system for UAS photogrammetry facilitates attaining centimeter- to decimeter-level object accuracy without deploying ground control points; this technique is generally known as direct georeferencing. The method was demonstrated at Mapa Republiky, a snow field located in the Krkonose, a mountain range in the Czech Republic. The location has attracted the interest of scientists due to its specific characteristics; multiple approaches to snow-field parameter estimation have thus been employed in that area to date. According to the results achieved within this study, the proposed method can be considered the optimum solution since it not only attains superior density and spatial object accuracy (approximately one decimeter) but also significantly reduces the data collection time and, above all, eliminates field work to markedly reduce the health risks associated with avalanches.

This article presents unmanned aerial system (UAS)-based photogrammetry as an efficient method for the estimation of snow-field parameters, including snow depth, volume, and~snow-covered area. Unlike~similar studies employing UASs, this method benefits from the rapid development of compact, high-accuracy global navigation satellite system (GNSS) receivers. Our custom-built, multi-sensor system for UAS photogrammetry facilitates attaining centimeter- to decimeter-level object accuracy without deploying ground control points; this technique is generally known as direct georeferencing. The method was demonstrated at Mapa Republiky, a snow field located in the Krkonose, a mountain range in the Czech Republic. The location has attracted the interest of scientists due to its specific characteristics; multiple approaches to snow-field parameter estimation have thus been employed in that area to date. According to the results achieved within this study, the proposed method can be considered the optimum solution since it not only attains superior density and spatial object accuracy (approximately one decimeter) but also significantly reduces the data collection time and, above all, eliminates field work to markedly reduce the health risks associated with avalanches.

This article presents unmanned aerial system (UAS)-based photogrammetry as an efficient method for the estimation of snow-field parameters, including snow depth, volume, and~snow-covered area. Unlike~similar studies employing UASs, this method benefits from the rapid development of compact, high-accuracy global navigation satellite system (GNSS) receivers. Our custom-built, multi-sensor system for UAS photogrammetry facilitates attaining centimeter- to decimeter-level object accuracy without deploying ground control points; this technique is generally known as direct georeferencing. The method was demonstrated at Mapa Republiky, a snow field located in the Krkonose, a mountain range in the Czech Republic. The location has attracted the interest of scientists due to its specific characteristics; multiple approaches to snow-field parameter estimation have thus been employed in that area to date. According to the results achieved within this study, the proposed method can be considered the optimum solution since it not only attains superior density and spatial object accuracy (approximately one decimeter) but also significantly reduces the data collection time and, above all, eliminates field work to markedly reduce the health risks associated with avalanches.

The georeferencing process is crucial to the accuracy of terrestrial laser scanner (TLS) data, in particular in the context of diachronic studies relying on multi-temporal surveys. The use of Ground Control Points in the georeferencing process can however be complex when confronted with the practical constraints of coastal surveying. A simple and quick alternative method called "pseudo-direct georeferencing" is proposed in the present paper. This method involves internal inclinometers to measure roll and pitch angles and a centimetric GPS to measure the position of the TLS center and the position of one backsight target. When assessing the transformational uncertainty by using a set of independent ground validation points for both classical indirect and proposed pseudo-direct methods, we respectively obtain root mean square errors of 4.4 cm for the indirect method and 3.8 cm for the pseudo-direct method.

Processing of raw point cloud data obtained as a result of terrestrial laser scanning (TLS) sometimes involves georeferencing, i.e. transformation of point cloud data to an external coordinate system. This paper focuses on defining the error model of point positions obtained through a "station-orientation" procedure of direct georeferencing. The original error model presented by the authors relevant in this field is partly altered. All modifications are explained in detail within the paper and the reported model is statistically verified based on the carefully conducted experiment using Leica ScanStation P20 scanner. The obtained values of the uncertainty measures of direct georeferencing Which are of a few millimetre magnitude prove that this procedure can be efficiently used for planning and carrying out even more demanding surveying tasks, including those during monitoring and maintenance of constructed facilities. Additionally, traversing capabilities of terrestrial laser scanners tightly connected with direct georeferencing should contribute to mass introduction of laser scanning into the construction industry thanks to its similarities to the highly automated procedures of polar surveying and traversing which are traditionally employed among surveyors.

