Skip to main content
Passa alla visualizzazione normale.

GIUSEPPE CIRAOLO

Critical analysis of the thermal inertia approach to map soil water content under sparse vegetation and changeable sky conditions

  • Authors: Maltese, A; Capodici, F; Corbari, C; Ciraolo, G; La Loggia, G.; Sobrino, JA
  • Publication year: 2012
  • Type: Proceedings
  • OA Link: http://hdl.handle.net/10447/66424

Abstract

The paper reports a critical analysis of the thermal inertia approach to map surface soil water content on bare and sparsely vegetated soils by means of remotely sensed data. The study area is an experimental area located in Barrax (Spain). Field data were acquired within the Barrax 2011 research project. AHS airborne images including VIS/NIR and TIR bands were acquired both day and night time by the INTA (Instituto Nacional de Técnica Aeroespacial) between the 11th and 13rd of June 2011. Images cover a corn pivot surrounded by bare soil, where a set of in situ data have been collected previously and simultaneously to overpasses. To validate remotely sensed estimations, a preliminary proximity sensing set up has been arranged, measuring spectra and surface temperatures on transects by means of ASD hand-held spectroradiometer and an Everest Interscience radiometric thermometer respectively. These data were collected on two transects: the first one on bare soil and the second from bare to sparsely vegetated soil; soil water content in both transects ranged approximately between field and saturation values. Furthermore thermal inertia was measured using a KD2Pro probe, and surface water content of soil was measured using FDR and TDR probes. This ground dataset was used: 1) to verify if the thermal inertia method can be applied to map water content also on soil covered by sparse vegetation, and 2) to quantify a correction factor of the downwelling shortwave radiation taking into account sky cloudiness effects on thermal inertia assessment. The experiment tests both Xue and Cracknell approximation to retrieve the thermal inertia from a dumped value of the phase difference and the three-temperature approach of Sobrino to estimate the phase difference spatial distribution. Both methods were then applied on the remotely sensed airborne images collected during the following days, in order to obtain the spatial distribution of the surface soil moisture on bare soils and sparse vegetation coverage. Results verify that the thermal inertia method can be applied on sparsely vegetated soil characterized by fractional cover up to ~0.25 (maximum value within this experiment); a lumped value of the phase difference allows a good estimate of the thermal inertia, whereas the comparison with the three-temperature approach did not give conclusive responses because ground radiometric temperatures were not acquired in optimal conditions. Results also show that clear sky only at the time of the remote sensing acquisitions is not a sufficient condition to apply the thermal inertia method. A corrective coefficient taking into account the actual sky cloudiness throughout the day allows accurate estimates of the spatial distribution of the thermal inertia (r2 ~ 0.9) and soil water content (r2 ~ 0.7).