Francesco Pirotti

State of the Art of Ground and Aerial Laser Scanning Technologies for High-Resolution Topography of the Earth Surface

Abstract Laser scanners have increased their efficiency exponentially when compared to state of the art ten years ago. More data can be acquired—and higher accuracy can be achieved—over longer ranges thanks to advancements in sensor technology. The goal of this review is to present state of the art of terrestrial and aerial laser scanner surveys with a critical discussion over quality, which is a very important aspect for high-resolution topography.

A Particle Filter for Smartphone-Based Indoor Pedestrian Navigation

This paper considers the problem of indoor navigation by means of low-cost mobile devices. The required accuracy, the low reliability of low-cost sensor measurements and the typical unavailability of the GPS signal make indoor navigation a challenging problem. In this paper, a particle filtering approach is presented in order to obtain good navigation performance in an indoor environment: the proposed method is based on the integration of information provided by the inertial navigation system measurements, the radio signal strength of a standard wireless network and of the geometrical information of the building. In order to make the system as simple as possible from the user’s point of view, sensors are assumed to be uncalibrated at the beginning of the navigation, and an auto-calibration procedure of the magnetic sensor is performed to improve the system performance: the proposed calibration procedure is performed during regular user’s motion (no specific work is required). The navigation accuracy achievable with the proposed method and the results of the auto-calibration procedure are evaluated by means of a set of tests carried out in a university building.

Collaborative Web-GIS Design: A Case Study for Road Risk Analysis and Monitoring

This article presents a methodology for designing a WebGIS framework intended for automatically analyzing spatial data and updating statistics of interest with new information inserted daily by multiple users via a Web portal. A practical example is used on vehicle accident data for assessing risk in specific road segments. Two main blocks integrated together will be described: the collaborative block and the data-analysis block. The former gives end-users computer-aided tools to view, insert, modify and manage data related to accidents and traffic monitoring sensors, whereas the latter is developed to automatically analyze the accident data coming from users collaboration. Because different agencies can survey accident sites, a collaborative environment is necessary – and a Web-based solution is ideal – for permitting multi-user access and data insertion. A centralized approach to process the data in real time is described in all its components. Server-side Structured Query Language functions optimize performance by using dedicated libraries for spatial processing and re-structuring the attributes associated with elements which are consequently re-classified for correct color-scaling. The end-product is a system that provides a seamless integration of front-end tools for user collaboration and back-end tools to update accident risk statistics in real time and provide them to stakeholders.

Using lidar data to analyse sinkhole characteristics relevant for understory vegetation under forest cover-case study of a high karst area in the dinaric mountains.

In this article, we investigate the potential for detection and characterization of sinkholes under dense forest cover by using airborne laser scanning data. Laser pulse returns from the ground provide important data for the estimation of digital elevation model (DEM), which can be used for further processing. The main objectives of this study were to map and determine the geomorphometric characteristics of a large number of sinkholes and to investigate the correlations between geomorphology and vegetation in areas with such characteristics. The selected study area has very low anthropogenic influences and is particularly suitable for studying undisturbed karst sinkholes. The information extracted from this study regarding the shapes and depths of sinkholes show significant directionality for both orientation of sinkholes and their distribution over the area. Furthermore, significant differences in vegetation diversity and composition occur inside and outside the sinkholes, which indicates their presence has important ecological impacts.

