Miscellanea 633 ANNALS OF GEOPHYSICS, VOL. 51, N. 4 August 2008 Key words Terrestrial Laser Scanner – Reflectance – RGB – Volcanoes – Vesuvius. 1. Introduction The terrestrial laser scanner (TLS) is gener- ally used for the geometrical and kinematical characterization of surfaces affected by defor- mation allowing the definition of very accurate digital models from remotely acquired data. Hunter et al. (2003) showed an interesting TLS application for ground deformation measure- ments at Mt. Etna. Teza et al. (2007) provided a method for displacement field computation of landslide ground surfaces by multi-temporal TLS-based models comparison. The new gen- eration of very long range scanners allows sur- face observation operating on ranges of some hundred meters and more providing very de- tailed (few centimeters) digital models (Re- mondino, 2003). A TLS scan provides the posi- tion of acquired points and a radiometric infor- mation; for each element of the point cloud, the intensity of received pulse is measured. It is re- lated to both the material reflectance and the relative position of instruments respect to the observed surface (Reshetyuk, 2006), and it is also highly sensitive to the water content (Lu et al., 2005). A time-of-flight terrestrial laser scanner (TLS) operates with nanosecond laser pulses Remote sensing of volcanic terrains by terrestrial laser scanner: preliminary reflectance and RGB implications for studying Vesuvius crater (Italy) Arianna Pesci (1), Giordano Teza (2) and Guido Ventura (3) (1) Istituto Nazionale di Geofisica e Vulcanologia, Sezione di Bologna, Bologna, Italy (2) Dipartimento di Geoscienze, Università degli Studi di Padova, Italy (3) Istituto Nazionale di Geofisica e Vulcanologia, Roma, Italy Abstract This article focuses on the use of terrestrial laser scanner (TLS) in the characterization of volcanic environments. A TLS survey of the Vesuvius crater (Somma-Vesuvius volcano, Italy) allows the definition of an accurate and georeferenced digital model of different sectors of the crater. In each sector, the intensity is computed for each point as the ratio between the emitted amplitude and the received one, normalized to the maximum signal. More- over, the RGB colors of the observed surfaces can be captured by means of a calibrated camera mounted on the TLS instrument. In this way, a multi-band information is given, since a long range TLS operates in the near in- frared band. The reflectance and RGB data are compared to verify their complementarities for model analysis and inspection. The collected data allowed the recognition of different volcanic deposits and stratigraphic fea- tures. In addition, our results shed light on the spatial extension of landslides and on the dimensions of rock fall/flow deposits affecting the inner walls of the crater. Mailing address: Dr. Arianna Pesci, Istituto Nazionale di Geofisica e Vulcanologia, Sezione di Bologna, Via Do- nato Creti 12, 40128 Bologna, Italy; tel. +39 0514151416; fax. +39 0514151498; e-mail: pesci@bo.ingv.it Miscellanea 9-03-2009 14:42 Pagina 633 634 A. Pesci, G. Teza and G. Ventura emitted along a direction defined by two cali- brated angular coordinates (φ, longitude and α, elevation). The signal is backscattered by the acquired target providing the time of flight t, and the path is computed as d = ct / 2 (c is the speed of light) leading to the complete spheri- cal coordinates (φk, αk, dk). The laser beam is automatically deflected over known directions by a moving mirror device providing the acqui- sition of a large number of points well distrib- uted on the observed physical surface. The laser beam properties assure spatial collimation and good waveform of the pulses, leading to high resolution and accuracy. The Optech ILRIS 3D, e.g., is able to acquire a point at 50 m distance with about 7 mm accuracy and with 17.7 mm resolution (Lichti and Jamtsho, 2006). The ac- curacy is mainly related to the internal teleme- ter efficiency in time measuring, leading to a precise range definition, whereas the resolution depends on spot size and on the level of data overlapping, based on the choice of the calibrat- ed angular grid. The product of a scan is the raw point cloud ��dk,φk,αk,I�dk,φk,αk,dk��, k = 1,2,···,N�, where I�dk,φk,θk,dk� is the intensity of the pulse corre- sponding to the k-th point and N is the number of acquired points (generally, N ~ 105-106). The raw point cloud is directly provided by the in- strument. The spherical coordinates are trans- formed into Cartesian ones and the intensity is normalized to the range 0-255 in order to allow the data importing by software intended for TLS data processing. When a calibrated camera is mounted on the TLS instrument, a series of RGB images of the observed scene can be acquired. The RGB and TLS-based data can be also merged by means of specific software leading to a colored point cloud or a textured digital model. Since a cam- era is a passive instrument, the RGB image crit- ically depends on the light conditions. On the contrary, since the TLS is an active instrument, the acquisition is independent from light condi- tions. Both the intensity and RGB data can be use- ful in point cloud inspection for edge detection and in the identification of different materials (Kurazume et al., 2002). Roncella et al. (2005) showed that a 3D model obtained from digital photogrammetric techniques can be used to rec- ognize geo-mechanical features, since image processing operators conceived for image seg- mentation (e.g., edge detection operators) can be applied. At present, few studies make specific use of the intensity data obtained by TLS or aerial laser scanner instruments (e.g. Mazzarini et al., 2007), but the geometric information is princi- pally used. This paper investigates the nature of TLS- derived intensity and coupled RGB data to ver- ify if: a) the corresponding information is re- dundant, or an integration could be useful or necessary, and b) the intensity and/or RGB da- ta can be used to recognize different material and to detect, for example, stratigraphic succes- sions. The crater of Vesuvius (Italy) is the test site selected to investigate the peculiarities of a volcanic environment. 