José A. Sobrino | Universitat de València (original) (raw)

Papers by José A. Sobrino

Recent Advances in Remote Sensing, 2024

The objective of this article was to develop a methodology for the burned areas delimitation and ... more The objective of this article was to develop a methodology for the burned areas delimitation and fire severity assessment in forest fires occurred in Spain between 2018 and 2022. As input data, this study was based on the use of Sentinel-2 spectral indices, which are characterized by having spectral bands in the near-infrared (NIR) and shortwave infrared (SWIR) spectral regions, allowing a high distinction between burned and unburned areas, and between different fire severity degrees too. All possible combinations between Sentinel-2 bands applied to a spectral normalized difference index (SP) were analyzed, along with the most commonly used burn spectral indices in remote sensing as the Burned Area Index (BAI), the Burned Area Index for Sentinel-2 (BAIS2), the Mid-Infrared Burn Index (MIRBI), the Normalized Burn Ratio (NBR), the Relativized Burn Ratio (RBR) and the relative differential Normalized Burn Ratio (RdNBR). In addition, in order to delete confusions between burned area and the presence of other land cover areas, the Sentinel-2 Global Land Cover (S2GLC 2017) and the temporal differences between pre-fire and post-fire dates were obtained for each spectral index (dSP). The results were compared by: in the case of burned areas, the Emergency Mapping Service (EMS) and the Galicia forest service; in the case of fire severity, using field plots classified as in Ruiz-Gallardo et al. (2004) study (null, low, moderate and high severity). The final statistic results obtained showed that the dNBR2 spectral index (using B11 and B12 Sentinel-2 spectral bands) provided the highest results of burned area delimitation (7% of commission error and 3% omission error, respectively) whereas, the combination of the BAIS2, the NBR and the modified Normalized Burn Ratio (NBR2, using B7 and B12 Sentinel-2 spectral bands), used in areas with low, mix and full vegetation respectively, provided the highest results in fire severity assessment (kappa statistic, F1-score and Balanced Accuracy equal to 0.87, 0.86 and 0.92, respectively). The methodology developed in this work allows obtaining accurate maps of burned area and fire severity in Spain, contributing to the reinforcement of national forest fires statistics.

Recent Advances in Remote Sensing, 2024

The Lake Surface Water Temperature (LSWT) evolution is analysed in ten of the largest lakes innth... more The Lake Surface Water Temperature (LSWT) evolution is analysed in ten of the largest lakes innthe world: Caspian Sea, Superior, Victoria, Huron, Michigan, Tanganyika, Baikal, Great Slave Lake, Erie and Ontario. The time span selected is 2003-2020 and the satellite product, MODIS Level 3
SST Thermal IR 8 Day 4km V2019.0. Results show warming trends ranging from 0.012◦C/yr. in the Victoria Lake to 0.083 ◦C/yr in the Baikal Lake. Results have been validated with the product MOD11L2 LSWT estimations for the years 2003-2014 in the Laurentian Great Lakes, obtaining correlations between 0.962 and a 0.998. The validation has been enlarged by considering Sentinel 3 observations from the Issyk-Kul lake, with a 0.99 correlation. The validation shows that the MODIS SST product is capable of estimating the LSWT parameter with a high precision.

Remote Sensing of Environment, Oct 1, 2010

Lecture Notes in Computer Science, 1997

The use of time frequency distributions (TFDs) with adaptive kernels for the spectral estimation ... more The use of time frequency distributions (TFDs) with adaptive kernels for the spectral estimation of non stationary signals has been shown to be an extremely useful tool in many applications. Nevertheless, their high computational cost, due to the necessity to calculate a new kernel in each time instance, poses an important problem in real time applications. Given that many real signals show intervals of relative stationarity, in this work we propose an algorithm for the control of the instant of adaptation in this type of technique, based on ...

