Juan-Carlos Jimenez-Munoz

One of the major problems in the monitoring of tropical rainforests using satellite imagery is their persistent cloud coverage. The use of daily observations derived from high temporal resolution sensors, such as Moderate Resolution Imaging Spectroradiometer (MODIS), could potentially help to mitigate this issue, increasing the number of clear-sky observations. However, the cloud contamination effect should be removed from these results in order to provide a reliable description of these forests. In this study the available MODIS Land Surface Temperature (LST) products have been reprocessed over the Amazon Basin (10 N–20 S, 80 W–45 W) by introducing different cloud masking schemes. The monthly LST datasets can be used for the monitoring of thermal anomalies over the Amazon forests and the analysis of spatial patterns of warming events at higher spatial resolutions than other climatic datasets.

En: XI Congreso Nacional de Teledetección, Teledetección, Avances en la Observación de la Tierra, M. Arbelo, A. González, J.C. Pérez (Eds.), pág.: 53-56, Tenerife, 21-23/9/2005. El sensor hiperespectral AHS (Airborrne Hyperspectal Scanner)fue utilizado para obtener imágenesde 2.5 m de resolución espacial en el espectro visible, infrarrojo cercano y térmico en una parcela de olivar en Córdoba (España) con el fin de estudiar la variabilidad espacial y temporal del estrés hídrico. Los datos térmicos del AHS permitieron obtener imágenes detemperatura de superficie de la parcela a las 7:30,9:30 y 12:30 GMTel 25 de julio de 2004. El diseño experimental en bloques aleatorios consistió en aplicar tres dosis diferentes de riego durante julio, agosto y septiembre, realizando medidas semanales de potencial hídrico, fotosíntesis y conductancia para estudiar los efectos del estrés hídrico en el cultivo. Los sensores de infrarrojo IRT permitieron la realización de medidas continuas de temperatura...

In this paper we present a LST product obtained from Advanced Along-Track Scanning Radiometer (AATSR) data. The product has been validated with in situ measurements carried out in the framework of the CarboEurope-Flex-Sentinel-2 (CEFLES2) campaign. In addition the paper present a comparison between the proposed product and the LST retrieved from different

The CEOP-AEGIS (Coordinated Asia-European long-term Observing system of Qinghai-Tibet Plateau hydro-meteorological processes and the Asian-monsoon systEm with Ground satellite Image data and numerical Simulations) project focuses on the water cycle on the Tibet Plateau and its surroundings. This region provides water to half of the human kind, and the understanding of its water cycle is therefore of utmost importance in the light of global warming. A key element in the study of the water cycle is the Land Surface Temperature (LST) since it characterizes the evapo-transpiration regime of the vegetation. To that end, LST retrieval algorithms were developed and adapted for the estimation of LST from various sensors: ERS (European Remote Sensing satellite)/ATSR2 (Along Track Scanning Radiometer), ENVISAT (Environmental Satellite)/AATSR (Advanced Along-Track Scanning Radiometer), TERRA/MODIS (MODerate resolution Imaging Spectroradiometer), AQUA/MODIS, NOAA-07 (National Oceanic and Atmosp...

ABSTRACT Land Surface Temperature (LST) is one of the key parameters in the physics of land-surface processes on regional and global scales, combining the results of all the surface-atmosphere interactions and energy fluxes between the surface and the atmosphere. Because of the strong heterogeneity in land surface characteristics such as vegetation, topography and soil physical properties, LST changes rapidly in space as well as in time. An adequate characterization of LST distribution and its temporal evolution, therefore, requires measurements with detailed spatial and temporal frequencies. With the advent of the ESA's Sentinel 2 and 3 series of satellites a unique opportunity exists to go beyond the current state of the art of single instrument algorithms. In this work we explore the synergistic use of future MSI instrument on board Sentinel-2 platform and OLCI/SLSTR instruments on board Sentinel-3 platform in order to improve LST products currently derived from the single AATSR instrument on board the ENVISAT satellite. For this purpose, the high spatial resolution data from Sentinel2/MSI will be used for a good characterization of the land surface sub-pixel heterogeneity, in particular for a precise parameterization of surface emissivity using a land cover map and spectral mixture techniques. On the other hand, the high spectral resolution of OLCI instrument, suitable for a better characterization of the atmosphere, along with the dual-view available in the SLTSR instrument, will allow a better atmospheric correction through improved aerosol/water vapor content retrievals and the implementation of novel cloud screening procedures. Effective emissivity and atmospheric corrections will allow accurate LST retrievals using the SLTSR thermal bands by developing a synergistic split-window/dual-angle algorithm. ENVISAT MERIS and AATSR instruments and different high spatial resolution data (Landsat/TM, Proba/CHRIS, Terra/ASTER) will be used as a benchmark for the future OLCI, SLTSR and MSI instruments. Results will be validated using ground data collected in the framework of different field campaigns organized by ESA.