The georeferencing process is crucial to the accuracy of terrestrial laser scanner (TLS) data, in particular in the context of diachronic studies relying on multi-temporal surveys. The use of Ground Control Points in the georeferencing process can however be complex when confronted with the practical constraints of coastal surveying. A simple and quick alternative method called "pseudo-direct georeferencing" is proposed in the present paper. This method involves internal inclinometers to measure roll and pitch angles and a centimetric GPS to measure the position of the TLS center and the position of one backsight target. When assessing the transformational uncertainty by using a set of independent ground validation points for both classical indirect and proposed pseudo-direct methods, we respectively obtain root mean square errors of 4.4 cm for the indirect method and 3.8 cm for the pseudo-direct method.

The georeferencing process is crucial to the accuracy of terrestrial laser scanner (TLS) data, in particular in the context of diachronic studies relying on multi-temporal surveys. The use of Ground Control Points in the georeferencing process can however be complex when confronted with the practical constraints of coastal surveying. A simple and quick alternative method called "pseudo-direct georeferencing" is proposed in the present paper. This method involves internal inclinometers to measure roll and pitch angles and a centimetric GPS to measure the position of the TLS center and the position of one backsight target. When assessing the transformational uncertainty by using a set of independent ground validation points for both classical indirect and proposed pseudo-direct methods, we respectively obtain root mean square errors of 4.4 cm for the indirect method and 3.8 cm for the pseudo-direct method.

Processing of raw point cloud data obtained as a result of terrestrial laser scanning (TLS) sometimes involves georeferencing, i.e. transformation of point cloud data to an external coordinate system. This paper focuses on defining the error model of point positions obtained through a "station-orientation" procedure of direct georeferencing. The original error model presented by the authors relevant in this field is partly altered. All modifications are explained in detail within the paper and the reported model is statistically verified based on the carefully conducted experiment using Leica ScanStation P20 scanner. The obtained values of the uncertainty measures of direct georeferencing Which are of a few millimetre magnitude prove that this procedure can be efficiently used for planning and carrying out even more demanding surveying tasks, including those during monitoring and maintenance of constructed facilities. Additionally, traversing capabilities of terrestrial laser scanners tightly connected with direct georeferencing should contribute to mass introduction of laser scanning into the construction industry thanks to its similarities to the highly automated procedures of polar surveying and traversing which are traditionally employed among surveyors.

The direct georeferencing in aerial photogrammetry requires precise measurement of position and attitude of an image sensor, because the object point position is computed directly using this data. But for several reasons, data from onboard inertial navigation system can not be used for this purpose directly. Especially GNSS antenna displacement and image sensor misalignment have to be compensated and different rotation and coordinate system conventions have to be taken into account. This paper describes the transformations of onboard GNSS/INS data for the needs of the direct georeferencing and demonstrates it on a real UAV photogrammetric mission.

The direct georeferencing in aerial photogrammetry requires precise measurement of position and attitude of an image sensor, because the object point position is computed directly using this data. But for several reasons, data from onboard inertial navigation system can not be used for this purpose directly. Especially GNSS antenna displacement and image sensor misalignment have to be compensated and different rotation and coordinate system conventions have to be taken into account. This paper describes the transformations of onboard GNSS/INS data for the needs of the direct georeferencing and demonstrates it on a real UAV photogrammetric mission.

The direct georeferencing in aerial photogrammetry requires precise measurement of position and attitude of an image sensor, because the object point position is computed directly using this data. But for several reasons, data from onboard inertial navigation system can not be used for this purpose directly. Especially GNSS antenna displacement and image sensor misalignment have to be compensated and different rotation and coordinate system conventions have to be taken into account. This paper describes the transformations of onboard GNSS/INS data for the needs of the direct georeferencing and demonstrates it on a real UAV photogrammetric mission.

