Open AccessArticle

Multi-Instrumental Approach to Slope Failure Monitoring in a Landslide Susceptible Newly Built-Up Area: Topo-Geodetic Survey, UAV 3D Modelling and Ground-Penetrating Radar

Paul Sestras

Ștefan Bilașco

^2,3,*

Sanda Roșca

Ioel Veres

¹,

Nicoleta Ilies

Artan Hysa

⁴

Velibor Spalević

⁵

and

Sorin M. Cîmpeanu

⁶

Faculty of Civil Engineering, Technical University of Cluj-Napoca, 400020 Cluj-Napoca, Romania

Faculty of Geography, Babes-Bolyai University, 400006 Cluj-Napoca, Romania

Cluj-Napoca Subsidiary Geography Section, Romanian Academy, 400015 Cluj-Napoca, Romania

⁴

Faculty of Architecture and Engineering, Epoka University, 1000 Tirana, Albania

⁵

Geography Department, Faculty of Philosophy, University of Montenegro, 81400 Niksic, Montenegro

⁶

Faculty of Land Reclamation and Environmental Engineering, University of Agronomic Sciences and Veterinary Medicine Bucharest, 011464 Bucharest, Romania

Author to whom correspondence should be addressed.

Remote Sens. 2022, 14(22), 5822; https://doi.org/10.3390/rs14225822

Submission received: 30 September 2022 / Revised: 7 November 2022 / Accepted: 14 November 2022 / Published: 17 November 2022

(This article belongs to the Special Issue UAVs for Civil Engineering Applications)

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Figure 1
Landslide susceptibility map [<a href="#B4-remotesensing-14-05822" class="html-bibr">4</a>] with relevant hotspots. "> Figure 2
The geographic location of the study area. "> Figure 3
Aerial photos of the emerged residential complex and monitored study area. "> Figure 4
Collage of images depicting the old retaining wall right before failure, and the damages that ensued on the industrial production hall after the slope failure. "> Figure 5
Collage of images depicting the newly constructed retaining wall and land improvement measures. "> Figure 6
Methodological flowchart. "> Figure 7
Map of the prior research study’s landslide susceptibility [<a href="#B4-remotesensing-14-05822" class="html-bibr">4</a>] (a) and of the study area (b); the twelve factors that have been examined as potential influencing factors for slope mass movement: altitude (c), slope (d), aspect (e), distance to settlements (f), roads (g), hydrography (h), wetness index (i), stream power index (j), land-use (k), geology (l), depth of fragmentation (m), and fragmentation density (n). "> Figure 8
Established local geodetic network. "> Figure 9
Obtained orthophoto with GCPs and CPs positioning and the instrumentation used. "> Figure 10
Obtained orthophoto with GPR profile locations and the instrumentation used. "> Figure 11
Displacement analysis on each axis, as well as overall spatial values. "> Figure 12
Surface movement rate from 2017 to 2019. "> Figure 13
GPR longitudinal profile from 2017 and 2019. "> Figure 14
The retaining wall subjected to slight rotation due to overall slope instability, with the displacements and values highlighted; GPR longitudinal profiles show changes in the depth layers of soil and rock. Note: the rotation is slightly exaggerated inside the left figure in order to have a better visualization of the process. The values recorded are relatively small and do not possess danger in the near future. ">

Versions Notes

Abstract

Slope failures and landslides cause economic damage and deaths worldwide. These losses can be minimized by integrating different methodologies, instruments, and data monitoring to predict future landslides. In the constantly growing metropolitan area of Cluj-Napoca, Romania, changes in land cover, land use, and build-up areas are an issue. The unprecedented urban sprawl pushed the city limits from the Somes River to hilly terrain prone to landslides and erosion. This study focuses on a landslide-prone area where a previous slope failure caused significant economic losses. It combines topo-geodetic measurements, UAV monitoring of surface displacement, GIS spatial analysis, ground-penetrating radar investigations, and geotechnical assessment. Two years of data show that the slope is undergoing surface erosion, with soil displacements of a few centimeters. Geodetic monitoring of the retaining wall’s control points indicates a small rotation. Coupled with georadar profile imaging showing changes in soil and rock layers with an uplift trend, it was deduced that the area suffers from a global instability. The findings provide valuable information about the dynamics of landslides and erosion for forecasting future movements and developing preventative strategies based on a new methodology that combines affordable and prevalent instrumentation and techniques.

Keywords:

geodesy; topography; GNSS; total station; surface erosion; deep landslide; displacements GIS spatial analysis; geomatics; geotechnics

1. Introduction

In the expanding and populous Transylvanian city of Cluj-Napoca, Romania, the transformations inflicted by the changes of land use and increasement in construction zones represents a current evolving issue, and the need for qualitative, safe, time, and cost-efficient methods of monitoring and evaluation is imperative [1,2]. With a general move towards urbanization and the expansion of city limits, land became a precious and difficult asset to acquire, and the construction industry is thriving, but with both favorable and unfavorable consequences. The unprecedented urban sprawl phenomenon generated the development of newly built-up areas on the hills surrounding the region and the conversion of neighboring villages from Cluj-Napoca into unprepared suburbs [2,3]. Due to the natural configuration represented by hilly terrain and the specific geomorphology of the region, natural hazards such as landslides and erosion processes are susceptible for occurrence or reactivation [4,5]. Although most of this area is in a relative dynamic stability, pressure on the slopes overloaded with buildings and infrastructure, combined with anthropogenic intervention in the territory, can induce changes in slopes’ stability, trigger landslides, and have drastic repercussions to the population and environment [6,7]. Due to the problematic nature of the region, research in this field is justified and of vital importance (Figure 1).

Previous research of the scientific team focused on developing a GIS-based spatial analysis and risk map [4], by means of identifying regions and hotspots vulnerable to landslides. This research, together with the bibliographic background of other studies related to the occurrence of landslides in the study area [8,9,10], became the inception of a larger desideratum of monitoring certain hotspots of significant value to the community and society, where occurring hazards can result in financial hardship and even mortality [5]. Thus, several chosen hotspots have been monitored or are currently under investigation by means of geodetic and topographic measurements with instrumentations such as GNSS systems and total stations, accompanied by flight surveys with UAVs and geomatics techniques, as opposed to the conventional survey method (control/monitored points), in order to examine the entire investigated region. Combining the two techniques, the outcomes attained are complex and provide a deeper comprehension of the intricate movements and displacements present in the monitored landslides, as well as the inclusion of additional instrumentation and methods in certain locations with optimal conditions. Nevertheless, the established methodology, as well as the previous one, has certain constraints and limitations. Thus, innovative alternatives are imperative for such complex measurements, with the desideratum of obtaining efficient and comprehensive solutions of measurement, monitoring, and evaluation. These can help in providing information regarding the triggering factors, susceptibility of occurrence, as well as solutions to stabilize the sites.