A series of dual-angle and split-window algorithms is presented for estimating sea (SST) and land... more A series of dual-angle and split-window algorithms is presented for estimating sea (SST) and land surface temperature (LST) from the Advanced Along-Track Scanning Radiometer (AATSR). The numerical values of the coefficients have been obtained from statistical regression method using synthetic data. The algorithms have been tested with simulated and real AATSR data. Comprehensive sensitivity and error analysis has been made to evaluate the performance of the proposed algorithms. A comparison using synthetic data suggests better results from the dual-angle algorithms than from the split-window ones and that the algorithms with water vapour dependence give an improvement of the accuracy of the results. A validation of split-window algorithms using a classification method shows a rmse better than 1.6 K. However, one of the conditions for precise dual-angle algorithms is an accurate knowledge of the angular variation of surface emissivity in the thermal infrared region. We provide angular emissivity measurements for representative samples (water, sand, clay, loam and gravel). The measurements have been made with a thermal infrared radiometer at angles from 0 to 60 degrees. The results show a general decrease of the emissivity with increasing viewing angles.

Http Dx Doi Org 10 1080 01431161003762363, Mar 28, 2011

In past decades, the Iberian Peninsula has been shown to have suffered vegetation changes such as... more 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.

Urban Ecosystems, 2014

ABSTRACT Urbanization is one of the most extreme forms of land alteration. Energy fluxes are seve... more ABSTRACT Urbanization is one of the most extreme forms of land alteration. Energy fluxes are severely affected and cities tend to have the Urban Heat Island (UHI) phenomenon, although vegetated areas inside cities could have a positive effect in mitigating UHI effect. Our main objective was to analyze the relationship between vegetation characteristics, patch size and land surface temperature (LST) in three urban areas of northwestern Argentina. We selected 38 green spaces of different size distributed in four cities, all located in the eastern foothills of the subtropical mountain forests. We used Landsat TM satellite images to calculate Normalized Difference Vegetation Index (NDVI) and LST. We assessed the net effect of patch size on LST by computing a Difference Temperature Index. At the regional scale, our results showed that vegetation patch size had a direct effect on reducing the LST of the green space. At a local scale, the analysis of the relationship between vegetation on urban green spaces and LST along a gradient of urbanization showed that green spaces with more vegetation tends to reduce LST. The results showed that largest green spaces were between 1.5 and 2.8 °C cooler than the surrounding built. In order to mitigate the UHI effect in cities, larger green spaces appear to be a possible solution

Remote Sensing of Environment, 2004

In this paper, three methods to retrieve the land surface temperature (LST) from thermal infrared... more In this paper, three methods to retrieve the land surface temperature (LST) from thermal infrared data supplied by band 6 of the Thematic Mapper (TM) sensor onboard the Landsat 5 satellite are compared. The first of them lies on the estimation of the land surface temperature from the radiative transfer equation using in situ radiosounding data. The others two are the mono-window algorithm developed by Qin et al. [International Journal of Remote Sensing 22 (2001) 3719] and the single-channel algorithm developed by Jiménez-Muñoz and Sobrino [Journal of Geophysical Research 108 ]. The land surface emissivity (LSE) values needed in order to apply these methods have been estimated from a methodology that uses the visible and near infrared bands. Finally, we present a comparison between the LST measured in situ and the retrieved by the algorithms over an agricultural region of Spain (La Plana de Requena-Utiel). The results show a root mean square deviation (rmsd) of 0.009 for emissivity and lower than 1 K for land surface temperature when the Jiménez-Muñoz algorithm is used.