The direct georeferencing in aerial photogrammetry requires precise measurement of position and attitude of an image sensor, because the object point position is computed directly using this data. But for several reasons, data from onboard inertial navigation system can not be used for this purpose directly. Especially GNSS antenna displacement and image sensor misalignment have to be compensated and different rotation and coordinate system conventions have to be taken into account. This paper describes the transformations of onboard GNSS/INS data for the needs of the direct georeferencing and demonstrates it on a real UAV photogrammetric mission.

The direct georeferencing in aerial photogrammetry requires precise measurement of position and attitude of an image sensor, because the object point position is computed directly using this data. But for several reasons, data from onboard inertial navigation system can not be used for this purpose directly. Especially GNSS antenna displacement and image sensor misalignment have to be compensated and different rotation and coordinate system conventions have to be taken into account. This paper describes the transformations of onboard GNSS/INS data for the needs of the direct georeferencing and demonstrates it on a real UAV photogrammetric mission.

The direct georeferencing in aerial photogrammetry requires precise measurement of position and attitude of an image sensor, because the object point position is computed directly using this data. But for several reasons, data from onboard inertial navigation system can not be used for this purpose directly. Especially GNSS antenna displacement and image sensor misalignment have to be compensated and different rotation and coordinate system conventions have to be taken into account. This paper describes the transformations of onboard GNSS/INS data for the needs of the direct georeferencing and demonstrates it on a real UAV photogrammetric mission.

In this paper, a combined terrestrial laser scanning survey system is presented, where GPS can be used for direct georeferencing of the point clouds. The results of investigations of this system show that it is possible to achieve the coordinate accuracy of better than 1 cm in the point cloud, both in plane and height, at the object distance of up to about 70 m., In diesem Artikel wird ein kombiniertes terrestrisches Laserscanning-Vermessungssystem vorgestellt, bei dem GPS für eine direkte Georeferenzierung der Punktwolken verwendet werden kann. Die Ergebnisse der Prüfung dieses Systems zeigen, dass es möglich ist, eine Koordinatengenauigkeit von mehr als 1 cm in der Punktwolke, sowohl in Fläche wie Höhe, bei einer Objektdistanz von bis zu 70 m zu erreichen., Originally published in zfv 3/2010, Vol. 135, pp 151-159, Wissner-Verlag, Augsburg, 2010. Reproduced with permission from the publisher.

In this paper, a combined terrestrial laser scanning survey system is presented, where GPS can be used for direct georeferencing of the point clouds. The results of investigations of this system show that it is possible to achieve the coordinate accuracy of better than 1 cm in the point cloud, both in plane and height, at the object distance of up to about 70 m., In diesem Artikel wird ein kombiniertes terrestrisches Laserscanning-Vermessungssystem vorgestellt, bei dem GPS für eine direkte Georeferenzierung der Punktwolken verwendet werden kann. Die Ergebnisse der Prüfung dieses Systems zeigen, dass es möglich ist, eine Koordinatengenauigkeit von mehr als 1 cm in der Punktwolke, sowohl in Fläche wie Höhe, bei einer Objektdistanz von bis zu 70 m zu erreichen., Originally published in zfv 3/2010, Vol. 135, pp 151-159, Wissner-Verlag, Augsburg, 2010. Reproduced with permission from the publisher.

