M. Romaguera

Land Surface Emissivity Retrieval From Different VNIR and TIR Sensors

This paper discusses the application and adaptation of two existing operational algorithms for land surface emissivity (epsiv) retrieval from different operational satellite/airborne sensors with bands in the visible and near-infrared (VNIR) and thermal IR (TIR) regions: (1) the temperature and emissivity separation algorithm, which retrieves epsiv only from TIR data and (2) the normalized-difference vegetation index thresholds method, in which epsiv is retrieved from VNIR data.

Single-channel and two-channel methods for land surface temperature retrieval from DAIS data and its application to the Barrax site

In this paper, a methodology using a single-channel and a two-channel method is presented to estimate the land surface temperature from the DAIS (Digital Airborne Imaging Spectrometer) thermal channels 74 (8.747 µm), 75 (9.648 µm), 76 (10.482 µm), 77 (11.266 µm), 78 (11.997 µm) and 79 (12.668 µm). The land surface temperature retrieved with both methods has been validated over the Barrax site (Albacete, Spain) in the framework of the DAISEX (Digital Airborne Imaging Spectrometer Experiment) field campaigns. Prior to the validation an analysis of the DAIS data quality has been performed in order to check the agreement between in situ data and the values extracted from the DAIS images supplied by the DLR (German Optoelectronic Institute). Suitable differences between in situ and DAIS data have been found. To solve this problem a linear re-calibration of the DAIS thermal channels has been applied using two ground calibration points (bare soil and water). For the land surface temperature retrieved, rms deviations of 0.96 K using a single-channel method and 1.46 K using a two-channel method with the DAIS thermal channels 77 and 78 have been obtained considering re-calibrated data.

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.

Potential of using remote sensing techniques for global assessment of Water Footprint of crops.

Remote sensing has long been a useful tool in global applications, since it provides physically-based, worldwide, and consistent spatial information. This paper discusses the potential of using these techniques in the research field of water management, particularly for ‘Water Footprint’ (WF) studies. The WF of a crop is defined as the volume of water consumed for its production, where green and blue WF stand for rain and irrigation water usage, respectively. In this paper evapotranspiration, precipitation, water storage, runoff and land use are identified as key variables to potentially be estimated by remote sensing and used for WF assessment. A mass water balance is proposed to calculate the volume of irrigation applied, and green and blue WF are obtained from the green and blue evapotranspiration components. The source of remote sensing data is described and a simplified example is included, which uses evapotranspiration estimates from the geostationary satellite Meteosat 9 and precipitation estimates obtained with the Climatic Prediction Center Morphing Technique (CMORPH). The combination of data in this approach brings several limitations with respect to discrepancies in spatial and temporal resolution and data availability, which are discussed in detail. This work provides new tools for global WF assessment and represents an innovative approach to global irrigation mapping, enabling the estimation of green and blue water use.

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.

Water-vapour retrieval from Meteosat 8/SEVIRI observations

This paper aims to propose operational algorithms to retrieve the total atmospheric water vapour content (W) using the Spinning Enhanced Visible and Infrared Imager (SEVIRI) on‐board Meteosat 8. MODTRAN3.5 was used to obtain simulated data in the thermal infrared channels IR10.8 and IR12.0, in order to determine the numerical values of the coefficients of the algorithms. The algorithm proposed for land pixels takes into account the SEVIRI observation geometry and the radiometric temperatures obtained in the split‐window channels at two different times during a day and requires a minimum difference of 10 K in terms of temperature between the two situations. Comprehensive error analyses gave rms errors lower than 0.5 g cm−2 when observations were taken between the nadir and 50°. The algorithm is validated with in situ values, i.e. radiosondes and W measurements with a CIMEL CE318 sun photometer, both obtained from a field campaign, with rms validation errors of 0.2 and 0.7 g cm−2, respectively. Additionally, six stations all over the SEVIRI field of view were selected to validate the algorithm from radiosondes data, providing an rms error of 0.4 g cm−2. Concerning sea pixels, the linear atmosphere–surface temperature relation is adapted to SEVIRI and takes into account the sea‐surface temperature, the atmospheric effective temperature, and the radiometric temperature in the IR10.8 channel. The total error obtained from this methodology has a value between 0.8 and 1.1 g cm−2, and the validation is carried out using radiosonde data from four stations near the sea, providing rms errors lower than 0.6 g cm−2.

