An Autonomous System to Take Angular Thermal-Infrared Measurements for Validating Satellite Products

Abstract

An autonomous system for field land surface temperature (LST) measurements taken at different observation angles was developed to be deployed easily at any conventional meteorological tower station. The system permits ground-truth data to be acquired on a continuous basis, and angularly scans land and sky hemispheres with a single thermal-infrared (TIR) radiometer. This paper describes the autonomous angular system and the methodology to assess ground-truth LST and relative-to-nadir emissivity data from system measurements. Ground-truth LSTs were used to validate satellite-retrieved LST products at two experimental sites (rice crop and shrubland areas). The relative-to-nadir emissivity values were used to analyze the anisotropy of surface emissive properties over thermally-homogeneous covers. The EOS-MODIS MOD11_L2/MYD11_L2 LST product was evaluated and shown to work within expected uncertainties (<2.0 K) when tested against the system data. A slight underestimation of around −0.15 K was observed, which became greater for the off-nadir observation angles at the shrubland site. The system took angular measurements for the different seasonal homogeneous covers at the rice crop site. These measurements showed emissivity angular anisotropies, which were in good agreement with previously published data. The dual-view ENVISAT-AATSR data reproduced them, and revealed that the system data collected for thermally-homogeneous surfaces could be used to test future satellite TIR sensors with multi-angular or bi-angular capabilities, like the forthcoming SLSTR on board Copernicus Sentinel-3A.

Landsat and Local Land Surface Temperatures in a Heterogeneous Terrain Compared to MODIS Values

“…When possible, the biases and RMSEs included in Table 1 correspond specifically to the same satellite products used in the current study. For MODIS, most of the results included correspond to cases where the gridded (Level 3) product MOD11A1 in its collection 5 was used ( [12][13][14]22]), although ( [15,16], and [13] for the rice crop area) the swath product MOD11_L2 was used, which is prior to the gridded one. For the ETM+ studies [18], local-radiosonde profiles were used to retrieve the atmospheric parameters in RTE instead of the synthetic ones generated by the web-tool calculator described in Section 2.1, while [17] compared both methodologies over a homogeneous surface, obtaining better results for the interpolated profiles.…”

“…Ref. [13] uses a single thermal-infrared radiometer that measured at different observation angles, while [14] built the ground truth LST after identifying the fractions of the main surface elements seen by the on-board sensor.…”

“…Most studies comparing satellite measurements and direct measurements of LST occur in homogeneous areas ( [12][13][14][15][16][17][18]; etc.). There are a few studies for heterogeneous areas, like the downscaling ones of [19,20] between MODIS and ETM+ sensors, or LST validation campaign of [16,21,22] where LST satellite data was compared with in situ measurements.…”

Validation of Sentinel-3 SLSTR Land Surface Temperature Retrieved by the Operational Product and Comparison with Explicitly Emissivity-Dependent Algorithms

“…This site has been extensively used for LST validation purposes [15,[25][26][27][28]. Previous studies demonstrated a high thermal homogeneity for this site at different spatial resolutions [27,[29][30][31] and concluded that it is suitable for validating satellite LST with in-situ measurements. For full vegetation cover, these studies found a standard deviation (SD) lower than 0.5 K for 33 × 33 ASTER pixels (~9 km 2 ) centered on the study area and for a Landsat TM5 scene (~16 km 2 ).…”

Active in situ and passive airborne fluorescence measurements for water stress detection on a fescue field

“…The use of these broad-band IRTs is widespread in agronomic applications such as plant water status estimation or surface energy balance modeling (Sánchez et al 2008(Sánchez et al , 2011(Sánchez et al , 2014(Sánchez et al , 2015(Sánchez et al , 2019 and also in surface temperature monitoring for remote sensing calibration/validation activities (Niclòs et al 2015;Sobrino and Skoković 2016;Sánchez et al 2020).…”