Journal of Geophysical Research, 2005

1] SPECTRA (Surface Processes and Ecosystem Changes Through Response Analysis) is one of the core... more 1] SPECTRA (Surface Processes and Ecosystem Changes Through Response Analysis) is one of the core candidate missions which is being proposed for implementation in the European Space Agency (ESA) Earth Explorer program of research oriented missions. The scientific objective of the SPECTRA mission is to describe, understand, and model the role of terrestrial vegetation in the global carbon cycle and its response to climate variability under the increasing pressure of human activity. The SPECTRA satellite will embark an optical hyperspectral payload covering the solar spectral range (0.4 to 2.4 mm) and thermal infrared region (10.3 to 12.3 mm). This paper is focused on the land surface temperature retrieval from SPECTRA thermal infrared data. In the first part of the paper, generalized single-channel and split-window methods are discussed and compared, showing that single-channel methods provide similar or better results than split-window methods for low atmospheric water vapor content, whereas split-window methods always provide better results for high atmospheric water vapor content. In the second part of the paper, split-window and dual-angle algorithms have been developed for SPECTRA thermal channels. A sensitivity analysis of the algorithms has been also carried out, revealing total errors for split-window algorithms of around 1.5 K. For dual-angle algorithms, total errors less than 1 K are obtained when the combination nadir-60°is considered. Finally, a dual-angle algorithm for sea surface temperature retrieval has been developed for different view angles. The study of the variation of the total error with observation angle allows estimation of the best nadir-forward combination. Hence an optimal forward view of 52°referred to the observer zenithal angle (or 45°for satellite view angle) has been obtained, leading to an error of 0.4 K when the sensor noise error is 0.1 K and 0.3 K when the sensor noise error is 0.05 K.

International Journal of Remote Sensing, 2011

International Journal of Remote Sensing, 2006

Radiometric corrections serve to remove the effects that alter the spectral characteristics of la... more Radiometric corrections serve to remove the effects that alter the spectral characteristics of land features, except for actual changes in ground target, becoming mandatory in multi-sensor, multi-date studies. In this paper, we evaluate the effects of two types of radiometric correction methods (absolute and relative) for the determination of land cover changes, using Landsat TM and Landsat ETM + images. In addition, we present an improvement made to the relative correction method addressed. Absolute correction includes a crosscalibration between TM and ETM + images, and the application of an atmospheric correction protocol. Relative correction normalizes the images using pseudo-invariant features (PIFs) selected through band-to-band PCA analysis. We present a new algorithm for PIFs selection in order to improve normalization results. A post-correction evaluation index (Quadratic Difference Index (QD)), and post-classification and change detection results were used to evaluate the performance of the methods. Only the absolute correction method and the new relative correction method presented in this paper show good postcorrection and post-classification results (QD index < 0; overall accuracy .80%; kappa .0.65) for all the images used. Land cover change estimations based on uncorrected images present unrealistic change rates (two to three times those obtained with corrected images), which highlights the fact that radiometric corrections are necessary in multi-date multi-sensor land cover change analysis.

IEEE Geoscience and Remote Sensing Letters, 2000

The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) provides the user comm... more The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) provides the user community with standard products of land-surface temperature (LST) and emissivity using the temperature and emissivity separation (TES) algorithm. This letter analyzes the feasibility of using two-channel (TC) algorithms for LST retrieval from ASTER data, which could be considered as an alternative or complementary procedure to the TES algorithm. TC algorithms have been developed for all the ASTER thermal infrared bands combinations, and they have been applied to six ASTER images acquired over an agricultural area of Spain in 2000, 2001, and 2004. LST values obtained with TC algorithms were compared with the TES product. In addition, the TC algorithms were tested using simulated data and ground-based measurements collected coincident with the ASTER acquisition in 2004. The results show that TC algorithms provide similar accuracies than the TES algorithm (∼1.5 K), with the main advantage that the atmospheric correction is included in the algorithm itself.

