Marco Scaioni

Remote Sensing for Landslide Investigations: An Overview of Recent Achievements and Perspectives

Landslides represent major natural hazards, which cause every year significant loss of lives and damages to buildings, properties and lifelines. In the last decades, a significant increase in landslide frequency took place, in concomitance to climate change and the expansion of urbanized areas. Remote sensing techniques represent a powerful tool for landslide investigation: applications are traditionally divided into three main classes, although this subdivision has some limitations and borders are sometimes fuzzy. The first class comprehends techniques for landslide recognition, i.e., the mapping of past or active slope failures. The second regards landslide monitoring, which entails both ground deformation measurement and the analysis of any other changes along time (e.g., land use, vegetation cover). The third class groups methods for landslide hazard analysis and forecasting. The aim of this paper is to give an overview on the applications of remote-sensing techniques for the three categories of landslide investigations, focusing on the achievements of the last decade, being that previous studies have already been exhaustively reviewed in the existing literature. At the end of the paper, a new classification of remote-sensing techniques that may be pertinently adopted for investigating specific typologies of soil and rock slope failures is proposed.

Photogrammetric techniques for monitoring tunnel deformation

This paper presents two innovative methods for tunnel monitoring that are based on digital photogrammetry. Both have been conceived to speed up operations that are currently accomplished by using engineering geodesy techniques and instruments. On the same time, proposed solutions are cheap and affordable. The first one is aimed at measuring relative deformations of transversal cross-section of tunnels. Some special targets are placed on the tunnel vault and their coordinates are measured by means of a small photogrammetric block made up of four images. A wire is used to setup the scale and to make all measurements comparable overtime. The second method can be applied for the measurement of vertical deformations along the longitudinal profile of tunnels. A new image-based approach called ‘photogrammetric levelling’ is discussed here, which is based on the metric rectification of each single image depicting a couple of special rods to be hung on levelling benchmarks. This technique can be used to replace traditional optical and digital level instruments. Both applications can be carried out by using a calibrated amateur camera. Some experiments in controlled and real environments allowed assessing performances and limitations of these techniques for operational surveys in tunnel monitoring.

Automatic Co-registration of Satellite Time Series via Least Squares Adjustment

Abstract Image-to-image co-registration is a fundamental task for data processing of satellite time series. This paper presents a new multi-image co-registration algorithm that simultaneously uses multi-image corresponding points in the whole multi-temporal sequence. Image co-registration parameters are then computed on the basis of a global adjustment. The implemented algorithm provides sub-pixel accuracy similar to that achievable with interactive measurements, but it is also able to register images which do not directly share corresponding features with the reference. Results for a (i) synthetic dataset and a (ii) real complex multi-temporal series made up of 13 Landsat images collected over a period of 30 years are illustrated and discussed. The obtained results showed that the implemented algorithm is atmospheric resistant and quite robust against land cover changes, cloud cover, and snow.

Fusion of aerial and satellite imagery over the city of Venezia

A large variety of satellite images are available for almost every land of the world. Thanks to the high resolution imagery, also urban areas may take advantage of this abundance of data. In fact, studying and monitoring phenomena concerning these areas require a high accuracy of details, which is attainable. However, any applications of this kind involves an accurate georeferencing of the images themselves to a given geodetic reference system. In this paper, a methodology for automatic high resolution satellite image georeferencing is proposed, taking advantage of existing digital orthophoto-maps and photo-planes derived from aerial photogrammetry. A case study applied to the historical urban area of Venezia is described.

Monitoring Riverbank Erosion in Mountain Catchments Using Terrestrial Laser Scanning

Sediment yield is a key factor in river basins management due to the various and adverse consequences that erosion and sediment transport in rivers may have on the environment. Although various contributions can be found in the literature about sediment yield modeling and bank erosion monitoring, the link between weather conditions, river flow rate and bank erosion remains scarcely known. Thus, a basin scale assessment of sediment yield due to riverbank erosion is an objective hard to be reached. In order to enhance the current knowledge in this field, a monitoring method based on high resolution 3D model reconstruction of riverbanks, surveyed by multi-temporal terrestrial laser scanning, was applied to four banks in Val Tartano, Northern Italy. Six data acquisitions over one year were taken, with the aim to better understand the erosion processes and their triggering factors by means of more frequent observations compared to usual annual campaigns. The objective of the research is to address three key questions concerning bank erosion: “how” erosion happens, “when” during the year and “how much” sediment is eroded. The method proved to be effective and able to measure both eroded and deposited volume in the surveyed area. Finally an attempt to extrapolate basin scale volume for bank erosion is presented.

