Dr.Tomas Fernandez
Professor - Cartography, GIS and Remote Sensing
University of Jaen
Spain

Biography
Born in 1967 in Granada (Spain).
Married, two daughters, I currently live in Jaén (Spain).
Degree in Geology in 1990 and PhD in Geology in 2001 at the University of Granada.
Professor of University of Jaen since 1995 in Cartography, GIS and Remote Sensing.
Director of the Department of Cartographic Engineering, Geodesy and Photogrammetry, University of Jaen, since 2007.
Research on Geomatics applied to natural hazards, specifically landslides.


Abstract
The Use of Geomatics Techniques for the Prevention and Management of Landslides

In this paper we present a proposal for integrated use of different geomatics techniques to analyse landslides with a view to preventing, mitigating and managing the risks derived of their occurrence. First there are data capture techniques that must be multi-scale and multi-temporal. Multi-scale data allow integrate the appropriate techniques to regional studies (remote sensing), local studies (aerial photogrammetry and UAVs) and detail studies (GNSS, survey and terrestrial laser scanner, TLS). Multitemporal data required to repeat the data acquisition (both updating or using historical data), which is possible with the aforementioned techniques along with the use of the so-called collaborative mapping , very useful for data updating affecting goods in urban areas or infrastructures. From multi-scale and multi-temporal data integrated in a geographical information system (GIS), it is possible to make inventory maps, which together with the mapping of determinant factors obtained explicitly or from information stored in spatial data infrastructures (SDI), allowing GIS analysis to elaborate susceptibility maps (spatial likelihood), danger (spatiotemporal likelihood) and, in some cases, vulnerability and risk maps. All these maps are an important tool in landslide risk prediction, and consequently, in its prevention and mitigation, to what is required the adoption of other measures. Meanwhile, the implementation of web sensors or wireless sensor networks (WSN) in high-risk sectors, which combine high hazard, vulnerability and exposure (urban zones and infrastructures), along with the implementation of platforms for collaborative and crowd sourcing mapping can become useful tools in early warning systems and management of risks arising from landslides.