Maria Mira

Soil Moisture Effect on Thermal Infrared (8–13-μm) Emissivity

Thermal infrared (TIR) emissivities of soils with different textures were measured for several soil moisture (SM) contents under controlled conditions using the Box method and a high-precision multichannel TIR radiometer. The results showed a common increase of emissivity with SM at water contents lower than the field capacity. However, this dependence is negligible for higher water contents. The highest emissivity variations were observed in sandy soils, particularly in the 8-9-μm range due to water adhering to soil grains and decreasing the reflectance in the 8-9-μm quartz doublet region. Thus, in order to model the emissivity dependence on soil water content, different approaches were studied according to the a priori soil information. Soil-specific relationships were provided for each soil texture and different spectral bands between 8 and 13 μm, with determination coefficients up to 0.99, and standard estimation errors in emissivity lower than ± 0.014. When considering a general relationship for all soil types, standard estimation errors up to ±0.03 were obtained. However, if other soil properties (i.e., organic matter, quartz, and carbonate contents) were considered, along with soil water content, the general relationship predicted TIR emissivities with a standard estimation error of less than ±0.008. Furthermore, the study showed the possibility of retrieving SM from TIR emissivities with a standard estimation error of about ±0.08 m3 . m-3.

Thermal Infrared Emissivity Dependence on Soil Moisture in Field Conditions

An accurate estimate of land surface temperature, which is a key parameter in surface energy balance models, requires knowledge of surface emissivity. Emissivity dependence on soil water content has been already reported and modeled under controlled conditions at the laboratory. This paper completes and extends that previous work by providing emissivity measurements under field conditions without elimination of impurities, local heterogeneities, or soil cracks appearing in the drying process. The multispectral radiometer CE312-2, with five narrow bands and a broad band in the 8-13-μm range, was used, and surface emissivity values were determined through a temperature-emissivity separation algorithm. A bare soil plot of 10 ×17 m2 was selected for this study in the framework of a camelina 2010 experiment. This experiment was carried out during March and April 2010 at The University of Arizona Maricopa Agricultural Center in central Arizona, USA. The soil plot was flood irrigated every two to three days and left to dry. Field emissivity measurements were collected under cloud-free skies, around noon, for different values of soil water content. Soil samples were collected to estimate the soil moisture (SM) using the gravimetric method. An overall increase of emissivity with SM was obtained in all channels. However, when wetted soils subsequently dried, the final minimum emissivity was greater than the initial minimum emissivity. This hysteresis could be due to cavity effects produced by soil cracks not originally present. Thus, the deterioration of soil surface tends to reduce the emissivity spectral contrast. Soil-specific and general relationships obtained by Mira et al. were tested and compared with the field measurements. Field emissivities agree within 2% with the modeled values for all bands under noncracked surface conditions, whereas differences reach 5% in the 8-9- μm range when cracks are present.

Comparison of Thermal Infrared Emissivities Retrieved With the Two-Lid Box and the TES Methods With Laboratory Spectra

Knowledge of surface emissivity in the thermal infrared (TIR) region is critical for determining the land surface temperature (LST) from remote-sensing measurements. If emissivity is not well determined, it can cause a significant systematic error in obtaining the LST. The main aim of this paper is to compare different methods for measuring accurate land surface emissivity in the field, namely, the box method and the temperature and emissivity separation (TES) algorithm. Field emissivities were compared with soil spectra from laboratory measurements. Emissivities were measured for the bands of a multispectral radiometer CE312-2 with effective wavelengths at 8.4, 8.7, 9.1, 10.6, and 11.3 mum, similar to the Advanced Spaceborne Thermal Emission and Reflection Radiometer TIR bands, and a wide channel 8-13 mum. The measurements were made at two sites in New Mexico: the White Sands National Monument and an open shrub land in the Jornada Experimental Range. The measurements show that for both sites the emissivities derived with the Box method agree with those derived with the TES algorithm for the 10.6 and 11.3 mum bands. However, the emissivities for the shorter wavelength bands are higher when derived with the Box method than those with the TES algorithm, with differences ranging from 2% to 7%. The field emissivities agree within 2% with the laboratory spectrum for the 8-13-, 11.3-, and 10.6-mum bands. However, the field and laboratory measurements in general differ from 2.4% to 9% for the shorter wavelength bands, with the larger value most likely caused by variations in soil moisture.

