Barbara Theilen-Willige 1) 1) Technical University of Berlin, Institute of Applied Geosciences, Department of Hydrogeology and

Bureau of Applied Geoscientific Remote Sensing (BAGF), Birkenweg 2, D-78333 Stockach,, Germany, Email: Barbara.Theilen-Willige@t-online.de

ABSTRACT:

In the fields of awareness, preparedness and mitigation of natural hazards a multidisciplinary integration of different methods and data has the greatest potential for substantial progress. In the scope of this study the use of remote sensing and Geographic Information Systems (GIS) is examined as contribution to a multi-risk database in N-Venezuela, Central Italy and SW-Germany/NW-Switzerland. Satellite imageries and digital elevation data form the basic data stock, combined with other geodata. Digital image processing methods are used to enhance satellite data in order to contribute to the investigation of environmental conditions and of natural hazards. LANDSAT ETM imageries merged with digitally processed digital elevation data clearly indicate areas that might be prone by flooding in case of extreme weather events, or are susceptible to landslides or soil erosion. Subsurface structures (as fault and fracture zones) and local site conditions of potential influence on earthquake damage intensity can be partly derived by geomorphmetric analysis methods and the identification of linear tonal anomalies on the imageries. 1. INTRODUCTION This contribution addresses problems caused by extreme geologic processes and hazards as earthquakes or flooding. For monitoring hazards and for assessing risks data availability is crucial. GIS integrated satellite observations can help considerably to show vulnerable areas, enhance mapping, to improve the understanding of hazards and to detect risk areas for infrastructural facilities. The use of GIS integrated remote sensing data in the scope of environmental studies has been a continuous process taking place over the last decades [1]. Data from earth observing satellites have become a valuable supporting tool for natural hazard damage detection. Many international organizations like UNOSAT, Joint Research Centre (JRC/ EU), or ESA provide satellite based information in the Web. Earth observation satellites as LANDSAT, SPOT, IKONOS, QUICKBIRD, ERS, or ENVISAT with increasing capabilities in terms of spatial, temporal and spectral resolution allow a more efficient, reliable and affordable monitoring over time. Thus, remote sensing technology has become a fundamental input

for Geoinformation Systems (GIS), especially for Natural Hazard Information Systems. The design of a common GIS database structure - always open to new data - can greatly contribute to the homogenisation of methodologies and procedures of natural hazard risk management requiring an approach by integrating remote sensing data, geologic, geophysic, seismotectonic and topo-graphic data and catalogues of historical hazardous events. 2. APPROACH ENVISAT ASAR, ERS, LANDSAT ETM, and Digital Elevation (DEM) data derived by the Shuttle Radar Topography Mission (SRTM, 2000) were investigated in order to detect traces of past natural hazard events and to delineate areas of hazard susceptibility. Digital image processing methods used to enhance satellite radar and LANDSAT ETM imageries and to produce morphometric maps (such as hillshade, slope, minimum and maximum curvature maps) based on SRTM DEM data, contribute to the detection of morphologic traces that might be related to past hazardous events. These maps combined with various geodata in a GIS environment allow the delineation of regions that might be prone to landslides, flooding, soil erosion, etc. This could contribute to the detection of future potential hazard source regions. Fig.2 shows how the causal factors for natural hazards are extracted systematically: From slope gradient maps are extracted those areas with the steepest slopes and from curvature maps the areas with the highest curvature as these are susceptible to land-slides, from height maps the lowest areas susceptible to flooding, from flow accumulations maps areas with highest flow accumulations. Height maps help to search for topographic depressions, which are often linked with water accumulations and wetlands. Linear morphologic features (lineaments) visible on hillshade maps and LANDSAT imageries are often related to traces of faults and fractures in the subsurface. This can be demonstrated by the examples of N-Venezuela, Central-Italy and SW-Germany / NW Switzerland. 3. EVALUATIONS OF REMOTE SENSING AND GIS DATA 3.1. Natural Hazard Site Detection in N-Venezuela

