Jose Gomez-Dans | University College London (original) (raw)

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Papers by Jose Gomez-Dans

Surveys in Geophysics

Imaging spectroscopy (IS), also commonly known as hyperspectral remote sensing, is a powerful 13 ... more Imaging spectroscopy (IS), also commonly known as hyperspectral remote sensing, is a powerful 13 remote sensing technique for the monitoring of the Earth's surface and atmosphere. Pixels in optical hyper-14 spectral images consist of continuous reflectance spectra formed by hundreds of narrow spectral channels, 15 allowing an accurate representation of the surface composition through spectroscopic techniques. However, 16 technical constraints in the definition of imaging spectrometers make spectral coverage and resolution to 17 be usually traded by spatial resolution and swath width, as opposed to optical multispectral (MS) systems 18 typically designed to maximize spatial and/or temporal resolution. This complementarity suggests that a 19 synergistic exploitation of spaceborne IS and MS data would be an optimal way to fulfill those remote 20 sensing applications requiring not only high spatial and temporal resolution data, but also rich spectral in-21 formation. On the other hand, IS has been shown to yield a strong synergistic potential with non-optical 22 remote sensing methods, such as thermal infrared (TIR) and light detection and ranging (LiDAR). In this 23 contribution we review theoretical and methodological aspects of potential synergies between optical IS 24 and other remote sensing techniques. The focus is put on the evaluation of synergies between spaceborne 25 optical IS and MS systems because of the expected availability of the two types of data in the next years.

Mitigating the impact of atmospheric effects on optical data is a critical for monitoringland pro... more Mitigating the impact of atmospheric effects on optical data is a critical for monitoringland processes. Consistent approaches to different sensors, which also quantify uncertainty, are required to combine surface reflectance observations from heterogeneous sensors. This paper provides a sensor agnostic approach to atmospheric correction, called SIAC. It exploits operational global datasets on (i) coarse resolution spectral surface bi-directional reflectance distribution function (BRDF) and (ii) coarse resolution atmospheric composition. The method infers aerosol optical thickness (AOT) and total columnar water vapour (TCWV) from top of atmosphere (TOA) reflectance observations, using a Bayesian framework that exploits the MODIS MCD43 BRDF descriptor product and the Copernicus Atmosphere Monitoring Service (CAMS) operational forecasts of AOT and TCWV to provide an \emph{a priori} estimate. Spatial smoothness constraints are assumed for AOT and TCWV, and efficient statistical approxi...

This MS describes a sensitivity analysis of the SPITFIRE fire model coupled to the Lund-Potsdam-J... more This MS describes a sensitivity analysis of the SPITFIRE fire model coupled to the Lund-Potsdam-Jena (LPJ) dynamic global vegetation model (DGVM). The study aims to investigate the parameters that control how the fire model calculates burnt area across different ecosystems. In different fire systems, different parameters are found to have higher sensitivity to burnt area, but in general, parameters controlling rate of spread and ignitions.

Scientific reports, Jan 31, 2018

Accurate terrestrial biosphere model (TBM) simulations of gross carbon uptake (gross primary prod... more Accurate terrestrial biosphere model (TBM) simulations of gross carbon uptake (gross primary productivity - GPP) are essential for reliable future terrestrial carbon sink projections. However, uncertainties in TBM GPP estimates remain. Newly-available satellite-derived sun-induced chlorophyll fluorescence (SIF) data offer a promising direction for addressing this issue by constraining regional-to-global scale modelled GPP. Here, we use monthly 0.5° GOME-2 SIF data from 2007 to 2011 to optimise GPP parameters of the ORCHIDEE TBM. The optimisation reduces GPP magnitude across all vegetation types except C4 plants. Global mean annual GPP therefore decreases from 194 ± 57 PgCyr to 166 ± 10 PgCyr, bringing the model more in line with an up-scaled flux tower estimate of 133 PgCyr. Strongest reductions in GPP are seen in boreal forests: the result is a shift in global GPP distribution, with a ~50% increase in the tropical to boreal productivity ratio. The optimisation resulted in a greater...

