GNSS and RPAS integration techniques for studying landslide dynamics: Application to the areas of Victoria and Colinas Lojanas, (Loja, Ecuador)

This research tests the application of GNSS and RPAS techniques to the spatiotemporal analysis of landslide 10 dynamics. Our method began by establishing non-permanent GNSS networks on the slope surfaces to perform periodic measurements by differential GNSS. Similarly, RPAS flights were made to acquire high-resolution images, which were oriented and georeferenced using ground control points and structure-from-motion algorithms to obtain digital surface models and orthophotos ultimately. Based on GNSS measurements, the direction and velocity of displacements were accurately calculated, and orthophotos and DSMs were used to calculate horizontal and vertical displacements in a set of significant 15 points throughout the study area, reaching accuracies higher than 0.035 m in the GNSS data and 0.10 m in the RPAS data. These values were within the accuracy required for such studies. Based on the field observations and the results from the photogrammetric studies, the two studied landslides were classified as very slow flows.


Study areas
The present research encompasses two study areas ( Figure. 1). Both are located near the city of Loja, in southern Ecuador, in 65 the sectors named Victoria and Colinas Lojanas. The climate is humid subtropical with an average annual precipitation of 917 mm, although the rainfall is concentrated from December to April. Palaeozoic, impure, fine-to medium-grain quartzites, black phyllites, slates, and schists (some graphitic) (Figure 1) (Hungerbühler et al., 2002). The Victoria sector is found in the Belén Formation (Miocene) and lithologically consists of thick-to-thin layers of sandstones with conglomerate lenses and, to a lesser extent, layers of lutites deposited with colluvial material. The formation setting is 75 mixed fluvial-deltaic (Hungerbühler et al., 2002). The landslide area is dominated by sands and clays caused by the weathering of pre-existing lithologies. The soil is highly saturated because this agricultural area is subjected to continuous irrigation in addition to the effects of rainfall. The predominant vegetation cover in the study area is grasses, with some isolated bushes.
The existing types of cover on landslide areas include cliffs, roads, buildings, and bare soil. The landslide surface area is 21,860 m 2 , and a 13.6% mean slope. Numerous several-metre-long tension cracks can be found running parallel to the crown of the 80 landslide, highlighting the landslide activity. Figure 2 shows images of the landslide surface in Victoria. There are signs of deformation, such as scarps and cracks (with widths of 0.20 m, lengths greater than 2 m and depths over 0.50 m).

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The Colinas Lojanas sector is located on the Quillollaco Formation, which has four lithologies: conglomerates, clays, sands, and limonites. The conglomerates are the predominant rocks in the Quillollaco Formation that outcrop in natural and anthropic slopes. These conglomerates show sub-rounded clasts, primarily quartz, up to 15 cm in size, cemented in a sandy-silty matrix, with colours ranging from yellowish brown to light grey. The unstable zone covers an area of 65,845m 2 , with an average slope of 11%. The presence of cracks, scarps, collapsed buildings, and affected road infrastructure is the main evidence of active 90 ground movement, as shown in Fig. 3.

GNSS measurements and processing
Two non-permanent GNSS control networks (Wang, 2013) were established in the study area. The first network, established in the Victoria sector, consisted of eight points, and the second network was installed in Colinas Lojanas with 24 points. These points consisted of concrete boundary markers with a 0.50 m long reinforcing steel rod at the centre and a tapered bore 3 mm 100 in diameter at the free end to mount the GNSS receiver on a range pole. The differential GNSS technique (Fast Static) (Akbarimehr et al., 2013;Pesci et al., 2013;Rawat et al., 2011) was used to monitor the network using a Trimble R6 dualfrequency GNSS receiver (rover) ( Figure. 4a) with a 10 minute occupation time, 1 second recording time, and 10° elevation mask. This technique establishes accuracies of 5 mm with a measurement time between 8 to 20 minutes (Gili et al., 2000). To ensure the accuracy of the GNSS data recording, the verticality of the range pole on the point was assessed by checking the 105 circular level.

