Environmental Monitoring and Assessment

, Volume 179, Issue 1–4, pp 521–529

Land cover change of watersheds in Southern Guam from 1973 to 2001

Article

Abstract

Land cover change can be caused by human-induced activities and natural forces. Land cover change in watershed level has been a main concern for a long time in the world since watersheds play an important role in our life and environment. This paper is focused on how to apply Landsat Multi-Spectral Scanner (MSS) satellite image of 1973 and Landsat Thematic Mapper (TM) satellite image of 2001 to determine the land cover changes of coastal watersheds from 1973 to 2001. GIS and remote sensing are integrated to derive land cover information from Landsat satellite images of 1973 and 2001. The land cover classification is based on supervised classification method in remote sensing software ERDAS IMAGINE. Historical GIS data is used to replace the areas covered by clouds or shadows in the image of 1973 to improve classification accuracy. Then, temporal land cover is utilized to determine land cover change of coastal watersheds in southern Guam. The overall classification accuracies for Landsat MSS image of 1973 and Landsat TM image of 2001 are 82.74% and 90.42%, respectively. The overall classification of Landsat MSS image is particularly satisfactory considering its coarse spatial resolution and relatively bad data quality because of lots of clouds and shadows in the image. Watershed land cover change in southern Guam is affected greatly by anthropogenic activities. However, natural forces also affect land cover in space and time. Land cover information and change in watersheds can be applied for watershed management and planning, and environmental modeling and assessment. Based on spatio-temporal land cover information, the interaction behavior between human and environment may be evaluated. The findings in this research will be useful to similar research in other tropical islands.

Keywords

Land cover classification Accuracy assessment Human-induced activities Remote sensing GIS 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Guam Bureau of Statistics and Plans (2005). 2004 Guam Statistical Yearbook. Hagatna: Guam Bureau of Statistics and Plans.Google Scholar
  2. Jensen, J. R. (2000). Remote sensing of the environment: An earth resource perspective. New York: Prentice Hall.Google Scholar
  3. Jensen, J. R. (2005). Introductory Digital Image Processing: A Remote Sensing Perspective (3rd edn). New York: Prentice Hall.Google Scholar
  4. Kepner, W. G., et al. (1999). The changing watershed: A 25-year history of land cover change in the San Pedro River, an American Semi-arid Bioregion. Presented at the Landscape Futures Symposium, University of New England, Armidale, New South Wales, Australia, 22–25 September.Google Scholar
  5. Kepner, W. G., et al. (2002). Remote sensing and geographic information systems for decision analysis in public resource administration: A case study of 25 years of landscape change in a Southwestern Watershed. EPA Report No. EPA/600/R-02/039Google Scholar
  6. Khosrowpanah, S., Heitz, L., Wen, Y., & Park, M. (2007a). Developing a GIS-based soil erosion potential model of the Uguam watershed. Technical Report 117, Water and Environmental Research Institute of the Western Pacific, University of Guam.Google Scholar
  7. Khosrowpanah, S., Wen, Y., and Heitz, L. (2007b). Development of a digital watershed atlas for Guam. Technical Report 116, Water and Environmental Research Institute of the Western Pacific, University of Guam.Google Scholar
  8. Sikdar, P. K., et al. (2004). Land use/land cover changes and groundwater potential zoning in and around Raniganj coal mining area, Bardhaman District, West Bengal—A GIS and Remote Sensing Approach. Journal of Spatial Hydrology, 4(2), 1–24.Google Scholar
  9. Tracey, J., et al. (1964). General geology of Guam, U.S. geological survey professional paper 403-A. Washington: US Government Printing Office.Google Scholar
  10. Wen, Y. (2005). Spatial diffusion model for simulation of urban land cover change. Doctoral dissertation, University of Rhode Island, published by UMI.Google Scholar
  11. Wickham, J. D., et al. (2004). Thematic accuracy of the 1992 national land-cover data for the western United States. Remote Sensing of Environment, 91, 452–468.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media B.V. 2010

Authors and Affiliations

  1. 1.Water and Environmental Research InstituteUniversity of GuamMangilaoUSA

Personalised recommendations