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UAV-Based Land Surface Temperatures and Vegetation Indices Explain and Predict Spatial Patterns of Soil Water Isotopes in a Tropical Dry Forest

Publikation: Beitrag in Fachzeitschrift › Artikel › Forschung › Peer-Review

Autorschaft

  • Matthias Beyer
  • Alberto Iraheta
  • Malkin Gerchow
  • Kathrin Kuehnhammer
  • Ana Claudia Callau-Beyer

Organisationseinheiten

Externe Organisationen

  • Technische Universität Braunschweig
  • Julius Kühn-Institut (JKI) Bundesforschungsinstitut für Kulturpflanzen Braunschweig Messeweg
  • Albert-Ludwigs-Universität Freiburg
  • Bundesanstalt für Geowissenschaften und Rohstoffe (BGR)
  • Leibniz-Zentrum für Agrarlandschaftsforschung (ZALF) e.V.
  • University of Texas at Arlington
  • Universidad de Costa Rica

Details

OriginalspracheEnglisch
Aufsatznummere2024WR037294
FachzeitschriftWater resources research
Jahrgang61
Ausgabenummer2
PublikationsstatusVeröffentlicht - 14 Feb. 2025

Abstract

The spatial variation of soil water isotopes (SWI)—representing the baseline for investigating root water uptake (RWU) depths with water stable isotope techniques—has rarely been investigated. Here, we use spatial SWI depth profile sampling in combination with unmanned aerial vehicle (UAV) based land surface temperature estimates and vegetation indices (VI) in order to improving process understanding of the relationships between the spatial variability of soil water content and soil water isotope patterns with canopy status, represented in the form of VI. We carried out a spatial sampling of 10 SWI depth profiles in a tropical dry forest. UAV data were collected and analyzed to obtain detailed characterization of soil temperature and canopy status. We then performed a statistical analysis between the VI and land surface temperatures with soil water content and SWI values at different spatial resolutions (3 cm–5 m). Best relationships were used for generating soil water isoscapes for the entire study area. Results suggest that soil water content and SWI values are strongly mediated by canopy parameters (VI). Various VI correlate strongly with soil water content and SWI values across all depths. SWI at the surface depend on land surface temperature (R2 of 0.66 for δ18O and 0.64 for δ2H). Strongest overall correlations were found at a spatial resolution of 0.5 m. We speculate that this might be the ideal resolution for spatially characterizing SWI patterns and investigate RWU in tropical dry forest environments. Supporting spatial analyses of SWI with UAV-based approaches might be a future avenue for improving the spatial representation and credibility of such studies.

ASJC Scopus Sachgebiete

Ziele für nachhaltige Entwicklung

Zitieren

UAV-Based Land Surface Temperatures and Vegetation Indices Explain and Predict Spatial Patterns of Soil Water Isotopes in a Tropical Dry Forest. / Beyer, Matthias; Iraheta, Alberto; Gerchow, Malkin et al.
in: Water resources research, Jahrgang 61, Nr. 2, e2024WR037294, 14.02.2025.

Publikation: Beitrag in Fachzeitschrift › Artikel › Forschung › Peer-Review

Beyer, M, Iraheta, A, Gerchow, M, Kuehnhammer, K, Callau-Beyer, AC, Koeniger, P, Dubbert, D, Dubbert, M, Sánchez-Murillo, R & Birkel, C 2025, 'UAV-Based Land Surface Temperatures and Vegetation Indices Explain and Predict Spatial Patterns of Soil Water Isotopes in a Tropical Dry Forest', Water resources research, Jg. 61, Nr. 2, e2024WR037294. https://doi.org/10.1029/2024WR037294
Beyer, M., Iraheta, A., Gerchow, M., Kuehnhammer, K., Callau-Beyer, A. C., Koeniger, P., Dubbert, D., Dubbert, M., Sánchez-Murillo, R., & Birkel, C. (2025). UAV-Based Land Surface Temperatures and Vegetation Indices Explain and Predict Spatial Patterns of Soil Water Isotopes in a Tropical Dry Forest. Water resources research, 61(2), Artikel e2024WR037294. https://doi.org/10.1029/2024WR037294
Beyer M, Iraheta A, Gerchow M, Kuehnhammer K, Callau-Beyer AC, Koeniger P et al. UAV-Based Land Surface Temperatures and Vegetation Indices Explain and Predict Spatial Patterns of Soil Water Isotopes in a Tropical Dry Forest. Water resources research. 2025 Feb 14;61(2):e2024WR037294. doi: 10.1029/2024WR037294
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title = "UAV-Based Land Surface Temperatures and Vegetation Indices Explain and Predict Spatial Patterns of Soil Water Isotopes in a Tropical Dry Forest",
abstract = "The spatial variation of soil water isotopes (SWI)—representing the baseline for investigating root water uptake (RWU) depths with water stable isotope techniques—has rarely been investigated. Here, we use spatial SWI depth profile sampling in combination with unmanned aerial vehicle (UAV) based land surface temperature estimates and vegetation indices (VI) in order to improving process understanding of the relationships between the spatial variability of soil water content and soil water isotope patterns with canopy status, represented in the form of VI. We carried out a spatial sampling of 10 SWI depth profiles in a tropical dry forest. UAV data were collected and analyzed to obtain detailed characterization of soil temperature and canopy status. We then performed a statistical analysis between the VI and land surface temperatures with soil water content and SWI values at different spatial resolutions (3 cm–5 m). Best relationships were used for generating soil water isoscapes for the entire study area. Results suggest that soil water content and SWI values are strongly mediated by canopy parameters (VI). Various VI correlate strongly with soil water content and SWI values across all depths. SWI at the surface depend on land surface temperature (R2 of 0.66 for δ18O and 0.64 for δ2H). Strongest overall correlations were found at a spatial resolution of 0.5 m. We speculate that this might be the ideal resolution for spatially characterizing SWI patterns and investigate RWU in tropical dry forest environments. Supporting spatial analyses of SWI with UAV-based approaches might be a future avenue for improving the spatial representation and credibility of such studies.",
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language = "English",
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issn = "0043-1397",
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TY - JOUR