IEEE Geoscience and Remote Sensing Letters, 2000

This letter presents an adaptation to Advanced Spaceborne Thermal Emission and Reflection Radiome... more This letter presents an adaptation to Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data of the generalized single-channel (SC) algorithm developed by Jiménez-Muñoz and Sobrino, also adapted to the Landsat thermal-infrared (TIR) channel (band 6) later by Jiménez-Muñoz et al. The SC algorithm relies on the concept of atmospheric functions (AFs), which are dependent on atmospheric transmissivity, upwelling, and downwelling atmospheric radiances. These AFs are fitted versus the atmospheric watervapor content for operational purposes, despite the fact that other computation options are also possible. The SC algorithm has been adapted to ASTER TIR bands 13 (10.659 μm) and 14 (11.289 μm), located in the typical split-window region (10.5-12 μm), where transmission through the atmosphere is higher and surface emissivity variations are lower in comparison with the ones in the 8-9.4 μm spectral region. Land-surface temperature retrieved with the SC algorithm has been tested over five different samples (including vegetated plots and bare soil) in an agricultural area using one single image. The comparison with ground-truth data provided a bias near to zero and standard deviations of around 2 K, with bands 13 and 14 providing similar results. Index Terms-Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), land-surface temperature (LST), single-channel (SC), thermal infrared (TIR).

Land surface energy fluxes are required in many environmental studies, including hydrology, agron... more 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. Remote-sensing-based surface energy flux-mapping was conducted using seven Landsat images from 1997 to 2002 at four contiguous crop fields located in Polk County, northwestern Minnesota. Spatially distributed surface energy fluxes were estimated and mapped at 30 m pixel level from Landsat Thematic Mapper and Enhanced Thematic Mapper images and weather information. Net radiation was determined using the surface energy balance algorithm for land (SEBAL) procedure. Applying the two-source energy balance (TSEB) model, the surface temperature and the latent and sensible heat fluxes were partitioned into vegetation and soil components and estimated at the pixel level. Yield data for wheat and soybean from 1997 to 2002 were mapped and compared with latent heat (evapotranspiration) for four of the fields at pixel level. The spatial distribution and the relation of latent heat flux and Bowen ratio (ratio of sensible heat to latent heat) to crop yield were studied. The root-mean-square error and the mean absolute percentage of error between the observed and predicted energy fluxes were between 7 and 22 W m 2 and 12 and 24% respectively. Results show that latent heat flux and Bowen ratio were correlated (positive and negative) to the yield data. Wheat and soybean yields were predicted using latent heat flux with mean R 2 D 0Ð67 and 0Ð70 respectively, average residual means of 4Ð2 bushels/acre and 0Ð11 bushels/acre respectively, and average residual standard deviations of 16Ð2 bushels/acre and 16Ð6 bushels/acre respectively (1 bushel/acre ³ 0Ð087 m 3 ha 1 ). The flux estimation procedure from the SEBAL-TSEB model was useful and applicable to agricultural fields.

Applied Optics, 1999

Multiangle algorithms for estimating sea and land surface temperature with Along-Track Scanning R... more 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-m͒ band of some representative samples was made at angles of 0°-65°͑at 5°increments͒ to the surface normal. The results show a decrease of the emissivity with increasing viewing angle, with water showing the highest angular dependence ͑ϳ7% from 0°to 65°views͒. 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.

Applied Optics, 2004

One condition for precise multiangle algorithms for estimating sea and land surface temperature w... more 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, gravel͒. The measurements are made in one thermal IR broadband ͑8 -13 m͒ and three narrower bands ͑8.2-9.2, 10.3-11.3, and 11.5-12.5 m͒ at angles of 0°-60°͑at 5°increments͒ to the surface normal. The results show a general decrease in emissivity with increasing viewing angles, with the 8.2-9.2-m channel the most sensitive to this dependence and sand the sample showing the greatest variation.

Applied Optics, 2006

Surface emissivities play an important role in thermal remote sensing, since knowledge of them is... more Surface emissivities play an important role in thermal remote sensing, since knowledge of them is required to estimate land surface temperature with enough accuracy. They are also important in other environmental or geological studies. We show the results obtained for the emissivity spectra of different natural surfaces (water, green, and senescent vegetation) by applying the temperature and emissivity separation (TES) algorithm to ground-based measurements collected at the field with a multiband thermal radiometer. The results have been tested with data included in spectral libraries, and rms errors lower than 0.01 have been found, except for senescent vegetation. Two methods are also proposed to apply the TES algorithm to measurements achieved in the laboratory: (i) by heating the sample and (ii) using a box with reflective walls.

