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Quick Identification of Regional Earthquake-Induced Landslides Based on Sharp NDVI Change

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Earthquake-Induced Landslides

Abstract

Landslides triggered by earthquake lead to substantial loss of life and damages to property. It was necessary and important to locate and plot out the landslides immediately after earthquake for quick victims rescuing. In addition, it is significant to map potential landslides for planning settlement and mitigating geological disaster. Landslide often results in sharp land cover changes in forested or bushed area, which can be easily detected by airborne or satellite-based remote sensing techniques. The region that landslide takes place is often inaccessible for field observation because of the accompanied temporary failure in transportation and communication. Therefore, remote sensing can be adopted to collect spatial information of landslide efficiently and quickly. By taking Wenchuan Earthquake as an example, this paper advanced one quick methodology to extract primary regional landslides with 8-day MODIS NDVI and terrain slope information. The threshold of temporal NDVI jump (value of 0.4) was introduced to discriminate landslide induced sharp NDVI decline from seasonal variations of vegetation cover, while slope information can be used to further confirm land cover change caused by landslide. In addition, the result emphasizes that region with slope over 15° is exposed to high landslide risk, which should be carefully taken into account in settlement and transportation planning.

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References

  • Canuti P, Casagli N, Catani F, Falorni G, Farina P (2007) Integration of remote Sensing techniques in different stages of landslide response. Progress in landslide science. Springer, Berlin, pp 251–260

    Google Scholar 

  • Cheng KS, Wei C, Chang SC (2004) Locating landslides using multi-temporal satellite images. Adv Space Res 33:296–301

    Article  Google Scholar 

  • Farr TG, Rosen PA, Caro E, Crippen R, Duren R, Hensley S, Kobrick M (2007) The shuttle radar topography mission. Rev Geophys 45: . doi:10.1029/2005RG000183

    Article  Google Scholar 

  • GLCF (2008) GLCF homepage. http://www.landcover.org/index.shtml. Cited on 25 Oct 2008

  • Hervas J, Barredo JI, Rosin PL, Pasuto A, Mantovani F, Silvano S (2003) Monitoring landslides from optical remotely sensed imagery: the case history of Tessina landslide, Italy. Geomorphology 54:63–75

    Article  Google Scholar 

  • Hong Y, Adler RF, Huffman G (2007) An experimental global prediction system for rainfall-triggered landslides using satellite remote sensing and geospatial datasets. IEEE Trans Geosci Remote Sens 45:1671–1680

    Article  Google Scholar 

  • Huete A, Didan K, Miura T, Rodriguez EP, Gao X, Ferreira LG (2002) Overview of the radiometric and biophysical performance of the MODIS vegetation indices. Remote Sens Environ 83:195–213

    Article  Google Scholar 

  • Metternicht G, Hurni L, Gogu R (2005) Remote sensing of landslides: an analysis of the potential contribution to geo-spatial systems for hazard assessment in mountainous environments. Remote Sens Environ 98:284–303

    Article  Google Scholar 

  • Miliaresis G, Sabatakakis N, Koukis G (2005) Terrain pattern recognition and spatial decision making for regional slope stability studies. Nat Resour Res 14:91–100

    Article  Google Scholar 

  • Nagarajan R, Mukherjee A, Roy A, Khire MV (1998) Temporal remote sensing data and GIS application in landslide hazard zonation of part of Western ghat, India. Int J Remote Sens 19:573–585

    Article  Google Scholar 

  • NASA (2008) EOS data gateway. http://delenn.gsfc.nasa.gov/~imswww/pub/imswelcome/. Cited on 15 June 2008

  • Park S, Feddema JJ, Egbert SL (2004) Impacts of hydrologic soil properties on drought detection with MODIS thermal data. Remote Sens Environ 89:53–62

    Article  Google Scholar 

  • Perotto-Baldiviezo HL, Thurow TL, Smith CT, Fisher RF, Wu XB (2004) GIS-based spatial analysis and modeling for landslide hazard assessment in steeplands, southern Honduras. Agric Ecosys Environ 103:165–176

    Article  Google Scholar 

  • Qi J, Chehbouni A, Huete AR (1994) A modified soil adjusted vegetation index. Remote Sens Environ 48:119–126

    Article  Google Scholar 

  • Rabus B, Eineder M, Roth A, Bamler R (2003) The shuttle radar topography mission–a new class of digital elevation models acquired by spaceborne radar. ISPRS J Photogram Rem Sens 57:241–262

    Article  Google Scholar 

  • Roessner S, Wetzel H-U, Kaufmann H, Sarnagoev A (2005) Potential of satellite remote sensing and GIS for landslide hazard assessment in Southern Kyrgyzstan (Central Asia). Nat Hazards 35:395–416

    Article  Google Scholar 

  • Temesgen B, Mohammed MU, Korne T (2001) Natural hazard assessment using GIS and remote sensing methods, with particular reference tot the landslides in the Wondogenet area, Ethiopia. Phys Chem Earth (C) 26:665–675

    Google Scholar 

  • TERRA (2008). Terra project science. http://terra.nasa.gov. Cited on 30 Sept 2008

  • Tralli DM, Blom RG, Zlotnicki V, Donnellan A, Evans DL (2005) Satellite remote sensing of earthquake, volcano, flood, landslide and coastal inundation hazards. ISPRS J Photogram Rem Sens 59:185–198

    Article  Google Scholar 

  • USGS (2008) USGS EROS Data Center. http://edcftp.cr.usgs.gov/pub/data/disaster/ 200805_Earthquake_ China/data/. Cited on 10 Oct 2008

  • Wang X, Xie H, Guan H, Zhou X (2007) Different responses of MODIS-derived NDVI to root-zone soil moisture in semi-arid and humid regions. J Hydrol 340:12–24

    Article  Google Scholar 

  • Zhang W, Lin J, Peng J, Lu Q (2010) Estimating Wenchuan earthquake of China induced landslides based on remote sensing. Int J Remote Sens 31:3495–3508

    Article  Google Scholar 

Download references

Acknowledgments

This work was supported by the Program of High Resolution Earth Observation System (China) and the Key Technology Research and Development Program of the Science & Technology Department of Sichuan Province (No. 2012SZ0057). It was also partly supported by the West Light Foundation of Chinese Academy of Sciences (“Obser-vation, Monitoring and Assessment of Landslide Disasters with UAV-based Multispectral Remote Sensing Technology”), the Foundation of State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing at Wuhan University (No.10R02), and the National Basic Research Program of China (973 Program) (No. 2010CB731504).

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Correspondence to Jiayuan Lin .

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Lin, J., Zhou, G. (2013). Quick Identification of Regional Earthquake-Induced Landslides Based on Sharp NDVI Change. In: Ugai, K., Yagi, H., Wakai, A. (eds) Earthquake-Induced Landslides. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32238-9_78

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