We present an analysis of the laboratory reflectance and emissivity spectra of 11 soil samples collected on different field campaigns carried out over a diverse suite of test sites in Europe, North Africa, and South America from 2002 to 2008. Hemispherical reflectance spectra were measured from 2.0 to 14 microm with a Fourier transform infrared spectrometer, and x-ray diffraction analysis (XRD) was used to determine the mineralogical phases of the soil samples. Emissivity spectra were obtained from the hemispherical reflectance measurements using Kirchhoff's law and compared with in situ radiance measurements obtained with a CIMEL Electronique CE312-2 thermal radiometer and converted to emissivity using the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) temperature and emissivity separation algorithm. The CIMEL has five narrow bands at approximately the same positions as the ASTER. Results show a root mean square error typically below 0.015 between labora...

... LAND COVER DYNAMIC IN THE MEDITERRANEAN BASIN JA SOBRINO, J. CUENCA, J. EL KHARRAZ, M. GOMEZ, JC JIMENEZ, N. RAISSOUNI, and ... In order to estimate the Q parameter, different types of vegetated structures: legume, vineyard, orange grove and forest have ...

– In this work we show the GEA prototype (an environmental information manager) in order to assess water deficits over the irrigated crops of large areas. The proposed solution consists of evapotranspiration and water deficit estimations from remote sensing and agrometeorological information. The designed prototype is composed of three modules: (i) a geostatistical module, which generates precipitation and reference evapotranspiration maps from measurements collected in agrometeorological stations; (ii) an image processing module, which processes remote sensing images (Landsat) in order to derive canopy parameters and real evapotranspiration following the "two-steps" FAO method, where the crop coefficient is obtained from remote sensing data and an empirical relationship proposed by the Instituto de Desarrollo Regional IDR of the Universidad de Castilla-La Mancha; and (iii) a module which uses information technologies to develop the GEA on-line application, which allows th...

Land surface temperature and emissivity retrieved from thermal infrared data are key variables for interpreting carbon, water and energy fluxes at the biosphere-atmosphere interface. Several authors have studied angular effects in the thermal infrared region, which is an important issue to obtain valuable information on canopy characteristics and in order to work with relatively new sensors including directional thermal infrared

We have applied a Land Surface Temperature algorithm to the whole Pathfinder AVHRR Land (PAL) database, aiming at studying the evolution of the vegetation at a global scale. The Land Surface Temperature parameter, along with NDVI, will allow retrieving vegetation changes between July 1981 and September 2001. We have also built a classification which takes into account both vegetation variations

In this paper, a methodology is presented to estimate evapotranspiration, net radiation flux and heat soil flux, using an energy balance model from DAIS (Digital Airborne Image Spectrometer) data. The images were obtained from the Barrax site over Castilla La Mancha (Spain) in the framework of DAISEX (Digital Airborne Imaging Spectrometer Experiments) campaigns, a series of experiments supported by ESA in 1999 (DAISEX-99). The theoretical error in daily estimated evapotranspiration, is around 15 %, and when we compared the daily evapotranspiration values obtained with the in situ measured a difference lower than 1 mm/day has been obtained.

ABSTRACT 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.

ABSTRACT Recent advances in spatial and spectral resolution of satellite imagery as well as in processing techniques are opening new possibilities of fine-scale vegetation analysis with interesting applications in natural resource management. Here we present the main results of a study carried out in Sierra Morena, Cordoba southern Spain, aimed at assessing the potential of remote-sensing techniques to discriminate and map individual wild pear trees Pyrus bourgaeana in Mediterranean open woodland dominated by Quercus ilex . We used high spatial resolution 2.4 m multispectral/0.6 m panchromatic QuickBird satellite imagery obtained during the summer of 2008. Given the size and features of wild pear tree crowns, we applied an atmospheric correction method, Fast Line-of-Sight Atmospheric Analysis of Spectral Hypercube FLAASH, and six different fusion ‘pan-sharpening’ methods wavelet ‘ à trous ’ weighted transform, colour normalized CN, Gram–Schmidt GS, hue–saturation–intensity HSI colour transformation, multidirection–multiresolution MDMR, and principal component PC, to determine which procedure provides the best results. Finally, we assessed the potential of supervised classification techniques maximum likelihood to discriminate and map individual wild pear trees scattered over the Mediterranean open woodland.