Landslides are natural disasters that occur worldwide, responsible for 9% of all calamities [11], and are defined as the movement of soil, debris, and rocks under the influence of gravity, with the largest occurrence in hilly and mountainous areas [12]. Accurate measurements of vertical and horizontal displacements are essential for forecasting future movements and help to better understand the landslide mechanisms that cause landslide dynamics and prevention measures [13]. There are numerous research studies and methodologies regarding the technologies and instruments used to detect landslides [14,15], from traditional geodetic–topographic apparatus (total stations, GNSS systems, terrestrial laser scanners) [16,17], to modern solutions: UAV (unmanned aerial vehicles) photogrammetry [18,19,20,21,22] or LiDAR (light detection and ranging) [23,24,25,26,27], InSAR, sensors, and geomatics applications [28,29,30,31,32,33]. Terrestrial solutions such as the mentioned geodetic–topographic instrumentation provide exact observations on potential displacements and surface movements and have pin-point accuracy [34,35]. The disadvantage of the obtainable millimetric precision of surveyed markers is a time-consuming, intense manual labore with sparse spatial coverage, which gives precise certain displacements in the detriment of limited representation of the Earth’s surface [5]. Despite being labor-intensive and having limited spatial coverage, terrestrial instrumentations such as total stations and GNSS systems allow for exact observations of the displacements of structures and surface movements and have pin-point accuracy [36,37]. When integrated with placed control points, markers, or landmarks, the recorded observations can offer insightful information on the intricate mechanisms generated in a specific area, including the various values and movements on the XYZ axis with a millimetric precision. In spite of the increasing use of new technologies, total stations remain an essential tool for many monitoring projects, such as those investigating over terrain and buildings [36]. When measuring the displacements of chosen monitoring sites or control points to assess surfaces, accurate distance and angle measurements are essential for identifying geomorphological evolutions.

An important emerging technology include the UAVs, commonly called drones, which deliver price savings, efficiency in terms of speed and accuracy, invaluable assistance, and safe operations on regions that are difficult to reach or navigate. UAVs are rising among many industries and becoming very popular, but for land survey and engineering in general, they represent a quantum leap [38,39]. In the past decade, there are numerous studies regarding landslide monitoring using UAVs to amass high-resolution imagery for sophisticated photogrammetry and geomatics methods [40]. Numerous studies have shown how effective and reliable structure from motion (SfM) software is, which is a computation-based image-processing method that permits the reconstruction of a photographed area [19,20,21]. Incorporated with the placement of ground control points (GCPs) of known or measured coordinates, the achieved georeferenced deliverables enable surface feature monitoring and displacement analysis [41]. The photogrammetric reconstruction process provides 3D information for each image pixel at considerable quality if sufficient images overlap and texture is available, with accuracy decrease in areas with low texture or shadowed areas [42]. The disadvantages of photogrammetry are the reliance on optimal light and sufficient texture, together with the impossibility to capture or penetrate structures and vegetation [43]. Photogrammetric reconstruction acquires the points from the topmost surface, and in the case of landslide monitoring and land survey in general, vegetation is present in considerable scenarios, limiting or excluding the use of such technique. Photogrammetry is a technology that has been around for a few decades, but recently became an invaluable solution and research topic after its incorporation on UAV platforms, availability in a size and power feasible for being carried on medium-to-large drones, as well as from affordable price ranges [44]. The technique is based on the reconstruction principles of ray triangulation have proven tremendous results [43,45], and is considered by many the next step in efficient and accurate land surveys, with many advantages with respect to classical field-based techniques. The UAV with SfM processes enabled the creation of digital surface models (DSMs), digital terrain models (DTMs), or digital elevation models (DEMs) that allowed the evaluation of the evolutionary behavior of the slope instability, geomorphic interpretations, and landslide monitoring [46]. Furthermore, they have potential usage and utility in different fields, such as: land surveying, civil engineering, geomorphology, cultural heritage, ecology, environment, precision in agriculture, and forestry, etc.

Ground-penetrating radar (GPR) is a non-invasive method of scanning and imaging the subsurface with electromagnetic waves by means of radar pulses that are transmitted, reflected, and scattered by subsurface structures and anomalies [47,48]. It is an environmentally friendly approach and nondestructive method that can be used for monitoring of active faults in the landslide-prone regions for investigation of objects in shallow subsurface at high resolution [49]. The advantages of the georadar method are the accuracy in detecting or mapping the subsurface structures, detecting ground water, pipelines, archaeological elements, exploration of minerals, as well as numerous civil engineering and geomorphology applications. GPR has been successfully applied in several landslide research studies [50,51,52,53,54,55] in order to obtain detailed images of the internal structure of landslides and of underlying strata and determine the maximum depth of sliding activities, geological and lithological boundaries, crevasses, etc. The precise location of an active fault in urban and inhabited areas is very important to be known for mitigation purposes, as well as requiring quick, efficient, and relatively unexpensive systems of investigation. GPR scanning provides valuable knowledge of the landslide internal structure, water flow, and its distribution in and around the landslide body and of the bedrock depth; thus, the potential landslide can be warned of early, to avoid serious hazard or disaster, and also provide remediation prospects, which can considerably decrease the time and cost of stabilization [56]. Therefore, the application of georadar for detecting the subsurface structures and monitoring of active faults for mitigation purposes are promising, especially for unstable areas in the urban environment with high populations where other active source and invasive methods are difficult or prohibited.

This study tackles the ongoing need for a procedure that is efficient, economical, and manageable for monitoring terrains during or after failures of slopes, and it does so via interdisciplinary means and using approaches that are not invasive. The overall significance, importance, and thus novelty of the present study is given by the established methodology, which efficiently combines elements of hazard susceptibility detection (based on machine learning and bivariate statistical analysis), field monitoring with topo-geodetic measurements and instrumentation, modern survey with UAV and geomatics tools, and GPR investigations. While some of the individual parts of the research are generally used in engineering works, the overall methodology enables the correlation between the three main components of the study, respectively, the topsoil, the retaining structure and the subsoil, to be evaluated by non-invasive techniques and easily available tools. This approach provides a comprehensive, non-invasive, and workable solution that can be carried out by researchers and specialists working in the field. Additionally, it can be easily adopted in a wide variety of additional scenarios that are beneficial to both the public and private sectors.

2. Materials and Methods

2.1. Study Area

The research study’s focus area consists of the greater metropolitan area of Cluj-Napoca City within Cluj County, which is located in the center of the historical province of Transylvania, Romania (Figure 2). Geographically speaking, Cluj County occupies a 6674 km² territory in the central-western region of Romania (area representing 2.8% of the country), with features that could be classified as a plateau, hills, and mountainous relief. The entire area is a hilly region, known as “Dealurile Clujului” (Cluj Hills) that is exposed to various hazards such as flooding [57], wildfires [58], and especially landslides [4,5,8,9]. These problematic conditions of the region, research in landslide prevention, and risk reduction at the local level are more than justified and of vital importance.

The studied area has recently become of significant importance due to the strategic location and socio-economic properties. The focal study area is located in the mixed industrial–residential area, on Muncii Boulevard, in the eastern part of Cluj-Napoca (Figure 2). The local area has developed exponentially in the last decade due to the continuous expansion of the city. Although the area was primarily considered the industrial zone of the city, increasingly more residential complexes emerged by replacing unused or declining industrial sites [59]. A similar situation happened on the nearby hills, formerly occupied by horticultural farms and orchards that have been altered by the amplification of construction works and the expansion of the built-up area. Consequently, the anthropogenic intervention became the determining instability factor of the slopes in the area (Figure 3).

