Background Paper for the Mountain GIS e-conference 14-25 January 2008 Monitoring/Impact of Wild Fires of the August 2007 in the Mountain Region of Ilia Prefecture (Western Greece) from Web Spatial (no cost) GIS Databases 1 George C. Miliaresis gmiliar@yahoo.com, http://miliaresis.tripod.com Abstract: Public domain GIS datasets (elevation, landcover, AVHHR imagery) were used in an attempt to monitor and map the impact of wild fires of August 2007 in Ilia Prefecture. It was concluded that the 44% percent of land was burned while objects with different geomorphometry that are subject to different hazards were identified. 1. Introduction Nowadays, broad-scale quantification of topography and digital elevation models (DEMs) represents the earth s relief at regional to moderate scale (Miliaresis 2007). At the same time various digital image processing (Mather 2004) and G.I.S. techniques (Burroughs and McDonnel 1998) are being developed in order to automate the segmentation and the qualitative interpretation of geomorphologic features (Miliaresis and Argialas 2000; Miliaresis 2001; Miliaresis and Kokkas 2004). Landcover change due to anthropogenic actions affects the current climatic state and plays an important role in climate forcing (Bartholome and Belward 2005). Reliable information on the state of our planet s landcover is thus, needed on a regular basis in order to understand the balance between global landcover patterns, climate and changes occurring in either of these. Towards this end, various efforts were made in order to document global and regional landcover characteristics from satellite imagery (Belward et al. 1999). These efforts resulted to the creation of landcover databases (Fuller et al. 2005). Figure 1. Study area. Figure 2. Burned areas in Peloponnesus during the august 2007 fires. 1 This research effort was supported by the Prefecture Authority of Ilia (Prefector Ch. Kafiras and Vice Prefector E. Balkamos). Contact address: Nomarxia Ilias, 31, Manolopoulou str., 27100 Pirgos, Greece, Email: support@nailias.gr, web page: http://www.nailias.gr 1
Satellites afford excellent means to monitor continuing ecological threats and damage and long term after effects to the Earth s natural surface and to areas relevant to human activities (NOAA 2008). Sometimes, ongoing ecological problems can be watched in near-real time (Figures 1 and 2) using meteorological satellites (CLASS 2008). Much obvious damage is imposed on vegetation, such as acreage affected by forest fires and grassland burns. Forest fires usually burn for a few days to several weeks (especially in isolated areas) until brought under control. Wild fires occur within very short time frames due to climatic change (increase of land surface temperature, decrease of rainfalls) in mid-latitude countries (IAF 2008). Monitoring from space is especially well suited to watching these fires as they occur and after they are extinguished to gauge their effects (Figure 3). Figure 3. Detection of thermal fronts from near, mid and thermal infrared AVHHR imagery. Forest fires raged unabated on 22 th to the 31 th of August 2007 in the Peloponnese peninsula (Figure 2) of southern Greece, killing at least 64 people as flames threatened historic sites including Ancient Olympia in the Prefecture of Ilia (Ilia 2008). The fires have gutted hundreds of homes, forcing thousands of villagers to flee and blackening hillsides. Vulnerability is termed the sensitivity of a region to the influence of unfavorable and dangerous natural events or phenomena (Petrova 2006) and it is function mainly of the relief and landcover. The quantification of knowledge related to the landscape organization from both digital elevation models (SRTM V2 2006) and the landcover databases (CLC 2000) is vital for the planning and economic development at both a country and a global level as well as for the 2
assessment of hazards (landslides and floods) related to the upcoming global climatic change (Miliaresis et al. 2005; Miliaresis 2006). The aim of this research effort is to present the crisis monitoring capabilities of the satellite imagery of meteorological satellites provided at no cost, outline the region affected by wild fires and estimate the impact to the landcover and geomorphologic features from spatial databases that provide data (imagery, elevation and landcover) at no cost through the web (Miliaresis 2008). 2. Study area Ilia prefecture belongs to the region of Western Greece, occupying the North-West part of the Peloponnese and on the west it is washed by the Ionian Sea (Ilia 2008). It is 2.618 square Kilometers in size and its population amounts to 193.288 inhabitants. Its capital is Pyrgos and on the east of Pyrgos, in a valley among the Cronius hill, the river Alfeios and its tributary Kladeos, spreads out one of the most significant archaeological sites in Greece, Ancient Olympia. The whole prefecture consists of 22 municipalities. Figure 4. Digital elevation model and digital contours within Ilia prefecture. Figure 5. Shaded Relief map and Ilia prefecture borders. 3. Elevation Data The Consortium for Spatial Information (CSI) of the Consultative Group for International Agricultural Research (CGIAR) is offering post-processed 3-arc second SRTM DEM data for the globe (SRTM V2 2005). The CGIAR-CSI SRTM data is available in 5 degree tiles, referenced to WGS-84 ellipsoid, forming a geographic grid with spacing 0.00083333 o. The data tile S_41_05 that includes Peloponnesus was used. It was reprojected to EGSA87, the Greek Geodetic System (Mugnier 2002), resampled by nearest neighbor and a DEM with spacing 100 m (Figures 4 and 5) was derived. 4. Satellite Imagery Satellite images from the National Oceanic and Atmospheric Administration (NOAA, 2008) and more specifically the Advanced Very High Resolution Radiometer (AVHRR) instrument (CLASS 2008) were used as an early warning system as well as a mapping instrument that 3
