E. Rubio

Emissivity measurements of several soils and vegetation types in the 8–14, μm Wave band: Analysis of two field methods

Abstract The two variants of the box method (with one and two lids) has been rigorously analyzed. As a result of this analysis, a correction factor that takes into account the nonideality of the materials used for the box, as well as its geometry, has been derived A simple method for determining the effective downward atmospheric temperature that uses only the temperature measurement at the zenith also has been proposed. Finally, by using one of the two variants of the box method, 72 in situ emissivity measurements in the 8–14 pin wave-band region of typical vegetation, soils, and rocks of Europe and South America, has been obtained. The use of these data for the ernissivity correction of satellite thermal measurements has been analyzed, and emissivities for the Landsat Thematic Mapper band 6 and NOAA Advanced Very High Resolution Radiometer channels 4 and 5 have been derived.

Thermal–infrared emissivities of natural surfaces: improvements on the experimental set-up and new measurements

Ground measurements of thermal infrared emissivities of terrestrial surfaces are required to derive accurate temperatures from radiometric measurements, and also to apply and validate emissivity models using satellite sensor observations. This paper focuses on the demanding aspects that are involved in the field measurement of emissivity using the box method and a hand-held radiometer. Measuring emissivities in field conditions can be hampered by external factors such as wind and solar irradiance. This can increase the time spent on the field campaign but, most importantly, it can cause no-sense fluctuations between consecutive observations. Here we propose original developments for the experimental instrumentation to ensure consistency of measurements. Moreover, we present a dataset of emissivity values for different soils, rocks and vegetation samples measured in the 8–14, 8.2–9.2, 10.5–1 1.5 and 11.5–12.5 µm wavebands.

Sea surface emissivity observations at L-band: first results of the Wind and Salinity Experiment WISE 2000

Sea surface salinity can be measured by passive microwave remote sensing at L-band. In May 1999, the European Space Agency (ESA) selected the Soil Moisture and Ocean Salinity (SMOS) Earth Explorer Opportunity Mission to provide global coverage of soil moisture and ocean salinity. To determine the effect of wind on the sea surface emissivity, ESA sponsored the Wind and Salinity Experiment (WISE 2000). This paper describes the field campaign, the measurements acquired with emphasis in the radiometric measurements at L-band, their comparison with numerical models, and the implications for the remote sensing of sea salinity.

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.

Mapping land surface emissivity using AVHRR data application to La Mancha, Spain

Abstract Land surface temperature can be determined applying the split‐window technique to the AVHRR channels 4 and 5. However, for this purpose the knowledge of land surface emissivities in the AVHRR channels 4 and 5 is essential. The paper proposes a simple method for mapping the difference between channels 4 and 5 surface emissivities (?? = ?4 ‐ ?5) at the AVHRR spatial scale. The method is based on the availability of radiosounding data coincident to the NOAA overpass for the study area and on the knowledge of the mean value of the land surface emissivity for channels 4 and 5 (? = (?4 + ?5)/2). Therefore, two simple methods for measuring and mapping the mean value of emissivity are also proposed, which use a reference calibrated sand and the normalized difference vegetation index (NDVI), respectively. And finally, a complete example of application of the methodology developed on the La Mancha region, Spain, is shown.

Temperature and emissivity separation from calibrated data of the Digital Airborne Imaging Spectrometer

Abstract The Digital Airborne Imaging Spectrometer (DAIS), with six thermal infrared channels in the 8–14 μm window, was flown over the Barrax test site, Spain, in the framework of the DAIS Experiment in the summer of 1998. Atmospheric correction of the DAIS thermal channels was performed by means of local radiosonde measurements and a radiative transfer model. Ground measurements of temperature and emissivity for six selected spots (two bare soils, two water bodies, and two vegetated fields) were conducted with the objective of providing calibration and validation targets. Three targets were used for a linear ground calibration of the DAIS thermal channels. With the ground-calibrated images, surface temperatures and channel emissivities were retrieved using a temperature–emissivity separation algorithm. We applied the Adjusted Normalized Emissivity Method (ANEM) in which an initial maximum emissivity was assumed for each surface type according to ground emissivity measurements. The other three targets were used to test the accuracy of the ground calibration and the ANEM method. The derived temperatures and channel emissivities were mostly within ±0.005 and ±1°C of the measured values, respectively. Such results are comparable to other methods for temperature and emissivity separation.

