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Development of an indicator to monitor mediterranean wetlands.

Sanchez A, Abdul Malak D, Guelmami A, Perennou C - PLoS ONE (2015)

Bottom Line: A validation process is put in place to compare outcomes with existing local wetland inventories to check the results reliability.The indicator´s results demonstrate an improvement in the level of precision of change detection methods achieved by traditional tools providing reliability up to 95% in main wetland areas.The results confirm that the use of RS techniques improves the precision of wetland detection compared to the use of CLC for wetland monitoring and stress the strong relation between the level of wetland detection and the nature of the wetland areas and the monitoring scale considered.

View Article: PubMed Central - PubMed

Affiliation: European Topic Centre, University of Málaga, Málaga, Spain.

ABSTRACT
Wetlands are sensitive ecosystems that are increasingly subjected to threats from anthropogenic factors. In the last decades, coastal Mediterranean wetlands have been suffering considerable pressures from land use change, intensification of urban growth, increasing tourism infrastructure and intensification of agricultural practices. Remote sensing (RS) and Geographic Information Systems (GIS) techniques are efficient tools that can support monitoring Mediterranean coastal wetlands on large scales and over long periods of time. The study aims at developing a wetland indicator to support monitoring Mediterranean coastal wetlands using these techniques. The indicator makes use of multi-temporal Landsat images, land use reference layers, a 50m numerical model of the territory (NMT) and Corine Land Cover (CLC) for the identification and mapping of wetlands. The approach combines supervised image classification techniques making use of vegetation indices and decision tree analysis to identify the surface covered by wetlands at a given date. A validation process is put in place to compare outcomes with existing local wetland inventories to check the results reliability. The indicator´s results demonstrate an improvement in the level of precision of change detection methods achieved by traditional tools providing reliability up to 95% in main wetland areas. The results confirm that the use of RS techniques improves the precision of wetland detection compared to the use of CLC for wetland monitoring and stress the strong relation between the level of wetland detection and the nature of the wetland areas and the monitoring scale considered.

No MeSH data available.


Related in: MedlinePlus

Results of Error A and B (%) obtained in the analysis of the wetland indicator in years 1984 and 2001.
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pone.0122694.g011: Results of Error A and B (%) obtained in the analysis of the wetland indicator in years 1984 and 2001.

Mentions: Two types of errors have been calculated in the areas detected by the indicator. Fig 11 shows the percentage of errors varying between 6–73%. Dep. 13 shows the least percentage of errors, rounding 6% for both errors in year 2001; 20% for error A and 10% for error B in 1984. This is expected as remote sensing has proven to be a very efficient tool in areas with flat topography where the wetlands are large and well defined [16]. Wetlands in this area have good flood conditions throughout the year, being mainly large lagoons, marshes, salines and rice fields receiving the majority of the water contributions of the basin. Therefore, as results showed, it is an ideal area for wetland detection through RS techniques. The results in this department are really good, in line with, and improving in some cases, those obtained by other wetland indicators [2, 16, 17]. In fact it has achieved similar results to those achieved with SPOT-5 imagery in the PNRC region [18, 19]


Development of an indicator to monitor mediterranean wetlands.

Sanchez A, Abdul Malak D, Guelmami A, Perennou C - PLoS ONE (2015)

Results of Error A and B (%) obtained in the analysis of the wetland indicator in years 1984 and 2001.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4380444&req=5

pone.0122694.g011: Results of Error A and B (%) obtained in the analysis of the wetland indicator in years 1984 and 2001.
Mentions: Two types of errors have been calculated in the areas detected by the indicator. Fig 11 shows the percentage of errors varying between 6–73%. Dep. 13 shows the least percentage of errors, rounding 6% for both errors in year 2001; 20% for error A and 10% for error B in 1984. This is expected as remote sensing has proven to be a very efficient tool in areas with flat topography where the wetlands are large and well defined [16]. Wetlands in this area have good flood conditions throughout the year, being mainly large lagoons, marshes, salines and rice fields receiving the majority of the water contributions of the basin. Therefore, as results showed, it is an ideal area for wetland detection through RS techniques. The results in this department are really good, in line with, and improving in some cases, those obtained by other wetland indicators [2, 16, 17]. In fact it has achieved similar results to those achieved with SPOT-5 imagery in the PNRC region [18, 19]

Bottom Line: A validation process is put in place to compare outcomes with existing local wetland inventories to check the results reliability.The indicator´s results demonstrate an improvement in the level of precision of change detection methods achieved by traditional tools providing reliability up to 95% in main wetland areas.The results confirm that the use of RS techniques improves the precision of wetland detection compared to the use of CLC for wetland monitoring and stress the strong relation between the level of wetland detection and the nature of the wetland areas and the monitoring scale considered.

View Article: PubMed Central - PubMed

Affiliation: European Topic Centre, University of Málaga, Málaga, Spain.

ABSTRACT
Wetlands are sensitive ecosystems that are increasingly subjected to threats from anthropogenic factors. In the last decades, coastal Mediterranean wetlands have been suffering considerable pressures from land use change, intensification of urban growth, increasing tourism infrastructure and intensification of agricultural practices. Remote sensing (RS) and Geographic Information Systems (GIS) techniques are efficient tools that can support monitoring Mediterranean coastal wetlands on large scales and over long periods of time. The study aims at developing a wetland indicator to support monitoring Mediterranean coastal wetlands using these techniques. The indicator makes use of multi-temporal Landsat images, land use reference layers, a 50m numerical model of the territory (NMT) and Corine Land Cover (CLC) for the identification and mapping of wetlands. The approach combines supervised image classification techniques making use of vegetation indices and decision tree analysis to identify the surface covered by wetlands at a given date. A validation process is put in place to compare outcomes with existing local wetland inventories to check the results reliability. The indicator´s results demonstrate an improvement in the level of precision of change detection methods achieved by traditional tools providing reliability up to 95% in main wetland areas. The results confirm that the use of RS techniques improves the precision of wetland detection compared to the use of CLC for wetland monitoring and stress the strong relation between the level of wetland detection and the nature of the wetland areas and the monitoring scale considered.

No MeSH data available.


Related in: MedlinePlus