revealed the impact of wild fires on land surface (Miliaresis 2008). NOAA-AVHRR images are characterized by a relatively high temporal resolution (4-6 images per day), but a low spatial resolution of approximately 1 km. Day and 2 night images were used. Figure 6. The typical land coverage (swath) of a NOAA/AVHHR image The images were radiometrically and geometrically corrected and georeferenced to the Greek Geodetic System. Image processing techniques applied to visible and infrared bands identified that fires started about 12 hours earlier than the central government estimated; the identification of the active fire fronts in both day (Figure 3) and night (Figure 7), the monitoring of smoke affected areas (Figure 8), and the mapping of the burned areas (Figures 2 and 9). Figure 7. Fire fronts in night imagery. Figure 8. smoke affected areas. Figure 9. Mapping of burned areas in post fire AVHHR imagery. 4
5. Landcover Data A comprehensive land cover database is available, for the 25 EC Member States and other European countries, named Corine (CLC 2000). Corine provides quantitative data on land cover, consistent and comparable across Europe at an original scale of 1: 100000 using 44 Corince landcover classes (CLCs) of a 3-level nomenclature (Table 1). The spatial distribution of CLCs within the study area is presented in Figure 10 while the occurrence of each class is given in Table 2. Table 1. Corine CLCs Figure 10. Corine CLCs in the study area. Table 2. Occurrence of CLCs in the study area 5
6. Landcover-Relief Assessment The burned areas were superimposed over the drainage network (Figure 11), the CLCs (Figure 12) and the digital elevation data (Figure 13) of the Ilia prefecture. The impact to landcover is presented in table 3. Figure 11. Drainage and burned areas Figure 12. CLCs within the burned areas Figure 13. The geomorphometric signature of the burned area (elevation and slope maps are presented in left and right images correspondingly). 6
Table 3. Burned CLCs 7. Conclusion The 44% percent of Ilia prefecture was burned from the August wild fires. Within the burned area, the 70.5% correspond to cultivated land, 8.5% to forest 20% to shrubs and the rest to residential and urban areas. From the geomorphologic point of view, burned areas are divided to two sub-regions (Figure 12). The region 2 presents greater mean elevation and mean slope as well as roughness (standard deviation) than region 1. Thus soil erosion, mud flows, floods and landslides is more likely to occur in region 2. GIS WEB landcover, elevation and imagery databases are key factors that provide means (at no cost) for crisis management, planning in mountain areas as well as decision making at a moderate resolution scale. 7
8. References Bartholome, E., Belward, A.S., (2005). CLC2000, a new approach to global land cover mapping from Earth observation data. International Journal of Remote Sensing, 26: 1959-1977. Burroughs, P.P. and Mc Donnel, R.A. (1998), Principles of GIS, Oxford University Press, CLASS, (2008), Comprehensive Large Array-data Stewardship System, NOAA, http://www.class.noaa.gov/ CLC (2000) Corine land cover ver. 5, European Environment Agency { EEA, Copenhagen}, 2005, http://dataservice.eea.eu.int/ Fuller, R., Cox, R., Clarke, R., Rothery, P., Hill, R., Smith, G., Thomson, A., Brown, N., Howard, D., Stott, A., (2005) The UK land cover map 2000: Planning, construction and calibration of a remotely sensed, user-oriented map of broad habitats. International Journal of Applied Earth Observation and Geoinformation, 7:202 216. IAF (2008) International Association of Wildland fires, http://www.iawfonline.org/index.php Ilia (2008), Ilia Prefecture (Western Greece). http://www.nailias.gr/ Mather P., (2004), Computer Processing of Remotely- Sensed Images, John Wiley and Sons. Miliaresis, G., (2001) Extraction of bajadas from digital elevation models & satellite imagery, Computers & Geosciences, 27:1157-1167. Miliaresis G., (2006) Geometric and landcover signatures of local authorities in Peloponnesus. WSEAS Transactions on Environment and Development 4 (2), 239-244 Miliaresis G., (2007) An upland object based modeling of the vertical accuracy of the SRTM-1 elevation dataset. Journal of Spatial Sciences, 52:3-29. Miliaresis G., 2008. Remote sensing and GIS techniques for crisis management. Web Course (in Greek) http://hydrogis.geology.upatras.gr/crisisweb/crisis0.htm Miliaresis, G., Argialas, D., (2000) Extraction & delineation of alluvial fans from DΕΜs & Landsat TM images, Photogrammetric Engineering & Remote Sensing, 66:1093-1101. Miliaresis G., Kokkas N., (2004) Segmentation and terrain modeling of extra-terrestrial chasmata, Journal of Spatial Sciences, 49:89-99. Miliaresis G., Sabatakakis N., Koukis G., (2005) Terrain pattern recognition and spatial decision making for regional slope stability studies, Natural Resources Research, 14:91-100. Mugnier, C., (2002) Grids & datum: the Hellenic Republic, Photogrammetric Engineering & Remote Sensing, 68:1237-38. NOAA, (2008). National Oceanic and Atmospheric Administration, http://www.noaa.gov/ Petrova, E., (2006) Vulnerability of Russian regions to natural risk: experience of a quantitative assessment, Natural Hazards and Earth System Sciences, 6:49-54. SRTM V2, (2005) Void-filled seamless SRTM data, International Centre for Tropical Agriculture (CIAT), available from the CGIAR-CSI SRTM 90m Database, URL: http://srtm.csi.cgiar.org 8