Small Footprint Full-Waveform Metrics Contribution to the Prediction of Biomass in Tropical Forests

We tested metrics from full-waveform (FW) LiDAR (light detection and ranging) as predictors for forest basal area (BA) and aboveground biomass (AGB), in a tropical moist forest. Three levels of metrics are tested: (i) peak-level, based on each return echo; (ii) pulse-level, based on the whole return signal from each emitted pulse; and (iii) plot-level, simulating a large footprint LiDAR dataset. Several of the tested metrics have significant correlation, with two predictors, found by stepwise regression, in particular: median distribution of the height above ground (nZmedian) and fifth percentile of total pulse return intensity (i_tot5th). The former contained the most information and explained 58% and 62% of the variance in AGB and BA values; stepwise regression left us with two and four predictors, respectively, explaining 65% and 79% of the variance. For BA, the predictors were standard deviation, median and fifth percentile of total return pulse intensity (i_totstdDev, i_totmedian and i_tot5th) and nZmedian, whereas for AGB, only the last two were used. The plot-based metric showed that the median height of echo count (HOMTC) performs best, with very similar results as nZmedian, as expected. Cross-validation allowed the analysis of residuals and model robustness. We discuss our results considering our specific case scenario of a complex forest structure with a high degree of variability in terms of biomass.

Low-Cost MEMS Sensors and Vision System for Motion and Position Estimation of a Scooter

The possibility to identify with significant accuracy the position of a vehicle in a mapping reference frame for driving directions and best-route analysis is a topic which is attracting a lot of interest from the research and development sector. To reach the objective of accurate vehicle positioning and integrate response events, it is necessary to estimate position, orientation and velocity of the system with high measurement rates. In this work we test a system which uses low-cost sensors, based on Micro Electro-Mechanical Systems (MEMS) technology, coupled with information derived from a video camera placed on a two-wheel motor vehicle (scooter). In comparison to a four-wheel vehicle; the dynamics of a two-wheel vehicle feature a higher level of complexity given that more degrees of freedom must be taken into account. For example a motorcycle can twist sideways; thus generating a roll angle. A slight pitch angle has to be considered as well; since wheel suspensions have a higher degree of motion compared to four-wheel motor vehicles. In this paper we present a method for the accurate reconstruction of the trajectory of a “Vespa” scooter; which can be used as alternative to the “classical” approach based on GPS/INS sensor integration. Position and orientation of the scooter are obtained by integrating MEMS-based orientation sensor data with digital images through a cascade of a Kalman filter and a Bayesian particle filter.

Evaluation of the dynamic processes of a landslide with laser scanners and Bayesian methods

This paper deals with the study of the dynamics of a landslide from two different but complementary point of views. The landslide is situated within the Miozza basin, an area of approximately 10.7 km2 located in the Alpine region of Carnia (Italy). In the first part of the paper, the macro-scale analysis of volumetric changes occurred after the reactivation of landslide in 2004 is addressed by using a two-epoch laser scanning surveys from airborne (ALS) and terrestrial (TLS) platforms. airborne laser scanning (ALS) data were collected in 2003 (before reactivation of the phenomenon) with an ALTM 3033 OPTECH sensor while terrestrial laser scanning (TLS) measurements were acquired in 2008 with a Riegl LMS-Z620. The second part of the paper deals with the study of dynamic processes of the landslide at micro-scale. To this aim, a global navigation satellite system (GNSS)-based monitoring network is analysed using a statistical approach to discriminate between measurement noise and possible actual displacements. This task is accomplished using both “classical” statistical testing and a Bayesian approach. The second method has been employed to verify some apparent vertical displacements detected by the classical test. As regards the first topic of the paper, achieved results show that long-range TLS instruments can be profitably used in mountain areas to provide high-resolution digital terrain models (DTMs) with superior quality and detail with respect to aerial light detection and ranging data only, even in areas with very low accessibility. Moreover, ALS- and TLS-derived DTMs can be combined each other in order to fill gaps in ALS data, mainly due to the complexity of terrain morphology, and to perform quite accurate calculations of volume changes due to landslide phenomenon. Finally, the outcomes of the application of Bayesian inference demonstrate the effectiveness of this method to better detect statistically significant displacements of a GNSS monitoring network points. However, the application of this method in the geodetic field requires the identification of a preferring direction of displacements, what is not always feasible in advance.