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The downloaded data were postprocessed using the software Trimble Business Centre V 2. The accuracy of these points was 0.03 m for horizontal positions and 0.035 m for vertical measurements (Zárate, 2011 To complement the GNSS measurement campaigns, two RPAS flights were made in the Victoria sector (18 February 2016 and 11 June 2016) and three flights in Colinas Lojanas (4 July 2016, 29 November 2016, and 12 January 2018). The flights in Victoria were made on the same day as the GNSS measurements were taken, in contrast to Colinas Lojanas, where the flights were made independently of the GNSS measurements. The flights were made with a DJI Phantom 2 drone (Fig. 4b) operating at flight heights of 50 m to 120 m. Flight time was 20 minutes using a smart battery with a capacity of 5200 mAh. The (obstacle-125 free) range was 1000 m. The elevation of the terrain was assessed to determine the highest and lowest topographic points (including the heights of structures and trees) to avoid collisions of the vehicle during the flight and to ensure a uniform resolution of the captured images that would be suitable for the study objectives. Rain and wind (Car et al., 2016) were the factors analysed before preparing the flight schedule due to their negative impact on electronic components, image quality, and UAV safety. The optimal weather conditions (Hackney and Clayton, 2015;Mozas-Calvache et al., 2012;Uysal et al., 130 2015) for landslide evaluation are cloudy skies without rain and without wind; however, flights can be made with winds of 8 km h -1 . The flights were planned using the photogrammetric software GroundStation v 4.0.11 and the web application www.mapsmadeeasy.com. These applications make it possible to define the flight path, flight height, and forward and side https://doi.org/10.5194/nhess-2021-32 Preprint. Images were acquired using a GoPro 3+ Silver Edition 10-megapixel digital camera with 2.77 mm focal distance and 2624×1968 px resolution. The camera was set to acquire images at a constant interval of 2 s.
For block orientation and subsequent DSM interpolation and orthophoto processing, the software Agisoft PhotoScan was used. 140 The workflow began with image alignment and georeferencing using dense matching and SfM techniques, involving the automatic measurement of thousands of common waypoints between photographs. Next, the DSM was generated by pointcloud densification and orthophotos, creating textured digital 3D models where appropriate (Yucel and Turan, 2016). For flight orientation and georeferencing, five ground control points (GCPs) were used in the Victoria sector and six GCPs in the Colinas Lojana sector, which are part of the GNSS control networks. The coordinate system used was WGS84-UTM 17S. The 145 coordinates of these control points were determined with Trimble R6 dual-frequency GNSS in differential mode. The accuracies obtained in the orientation process, expressed as root-mean-square error (RMSE) in both GCPs and checkpoints (three in the Victoria sector and four in Colinas Lojanas), are outlined in Table 3. Thus, the horizontal errors (XY) of both control points and checkpoints ranged from 0.025 to 0.056 m; vertical errors varied usually within the range 0.024-0.059 m, and in any case they were below 0.10 m. These accuracies, both horizontal and vertical, were within the ranges established by 150 the American Society for Photogrammetry and Remote Sensing (Agüera-Vega et al., 2017). In turn, the DSMs and orthophotos were exported as images, both with 0.05 m resolution. Figure 5 shows the orthophotos and DSMs generated for the Victoria sector, and Fig. 6 shows the orthophotos and DSM generated for the Colinas Lojanas sector, according to the flights detailed in Table 2.

Displacement measurements
In the case of GNSS networks, the displacements between each pair of campaigns are easily measured by subtracting the coordinates of the points of each campaign from those of the next campaign. Thus, the total displacements throughout the entire monitoring period were calculated by subtracting the initial coordinates (first campaign) from the final coordinates (last 170 campaign). Thus, positive values indicated eastward, northward, and upward displacements, and negative values indicated westward, southward, and downward displacements.
In RPAS images, two types of approximations were made to measure changes in the terrain surface: calculating displacements between monitoring points and calculating differential models. The former consisted of calculating displacements in a series of significant monitoring points extracted from orthophotos and DSM. The monitoring points were manually located using the 175 first orthophotos in the stable and unstable areas to put them as much as possible in bare soil without vegetation. The displacements calculated in the stable zone served to evaluate the accuracies and uncertainties of the images and calculations in the unstable zone to analyse the kinematics of the movements. This network of checkpoints was created and stored as a point layer in ArcGIS and was based on the WGS84-UTM 17S coordinate system. The latter consisted of calculating DoD, which showed areas with vertical, and even horizontal, changes in the terrain surface. 180 For this purpose, the corresponding tool of the ArcGIS software was used, adjusting the elevation ranges and eliminating values higher than 3 m, which made it possible to saturate the colour palette at lower values and to detect subtle movements.