In this paper, a combined terrestrial laser scanning survey system is presented, where GPS can be used for direct georeferencing of the point clouds. The results of investigations of this system show that it is possible to achieve the coordinate accuracy of better than 1 cm in the point cloud, both in plane and height, at the object distance of up to about 70 m., In diesem Artikel wird ein kombiniertes terrestrisches Laserscanning-Vermessungssystem vorgestellt, bei dem GPS für eine direkte Georeferenzierung der Punktwolken verwendet werden kann. Die Ergebnisse der Prüfung dieses Systems zeigen, dass es möglich ist, eine Koordinatengenauigkeit von mehr als 1 cm in der Punktwolke, sowohl in Fläche wie Höhe, bei einer Objektdistanz von bis zu 70 m zu erreichen., Originally published in zfv 3/2010, Vol. 135, pp 151-159, Wissner-Verlag, Augsburg, 2010. Reproduced with permission from the publisher.

In this paper, a combined terrestrial laser scanning survey system is presented, where GPS can be used for direct georeferencing of the point clouds. The results of investigations of this system show that it is possible to achieve the coordinate accuracy of better than 1 cm in the point cloud, both in plane and height, at the object distance of up to about 70 m., In diesem Artikel wird ein kombiniertes terrestrisches Laserscanning-Vermessungssystem vorgestellt, bei dem GPS für eine direkte Georeferenzierung der Punktwolken verwendet werden kann. Die Ergebnisse der Prüfung dieses Systems zeigen, dass es möglich ist, eine Koordinatengenauigkeit von mehr als 1 cm in der Punktwolke, sowohl in Fläche wie Höhe, bei einer Objektdistanz von bis zu 70 m zu erreichen., Originally published in zfv 3/2010, Vol. 135, pp 151-159, Wissner-Verlag, Augsburg, 2010. Reproduced with permission from the publisher.

In this paper, a combined terrestrial laser scanning survey system is presented, where GPS can be used for direct georeferencing of the point clouds. The results of investigations of this system show that it is possible to achieve the coordinate accuracy of better than 1 cm in the point cloud, both in plane and height, at the object distance of up to about 70 m., In diesem Artikel wird ein kombiniertes terrestrisches Laserscanning-Vermessungssystem vorgestellt, bei dem GPS für eine direkte Georeferenzierung der Punktwolken verwendet werden kann. Die Ergebnisse der Prüfung dieses Systems zeigen, dass es möglich ist, eine Koordinatengenauigkeit von mehr als 1 cm in der Punktwolke, sowohl in Fläche wie Höhe, bei einer Objektdistanz von bis zu 70 m zu erreichen., Originally published in zfv 3/2010, Vol. 135, pp 151-159, Wissner-Verlag, Augsburg, 2010. Reproduced with permission from the publisher.

An important step in data processing from terrestrial laser scanning (TLS) is georeferencing, i.e. transformation of the scanner data (point clouds) into a real world coordinate system, which is important for their integration with other geospatial data. An efficient approach for this is direct georeferencing, whereby the position and orientation of the scanner can be determined in the field, similarly to the working routine of total stations. Thus the efficiency of the survey can be increased, and the project time and costs reduced. An important factor that affects the results of TLS surveys, especially those with direct georeferencing, is scanner calibration. In the recent years, the method of self-calibration used in photogrammetry has become popular for the recovery of systematic errors in laser scanners. This thesis has two main aims. The first one is to develop an approach for self-calibration of terrestrial laser scanners, which can be made available to users, and apply it to the calibration of a number of pulsed laser scanners in order to get a better insight into the systematic instrumental errors present in these instruments. The second aim is to investigate the possibilities for direct georeferencing in TLS in static applications, with the focus on the use of GPS for this purpose, and to develop a survey system based on the combination of TLS and GPS. An additional aim of the thesis is to make a systematic description of the error sources in TLS surveys, where direct georeferencing is employed. A good understanding of these error sources is necessary to secure the data accuracy. We subdivide these errors into four groups: instrumental, object-related, environmental and georeferencing. We have developed a unified approach for self-calibration of terrestrial laser scanners, where one can introduce stochastic information about all the estimated parameters, which helps in reducing their correlations. In part, it is possible to use direct georeferencing to det, QC 20100806, 3D laser scanning of engineering constructions and historical monuments

