Resolution vs. image quality in pre-tsunami imagery used for tsunami impact models in Aceh,Indonesia |
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| Institution: | 1. Caroline Amalie Vej 78, Kongens Lyngby 2800, Denmark;2. Viikki Tropical Resources Institute (VITRI), University of Helsinki, Department of Forest Sciences, P.O. Box 27, (Latokartanonkaari 7), FI-00014 University of Helsinki, Finland;3. Center for International Forestry Research (CIFOR), Jalan CIFOR, Situ Gede, Sindang Barang, Bogor (Barat) 16115, Indonesia;4. University of Copenhagen, Rolighedsvej 25, 1258 Frederiksberg, Denmark;1. University of Passau, Germany;2. TH Koeln, University of Applied Sciences, Germany;3. World Agroforestry Centre (ICRAF), Kenya;4. Centro de Investigaciones en Geografía Ambiental (CIGA) & Laboratorio Nacional de Análisis y Síntesis Ecológica (LANASE), Escuela Nacional de Estudios Superiores, Universidad Nacional Autónoma de México, Mexico;5. Japan International Research Center for Agricultural Sciences (JIRCAS), Japan;1. Yunnan Key Laboratory of Pollution Process and Management of Plateau Lake-Watershed, Yunnan Institute of Environmental Sciences, Kunming, 650034, China;2. World Agroforestry Centre, East and Central Asia Region, Kunming, 650204, China;3. Shilin Meteorological Bureau, Kunming, 652200, China;4. World Agroforestry Centre, Southeast Asia, Bogor 16001, Indonesia;5. Department of Geography, National University of Singapore, 117570, Singapore;1. University of Twente, Twente Water Centre, P.O. Box 217, 7522AE Enschede, The Netherlands;2. International Livestock Research Institute (ILRI), P.O. Box 30709, 00100 Nairobi, Kenya;3. World Agroforestry Centre (ICRAF), P.O. Box 30677, Nairobi 00100, Kenya;4. University of Hohenheim, Institute for Crop Science, Biostatistics Unit, 70599 Stuttgart, Germany |
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| Abstract: | Land cover roughness coefficients (LCRs) have been used in multivariate spatial models to test the mitigation potential of coastal vegetation to reduce impacts of the 2004 tsunami in Aceh, Indonesia. Previously, a Landsat 2002 satellite imagery was employed to derive land cover maps, which were then combined with vegetation characteristics, i.e., stand height, stem diameter and planting density to obtain LCRs. The present study tested LCRs extracted from 2003 and 2004 Landsat (30 m) images as well as a combination of 2003 and 2004 higher spatial resolution SPOT (10 m) imagery, while keeping the previous vegetation characteristics. Transects along the coast were used to extract land cover, whenever availability and visibility allowed. These new LCRs applied in previously developed tsunami impact models on wave outreach, casualties and damages confirmed previous findings regarding distance to the shoreline as a main factor reducing tsunami impacts. Nevertheless, the models using the new LCRs did not perform better than the original one. Particularly casualties models using 2002 LCRs performed better (δAIC > 2) than the more recent Landsat and SPOT counterparts. Cloud cover at image acquisition for Landsat and low area coverage for SPOT images decreased statistical predictive power (fewer observations). Due to the large spatial heterogeneity of tsunami characteristics as well as topographic and land-use features, it was more important to cover a larger area. Nevertheless, if more land cover classes would be referenced and high resolution imagery with low cloud cover would be available, the full benefits of higher spatial resolution imagery used to extract more precise land use roughness coefficients could be exploited. |
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| Keywords: | Tsunami West Aceh GLIMMIX Land cover roughness Model selection Landsat SPOT |
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