Displacements in control points measured by GNSS
The time interval between GNSS monitoring campaigns was 94 days (3.13 months) for Victoria and 104 days (4.87 months) 185 for Colinas Lojanas. Table 4 outlines the effective displacements, direction, and velocity of the points of the GNSS network established in Victoria. Velocity (VH) was assessed by comparing the resulting displacement vector (DNE) and the corresponding monitoring time. The analysis of displacement components of control points showed a predominantly northward (N) direction, especially at points 4, 5, 6, 7, and 8, with displacement ranging from 0.118 m to 0.212 m. Points 1, 2, and 3 showed an eastward (E) trend, with values lower than 0.10 m. Points 4, 5, 6, 7, and 8 were located within the zone of depletion, 190 from the head to the foot, with higher displacements towards the top (0.216 m) and lower displacements at the toe (0.056 m).
In turn, the other points were located on the west (W) (1 and 2) or east flanks (3), although the latter point was outside the landslide boundary. In all cases, the total horizontal displacements widely exceeded at all points the threshold defined by the accuracy of the instruments and GPS positioning method used (0.03 m + 1 ppm) and therefore could be considered significant.  0.098 m, and were in general above the instrument accuracy of 0.035 m, except at points 1 and 2. The highest downward movements were observed in the head and main body (points 5, 6, and 7).
The velocities or displacement rates ranged from 0.013 to 0.069 m month -1 in the horizontal component, although they were slightly higher at the top and main body (points 4, 5, 6, and 7), with rates ranging from 0.050 to 0.069 m month -1 , than in the foot (point 1) and flanks (2 and 3), which show minimum rates (0.017 -0.035 m month -1 ). 210 The vertical displacement rates also peaked in the head and main body zones (downward movements ranging from 0.022 to 0.031 m month -1 ) and were lower at the landslide boundary (downward movements ranging from 0.008 to 0.013 m month -1 ). Table 5 presents the results of displacements, direction, and horizontal and vertical velocities at Colinas Lojanas with data from the GNSS network. Considering the horizontal accuracy threshold of 0.03 m + 1 ppm, points 3 and 21 were discarded because their values were below this threshold and did not represent significant displacement. The other points showed 215 significant displacement values, ranging from 0.033 to 0.151 m, and were generally lower than 0.053 m in the foot of the landslide (points 1, 2, 4, 5, 6, and 7), where the predominant direction is N. Conversely, the displacements were generally higher in the main body and head, showing values higher than 0.053 m at points 11, 12, 13, 14, 15, 16, 18, 22, 23, and 24, and even higher than 0.109 m at points 8, 9, 10, 17, 19, and 20. The directions of displacement, with some variations, tended to be https://doi.org/10.5194/nhess-2021-32 Preprint. Discussion started: 8 February 2021 c Author(s) 2021. CC BY 4.0 License.
north-east (NE) in this zone of the body, although some points, such as 16 and 20, had south-eastward (SE) and north-westward 220 (NW) directions, respectively. (points 1, 2, 3, 4, 5, 6, and 9), specifically on the road to the north of the study area, showed upward movements lower than 230 0.10 m.
The horizontal displacement rates ranged from 0.010 to 0.015 m month -1 at points located on the foot, while these rates ranged from 0.018 to 0.043 m month -1 in the main body and head. In turn, the vertical displacement rates of the landslide main body and head showed negative values (downward movements), ranging from 0.017 to 0.053 m month -1 , while positive values (upward movements) ranging from 0.020 to 0.030 m month -1 were observed in the foot. 235