Validation of a temperature emissivity separation hybrid method from airborne hyperspectral scanner data and ground measurements in the SEN2FLEX field campaign

This paper presents an assessment of the performance of a hybrid method that allows a simultaneous retrieval of land‐surface temperature (LST) and emissivity (LSE) from remotely‐sensed data. The proposed method is based on a synergistic usage of the split‐window (SW) algorithm and the two‐temperature method (TTM) and combines the advantages of both procedures while mitigating their drawbacks. The method was implemented for thermal channels 76 (10.56 µm) and 78 (11.72 µm) of the Airborne Hyperspectral Scanner (AHS), which was flown over the Barrax test site (Albacete, Spain) in the second week of July 2005, within the framework of the Sentinel‐2 and Fluorescence Experiment (SEN2FLEX) field campaign. A set of radiometric measurements was performed in the thermal infrared region in coincidence with aircraft overpasses for different surface types, e.g. bare soil, water body, corn, wheat, grass. The hybrid method was tested and compared with a standard SW algorithm and the results obtained show that the hybrid method is able to provide better estimates of LST, with values of bias (RMSE) of the order of 0.8 K (1.9 K), i.e. about one third (one half) of the corresponding values of 2.7 K (3.4 K) that were obtained for bias (RMSE) when using the SW algorithm. These figures provide a sound indication that the developed hybrid method is particularly useful for surface and atmospheric conditions where SW algorithms cannot be accurately applied.

Application of a remote sensing method for estimating monthly blue water evapotranspiration in irrigated agriculture

In this paper we show the potential of combining actual evapotranspiration (ETactual) series obtained from remote sensing and land surface modelling, to monitor community practice in irrigation at a monthly scale. This study estimates blue water evapotranspiration (ETb) in irrigated agriculture in two study areas: the Horn of Africa (2010-2012) and the province of Sichuan (China) (2001-2010). Both areas were affected by a drought event during the period of analysis, but are different in terms of water control and storage infrastructure. The monthly ETb results were separated by water source—surface water, groundwater or conjunctive use—based on the Global Irrigated Area Map and were analyzed per country/province. The preliminary results show that the temporal signature of the total ETb allows seasonal patterns to be distinguished within a year and inter-annual ETb dynamics. In Ethiopia, ETb decreased during the dry year, which suggests that less irrigation water was applied. Moreover, an increase of groundwater use was observed at the expense of surface water use. In Sichuan province, ETb in the dry year was of similar magnitude to the previous years or increased, especially in the month of August, which points to a higher amount of irrigation water used. This could be explained by the existence

Estimation of sea surface temperature from SEVIRI data: algorithm testing and comparison with AVHRR products

Three surface temperature (ST) algorithms for Spinning Enhanced Visible and InfraRed Imager (SEVIRI) data are developed and tested. A general split window algorithm for ST estimation, a sea surface temperature (SST) algorithm and a nonlinear algorithm (NLSST) developed for SEVIRI data. The test was carried out by comparing SEVIRI data with two types of data: (a) in situ and (b) obtained with the NLSST algorithm applied to Advanced Very High Resolution Radiometer (AVHRR). The field campaign was carried out over sea using a thermal radiometer. The algorithms were applied to SEVIRI images in coincidence with the field campaign and the results show an rms error lower than 0.7 K. The comparison with AVHRR data was carried out in six test regions and provided an rms error lower than 1.3 K. The best results were obtained for the SST algorithm proposed.

Land cover dynamic analysis over the Mediterranean Basin by means of remotely sensed and climate data

WATERMED project contributes to the international efforts in analyzing efficiency in water use, in particular for the Mediterranean Basin countries. The general aim of this project is to develop a comprehensive method for the study of the water use and the resistance to the drought of the natural and irrigated vegetation in the Mediterranean Basin, by means of a combined historical remote sensing database, vegetation models and field measurements. The project has provided regional maps of critical parameters at regional scale, such as land surface temperature, emissivity, and NDVI. A multi-temporal analysis using the PATHFINDER AVHRR land data has been carried out into the frame of this project to map and monitor changes in the biophysical characteristics of land cover over the last 20 years. On the other hand, REANALYSIS data, which is a result of a joint project NCEP/NCAR, have been incorporated to provide mean monthly climate data over the study area.