REMOTE SENSING AND GIS CONTRIBUTION TO NATURAL HAZARD RISK SITE DETECTION - DEMONSTRATED BY EXAMPLES

FROM N-VENEZUELA, CENTRAL ITALY AND SW-GERMANY / NW-SWITZERLAND

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Proc. ‘Envisat Symposium 2007’, Montreux, Switzerland 23–27 April 2007 (ESA SP-636, July 2007)

Figure 1. Remote sensing based spatial data base

Figure 2. Extraction of causal or preparatory factors influencing susceptibility to natural hazards North- Venezuela lies within the interaction zone of the Caribbean and South America plates and is being subjected to a stress field characterized by a NNW-SSE maximum horizontal stress and a ENE-WSW minimum horizontal stress (strike-slip regime). This stress tensor is responsible for present kinematics, seismicity and activity of sets of faults: east-west right-lateral faults, NW-SE right-lateral faults, NNW-SSE normal faults, north-south to NNE-SSW left-lateral faults and ENE-WSW reverse faults [2]. The Venezuelan Coast Ranges outline a major transfer zone between the westward-dipping subduction of the Atlantic oceanic lithosphere beneath the Lesser Antilles volcanic arc and the westward-dipping subduction of the South American continental lithospere beneath the Andes. At the surface this part is characterized by the occurrence of a major transform fault as the dextral, E-W-oriented El Pilar shear zone, 5 to10 km-width where seismicity occurs concentrated. The El Pilar Fault is located within an east-west trending topographic depression formed by a graben (Pliocene and early Pleistocene) and since then is subjected to right-lateral strike slip movement. The El Pilar fault is clearly visible on an overlay of SRTM DEM based hillshade and slope map (Fig.3 a and b) of the Paria peninsula / NE Venezuela. Based on the ENVISAT ASAR image of that area combined with SRTM derived morphometric maps a detailed lineament analysis

was carried out as shown in Fig.4. Northern Venezuela is often prone as well to flooding, landslides, debris flow and soil erosion due to intense precipitations. The coastal areas might be hit by tsunamis. Some factors influencing damage intensity during natural hazards can be derived systematically from remote sensing data as shown in Fig.5.

Figure 3 a. SRTM hillshade / convexity / height map overlay of Paria

Figure 3 b. SRTM hillshade / ENVISAT ASAR / height map overlay of Paria and lineament analysis Estimating the degree of earthquake damage due to local site conditions, including damage of second-dary effects is essential for damage mitigation planning. Therefore causal / preparatory factors influencing the intensity of seismic shock at the earth surface and earthquake induced secondary effects such as liquefaction or landslides is essential. Lowlands and depressions with high ground water tables usually show higher earthquake shock [3]. The fundamental phenomenon responsible for the amplification of motion over soft sediments as in depressions is the trapping of seismic waves due to the impedance contrast between sediments and underlying bedrock [5]. These areas can be easily visualized by height maps. Areas with steeper slopes susceptible to landslides can be derived from slope gradient maps. As there is a potential of rainstorms inducing flash floods, mudflows, debris flows and landslides in Northern Venezuela, these catastrophic events have to be considered in disaster preparedness. Debris flows and flash floods on alluvial fans inundated

coastal communities as in December 1999 [4]. Because most of the coastal zones consists of mountain fronts that rise abruptly from the Caribbean Sea, the alluvial fans are the only areas where slopes are not too steep to build. Rebuilding and reoccupation of these areas requires careful determination of potential hazard zones including tsunami hazard to avoid future loss of life and property. For tsunami risk site analysis it is very important to investigate very detailed the geomorphologic features that are obviously related to tsunami events such as coast-near ponds and lakes and the height level, see Fig.5.

Figure 5. Areas susceptible to tsunami flooding at the northern coast of Paria as derived from SRTM height map, ENVISAT ASAR and LANDSAT ETM overlay The occurrence of mass movements and soil erosion is influenced by the lack of vegetation. A classification of LANDSAT ETM data helps to detect those areas at upper hill slopes without vegetation cover (Fig.6). In Fig.7 some of the causal factors are summarized.