Displacements in monitoring points assessed by RPAS
The displacements at the monitoring points are shown in the corresponding vector maps for the Victoria (Fig. 7) and Colinas Lojanas sectors (Fig. 8) and are summarised in Tables 6-9. The results of the displacements measured at monitoring points extracted from the DSMs and orthophotos in the stable zones, to validate the accuracy of these data, are outlined in Table 6 (Victoria) and Table 7       7a) shows that the points with the highest displacement were found in the SW, which corresponded to the upper area of the landslide, or head, and decreased down the landslide toward the main body and foot. The trend was almost always towards the NE (range between N049 and N059), although occasionally some points deviated to the N and even to the NW. Thus, in the summary of values presented in Table 8, the horizontal displacements averaged 0.145 m in the head, while the mean values in the main body and foot were both cases 0.081 m. In terms of displacement rate or velocity, the mean value in the head was 275 0.038 m month -1 , decreasing to 0.021 m month -1 in the main body and foot. Fig. 7b shows that the vertical displacements were predominantly negative, expressing downward movement or depletion, especially in the head of the landslide and, to some extent, in the body and foot, where many points were positive, expressing upward movement or accumulation. Thus, in the summary of Table 8 Table 9 show a rather uniform mean horizontal 285 displacement in the head and the main body of the landslide (0.056 and 0.054 m, respectively), slightly decreasing towards the foot (0.045 m). The velocity averaged 0.011 m month -1 in the head and main body and 0.001 m month -1 in the foot.
In the second period, the map of horizontal displacement vectors (Fig. 8c) also showed a decrease in displacement modulus from SW (head) to NE (foot), with a tendency towards NNE (N029-N039), albeit with a greater dispersion of directions in some points between ENE and NW. In summary in Table 9, the mean horizontal displacements range from 0.531 m in the 290 head to 0.316 m in the main body, and 0.221 m in the foot, which in velocity terms meant 0.038 m month -1 , 0.022 m month -1 , and 0.016 m month -1 , respectively.
The vertical displacements varied in a different way between the two periods. Accordingly, the values of Table 9 show that, in the first period (4 July 2016 -29 November 2016), the mean displacements were higher in the head (0.165 m) and main body (0.325 m) than in the foot, where they decreased to values of 0.063 m of upward movement or accumulation. The velocity 295 was higher in the head and main body (0.033 and 0.065 m month -1 , respectively) and lower in the foot (0.013 m month -1 ). In the second period (29 November 2016 -12 January 2018), the mean vertical displacement values were -0.342 m in the head, m month -1 , that is, gradually decreasing from the head to the main body and foot of the landslide. The head and main body showed downward movements, and the foot showed upward movements. Vegetation changes mainly influence the 300 determination of terrain elevation changes due to the use of digital surface models.

Differential models
The DoDs are shown in Fig. 9a (Victoria) and, b and c (Colinas Lojanas). The colour palette has been designed and adjusted to identify subtle changes in the DoD, which made it possible to stretch the colour palette at lower values. In addition, the 305 trimodal colour palette set negative (in blue) and positive values (in red), the former corresponding to a downward movement and the latter to an upward movement of the terrain.

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Thus, the Victoria sector showed downward movements of the surface predominantly in the upper part of the landslide (head) and upward movements predominantly in the lower part (foot), with a gradient from the highest negative values in absolute terms to the highest values in absolute terms when moving down the slope, reaching the lowest values in absolute terms in the central zone. In addition, some areas had marked downward and upward movements that contrasted with the surrounding areas more moderate changes in slope, as well as a general upward zone near the left flank overlapping with a densely vegetated 315 thalweg or ravine, as shown in the orthophotos ( Fig. 5a and b).
In the Colinas Lojanas sector, the DoDs were interpolated for the two study periods: July -November 2016 (Fig. 9b) and November 2016 -January 2018 (Fig. 9c). In the first period, the downward (negative) zone was identified at the head and main body, along with a slight accumulation in the foot. In the second period, displacement was highlighted by the accumulation of material at the foot and by depletion (loss of material) in some cracks, as shown in Fig. 6a, c and e. This 320 downward movement of the surface at the head and main body increased down the slope to the foot, next to the road, which showed significant upward movements.