Carbon sequestration of naturally regenerated Aleppo pine stands in response to early thinning

Sustainable forest management ought to include the production of non-use value, mainly in forests with low value of direct production. Predictions on climate change points out increase in aridity and changes in fire regime (increasing fire risk, recurrence and severity), particularly in the Mediterranean Basin. However, we have to question whether this implies a decrease in forest resilience and productivity. In summer 1994, large forest fires burned a huge surface of Aleppo pine stands in Spain. In areas naturally regenerated, we carried out early thinning and sampled 18 plots. In winter 2008 and 2009, we inventoried all pine trees in sampling plots, recording total height, diameter and canopy cover for scaling-up results to stand-level estimation. In addition, we destructively sampled 54 individual pine trees, selecting various thinning and dating treatments, to measure and estimate biomass and partitioning. The date of thinning influenced allometric relationships, earlier thinning stimulated the productivity of individual pine saplings, increasing the three components of carbon intake. Although, the total net carbon value was lower in almost all thinned plots (at least for short periods after thinning), differences were actually found depending on the cutting age and thinning severity. Control and thinned plots (mainly those thinned earlier and heavier) showed similar amounts of carbon but comprised in a low number of living trees with high productivity. Thus, productivity and carbon storage assessment should be monitored, in the long-term, to check prediction of proposed models for evaluation on early treatments.

Validation of temperature-emissivity separation and split-window methods from TIMS data and ground measurements

Abstract Land surface temperature retrieved with temperature-emissivity separation (TES) and split-window (SW) algorithms from six-channel Thermal Infrared Multispectral Scanner (TIMS) data in the HAPEX-Sahel experiment agreed with contemporaneous ground temperature measurements to within ±1 °C (TES and SW with channels at 10.8 and 11.7 μm, or SW-56). The SW algorithm used with TIMS channels at 8.4 and 8.7 μm (SW-12) underestimated ground temperatures by 2–5 °C. The TES method required atmospheric correction of at-sensor radiances, which was done with local radiosonde data and MODTRAN 4, and an empirical relationship between the spectral range of emissivity and its minimum value. Emissivity data required for the SW algorithms were obtained using vegetation cover estimates from near-coincident reflective remote sensing data. The temperature underestimation of the SW-12 algorithm could be caused by errors in the emissivity inputs calculated from the vegetation cover. Such errors were due to the high variability of surface emissivity in the 8–9-μm waveband, which was much larger than in the 10–12-μm region. This was checked using TES derived emissivities as inputs of the SW algorithms, and comparing the resulting temperatures with the TES temperatures. In this case, both the SW-56 and SW-12 temperatures agreed with TES within ±1 °C for all sites and scenes.

Thermal band selection for the PRISM instrument 2. Analysis and comparison of existing atmospheric and emissivity correction methods for land surface temperature recovery

This is the second paper in a series which discusses the thermal band selection for the Processes Research by Imaging Space Mission (PRISM) planned by the European Space Agency (ESA). In part 1, algorithms for emissivity-temperature decoupling were analyzed with the aim of identifying optimum methods and attainable accuracies for extracting emissivity values in the PRISM thermal bands. In this paper, we have focused on studying the existing methods for land surface temperature (LST) recovery. The preliminary configuration of the PRISM instrument includes four thermal channels: A (∼3.7 μm ), B (∼8.8 μm ), C (∼10.8 μm ), and D (∼11.9 μm) and along-track multipointing capability. Single-channel, split-window, and dual-angle algorithms have been tested and compared using a database of simulated brightness temperatures. Although focused on PRISM, the study is relevant to present instruments with similar features, such as the advanced very high resolution radiometer (AVHRR) and the along-track scanning radiometer (ATSR). In particular, we have shown that (1) atmospheric effects dominate errors in single-channel LST recovery methods, (2) spectral emissivity dominates errors in the dual-angle and split-window methods, and (3) current AVHRR split-window channel combination (channels C and D) provide the best results. It does not need auxiliary atmospheric information and therefore it can work in an operational scheme using only satellite data. It can be applied to any type of surface, and accuracies around ±1 K can be obtained for most natural surfaces. For the single-channel method the use of coincident radiosoundings is necessary, because of the high sensitivity to the atmospheric variability. Dual-angle methods are constrained to homogeneous surfaces, since in heterogeneous, rough surfaces, the temperatures measured at the two observation angles may present directional effects caused by the surface structure and the differences between vegetation and background temperatures. We have also shown that the utility of channel B to LST recovery is marginal. Combinations including channel A are only applicable in nighttime conditions owing to reflected radiation. For these reasons the split-window algorithm, using channels within the 10–12.5 μm window, has been suggested for operational determination of LST.

Autonomous Measurements of Sea Surface Temperature Using In Situ Thermal Infrared Data

Abstract In situ and autonomous measurements of sea surface temperature (SST) have been performed with a thermal infrared radiometer mounted on a fixed oil rig. The accuracy limit was established at ±0.3 K for these SST measurements in order to meet the requirements of the Tropical Ocean Global Atmosphere (TOGA) program for global climate research and the Soil Moisture and Ocean Salinity (SMOS) mission for salinity retrieval. With this aim, the optimal observation angle and spectral channel for SST measurements have been identified. Then, a methodology has been developed for the radiometer calibration and the emissivity correction, including the reflection of the downwelling sky radiance, which was directly measured simultaneously to the sea surface observation. The effect of the atmospheric path between the sea surface and the sensor has been also studied and found negligible for the particular viewing conditions. A sensitivity analysis of the proposed methodology has shown a precision of ±0.15 K in the ...