Evaluating the Landslides Characterization and Deformation Using Multi-Temporal Uav Imageries in Northern Pakistan

Abstract The Un Manned Aerial Vehicles (UAVs) have emerged as an effective tool for mapping and evaluating the landslides dynamics. This study aims to evaluate the dynamics of the landslide using the UAV derived aerial photos and Digital Surface Model (DSM). The selected landslides are the Nara and Nokot landslides in the rough terrain of Balakot, north Pakistan. The UAV survey was carried in April and August 2019 for Nara and Nokot landslides in Balakot. The images were processed in the Pix4D mapper to compute the orthomosaic and DSMs. The Ground Control Points (GCPs) collected in the geodetic survey with the Global Navigation Satellite System (GNSS) using Post Processing Kinematic (PPK) were used to accurately co-register and orthorectify the UAV imageries. The derived DSMs were analyzed to evaluate the dynamics in the landslide’s topography and volumetric changes. The shaded relief single band was used to correlate the temporal images for the Nara and Nokot landslide using the COSI-Corr algorithm. The statistical and frequent correlator was used for landslide displacement. The result shows that the Nara landside has a surface movement ranging from 1 to 29 m in the NE scarp and lateral areas. The Nokot landslide has active NS, NE and NW scarps with a surface movement ranging from 1 to 25.5 m. The accuracy assessment reveals the RMSE calculated for the Nara landslide as 4.58 m and 4.24 m for the Nokot landslide. This study reflected the potential application of UAVs for monitoring the landslides dynamics to mitigate the hazard.

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MULTI-TEMPORAL IMAGE CO-REGISTRATION OF UAV BLOCKS: A COMPARISON OF DIFFERENT APPROACHES

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprs-archives-xliii-b2-2021-9-2021 ◽

2021 ◽

Vol XLIII-B2-2021 ◽

pp. 9-16

Author(s):

P. Garieri ◽

M. Riboloni ◽

G. Forlani ◽

R. Roncella

Keyword(s):

Environmental Changes ◽

Satellite System ◽

Ground Control ◽

Unmanned Aerial Systems ◽

Additional Information ◽

Ground Control Points ◽

Multi Temporal ◽

Survey Accuracy ◽

Global Navigation Satellite ◽

Aerial Systems

Abstract. Traditionally, data co-registration of survey epochs in photogrammetry relied on Ground Control Points (GCP) to keep the reference system unchanged. In the last years, Unmanned Aerial Systems (UAV) are increasingly used in photogrammetric environmental monitoring. The diffusion of affordable UAV platforms equipped with GNSS (Global Navigation Satellite System) centimetre-grade receivers might reduce, but not eliminate, the need for GCP. Conversely, if GNSS-assisted orientation cannot be used or if additional ground control and reliability checks are required, alternatives to repeated GCP survey have been proposed, taking advantage of Structure from Motion (SfM) photogrammetry. In particular, co-registering different epochs image blocks together, identifying corresponding features, has been demonstrated as a viable and efficient approach. In this paper four different strategies easily implementable in a generic commercial photogrammetric software are presented and compared considering three different test sites in Italy subject to different amounts of environmental changes. The influence of the amount and distribution of inter-epoch corresponding points on the accuracy of the reconstruction is investigated. The results show that some of the tested strategies obtains very good results and can be used (although not needed) also in RTK centimetre-grade UAV surveys, leveraging the additional information coming from previous epochs survey to actually increase the survey accuracy and reliability.

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DIGITAL SURFACE MODEL DERIVED FROM UAS IMAGERY ASSESSMENT USING HIGH-PRECISION AERIAL LIDAR AS REFERENCE SURFACE

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprs-archives-xliv-m-2-2020-61-2020 ◽

2020 ◽

Vol XLIV-M-2-2020 ◽

pp. 61-67

Author(s):

J. Lopez ◽

R. Munjy

Keyword(s):

