Call for Paper - July 2020 Edition
IJCA solicits original research papers for the July 2020 Edition. Last date of manuscript submission is June 22, 2020. Read More

Modelling and Estimation of Spatiotemporal Surface Dynamics Applied to a Middle Himalayan Region

Print
PDF
International Journal of Computer Applications
© 2012 by IJCA Journal
Volume 54 - Number 7
Year of Publication: 2012
Authors:
Prashant Kumar
Amol P. Bhondekar
Pawan Kapur
10.5120/8578-2317

Prashant Kumar, Amol P Bhondekar and Pawan Kapur. Article: Modelling and Estimation of Spatiotemporal Surface Dynamics Applied to a Middle Himalayan Region. International Journal of Computer Applications 54(7):17-24, September 2012. Full text available. BibTeX

@article{key:article,
	author = {Prashant Kumar and Amol P. Bhondekar and Pawan Kapur},
	title = {Article: Modelling and Estimation of Spatiotemporal Surface Dynamics Applied to a Middle Himalayan Region},
	journal = {International Journal of Computer Applications},
	year = {2012},
	volume = {54},
	number = {7},
	pages = {17-24},
	month = {September},
	note = {Full text available}
}

Abstract

Accurate and timely estimation of the spatiotemporal surface dynamics is very important for natural resource planning and disaster mitigation. This paper discusses a novel technique to assess the patterns of the surfaces of a particular severe landslide susceptible zone (Kullu-Larji-Rampur geological window, near Aut village, district Mandi, Himachal Pradesh, India; N 31°44'34. 78'' E 77°12'29. 02''). The spatiotemporal surface dynamics of this region, spanning over last 20 years (1989 - 2009), has been modelled using Landsat TM images acquired during summers of 1989, 2000 and 2009. The proposed technique uses image processing to derive regression models of selected area segments, these models are then used to measure area under the curve to estimate the surface area changes. The surface area changes thus obtained have also been validated by standard method of pixel counting. Principal component analysis has been done in order to understand the correlations amongst the estimated parameters, namely; segment lengths, percentage area change and the area change in the first (1989-2000) and second (2000-2009) decades. The results obtained show a fair degree of accuracy as compared to the standard method of pixel counting.

