Modeling and Inversion in Thermal Infrared Remote Sensing over Vegetated Land Surfaces

Abstract

U n c o r r e c t e d P r o o f 244 F. Jacob et al.Abstract Thermal Infra Red (TIR) Remote sensing allow spatializing various land surface temperatures: ensemble brightness, radiometric and aerodynamic temperatures, soil and vegetation temperatures optionally sunlit and shaded, and canopy temperature profile. These are of interest for monitoring vegetated land surface processes: heat and mass exchanges, soil respiration and vegetation physiological activity. TIR remote sensors collect information according to spectral, directional, temporal and spatial dimensions. Inferring temperatures from measurements relies on developing and inverting modeling tools. Simple radiative transfer equations directly link measurements and variables of interest, and can be analytically inverted. Simulation models allow linking radiative regime to measurements. They require indirect inversions by minimizing differences between simulations and observations, or by calibrating simple equations and inductive learning methods. In both cases, inversion consists of solving an ill posed problem, with several parameters to be constrained from few information. Brightness and radiometric temperatures have been inferred by inverting simulation models and simple radiative transfer equations, designed for atmosphere and land surfaces. Obtained accuracies suggest refining the use of spectral and temporal information, rather than innovative approaches. Forthcoming challenge is recovering more elaborated temperatures. Soil and vegetation components can replace aerodynamic temperature, which retrieval seems almost impossible. They can be inferred using multiangular measurements, via simple radiative transfer equations previously parameterized from simulation models. Retrieving sunlit and shaded components or canopy temperature profile requires inverting simulation models. Then, additional difficulties are the influence of thermal regime, and the limitations of spaceborne observations which have to be along track due to the temperature fluctuations. Finally, forefront investigations focus on adequately using TIR information with various spatial resolutions and temporal samplings, to monitor the considered processes with adequate spatial and temporal scales. IntroductionUsing TIR remote sensing for environmental issues have been investigated the last three decades. This is motivated by the potential of the spatialized information for documenting the considered processes within and between the Earth system components: cryosphere [1-2], atmosphere [3][4][5][6], oceans [7][8][9], and land surfaces [10]. For the latter, TIR remote sensing is used to monitor forested areas [11][12][13][14], urban areas [15][16][17], and vegetated areas. We focus here on vegetated areas, natural and cultivated. The monitored processes are related to climatology, meteorology, hydrology and agronomy: (1) radiation, heat and water transfers at the soil-vegetation-atmosphere interface [18][19][20][21][22][23][24]; (2) interactions between land surface and atmospheric boundary la...

Combined use of FORMOSAT-2 images with a crop model for biomass and water monitoring of permanent grassland in Mediterranean region

“…In addition, these observations must be acquired with a fine time step for following irrigation practices (<10 days). Numerous studies have discussed about the potentialities of thermal or microwave data for assessing soil moisture variability (Jacob et al, 2008;Wigneron et al, 1999). But currently, there are no satellites which provide similar temporal and spatial resolution such as FORMOSAT-2 in this spectral range.…”

“…A higher resolution was achieved by Landsat (TM: 120 m, ETM: 60 m), and ASTER (90 m) but the time revisit is low (16 days), and do not allow to detect grassland irrigation occurring with on average every 10 days in our study region. There is currently a strong demand from the scientific community for having thermal sensors with finer resolution, such as the former European Space Agency candidate Earth Explorer mission, SPECTRA mission (Jacob et al, 2008), or future MISTIGRI mission currently in study by CNES (Garcia Moreno et al, 2009) or HyspIRI (see http://hyspiri.jpl.nasa.gov/). It should be noted also the future high-temporal SAR data eg Sentinel-1, (see http://space.skyrocket.de/index frame.htm?http://space.…”

Assessing the Potentialities of FORMOSAT-2 Data for Water and Crop Monitoring at Small Regional Scale in South-Eastern France

“…A higher resolution was achieved by Landsat (TM: 120m, ETM: 60m), and ASTER (90m) but the time revisit is low (16 days), and do not allow to detect for example meadow irrigation occurring every 11 days in our region. There is currently a strong demand from the scientific community for having thermal sensors with finer resolution, such as the former European SPECTRA mission which yielded the Chinese SPECTLA mission (Menenti, 2005 personal communication), or future MISTIGRI mission currently in study by CNES [34]. Meanwhile, recent works have explored the possibility to use simultaneously various spatial resolutions [39] Different methodologies have been proposed to disaggregate large pixels of T s to estimate subpixel T s combining various information at different wavelengths [40, 41].…”

“…However, these last satellites do not have spectral bands in the thermal range. Several missions (conducted by CNES: Centre National d´Etudes Spatiales, Toulouse 3w/cnes.fr: IRSUTE [56], SEXTET [34]) have studied the interest of TIR data acquired at fine spatial and temporal resolution. Actually there is no current satellites which have these specific configurations.…”

The surface temperatures of Earth: steps towards integrated understanding of variability and change

“…LST standard products from MODIS, SEVIRI, VIIRS and future GOES-R ABI sensors are based on these methods (with the effect of view angle explicitly represented by an additional term in the retrieval algorithms used for VIIRS and ABI). The work of Jacob et al (2008) discusses the different types of temperature measurands in vegetated regions and their interrelation in the context of thermal infrared (TIR) remote sensing, and that of Li et al (2013) Gleckler et al, 2011), and ideally an existing approach already in use within the surface temperature community should be adopted. It may be necessary to supplement an existing approach -for example, with a structured discussion of how the surface temperature of a particular dataset is different to, as well as complements, other types of surface temperature.…”