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Land Surface Temperature Retrieval for Agricultural Areas Using a Novel UAV Platform Equipped with a Thermal Infrared and Multispectral Sensor

Heinemann, Sascha and Siegmann, Bastian and Thonfeld, Frank and Muro, Javier and Jedmowski, Christoph and Kemna, Andreas and Kraska, Thorsten and Muller, Onno and Schultz, Johannes and Udelhoven, Thomas and Wilke, Norman and Rascher, Uwe (2020) Land Surface Temperature Retrieval for Agricultural Areas Using a Novel UAV Platform Equipped with a Thermal Infrared and Multispectral Sensor. Remote Sensing, 12 (7), e1075. Multidisciplinary Digital Publishing Institute (MDPI). DOI: 10.3390/rs12071075 ISSN 2072-4292

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Official URL: https://www.mdpi.com/2072-4292/12/7/1075


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.

Item URL in elib:https://elib.dlr.de/135393/
Document Type:Article
Title:Land Surface Temperature Retrieval for Agricultural Areas Using a Novel UAV Platform Equipped with a Thermal Infrared and Multispectral Sensor
AuthorsInstitution or Email of AuthorsAuthor's ORCID iD
Heinemann, SaschaForschungszentrum Jülich GmbHUNSPECIFIED
Siegmann, Bastianbsiegmann (at) igf.uos.deUNSPECIFIED
Thonfeld, FrankFrank.Thonfeld (at) dlr.dehttps://orcid.org/0000-0002-3371-7206
Kraska, ThorstenCampus Klein-Altendorf, Agricultural Faculty, University of BonnUNSPECIFIED
Udelhoven, ThomasUniversity of TrierUNSPECIFIED
Date:27 March 2020
Journal or Publication Title:Remote Sensing
Refereed publication:Yes
Open Access:Yes
Gold Open Access:Yes
In ISI Web of Science:Yes
DOI :10.3390/rs12071075
Page Range:e1075
Publisher:Multidisciplinary Digital Publishing Institute (MDPI)
Keywords:UAV; thermal infrared; multispectral VNIR; LST; emissivity; NDVI thresholds; atmospheric correction; agricultural mapping; low-cost applications
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Earth Observation
DLR - Research area:Raumfahrt
DLR - Program:R EO - Erdbeobachtung
DLR - Research theme (Project):R - Remote sensing and geoscience
Location: Oberpfaffenhofen
Institutes and Institutions:German Remote Sensing Data Center > Land Surface Dynamics
Deposited By: Kraus, Dr. Tanja
Deposited On:24 Jun 2020 11:22
Last Modified:24 Jun 2020 11:22

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