A Geostatistical Approach to Map Near-Surface Soil Moisture Through Hyperspatial Resolution Thermal Inertia

Abstract

Thermal inertia has been applied to map soil water content exploiting remote sensing data in the short and long wave regions of the electromagnetic spectrum. Over the last years, optical and thermal cameras were sufficiently miniaturized to be loaded onboard of unmanned aerial systems (UASs), which provide unprecedented potentials to derive hyperspatial resolution thermal inertia for soil water content mapping. In this study, we apply a simplification of thermal inertia, the apparent thermal inertia (ATI), over pixels where underlying thermal inertia hypotheses are fulfilled (unshaded bare soil). Then, a kriging algorithm is used to spatialize the ATI to get a soil water content map. The proposed method was applied to an experimental area of the Alento River catchment, in southern Italy. Daytime radiometric optical multispectral and day and nighttime radiometric thermal images were acquired via a UAS, while in si t u soil water content was measured through the thermo-gravimetric and time domain reflectometry (TDR) methods. The determination coefficient between ATI and soil water content measured over unshaded bare soil was 0.67 for the gravimetric method and 0.73 for the TDR. After interpolation, the correlation slightly decreased due to the introduction of measurements on vegetated or shadowed positions (r 2 = 0.59 for gravimetric method; r 2 = 0.65 for TDR). The proposed method shows promising results to map the soil water content even over Manuscript

Unmanned Aerial Vehicles in Hydrology and Water Management: Applications, Challenges, and Perspectives

“…A survey of recent studies indicate the use of UAV-acquired hyper-spatial imagery, including thermal techniques (Paruta et al, 2020), optical data , and their synergy (Hassan- Esfahani et al, 2015Esfahani et al, , 2017Wang et al, 2018;Wigmore & Mark, 2018), and GPR systems/microwave (Wu, Li, et al, 2019;Wu, Rodriguez, et al, 2019) to estimate soil moisture content. Paruta et al ( 2020) used a Phantom 3 quadcopter with a FLIR Tau2 thermal camera and 12.4 MP CMOS sensor RGB camera to capture hyper-spatial images subsequently processed using the apparent thermal inertia method.…”

“…UAV‐based data products are generated within a broad timing range, and depending on the specific workflow; this data generation time could vary from few seconds to hours and days (see e.g., Tosi et al., 2020 for in situ and near real‐time image velocimetry processing taking seconds to compute velocities in rivers). Pre‐processing, processing, and post‐processing phases are usually performed later in a processing center (see, e.g., Dal Sasso et al., 2021; Paruta et al., 2020), not at the moment of data acquisition. However, recent attempts—incorporating processing units’ in situ—are changing this modus operandis with views to real‐time computations.…”

“…A survey of recent studies indicate the use of UAV‐acquired hyper‐spatial imagery, including thermal techniques (Paruta et al., 2020), optical data (Lee, Yoon, et al., 2016), and their synergy (Hassan‐Esfahani et al., 2015, 2017; Wang et al., 2018; Wigmore & Mark, 2018), and GPR systems/microwave (Wu, Li, et al., 2019; Wu, Rodriguez, et al., 2019) to estimate soil moisture content. Paruta et al.…”

“…Paruta et al. (2020) used a Phantom 3 quadcopter with a FLIR Tau2 thermal camera and 12.4 MP CMOS sensor RGB camera to capture hyper‐spatial images subsequently processed using the apparent thermal inertia method. Similar to other findings in bare soils, their study discerned a strong correlation ( R 2 = 0.7) between soil moisture and apparent thermal inertia for un‐shaded non‐vegetated pixels.…”

Mapping Water Infiltration Rate Using Ground and UAV Hyperspectral Data: A Case Study of Alento, Italy

“…The Alento catchment has long been a critical observatory for monitoring climate change, hydrological processes, anthropogenic disturbances, drought conditions, etc. [34,37,38]. The Alento River catchment is located in the Campania region (Salerno Province, Italy).…”