Journal of Coastal Conservation

, Volume 17, Issue 4, pp 709–718 | Cite as

Ten years of land cover change on the California coast detected using Landsat satellite image analysis: Part 2—San Mateo and Santa Cruz counties

  • Christopher PotterEmail author


Landsat satellite imagery was analyzed to generate a detailed record of 10 years of vegetation disturbance and regrowth for Pacific coastal areas of San Mateo and Santa Cruz Counties. The Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) methodology, a transformation of Tasseled-Cap data space, was applied to detected changes in perennial coastal shrubland, woodland, and forest cover from 1999 to 2009. Results showed several principal points of interest, within which extensive contiguous areas of similar LEDAPS vegetation change (either disturbed or restored) were detected. Regrowth of evergreen shrub and tree cover was prevalent along the several long stretches of the coast highway (CA Route 1) between the cities of Half Moon Bay and Santa Cruz. A number of state parks areas showed measurable vegetation restoration as well. The most prominent loss of perennial coastal vegetation over decade was in the Pescadero Marsh area, where the continued presence of levees has historically reduced flood conveyance capacity into and through the marshlands. Based on these examples, the LEDAPS methodology was determined to be capable of fulfilling much of the need for continual, low-cost monitoring of emerging changes to coastal ecosystems.


Landsat Coastal vegetation Disturbance Regrowth Restoration 



This work was supported by grants from NASA Ames Research. The author thanks Tim Hyland, Environmental Scientist, California State Parks for assistance with image interpretations and historical information on the Ano Nuevo State Reserve area.


  1. California Beach Erosion Assessment Survey (CBEAS) (2010) California Coastal Sediment Management Workgroup, Sacramento, CAGoogle Scholar
  2. California Coastal Conservancy (2004) Pillar point bluff acquisition and trail planning, Staff recommendation, June 30, 2004, File No. 04–026, 8 ppGoogle Scholar
  3. Cohen WB, Goward SN (2004) Landsat’s role in ecological applications of remote sensing. BioScience 54:535–545CrossRefGoogle Scholar
  4. Crist EP, Cicone RC (1984) Application of the tasseled-cap concept to simulated thematic mapper data. Photogramm Eng Remote Sens 50:343–352Google Scholar
  5. Curry R, Houghton R, Kidwell T, Tang P (1985) Pescadero marsh management: A plan for persistence and productivity. January 28:1985Google Scholar
  6. Environmental Science Associates (ESA) (2008) Pescadero marsh: Restoration assessment and recommendations for ecosystem management. Prepared for the California Department of Parks and Recreation, San Francisco, p 54Google Scholar
  7. Hanak E, Moreno G (2012) California coastal management with a changing climate. Clim Chang 111(1):45–73CrossRefGoogle Scholar
  8. Healey SP, Cohen WB, Zhiqiang Y, Krankina ON (2005) Comparison of tasseled-cap-based Landsat data structures for use in forest disturbance detection. Remote Sens Environ 97:301–310CrossRefGoogle Scholar
  9. Huang C, Wylie B, Yang L, Homer C, Zylstra G (2002) Derivation of a tasseled-cap transformation based on Landsat-7 at-satellite reflectance. Int J Remote Sens 23:1741–1748CrossRefGoogle Scholar
  10. Johnstone JA, Dawson TE (2010) Climatic context and ecological implications of summer fog decline in the coast redwood region. Proc Natl Acad Sci. doi: 10.1073/pnas.0915062107 Google Scholar
  11. Kauth RJ, Thomas GS (1976) The tasseled-cap—A graphic description of the spectral–temporal development of agricultural crops as seen by Landsat. Proceedings, Symposium on Machine Processing of Remotely Sensed Data. LARS, West Lafayette, pp 41–51Google Scholar
  12. Kildow J, Colgan CS (2005) California’s Ocean Economy, Report to the Resource Agency, State of California, National Ocean Economics Program, July 2005Google Scholar
  13. Masek JG, Huang CQ, Wolfe R, Cohen W, Hall F, Kutler J, Nelson P (2008) North American forest disturbance mapped from a decadal Landsat record. Remote Sens Environ. doi: 10.1016/j.rse.2008.02.010 Google Scholar
  14. Rahmstorf S (2007) A semi-empirical approach to projecting future sea-level rise. Science 315:368–370CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht (outside the USA) 2013

Authors and Affiliations

  1. 1.NASA Ames Research CenterMoffett FieldUSA

Personalised recommendations