2. Terrestrial laser scanner: fundamentals and properties of acquired data As stated above, the TLS point cloud is ��xk,yk,zk,In�xk,yk,zk��, k = 1,2,···,Ne�, where In is the normalized intensity and Ne ≅ N is the num- ber of points where the intensity can be effec- tively considered (for example, a signal satura- tion in the internal sensor consists of correspon- ding point removal). The raw intensity I, direct- ly provided by the instrument, is converted into the normalized intensity In by means of: a) tar- get-distance corrections, and b) transformation of obtained results into the 0-255 range of inte- gers, like a grey level image. The target-dis- tance correction is applied to provide similar in- tensity values for a same material acquired at different distances, taking into account the ob- vious fact that the raw intensity depends on the inverse square distance. In a straightforward ap- proach, the distance-corrected intensity can be IC,k = Ik (dk / d0)2, where d0 is a reference dis- tance (generally unknown to the user), resulting in In,k = [255(IC,k – IC,min) / (IC,max – IC,min)], where [r] indicates the nearest integer to the re- al number r, and IC,max, IC,min are the maximum and minimum values of the set of distance-cor- rected intensities. In this way, the point cloud Miscellanea 9-03-2009 14:42 Pagina 634 635 Remote sensing of volcanic terrains by terrestrial laser scanner: preliminary reflectance and RGB implications for studying Vesuvius crater (Italy) can be inspected using TLS data processing software (e.g. Innovmetric PolyWorksTM, I- SiTE StudioTM, and others). This transformation is performed using a parsing software provided by TLS manufacturer (e.g. Optech Parser). The actually implemented algorithm, where some elaborations are joined to the straightforward approach to improve the visualization, is deemed to be proprietary information and is therefore unknown. The rate of the backscattered signal depends on both target physical properties and geomet- rical conditions, that is the relative position of TLS and observed surface, or better the angle of incidence. A common material is generally characterized by a quasi-Lambertian behavior, diffusing the incident radiation on the semi- space, mainly concentrated along the preferen- tial scattering direction, depending on the mi- croscopic surface irregularities of the observed object (roughness), on the laser wavelength and on the incident angle (Baltsavias, 1999). Theo- retically, a Lambertian reflection is a complete and total signal diffusion along each possible direction in the semi-space over the shot ele- ment. A good practice of TLS observation re- quires the incidence to be as normal as possible, to have maximum precision and resolution, which also depend on both instrumental per- formances and observational conditions. The area illuminated by a laser beam (the footprint) results from a thin-cone/plane (beam/surface) intersection, leading to a circle (or ellipse) with a small but finite diameter, linearly increasing with the distance d of the target (cone height). The probability of return detection decreases if the angle between the laser beam and the nor- mal to observed surface increases. If this angle is too high, fewer points are acquired, and the accuracy on their coordinates is worse because of footprint deformation (spreading on the sur- face). If the characteristic size of the macro- roughness of the observed surface is similar to the footprint diameter, the intensity does not de- pend on observation angle because a significant part of the area illuminated by the laser is al- ways oriented towards the instrument, i.e. is not very far from normal incidence conditions (see Appendix C). If two areas are observed under the same conditions, i.e. similar distance and angle re- spect to the surface normal, the different inten- sities are proportional to the corresponding re- flectance and could be theoretically used to dis- criminate between different materials. Never- theless, the intensity strongly depends on mois- ture of the material, since a TLS generally op- erates in IR band. So, the radiometric data can- not be generally used for classification purpos- es if multi-temporal point clouds are consid- ered, that is a classification can be attempted only if homogeneous data are compared. More- over, the parsing actions have to be carefully in- vestigated for subsequent data interpretation based on intensity values, using raw data. Many TLS typologies exist, characterized by different wavelength, accuracy, and achiev- able maximum range (Boehler et al., 2003). An online description of the available instruments and processing software can be found at POB (2008). Long range instruments are very inter- esting in geological/geophysical applications. In fact, they allow the data acquisition also of inaccessible areas like volcanic craters or land- slides since observation distances of about one kilometer or better can be reached. A TLS sur- vey does not require contact with the observed surface but a series of high-reflectance artifi- cial targets can be placed on the scene in order to allow the georeferencing of the point cloud. These targets, whose centers are the ground control points (GCPs), can be concurrently ac- quired by TLS and topographical techniques like total station and/or GPS. This operation can be useful to provide some reference point for a next data registration on external frames. The GCP positions can be chosen on the basis of accessibility, the only requirement is their good spatial distribution. Some instruments are equipped with a calibrated camera and directly provide both intensity and RGB