An important step in data processing from terrestrial laser scanning (TLS) is georeferencing, i.e. transformation of the scanner data (point clouds) into a real world coordinate system, which is important for their integration with other geospatial data. An efficient approach for this is direct georeferencing, whereby the position and orientation of the scanner can be determined in the field, similarly to the working routine of total stations. Thus the efficiency of the survey can be increased, and the project time and costs reduced. An important factor that affects the results of TLS surveys, especially those with direct georeferencing, is scanner calibration. In the recent years, the method of self-calibration used in photogrammetry has become popular for the recovery of systematic errors in laser scanners. This thesis has two main aims. The first one is to develop an approach for self-calibration of terrestrial laser scanners, which can be made available to users, and apply it to the calibration of a number of pulsed laser scanners in order to get a better insight into the systematic instrumental errors present in these instruments. The second aim is to investigate the possibilities for direct georeferencing in TLS in static applications, with the focus on the use of GPS for this purpose, and to develop a survey system based on the combination of TLS and GPS. An additional aim of the thesis is to make a systematic description of the error sources in TLS surveys, where direct georeferencing is employed. A good understanding of these error sources is necessary to secure the data accuracy. We subdivide these errors into four groups: instrumental, object-related, environmental and georeferencing. We have developed a unified approach for self-calibration of terrestrial laser scanners, where one can introduce stochastic information about all the estimated parameters, which helps in reducing their correlations. In part, it is possible to use direct georeferencing to det, QC 20100806, 3D laser scanning of engineering constructions and historical monuments

During the last decade, terrestrial laser scanning (TLS) has appeared as a new surveying technique. Its proper use requires good knowledge of the error sources, comprehensive description of which is currently lacking. Especially important are systematic instrumental errors, which are determined during calibration. Recently, the method of self-calibration used in photogrammetry has been shown to be efficient for laser scanners. Another important task in TLS is georeferencing – transformation of the point clouds into a specific coordinate system. This book provides a systematic description of the error sources in TLS surveys conducted with direct georeferencing. Further, a new, unified approach for laser scanner self-calibration is described, and the results of calibration of three scanners are reported. Finally, a prototype combined TLS survey system is presented, which employs GPS for direct georeferencing of the point clouds, and can be used for accurate surveys of built environments. The book should be useful to students and researchers in Engineering Surveying as well as surveyors in public and private sector., Innehållet i boken är refereegranskat, eftersom boken är en omarbetad doktorsavhandling.

An important step in data processing from terrestrial laser scanning (TLS) is georeferencing, i.e. transformation of the scanner data (point clouds) into a real world coordinate system, which is important for their integration with other geospatial data. An efficient approach for this is direct georeferencing, whereby the position and orientation of the scanner can be determined in the field, similarly to the working routine of total stations. Thus the efficiency of the survey can be increased, and the project time and costs reduced. An important factor that affects the results of TLS surveys, especially those with direct georeferencing, is scanner calibration. In the recent years, the method of self-calibration used in photogrammetry has become popular for the recovery of systematic errors in laser scanners. This thesis has two main aims. The first one is to develop an approach for self-calibration of terrestrial laser scanners, which can be made available to users, and apply it to the calibration of a number of pulsed laser scanners in order to get a better insight into the systematic instrumental errors present in these instruments. The second aim is to investigate the possibilities for direct georeferencing in TLS in static applications, with the focus on the use of GPS for this purpose, and to develop a survey system based on the combination of TLS and GPS. An additional aim of the thesis is to make a systematic description of the error sources in TLS surveys, where direct georeferencing is employed. A good understanding of these error sources is necessary to secure the data accuracy. We subdivide these errors into four groups: instrumental, object-related, environmental and georeferencing. We have developed a unified approach for self-calibration of terrestrial laser scanners, where one can introduce stochastic information about all the estimated parameters, which helps in reducing their correlations. In part, it is possible to use direct georeferencing to det, QC 20100806, 3D laser scanning of engineering constructions and historical monuments