Remote Sensing

Biomass burning is a global phenomenon and systematic burned area mapping is of increasing import... more Biomass burning is a global phenomenon and systematic burned area mapping is of increasing importance for science and applications. With high spatial resolution and novelty in band design, the recently launched Sentinel-2A satellite provides a new opportunity for moderate spatial resolution burned area mapping. This study examines the performance of the Sentinel-2A Multi Spectral Instrument (MSI) bands and derived spectral indices to differentiate between unburned and burned areas. For this purpose, five pairs of pre-fire and post-fire top of atmosphere (TOA reflectance) and atmospherically corrected (surface reflectance) images were studied. The pixel values of locations that were unburned in the first image and burned in the second image, as well as the values of locations that were unburned in both images which served as a control, were compared and the discrimination of individual bands and spectral indices were evaluated using parametric (transformed divergence) and non-parametric (decision tree) approaches. Based on the results, the most suitable MSI bands to detect burned areas are the 20 m near-infrared, short wave infrared and red-edge bands, while the performance of the spectral indices varied with location. The atmospheric correction only significantly influenced the separability of the visible wavelength bands. The results provide insights that are useful for developing Sentinel-2 burned area mapping algorithms.

IEEE Geoscience and Remote Sensing Magazine, 2016

Gaussian Process (GP) has experienced tremendous success in bio-geophysical parameter retrieval i... more Gaussian Process (GP) has experienced tremendous success in bio-geophysical parameter retrieval in the last years. It goes without saying that GPs constitute a solid Bayesian framework to formulate many function approximation problems consistently. This paper reviews the main theoretical GP developments in the field. We review new algorithms that respect the signal and noise characteristics, that extract knowledge via automatic relevance kernels to yield feature rankings automatically, that allow applicability of associated uncertainty intervals to transport GP models in space and time, that can be used to uncover causal relations between variables, and that can encode physicallymeaningful prior knowledge via radiative transfer model emulation. We will treat the important issue of computational efficiency as well. All these developments are illustrated in the field of geosciences and remote sensing at a local and global scales through a set of illustrative examples. In particular, we treat important problems for land, ocean and atmosphere monitoring: from accurate estimation of oceanic chlorophyll content and pigments, to vegetation properties retrieval from multi-and hyperspectral sensors, as well as the estimation of atmospheric parameters (such as temperature, moisture and ozone) from infrared sounders. We conclude the survey with a discussion on the upcoming challenges and research directions.

PloS one, 2016

Recent studies show widespread encroachment of forest into savannas with important consequences f... more Recent studies show widespread encroachment of forest into savannas with important consequences for the global carbon cycle and land-atmosphere interactions. However, little research has focused on in situ measurements of the successional sequence of savanna to forest in Africa. Using long-term inventory plots we quantify changes in vegetation structure, above-ground biomass (AGB) and biodiversity of trees ≥10 cm diameter over 20 years for five vegetation types: savanna; colonising forest (F1), monodominant Okoume forest (F2); young Marantaceae forest (F3); and mixed Marantaceae forest (F4) in Lopé National Park, central Gabon, plus novel 3D terrestrial laser scanning (TLS) measurements to assess forest structure differences. Over 20 years no plot changed to a new stage in the putative succession, but F1 forests strongly moved towards the structure, AGB and diversity of F2 forests. Overall, savanna plots showed no detectable change in structure, AGB or diversity using this method, w...

