Assessment of Landsat 5 Images Atmospherically Corrected with LEDAPS in Water Quality Time Series

• Published in: Canadian journal of remote sensing Vol. 45; no. 5; pp. 691 - 706
• Main Authors: Carolina Echavarría-Caballero, José Antonio Domínguez-Gómez, Concepción González-García, María Jesús García-García
• Format: Journal Article
• Language: English
• Published: Taylor & Francis Group 03-09-2019
• ISSN: 1712-7971
• DOI: 10.1080/07038992.2019.1674136

The main objective of this work is to assess and use Landsat TM5 for the inventory and study of the evolution of water quality in gravel pit ponds within the natural park, Parque Regional del Sureste (PRSE), from 1984 to 2011. First, the normalized difference water index (NDWI) was applied to 230 Landsat TM5 images to distinguish water and non-water information. Next, the surface reflectance derived from Landsat TM5 images atmospherically corrected with the Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) was compared to water-leaving reflectance measured in the field, showing a significant overestimation of surface reflectance derived from Landsat data. Thus, a new regression equation was proposed linking the in situ Secchi depth (SD) measurements to surface reflectance measured by Landsat 5. This regression was validated and subsequently applied to every image, providing an SD value for each pixel in the time series. Finally, the retrieved SD values were used to compute the trophic state of water bodies according to the Organization for Economic Co-operation and Development (OECD) classification. The results show an increase in the surface area of water bodies in the PRSE from 1984 to 2006, as well as an improvement in their water quality.