Recent Advances in Remote Sensing, 2024

The objective of this article was to develop a methodology for the burned areas delimitation and ... more The objective of this article was to develop a methodology for the burned areas delimitation and fire severity assessment in forest fires occurred in Spain between 2018 and 2022. As input data, this study was based on the use of Sentinel-2 spectral indices, which are characterized by having spectral bands in the near-infrared (NIR) and shortwave infrared (SWIR) spectral regions, allowing a high distinction between burned and unburned areas, and between different fire severity degrees too. All possible combinations between Sentinel-2 bands applied to a spectral normalized difference index (SP) were analyzed, along with the most commonly used burn spectral indices in remote sensing as the Burned Area Index (BAI), the Burned Area Index for Sentinel-2 (BAIS2), the Mid-Infrared Burn Index (MIRBI), the Normalized Burn Ratio (NBR), the Relativized Burn Ratio (RBR) and the relative differential Normalized Burn Ratio (RdNBR). In addition, in order to delete confusions between burned area and the presence of other land cover areas, the Sentinel-2 Global Land Cover (S2GLC 2017) and the temporal differences between pre-fire and post-fire dates were obtained for each spectral index (dSP). The results were compared by: in the case of burned areas, the Emergency Mapping Service (EMS) and the Galicia forest service; in the case of fire severity, using field plots classified as in Ruiz-Gallardo et al. (2004) study (null, low, moderate and high severity). The final statistic results obtained showed that the dNBR2 spectral index (using B11 and B12 Sentinel-2 spectral bands) provided the highest results of burned area delimitation (7% of commission error and 3% omission error, respectively) whereas, the combination of the BAIS2, the NBR and the modified Normalized Burn Ratio (NBR2, using B7 and B12 Sentinel-2 spectral bands), used in areas with low, mix and full vegetation respectively, provided the highest results in fire severity assessment (kappa statistic, F1-score and Balanced Accuracy equal to 0.87, 0.86 and 0.92, respectively). The methodology developed in this work allows obtaining accurate maps of burned area and fire severity in Spain, contributing to the reinforcement of national forest fires statistics.

Recent Advances in Remote Sensing, 2024

The Lake Surface Water Temperature (LSWT) evolution is analysed in ten of the largest lakes innth... more The Lake Surface Water Temperature (LSWT) evolution is analysed in ten of the largest lakes innthe world: Caspian Sea, Superior, Victoria, Huron, Michigan, Tanganyika, Baikal, Great Slave Lake, Erie and Ontario. The time span selected is 2003-2020 and the satellite product, MODIS Level 3
SST Thermal IR 8 Day 4km V2019.0. Results show warming trends ranging from 0.012◦C/yr. in the Victoria Lake to 0.083 ◦C/yr in the Baikal Lake. Results have been validated with the product MOD11L2 LSWT estimations for the years 2003-2014 in the Laurentian Great Lakes, obtaining correlations between 0.962 and a 0.998. The validation has been enlarged by considering Sentinel 3 observations from the Issyk-Kul lake, with a 0.99 correlation. The validation shows that the MODIS SST product is capable of estimating the LSWT parameter with a high precision.

Remote Sensing of Environment, Oct 1, 2010

Lecture Notes in Computer Science, 1997

The use of time frequency distributions (TFDs) with adaptive kernels for the spectral estimation ... more The use of time frequency distributions (TFDs) with adaptive kernels for the spectral estimation of non stationary signals has been shown to be an extremely useful tool in many applications. Nevertheless, their high computational cost, due to the necessity to calculate a new kernel in each time instance, poses an important problem in real time applications. Given that many real signals show intervals of relative stationarity, in this work we propose an algorithm for the control of the instant of adaptation in this type of technique, based on ...