Figure 6. Deriving areas susceptible to soil erosion and mass movements from LANDSAT data 3.2. Local Site Conditions influencing Earth-quake Damage in Central Italy Another objective of this study was to investigate the potential of satellite data to contribute to the knowledge of the subsurface conditions in the earthquake prone areas of Central Italy.

Figure 7. Causal / preparatory factors influencing damage susceptibility as slope degree, groundwater level, larger fault zones, etc. In the Central Apennines three major structural domains can be recognized: the Umbria and Marche pelagic domains and the Lazio-Abruzzi carbonate platform. These zones are part of the axial belt of the Apennine chain, which is characterized by mainly NW-SE to N-S trending normal and oblique faults [5]. Satellite data, geologic and seismotec-tonic data from Central Italy were analyzed in order to contribute to a better understanding of processes influencing the damage intensity of stronger earthquakes and to microzonation maps. Linear features were mapped, integrated as layers into a GIS, and compared with geological and geophysical data. The overlay of ENVISAT ASAR data and SRTM based slope and hillshade maps clearly shows the structural pattern (Fig.8).

Figure 8. Fault zones visible on a ENVISAT ASAR, SRTM slope and hillshade map overlay As the topographic setting of an area makes an impact on earthquake damage intensity to a certain extent, it is necessary to analyse the geomorpho-logic conditions. Intermontane basins and depressions can be assumed to be exposed to a higher earthquake shock than the environment due to reflection and amplification of seismic waves [3]. Some of the factors influencing the susceptibility to natural hazards are summarized in Fig.9. Fig.9 shows the mapped lineaments and their density, combined with the presentation of areas with slope degrees of more than 20° and lowlands.

Figure 9. Areas prone to natural hazards Lowest area s- susceptible to flooding, steeper slope gradient areas and higher density of lineaments - susceptible to mass movements and soil erosion, intermontane basins, intersected by fault zones - susceptible to higher earthquake shock 3.3. Neotectonic Setting in SW Germany and NW Switzerland The geologic structure of Southwest Germany / Northern Switzerland is governed by the ongoing plate tectonic activity and geodynamic processes in the Alpine region which are accompanied by rela-tive motions between the Eurasian plate and the Adriatic promontory of the African plate [6]. Crustal convergence within the Alpine collision zone still is the driving force for the tectonic structures in the test site causing compression and a block-wise tectonic structure. Traces of neotectonic movements are clearly detectable on the satellite imageries: Evidence for neotectonism is indicated by geomorphologic features (distortion of alluvial fans, linear scarps, etc.), especially by the drainage pattern (bending and off-setting of river segments). Examples for traces of neotectonic activity are shown from the alpine collision zone into the foreland south of Lake Zuerich. by Envisat ASAR and LANDSAT scenes, merged with the SRTM hillshade map. These traces of orogenic crustal fores-hortening from the Alpine collision zone can be detected by parallel and linear SW-NEW oriented, hills and depressions (Fig.10,11,12).

Figure 10. Perspective view of the ENVISAT ASAR image from the Alpine foreland

Figure 11 a . Valleys and depressions parallel to the Alpine compression from SE visible on the ASAR image

Figure 11 b. Valleys and depressions parallel to the Alpine compression visible on the LANDSAT image due to the drainage pattern

Figure 12. Factors influencing susceptibility to natural hazards: Areas with slope degree > 20° and high curvatures – susceptible to mass movements, unconsolidated sedimentary covers and higher groundwater tables in depressions and broader valleys – susceptible to soil amplification and liquefaction in case of stronger earthquakes, heights below 410 m – susceptible to flooding, high density of tectonic and structural features - neotectonic movements (?)