High Precision ◽

Focal Length ◽

Vertical Plane ◽

Satellite System ◽

Ease Of Use ◽

Surface Model ◽

Digital Surface Model ◽

Ground Control Points ◽

Global Navigation Satellite ◽

A Site

Abstract. Imagery captured from aerial unmanned systems (UAS) has found significant utility in the field of surveying and mapping as the efforts of the computer vision field combined the principles of photogrammetry. Its respectability in the remote sensing community as increased as the miniaturization of on-board survey-grade global navigation satellite system (GNSS) signal receivers has made it possible to produce high network accuracy contributing to effective aerotriangulation. UAS photogrammetry has gained much popularity because of its effectiveness, efficiency, economy, and especially its availability and ease of use. Although photogrammetry has proven to meet and exceed planimetric precision and accuracy, variables tend to cause deficiencies in the achievement of accuracy in the vertical plane. This research aims to demonstrate achievable overall accuracy of surface modelling through minimization of systematic errors at a significant level using a fixed-wing platform designed for high-accuracy surveying with the eBee Plus and X models by SenseFly equipped with survey-grade GNSS signal-receiving capabilities and 20MP integrated, fixed-focal length camera. The UAS campaign was flown over a site 320 m by 320 m with 81 surveyed 3D ground control points, where horizontal positions were surveyed to 1.0 cm horizontal accuracy and 0.5 cm vertical accuracy using static GNSS methods and digital leveling respectively. All AT accuracy was based on 75 independent checkpoints. The digital surface model (DSM) was compared to a reference DSM generated from high-precision manned aerial LiDAR using the Optech Galaxy scanner. Overall accuracy was in the sub-decimeter level vertically in both commercial software used, including Pix4Dmapper and Agisoft Metashape.

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Deriving surface soil moisture from reflected GNSS signal observations from a grassland site in southwestern France

10.5194/hess-2017-597 ◽

2017 ◽

Author(s):

Sibo Zhang ◽

Jean-Christophe Calvet ◽

José Darrozes ◽

Nicolas Roussel ◽

Frédéric Frappart ◽

...

Keyword(s):

Soil Moisture ◽

Land Surface ◽

Land Surface Model ◽

Ground Surface ◽

Satellite System ◽

Surface Model ◽

Global Navigation Satellite ◽

Grassland Site

Abstract. This work aims to assess the estimation of surface volumetric soil moisture (VSM) using the Global Navigation Satellite System Interferometric Reflectometry (GNSS-IR) technique. Year-round observations were acquired from a grassland site in southwestern France using an antenna consecutively placed at two contrasting heights above the ground surface (3.3 or 29.4 m). The VSM retrievals are compared with two independent reference datasets: in situ observations of soil moisture, and numerical simulations of soil moisture and vegetation biomass from the ISBA (Interactions between Soil, Biosphere and Atmosphere) land surface model. Scaled VSM estimates can be retrieved throughout the year removing vegetation effects by the separation of growth and senescence periods and by the filtering of the GNSS-IR observations that are most affected by vegetation. Antenna height has no significant impact on the quality of VSM estimates. Comparisons between the VSM GNSS-IR retrievals and the in situ VSM observations at a depth of 5 cm show a good agreement (R2 = 0.86 and RMSE = 0.04 m3 m−3). It is shown that the signal is sensitive to the grass litter water content and that this effect triggers differences between VSM retrievals and in situ VSM observations at depths of 1 cm and 5 cm, especially during light rainfall events.

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Simulation of GNSS Availability in Urban Environments Using a Panoramic Image Dataset

International Journal of Navigation and Observation ◽

10.1155/2017/8047158 ◽

2017 ◽

Vol 2017 ◽

pp. 1-12 ◽

Cited By ~ 4

Author(s):

Sakpod Tongleamnak ◽

Masahiko Nagai

Keyword(s):

Urban Areas ◽

Accuracy Assessment ◽

Satellite System ◽

Urban Environments ◽

Panoramic Image ◽

Image Processing Techniques ◽

Gnss Positioning ◽

Image Dataset ◽

Global Navigation Satellite ◽

Processing Techniques

Performance of Global Navigation Satellite System (GNSS) positioning in urban environments is hindered by poor satellite availability because there are many man-made and natural objects in urban environments that obstruct satellite signals. To evaluate the availability of GNSS in cities, this paper presents a software simulation of GNSS availability in urban areas using a panoramic image dataset from Google Street View. Photogrammetric image processing techniques are applied to reconstruct fisheye sky view images and detect signal obstacles. Two comparisons of the results from the simulation and real world observation in Bangkok and Tokyo are also presented and discussed for accuracy assessment.

