Abstract
Soil moisture (SM) plays a fundamental role in the terrestrial water cycle and in agriculture, with key applications such as the monitoring of crop growing and hydrogeological management. In this study, a calibration procedure was applied to estimate SM based on the integration of in situ and airborne thermal remote sensing data. To this aim, on April 2018, two airborne campaigns were carried out with the TASI-600 multispectral thermal sensor on the Petacciato (Molise, Italy) area. Simultaneously, soil samples were collected in different agricultural fields of the study area to determine their moisture content and the granulometric composition. A WorldView 2 high-resolution visible-near infrared (VNIR) multispectral satellite image was acquired to calculate the albedo of the study area to be used together with the TASI images for the estimation of the apparent thermal inertia (ATI). Results show a good correlation (R2 = 0.62) between the estimated ATI and the SM of the soil samples measured in the laboratory. The proposed methodology has allowed us to obtain a SM map for bare and scarcely vegetated soils in a wide agricultural area in Italy which concerns cyclical hydrogeological instability phenomena.
Highlights
Soil moisture (SM) is a variable that is influenced by a wide range of processes that occur in the land–atmosphere interface, including water infiltration, water outflow, evaporation, heat and gas exchange, infiltration of solutes, erosion, etc
We propose a simplified approach based on the integration of in situ measurements with reflectance and thermal remote sensing data to extend the SM information to a wide area characterized by bare soils and low vegetated agricultural fields
We present a first attempt to SM mapping for bare and scarcely vegetated soils by
Summary
Soil moisture (SM) is a variable that is influenced by a wide range of processes that occur in the land–atmosphere interface, including water infiltration, water outflow, evaporation, heat and gas exchange, infiltration of solutes, erosion, etc. Different studies have demonstrated that SM is a function of different processes (precipitation, evapotranspiration, etc.) and is influenced by various factors, e.g., topography, land use, and soil texture. SM is highly varied in space and time and across different scales [1,2,3,4,5]. Many authors has highlighted the importance of measuring and monitoring SM and, in particular, the water in the upper 10 cm of soil at different spatial scales [2,3,4,5]. Some practical applications of SM retrieval can be found in the works of [9,10]
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