Accuracies and errors
In the analysis of displacements from GNSS points, uncertainty was estimated from the combined error in the measurement 325 of the points (1) (2), which, according to the error propagation rule (Bossi et al., 2015;Fernández et al., 2016;Wheaton et al., 2010), is: In turn, in the analysis of displacements based on UAV flights and their images, uncertainty was estimated in two ways. First, uncertainty was estimated based on errors of the orientation process calculated at control and checkpoints, provided by the PhotoScan software (Table 3). These errors, which were assumed to be uncertainty, were smaller than 0.10 m for virtually all flights in both study areas, for both horizontal (XY) and vertical (Z) components, which generally corroborated those assessed 335 in previous studies (Carvajal et al., 2012;Eltner et al., 2016;Kršák et al., 2016;Vrublová et al., 2015) and they were within the ranges established by the American Society for Photogrammetry and Remote Sensing. Second, the mean values, standard deviation (SD), and root mean square error (RMSE) were calculated from displacements between points located in stable areas, which theoretically should be null at those points. The mean tells us about the general agreement between models and images (DSMs and orthophotos) from different periods, while the SD and RMSE tell us about 340 the individual agreement between them. Thus, the SD and RMSE values measure the uncertainty in the horizontal and vertical components of the displacements between points . These values generally ranged from 0.05 and 0.10 m for both components, so they were on the same order as the aforementioned control and checkpoint errors and those assessed in previous studies based on RPAS surveys (Fernández et al., 2015 when setting an uncertainty threshold of 0.10 m for horizontal and vertical displacements, above which displacements are considered significant. 345