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RTK GNSS-Assisted Terrestrial SfM Photogrammetry without GCP: Application to Coastal Morphodynamics Monitoring

Remote Sensing ◽

10.3390/rs12111889 ◽

2020 ◽

Vol 12 (11) ◽

pp. 1889 ◽

Cited By ~ 3

Author(s):

Marion Jaud ◽

Stéphane Bertin ◽

Mickaël Beauverger ◽

Emmanuel Augereau ◽

Christophe Delacourt

Keyword(s):

Standard Deviation ◽

Low Cost ◽

Laser Scanner ◽

Satellite System ◽

Mean Error ◽

Ground Control Points ◽

Participatory Science ◽

Gnss Network ◽

Global Navigation Satellite

The present article describes a new and efficient method of Real Time Kinematic (RTK) Global Navigation Satellite System (GNSS) assisted terrestrial Structure-from-Motion (SfM) photogrammetry without the need for Ground Control Points (GCPs). The system only requires a simple frame that mechanically connects a RTK GNSS antenna to the camera. The system is low cost, easy to transport, and offers high autonomy. Furthermore, not requiring GCPs enables saving time during the in situ acquisition and during data processing. The method is tested for coastal cliff monitoring, using both a Reflex camera and a Smartphone camera. The quality of the reconstructions is assessed by comparison to a synchronous Terrestrial Laser Scanner (TLS) acquisition. The results are highly satisfying with a mean error of 0.3 cm and a standard deviation of 4.7 cm obtained with the Nikon D800 Reflex camera and, respectively, a mean error of 0.2 cm and a standard deviation of 3.8 cm obtained with the Huawei Y5 Smartphone camera. This method will be particularly interesting when simplicity, portability, and autonomy are desirable. In the future, it would be transposable to participatory science programs, while using an open RTK GNSS network.

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Subsidence determination in the Central Valley, California

Reports on Geodesy and Geoinformatics ◽

10.2478/rgg-2018-0012 ◽

2018 ◽

Vol 106 (1) ◽

pp. 35-42 ◽

Cited By ~ 1

Author(s):

Marcelo Romero ◽

Mike Mustafa Berber

Keyword(s):

Central Valley ◽

Satellite System ◽

Geodetic Survey ◽

Reference Station ◽

National Geodetic Survey ◽

The North ◽

Elevation Changes ◽

System Data ◽

Global Navigation Satellite ◽

Gnss Data

Abstract Twenty four hour GNSS (Global Navigation Satellite System) data acquired monthly for 5 years from 8 CORS (Continuously Operating Reference Station) stations in Central Valley, California are processed and vertical velocities of the points are determined. To process GNSS data, online GNSS data processing service APPS (Automatic Precise Positioning Service) is used. GNSS data downloaded from NGS (National Geodetic Survey) CORS are analyzed and subsidence at these points is portrayed with graphics. It is revealed that elevation changes range from 5 mm uplift in the north to 163 mm subsidence in the southern part of the valley.

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Towards Automatic UAS-Based Snow-Field Monitoring for Microclimate Research

Sensors ◽

10.3390/s19081945 ◽

2019 ◽

Vol 19 (8) ◽

pp. 1945 ◽

Cited By ~ 2

Author(s):

Petr Gabrlik ◽

Premysl Janata ◽

Ludek Zalud ◽

Josef Harcarik

Keyword(s):

Rapid Development ◽

Field Work ◽

Satellite System ◽

Mountain Range ◽

Ground Control Points ◽

Snow Covered Area ◽

Covered Area ◽

Gnss Receivers ◽

Global Navigation Satellite ◽

Optimum Solution

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.

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Quantifying the influence of low vegetation on vertical uncertainties of 3D point clouds derived from UAV-based ground surface measurements

10.5194/egusphere-egu2020-20468 ◽

2020 ◽

Author(s):

Sebastian Fischer ◽

Anne Hormes ◽

Marc S. Adams ◽

Thomas Zieher ◽

Magnus Bremer ◽

...

Keyword(s):

Ground Surface ◽

Surface Displacement ◽

Point Clouds ◽

Satellite System ◽

Vegetation Height ◽

3D Point Clouds ◽

Dense Image ◽

Multi Temporal ◽

Surface Measurements ◽

Global Navigation Satellite

<p>The use of unmanned aerial vehicles (UAV) for ground surface measurements in natural hazard studies has strongly increased in recent years. Multi-temporal 3D point clouds derived from light detection and ranging (LiDAR) sensors and photogrammetric techniques including structure-from-motion (SfM) and dense image matching (DIM) have become important tools for monitoring the activity of geomorphic processes. However, due to georeferencing errors and measurement inaccuracies, change detection with centimeter precision remains challenging, especially in study areas covered by vegetation. This study aims at quantifying the influence of low vegetation on the vertical uncertainties of 3D point clouds in a study area mostly covered by meadows and pastures with different grass heights. 3D point clouds derived from UAV-SfM and UAV-LiDAR are compared to terrestrial ground surface measurements of a differential global navigation satellite system (dGNSS) receiver in order to quantify the vertical uncertainties and to detect advantages/disadvantages of the different sensors. The results indicate that neither method is able to detect the ground surface under dense low vegetation with centimeter precision, and that surface displacement rates derived from multi temporal analyses can be highly influenced by changes in vegetation height between surveys.</p>