colors of the point cloud. A specific processing procedure, usually performed by means of specific software, is re- quired to extract useful information from the TLS data and to generate a final and complete digital model (Remondino, 2003). If an object is observed from more than one viewpoint (for example, Vesuvius crater), the processing starts Miscellanea 9-03-2009 14:42 Pagina 635 636 A. Pesci, G. Teza and G. Ventura with the registration of the point clouds, that is their linking on a common reference frame to provide a global point cloud. Generally, surface matching algorithms are used for the data regis- tration, e.g. the Iterative Closest Point (ICP) al- gorithm (Besl and McKay, 1992; Chen and Medioni, 1992). The global point cloud is then georeferenced by using a series of GCPs. A da- ta filtering/cleaning could be necessary, espe- cially if elements to remove (e.g., trees) are present. Some expedients are used to better solve for the possible presence of vegetation, like the choice of the last pulse mode for data acquisition, providing the last arrival time for pulse detection and increasing the possibility to receive a terrain backscattered signal. More- over, the intensity values can also be used to identify, select and remove the points corre- sponding to vegetation, due to water-content leading to low reflection. The generation of a 3D polygonal model is the central point of data processing. It is a trian- gular mesh whose vertices are the points of the filtered and/or smoothed point cloud. The tex- ture associated to the mesh can contain infor- mation on reflectance, RGB color, as well as on physical properties of the material. 3. Study area The Somma-Vesuvius volcano consists of two main edifices: the Somma edifice, which is affected by a summit caldera, and the Vesuvius cone (1281 m a.s.l.), which is located within the caldera (fig. 1; Santacroce, 1987). The Somma products, which include lava flows and scorias, are older than 18.3 ky. The Somma caldera re- sulted from collapses related to four Plinian eruptions occurred between 18 ky and AD 79. Sub-Plinian eruptions also occurred between 16.1 ky and AD 1631 (Andronico et al., 1996). Lava flows in alternation with explosive phases characterized the activity between AD 79 and AD 472, and mainly between AD 1637 and 1944 (Arnò et al., 1987). The present-day Vesuvius crater formed during the last AD 1944 eruption (Santacroce, 1987). The volcano is in a quiescent stage and only seismic and fumarolic activity occurs. The volcanic hazard is, however, high because of 600,000 people live around the Vesuvius and an inverse relation between the duration of the qui- escent periods and energy of the eruptions ex- ists (Santacroce, 1987). The present-day inner walls of the Vesuvius crater, which measures about 550 m in diame- ter, consist of lavas related to the pre-1906 ac- tivity (southwestern wall) and of lavas of 1913- 1944 activity (northeastern wall), as depicted in fig. 1. Spatters and pyroclastic deposits cover the Vesuvius cone and outcrop on the northeast- ern inner wall of the crater. The crater floor is filled by slide deposits resulting from the down- fall of lava fragments/blocks outcropping on the steep, inner walls. The crater rim results from the superimposition of the northeastern rim re- lated to the 1944 eruption on that of the pre- 1944 period of activity (southeastern rim). Fol- lowing Ventura et al. (2005), the collapse of the small cone located before the 1944 eruption, as well as the sharp contact between the pre-1906 and 1913-1944 lavas of the inner crater walls is guided by a NW-SE striking fracture. The strike of this fracture is that of the main structural dis- continuity affecting the whole Somma-Vesu- vius edifice and crossing the Vesuvius cone (Bianco et al., 1998). 4. Data acquisition The Vesuvius crater was observed twice times by TLS, on May 2005 (Pesci et al., 2007a) and October 2006 respectively. The in- strument used was the Optech ILRIS 3D TLS (May 2005) and its upgraded, extended range (ER) version ILRIS 3DER (October 2006). The ER version can operate in two modes, extend- ing the maximum achievable range if necessary. This option is particularly useful in a volcanic environment where low-reflectance lavic mate- rial exists. The whole crater was observed from differ- ent viewpoints located in the crown, chosen in order to operate with good incident angles as normal as possible, providing the total surface coverage (fig. 2). In the 2005 measurement campaign the access to the northern part of the crater was forbidden, while in October 2006 Miscellanea 9-03-2009 14:42 Pagina 636 637 Remote sensing of volcanic terrains by terrestrial laser scanner: preliminary reflectance and RGB implications for studying Vesuvius crater (Italy) five station points well distributed around the crater were used. Each single scan covered the angular space of about 40°, and the acquisition distance ranged from 300 m to 600 m. At 500 m distance the mean sampling step at the ground was about 5 cm. For the used instrument, the footprint di- ameter on a surface orthogonal to the laser beam is D=12+0.17d, where d is the distance ex- pressed in m and D is in mm. Therefore, in this application D ranged from 6 cm to 11 cm. Since the resolution depends on both the footprint size and the sampling step, and the first dominates because its diameter is considerably greater re- Fig. 1. Digital terrain model of the Somma-Vesuvius volcano and simplified geological sketch map of the Vesuvius crater (modified from Santacroce, 1987). The reference frame is the WGS84 (UTM coordinates). Miscellanea 9-03-2009 14:42 Pagina 637 638 A. Pesci, G. Teza and G. Ventura spect to the sampling step (Lichti and Jamtsho, 2006), 10 cm can be considered a good estimate of the mean actual spatial resolution. A calibrated camera was mounted over the laser unit to provide RGB colors for texturing; the camera was characterized by 