Feature-constrained registration of building point clouds acquired by terrestrial and airborne laser scanners

Abstract Point-cloud registration is usually accomplished on the basis of several corresponding features to compute the parameters of the transformation model. However, common point features are difficult to select because airborne laser scanner (ALS) and terrestrial laser scanner (TLS) point clouds of the same object have be aligned due to the different sensing positions and sampling modes. Taking building profile features as objects, a registration method based on feature constraints is proposed here. The standard six-parameter rigid-body transformation adopted for alignment of laser scans is replaced by a two-step transformation: horizontal registration based on a two-dimensional similarity transformation and vertical registration based on a simple vertical shift. First, the feature-line and feature-plane equation parameters are obtained from both the airborne and terrestrial point clouds. Second, the plane transformation parameters are computed after projecting the extracted features onto a horizontal reference plane. Finally, the elevation transformation parameter is calculated by comparing the heights of flat features. The ALS and TLS datasets of two buildings (Shanghai Pudong International Conference Center and Shanghai Ocean Aquarium, China) were used to evaluate the robustness and accuracy. The results show that the proposed feature-constrained method works well for registration between two datasets. Five checkpoints and one overlap zone for the Pudong International Conference Center were selected to evaluate the accuracy and resulted in accuracies of 0.15 to 0.5 m in the horizontal direction and 0.20 m in the vertical direction.

Remote Sensing for Landslide Investigations: From Research into Practice

The relevant impact [1] that landslide geo-hazards may have on society in terms of human lives and economic losses, has resulted in great efforts to develop sustainable solutions to deal with their prediction and mitigation. To date, several aspects have been investigated involving geological and geo-statistical analysis, geotechnical modeling, design of effective mitigation and protection structures, and sensor development [2]. [...]

Some applications of 2-D and 3-D photogrammetry during laboratory experiments for hydrogeological risk assessment

Scaled-down flume tests are largely used to support investigations for the assessment of hydrogeological risk. Achieved outcomes can be integrated to numerical analyses for the study of unstable slope collapse, debris transport, and hydrological models in general. In the set-up of such simulation platforms, a relevant role has to be given to the Spatial Sensor Network (SSN) which is in charge of collecting geo-referenced, quantitative information during experiments. Photogrammetry (including 3-D imaging sensors) can play an important role in SSN because of its capability of collecting information covering wide surfaces without any contact. The aim of this paper is to give an overview and some examples of the potential of photogrammetry in hydrogeological simulation experiments. After a general introduction on a few preliminary issues (sensors, calibration, ground reference, usage of imaging or ranging sensors), potential applications are classified into 2-D and 3-D categories. Examples are focused on a scaled-down landslide simulation platform, which has been developed at Tongji University (Shanghai, P.R. China).

Model test study on monitoring dynamic process of slope failure through spatial sensor network

Landslides represent a major type of natural hazards worldwide. For development of risk mitigation capabilities, an effective system for monitoring dynamic process of slope failure, capable of gathering spatially distributed information before, during and after a landslide occurrence at real-time manner is essential. A spatial sensor network (SSN), which integrates the real-time communication infrastructure and observations from in situ sensors and remote sensing platforms, offers an efficient and effective approach for such purpose. In this paper, a SSN-based landslide monitoring system was designed and evaluated through a model test study conducted at Tongji University, China. This system, MUNOLD (MUlti-Sensor Network for Observing Landslide Disaster), has been designed as a comprehensive monitoring framework, including sensor observations, multi-channel wireless communication, remote data storage, visualization, data processing and data analysis. In this model test study, initial experimentation demonstrated the capabilities of the MUNOLD system for collecting real-time information about the dynamic process and propagation of slope failure. Innovatively, generated from the high-speed stereo images, the sequential surface deformation vector field can be created and may exhibit the dynamic process during the extremely critical and short period of the slope failure. After this model test study, the MUNOLD system is going to be further improved and extended in a landslide prone region in Sichuan Province, China.

Accurate 3D surface measurement of mountain slopes through a fully automated image-based technique

In this paper an automated procedure for surface reconstruction that can be used for surveying and monitoring rock and ground slopes is presented. This method has been developed for geological and engineering applications, where accuracy and completeness are factors of primary importance for the final 3D model, which must provide a detailed metric survey and not only a visual reconstruction of the scene. The proposed procedure integrates two image matching techniques. The first one is used to automatically extract a set of tie points that are needed for computing the exterior orientation parameters of all images through a photogrammetric bundle adjustment. Such tie oints are also exploited to obtain a preliminary seed model that is then enriched based on Multi-photo Least Squares Matching. During this second stage, the surface model is improved in terms of point density and accuracy. Different strategies were implemented to successfully combine both techniques, along with some new improvements. The presented procedure has been tested in two different applications: geometric modelling of rock cliffs and evaluation of weathering of a ground slope. In both cases the obtained results presented accuracy sufficient for geological investigation. Moreover, outcomes were comparable to the ones from laser scanning surveying and other photogrammetric implementations.