The specific site of our study that has been monitored and evaluated from the point of view of landslides is located in a strongly developed, newly built-up area (Figure 3). The construction in the area has mixed functions, respectively, industrial in the lower part of the slope, as well as residential construction arranged in the upper part of the slope. The area is well known for the high risk to landslide occurrences, and it is mentioned in the local construction regulations. In the past, it was an area with orchards or as an agricultural destination, but due to the urban sprawl and land use changes, it became an area of great interest for investors in the construction industry [2,4]. As a consequence, landslides developed also as a result of changes in the soil structure and geomorphological processes that increased the dynamic potential of the territory, especially due to overloading the slope with new construction and the conversion of orchards to urbanized space. In addition, due to the extension of the building perimeter and the required infrastructure, various interventions, such as uncovering vegetation, earthworks, and cuttings in the slopes, took place and affected the stability of the hill within the investigated area.

The area proposed for evaluation and subsequent monitoring experienced a remarkable landslide event in 2017, resulting in significant financial and material losses. The retaining wall suffered a failure due to inadequate design and improper construction, as well as the previously mentioned anthropic interventions in the vicinity and the slope overloading. Once the retaining wall collapsed (Figure 4), the adjacent industrial production hall was structurally affected, especially the foundation, ground slab, and the steel super structure. The damage caused was due to the retaining wall failing to withstand the earth force. Displacement landslides are widespread, and the investigated area is very susceptible to such hazards, manifesting themselves especially on the excavated slopes after the removal by natural erosion or by human intervention of the resistance forces from the base of the hill. Combined with another important factor for triggering landslides being the overloading of the slope with numerous construction and infrastructure elements, without taking appropriate protection measures, the old retaining wall was prone to failure.

In order to stabilize the terrain and avoid other landslides, ameliorative and improvement measures were applied in order to decrease the triggering factors. Thus, a complex solution was implemented that consisted of water collection wells, a drainage system, terracing, and a newly erected reinforced concrete cantilever retaining wall (Figure 5). Due to the complex nature of the implemented solutions, as well as the precedent failure and lack of appropriate protection measures, the beneficiary and investors at the affected industrial production hall have decided to evaluate and monitor the perimeter in order to ensure that the area is stabilized. As a result, the present case study consisted of the evaluation and monitoring of the landslide susceptible area by an interdisciplinary team of researchers and specialists, with different methods and instrumentations (Figure 6).

2.2. Geological/Geotechnical Background and Methodological Approach

The analyzed slope belongs to the hilly area of Cluj-Napoca, located on Sfantu Gheorghe Hill, on the western part of the city, with a southern exposure. Maximum altitude in the area is about 500 m asl. From a geological point of view, the site is characterized by sedimentary deposits, belonging to the Transylvanian basin and quaternary terrace deposits. The Neogene deposits belong to the Iris formations (Miocene and Sarmatian), layers of sand and yellowish sandstone, interposed with clayey layers and volcanic tuff. The site is located in the Somesul Mic River basin, at about 2 km north of it and near a creek that springs from the terrace deposits. The site has about 6° inclination, varying due to the earth cuts and levelling of the site. The slope has visible traces of old landslides, currently in an apparent equilibrium. From geotechnical investigations in the area, the common stratigraphy consists of layers of silty clay, of a hard consistency, having high plasticity, with intercalated layers of reddish sands or limestone boulders. A special property of these clays is that they are very active (I_A > 1), being considered difficult soils according to Romanian norms. The slope inclinations and the shrinking clays layers are geotechnical factors for triggering the landslides in the area.

Figure 6. Methodological flowchart.

2.3. Bivariate Statistical Analysis (BSA)

After careful analysis and based on prior research [4,5], the current study of multi-instrumental evaluation and monitoring of a human-induced landslide was chosen. By determining the investigated area’s landslide susceptibility using a bivariate statistical analysis method, it was possible to compare the landslide inventory map with maps of landslide influence parameters and rank the corresponding classes in accordance with their contribution to landslide formation [7]. The initial model of the area under study included Cluj Hills and the present slope, with Figure 7 highlighting the current case study. The model ensured that landslide susceptibility maps were created based on the twelve criteria that were further evaluated and shown in Figure 7 [60,61,62]. As a result, detailed maps were made for each component that affects landslide susceptibility on five levels of vulnerability: low, medium, medium-high, high, very high. It is advised to carry out land development and stabilizing works for all identified hotspots, as well as for the remainder of the region covered in the high and very high susceptibility class (with a large impact on the human component), to lessen the dangers to which they are exposed [63,64]. Concrete steps and activities are needed in this area, along with some restrictions put in place by the local government.

The outcomes of using the spatial analysis equation based on ArcGIS geoinformation software and building a raster database with the spatial representation of cumulative susceptibility and natural breaks (Jenks) classification approach for the entire examined territory were very conclusive [65,66]. The modeling’s final output indicated several “hotspots” (important regions on the map) of crucial value, including for the city of Cluj-Napoca. The current case study in an illustration of this, being located in the newly built-up area of Muncii Boulevard. The Cluj Hills have this overlaid surface with the emerging community, and it is categorized as having a high or very high susceptibility due to the increased risk it poses to the local residential properties, communication networks, and infrastructure.

2.4. Geodetic Network, Monitoring Control Points and Periodic Survey

In order to monitor landslides or other precision projects and depending on the configuration and size of area studied, different combinations of existing or determined geodetic points, measurement methods, and instrumentations is required. The design of a geodetic network and the positioning of control stations for repeated observations are necessary for the geodetic–topographic technologies used to detect land movements. In the case of small areas, as in the present situation, a local geodetic network was established, from which the coordinates of the monitored points on the retaining wall were evaluated to establish the parameters of the displacement process on slopes by repeated measurements (Figure 8).

The geodetic network used in the monitoring process of the retaining wall must be checked from one measurement stage to another in order to evaluate if it remained stable over time. All measurements on slope and retaining wall must be reported in the same reference system materialized in the field through the geodetic network station points, which must remain unchanged in position. Checking their stability is a very important step and can be accomplished by several methods: Hannover [67]; Delft [68]; Munich [69]; Fredericton [70]; robust estimation [71,72]; etc.

The network was built by placing 4 geodetic marks, S1–S4, in the vicinity of the area to be monitored. Points S1 and S2 were placed in an area considered stable, which is why they were used as a reference basis for all the determinations that were subsequently made in the support network. The configuration of the monitoring network was chosen, taking into consideration the stabilized terrain in regard to the previous active fault slope, as well as to property law and the boundaries where we had permission to operate. The position of the four control points was selected outside the monitored slope in order for it to not be affected by subsequent displacements that would invalidate the monitoring process, but also at a relatively close distance in order to have direct measurements. Thus, S4 served as the principal station point from which all of the measured monitoring locations on the retaining wall could be observed, with the reference direction to point S3. Station points S1 and S2 were placed in a very stable location, respectively, on the near boulevard and served as fixed points in order to detect possible movement or damage to S4 and S3. The detailed presentation of the monitoring network, as well as the planimetric and altimetric adjustment and verifications made, are presented in Appendix A.

