Assessing spatial variability of soil water content through thermal inertia and NDVI

Abstract

AVHRR (Advanced Very High Resolution Radiometer on board NOAA satellites) data are considered here to evaluate the possibility of using the surface temperature as an indicator of the soil/canopy water content at the short timescale. This is obtained by means of an indirect approach based on a simplified soil-atmosphere energy balance. The techniques provide sufficiently detailed coverage of the processes in terms of the time and spatial scale with respect to hydrological applications. Two different approaches have been tried: the first based on thermal inertia measurements (Xue & Cracknell, 1995) 1 through ATI (Apparent Thermal Inertia), the second based on surface temperature (LST) and vegetation indices (NDVI), with the TVDI (Temperature Vegetation Dryness Index) suggested by Sandholt et al. (2002) 2. Both techniques were used in detecting moist areas in a single image (or day/night images), and in multitemporal multitemporal applications. In particular, a new cloud detection algorithm, based on the bimodal frequency distribution of the infrared brightness temperatures (Ch 5 AVHRR) when clouds affect the image, has been proposed for ATI. As regards TVDI, a modified technique has been proposed for fixing the warm edge of the triangle based on the detection of the extreme dryness conditions on a monthly basis. The modified TVDI has been tested in comparison with an antecedent precipitation index (API) for moisture detection in single images. The substitution of day/night land surface temperature differences instead of noon temperatures in the "triangle method" has been also tested with good results in the multitemporal approach. Application of the proposed techniques can allow one to track the evolution of soil moisture in space and time and to improve the knowledge on the relationship between vegetation (NDVI) and soil moisture dynamics.

Soil moisture retrieval using thermal inertia, determined with visible and thermal spaceborne data, validated for European forests

“…In an attempt to underpin our validation results of soil moisture retrieval using thermal inertia, with data cited in the literature, optical and thermal approaches can only scarcely be found (Claps and Laguardia, 2004;Gillies et al, 1997;Liu et al, 2003;Nemani et al, 1993;Sandholt et al, 2002 among them). In many cases even the most cited validation results originate from radar applications (Ceballos et al, 2005;De Ridder, 2000;Narayan et al, 2004;Quesney et al, 2000;Scipal et al, 2005;Wagner et al, 1999;Wagner et al, 2003).…”

“…thermal inertia, albedo and surface temperature differences. A much more simple formulation of TI is the apparent thermal inertia (ATI) which is derived directly from multi-spectral remote sensing imagery (Claps & Laguardia, 2004;Tramutoli et al, 2000). We adopted the approach of Mitra and Majumdar (2004) to infer ATI since this approach is easily implemented operationally and is obtained by measurements of spectral surface albedo α 0 and the diurnal temperature range ΔLST 0 :…”

Satellite remote sensing applications for surface soil moisture monitoring: A review

“…A simple surrogate of TI is the apparent thermal inertia (ATI), which can be derived directly from multispectral remote sensing imagery (Tramutoli et al, 2000;Claps and Laguardia, 2004;Verstraeten et al, 2006), by measurements of spectral surface albedo α and the diurnal temperature range ΔT:…”

A Synergetic Algorithm for Mid-Morning Land Surface Soil and Vegetation Temperatures Estimation Using MSG-SEVIRI Products and TERRA-MODIS Products

“…It is a key parameter in a variety of scientific studies including climatology, hydrology, ecology, biogeology, etc. [2][3][4][5]. Remote sensing techniques are a unique way for deriving the contiguous surface temperature on regional or global scale, and two spectral regions, which are referred to as thermal infrared (TIR, 3-15 μm) and microwave (1 mm-1 m), are commonly used to retrieve regional LST [6].…”