Post on 01-Aug-2020
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EGU2020-8098: Mapping the dynamics of the Lagunas de Ruidera wetland (Spain) using remote sensing
Mapping the dynamics of the Lagunas de Ruidera wetland (Spain) using remote sensing
Eulogio Pardo-Iguzquiza1, David Pulido-Velazquez2, Antonio-Juan Collados-Lara2, and Leticia Baena-Ruiz2
1Instituto Geológico y Minero de España, Ríos Rosas, 23, 28003 Madrid (Spain). e-mail: e.pardo@igme.es
2Instituto Geológico y Minero de España, Urb. Alcázar del Genil, 4. Edificio Zulema Bajo, 18006, Granada (Spain). e-mails: d.pulido@igme.es; aj.collados@igme.es; l.baena@igme.es
© 2020 Authors. All rights reserved.
Case study Lagunas de Ruidera Wetland (Spain)
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EGU2020-8098: Mapping the dynamics of the Lagunas de Ruidera wetland (Spain) using remote sensing
Data LANDSAT 5, 7, and 8 images (1984 to 2015)
MODIS Surface Reflectance (2000 to 2015)
Objectives
Mapping the dynamic of the wetland
Study correlations with others variables (Precipitation, Aquifer discharge)
Methodology
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EGU2020-8098: Mapping the dynamics of the Lagunas de Ruidera wetland (Spain) using remote sensing
Supervised Classification Method: pixels of known identity, located within training or calibration areas, are used to classify pixels of unknown identity
1) Calibration area: pixels of the reservoir close to the dam
Cw is the median surface reflectance (SR) of these pixels
If SR > Cwr then the pixel is covered by water
2) Optimal Calibration area:
High value of the number of days with SR>Cw
Methodology
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EGU2020-8098: Mapping the dynamics of the Lagunas de Ruidera wetland (Spain) using remote sensing
2) Optimal Calibration area:
High value of the number of days with SR>Cw
Methodology
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EGU2020-8098: Mapping the dynamics of the Lagunas de Ruidera wetland (Spain) using remote sensing
2) Optimal Calibration area
Poor efficiency of the algorithm
Why?
Day 1995-05-06
Estimated surface of water
Methodology
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EGU2020-8098: Mapping the dynamics of the Lagunas de Ruidera wetland (Spain) using remote sensing
2) Optimal Calibration area
Day:
Poor efficiency of the algorithm
Why?
Different Cw for the two calibration areas
In general Cw of the reservoir is lower than Cw of the lagoon
Methodology
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EGU2020-8098: Mapping the dynamics of the Lagunas de Ruidera wetland (Spain) using remote sensing
3) Calibration using both areas
and
Cw as percentil 99
Good efficiency of the algorithm
Day 1995-05-06
Estimated surface of water
Methodology
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EGU2020-8098: Mapping the dynamics of the Lagunas de Ruidera wetland (Spain) using remote sensing
3) Elimination of images with errors or clouds
Used filter Clouds < 15000 pixels Cw < 25 (range 0 a 255) 3000 pixels < Water< 7000 pixels
Methodology
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EGU2020-8098: Mapping the dynamics of the Lagunas de Ruidera wetland (Spain) using remote sensing
3) Creation of a mask to avoid errors:
Considering all the pixels where water was detected for the entire period and filtering by visual inspection
Possible pixels with water
Results
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EGU2020-8098: Mapping the dynamics of the Lagunas de Ruidera wetland (Spain) using remote sensing
Daily dynamics
Results
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EGU2020-8098: Mapping the dynamics of the Lagunas de Ruidera wetland (Spain) using remote sensing
Monthly dynamics
Results
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EGU2020-8098: Mapping the dynamics of the Lagunas de Ruidera wetland (Spain) using remote sensing
Yearly mean
Results
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EGU2020-8098: Mapping the dynamics of the Lagunas de Ruidera wetland (Spain) using remote sensing
Mean year at monthly scale
Results Spatial distribution of the maximum and minimum during the period studied
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EGU2020-8098: Mapping the dynamics of the Lagunas de Ruidera wetland (Spain) using remote sensing
5649 pixels 4966 pixels 4900 pixels
5435 pixels 4571 pixels 4243 pixels
4943 pixels 4678 pixels
6804 pixels 3001 pixels
Results
Spatial distribution water surface dynamic 2000
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EGU2020-8098: Mapping the dynamics of the Lagunas de Ruidera wetland (Spain) using remote sensing
5649 pixels 4966 pixels 4900 pixels
5435 pixels 4571 pixels 4243 pixels
4943 pixels 4852 pixels 4678 pixels