Although the monitoring network can be determined and used in a local coordinate system, points S1 and S2 were determined using the GNSS technology in order to frame the network in the national reference system. The ROMPOS system, developed by the ANCPI (National Cadastral and Land Registration Agency), is a national network of permanent GNSS stations that guarantees precise positioning in the Stereographic 1970 coordinate system (the national projection system of Romania). The planimetric and altimetric positioning of the geodetic points was obtained using a Leica GS08 Plus GNSS system, with measurement and recording configured for 180 determinations, with a one-second recording rate between determinations in order to obtain a centimetric horizontal accuracy. To precisely establish the coordinates of the sites in the locally developed geodetic network, the Leica GNSS system was placed on a pole on each anchorable geodetic landmark. Because landslides, subsidence, accidents caused by humans, and other factors can cause observation points to move, it was important to locate them as far away from the monitored study area as possible, where they would be as stable as possible. It was also important to ensure good visibility between station points and control points, so that they could be mutually targeted.

From an altimetric point of view, trigonometric level observations were made in the support network, which were also processed by the method of indirect measurements. The reference point S1 of elevation 324,240 m a.s.l. was used as a reference point. In relation to this, the approximate dimensions of points S2, S3, and S4 were determined.

After the creation of the support network used in the monitoring process, from the four points were made observations on the control points used to monitor the stability of the retaining structure. Several cycles of observations were made after certain periods of time. The stability of the support network was checked before each year of observation cycle. The verification consisted in redetermining the coordinates of points S3, S4 and the elevations of points S2, S3, and S4 using the same type of observations and the same procedure for processing the observations with the one used in the initial stage (stage zero).

Given the fact that the differences from one stage to another were very small, of a few millimeters, which could occur from instrumental or fixation errors (total station and reflector), it was determined that the obtained geodetic points of the monitoring network are stable and are feasible for the complex process of deformation analysis.

2.5. UAV Monitoring

Digital photogrammetry and structure from motion (SfM) software and hardware were the methods employed for the UAV slope monitoring in order to provide 3D data. Using inexpensive UAVs and structure from motion (SfM) software is an increasingly popular method for achieving good results with centimeter-level accuracy. The system’s overall low cost, easy learning curve, excellent compatibility with various mission planners and processing software, as well as the generally high accuracy of deliverables (3D models, DEMs, orthophotos) when used under ideal circumstances and parameters, all contribute to the system’s popularity [19,20,73]. Given the current case study’s challenging terrain conditions of the monitored slope and the difficulties associated with precise land surveying, this paper evaluates the traditional monitoring of established techniques and instrumentation with the use of UAV, which ensures accuracy and viability as an affordable and effective method that supplements traditional surveys for more thorough results [74,75,76,77,78,79]. The UAV flight metric are further presented in Table 1.

Planimetric and altimetric positioning of GCPs was obtained with a Stonex S8+ GNSS in real-time kinematics (RTK) mode as part of the reference procedure, which merged the UAV-acquired digital pictures with ground control points to achieve a high degree of precision (Figure 9). The coordinates of the center of the GCPs are measured by this topographic and geodetic instrument, with a horizontal precision of 0.014 m to 0.020 m and a vertical precision of 0.020 m to 0.030 m at each point. In accordance with scientific and general practice, GCPs have been spread across the terrain and monitored slope area and must cover both high and low elevations [5,39,41]. Using Agisoft Metashape software, the coordinates of the GCPs were referenced in the orthophoto images to assess the precision and correctness of the final position in the geometric model that was built. From the nine total GCPs used for the relatively small study area, six of them with the best distribution were used as GCPs in the georeferencing process, and the remaining three were used as check points (CPs). The results highlight that the calculated RMSE values were 0.019 m in the horizontal direction and 0.022 m in the vertical direction, with obtained ground resolution of ~1.02 cm/px, which are enough for the majority of engineering tasks and provide very good overall georeferencing results. All appropriate images were processed using Agisoft Metashape in accordance with a predetermined workflow that includes image alignment, manual georeferencing, optimization techniques, generation of sparse and dense point clouds, orthomosaics, and DEMs in order to produce the deliverables further required for the spatial analysis.

The slope displacements were estimated using spatial analysis procedures based on the geomorphic change detection (GCD) extension and ArcMap 10.8 software. These tools for analyzing topographic change detection on surfaces were used successfully in similar studies on areas with different spatial extensions [5,73]. The main method of analysis by means of the mentioned extension and software is to identify the difference between two digital elevation models acquired from different time sequences. The main result of the comparative analysis of the two digital elevation models is a raster database that highlights positive and negative displacements, taking into account the threshold set in the analysis [80], offering the possibility of quantitative analysis (volumetric or surface) of the results.

The presented UAV monitoring case study was first implemented in 2017, concomitant with the topo–geodetic survey on the retaining wall, and was repeated in the 2019 last stage of monitoring in accordance with the technical project specifications. The parameters utilized in the 2017 flight survey were replicated in the 2019 mission, including: identical mission planner and flight metrics, similar instrumentation and data processing, and replacement of GCPs, etc., in order to generate accurate and comparable 3D models and DEMs between the two flight missions. The objective was to apply GIS spatial analysis and the two DEMs acquired over a two-year period to determine the values for slope displacements brought on by erosion and landslides.

2.6. Ground Penetrating Radar Evaluation

Ground-penetrating radar (GPR) scanning is widely used in various fields of activity for non-invasive investigations to be carried out on terrains that require information on the existence or non-existence of underground formations that could be affected or damaged [50,51,52,53,54,55,81]. The valuable results obtained in areas with different structures and degrees of soil or rock hardness required the technique of investigating the terrain with the help of ground-penetrating radar to be properly implemented for the study and analysis of landslides. Due to the fact that soil and rock types have different particle size and hardness, they have a different spectral response in terms of electric wave reflections generated by the GPR [55,56,57,82]. Based on the analysis of the images obtained as a result of the GPR scan, that is a non-invasive procedure compared to the results obtained from geotechnical drilling and sampling; the image of the geological composition is made in vertical profiles as a result of identifying the electrical constant specific to the area. The GPR instrumentation used was the MALA X3M Ramac 50 Mhz system (Figure 10).

The vertical profile analysis of the landslide structure was performed on the basis of a longitudinal transect on the anthropically stabilized slope, on a length of approximately 40 m, having as a starting point the upper part of the slope and the end point on the retaining wall. To track the landslide dynamics by the GPR method, two scans were performed every 2 years, the first in 2017 and the second in 2019, both being performed in terms of spatial location on the same transect. The analysis of the results obtained as a result of the two scans highlights the behavior of the terrain, both in terms of stability and in terms of internal mobility of different soil and rock structures. The direction of the transect was established from north to south, a direction that coincides with the general direction of the analyzed landslide, thus being able to identify the surface of rupture, shape, and depth in longitudinal profile.

The induced risk affects two main and different components in terms of their functionality. First, it affects the industrial production hall, which is a steel structure, being flexible, and with immediate response to the force exerted by the movement of the slope, currently protected by the retaining wall. Second, the residential infrastructures in the immediate upper part of the hill (buildings intended for housing) are affected due to the displacement of the material and the accentuated erosion towards the foundations of the buildings, thus making it possible to destabilize them. Also affected is the transportation infrastructure (adjacent street to the east), which provides access to the residential neighborhood that is under ongoing development processes. This street has some unevenness in the immediate vicinity of the study area.

3. Results

The acquired results provide useful information on the dynamics of landslides and erosion for projecting future movements and devising preventative tactics based on an established methodology that combines inexpensive and readily available sensors and methodologies. The devised methodology permits the correlation between the topsoil, the retaining structure, and the subsoil to be assessed using non-invasive procedures. In order to comprehend the dynamics of the entire landslide body, the results are capable of providing correlative analysis and cross-referencing the surface study with the subsoil investigation. Thus, accurate topo–geodetic measurements reflect the retaining structure evaluation, UAV analysis represents the topsoil evaluation with erosion and surface changes, and GPR analysis represents the subsoil evaluation provided by scanning and imaging of the soil and rock layers.

