Abstract 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.

中文翻译：

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在水质时间序列中使用 LEDAPS 进行大气校正的 Landsat 5 图像的评估

摘要 这项工作的主要目标是评估和使用 Landsat TM5 对 1984 年至 2011 年自然公园 Parque Regional del Sureste (PRSE) 内砾石坑池塘水质的演变进行清查和研究。将归一化差异水指数（NDWI）应用于 230 张 Landsat TM5 图像以区分水和非水信息。接下来，将使用 Landsat 生态系统干扰自适应处理系统 (LEDAPS) 进行大气校正的 Landsat TM5 图像得出的表面反射率与实地测量的离水反射率进行比较，显示对源自 Landsat 数据的表面反射率的显着高估。因此，提出了一个新的回归方程，将原位 Secchi 深度 (SD) 测量与 Landsat 5 测量的表面反射率联系起来。此回归得到验证并随后应用于每个图像，为时间序列中的每个像素提供 SD 值。最后，根据经济合作与发展组织 (OECD) 的分类，检索到的 SD 值用于计算水体的营养状态。结果表明，从 1984 年到 2006 年，PRSE 中水体的表面积有所增加，水质也有所改善。