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5. Würzburger Wirtschaftssymposium, 20.11.2008 Deutsche Erfindungen verändern die Welt - heute wie vor 500 Jahren. Von Buchdruck, über Dieselmotor, Glühbirne bis hin zu Airbag, Aspirin, Dübel, Fernseher und mp3-Format. Alleine dieser bescheidene Überblick des Phänomens “Made in Germany” lässt den Betrachter die Bedeutung und das Potenzial von Innovationen am Standort Deutschland schnell erkennen. Experten aus Wirtschaft, Politik und Gesellschaft setzten sich am 20.11.2008 unter der Leitfrage: “Innovationen – Performancetreiber und nachhaltiger Wirtschaftsmotor in Deutschland?” mit der Bedeutung von Innovationen für den Standort Deutschland auseinander. Die Festschrift rundet - neben Interviews mit und Gastbeiträgen von Referenten der Veranstaltung - das 5. Würzburger Wirtschaftssymposium mit Stellungnahmen und Beiträgen renommierter Experten ab. Zu Wort kommen dabei Jungunternehmer ebenso wie Wissenschaftler der Universität Würzburg und Vertreter externer Organisationen.
Land surface temperature (LST) is a fundamental parameter within the system of the Earth’s surface and atmosphere, which can be used to describe the inherent physical processes of energy and water exchange. The need for LST has been increasingly recognised in agriculture, as it affects the growth phases of crops and crop yields. However, challenges in overcoming the large discrepancies between the retrieved LST and ground truth data still exist. Precise LST measurement depends mainly on accurately deriving the surface emissivity, which is very dynamic due to changing states of land cover and plant development. In this study, we present an LST retrieval algorithm for the combined use of multispectral optical and thermal UAV images, which has been optimised for operational applications in agriculture to map the heterogeneous and diverse agricultural crop systems of a research campus in Germany (April 2018). We constrain the emissivity using certain NDVI thresholds to distinguish different land surface types. The algorithm includes atmospheric corrections and environmental thermal emissions to minimise the uncertainties. In the analysis, we emphasise that the omission of crucial meteorological parameters and inaccurately determined emissivities can lead to a considerably underestimated LST; however, if the emissivity is underestimated, the LST can be overestimated. The retrieved LST is validated by reference temperatures from nearby ponds and weather stations. The validation of the thermal measurements indicates a mean absolute error of about 0.5 K. The novelty of the dual sensor system is that it simultaneously captures highly spatially resolved optical and thermal images, in order to construct the precise LST ortho-mosaics required to monitor plant diseases and drought stress and validate airborne and satellite data.