3.1. Results and Discussions following the Geodetic-Topographic Measurements

Using a Leica TS06 total station and the established geodetic monitoring network, measurements were taken every two years, respectively, with the basic measurement (first measurement) in February 2017, second measurement in September 2017, third measurement in February 2018, fourth measurement in September 2018, and the final measurement (fifth) in February 2019. In the present case study, the observations and evaluations of monitoring points on the newly constructed retaining wall were made using survey control points accessories, respectively, twelve concrete survey markers that were placed firmly inside the structure and along its length. These served as the monitoring metrics for assessing the slopes’ sliding progress, and the effects by means of displacements registered on the retaining wall. The instrumentation used (Leica TS06 total station) ensured a very good measurement accuracy of angles of 2” and distances of ±2 mm + 2 ppm, satisfying the technical requirements and accuracies for such a complex engineering project. Control points were placed on the observed structure, and then their positions were measured planimetrically and altimetrically using the aforementioned equipment. XYZ coordinates of the monitoring stations, intended to record any displacements and deformations of the structure due to landslides or slope failure, were determined using topographic survey methods. The model is important because, based on displacements and deformations, the evolution of the sliding process can be determined, and the information is utilized to develop the sliding forecast.

The findings of a multiannual monitoring research study that was carried out in close proximity to a recently created residential neighborhood in Est of Cluj-Napoca have revealed a high degree of scientific congruence. Both the topographic–geodetic measurements and the 3D UAV modeling provided support for the hypothesis that the examined slope had experienced surface movement as a result of deep-seated landslides and surface erosion. On hills and slopes, landslides are a common occurrence that can be attributed to the simultaneous or prolonged action of a number of different factors. The presence of surplus water in the soil and surface, the slope of the ground, and gravity are often favorable elements in the onset of landslides. As a result, many landslides are slow and may be predicted. Monitoring and assessing landslides can be improved with the help of consistent field observations. These observations are helpful in assessing how the displacement forecast has evolved and been refined as a result of the changes.

In order to make it easier to grasp the geomorphological phenomena that took place on the investigated area, the data from the observations of five intervals and stages, respectively, between February 2017 and February 2019, were processed in the current case study. The results obtained are presented for each directional axis (X, Y, and Z), as well as a spatial displacement that combines the values of ΔX, ΔY, ΔZ and are expressed in millimeters (Figure 11).

The most significant displacements were on the X axis and had a positive value, suggesting a movement opposite of the directional landslide, towards the top of the slope. While the values are not high and do not possess significant dangers in the near future, they highlight a progressive movement throughout the two years that is likely to continue until the area reaches a global stability. Similar movements were recorded on the Z axis, but with a negative value, suggesting a small settlement or rotation of the retaining wall. The values on the Y axis were arbitrary and with negligible value, suggesting a stability of the retaining wall on the left–right (west–east) direction. The spatial displacement chart highlights the overall values recorded on each control point over the two-year survey period. The most noticeable values that reach almost 3 cm are recorded on points P1, P11, and P12, which are located on the extremities of the retaining wall.

Although the values are on the lower end of the spectrum, this does not mean that they are insignificant. The observations are necessary for predicting future movements and can provide knowledge that is both enlightening and useful regarding the mechanisms that underlie the dynamics of landslides. They also emphasize the valuable gains and stability that the recently completed retaining wall provides for the slope that was evaluated and was suspectable to failures. The obtained results, by means of precise topo-geodetic measurements, represent the retaining structure evaluation from the three main evaluated components, which are correlated in the overall methodology. The directional movements of positive values on X axis, negative values on Z axis, and relative stability on Y axis assist the evaluation and supposition further presented in the Discussion section.

3.2. Results and Discussions following the 3D UAV Modeling

The spatial analysis based on the GIS and GCD processing enabled the evaluation of changes and displacements of the slope by means of DEM of difference (DoD) between the altitudinal databases obtained in 2017 and 2019. Due to several changes in the vicinity of the study area, the DoD was performed only on the slope north of the retaining wall, which was the initial hotspot and failure of the main body surface. The DEMs that were generated by the UAVs do not have the millimetric precision that was produced by the geodetic–topographic measurements and instruments, but they do make it possible to monitor a significantly broader region than was possible with individual markers or control points. In addition to this, it is a very good companion for the sophisticated monitoring of the terrain and the retaining wall, as it made it possible to calculate the exchange rate of the terrain as well as the surfaces that had positive and negative deformations (Figure 12).

This type of analysis is conclusive due to the fact that the influence of the zone of depletion and zone of deposition on the vertical movement is evaluated. The GCD analysis of the deformations clearly highlights its instability, both as a positive and negative displacement of the slope, with a direct effect towards the retaining wall. Two value ranges stand out very well, highlighting large dust particles characterized by negative displacement (−0.05 to −0.02 m) in a percentage of approx. 52% of the surface, caused mainly by surface erosion manifested by the washing of sandy material on the top of the slope.

Also highlighted is the unchanged or low positive displacement interval (−0.02 to 0.02 m), caused by the deposition of the eroded and washed material on the terracing earthworks that account for approx. 44%, which compensates the area percentage characterized by the negative displacement. The other intervals with negative and positive values higher than 0.02 m and, respectively, lower than −0.05 m were identified on very small surfaces being caused especially by the anthropic activity, deposits of construction material residues, and excavations or landscaping with the purpose of site maintenance.

Because they are the combined consequence of a shallow landslide and the surface erosion on an area that is not stabilized due to the lack of vegetation on the monitored slope, the identified modifications and displacements are not considerable. This is because they are the combined outcome of these two processes. The results of the GPR scanning have been validated by the correlative analysis, which also brings to light, once more, the relative dynamic stability of the slope, which is influenced both by the vertical variation and by the pushing force that is exerted on the retaining wall. The obtained results, by means of UAV and GCD analysis, represent the topsoil evaluation from the main three evaluated components, which are correlated in the overall methodology.

3.3. Results and Discussions following the GPR Investigation

The analysis of the results obtained from the GPR scanning in the different years highlights the influence of the anthropic stabilization works of the slope failure, both in terms of terracing earthworks and the influence that the built retaining wall provided. The terracing earthworks are areas with accentuated subsidence corresponding to the terraced surfaces and areas with less accentuated subsidence correlated with the slopes between terraces. The retaining wall provided a very strong compaction of the soil and rock materials identified in the immediate vicinity of the retaining wall, both due to the different forces acting on it and the compaction that ensued after the established stabilization works.

Longitudinal profile analysis highlights the surface of rupture for both years taken into account, with an extension in depth between 3 and approximately 25 m (Figure 13). GPR profile no. 3 was the primary longitudinal profile that was studied and interpreted out of the first five profiles that were gathered in the field, and it was the GPR profile that was used for interpreting and evaluating the subsoil (Figure 10). This one provided the clearest imaging (with the least amount of noise) and visualization of the process and changes in the rock and soil layers, showing an upward tendency in the layers. Comparing the results between 2017 and 2019 from the surface of rupture point of view, a decrease in the slope in the maximum depth section stands out, the slope becoming almost non-existent. This is likely due to the stabilization of the slope after the construction of the new retaining wall that stops the horizontal movement of the driven ground.

