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Journal of Coastal Conservation

, Volume 2, Issue 1, pp 23–32 | Cite as

Assessing wetland changes in the venice lagoon by means of satellite remote sensing data

  • Brivio P. A. Email author
  • Zilioli E. 
Article

Abstract

Not only does lagoon ecology represent a transitional zone between the sea and the continent but it also expresses the equilibrium belt between erosion and sedimentation processes. Within the framework of a coastal management scheme, a precise and timely mapping of morphological changes in this environment is important. This paper illustrates the possible contribution of multi-temporal satellite observations in the monitoring of the erosion/sedimentation processes of coastal zones, where landscape features are subjected to highly morphodynamical modifications. In particular, an improved mapping accuracy was obtained by the successive application of the Maximum Likelihood (MLH) classifier and the Linear Mixture Model (LMM) techniques to the satellite image classification procedure. In fact, by estimating the amount of shallow water and wetland within each satellite pixel, the LMM technique allows for an accurate mapping of the transitional zones in the lagoon environment, thus permitting an optimal separation between land and water. The study concerns the Venice lagoon (Italy) which has been sinking slowly since the beginning of this century. This has led to widespread loss of wetlands. In order to monitor the development of the land cover, four Landsat Thematic Mapper scenes were examined, during the period 1984 to 1993. The results obtained proved that the digital analysis method of multitemporal satellite imagery, applied over a selected test area, enables the evolution of an estuarine environment landscape, with its different sequences of erosion and periods of accretion, to be monitored. The significant influence of tidal stages is discussed in the data analysis.

Keywords

Image classification Landsat Linear Mixture Model Maximum likelihood Morphodynamics Subsidence 

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Copyright information

© EUCC; Opulus Press Uppsala 1996

Authors and Affiliations

  1. 1.Remote Sensing Dept.Istituto di Recerca sul Rischio Sismico-CNR-IRRSMilanoItaly

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