EGU2020-19560
https://doi.org/10.5194/egusphere-egu2020-19560
EGU General Assembly 2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Soil Moisture Retrievals from Unmanned Aerial Systems (UAS)

ruodan zhuang1, Salvatore Manfreda2, Yijian Zeng3, Zhongbo Su3,4, Nunzio Romano5,6, Eyal Ben Dor7, Antonino Maltese8, Fulvio Capodici8, Antonio Paruta8, Paolo Nasta5, Nicolas Francos7, Giuseppe Ciraolo8, Brigitta Szabó9, János Mészáros9, and George P. Petropoulos10
ruodan zhuang et al.
  • 1Department of European and Mediterranean Cultures, Architecture, Environment, Cultural Heritage, University of Basilicata, 75100 Matera, Italy (ruodan.zhuang@unibas.it)
  • 2Department of Civil, Architectural and Environmental Engineering, Federico II University, via Claudio 21, 80125 Napoli, Italy (salvatore.manfreda@unibas.it)
  • 3Faculty of Geo-Information Science and Earth Observation, University of Twente, Hengelosestraat 99, Enschede 7514 AE, The Netherlands (y.zeng@utwente.nl; z.su@utwente.nl)
  • 4Key Laboratory of Subsurface Hydrology and Ecological Effect in Arid Region of Ministry of Education, School of Water and Environment, Chang’an University, Xi’an, 710054, China (z.su@utwente.nl)
  • 5Department of Agricultural Sciences, AFBE Division, University of Napoli Federico II, Portici (Napoli), Italy (nunzio.romano@unina.it; paolo.nasta@unina.it)
  • 6Interdepartmental Center for Environmental Research (C.I.R.AM.), University of Napoli Federico II, Napoli, Italy (nunzio.romano@unina.it)
  • 7Department of Geography and Human Environment, Tel Aviv University (TAU), Tel Aviv 6997801, Israel (bendor@tauex.tau.ac.il)
  • 8Department of Engineering, University of Palermo, 90128 Palermo, Italy (antonino.maltese@unipa.it)
  • 9Institute for Soil Sciences and Agricultural Chemistry, Centre for Agricultural Research, H-1022 Budapest, Hungary (toth.brigitta@agrar.mta.hu; messer.janos@gmail.com)
  • 10School of Mineral Resources Engineering, Technical University of Crete, Kounoupidiana Campus, 73100, Chania, Greece (petropoulos.george@gmail.com)

Quantification of the spatial and temporal behavior of soil moisture is vital for understanding water availability in agriculture, ecosystems research, river basin hydrology and water resources management. Unmanned Aerial Systems (UAS) offer a great potential in monitoring this parameter at sub-meter level and at relatively low cost. The standardization of operational procedures for soil moisture monitoring with UAS can be beneficial to understanding and quantify the quality of retrieved soil moisture (e.g., from different platforms and sensors).

In this study, soil moisture retrieved from UAS using different retrieval algorithms was compared to collocated ground measurements. The thermal inertia model builds upon the dependence of the thermal diffusion on soil moisture. The soil thermal inertia is quantified by processing visible and near-infrared (VIS-NIR) and thermal infrared (TIR) images, acquired at two different times of a day. The temperature–vegetation trapezoidal model is also used to map soil moisture over vegetated pixels. This trapezoidal model depicts the soil moisture dependence of the surface energy balance. The comparison of the two algorithms helps define a preliminary standard procedure for retrieving soil moisture with UAS.

As a case study, a typical cropland area with olive orchard, cherry and walnut trees in the region of Monteforte Cilento (Italy, Salerno) is used, where optical and thermal images and in situ data were simultaneously acquired. In the Alento observatory, long-term studies on vadose zone hydrology have been conducting across a range of spatial scales. Our findings provide an important contribution towards improving our knowledge on evaluating the ability of UAS to map soil moisture, in support of sustainable natural resources management and climate change studies.

This research is a part of EU COST-Action “HARMONIOUS: Harmonization of UAS techniques for agricultural and natural ecosystems monitoring”.

Keywords: soil moisture, Unmanned Aerial Systems, thermal inertia, HARMONIOUS

How to cite: zhuang, R., Manfreda, S., Zeng, Y., Su, Z., Romano, N., Ben Dor, E., Maltese, A., Capodici, F., Paruta, A., Nasta, P., Francos, N., Ciraolo, G., Szabó, B., Mészáros, J., and Petropoulos, G. P.: Soil Moisture Retrievals from Unmanned Aerial Systems (UAS), EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-19560, https://doi.org/10.5194/egusphere-egu2020-19560, 2020

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  • CC1: Comment on EGU2020-19560, Solomon Isiorho, 07 May 2020

    I think this is interesting and would have wide applications in developing nations. Do you take into account the landuse...by that I mean how the land has chnaged with time?

     

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