The sliding bed can be divided into three main areas in terms of its angle of fall: the first part identified at the top of the slide up to approximately 14 m is characterized by a moderate slope and a vertical fall of approximately 13 m. It highlights the relative stability of the slide in the upper part, and between the two years no significant change was identified.

The middle part runs longitudinally over a distance of 14 m between the lower limit of the first part and approximately 32 m to the S and S-W. This sector characterizes the sliding as unstable and dynamic, at the same time being characterized by a higher slope and a vertical drop of 7 m for 2017, thus gaining a much higher energy by forcing the material from the top and the bottom in the sliding mechanism. The middle part is subjected with major changes in terms of the transverse profile structure of the stabilized slip in terms of its dynamics. Thus, a portion with major changes in terms of the direction of the layers can be noticed, identifying an attenuation of the slope of the sliding bed in 2019 on the sector between 17 and approximately 32 m, as well as an incipient elevation of the upper layers with the maximum vaulting at 4 m, an uprise that does not influence the superior layers of the transverse profile. The rise is likely caused by the pressure exerted by the material from the upper part of the sliding on the base of the retaining wall, thus causing changes in the sliding body and influencing the direction of the layers in the third part of the transverse profile.

The third part is characterized by a relative dynamic stability of the sliding bed, distinguished by a small slope and a small vertical drop of approximately 4 m for both 2017 and 2019. Dynamics of the vaulting identified in 2019 in the second part of the slide visibly influences the final part, which is in direct contact with the retaining wall. Thus, in 2019, there is a change in the direction of the layers from the relatively horizontal direction to a vertical ascent direction starting from 32 m, a direction that generates an active thrust on the upper part of the retaining wall.

The comparative analysis of the two GPR scans highlights the accentuated dynamics of the sliding body and the influence of the retaining wall on it. The force of pushing the sliding mass on the retaining wall imprints three essential modifications that highlight the dynamic stability of the analyzed slope. First of all, the slope dynamic of the sliding bed in the lower half of the slip is highlighted, which makes the sliding body stabilize over time in terms of horizontal movement. The second effect is also identified in the middle and lower part of the slide, the most active parts from a dynamic point of view, where the direction of the layers changes from approximately horizontal in the initial 2017 scan to a vertical rise, by vaulting in the middle part, thus affecting the topography and the configuration of the terrain over time. Last, but not least, the vertical movement and general depth rotation of the soil and rock layers at contact with the retaining wall generated a deep-seated movement, determining its horizontal and vertical displacements.

Our research indicates that monitoring of the retaining wall must be carried out, not only as a horizontal displacement of its base, but also as a vertical displacement. This is due to the fact that the greatest dynamics, both horizontally and vertically, of the sliding bed is identified under the foundation of the retaining wall and the foundation of the industrial production hall. This is due to the fact that the entire area is built on a sliding body of great depth (over 30 m), which is located in a relatively dynamic stability. The obtained results, by means of GPR analysis, represent the subsoil evaluation from the main three evaluated components, which are correlated in the overall methodology and monitoring.

4. Discussion

A multi-instrumental strategy was applied in the evaluation and monitoring of the study region, which has only recently had a slope failure. This approach revealed a surprising progression of the displacements. Based on the topo–geodetic precision measurements of the monitoring points located on the newly built retaining wall, the measured displacements highlighted a general trend of movement on the X axis, with positive values toward the hill (north direction), with a maximum value of +23 mm recorded on the monitoring point P12 (located on the west extremity of the retaining wall), and an average value of +20 mm based on the twelve monitoring points. The measured displacements on the Z axis indicated a negative vertical movement, thus a settlement of the retaining wall with a maximum value of −15 mm recorded again on the monitoring point P12, and an average value of −14 mm based on the twelve monitoring points. The displacements recorded on the Y axis were relatively small, with an average of just +3 mm. These Y axis results indicate the stability of the retaining wall in regard to side movements (west to east).

4.1. Geotechnical Assessment of the Displacements

On the basis of the knowledge that geotechnical experts have regarding the main types of retaining wall failures and the behaviors that they exhibit over time, it is possible to take into consideration a number of different scenarios because the activity of the retaining wall could have a number of different causes. Taking into account the displacements and directions recorded on the X and Z axis, a plausible cause for the displacements is the post tensioned anchors induced stresses. This induced stress might initiate a retaining wall and soil displacement, which will be consumed if the terrain starts sliding. It is also possible to have a small rotation of the retaining wall due to anchorage system induced force. By using the GPR scanning as part of the evaluation and monitoring approach, a second prediction is brought to light and is shown to be more plausible. Considering the GPR investigation, indicating an uplift trend of the soil layers, and the displacements observed, the cause of the retaining wall displacements might be a deep landslide. The displacements observed from the topo–geodetic monitoring survey, and the GPR longitudinal profile changes in the depth layers of soil and rock, indicate an overall slope instability. Thus, the retaining wall was subjected to a slight rotation due to overall slope instability, which explains the X (positive) and Z (negative) axis differences. The scope of the examination was therefore constrained to the aforementioned property, and it was determined that the industrial building’s superstructure and slab exhibited no signs of structural deterioration during the course of the research. In order to determine the reason for the displacement, additional geotechnical investigation and a numerical stability analysis will need to be carried out.

4.2. Correlations between the Multi-Instrumental Monitoring Approach

Regarding the study based on the GIS spatial analysis using UAV collected databases utilizing DoD geomatics software, there is a correlation between the results and the measurements performed directly on the retaining wall in the field, as well as the imaging of the GPR profiles. Thus, in addition to the deep landslide confirmed by the GPR scanning and the rotation of the retaining wall due to global instability, the area in issue has experienced substantial land erosion. The amount of eroded and collected material close to the retaining wall serves as a point of instability in the analysis. The soil moves naturally and continuously during erosion, primarily due to the action of water [83,84,85]. Since the soil layer is thin and the slope is somewhat steep, shallow landslides and erosion are created on a hilly terrain, like that of the research region explored. The presence of water from heavy or prolonged rainfall appears to be the key causative element [5,86,87,88]. The material drains onto the slope under the action of the erosive agent as a result of rain, melting snow, and groundwater. Surface water erosion is described as the process of detachment and transport of soil particles by the action of water. The results of all of the multi-instrumental procedures and careful assessments of the intricate processes that contribute to the mechanisms that can induce or precipitate sliding movements on the slope make it possible to develop some preventative measures. These outcomes also enable the development of some corrective measures. In this respect, prior plans for geotechnical and land improvement measures in the region were carried out. These measures include water collecting wells, drains, and a newly built retaining wall. Although there are discernible benefits based on the relatively small displacements observed on the retaining wall, further environmental and biological interventions, such as changes in land use, the cultivation of species that have the ability to enhance the soil, and greater resistance of the land to displacement and erosion, should also be taken into consideration.

