Juan Cuenca

Angular variation of thermal infrared emissivity for some natural surfaces from experimental measurements

Multiangle algorithms for estimating sea and land surface temperature with Along-Track Scanning Radiometer data require a precise knowledge of the angular variation of surface emissivity in the thermal infrared. Currently, few measurements of this variation exist. Here an experimental investigation of the angular variation of the infrared emissivity in the thermal infrared (8-14-microm) band of some representative samples was made at angles of 0 degrees-65 degrees (at 5 degrees increments) to the surface normal. The results show a decrease of the emissivity with increasing viewing angle, with water showing the highest angular dependence (approximately 7% from 0 degrees to 65 degrees views). Clay, sand, slime, and gravel show variations of approximately 1-3% for the same range of views, whereas a homogeneous grass cover does not show angular dependence. Finally, we include an evaluation of the impact that these data can produce on the algorithms for determining land and sea surface temperature from double-angle views.

Experimental measurements for studying angular and spectral variation of thermal infrared emissivity

One condition for precise multiangle algorithms for estimating sea and land surface temperature with the data from the Advanced Along Track Scanning Radiometer is accurate knowledge of the angular variation of surface emissivity in the thermal IR spectrum region. Today there are very few measurements of this variation. The present study is conducted to provide angular emissivity measurements for five representative samples (water, clay, sand, loam, gravel). The measurements are made in one thermal IR broadband (8-13 microm) and three narrower bands (8.2-9.2, 10.3-11.3, and 11.5-12.5 microm) at angles of 0 degrees-60 degrees (at 5 degrees increments) to the surface normal. The results show a general decrease in emissivity with increasing viewing angles, with the 8.2-9.2-microm channel the most sensitive to this dependence and sand the sample showing the greatest variation.

Thermal remote sensing in the framework of the SEN2FLEX project: field measurements, airborne data and applications

A description of thermal radiometric field measurements carried out in the framework of the European project SENtinel‐2 and Fluorescence Experiment (SEN2FLEX) is presented. The field campaign was developed in the region of Barrax (Spain) during June and July 2005. The purpose of the thermal measurements was to retrieve biogeophysical parameters such as land surface emissivity (LSE) and temperature (LST) to validate airborne‐based methodologies and to characterize different surfaces. Thermal measurements were carried out using two multiband field radiometers and several broadband field radiometers, pointing at different targets. High‐resolution images acquired with the Airborne Hyperspectral Scanner (AHS) sensor were used to retrieve LST and LSE, applying the Temperature and Emissivity Separation (TES) algorithm as well as single‐channel (SC) and two‐channel (TC) methods. To this purpose, 10 AHS thermal infrared (TIR) bands (8–13 µm) were considered. LST and LSE estimations derived from AHS data were used to obtain heat fluxes and evapotranspiration (ET) as an application of thermal remote sensing in the context of agriculture and water management. To this end, an energy balance equation was solved using the evaporative fraction concept involved in the Simplified Surface Energy Balance Index (S‐SEBI) model. The test of the different algorithms and methods against ground‐based measurements showed root mean square errors (RMSE) lower than 1.8 K for temperature and lower than 1.1 mm/day for daily ET.

Temporal analysis of normalized difference vegetation index (NDVI) and land surface temperature (LST) parameters to detect changes in the Iberian land cover between 1981 and 2001

In past decades, the Iberian Peninsula has been shown to have suffered vegetation changes such as desertification and reforestation. Normalized difference vegetation index (NDVI) and land surface temperature (LST) parameters, estimated from data acquired by the Advanced Very High Resolution Radiometer (AVHRR) sensor onboard the National Oceanic and Atmospheric Administration (NOAA) satellite series, are particularly adapted to assess these changes. This work presents an application of the yearly land-cover dynamics (YLCD) methodology to analyse the behaviour of the vegetation, which consists of a combined multitemporal study of the NDVI and LST parameters on a yearly basis. Throughout the 1981–2001 period, trend analysis of the YLCD parameters emphasizes the areas that have endured the greatest changes in their vegetation. This result is corroborated by results from previous studies.

Evaluation of the surface urban heat island effect in the city of Madrid by thermal remote sensing

The surface urban heat island (SUHI) effect is defined as the increased surface temperatures in urban areas in contrast to cooler surrounding rural areas. In this article, the evaluation of the SUHI effect in the city of Madrid (Spain) from thermal infrared (TIR) remote-sensing data is presented. The data were obtained from the framework of the Dual-use European Security IR Experiment (DESIREX) campaign that was carried out during June and July 2008 in Madrid. The campaign combined the collection of airborne hyperspectral and in situ measurements. Thirty spectral and spatial high-resolution images were acquired with the Airborne Hyperspectral Scanner (AHS) sensor in a 11, 21, and 4 h UTC scheme. The imagery was used to retrieve the SUHI effect by applying the temperature and emissivity separation (TES) algorithm. The results show a nocturnal SUHI effect with a highest value of 5 K. This maximum value agrees within 1 K with the highest value of the urban heat island (UHI) observed using air temperature data (AT). During the daytime, this situation is reversed and the city becomes a negative heat island.