A series of dual-angle and split-window algorithms is presented for estimating sea (SST) and land... more A series of dual-angle and split-window algorithms is presented for estimating sea (SST) and land surface temperature (LST) from the Advanced Along-Track Scanning Radiometer (AATSR). The numerical values of the coefficients have been obtained from statistical regression method using synthetic data. The algorithms have been tested with simulated and real AATSR data. Comprehensive sensitivity and error analysis has been made to evaluate the performance of the proposed algorithms. A comparison using synthetic data suggests better results from the dual-angle algorithms than from the split-window ones and that the algorithms with water vapour dependence give an improvement of the accuracy of the results. A validation of split-window algorithms using a classification method shows a rmse better than 1.6 K. However, one of the conditions for precise dual-angle algorithms is an accurate knowledge of the angular variation of surface emissivity in the thermal infrared region. We provide angular emissivity measurements for representative samples (water, sand, clay, loam and gravel). The measurements have been made with a thermal infrared radiometer at angles from 0 to 60 degrees. The results show a general decrease of the emissivity with increasing viewing angles.

Http Dx Doi Org 10 1080 01431161003762363, Mar 28, 2011

In past decades, the Iberian Peninsula has been shown to have suffered vegetation changes such as... more 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.

Urban Ecosystems, 2014

ABSTRACT Urbanization is one of the most extreme forms of land alteration. Energy fluxes are seve... more ABSTRACT Urbanization is one of the most extreme forms of land alteration. Energy fluxes are severely affected and cities tend to have the Urban Heat Island (UHI) phenomenon, although vegetated areas inside cities could have a positive effect in mitigating UHI effect. Our main objective was to analyze the relationship between vegetation characteristics, patch size and land surface temperature (LST) in three urban areas of northwestern Argentina. We selected 38 green spaces of different size distributed in four cities, all located in the eastern foothills of the subtropical mountain forests. We used Landsat TM satellite images to calculate Normalized Difference Vegetation Index (NDVI) and LST. We assessed the net effect of patch size on LST by computing a Difference Temperature Index. At the regional scale, our results showed that vegetation patch size had a direct effect on reducing the LST of the green space. At a local scale, the analysis of the relationship between vegetation on urban green spaces and LST along a gradient of urbanization showed that green spaces with more vegetation tends to reduce LST. The results showed that largest green spaces were between 1.5 and 2.8 °C cooler than the surrounding built. In order to mitigate the UHI effect in cities, larger green spaces appear to be a possible solution

Remote Sensing of Environment, 2004

In this paper, three methods to retrieve the land surface temperature (LST) from thermal infrared... more In this paper, three methods to retrieve the land surface temperature (LST) from thermal infrared data supplied by band 6 of the Thematic Mapper (TM) sensor onboard the Landsat 5 satellite are compared. The first of them lies on the estimation of the land surface temperature from the radiative transfer equation using in situ radiosounding data. The others two are the mono-window algorithm developed by Qin et al. [International Journal of Remote Sensing 22 (2001) 3719] and the single-channel algorithm developed by Jiménez-Muñoz and Sobrino [Journal of Geophysical Research 108 ]. The land surface emissivity (LSE) values needed in order to apply these methods have been estimated from a methodology that uses the visible and near infrared bands. Finally, we present a comparison between the LST measured in situ and the retrieved by the algorithms over an agricultural region of Spain (La Plana de Requena-Utiel). The results show a root mean square deviation (rmsd) of 0.009 for emissivity and lower than 1 K for land surface temperature when the Jiménez-Muñoz algorithm is used.