Evaluation of Different Methods to Retrieve the Hemispherical Downwelling Irradiance in the Thermal Infrared Region for Field Measurements

The thermal infrared hemispherical downwelling irradiance (HDI) emitted by the atmosphere and surrounding elements contributes through reflection to the signal measured over an observed surface by remote sensing. This irradiance must be estimated in order to obtain accurate values of land-surface temperature (LST). There are some fast methods to measure the HDI with a single measurement pointing to the sky at a specified viewing direction, but these methods require completely cloud-free or cloudy skies, and they do not account for the radiative contribution of surrounding elements. Another method is the use of a diffuse reflectance panel (usually, a rough gold-coated surface) with near-Lambertian behavior. This method considers the radiative contribution of surrounding elements and can be used under any sky condition. A third possibility is the use of atmospheric profiles and a radiative transfer code (RTC) in order to simulate the atmospheric signal and to calculate the HDI by integration. This study compares the HDI estimations with these approaches, using measurements made on four different days with a completely clear sky and two days with a partially cloudy sky. The measurements were made with a four-channel CIMEL Electronique radiometer working in the 8-14-μm spectral range. The HDI was also estimated by means of National Centers for Environmental Prediction atmospheric profiles introduced in the MODTRAN RTC. Additionally, the measurements were made at two different places with very different environments to quantify the effect of the contributing surroundings. Results showed that, for a clear-sky day with a minimal contribution of the surroundings, all methods differed from each other between 5% and 11%, depending on the spectral range, and any of them could be used to estimate HDI in these conditions. However, in the case of making surface measurements in an area with significant surrounding elements (buildings, trees, etc.), HDI values retrieved from the panel present an increase of +3 W·m-2·μm-1 compared with the other methods; this increase, if ignored, implies to make an error in LST ranging from +0.5 °C to +1.5 °C, depending on the spectral range and on surface emissivity and temperature. Comparison under heterogeneous skies with changing cloud coverage showed also large differences between the use of panel and the other methods, reaching a maximum difference of +4.6 W·m-2·μm-1, which implies to make an error on LST of +2.2 °C. In these cases, the use of the diffuse reflectance panel is proposed, since it is the unique way to capture the contribution of the surroundings and also to adequately measure HDI for sky changing conditions.

Analysis of ASTER Emissivity Product Over an Arid Area in Southern New Mexico, USA

The accuracy of thermal infrared emissivities derived from Advanced Spaceborne Thermal Emission and Reflectance radiometer (ASTER) was assessed in an arid area in southern New Mexico, which includes the White Sands National Monument (WSNM) during 2006-2008. ASTER emissivities retrieved by the temperature and emissivity separation (TES) algorithm were directly compared with laboratory measurements of samples from WSNM. Good agreement was found for the high spectral contrast of gypsum and for the low spectral contrast of water bodies. Furthermore, the day/night consistency of ASTER emissivities was checked, and day/night emissivity differences lower than ±0.013 were observed. However, unexpected emissivity values larger than unity were retrieved by ASTER/TES at 8-9 μm , mainly concentrated over lava flow surfaces. The thermal infrared radiance image data with 90-m spatial resolution was resized to 180 m for the analysis in this paper to avoid misregistration problems due to terrain topography. Emissivity temporal variations were analyzed and attributed, in some cases, to the soil moisture variations. This was particularly noted after periods of high precipitation which occurred in August 2006. The results presented here show the high emissivity accuracy achievable with ASTER data in ideal atmospheric conditions and discuss some problems which should be considered in the future, as the retrieval of overestimated emissivity values.

