Paper
28 January 2002 Relation between bulk temperature based on in-situ temperature profiles and NOAA-AVHRR sea surface temperature data for Lake Constance
Sabine Thiemann, Clivia Haese, Thomas Heege
Author Affiliations +
Proceedings Volume 4542, Remote Sensing for Agriculture, Ecosystems, and Hydrology III; (2002) https://doi.org/10.1117/12.454195
Event: International Symposium on Remote Sensing, 2001, Toulouse, France
Abstract
The determination of phytoplankton primary production is one key future application of remote sensing data in Lake Constance. One of the main influencing factors of the maximum photosythetic rate in waters is the bulk temperature. From satellite data like NOAA-AVHRR, the skin temperature can be retrieved at high temporal resolution. However, as parameter for primary production, the bulk temperature in the mixed water layer is needed. In this study, an extensive multi-temporal set of AVHRR data is used to set up a relationship between lake skin temperature from satellite data and the bulk temperature in 0.1 m depth from in situ temperature profiles. Temperature profiles exist for a fixed station in Lake Constance in 20 min intervals over the last twelve years. From 245 cloudless AVHRR-scenes for the years 1995 until 1999, the skin temperature was derived using the split window technique. Different approaches of this technique are intercompared for their accuracy for Lake Constance. In a future step, the bulk temperature in the upper 4 m and the depth of the mixed layer will be determined for input in a primary production model. Multiple regression analysis as well as a neural network approach will be used for the prediction of the bulk temperature from the skin temperature for Lake Constance.
© (2002) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Sabine Thiemann, Clivia Haese, and Thomas Heege "Relation between bulk temperature based on in-situ temperature profiles and NOAA-AVHRR sea surface temperature data for Lake Constance", Proc. SPIE 4542, Remote Sensing for Agriculture, Ecosystems, and Hydrology III, (28 January 2002); https://doi.org/10.1117/12.454195
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KEYWORDS
Satellites

Algorithm development

Temperature metrology

Skin

Neural networks

Calibration

Remote sensing

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