28 mm focal distance and 0.007 mm pixel size, so the corre- sponding pixel size on the ground surface was about 12.5 cm at 500 m distance. The ground spatial resolution of camera and TLS were about the same in similar observational condi- tions. In this way, a comparison between inten- sity and RGB data, as well as an integration of these data to provide a better knowledge of the observed structures, were allowed. The standard data processing is performed using the Innovmetric PolyWorksTM software package, providing a georeferenced 3D polygo- nal model for each survey. These models were also integrated with a digital terrain model (DTM) of the volcano generated by using data obtained from aerial photogrammetry enlarging the surveyed area (see fig. 2). Moreover, a pre- liminary comparison between 2005 and 2006 models was presented and discussed, pointing out the capability of this surveying methodolo- gy to recognize and measure surface variations in a volcanic environment (Pesci et al., 2007b). The present article presents the main results of an analysis aimed to understand the impor- tance of radiometric contributions to the point cloud and image inspection in a volcanic envi- ronment. In particular, the analysis is focused on three selected zones of the crater character- ized by different origin, morphology and visi- ble features (fig. 2). A-zone is the fracture area that coincides with the morphological disconti- nuity separating the two half parts of the crater and differ for age and lithology and was ob- served from about 500 m distance. B-zone is a volcanic wall acquired in a very detailed way thanks to short range of about 50-80 m. The last, C-zone, is a portion of a landslide lying in the NW sector of the crater, scanned from about 500 m. Since in each considered zone the acquisi- tion distances were roughly constants (A and C: 500 m, B: ~60 m), the observational conditions allowed a quantitative analysis of the intensity provided by TLS. 4.1. Crater fracture zone The fracture area occurring at the south- eastern tip of the Vesuvius crater (A-zone in fig. 2) marks the contact between the more recent and steepest north-eastern wall and the older south-eastern wall. A vertical displacement of about 1.5 m can be recognized in the A-zone by means of the point cloud intensity analysis. The vertical step is clearly visible in the intensity image (fig. 3b) but cannot be directly detected in the ordinary red-saturated RGB image (see fig. 3a), also due to shadows that hide morpho- logical features. Nevertheless, some hide fea- tures in the RGB image could be detected by means of a re-balancing of the R, G and B com- ponents to create a false color image; this process, anyway, is not easy and requires man- ual editing and several trials. The properties of an RGB image strictly de- pends on illumination conditions, in particular a shadow can hide interesting features. On the contrary, the TLS-based intensity data are ob- tained by active independent illumination but its relative nature, depending on geometry of observation and weather conditions, must be taken in account. On the other hand, materials characterized by the same color tones may have different physical properties and chemical com- position, whereas difference in composition could be easily detected using IR signal. In con- clusion, if intensity data are used, in some cas- es a direct and easy recognition of some fea- tures can be performed, without additional im- age processing efforts. 4.2. Crater inner wall The B-zone (fig. 2) is a relatively small, NW-SE striking sub-vertical cliff located near the previously described fracture area. Different lithologies, which include welded scorias, mas- sive and scoriaceous lavas, can be recognized. A first approach to remotely map volcanic rocks is the analysis of a reduced number of da- ta extracted from some selected sections. Six vertical profiles are considered, and both inten- sity and RGB data are extracted to compare da- ta distributions and searching for data correla- Miscellanea 9-03-2009 14:42 Pagina 638 639 Remote sensing of volcanic terrains by terrestrial laser scanner: preliminary reflectance and RGB implications for studying Vesuvius crater (Italy) tion. In particular, fig. 4a shows the intensity statistical distribution of data extracted along the third vertical profile (from the left, the red one in fig. 2). This distribution clearly indicates preferential intensity values corresponding to histogram peaks. On the contrary, the three col- or channels are distributed in an almost Gauss- ian way leading to standard deviation values of 55, 68 and 86 for the red, green and blue com- ponent respectively. Another important result is the high correlation between the color channels, which is 0.984, 0.933 and 0.967 for the R-G, R- B and G-B combinations respectively. There- fore, the relations among the three basic colors are here linear trends, and each channel carries nearly all the information of the RGB image. For this reason, the analyses presented there are based, besides on TLS-based IR intensity data, on the R channel only. The complete analysis is reported in Pesci et al. (2007c). In the intensity vs. color plot of the consid- ered vertical profile, the point distribution shows a «comb-peak» shape. Despite large da- ta dispersion, this distribution highlights the different behavior of intensity, which is organ- ized in some defined bands, and color channels, which are spread. The same results are obtained over the other profiles (not shown here for the sake of brevity). Dealing with a clear surface, composed of different materials distributed into irregular geometrical zones, these bands are probably re- lated to the physical surface properties (rough- ness, moisture, etc.). The comb-peak structure consists of about 9-10 bands in the intensity distribution. Moreover, this structure is weak- ened if the entire surface is considered instead