Landslides triggered by seismic shock are documented: During the 16.11.1911 – earthquake event landslides in areas with existing slope instabilities demonstrated the existence of potentially secondary effects [7]. The glaciations of the Quaternary period were of great importance in the sculpturing of the Alps and Alpine foreland [8]. Vast ice masses moved through the valleys, transforming them into deep troughs with steep walls leaving glacial deposits. Glacial rebound and glacial erosion of the slope toe play an important role for slope instability as in the Lake Constance area. Most of the landslides occur in those valleys covered by large glaciers during the Pleistocene. In the scope of this study remote sensing data and further geodata from the Lake Constance area at the south-western part of Germany were used as example for mapping causal factors related to the occurrence of landslides such as surface morphology, structural and lithological properties, land cover, and at least, temporal changes of these factors (Fig.13).

Figure 13. Causal factors influencing landslide susceptibility in the Western Lake Constance area Tectonic, lithologic and earthquake zonation data: Landesamt für Geologie, Rohstoffe und Bergbau, Baden-Württemberg(1998) 4. CONCLUSIONS

Satellite observations can help considerably to show vulnerable areas, enhance mapping, and ameliorate the understanding of hazards and their complex interactions. The main advantages to be outlined refer to the spatially extending information collection, data base creation and the monitoring capabilities. Thus, the path of sytematic integration of satellite data analysis results into hazard zone mapping is demonstrated that can be easily adopted for other areas. Acknowledments The ERS and ENVISAT satellite radar data were investigated in the scope of the ENVISAT Mission (AO ID AEO.211). The author thanks ESA /ESRIN for providing ENVISAT ASAR and ERS data of Northeast Venezuela, Central Italy and SW-Germany free of charge being part of the support as Principle Investigator. The support of the European Community, Project

funded by the European Community under the ‘Energy, Environment and Sustainable Development Programme’, Contract N° : EVG1-CT2002-00061, Project N° : EVG1-2001-00061, Brussels, is kindly acknowledged. References 1. Gupta,R.P.(2003). Remote Sensing in Geology.-

Springer-Verlag, Berlin- Heidelberg-New York 2. Audemard,F.A. (2001). Quaternary tectonics

and present stress tensor of the inverted northern Falcon Basin, northwestern Venezuela. Journal of Structural Geology 23 (2001) 431-453

3. Schneider,G.(2004). Erdbeben – Eine Einführung für Geowissenschaftler und Bauingenieure: 246 p., Spektrum Akademischer Verlag, Elsevier, München

4. Larsen,M.C., Gerald F.Wieczorek, G.F., Eaton,L. , Morgan,B.A. & Torres-Sierra,H. (2001). Natural Hazards on Alluvial Fans: The Venezuela Debris Flow and Flash Food Disaster. US Department of the Interior, USGS Fact Sheet FS 103-01

5. Stucchi,M., Galadini,F.& Monachesi,G. The earthquakes of September/October 1997 in the frame of tectonics and long-term seismicity of the Umbria-Marche (Central Italy) Apennines, http://emidius.mi.ingv.it/GNDT/T19970926_eng/sism_stor.html

6. Giardini,D.,Wiemer,S.,Fäh,D.&Deichmann,N. (2004). Seismic Hazard Assessment of Switzerland,2004.- Swiss Seismological Service, ETH Zürich, Zürich, Switzerland

7. Sieberg,A. & Lais,R.(1925). Das mitteleuro-päische Erdbeben vom 16.11.1911, Bearbeitung der makroseismischen Beobachtungen.- Veröff. Reichsanstalt für Erdbebenforschung, 4, Jena

8. Geyer,O., Schober,Th.& Geyer,M.(2003). Sammlung geologischer Führer 94 – Die Hochrhein-Regionen zwischen Bodensee und Basel.- Gebr.Bornträger, Berlin –Stuttgart

Satellite Data: LANDSAT ETM and SRTM data: Earth Science Data Interface (ESDI) at the Global Land Cover Facility,University of Maryland, USA: http://glcfapp.umiacs.umd.edu:8080/esdi/index.jsp http://srtm.csi.cgiar.org/SELECTION/inputCoord.asp