Thermal inertia mapping from NOAA-AVHRR data

Abstract This paper presents a method to retrieve thermal inertia from NOAA-AVHRR data. The method, based on Xue and Cracknells model (1992), involves using the phase angle information of the diurnal surface temperature change. The method needs three different NOAA overpasses of the same area throughout a single diurnal cycle. To apply this method we present a methodology that takes into account satellite calibrations, viewing geometry and correction of atmospheric effects. The advantage is that it does not need other data than the ones supplied by the satellite. Finally, we present the preliminary results obtained using the proposed method and the methodology for AVHRR data over the Iberian Peninsula.

Ultrastructure of regions containing homologous loci in polytene chromosomes of Drosophila melanogaster and Drosophila subobscura

Abstract. We have used a new approach involving in situ hybridisation and electron microscopy to establish ultrastructural homologies between polytene chromosome regions of Drosophila melanogaster and Drosophila subobscura. Twelve probes were chosen to cover all the chromosomal elements: the myospheroid gene, the collagen type IV gene, the collagen-like gene, the w26 homeobox gene, the β3 tubulin gene, the kinesin heavy chain gene, the tryptophan hydrolase gene, the Hsp82, Hsp22–26 and Hsp23–28, Hsp68, Hsp70 genes and the β unit of the F0–F1 ATPase gene. Most of these loci were previously undescribed in D. subobscura and imprecisely located in D. melanogaster. We have demonstrated here, by an ultrastructural analysis of each chromosomal region, that homologous genetic loci tend to show a similar ultrastructure in the two species. With a few exceptions, the structural homology extends to the chromosomal regions surrounding the loci. In some cases, however, no structurally recognisable homology can be seen either in the locus or in its flanking regions.

Mapping sub-pixel burnt percentage using AVHRR data. Application to the Alcalaten area in Spain

The purpose of this work is to estimate at sub-pixel scale the percentage of burnt land using the Advanced Very High Resolution Radiometer (AVHRR) through a simple approach. This methodology is based on multi-temporal spectral mixture analysis (MSMA), which uses a normalized difference vegetation index (NDVI) and a land-surface temperature (LST) image as input bands. The area of study is located in the Alcalaten region in Castellon (Spain), a typical semi-arid Mediterranean region. The results have shown an extension of approximately 55 km2 affected by fire, which is only 5% lower than the statistic reports provided by the Environmental Ministry of Spain. Finally, we include a map of the area showing the percentage of estimated burnt area per pixel and its associated uncertainties. The map was validated through supervised classification of an Airborne Hyperspectral Sensor (AHS) image taken on 27 September 2007. Results have a high accuracy, with a mean error of 6.5%.

The polytene dot chromosome of Drosophila: D. melanogaster and D. subobscura.

Abstract. The chromosome arms are assumed to be homologous within the genus Drosophila. Homology at the level of the polytene chromosome banding pattern between non-sibling species is, however, almost impossible to establish as different processes such as inversion, transposition and unequal crossing over, have disturbed it. Even though the band sequences cannot be followed, we may ask whether there is a correlation in the total number of bands between species. The polytene dot chromosome is an excellent starting point for such an approach. Here we present the detailed cytology of polytene chromosome 4 of D. melanogaster and the polytene dot chromosome of D. subobscura using electron microscopy. The results show that the number of bands is about the same, around 30, in both species. We predict that by using thin sections and electron microscopy for the longer polytene chromosome arms, both species will turn out to have approximately equal band numbers.

Algorithms for estimating surface temperature from ATSR-2 data

A study has been carried out using MODTRAN 3.5 simulations of the Along-Track Scanning Radiometer-2 (ATSR-2) data at 3.7, 11 and 12 µm wavelengths to give a great range of algorithms for estimating sea surface temperature (SST) and land surface temperature (LST). Algorithms based on split-window, dual-angle and mixed structure have been considered. The coefficients of the algorithms are derived by regression analysis using the MATLAB code. The results show that, in general, dual-angle algorithms give better results than split-window ones, retrieving LST with a standard deviation as low as 0.4 K and 0.6 K respectively if the satellite data are error free. The introduction of 3.7 µm channel involves less error in the estimation of surface temperature. Water vapor dependence supposes an improvement of the accuracy of the results.