of vertical sections, due to a more noisy data set. In addition, a large number of narrow bands (with steps of some intensity units) can be ob- served in both the sections and the whole area. This second effect is related to the quantization Fig. 2. Left panel: perspective view of the Vesuvius crater. The TLS viewpoints are marked by red and blue dots, concerning 2005 and 2006 surveys respectively. Lines-of-sight are reported as arrows. Right panel: front view of the three studied outcrops (yellow boxes A, B, and C in the left panel) and vertical sections used for pre- liminary data analysis (see later on). Miscellanea 9-03-2009 14:42 Pagina 639 640 A. Pesci, G. Teza and G. Ventura effect of the TLS detector, whose dynamics could be unable to capture the entire range of received signal intensity. Note that the quanti- zation effect, which is an instrumental artifact, can be also sharply observed in those condi- tions where the comb-peak pattern does not ap- Fig. 3a,b. A-zone is a fracture zone in the SE part of the Vesuvius crater. The point cloud is colored using the RGB texture (a) and the intensity data (b). The zoomed area shows a vertical discontinuity of a high intensity horizontal layer, leading to a step of about 1.5 m. In order to better recognize the fracture zone, the line-of-sight is far from the normal to the surface. The 15-m scale is referred to the square-framed zone only. Fig. 4a,b. Statistical distribution of intensity data extracted from the vertical profile 3 (a), and plot of TLS-based intensity vs. red channel of the RGB image (b). Miscellanea 9-03-2009 14:42 Pagina 640 641 Remote sensing of volcanic terrains by terrestrial laser scanner: preliminary reflectance and RGB implications for studying Vesuvius crater (Italy) pear neither in the vertical sections, nor in the entire surface. Moreover, the comb-peak effect and the quantization one differ by one order of magnitude. Therefore, the comb-peak effect seems to be not related to instrumental troubles. To exclude possible systematism, a further site area was selected and analyzed (C-zone, fig. 2). 4.3. Landslide This study case (C-zone in fig. 2) is the cen- tral sector of a landslide affecting the north- western inner wall of the crater. C-zone was se- lected because its material (chaotic lava blocks and loose scorias) is the same as the B-zone, but it is not stratigraphically organized. C-zone rep- resents a debris/fall slide. Figures 5a and 5b show intensity data statistical distribution and correlations, respectively. The lack of a well de- fined point distribution (no comb-peak shape is observed in this case) and the detection of al- most the same intensity peaks leads to the con- clusion that the comb-peak shape, if it exists, is not an artifact but is related to material proper- ties. The distributions of the intensity peaks of vertical sections related to the volcanic wall and landslide are compared. Data are fitted by Gaussian functions over the peak intensity fre- quencies considering an a priori sigma of 10 in- tensity points. Figure 6 shows the results in terms of central values of Gaussian functions, with errors at 1-σ level. The landslide data show larger errors, whereas the volcanic wall data are clearly described by function with a very sharp shape. Nine peaks are selected for each data set, with similar values taking into ac- count errors. The main discrepancies are high- lighted in the figure. A further test is performed using data be- longing to a non-volcanic environment. See Appendix A, where results related to a coal quarry in South Africa are presented. These re- sults underlie the relation of intensity and envi- ronment and partially reinforce the exclusion of instrumental effects. 5. Discussion and data interpretation The analysis of the data from the B-zone of Vesuvius highlights the lack of correlation be- tween intensity and colors. In particular, the correlation coefficient computed using all the points is about -0.06 value. Further computa- tions, performed over some vertical surface boxes of the inner wall of the crater are shown in fig. 7. Data distribution confirms the occur- rence of comb-peak-shaped trends, even if it can be easily recognized in the case of vertical profiles only, since the noise is lower and the Fig. 5a,b. Statistical distribution of intensity data extracted from the vertical profile of the landslide (a), and plot of intensity vs. red channel (b). Miscellanea 9-03-2009 14:42 Pagina 641 642 A. Pesci, G. Teza and G. Ventura number of data is reduced. This consideration can be supported consid- ering data from some vertical surface bands in- stead of the whole data set or some profiles on- ly. In this way a large number of data can be considered but limited to almost the same verti- cal zones represented by previous profiles. Fig- ure 8 shows results concerning 5 m width bands located at the left, at the center and at the right of the site-test volcanic wall. The main peaks are newly computed and evidenced in the statis- tical distribution histograms but now, the noise is higher, leading to fatter Gaussians in the peak finder analysis. Also in this case the data are processed by recognition of significant peaks in the distribu- Fig. 6. Peaks distribution comparisons: red and black points are referred to landslide and volcanic wall respec- tively. Yellow boxes evidence the discrepancies. Fig. 7. Statistical distribution of the complete intensity data set extracted from the whole volcanic wall (a), and red channel and Intensity correlation (b). Miscellanea 9-03-2009 14:42 Pagina 642 643 Remote sensing of volcanic terrains by terrestrial laser scanner: preliminary reflectance and RGB implications for studying Vesuvius crater (Italy) Fig. 8. Statistical distribution and data correlation of 3 data sub-sets. Also in these cases, despite larger noise, peaks are well visible. Miscellanea 9-03-2009 14:42 Pagina 643 644 A. Pesci, G. Teza and