Developing Advanced Photogrammetric Methods for Automated Rockfall Monitoring

Abstract

In recent years, photogrammetric models have become a widely used tool in the field of geosciences thanks to their ability to reproduce natural surfaces. As an alternative to other systems such as LiDAR (Light Detection and Ranging), photogrammetry makes it possible to obtain 3D points clouds at a lower cost and with a lower learning curve. This combination has allowed the democratisation of this 3D model creation strategy. On the other hand, rockfalls are one of the geological phenomena that represent a risk for society. It is the most common natural phenomenon in mountainous areas and, given its great speed, its hazard is very high.

This doctoral thesis deals with the creation of photogrammetric systems and processing algorithms for the automatic monitoring of rockfalls. To this end, 3 fixed camera photogrammetric systems were designed and installed in 2 study areas. In addition, 3 different workflows have been developed, two of which are aimed at obtaining comparisons of higher quality using photogrammetric models and the other focused on automating the entire monitoring process with the aim of obtaining automatic monitoring systems of low temporal frequency.

The photogrammetric RasPi system has been designed and installed in the study area of Puigcercós (Catalonia). This very low-cost system has been designed using Raspberry cameras. Despite being a very low-cost and low-resolution system, the results obtained demonstrate its ability to identify rockfalls and pre-failure deformation. The HRCam photogrammetric system has also been designed and installed in the Puigcercós study area. This system uses commercial cameras and more complex control systems. With this system, higher quality models have been obtained that enable better monitoring of rockfalls. Finally, the DSLR system has been designed similarly to the HRCam system but has been installed in a real risk area in the Tajo de San Pedro in the Alhambra (Andalusia). This system has been used to constantly monitor the rockfalls affecting this escarpment.

In order to obtain 3D comparisons with the highest possible quality, two workflows have been developed. The first, called PCStacking, consists of stacking 3D models in order to calculate the median of the Z coordinates of each point to generate a new averaged point cloud. This thesis shows the application of the algorithm both with ad hoc created synthetic point clouds and with real point clouds. In both cases, the 25th and 75th percentile errors of the 3D comparisons were reduced from 3.2 cm to 1.4 cm in synthetic tests and from 1.5 cm to 0.5 cm in real conditions.

The second workflow that has been developed is called MEMI (Multi-Epoch and Multi-Imagery). This workflow is capable of obtaining photogrammetric comparisons with a higher quality than those obtained with the classical workflow. The redundant use of images from the two periods to be compared reduces the error to a factor of 2 compared to the classical approach, yielding a standard deviation of the comparison of 3D models of 1.5 cm.

Finally, the last workflow presented in this thesis is an update and an automation of the method for detecting rockfalls from point-clouds carried out by the RISKNAT research group. The update has been carried out with two objectives in mind. The first is to transfer the entire working method to free licence (both language and programming), and the second is to include in the processing the new algorithms and improvements that have recently been developed. The automation of the method has been performed to cope with the large amount of data generated by photogrammetric systems. It consists of automating all the processes, which means that everything from the capture of the image in the field to the obtention of the rockfalls is performed automatically. This automation poses important challenges, which, although not completely solved, are addressed in this thesis.

Thanks to the creation of photogrammetric systems, 3D model improvement algorithms and automation of the rockfall identification workflow, this doctoral thesis presents a solid and innovative proposal in the field of low-cost automatic monitoring. The creation of these systems and algorithms constitutes a further step in the unimpeded expansion of monitoring and warning systems, whose ultimate goal is to enable us to live in a safer world and to build more resilient societies to deal with geological hazards.

En els darrers anys, els models fotogramètrics s’han convertit en una eina molt utilitzada en l’àmbit de les geociències gràcies a la seva capacitat per reproduir superfícies naturals. Com a alternativa a altres sistemes com el LiDAR (Light Detection and Ranging), la fotogrametria permet obtenir núvols de punts 3D a un cost més baix i amb una corba d’aprenentatge menor. Per altra banda, els despreniments de roca són un dels fenòmens geològics que representen un risc per al conjunt de la societat.

Aquesta tesi doctoral aborda la creació de sistemes fotogramètrics i algoritmes de processat per al monitoratge automàtic de despreniments de roca. Per una banda, s’ha dissenyat un sistema fotogramètric de molt baix cost fent servir càmeres Raspberry Pi, anomenat RasPi System, instal·lat a la zona d’estudi de Puigcercós (Catalunya). Per altra banda, s’ha dissenyat un sistema fotogramètric d’alta resolució anomenat HRCam també instal·lat a la zona d’estudi de Puigcercós. Finalment, s’ha dissenyat un tercer sistema fotogramètric de manera similar al sistema HRCam anomenat DSLR, instal·lat en una zona de risc real al Tajo de San Pedro de l’Alhambra (Andalusia).

Per obtenir comparacions 3D amb la màxima qualitat possible, s’han desenvolupat dos fluxos de treball. El primer, anomenat PCStacking consisteix a realitzar un apilament de models 3D per tal de calcular la mediana de les coordenades Z de cada punt. El segon flux de treball que s’ha desenvolupat s’anomena MEMI (Multi-Epoch and Multi-Imagery). Aquest flux de treball és capaç d’obtenir comparacions fotogramètriques amb una qualitat superior a les que s’obtenen amb el flux de treball clàssic.

Finalment, el darrer flux de treball que es presenta en aquesta tesi és una actualització i una automatització del mètode de detecció de despreniments de roca del grup de recerca RISKNAT. L’actualització s’ha dut a terme perseguint dos objectius. El primer, traspassar tot el mètode de treball a llicència lliure (tant llenguatge com programari) i el segon, incloure els nous algoritmes i millores desenvolupats en aquesta tesi en el processat fotogramètric

Gràcies a la creació dels sistemes fotogramètrics, algoritmes de millora de models 3D i l’automatització en la identificació de despreniments aquesta tesi doctoral presenta una proposta sòlida i innovadora en el camp del monitoratge automàtic de baix cost. La creació d’aquests sistemes i algoritmes representen un avenç important en l’expansió dels sistemes de monitoratge i alerta que tenen com a objectiu final permetre'ns viure en un món més segur i construir societats més resilients enfront dels riscos geològics.