Impact of surface emissivity and atmospheric conditions on surface temperatures estimated from top of canopy brightness temperatures derived from Landsat 7 data

The method to derive surface temperature from top of canopy brightness temperature developed by Olioso (1995b) [20] is tested over the Avignon-Crau-Camargue area (France) using Landsat-7 ETM+ images. The difference between surface temperature and brightness temperature depends on surface emissivity, incident atmospheric radiation and the temperature itself. Differences up to 2 K were obtained for a surface emissivity of 0.97. It can increase up to 7 K when surface emissivity was 0.91. The surface temperature derived from Landsat data were in agreement with the ground measurements when using local calibration of the surface emissivity derivation method and a modification of the calculation of atmospheric radiation as compared to [20]. The impact of error in emissivity derivation was higher than the impact of errors in deriving atmospheric radiation.

Evaluation of Surface Temperature and Emissivity Derived from ASTER Data: A Case Study Using Ground-Based Measurements at a Volcanic Site

Abstract The land surface temperature (LST) and emissivity (LSE) derived from Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data were evaluated in a low spectral contrast volcanic site at an altitude of 2000 m on the island of Tenerife, Spain. The test site is almost flat, thermally homogeneous, and without vegetation cover or variation in its surface composition. ASTER data correspond to six scenes, under both day- and nighttime conditions during 2008. This case study analyzes the impacts of the sources of inaccuracies using the temperature–emissivity separation (TES) algorithm. Uncertainties associated with inaccurate atmospheric correction were minimized by means of local soundings and the climate advantages of the area. Concurrent ground-based radiometric measurements were performed for LST, and laboratory and field measurements for LSE, to obtain reference values. The TES evaluation showed a good level of agreement in the emissivity derived for ASTER bands 13 and 14 [root-mea...

Angular dependence of the emissivity of bare soils in the thermal infrared

Emissivity is one of the main factors to take into account when studying processes that take place in the Earth surface by using radiance measurements in the thermal infrared, such as surface energy balance, land surface temperature (LST) retrieval, classification of different types of surface, etc. For this reason it is necessary to study the factors that can influence the emissivity. The present work evaluates one of these factors: the variation of the emissivity with the zenithal observation angle over bare soils, specifically the variation of the relative emissivity calculated from measurements of radiances, almost simultaneous, at nadir (0o) and at a certain angle (¿). The measurements of radiance were taken with the aid of a straightforward goniometric system that allows the measurement from nadir observation to 70o (at 10o increments) for a fixed azimuthal angle. The results show a significant decrease of emissivity with observation angle, which is especially accentuated in the case of sandy soils with high quartz content.

Quantifying uncertainties in land surface temperature due to atmospheric correction: Application to Landsat-7 data over a Mediterranean agricultural region

The impact of using non-coincident radiosoundings to remove atmosphere effect from thermal radiances is analyzed here. We considered 27 Landsat-7 ETM+ images acquired over a Mediterranean agricultural region, benefiting from nearby radiosoundings launched almost 2 hours later, and from the availability of a network of ground stations deployed over different types of ecosystems. We observed that, in the conditions of our images, surface temperature estimates slightly improved when considering one atmospheric profile interpolated to our particular date, time and location, in comparison with the use of non-coincident radiosoundings. However, it may imply an error up to ±2.5 K for brightness temperatures (in particular for very high temperatures and during summer when the atmosphere was warmer and the vapor pressure was higher), leading to important errors in the derivation of surface energy fluxes. The characterization of the lowest atmosphere layer appeared to be essential to improve the estimates of brightness temperatures.

Validation of MODIS albedo products with high resolution albedo estimates from FORMOSAT-2

Among MODIS products (freely available to the scientific community from 2001), albedo data (MCD43B3) are 16 days composites at 1km spatial resolution, widely used for various applications in climate models, but which still remains difficult to validate. The objective of this study is to propose a method to validate these products with high spatial and temporal resolution data. 31 FORMOSAT-2 images acquired over a small region in the South-Eastern France at 8m for spatial resolution were aggregated at MODIS resolution using a Point Spread Function. The correlation coefficient resulting from comparisons between albedo MODIS and the 1-km FORMOSAT-2 albedos varied from 0.93 to 0.98, which show reasonably accurate results for this study area.