ABSTRACT Atmospheric corrections for hyperspectral thermal images acquired with nadir, horizontal, and oblique views have typically relied on atmospheric modelling software, such as Moderate Resolution Atmospheric Transmission MODTRAN, to estimate atmospheric parameters. Data-only corrections, which require only information from the scene, are more versatile and less labour intensive, but do not yet seem to have been applied to horizontal and oblique views. Here, we apply, and modify where necessary, one published data-only algorithm in-scene atmospheric correction ISAC to nadir, horizontal, and slanted views The Aerospace Corporation's Spatially Enhanced Broadband Array Spectrograph System SEBASS and Telops Inc.'s Hyper-Cam data sets to assess the applicability for different viewing geometries. We find that it successfully retrieves characteristic mineralogical emissivity spectra in scenes taken from all geometries. We also discuss additional corrections to the Hyper-Cam data set to correct for instrumental artefacts.

A simple approach for correcting for the effect of vegetation in the estimation of the surface soil moisture $(w_{\rm S})$ from L-band passive microwave observations is presented in this study. The approach is based on semi-empirical relationships between soil moisture and the polarized reflectivity including the effect of the vegetation optical depth which is parameterized as a function of the

Land surface energy fluxes are required in many environmental studies, including hydrology, agronomy and meteorology. Surface energy balance models simulate microscale energy exchange processes between the ground surface and the atmospheric layer near ground level. Spatial variability of energy fluxes limits point measurements to be used for larger areas. Remote sensing provides the basis for spatial mapping of energy fluxes.

RESUMEN Entre el 23 de junio y el 6 de julio de 2008 tuvo lugar en Madrid la campaña experimental DESIREX2008 (Dualuse European Security IR Experiment 2008), de la agencia espacial europea ESA, con el objetivo de estudiar el efecto de isla de calor en ...

ABSTRACT Poster presentado en el Congreso Airborne Imaging Spectroscopy Workshop, Bruges, Belgium, 7/10/2005 Methods for water stress and chlorosis detection in crops are presented using the Airborne Hyperspectral Scanner (AHS), Compact Airborne Spectrographic Imager (CASI) and the Reflective Optics System Imaging Spectrometer (ROSIS) airborne sensors. The AHS sensor was used to acquire images of 2-m spatial resolution in the visible, near infrared and thermal spectral regions over an olive orchard in southern Spain to study the spatial variability of water stress and the potential for detecting water deficit conditions at the tree level. ROSIS and CASI sensors were flown at 1 m spatial resolution over 24 vineyard fields with a gradient of nutrient deficiencies, comprising 103 study areas of 10x10 m in size. The AHS sensor was equipped with 20 channels of 20 nm bandwidth for visible and near infrared, 1 channel of 200 nm bandwidth and 42 channels of 13 nm bandwidth for mid infrared, 7 channels of 300 nm bandwidth for short-wave infrared and 10 channels of 400 nm for long-wave infrared. AHS aircraft flights at 7:30, 9:30 and 12:00 GTM in July 2004 were scheduled to study the spatial and temporal variation of the orchard tree temperature as a function of the diurnal variation of water stress. Water and bare soil temperatures were measured simultaneously with airborne sensor flights to calibrate the thermal AHS imagery, acquiring atmospheric optical thickness at the time of image collection. Imagery was processed applying geometric, radiometric and atmospheric correction, obtaining surface temperature with Split-Window algorithms from 17 AHS thermal infrared channels. Water potential, photosynthesis, and stomatal conductance were measured in the field under 3 different water stress treatments weekly from July until November 2004 to track the effects of water stress on the tree status and functioning. Yield data on each olive tree and vineyard 10x10 m study site were measured, including indicators of yield quality. Results obtained between different indicators of yield and quality with i) crown temperature as function of water deficit in olive trees, and ii) chlorosis detection in vineyards as function of nutrient deficiencies will be presented. This methodology shows potential for mapping the spatial variability of water stress and nutrient deficiencies in precision agriculture, enabling the connection with yield reduction as function of stress detection. Peer reviewed