T1 - UAV-Based Land Surface Temperatures and Vegetation Indices Explain and Predict Spatial Patterns of Soil Water Isotopes in a Tropical Dry Forest

AU - Beyer, Matthias

AU - Iraheta, Alberto

AU - Gerchow, Malkin

AU - Kuehnhammer, Kathrin

AU - Callau-Beyer, Ana Claudia

AU - Koeniger, Paul

AU - Dubbert, David

AU - Dubbert, Maren

AU - Sánchez-Murillo, Ricardo

AU - Birkel, Christian

N1 - Publisher Copyright: © 2025. The Author(s).

PY - 2025/2/14

Y1 - 2025/2/14

N2 - The spatial variation of soil water isotopes (SWI)—representing the baseline for investigating root water uptake (RWU) depths with water stable isotope techniques—has rarely been investigated. Here, we use spatial SWI depth profile sampling in combination with unmanned aerial vehicle (UAV) based land surface temperature estimates and vegetation indices (VI) in order to improving process understanding of the relationships between the spatial variability of soil water content and soil water isotope patterns with canopy status, represented in the form of VI. We carried out a spatial sampling of 10 SWI depth profiles in a tropical dry forest. UAV data were collected and analyzed to obtain detailed characterization of soil temperature and canopy status. We then performed a statistical analysis between the VI and land surface temperatures with soil water content and SWI values at different spatial resolutions (3 cm–5 m). Best relationships were used for generating soil water isoscapes for the entire study area. Results suggest that soil water content and SWI values are strongly mediated by canopy parameters (VI). Various VI correlate strongly with soil water content and SWI values across all depths. SWI at the surface depend on land surface temperature (R2 of 0.66 for δ18O and 0.64 for δ2H). Strongest overall correlations were found at a spatial resolution of 0.5 m. We speculate that this might be the ideal resolution for spatially characterizing SWI patterns and investigate RWU in tropical dry forest environments. Supporting spatial analyses of SWI with UAV-based approaches might be a future avenue for improving the spatial representation and credibility of such studies.

AB - The spatial variation of soil water isotopes (SWI)—representing the baseline for investigating root water uptake (RWU) depths with water stable isotope techniques—has rarely been investigated. Here, we use spatial SWI depth profile sampling in combination with unmanned aerial vehicle (UAV) based land surface temperature estimates and vegetation indices (VI) in order to improving process understanding of the relationships between the spatial variability of soil water content and soil water isotope patterns with canopy status, represented in the form of VI. We carried out a spatial sampling of 10 SWI depth profiles in a tropical dry forest. UAV data were collected and analyzed to obtain detailed characterization of soil temperature and canopy status. We then performed a statistical analysis between the VI and land surface temperatures with soil water content and SWI values at different spatial resolutions (3 cm–5 m). Best relationships were used for generating soil water isoscapes for the entire study area. Results suggest that soil water content and SWI values are strongly mediated by canopy parameters (VI). Various VI correlate strongly with soil water content and SWI values across all depths. SWI at the surface depend on land surface temperature (R2 of 0.66 for δ18O and 0.64 for δ2H). Strongest overall correlations were found at a spatial resolution of 0.5 m. We speculate that this might be the ideal resolution for spatially characterizing SWI patterns and investigate RWU in tropical dry forest environments. Supporting spatial analyses of SWI with UAV-based approaches might be a future avenue for improving the spatial representation and credibility of such studies.

KW - isoscapes

KW - land surface temperature

KW - plant water uptake

KW - thermal infrared

KW - tropical dry forest

KW - unmanned aerial vehicle

KW - vegetation index

KW - water isotopes

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U2 - 10.1029/2024WR037294

DO - 10.1029/2024WR037294

M3 - Article

AN - SCOPUS:85218925706

VL - 61

JO - Water resources research

JF - Water resources research

SN - 0043-1397

IS - 2

M1 - e2024WR037294

ER -