Potential of ALOS2 and NDVI to estimate forest above-ground biomass, and comparison with lidar-derived estimates

Remote sensing supports carbon estimation, allowing the upscaling of field measurements to large extents. Lidar is considered the premier instrument to estimate above ground biomass, but data are expensive and collected on-demand, with limited spatial and temporal coverage. The previous JERS and ALOS SAR satellites data were extensively employed to model forest biomass, with literature suggesting signal saturation at low-moderate biomass values, and an influence of plot size on estimates accuracy. The ALOS2 continuity mission since May 2014 produces data with improved features with respect to the former ALOS, such as increased spatial resolution and reduced revisit time. We used ALOS2 backscatter data, testing also the integration with additional features (SAR textures and NDVI from Landsat 8 data) together with ground truth, to model and map above ground biomass in two mixed forest sites: Tahoe (California) and Asiago (Alps). While texture was useful to improve the model performance, the best model was obtained using joined SAR and NDVI (R2 equal to 0.66). In this model, only a slight saturation was observed, at higher levels than what usually reported in literature for SAR; the trend requires further investigation but the model confirmed the complementarity of optical and SAR datatypes. For comparison purposes, we also generated a biomass map for Asiago using lidar data, and considered a previous lidar-based study for Tahoe; in these areas, the observed R2 were 0.92 for Tahoe and 0.75 for Asiago, respectively. The quantitative comparison of the carbon stocks obtained with the two methods allows discussion of sensor suitability. The range of local variation captured by lidar is higher than those by SAR and NDVI, with the latter showing overestimation. However, this overestimation is very limited for one of the study areas, suggesting that when the purpose is the overall quantification of the stored carbon, especially in areas with high carbon density, satellite data with lower cost and broad coverage can be as effective as lidar.

Toward the use of smartphones for mobile mapping

Abstract This paper considers the use of a low cost mobile device in order to develop a mobile mapping system (MMS), which exploits only sensors embedded in the device. The goal is to make this MMS usable and reliable even in difficult environments (e.g. emergency conditions, when also WiFi connection might not work). For this aim, a navigation system able to deal with the unavailability of the GNSS (e.g. indoors) is proposed first. Positioning is achieved by a pedestrian dead reckoning approach, i.e. a specific particle filter has been designed to enable good position estimations by a small number of particles (e.g. 100). This specific characteristic enables its real time use on the standard mobile devices. Then, 3D reconstruction of the scene can be achieved by processing multiple images acquired with the standard camera embedded in the device. As most of the vision-based 3D reconstruction systems are recently proposed in the literature, this work considers the use of structure from motion to estimate the geometrical structure of the scene. The detail level of the reconstructed scene is clearly related to the number of images processed by the reconstruction system. However, the execution of a 3D reconstruction algorithm on a mobile device imposes several restrictions due to the limited amount of available energy and computing power. This consideration motivates the search for new methods to obtain similar results with less computational cost. This paper proposes a novel method for feature matching, which allows increasing the number of correctly matched features between two images according to our simulations and can make the matching process more robust.

Preface to the special issue: the role of geomatics in hydrogeological risk

In accordance with recent studies, most of the observed natural hazards throughout the globe are related to the dynamics of hydrological variability. This determines the fundamental importance of studies related to hydrogeological risk assessment, in terms of both prevention and mitigation of damages; science shall provide the modelling and forecasting tools in order to support the management of natural phenomena. Geomatic technologies have a leading role in this context, as they model the physical elements in the earths surface, their dynamics in time and space, and the causes of their modifications. The main aim of this special issue is to provide a review of the state-of-the-art of geomatic technologies applied to landslides and flooding and to give certain insights on new ideas and future perspectives on these themes. The contributions presented in this issue were presented at the workshop “The Role of Geomatics in Hydrogeological Risk” held in Padova, Italy, where 82% of the municipalities are subject to a degree of hydrogeological risk and where several natural disasters occurred in the past years, which made the workshop location particularly well suited and makes this special issue significant.