G. Ventura tion. For each vertical band, mean and standard deviation of the Gaussian distribution are esti- mated and shown in fig. 9. Another global surface study was carried out by means of estimation of residuals ob- tained from the difference of intensity and col- or data. The residuals are shown in figure 10 and point out different patterns. The B-zone residuals have a mean value of 18, a standard deviation of 71, and a non-normal distribution. The latter may result from the sum of two nor- mal distributions peaked at 70 and -30. A clear Fig. 9. Intensity peaks recognized considering three vertical bands 5 m width in the B-zone. Fig. 10. Residuals map of B-zone and their statistical distribution. The residuals are computed as difference be- tween intensity and R component of the RGB image (see also fig. 4). The distribution is not-normal, but can be considered as overlap of two normal distributions whose means and standard deviations are also reported. Miscellanea 9-03-2009 14:42 Pagina 644 645 Remote sensing of volcanic terrains by terrestrial laser scanner: preliminary reflectance and RGB implications for studying Vesuvius crater (Italy) boundary between the positive (red) and nega- tive (blue) values of the residuals can be detect- ed in the map. The analyses presented above on the differ- ence between intensity and color data are very simple and directly relate different datasets af- fected by major noise. For this reason, a princi- pal components analysis (PCA) was also per- formed on data images by computing the most meaningful basis to re-express a noisy data set (Jolliffe, 2002; Shlens, 2005). This analysis transforms the input data so that the elements of the obtained vectors are uncorrelated. In addi- tion, the number of vectors obtained may be re- duced by retaining only those components that contribute more than a specified fraction of the total variance of the dataset. In this way, only the meaningful and no redundant information is retained, and the possibility of easy detection of particulars in the transformed images is associ- ated to a significant reduction of the data stor- age requirements. A standard PCA procedure of analysis was applied using Matlab functions (see Appendix B) to process a full data matrix composed by the RGB and the Intensity data sets. Results show the independence of the two data set, con- firming the correctness of previous analysis. The same procedure was also applied to demonstrate that intensity information is inde- pendent from the stationing point of the instru- ment in this configuration of acquisition (Ap- pendix C). In fact, the surface natural corruga- tion and the footprint have sizes that allow the laser beam to be diffused along each angles in the space, providing the same signal amplitude neglecting the geometry of acquisition. Data extracted from A-zone clearly show a 1.5 m long vertical step (fig. 3). This step cor- responds to the zone where a fracture is mapped by Ventura et al. (2005). The collected data in- dicate that this fracture is not an open crack, but a fault separating the products of the 1913-1944 activity from those of the pre-1906 activity. The age of the younger deposits affected by this fault and the 1.5 m slip evidenced from TLS da- ta suggest an average slip rate of 2.4 cm/y. However, the slip rate along this fault cannot be constant over time, and could be related to a single or few post-1944 faulting episode(s). In- tensity profiles from the zone B (fig. 4) high- light the transition from the uppermost welded scoria layer of the 1944 eruption, characterized by high intensity values, and the underlying lavas of the 1913-1944 period of activity, which show lower values. More in detail, the profiles also mark the boundaries between the massive and scoriaceous portions of the lavas (see pro- files 2-5 in fig. 11). The rough boundary between the lavas and Fig. 11. Intensity of the six profiles selected in the B-zone (fig. 4). Data (in white) are smoothed (red line) us- ing a FFT filter to better display slow variations and examine the intensity trend along the sections. A common scale of 0-300 is adopted. Miscellanea 9-03-2009 14:42 Pagina 645 646 A. Pesci, G. Teza and G. Ventura the upper welded scoria layer is also evidenced in the map of the residuals (fig. 10). However, the residuals do not clearly discriminate the scoriaceous portions of the lavas from the mas- sive ones (see fig. 4 for a comparison). To bet- ter analyze the geological features of the B- zone, the cloud of points was divided in inten- sity bands at intervals [50, 80], [120, 150], [150, 200] and [220, 255] based on peaks distri- bution. These intervals were obtained comput- ing the main Gaussian peaks of the six profiles, performing averages and creating intensity box- es to efficiently subdivide the data for material characteristics detection. Results of this analy- sis are shown in fig. 11. The image with inten- sity range [50- 80] highlights the massive por- tions of the 1913-1944 lavas depicted in fig. 4, whereas the images with intensities in the ranges [150, 200] and [220, 255] show the sco- riaceous levels. The image in the range [120, 150] marks the boundaries among the different lithological units. Therefore, we conclude that the integrated analysis of the residuals, intensi- ty profiles and bands gives useful information on the lithology and stratigraphy of volcanic deposits. Data from the C-zone clearly show the dif- ferent layering of the lavas in the N-W and S-E inner walls of the Vesuvius crater. These slides are related to both gravity instability and earth- quake shaking (Ventura et al., 1996). The point cloud shows the spatial extent of the debris/fall slide separating the two sectors of the Vesuvius crater, the source area, the summit scar, the slide wedge and basal fan (see fig. 6). Based on the grey intensity of the slide material, a more recent (shining pixels in fig. 13) slide deposit can