All the research described in the previous sections is devoted to perform a step forward the state-of-the-art of surveying methods and procedures.
SMART CITIES: Accessibility maps
Accessible cities with accessible services are an old claim of people with reduced mobility. But this demand is still far away of becoming a reality as lot of work is required to be done yet. First step towards accessible cities is to know about real situation of the cities and its pavement infrastructure. Detailed maps or databases on street slopes, access to sidewalks, mobility in public parks and gardens, etc. are required. In this paper, we propose to use smartphone based photogrammetric point clouds, as a starting point to create accessible maps or databases. Our research analyses the performance of these point clouds and the complexity of the image acquisition procedure required to obtain them. The research indicates, through two test cases, that smartphone technology is an economical and feasible solution to get the required information, which is quite often seek by city planners to generate accessible maps. The proposed approach paves the way to generate, in a near term, accessibility maps through the use of point clouds derived from crowdsourced smartphone imagery.
E. Angelats, M. E. Parés, P. Kumar, Feasibility of smartphone based photogrammetric point clouds for the generation of accesibility maps , in Proceedings of the International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XLII-2, 2018. ISPRS TC II Mid-term Symposium “Towards Photogrammetry 2020″, 4–7 June 2018, Riva del Garda (Italy).
BIOSYSTEMS & AGRI-FOOD
One of the most recent application of our work is related to the application of remote sensing techniques to aquaculture. In join collaboration with UPC and IRTA we studied the potential of clorophyll-a estimation from Sentinel 2 imagery to monitor the distribution and amount of phytoplankton in Ebro Delta’s bay.
Figure. Chl-a maps. Time series of Alfacs (left column) and Fangar (right column) bays. The seasons of winter and early spring spring are covered in: (a) 16 January 2017; (b) 25 Febrary 2017; (c-d) 17 March 2017; Black: rafts; Blue: freshwater discharge; Spatial scale: 4 km with divisions every 1 km. A mask to avoid interferences due to submerged macrophytes and/or shallow waters (>2m) was used in each bay.
Soriano, J. “Caracterización de la dinámica espacial del fitoplancton en las bahías del delta del Ebro a partir de la estimación de la clorofila-a con Sentinel 2: Implicaciones para la miticultura” Supervisors: Eduard Angelats (CTTC), Margarita Fernández(IRTA), Lourdes Reig (UPC). September 2017.
NDVI in Indoor environments with low-cost imaging sensors
In this research, a NDVI point cloud generator tool based on low-cost active RGB-D sensor was developed. Taking advantage of currently available ROS point cloud generation tools and RGB-D sensor technology (like Microsoft Kinect), that includes an inbuilt active IR camera and a RGB camera, 3D NDVI maps can be quickly and easily generated for vegetation monitoring purposes. When using low-cost sensors for vegetation index estimation, it is necessary to apply a rigorous methodology for extracting reliable information. In this paper, the methodology for NDVI generation using a low-cost sensor as well as experiments to evaluate its performance is presented. The experiments performed show that it is possible to obtain a reliable NDVI point cloud from a Kinect V2.
Figure. NDVI images of a set of leaves in an indoor environment.
D. Calero, E. Fernández, M. E. Parés, E. Angelats, NDVI point cloud generator tool using low-cost RGB-D sensor , in Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (iROS2018), 1-5 October 2018, Madrid (Spain).
CIVIL PROTECTION: Indoor mapping and Personnel Tracking
The research carried out at our group aims to be a step forward in improving methods and procedures for indoor navigation and mapping. Currently, the generation of this information is a technological trending topic. We have low quality solutions at very reasonable cost (few hundred euros), but good performance positioning and mapping in interiors is still expensive (tens of thousands of euros) and requires very long acquisition campaigns.
We are working in a new low-cost modular, multi-sensor acquisition and processing platform. The platform uses the newest Commercial-of-the-Shelf sensors and process data under geodetic criteria (redundancy, heterogeneity and rigour).
Latest relevant publications:
E. Angelats, J. A. Navarro, A concept for fast indoor mapping and positioning in post-disaster scenarios , in Proceedings of the 4th International Conference on Geographical Information Systems Theory, Applications and Management (GISTAM 2018), 17-19 March 2018, Funchal (Portugal).
E. Angelats, J. A. Navarro, Towards a fast, low-cost indoor mapping and positioning system for civil protection and emergency teams , in Proceedings of the International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XLII-2/W8, 2017. 5th International Workshop LowCost 3D – Sensors, Algorithms, Applications, 28–29 November 2017, Hamburg (Germany).
D. Calero, E. Fernández, M. E. Parés, Autonomous wheeled robot platform testbed for navigation and mapping using low-cost sensors , in Proceedings of the LowCost 3D 2017, 28-29 November 2017, Hamburg (Germany).
Chesa, M., “Autonomous Rover for Obstacle Avoidance”. Advisors: Calero, D. (CTTC), Casas, O. (UPC). July 2017.
Vukmirika, N., “Autonomous Rover for Indoor Localization”, Advisors: Fernández, E. (CTTC), Pino, D. (UPC), June 2017.
Figure. ARAS platform for indoor positioning and mapping.
SURVEYING: Road inspection
Road traffic safety is one of the key issue for policy makers and authorities, which is required to be addressed for enabling safe and comfortable movement of goods, people and services. The safety of road users may be affected by the existence and condition of road geometry and physical factors present along the route corridor. These factors are required to be located, measured, classified and recorded in a timely, cost effective manner in order to schedule their maintenance and proper management of the road networks. The use of Mobile Laser Scanning (MLS) system overcomes the limitations existing in current road safety inspection methods by enabling rapid and cost effective acquisition of accurate information about road and its infrastructure. The acquired 3D information facilitates the comprehensive monitoring and evaluation of road infrastructure elements to identify any risk elements along the route corridor.
The main objective of the research carried out in CTTC regarding this topic aims to develop a set of methodologies and algorithms to locate, classify and measure the road infrastructure elements and any deformation existing in them, based on 3D data acquired using MLS system.
Latest relevant publications:
P. Kumar, P. Lewis, C. P. McElhinney, P. Boguslawski, T. McCarthy, Snake energy analysis and results validation for a mobile laser scanning data based automated road edge extraction algorithm , IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol. 10, No. 2, pp. 763-773, February 2017, http://ieeexplore.ieee.org/document/7473830/.
P. Kumar, P. Lewis, T. McCarthy, The potential of active contour models in extracting road edges from mobile laser scanning data , Infrastructures, Vol. 2, No. 3, pp. 16, July 2017.