Journal of Geophysical Research, 2005

1] SPECTRA (Surface Processes and Ecosystem Changes Through Response Analysis) is one of the core... more 1] SPECTRA (Surface Processes and Ecosystem Changes Through Response Analysis) is one of the core candidate missions which is being proposed for implementation in the European Space Agency (ESA) Earth Explorer program of research oriented missions. The scientific objective of the SPECTRA mission is to describe, understand, and model the role of terrestrial vegetation in the global carbon cycle and its response to climate variability under the increasing pressure of human activity. The SPECTRA satellite will embark an optical hyperspectral payload covering the solar spectral range (0.4 to 2.4 mm) and thermal infrared region (10.3 to 12.3 mm). This paper is focused on the land surface temperature retrieval from SPECTRA thermal infrared data. In the first part of the paper, generalized single-channel and split-window methods are discussed and compared, showing that single-channel methods provide similar or better results than split-window methods for low atmospheric water vapor content, whereas split-window methods always provide better results for high atmospheric water vapor content. In the second part of the paper, split-window and dual-angle algorithms have been developed for SPECTRA thermal channels. A sensitivity analysis of the algorithms has been also carried out, revealing total errors for split-window algorithms of around 1.5 K. For dual-angle algorithms, total errors less than 1 K are obtained when the combination nadir-60°is considered. Finally, a dual-angle algorithm for sea surface temperature retrieval has been developed for different view angles. The study of the variation of the total error with observation angle allows estimation of the best nadir-forward combination. Hence an optimal forward view of 52°referred to the observer zenithal angle (or 45°for satellite view angle) has been obtained, leading to an error of 0.4 K when the sensor noise error is 0.1 K and 0.3 K when the sensor noise error is 0.05 K.

International Journal of Remote Sensing, 2011

International Journal of Remote Sensing, 2006

Radiometric corrections serve to remove the effects that alter the spectral characteristics of la... more Radiometric corrections serve to remove the effects that alter the spectral characteristics of land features, except for actual changes in ground target, becoming mandatory in multi-sensor, multi-date studies. In this paper, we evaluate the effects of two types of radiometric correction methods (absolute and relative) for the determination of land cover changes, using Landsat TM and Landsat ETM + images. In addition, we present an improvement made to the relative correction method addressed. Absolute correction includes a crosscalibration between TM and ETM + images, and the application of an atmospheric correction protocol. Relative correction normalizes the images using pseudo-invariant features (PIFs) selected through band-to-band PCA analysis. We present a new algorithm for PIFs selection in order to improve normalization results. A post-correction evaluation index (Quadratic Difference Index (QD)), and post-classification and change detection results were used to evaluate the performance of the methods. Only the absolute correction method and the new relative correction method presented in this paper show good postcorrection and post-classification results (QD index < 0; overall accuracy .80%; kappa .0.65) for all the images used. Land cover change estimations based on uncorrected images present unrealistic change rates (two to three times those obtained with corrected images), which highlights the fact that radiometric corrections are necessary in multi-date multi-sensor land cover change analysis.

IEEE Geoscience and Remote Sensing Letters, 2000

The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) provides the user comm... more The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) provides the user community with standard products of land-surface temperature (LST) and emissivity using the temperature and emissivity separation (TES) algorithm. This letter analyzes the feasibility of using two-channel (TC) algorithms for LST retrieval from ASTER data, which could be considered as an alternative or complementary procedure to the TES algorithm. TC algorithms have been developed for all the ASTER thermal infrared bands combinations, and they have been applied to six ASTER images acquired over an agricultural area of Spain in 2000, 2001, and 2004. LST values obtained with TC algorithms were compared with the TES product. In addition, the TC algorithms were tested using simulated data and ground-based measurements collected coincident with the ASTER acquisition in 2004. The results show that TC algorithms provide similar accuracies than the TES algorithm (∼1.5 K), with the main advantage that the atmospheric correction is included in the algorithm itself.