References

  • V. B. S. Chandel, K. K. Brar, and Y. Chauhan, "RS & GIS Based Landslide Hazard Zonation of Mountainous Terrains A Study from Middle Himalayan Kullu District, Himanchal Pradesh, India," International Journal of Geomatics and Geosciences, vol. 2, no. 1, 2011.
  • R. R. Bharti, B. S. Adhikari, and G. S. Rawat, "Assessing vegetation changes in timberline ecotone of Nanda Devi National Park, Uttarakhand," International Journal of Applied Earth Observation and Geoinformation, no. 0, 2011.
  • J. S. Gardner, "NATURAL HAZARDS RISK IN THE KULLU DISTRICT, HIMACHAL PRADESH, INDIA*," Geographical Review, vol. 92, no. 2, pp. 282-306, 2002.
  • R. S. Lunetta, J. F. Knight, J. Ediriwickrema et al. , "Land-cover change detection using multi-temporal MODIS NDVI data," Remote Sensing of Environment, vol. 105, no. 2, pp. 142-154, 2006.
  • A. Singh, "Review Article Digital change detection techniques using remotely-sensed data," International Journal of Remote Sensing, vol. 10, no. 6, pp. 989-1003, 1989/06/01, 1989.
  • P. R. Coppin, and M. E. Bauer, "Digital change detection in forest ecosystems with remote sensing imagery," Remote Sensing Reviews, vol. 13, no. 3-4, pp. 207-234, 1996/04/01, 1996.
  • T. R. Martha, N. Kerle, V. Jetten et al. , "Characterising spectral, spatial and morphometric properties of landslides for semi-automatic detection using object-oriented methods," Geomorphology, vol. 116, no. 1–2, pp. 24-36, 2010.
  • B. Ahmed, and R. Ahmed, "Modeling Urban Land Cover Growth Dynamics Using Multi?Temporal Satellite Images: A Case Study of Dhaka, Bangladesh," ISPRS International Journal of Geo-Information, vol. 1, no. 1, pp. 3-31, 2012.
  • M. E. Bauer, B. C. Loffelholz, and B. Wilson, Estimating and Mapping Impervious Surface Area by Regression Analysis of Landsat Imagery, p. ^pp. 488: CRC Press, 2007.
  • P. Griffiths, P. Hostert, O. Gruebner et al. , "Mapping megacity growth with multi-sensor data," Remote Sensing of Environment, vol. 114, no. 2, pp. 426-439, 2010.
  • M. -K. Kim, and J. Daigle, "Detecting vegetation cover change on the summit of Cadillac Mountain using multi-temporal remote sensing datasets: 1979, 2001, and 2007," Environmental Monitoring and Assessment, vol. 180, no. 1, pp. 63-75, 2011.
  • F. Fiorucci, M. Cardinali, R. Carlà et al. , "Seasonal landslide mapping and estimation of landslide mobilization rates using aerial and satellite images," Geomorphology, vol. 129, no. 1–2, pp. 59-70, 2011.
  • S. Ghosh, C. J. van Westen, E. J. M. Carranza et al. , "Generating event-based landslide maps in a data-scarce Himalayan environment for estimating temporal and magnitude probabilities," Engineering Geology, vol. 128, no. 0, pp. 49-62, 2012.
  • C. J. van Westen, E. Castellanos, and S. L. Kuriakose, "Spatial data for landslide susceptibility, hazard, and vulnerability assessment: An overview," Engineering Geology, vol. 102, no. 3–4, pp. 112-131, 2008.
  • A. Emerson, G. C. L. Howell, and H. L. Wright, Gazetteer of the Mandi State, New Delhi: Indus Publishing, 1998.
  • M. Sah, and R. Mazari, "An overview of the geoenvironmental status of the Kullu Valley, Himachal Pradesh, India," Journal of Mountain Science, vol. 4, no. 1, pp. 003-023, 2007.
  • R. Shankar, and K. J. S. Dua, "On the Existence of a Tear Fault Along Upper Beas Valley, District Kulu, Himachal Pradesh, and its Bearing on the Thermal Activity," Himalayan Geology, vol. 8, no. 1, pp. 466-472, 1978.
  • United States Geological Survey. http://www. usgs. gov/.
  • R. C. Gonzalez, R. E. Woods, and S. L. Eddins, Digital Image Processing Using MATLAB, p. ^pp. 827: Gatesmark Publishing, 2009
  • T. Kim, and Y. -J. Im, "Automatic satellite image registration by combination of matching and random sample consensus," IEEE Transactions on Geoscience and Remote Sensing, vol. 41, no. 5, pp. 1111- 1117 2003.
  • J. Canny, "A Computational Approach to Edge Detection," Pattern Analysis and Machine Intelligence, IEEE Transactions on, vol. PAMI-8, no. 6, pp. 679-698, 1986.
  • A. Carrara, M. Cardinali, R. Detti et al. , "GIS techniques and statistical models in evaluating landslide hazard," Earth Surface Processes and Landforms, vol. 16, no. 5, pp. 427-445, 1991.
  • N. Sarkar, and B. B. Chaudhuri, "An efficient differential box-counting approach to compute fractal dimension of image," Systems, Man and Cybernetics, IEEE Transactions on, vol. 24, no. 1, pp. 115-120, 1994.
  • A. P. Bhondekar, M. Dhiman, A. Sharma et al. , "A novel iTongue for Indian black tea discrimination," Sensors and Actuators B: Chemical, vol. 148, no. 2, pp. 601-609, 2010.
  • R. Soeters, and C. J. van Westen, "LANDSLIDES: INVESTIGATION AND MITIGATION," SLOPE INSTABILITY RECOGNITION, ANALYSIS, AND ZONATION, A. K. Turner and L. R. Schuste, eds. , pp. 129-177: Transportation Research Board, 1996.
  • F. C. Dai, and C. F. Lee, "Landslide characteristics and slope instability modeling using GIS, Lantau Island, Hong Kong," Geomorphology, vol. 42, no. 3–4, pp. 213-228, 2002.
  • J. B. Adams, D. E. Sabol, V. Kapos et al. , "Classification of multispectral images based on fractions of endmembers: Application to land-cover change in the Brazilian Amazon," Remote Sensing of Environment, vol. 52, no. 2, pp. 137-154, 1995.
  • J. W. Dalling, "Vegetation Colonization of Landslides in the Blue Mountains, Jamaica," The Association for Tropical Biology and Conservation, vol. 26, no. 4, pp. 392-399, 1994.