Retrieval of Water Constituents from Hyperspectral In-Situ Measurements under Variable Cloud Cover—A Case Study at Lake Stechlin (Germany)

Anna Göritz,Jens Nejstgaard,Rüdiger Röttgers,Sebastian Riedel,Hans-Peter Grossart,Peter Gege,Stella Berger,Christian Utschig

doi:10.3390/rs10020181

Abstract

Remote sensing and field spectroscopy of natural waters is typically performed under clear skies, low wind speeds and low solar zenith angles. Such measurements can also be made, in principle, under clouds and mixed skies using airborne or in-situ measurements; however, variable illumination conditions pose a challenge to data analysis. In the present case study, we evaluated the inversion of hyperspectral in-situ measurements for water constituent retrieval acquired under variable cloud cover. First, we studied the retrieval of Chlorophyll-a (Chl-a) concentration and colored dissolved organic matter (CDOM) absorption from in-water irradiance measurements. Then, we evaluated the errors in the retrievals of the concentration of total suspended matter (TSM), Chl-a and the absorption coefficient of CDOM from above-water reflectance measurements due to highly variable reflections at the water surface. In order to approximate cloud reflections, we extended a recent three-component surface reflectance model for cloudless atmospheres by a constant offset and compared different surface reflectance correction procedures. Our findings suggest that in-water irradiance measurements may be used for the analysis of absorbing compounds even under highly variable weather conditions. The extended surface reflectance model proved to contribute to the analysis of above-water reflectance measurements with respect to Chl-a and TSM. Results indicate the potential of this approach for all-weather monitoring.

Highlights

Recent advances in sensor technology and progress in algorithm development open new perspectives for inland water remote sensing
In the present case study, we investigated the potential of water constituent retrieval from hyperspectral in-situ measurements acquired under variable cloud cover without additional Lsky measurements
We examined which of the parameters of the resulting four component (4C) model need to be treated as fit parameters during inversion in order to mimic the surface reflectance

Summary

Introduction

Recent advances in sensor technology and progress in algorithm development open new perspectives for inland water remote sensing. Along with an increasing need for water quality monitoring and holistic views on globally distributed inland water ecosystems, remote sensing applications are becoming an important complementary approach to classic monitoring routines [1,2,3,4]. While spaceborne optical remote sensing requires mostly clear sky conditions, airborne and in-situ (above- and in-water) measurements can, in principle, be performed on cloudy days as well. A major challenge for this kind of application is that retrieval algorithms need to account for the variability in the illumination conditions. Changes in illumination can lead to intense and highly variable water surface reflections, which depend on several factors such as viewing geometry, sun position, angular distribution of the sky radiance (Lsky), and on the slope distribution of the surface (waves) [13]. Since reflections of direct sunlight (sun glint) and clouds can be an order of magnitude higher than the water leaving radiance itself [14,15], their effect needs to be minimized during data acquisition or corrected very accurately during data analysis

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Conclusion