IEEE Geoscience and Remote Sensing Letters, 2000

This letter presents an adaptation to Advanced Spaceborne Thermal Emission and Reflection Radiome... more This letter presents an adaptation to Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data of the generalized single-channel (SC) algorithm developed by Jiménez-Muñoz and Sobrino, also adapted to the Landsat thermal-infrared (TIR) channel (band 6) later by Jiménez-Muñoz et al. The SC algorithm relies on the concept of atmospheric functions (AFs), which are dependent on atmospheric transmissivity, upwelling, and downwelling atmospheric radiances. These AFs are fitted versus the atmospheric watervapor content for operational purposes, despite the fact that other computation options are also possible. The SC algorithm has been adapted to ASTER TIR bands 13 (10.659 μm) and 14 (11.289 μm), located in the typical split-window region (10.5-12 μm), where transmission through the atmosphere is higher and surface emissivity variations are lower in comparison with the ones in the 8-9.4 μm spectral region. Land-surface temperature retrieved with the SC algorithm has been tested over five different samples (including vegetated plots and bare soil) in an agricultural area using one single image. The comparison with ground-truth data provided a bias near to zero and standard deviations of around 2 K, with bands 13 and 14 providing similar results. Index Terms-Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), land-surface temperature (LST), single-channel (SC), thermal infrared (TIR).

Land surface energy fluxes are required in many environmental studies, including hydrology, agron... more 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. Remote-sensing-based surface energy flux-mapping was conducted using seven Landsat images from 1997 to 2002 at four contiguous crop fields located in Polk County, northwestern Minnesota. Spatially distributed surface energy fluxes were estimated and mapped at 30 m pixel level from Landsat Thematic Mapper and Enhanced Thematic Mapper images and weather information. Net radiation was determined using the surface energy balance algorithm for land (SEBAL) procedure. Applying the two-source energy balance (TSEB) model, the surface temperature and the latent and sensible heat fluxes were partitioned into vegetation and soil components and estimated at the pixel level. Yield data for wheat and soybean from 1997 to 2002 were mapped and compared with latent heat (evapotranspiration) for four of the fields at pixel level. The spatial distribution and the relation of latent heat flux and Bowen ratio (ratio of sensible heat to latent heat) to crop yield were studied. The root-mean-square error and the mean absolute percentage of error between the observed and predicted energy fluxes were between 7 and 22 W m 2 and 12 and 24% respectively. Results show that latent heat flux and Bowen ratio were correlated (positive and negative) to the yield data. Wheat and soybean yields were predicted using latent heat flux with mean R 2 D 0Ð67 and 0Ð70 respectively, average residual means of 4Ð2 bushels/acre and 0Ð11 bushels/acre respectively, and average residual standard deviations of 16Ð2 bushels/acre and 16Ð6 bushels/acre respectively (1 bushel/acre ³ 0Ð087 m 3 ha 1 ). The flux estimation procedure from the SEBAL-TSEB model was useful and applicable to agricultural fields.

Applied Optics, 1999

Multiangle algorithms for estimating sea and land surface temperature with Along-Track Scanning R... more 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-m͒ band of some representative samples was made at angles of 0°-65°͑at 5°increments͒ to the surface normal. The results show a decrease of the emissivity with increasing viewing angle, with water showing the highest angular dependence ͑ϳ7% from 0°to 65°views͒. 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.

Applied Optics, 2004

One condition for precise multiangle algorithms for estimating sea and land surface temperature w... more 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, gravel͒. The measurements are made in one thermal IR broadband ͑8 -13 m͒ and three narrower bands ͑8.2-9.2, 10.3-11.3, and 11.5-12.5 m͒ at angles of 0°-60°͑at 5°increments͒ to the surface normal. The results show a general decrease in emissivity with increasing viewing angles, with the 8.2-9.2-m channel the most sensitive to this dependence and sand the sample showing the greatest variation.

Applied Optics, 2006

Surface emissivities play an important role in thermal remote sensing, since knowledge of them is... more Surface emissivities play an important role in thermal remote sensing, since knowledge of them is required to estimate land surface temperature with enough accuracy. They are also important in other environmental or geological studies. We show the results obtained for the emissivity spectra of different natural surfaces (water, green, and senescent vegetation) by applying the temperature and emissivity separation (TES) algorithm to ground-based measurements collected at the field with a multiband thermal radiometer. The results have been tested with data included in spectral libraries, and rms errors lower than 0.01 have been found, except for senescent vegetation. Two methods are also proposed to apply the TES algorithm to measurements achieved in the laboratory: (i) by heating the sample and (ii) using a box with reflective walls.