V. Hidalgo

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.

Mass and energy flux estimates at different spatial resolutions in a heterogeneous area through a distributed energy–water balance model and remote-sensing data

A physically based, distributed energy–water balance model, Flash-Flood Event-Based Spatially Distributed Rainfall–Runoff Transformation-Energy Water Balance (FEST-EWB) model, and remote-sensing data were analysed to study the representativeness of mass and energy fluxes at different spatial resolutions. The analyses were performed in an agricultural area of Barrax (Spain) in the framework of the Sentinel-2 and Fluorescence Experiment (SEN2FLEX). In particular, there were two main objectives: (1) to evaluate the ability of the distributed hydrological model to compute energy and mass fluxes for a heterogeneous area compared to remote-sensing and ground data and (2) to define the length scales of different processes (evapotranspiration (ET) and land surface temperature (LST)) above which the variance of the different variables becomes insignificant for the process, so that bare soil and vegetation behaviours are no longer distinguishable. Mass and energy fluxes were collected from ground data and from an Airborne Hyperspectral Scanner (AHS), with a spatial resolution between 2 and 4 m, and from the Moderate Resolution Imaging Spectroradiometer (MODIS), with a spatial resolution of 1000 m, and then compared with hydrological model outputs. ET and LST spatial variability was analysed at different spatial resolutions using histograms, statistical parameters, and spatial autocorrelation functions. Computed ET with the FEST-EWB model at high spatial resolution (10 m) showed for the three days of analysis a mean relative error of 9.4% compared to AHS data, whereas for land surface temperature comparison a relative error of 1.6% was found. Then, LSTs from AHS and FEST-EWB were aggregated at decreasing spatial resolutions (50, 150, 300, 400, 500, 600, 750, and 1000 m), showing that the thermodynamic variability tends to disappear with a lower number of classes in the histograms and with a decrease of the coefficient of variation (CV) and of standard deviation values. At each scale, a similar behaviour was reported between each pair of images, with the values of standard deviation starting, respectively, from 8.9°C and 9.6°C at 10 m of spatial resolution to 7.7°C and 7.9°C at 1000 m of spatial resolution. Similar results were obtained from the spatial aggregation of ET images. The decrease in standard deviation values of LST and ET with a decrease in the scale became substantial around pixel dimensions equal to 400 m.

Estimation of the Spatially Distributed Surface Energy Budget for AgriSAR 2006, Part I: Remote Sensing Model Intercomparison

A number of energy balance models of variable complexity that use remotely sensed boundary conditions for producing spatially distributed maps of surface fluxes have been proposed. Validation typically involves comparing model output to flux tower observations at a handful of sites, and hence there is no way of evaluating the reliability of model output for the remaining pixels comprising a scene. To assess the uncertainty in flux estimation over a remote sensing scene requires one to conduct pixel-by-pixel comparisons of the output. The objective of this paper is to assess whether the simplifications made in a simple model lead to erroneous predictions or deviations from a more complex model and under which circumstances these deviations most likely occur. Two models, the S-SEBI and TSEB algorithms, which have potential for operationally monitoring ET with satellite data are described and a spatial inter-comparison is made. Comparisons of the spatially distributed flux maps from the two models are made using remotely sensed imagery collected over an agricultural test site in Northern Germany. With respect to model output for radiative and conductive fluxes no major differences are noted. Results for turbulent flux exchange demonstrate that under relatively dry conditions and over tall crops model output differs significantly. The overall conclusion is that under unstressed conditions and over homogeneous landcover a simple index model is adequate for determining the spatially distributed energy budget.

Estimation of the Spatially Distributed Surface Energy Budget for AgriSAR 2006, Part II: Integration of Remote Sensing and Hydrologic Modeling

In most hydrologic modeling studies, the hypothesis is made that an improvement in the modeled soil moisture leads to an improvement in the modeled surface energy balance. The objective of this paper is to assess whether this hypothesis is true. The study was performed over the winter wheat fields in the AgriSAR 2006 domain. Remotely sensed soil moisture values and latent heat fluxes were used, in combination with in situ observations. First, the land cover and saturated subsurface flow parameters were estimated using the in situ observations. A spatially distributed model simulation was then performed, for which the Brooks-Corey parameters were derived from a soil texture map, and of which the results were validated using the remote sensing data. The remotely sensed soil moisture values were then used to optimize the Brooks-Corey parameters. As expected, a better performance with respect to the soil moisture estimation was obtained. However, this did not improve the latent heat flux estimates. This can be explained by the consumption of water from the deeper soil layers by the vegetation. The overall conclusion is that, under conditions where evapotranspiration is limited by energy and not by the soil moisture content, surface soil moisture values alone are not sufficient for the optimization of hydrologic model results. More data sets are needed for this purpose.

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%.

Fluorescence estimation in the framework of the CEFLES2 campaign

Chlorophyll fluorescence (ChF) is a relevant indicator of the actual plant physiological status. In this article different methods to measure ChF from remote sensing are evaluated: the Fraunhofer Line Discrimination (FLD), the Fluorescence Radiative Method (FRM) and the improved Fraunhofer Line Discrimination (iFLD). The three methods have been applied to data acquired in the framework of the CarboEurope, FLEX and Sentinel-2 (CEFLES2) campaign in Les Landes, France in September 2007. Comparing with in situ measurements, the results indicate that the methods that provide the best results are the FLD and the iFLD with root mean square errors (RMSEs) of 0.4 and 0.5 mW m−2 sr−1 nm−1, respectively, while the FRM provides an error of 0.8 mW m−2 sr−1 nm−1.

Surface temperature in the context of FLuorescence EXplorer (FLEX) mission

It has been demonstrated that the spectrum of fluorescence emission is dependent on leaf temperature, thus there is a need for thermal information in order to interpret fluorescence signals. Temperature is also related to transpiration and stomata closure, which affects CO2 uptake and fluorescence. Therefore temperature measurements help to confirm the trends observed in fluorescence measurements. While fluorescence is immediately and uniquely related to photosynthesis, temperature provides additional information about plant status and instantaneous energy/water fluxes between plants and the atmosphere. The objective of this paper is to demonstrate the role of surface temperature in the context of FLuorescence EXplorer (FLEX) mission. To this end a database of land surface emissivity and temperature obtained from thermal radiometric measurements carried out in the framework of the Sen2FLEX (SENtinel-2 and FLuorescence Experiment) campaign has been used. These data were acquired in the agricultural site of Barrax (Spain) in June and July of 2005 simultaneously with airborne imagery acquired with Airborne Hyperspectral Scanner (AHS) and Compact Airborne Spectrographic Imager (CASI) sensors and data from the airborne fluorescence measuring instrument (AIRFLEX). As a result of these studies we have identified the optimal band configuration for the FLEX mission, that allows the estimation of land surface temperature with an accuracy lower than 1.5 K. To this end single-channel, split-window, and Temperature Emissivity Separation algorithms have been compared using a database of simulated brightness temperatures.