Analysis of displacements in unstable zones
The horizontal and vertical displacement vectors assessed by processing RPAS flights make it possible to approximately delimit stable and unstable areas and, within these areas, identify different sectors with more or less intense movements.
In the Victoria study area, the horizontal displacement vectors maintained a consistent movement, with a tendency towards N and NE, although deviations from this trend were observed on the flanks, towards the centre of the zone of depletion, or in 350 other directions, due to the unevenness of the ground surface. The values of horizontal displacements were higher in the upper zone or head, where they generally exceeded the uncertainty threshold (0.10 m), reaching means close to 0.15 m and even higher values at some points. These values decreased towards the middle (main body) and lower (foot) parts of the landslide, where means were lower than the uncertainty threshold (0.08 m). However, in some points, the threshold was exceeded and therefore ground movement occurred in these sectors. Based on the above, the maximum deformation occurred in the head 355 where cracks and other landslides elements formed. The estimated velocities, which ranged from 0.046 m month -1 in the head to 0.026 m month -1 in the main body and foot, are typical of a very slow movement (Cruden and Varnes, 1996;Hungr et al., 2014;WP/WLI, 1993). The horizontal displacements measured with greater accuracy in GNSS points were consistent with the above. Thus, the displacements at points of the head reached values close to 0.20 m, while they decreased to values close to 0.06 m in the foot and flanks, which in velocity terms mean 0.070 m month -1 and 0.016 m month -1 , respectively, and in the 360 latter they are virtually at the limit of extremely slow movements. By period, although the displacements were most often nonsignificant in absolute terms, the mean velocity of the set of points showed considerable variations, ranging from 0.020 m month -1 (near the limit between extremely slow and very slow) and 0.070 m month -1 (very slow).
The vertical displacements were generally lower than horizontal displacements, which usually indicates flow-type movements (Cruden and Varnes, 1996;Fernández et al., 2016;Hungr et al., 2014). The vertical displacements were predominantly 365 negative, which indicates that the terrain tended to move downward through slope kinematics, and they were clearly above the significance threshold at the head (0.092 m) and near this threshold at the main body (0.085 m). At the foot, however, they were significant and positive (0.211 m), which is typical of zones of accumulation. For horizontal displacements, the highest value of vertical displacement indicates maximum deformation at the head, forming scarps, stepped terraces, and cracks. The rates of vertical velocity ranged from -0.112 m month -1 to -0.027 m month -1 at the head and main body (a very slow downward 370 movement) and 0.067 m month -1 (very slow upward movement). The GNSS data generally corroborated these kinematics, with lower, albeit significant, displacement and velocity values (also classified as very slow). The GNSS data by period also showed only significant vertical displacements between some points, although the same variations in velocities were generally observed between the different study periods, as observed in the horizontal displacements.
In conclusion, considering the horizontal and vertical displacements, the corresponding rates, and their distribution, a flow 375 process was active during the study period in the Victoria sector, specifically downhill creep. This movement showed very slow to extremely slow displacement rates, with some phases of increased deformation transitioning towards flow. The deformation was higher at the head, with horizontal and vertical decimetre displacements, and lower at the foot, with nonsignificant horizontal displacements and slight upward vertical displacements, indicating accumulation of material in this zone. 380 The Colinas Lojanas sector in the first study period showed horizontal displacements with a fairly uniform tendency towards N-NE, which rotated slightly towards N at the foot. This tendency was upheld in the second period, albeit with a greater dispersion of directions between NW and E. The modulus of the vectors (approximately 0.05 m) did not generally exceed the significance threshold, but the values were higher than 0.10 m at some points, indicating some activity in the area, as confirmed by the displacement values at GNSS points, which were 0.073 m at the head, 0.084 m at the main body, and 0.036 m at the 385 foot. These values translate into velocities of 0.027 m month -1 , 0.024 m month -1 , and 0.012 m month -1 , that is, a very slow movement, which actually fell below the threshold of extremely slow movement at the foot.
The vertical displacements of downward movement were above the significance threshold in the head and main body (0.165 m and 0.325 m) and below the threshold at the foot (0.063 m). The displacements measured with GNSS generally confirm the values assessed by RPAS and are significant in all cases, although positive displacements of upward ground movement were 390 measured at the foot. Velocity ranged from 0.024 m month -1 to 0.033 m month -1 at the head (in absolute terms), that is, slow movements, albeit close to the threshold of extremely slow movements.
In the second study period, the horizontal displacements were clearly above the significance threshold, peaking at the head (0.531 m) and decreasing towards the main body (0.316 m) and foot (0.221 m). Velocity was 0.038 m month -1 , 0.022 m month -1 and 0.016 m month -1 , respectively, that is, very slow, albeit higher than those of the first period. Major displacements stood 395 out at the head, indicating higher deformation in this zone than in the lower parts of the landslide. The vertical displacements were negative at the head and main body (-0.342 m and -0.187 m), exceeding the significance threshold, and positive at the foot (0.054 m), albeit below the significance threshold. These findings indicate downward movement of the displaced mass with accumulation towards the foot, producing maximum deformation at the head. These rates also correspond to a very slow movement.
The above suggests the existence of a downhill creep process, which is particularly evident in the first period, with very slow to extremely slow movements of displaced mass. The movement shows no considerable differences between the different zones of the unstable area, and the horizontal and vertical displacements are quite similar and low. In the second period, the displacements and velocities are higher in general. Differences are also identified between different zones, with higher deformation at the head area than at the footwhere material is accumulatedand with more horizontal than vertical 405 development. This suggests some acceleration of the process in this second phase compared to the first, most likely shifting from a downhill creep process, with little deformation, to a flow process, with more deformation.