According to the findings of our research, identifying the ground’s movement using GPR scanning is a method that is both trustworthy and extremely helpful. The soil displacement variations from 2017 to 2019, demonstrating the positive impact of the retaining wall, may be compared using Figure 14 (right), and some conclusions can be inferred from this comparison. On substantial depth, there are still some displacements, which is an indication that there is some activity. This might be due to the ongoing building work that is taking place on nearby sites, a fluctuating ground water table, or swelling and contracting on the surface. As a result of these observations, one might deduce that multidisciplinary approaches should be utilized wherever possible when addressing similar issues. The instability phenomenon can be evaluated by combining extensive geotechnical investigation with a non-invasive monitoring methodology (topo–geodetic measurements, UAV DoD spatial analysis, inclinometric measurements, and GPR profiles) and stability analysis calculation. In this way, failures with significant economic losses can be avoided. Both the overall displacement on the retaining wall and the UAV GCD analysis of the deformations are relatively small in this case study, which indicates that there is a lower chance of failure in the near future. However, due to the geomorphic characteristics of the study area and the previous slope failure, the non-invasive monitoring and evaluation should be reassessed annually or every few years. If significant changes do occur, a more complex and invasive geotechnical investigation will need to be conducted.

Periodic monitoring by non-invasive and interdisciplinary means provides new information on erosion and landslide surface displacements, the structural integrity of the retaining system, and further knowledge on deep-seated landslide kinematics. This is true despite the fact that reliable measurements and interpretations of the complex process behind landslide kinematics remain a challenge. The tested monitoring technique is able to provide information and connect the surface study with the subsoil inquiry, which is necessary in order to understand the dynamics of the complete landslide body. The workflow that has been established permits a correlation of displacements across all three key components: the topsoil, in our case mostly affected by erosion, with the surface movement rates illustrated using the UAV GCD analysis; the retaining system, where based on the precise topo–geodetic measurements a slight rotation of the structure was identified; the subsoil, which normally is the hardest to evaluate without extensive procedures, was successfully scanned with GPR technology that enabled the imaging of the soil and rock layers, as well as the changes that occurred due to the global instability of the region. All the mentioned correlations of the primary components affected in the study area are based on tools, techniques, and instrumentation that are easily accessible to researchers and specialists in the field, thus enabling the current methodology to be implemented in similar conditions worldwide.

5. Conclusions

Due to recent changes in the study area, including a new residential neighborhood and significant changes in land use and land cover, the slope and structure monitoring research has practical importance. Our study’s interdisciplinary methodology proved feasible, reliable, and effective. The geodetic network allowed a topo–geodetic measurement and analysis of the retaining wall’s displacement processes; UAV 3D modeling of the investigated slope highlighted surface erosion processes corelated with deep-seated movements best displayed by GPR scanning. Data, interpretation, and discussion provided scientific and practical knowledge relevant to the examined area and other study areas worldwide. Our findings show how stabilization solutions improved the terrain (water collection wells, drainage system, terracing, and a newly erected reinforced concrete cantilever retaining wall). Our work also indicates that the study area has deep-seated slope instability, which caused small geotechnical rotation on the retaining wall and visible soil and rock layer changes. Future investigations and instrumentation should be expanded based on the data, the significance of the study area, and the confirmed geomorphic activities. Thus, LiDAR-equipped UAVs are proposed, along with sensors on structures for additional monitoring. All of these onsite monitoring observations should be used to prove the retaining system’s efficiency and to make intervention decisions. Geodetic, geomatic, and geotechnical monitoring evaluations should be the trend in approaching any site with high landslide risks, offering information about complex movement processes, triggering factors, and stabilization solutions.

Author Contributions

All authors have contributed equally to the work. All authors have read and agreed to the published version of the manuscript.

Funding

The APC was funded by the Technical University of Cluj-Napoca.

Data Availability Statement

Not applicable.

Acknowledgments

This work was supported by a grant of the Ministry of Research, Innovation and Digitization, CNCS—UEFISCDI, project number PN-III-P1-1.1-PD-2021-0145, within PNCDI III. The authors would like to thank the academic editor and anonymous reviewers for their helpful and valuable comments and suggestions that helped improve this paper.

Conflicts of Interest

The authors declare no conflict of interest.

Appendix A

Between the network points, angular observations were made both horizontally and vertically:

Table A1. The base angular observations (2017).

Station Point	Target Point	Hz	V	Instrument Height [m]	Prism Height [m]
S1	S2	0.0000	−1.0111	1.483	0.375
	S4	98.3021	4.7390
	S3	104.9508	4.6329
S2	S3	0.0000	4.3460	1.564
	S4	2.4880	4.3887
	S1	74.7849	−0.5207
S3	S1	0.0000	−5.1108	1.457
	S4	14.3691	−4.9647
	S2	20.2641	−4.8234
S4	S1	0.0000	−5.4919	1.595
	S2	29.4009	−5.0995
	S3	221.0153	3.3822

The coordinates of these points are:

Table A2. Coordinates of S1 and S2.

	x	y
S1	589,413.255	396,830.215
S2	589,414.650	396,734.405

The determination of the position of points S3 and S4 was calculated rigorously using the method of indirect measurements based on the least squares method. The approximate coordinates were first determined for points S3 and S4:

Table A3. Approximate coordinates of S3 and S4.

	x	y
S3	589,694.527	396,856.253
S4	589,608.233	396,827.877

These approximate coordinates, determined by GNSS measurements, were to be corrected following the processing of the measured angular and distance values with a Leica TS06 total station.

The matrix relation that underlies the measurements processing in the network is:

A t + l = v,

(A1)

The aim is to obtain the matrix of corrections x under the conditions of a minimum of the sum of the squares for the measurement errors:

v^{T} p v = m i n i m,

(A2)

Matrix A specific to the presented monitoring network and the matrix of free terms are those presented below:

	0	0	0	0		−6
	0	0	39,380	3264.595		25
	−207.736	2244.131	0	0		−19
	−207.736	2244,131	39,380	3264.595		0
	−832.497	1912.207	0	0		−23
	0	0	−1287.564	2666.992		29
	0	0	0	0		−7
A=	−832.497	1912.207	−1287.564	2666.992	l=	0
	−207.736	2244.131	0	0		39
	−2190,026	6656.940	2190.026	−6656.940		−78
	−832.497	1912.207	0	0		38
	−3230.259	10,813.278	2190.026	−6656.940		0
	0	0	39.380	3264.595		44
	0	0	−1287.564	2666.992		49
	−2190.026	6656.940	2190.026	−6656.940		−93
	−2190.026	6656.940	941.842	−725.354		0

Corrections are obtained with the relationship:

x = - {(A^{T} p A)}^{- 1} A^{T} l,

(A3)

They have the values:

	−0.006
x=	0.004
x=	0.008
	−0.009

Thus, the corrected (adjusted) values of the coordinates will be:

Table A4. Adjusted coordinates of S3 and S4.

	x	y
S3	589,694.521	396,856.257
S4	589,608.241	396,827.868

The mean square error of the unit of weight (standard deviation) is the following:

m_{0} = \pm 6.46

The errors with which the coordinates were obtained are:

Table A5. Obtained coordinates errors.

	$m_{x}$	$m_{y}$
S3	±0.010	±0.004
S4	±0.005	±0.002

Table A6. Elevations of S2, S3 and S4.

