Using Landsat image time series to study a small water body in Northern Spain.
Ramsar Convention and EU Water Framework Directive are two international agreements focused on the conservation and achievement of good ecological and chemical status of wetlands. Wetlands are important ecosystems holding many plant and animal communities. Their environmental status can be characterised by the quality of their water bodies. Water quality can be assessed from biophysical parameters (such as Chlorophyll-a concentration ([Chla]), water surface temperature and transparency) in the deeper or lacustrine zone, or from bioindicators (as submerged aquatic vegetation) in the shallow or palustrine zone. This paper proves the use of Landsat time series to measure the evolution of water quality parameters and the environmental dynamics of a small water body (6.57 ha) in a Ramsar wetland (Arreo Lake in the North of Spain). Our results show that Landsat TM images can be used to describe periodic behaviours such as the water surface temperature or the phenologic state of the submerged vegetation (through normalized difference vegetation index, NDVI) and thus detect anomalous events. We also show how [Chla] and transparency can be measured in the lacustrine zone using Landsat TM images and an algorithm adjusted for mesotrophic Spanish lakes, and the resulting values vary in time in accordance with field measurements (although these were not synchronous with the images). The availability of this algorithm also highlights anomalies in the field data series that are found to be related with the concentration of suspended matter. All this potential of Landsat imagery to monitor small water bodies in wetlands can be used for hindcasting of past evolution of these wetlands (dating back to 1970s) and will be also useful in the future thanks to the Landsat continuity mission and the Operational Land Imager.
Departamento de Física Matemática y de Fluidos, Facultad de Ciencias, UNED, c/Senda del Rey, 9, 28040, Madrid, Spain.
Y
Y
Chao Rodríguez
A
A
el Anjoumi
J A
JA
Domínguez Gómez
D
D
Rodríguez Pérez
E
E
Rico
D002734:Chlorophyll / Q000032:analysis; D000077194:Chlorophyll A; D004784:Environmental Monitoring / Q000379:methods*; D060106:Lakes / Q000737:chemistry*; D010944:Plants; D058998:Remote Sensing Technology; D063809:Satellite Imagery; D018531:Spacecraft; D013030:Spain; D053833:Wetlands
D002734:Chlorophyll; D000077194:Chlorophyll A