Remote sensing and GIS for wetland vegetation study

Al Sghair, Fathi Goma (2013) Remote sensing and GIS for wetland vegetation study. PhD thesis, University of Glasgow.

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Remote Sensing (RS) and Geographic Information System (GIS) approaches, combined with ground truthing, are providing new tools for advanced ecosystem management, by providing the ability to monitor change over time at local, regional, and global scales.

In this study, remote sensing (Landsat TM and aerial photographs) and GIS, combined with ground truthing work, were used to assess wetland vegetation change over time at two contrasting wetland sites in the UK: freshwater wetland at Wicken Fen between 1984 and 2009, and saltmarsh between 1988 and 2009 in Caerlaverock Reserve. Ground truthing studies were carried out in Wicken Fen (UK National Grid Reference TL 5570) during 14th - 18th June 2010: forty 1 m2 quadrats were taken in total, placed randomly along six transects in different vegetation types. The survey in the second Study Area Caerlaverock Reserve (UK National Grid Reference NY0464) was conducted on 5th - 9th July 2011, with a total of forty-eight 1 m2 quadrats placed randomly along seven transects in different vegetation types within the study area. Two-way indicator species (TWINSPAN) was used for classification the ground truth samples, taking separation on eigenvalues with high value (>0.500), to define end-groups of samples. The samples were classified into four sample-groups based on data from 40 quadrats in Wicken Fen, while the data were from 48 quadrats divided into five sample-groups in Caerlaverock Reserve.

The primary analysis was conducted by interpreting vegetation cover from aerial photographs, using GIS combined with ground truth data. Unsupervised and supervised classifications with the same technique for aerial photography interpretation were used to interpret the vegetation cover in the Landsat TM images. In Wicken Fen, Landsat TM images were used from 18th August 1984 and 23rd August 2009; for Caerlaverock Reserve Landsat TM imagery used was taken from 14th May 1988 and 11th July 2009. Aerial photograph imagery for Wicken Fen was from 1985 and 2009; and for Caerlaverock Reserve, from 1988 and 2009.

Both the results from analysis of aerial photographs and Landsat TM imagery showed a substantial temporal change in vegetation during the period of study at Wicken Fen, most likely primarily produced by the management programme, rather than being due to natural change. In Cearlaverock Reserve, results from aerial photography interpretation indicated a slight change in the cover of shrubs during the period 1988 to 2009, but little other change over the study period.

The results show that the classification accuracy using aerial photography was higher than that of Landsat TM data. The difference of classification accuracy between aerial photography and Landsat TM, especially in Caerlaverock Reserve, was due to the low resolution of Landsat TM images, and the fact that some vegetation classes occupied an area less than that of the pixel size of the TM image. Based on the mapping exercise, the aerial photographs produced better vegetation classes (when compared with ground truthing data) than Landsat TM images, because aerial photos have a higher spatial resolution than the Landsat TM images.

Perhaps the most important conclusion of this study is that it provides evidence that the RS/GIS approach can provide useful baseline data about wetland vegetation change over time, and across quite expansive areas, which can therefore provide valuable information to aid the management and conservation of wetland habitats.

Item Type: Thesis (PhD)
Qualification Level: Doctoral
Keywords: Medium resolution Landsat TM images, aerial photography, unsupervised classification, supervised classification.
Subjects: Q Science > QK Botany
Colleges/Schools: College of Medical Veterinary and Life Sciences > Institute of Biodiversity Animal Health and Comparative Medicine
Supervisor's Name: Murphy, Dr. K. and Drummond , Dr. J.
Date of Award: September 2013
Depositing User: Mr Fathi Al Sghair
Unique ID: glathesis:2013-4581
Copyright: Copyright of this thesis is held by the author.
Date Deposited: 17 Sep 2013 14:16
Last Modified: 17 Sep 2013 15:08

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