be recognized from the older slides. The di- Fig. 12. Selection of the points of the B-zone on the basis of the intensity ranges. Four ranges are considered: [50- 80], [120-150], [150-200] and [220, 255]. Miscellanea 9-03-2009 14:42 Pagina 646 647 Remote sensing of volcanic terrains by terrestrial laser scanner: preliminary reflectance and RGB implications for studying Vesuvius crater (Italy) mensions of the slide material can be also deter- mined using point cloud coordinates. As an ex- ample, the largest block of this slide measures 3.7 m x 2.4 m x 1.6 m. The integration of TSL data and the geolog- ical knowledge of the Vesuvius volcanic crater allow the recognition of some patterns: dark zones highlight lava blocks, data belonging to the second interval seems to be familiar with the contact area between different lithologies, and the higher values are probably due to pyro- clastic materials of different size. 6. Conclusions This study focuses on the analysis of radio- metric data in volcanic environments and in- vestigates the difference between color infor- mation content and TLS-based IR intensity. In particular, the RGB data from a calibrated camera can be independent or highly correlat- ed to IR, depending on the geological environ- ments, the intensity being strictly related to the physical/chemical properties of the material. Some selected sites of the Vesuvius crater were tested to investigate the relation between RGB and intensity, and to give preliminary results on the impact of such an approach on geological studies. Results show that intensity data are in- dependent enough from RGB adding valuable information to image analysis, which can be considered a different channel, as shown by both a classical data treatment and PCA mod- ern processing. The data analyzed here allow: i) discrimination between different lava flow faces, block and welded scorias, ii) identification of the layering of volcanic deposits, and iii) recognition of slide material and slide- related morphologies. In addition, quantitative estimates of the dimension of single clasts can be done. These applications and analyses repre- sent a preliminary approach to validate a new method for data inspection based on integration between TLS data and photographic images. The analytical approach reported here could be extended to other non-volcanic environ- Fig. 13. Point cloud of the C-zone (landslide in volcanic environment, see fig. 6). The detail of a slide lava block and the size of the modeled surface are shown. Miscellanea 9-03-2009 14:42 Pagina 647 648 A. Pesci, G. Teza and G. Ventura ments, as suggested by the example of a coal quarry. Researches in this field are in progress and the next step includes (a) monitoring slide movements within the Vesuvius crater, and (b) planning a multidisciplinary experiment based on scanning of an artificial surface composed of several elements disposed to reproduce a syn- thetic, stratified, surface. Concerning the sec- ond point, a new experiment was performed in April 2008 showing that the intensity data is al- most independent with respect to the incident angle if the observed surface irregularities are of the same order of the spot size. A complete description of the experiment and results is now submitted on Annals of Geophysics journal and partially satisfies the search for a new method to better analyze intensity data and their impli- cation in geophysical/geological studies. Acknowledgments The authors thank Fabiana Loddo (INGV), Andrea Faccioli and Marco Bacciocchi (Codev- intec Italiana s.r.l.) and Dario Conforti (Optech Inc.) for their kind support in the experimental phase. Very special thanks to Massimiliano Cerrone and to all the staff of the «Ufficio Tecnico» (IN- GV-Rome) for their great contribute in the real- ization of an international seminar concerning Laser Scanner applications on 6-7 June 2007. Fig. A1. Point cloud of a coal quarry (South Africa): RGB texture (a) and intensity image (a). The dashed yel- low line is the selected profile. Appendix A Results reported in chapter 4 about on intensity and color statistical distribution and their correlation show that data are widely independent, suggesting that important information can be added for a geological and geomor- phological study of the area. In particular, the simple analysis of volcanic wall data set, shows a peak distribu- tion (authors named «comb-peak shape»). Several considerations and data checks were done to exclude system- atism, data alteration or instruments anomalies to verify the results reliability. Moreover, the same analysis per- formed on a landslide in a different part of the crater shows a completely different statistical distribution but with similar intensity values. This Appendix reports the results of a further test performed in a non-volcanic environment (coal quarry at Mid- delburg, Moumalanga Province, South Africa) using the same instrument (Optech ILRIS 3D). With this addition- al test, the peculiarities of a volcanic area with respect to another geological environment can be highlighted. A single scan of a 25 m x 25 m vertical wall was acquired from a distance of 100 m. After modeling and RGB da- ta rendering, both intensity and color information are extracted along a profile (fig. A1). Results are quite differ- ent from those of the previous study cases, showing a clear correlation between the two kinds of data (fig. A2). Miscellanea 9-03-2009 14:42 Pagina 648 649 Remote sensing of volcanic terrains by terrestrial laser scanner: preliminary reflectance and RGB implications for studying Vesuvius crater (Italy) In a first approximation, a linear trend can be recognized, even if the linear correlation coefficient is ~0.6. How- ever, the high noise level, as well as the absence of correlation in volcanic environments, suggest that this rela- tively low value reflects, in any case, some data dependence. The statistical distribution analysis