Point	Elevation [m]
S2	323.830
S3	345.920
S4	339.870

The adjustments of the elevations were performed by solving a system of equations written in matrix form as in Equation (1). The matrices A and l used in the adjustment of the elevations are:

	6642.2	0,0	0,0		26
	0.0	0,0	3246.7		−67
	0.0	2241.9	0.0		−46
	−2075.9	2075.9	0.0		63
	−2947.4	0.0	2947.4		23
A=	−6643.5	0.0	0.0	l=	32
	0.0	−2239.3	0.0		−82
	0.0	−6966.3	6966.3		−238
	2073.6	−2073.6	0.0		−1
	0.0	0.0	−3240.5		45
	2942.5	0.0	−2942.5		−10
	0.0	6989.1	−6989.1		−1

The elevation corrections obtained with Equation (2) are:

	0.003
x=	−0.009
	0.008

The probable elevations and their errors (deviations) are:

Table A7. Transformation parameters.

Point	Elevation [m]	$m_{H}$
S2	323.833	±0.007
S3	345.911	±0.011
S4	339.878	±0.010

The observations made in stage 1 are:

Table A8. The angular observations after 1 year (2018).

Station Point	Target Point	Hz	V	Instrument Height [m]	Prism Height [m]
S1	S2	0.0000	−1.0991	1.625	0.375
	S4	98.3072	4.6939
	S3	104.9498	4.6008
S2	S3	0.0000	4.3409	1.641
	S4	2.4934	4.3762
	S1	74.7852	−0.5641
S3	S1	0.0000	−5.1303	1.533
	S4	14.3565	−5.0288
	S2	20.2645	−4.8361
S4	S1	0.0000	−5.4862	1.597
	S2	29.3988	−5.0991
	S3	220.9997	3.3761

The observations made in stage 2 are:

Table A9. The angular observations after 2 years (2019).

Station Point	Target Point	Hz	V	Instrument Height [m]	Prism Height [m]
S1	S2	0.0000	−1.0710	1.584	0.375
	S4	98.3059	4.6907
	S3	104.9509	4.6111
S2	S3	0.0000	4.3484	1.606
	S4	2.4914	4.3846
	S1	74.7842	−0.5516
S3	S1	0.0000	−5.1259	1.496
	S4	14.3607	−5.0111
	S2	20.2635	−4.8291
S4	S1	0.0000	−5.4732	1.551
	S2	29.4003	−5.0865
	S3	221.0067	3.4075

Comparative values of the coordinates and their very small deviations:

Table A10. Comparative values of the coordinates.

		Stage 0	Stage 1	Stage 2
S3	X	589,694.521 ± 0.010	589,694.520 ± 0.009	589,694.524 ± 0.006
S3	Y	396,856.257 ± 0.004	396,856.255 ± 0.003	396,856.261 ± 0.002
S4	X	589,608.241 ± 0.005	589,608.245 ± 0.004	589,608.240 ± 0.003
S4	Y	396,827.868 ± 0.002	396,827.871 ± 0.002	396,827.866 ± 0.001

Comparative values of the elevations and their very small deviations:

Table A11. Comparative values of the elevations.

	Stage 0	Stage 1	Stage 2
S2	323.833 ± 0.007	323.829 ± 0.005	323.835 ± 0.005
S3	345.911 ± 0.011	345.918 ± 0.008	345.919 ± 0.008
S4	339.878 ± 0.010	339.880 ± 0.007	339.874 ± 0.007

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Figure 1. Landslide susceptibility map [4] with relevant hotspots.

Figure 2. The geographic location of the study area.

Figure 3. Aerial photos of the emerged residential complex and monitored study area.

Figure 4. Collage of images depicting the old retaining wall right before failure, and the damages that ensued on the industrial production hall after the slope failure.

Figure 5. Collage of images depicting the newly constructed retaining wall and land improvement measures.

Figure 7. Map of the prior research study’s landslide susceptibility [4] (a) and of the study area (b); the twelve factors that have been examined as potential influencing factors for slope mass movement: altitude (c), slope (d), aspect (e), distance to settlements (f), roads (g), hydrography (h), wetness index (i), stream power index (j), land-use (k), geology (l), depth of fragmentation (m), and fragmentation density (n).

Figure 8. Established local geodetic network.

Figure 9. Obtained orthophoto with GCPs and CPs positioning and the instrumentation used.

Figure 10. Obtained orthophoto with GPR profile locations and the instrumentation used.

Figure 11. Displacement analysis on each axis, as well as overall spatial values.

Figure 12. Surface movement rate from 2017 to 2019.

Figure 13. GPR longitudinal profile from 2017 and 2019.

Figure 14. The retaining wall subjected to slight rotation due to overall slope instability, with the displacements and values highlighted; GPR longitudinal profiles show changes in the depth layers of soil and rock. Note: the rotation is slightly exaggerated inside the left figure in order to have a better visualization of the process. The values recorded are relatively small and do not possess danger in the near future.

Table 1. UAV and flight metrics.

	Flight Plan Properties
Aircraft	DJI Phantom 4 Pro
Flight Date	May 2017/May 2019
Mapping Flight Speed	4 m/s
Sensor	4K RGB camera with 20 MP; f/2.8–f/11, 24 mm lens
Fly Height Ground Level (m)	40 m
Image Forward Overlap (%)	85%
Image Side Overlap (%)	75%
Image Overlap	>9
Number of Images Captured	456 (crosshatch 3D flight pattern)
Covered Area vs Area of Interest [m²]	~22,000/~2500
Number of GCPs	9 (placed inside/surrounding the area of interest)
Ground Resolution	~1.02 cm/px
RMSE	0.019 m XY and 0.022 Z

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Sestras, P.; Bilașco, Ș.; Roșca, S.; Veres, I.; Ilies, N.; Hysa, A.; Spalević, V.; Cîmpeanu, S.M. Multi-Instrumental Approach to Slope Failure Monitoring in a Landslide Susceptible Newly Built-Up Area: Topo-Geodetic Survey, UAV 3D Modelling and Ground-Penetrating Radar. Remote Sens. 2022, 14, 5822. https://doi.org/10.3390/rs14225822

AMA Style

Sestras P, Bilașco Ș, Roșca S, Veres I, Ilies N, Hysa A, Spalević V, Cîmpeanu SM. Multi-Instrumental Approach to Slope Failure Monitoring in a Landslide Susceptible Newly Built-Up Area: Topo-Geodetic Survey, UAV 3D Modelling and Ground-Penetrating Radar. Remote Sensing. 2022; 14(22):5822. https://doi.org/10.3390/rs14225822

Chicago/Turabian Style

Sestras, Paul, Ștefan Bilașco, Sanda Roșca, Ioel Veres, Nicoleta Ilies, Artan Hysa, Velibor Spalević, and Sorin M. Cîmpeanu. 2022. "Multi-Instrumental Approach to Slope Failure Monitoring in a Landslide Susceptible Newly Built-Up Area: Topo-Geodetic Survey, UAV 3D Modelling and Ground-Penetrating Radar" Remote Sensing 14, no. 22: 5822. https://doi.org/10.3390/rs14225822

APA Style

Sestras, P., Bilașco, Ș., Roșca, S., Veres, I., Ilies, N., Hysa, A., Spalević, V., & Cîmpeanu, S. M. (2022). Multi-Instrumental Approach to Slope Failure Monitoring in a Landslide Susceptible Newly Built-Up Area: Topo-Geodetic Survey, UAV 3D Modelling and Ground-Penetrating Radar. Remote Sensing, 14(22), 5822. https://doi.org/10.3390/rs14225822

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