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Photogrammetric 3D Model via Smartphone GNSS Sensor: Workflow, Error Estimate, and Best Practices

Remote Sensing ◽

10.3390/rs12213616 ◽

2020 ◽

Vol 12 (21) ◽

pp. 3616

Author(s):

Stefano Tavani ◽

Antonio Pignalosa ◽

Amerigo Corradetti ◽

Marco Mercuri ◽

Luca Smeraglia ◽

...

Keyword(s):

3D Model ◽

Model Building ◽

Satellite System ◽

Test Case ◽

Digital Terrain ◽

Ground Control Points ◽

Terrain Models ◽

Aerial Vehicle ◽

Global Navigation Satellite ◽

The Impact

Geotagged smartphone photos can be employed to build digital terrain models using structure from motion-multiview stereo (SfM-MVS) photogrammetry. Accelerometer, magnetometer, and gyroscope sensors integrated within consumer-grade smartphones can be used to record the orientation of images, which can be combined with location information provided by inbuilt global navigation satellite system (GNSS) sensors to geo-register the SfM-MVS model. The accuracy of these sensors is, however, highly variable. In this work, we use a 200 m-wide natural rocky cliff as a test case to evaluate the impact of consumer-grade smartphone GNSS sensor accuracy on the registration of SfM-MVS models. We built a high-resolution 3D model of the cliff, using an unmanned aerial vehicle (UAV) for image acquisition and ground control points (GCPs) located using a differential GNSS survey for georeferencing. This 3D model provides the benchmark against which terrestrial SfM-MVS photogrammetry models, built using smartphone images and registered using built-in accelerometer/gyroscope and GNSS sensors, are compared. Results show that satisfactory post-processing registrations of the smartphone models can be attained, requiring: (1) wide acquisition areas (scaling with GNSS error) and (2) the progressive removal of misaligned images, via an iterative process of model building and error estimation.

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Combining Sentinel-1 Interferometry and Ground-Based Geomatics Techniques for Monitoring Buildings Affected by Mass Movements

Remote Sensing ◽

10.3390/rs13030452 ◽

2021 ◽

Vol 13 (3) ◽

pp. 452

Author(s):

Xue Chen ◽

Vladimiro Achilli ◽

Massimo Fabris ◽

Andrea Menin ◽

Michele Monego ◽

...

Keyword(s):

Laser Scanning ◽

Large Scale ◽

Ground Deformation ◽

Satellite System ◽

Mass Movements ◽

The North ◽

Geological Processes ◽

Multi Temporal ◽

Image Pixels ◽

Global Navigation Satellite

Mass movements represent a serious threat to the stability of human structures and infrastructures, and cause loss of lives and severe damages to human properties every year worldwide. Built structures located on potentially unstable slopes are susceptible to deformations due to the displacement of the ground that at worst can lead to total destruction. Synthetic aperture radar (SAR) data acquired by Sentinel-1 satellites and processed by multi-temporal interferometric SAR (MT-InSAR) techniques can measure centimeter to millimeter-level displacement with weekly to monthly updates, characterizing long-term large-scale behavior of the buildings and slopes. However, the spatial resolution and short wavelength weaken the performance of Sentinel-1 in recognizing features (i.e., single buildings) inside image pixels and maintaining the coherence in mountainous vegetated areas. We have proposed and applied a methodology that combines Sentinel-1 interferometry with ground-based geomatics techniques, i.e., global navigation satellite system (GNSS), terrestrial laser scanning (TLS) and terrestrial structure from motion photogrammetry (SfM), for fully assessing building deformations on a slope located in the north-eastern Italian pre-Alps. GNSS allows verifying the ground deformation estimated by MT-InSAR and provides a reference system for the TLS and SfM measurements, while TLS and SfM allow the behavior of buildings located in the investigated slope to be monitored in great detail. The obtained results show that damaged buildings are located in the most unstable sectors of the slope, but there is no direct relationship between the rate of ground deformation of these sectors and the temporal evolution of damages to a single building, indicating that mass movements cause the displacement of blocks of buildings and each of them reacts differently according to its structural properties. This work shows the capability of MT-InSAR, GNSS, TLS and SfM in monitoring both buildings and geological processes that affect their stability, which plays a key role in geohazard analysis and assessment.

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