Differential models
The differential models interpolated by DSM subtraction were used to visually assess the characteristics and evolution of the study landslides and to estimate the vertical, and in part the horizontal, displacements (Cardenal et al., 2019;Fernández et al., 410 2016). In addition, increases in surface elevation corresponded to changes not only in terrain elevation but also in vegetation cover. In general, predominant downward movements of the ground surface were identified at the head and predominant upward movements at the foot, which are typical of landslides with scarp zones at the head and accumulation of material at the foot. In the scarps, downward and forward movements, with loss of material, translated into downward movement of the ground surface; in contrast, at the foot, the forward movement of the mass itself elevated the surface when comparing the 415 models, which was eventually reinforced with true upward movements due to the accumulation of material (Cardenal et al., 2019;Fernández et al., 2016). In turn, the zones with sporadic and highly marked downward and upward movements, which contrasted with the surrounding zones, primarily resulted from changes in vegetation and crops, although some construction may eventually have occurred. Thus, some of these zones had well-defined geometric shapes, with both upward and moderately downward movements, which, when observing the orthophotos, were clearly interpreted as crops either grown or reaped in 420 the study period.
Conversely, other sectors had more intense changes, generally consisting of upward movements, which corresponded to zones of tree or shrub growth. This was mainly observed near the right flank, through which a gully runs and where there was intense vegetation growth in that period, and in other zones at the head, foot, and main body, where vegetation also clearly grew.
Nevertheless, when avoiding these effects, the subtle movement of the terrain is evidenced in the study area. 425 In the Colinas Lojanas sector in the first period (July -November 2016), few changes were observed in the models within the movement zone. The most abrupt changes occurred in woodlands and generally corresponded to tree growth (upward movements of the DSM) although downward-upward movements also occurred due to the limited accuracy of DSMs in these woodlands. Only moderate general upward movement was observed in the main body of the landslide, while slight downward movements were observed in the head and main body, albeit non-significant. In the second period (November 2016 -January 430 2018), some zones showed abrupt changes of irregular shapes, with both upward and downward movements, which occurred sporadically in tree or shrub areas and could be equally attributed to tree changes (growth, pruning, and cutting, for example) https://doi.org/10.5194/nhess-2021-32 Preprint. Discussion started: 8 February 2021 c Author(s) 2021. CC BY 4.0 License.
as to the accuracy of the DSM. However, a more or less generalised downward movement was also observed in the main body and head, despite some plant growth in this zone. Nevertheless, the most visible changes occurred in the main body and foot of the landslide, where downward movements may have corresponded to an area of scarp or secondary terrace, and significant 435 upward movements at the foot, next to the road, resulted from both a horizontal forward movement of the ground mass and a true upward movement of the surface as the mass of material accumulated. The road itself is raised; therefore, the upward movement of the surface corroborates the displacement of the points.

Conclusions
The monitoring technique by GNSS demonstrates the accuracy of this technology, which can detect centimetre deformations 440 in short periods and under all weather circumstances (rain, mist, fog, strong sunshine, by night). RPAS remains a useful tool for rapid surveys, with centimetre resolution and centimetre-decimetre accuracy, on plots smaller than 100 km 2 . The latter has the advantage of enabling a survey of the entire surface.
Both techniques estimate deformations by measuring horizontal or vertical displacements. In GNSS they are determined directly from points measured on the ground. In contrast, in RPAS they are determined from points extracted from the DSMs 445 and orthophotos resulting from UAV image processing by SfM and MVS. The advantage is that these points can be extracted later, after examining the DSMs and the orthophotos. Also, DoDs can be constructed to estimate vertical and even horizontal displacements of the terrain surface. Lastly, RPAS techniques provide a very general view of the phenomenon, though since they use DSM and not DTM on the one hand and combine horizontal and vertical movement parameters on the other hand, the data must be interpreted carefully. Accordingly, combining this technique with the calculation of displacements between 450 monitoring points and with the accurate measurement of GNSS points makes it possible to determine the kinematics of movement with high resolution, even in cases of subtle movements, such as those discussed above. Thus, the techniques described in the present study show that the two landslides had a predominantly NE direction. In Victoria, the horizontal velocity ranged from 0.017 to 0.069 m month -1 , and the vertical downward velocity ranged from -0.008 to -0.031 m month -1 , so this movement is classified as very slow. In Colinas Lojanas, the horizontal velocities ranged from 0.006 455 to 0.044 m month -1 . As for the vertical velocities, two ranges were defined for upward (0.010 to 0.030 m month -1 ) and downward movements (-0.012 to -0.053 m month -1 ). Thus, these movements are also classified as very slow.
Future research could focus on improving the methodology by studying the generation of DSMs using RPAS with the application of filters to eliminate vegetation to reduce its effect on displacement measurements. Filtering is expected to improve the accuracy of DTM-based measurements.