Abstract
In this paper, a semiautomatic method for landslide detection from satellite images and digital terrain information using generalized improved fuzzy Kohonen clustering network (GIFKCN) classifier is presented. The proposed method classifies the pre- and post-landslide images using the GIFKCN classifier which is trained using spectral indices such as normalized difference vegetation index, normalized difference building index and normalized difference water index. The changes in the vegetation class are identified using the pre- and post-classified images. Generally, landslides result in loss of vegetation; thus, using this property, candidate landslides are identified. Finally, false positives are removed using a rule set created from DEM derivatives slope and aspect. The proposed method is applied on Landsat 5 and Advanced Land Imager EO-1 satellite images to detect earthquake-induced landslides that occurred in Sikkim state of India due to the September 18, 2011, earthquake of magnitude M w = 6.9. The terrain information used is ASTER Global Digital Elevation Model of the area. The accuracy assessment of the method is done, and the results show that the landslides are identified and classified efficiently.
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Casson B, Delacourt C, Baratoux D, Allemand P (2003) Seventeen years of the “La Clapière” landslide evolution analysed from ortho-rectified aerial photographs. Eng Geol 68(1):123–139
Cheng KS, Wei C, Chang SC (2004) Locating landslides using multi-temporal satellite images. Adv Space Res 33(3):296–301
Cheng G, Guo L, Zhao T, Han J, Li H, Fang J (2013) Automatic landslide detection from remote-sensing imagery using a scene classification method based on BoVW and pLSA. Int J Remote Sens 34(1):45–59
Congalton RG, Green K (2008) Assessing the accuracy of remotely sensed data: principles and practices. CRC Press, Boca Raton
Hervás 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(1):63–75
Kääb A (2002) Monitoring high-mountain terrain deformation from repeated air-and spaceborne optical data: examples using digital aerial imagery and ASTER data. ISPRS J Photogr Remote Sens 57(1):39–52
Kohonen T (1990) The self-organizing map. Proc IEEE 78(9):1464–1480
Li Y, Chen G, Wang B, Zheng L, Zhang Y, Tang C (2013) A new approach of combining aerial photography with satellite imagery for landslide detection. Nat Hazards 66(2):649–669
Mantovani F, Soeters R, Van Westen CJ (1996) Remote sensing techniques for landslide studies and hazard zonation in Europe. Geomorphology 15(3):213–225
Martha TR, Kerle N, van Westen CJ, Jetten V, Vinod Kumar K (2012) Object-oriented analysis of multi-temporal panchromatic images for creation of historical landslide inventories. ISPRS J Photogramm Remote Sens 67:105–119
Nagarajan R, Mukherjee A, Roy A, Khire MV (1998) Technical note Temporal remote sensing data and GIS application in landslide hazard zonation of part of Western ghat, India
Ren Z, Lin A (2010) Co-seismic landslides induced by the 2008 Wenchuan magnitude 8.0 Earthquake, as revealed by ALOS PRISM and AVNIR2 imagery data. Int J Remote Sens 31(13):3479–3493
Singh KK, Nigam MJ, Pal K (2014) Detection of 2011 Tohoku tsunami inundated areas in Ishinomaki City using generalized improved fuzzy Kohonen clustering network. Eur J Remote Sens 47:461–475
Singhroy V (2002) Landslide hazards: CEOS, The use of earth observing satellites for hazard support: assessments and scenarios. Final report of the CEOS Disaster Management Support Group, NOAA, p 98
Singhroy V, Molch K (2004) Characterizing and monitoring rockslides from SAR techniques. Adv Space Res 33(3):290–295
Siyahghalati S, Saraf AK, Pradhan B, Jebur MN, Tehrany MS (2014) Rule-based semi-automated approach for the detection of landslides induced by 18 September 2011 Sikkim, Himalaya, earthquake using IRS LISS3 satellite images. Geomat Nat Hazards Risk 7(1):326–344
Tsai F, Hwang JH, Chen LC, Lin TH (2010) Post-disaster assessment of landslides in southern Taiwan after 2009 Typhoon Morakot using remote sensing and spatial analysis. Nat Hazards Earth Syst Sci 10:2179–2190
USGS Global Visualization Viewer. http://glovis.usgs.gov
Van Westen CJ, Lulie Getahun F (2003) Analyzing the evolution of the Tessina landslide using aerial photographs and digital elevation models. Geomorphology 54(1):77–89
Zhang W, Lin J, Peng J, Lu Q (2010) Estimating Wenchuan Earthquake induced landslides based on remote sensing. Int J Remote Sens 31(13):3495–3508
Zhou CH, Lee CF, Li J, Xu ZW (2002) On the spatial relationship between landslides and causative factors on Lantau Island, Hong Kong. Geomorphology 43(3):197–207
Zhu L, Chung FL, Wang S (2009) Generalized fuzzy c-means clustering algorithm with improved fuzzy partitions. Syst Man Cybern Part B Cybern IEEE Trans 39(3):578–591
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Singh, K.K., Singh, A. Detection of 2011 Sikkim earthquake-induced landslides using neuro-fuzzy classifier and digital elevation model. Nat Hazards 83, 1027–1044 (2016). https://doi.org/10.1007/s11069-016-2361-6
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DOI: https://doi.org/10.1007/s11069-016-2361-6