shows a lower number of intensity peaks with respect to that of the B and C volcanic sites. This can be related to the different analyzed surfaces and material properties. This analysis is not discussed here because it was performed only for comparison reasons to show that different geological environments give different responses. Appendix B Despite the evidence of a clear distribution, data belonging to the volcanic wall are characterized by high noise. Therefore, a more specific analysis was performed to validate the results reported in chapter 5, considering an approach based on principal component analysis (PCA). The PCA allows a reduction of redundant data and an easy recognition of details and hide features; in this case the method is used to highlight correlations between intensity and RGB data set. The PCA application requires a preliminary transformation of all the data (the three RGB channels and the in- tensity data) to have zero mean and variance 1. The results of PCA are still four datasets, but they are uncorre- lated and ordered in a way that their participation to the data variance highly decrease from the first to the fourth. So, the less significant datasets can be excluded considering a limit-variance, e.g. 0.02. In the present work, Mat- labTM package was used to perform the PCA via the singular value decomposition (Golub and Reinsch, 1970). Fig. A2. Correlation between intensity and image levels along the coal quarry profile. Also this image shows great differences respect to the cases of volcanic zones. Miscellanea 9-03-2009 14:42 Pagina 649 650 A. Pesci, G. Teza and G. Ventura Input vectors were multiplied by a matrix whose rows consist of the eigenvectors of the input covariance matrix, producing transformed vectors. Clearly, all the transformed vectors, in particular the ones characterized by the higher variances, can contain information extracted from all the original input vectors. For a given portion of the investigated surface, the RGB image and the intensity data can be considered. After registration on a common reference frame, the original data were interpolated to provide two images having ex- actly the same size. The RGB image is represented by three N-by-M matrices and the intensity data by one N- by-M matrix. Each of these matrices is transformed into a row vectors having NM length. If an RGB and an in- tensity image are considered, a 4-by-NM matrix is therefore built. Thanks to PCA, the real color information, the relations between colors and intensity, as well as the implications of using the red component alone can be investigated. In particular, the following analyses were performed: i) PCA of the three components of the RGB image (three input vectors), ii) PCA of the R component and of intensity data (two input vectors), iii) PCA of the RGB and intensity data (four input vectors), and iv) PCA of the intensity data provided by TLS acquisition of a same area from two different viewpoints (two components). In all the cases, several variance-limits were considered. In the first case the RGB image was considered, without intensity data. Only a vector is obtained from the PCA if a 0.06 limit variance was considered, and this fact is expected since the previous analyses have highlighted that the three color components are strongly correlated. The results are shown in fig. B1. Fig. B1. Principal component analysis of the RGB image of a selected part in the B-zone: the principal compo- nents (a, b), a virtual image obtained choosing 0.06 variance (c), the initial RGB image (d). Miscellanea 9-03-2009 14:42 Pagina 650 Appendix C The PCA can be also used to check for intensity data reliability when the same area is acquired from two or more viewpoints, i.e. different distances and different geometrical conditions are considered. The angle of inci- dence affects the resulting intensity (Reshetyuk, 2006), but also the spot size and the surveyed area have to be considered. The surveyed volcanic surfaces are very corrugated with respect to the 5-10 cm illuminated element by the laser pulses. Therefore, no significant variations of the intensity data are expected. Figure C1 shows the 651 Remote sensing of volcanic terrains by terrestrial laser scanner: preliminary reflectance and RGB implications for studying Vesuvius crater (Italy) The results obtained in the second and third case are very similar, as expected. For this reason, only the results of the second analysis (R component and intensity) are reported here. If a 0.05 limit-variance is considered, two matrices are obtained (fig. B2a). They cannot be combined because the synthesis of the two outputs would be very confusing. On the other hand, the principal component with largest variance (0.3 is the chosen limit-vari- ance) contains all the information contained in both color and intensity image. All the intensity and red-compo- nent features are clearly visible, like the shadow in the right bottom of the image. Fig. B2. Principal component analysis of R channel of the RGB image and TLS-based intensity: original R chan- nel (a); intensity (b), principal component having the largest variance (c,d). Note that on this PC, which is the only output component if the 0.3 limit-variance is considered, contains information related to both the vectors, shows features that can be easily detected. Miscellanea 9-03-2009 14:42 Pagina 651 652 A. Pesci, G. Teza and G. Ventura results of PCA of the intensity patterns related to a same portion of the B-zone acquired from different view- points. The resulting image shows all the features related to both the input images. In digital image processing, the PCA can be performed in another way. Instead of the application to a set of vectors representing several registered images, this technique can be applied to one image only. Boundaries and regions in a single image can be therefore described. 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