2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 2015

ABSTRACT

The Earth Observation Land Data Assimilation System (EO-LDAS) is a system that allows interpretin... more The Earth Observation Land Data Assimilation System (EO-LDAS) is a system that allows interpreting spectral observations of the land surface to provide an optimal estimate of the Earth surface state. It allows a consistent combination of observations from different sensors despite the difference in spatial and spectral resolution and acquisition frequencies. The system is based on variational data assimilation (DA) scheme, and uses physically-based radiative transfer models (RTM) to map from state to observation. In addition the system takes into account observational uncertainty, prior information and a model of spatial/temporal evolution of the state. Such approach is very useful for the future satellite constellations as well as for reanalysis of historical data. In this study synergy of MISR and Landsat information in EO-LDAS was validated. Data of the ESA SPARC 2004 field campaign was used. The validation was made by reconstruction of CHRIS/PROBA spectral bands. In turn the rec...

Fire is arguably the most important and widespread agent of ecosystem disturbance worldwide. It a... more Fire is arguably the most important and widespread agent of ecosystem disturbance worldwide. It affects the Carbon cycle, is a control on ecosystem structure, and can potentially impact humans both directly and indirectly. There is a long history of using Earth Observation (EO) data in monitoring wildfires that has led to the development of operational products measuring fire occurrence. These tend to use thermal and/or optical observations to denote an area as being affected by fire if, for instance, the thermal signature is high or the reflectance in near infrared (NIR) or middle infrared (MIR) follows the patterns expected of fire impacts. In recent years, more refined information from time series of thermal observations has allowed the calculation of Fire Radiative Energy that can be related to Carbon release due to fire. Various researchers have attempted to characterise fire ‘severity’ from optical data — usually focusing on a change in a normalised ‘burn ratio’ (NBR) from sa...

Fire is the most important ecological and forest disturbance agent worldwide, is a major way by w... more Fire is the most important ecological and forest disturbance agent worldwide, is a major way by which carbon is transferred from the land to the atmosphere, and is globally a significant source of greenhouse gases and aerosols. Wildfires across all major biome types globally consume about 5% of net annual terrestrial primary production per annum, and release about 2-4 Pg C per annum, of which approximately 0.6 Pg C comes from tropical deforestation and below-ground peat fires. The global figure is equivalent to about 20-30% of global emissions from fossil fuels. Tropical savannas comprise the largest areas burned and greatest emissions sources from vegetation wildfires. Fires in Mediterranean forests and shrublands, tropical forests and boreal forests are also significant sources of emissions because they are generally characterised by much higher fuel loads per unit area compared with grasslands. Improved satellite data and sophisticated biogeochemical modeling enables emis-sions a...

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In this paper, we argue that the exploitation of EO land surface data for modelling and monitorin... more In this paper, we argue that the exploitation of EO land surface data for modelling and monitoring would be greatly facilitated by the routine generation of interoperable low-level surface bidirectional reflectance factor (BRF) products. We consider evidence from a range of ESA, NASA and other products and studies as well as underlying research to outline the features such a processing system might have, and to define initial research priorities.

Surveys in Geophysics

Imaging spectroscopy (IS), also commonly known as hyperspectral remote sensing, is a powerful 13 ... more Imaging spectroscopy (IS), also commonly known as hyperspectral remote sensing, is a powerful 13 remote sensing technique for the monitoring of the Earth's surface and atmosphere. Pixels in optical hyper-14 spectral images consist of continuous reflectance spectra formed by hundreds of narrow spectral channels, 15 allowing an accurate representation of the surface composition through spectroscopic techniques. However, 16 technical constraints in the definition of imaging spectrometers make spectral coverage and resolution to 17 be usually traded by spatial resolution and swath width, as opposed to optical multispectral (MS) systems 18 typically designed to maximize spatial and/or temporal resolution. This complementarity suggests that a 19 synergistic exploitation of spaceborne IS and MS data would be an optimal way to fulfill those remote 20 sensing applications requiring not only high spatial and temporal resolution data, but also rich spectral in-21 formation. On the other hand, IS has been shown to yield a strong synergistic potential with non-optical 22 remote sensing methods, such as thermal infrared (TIR) and light detection and ranging (LiDAR). In this 23 contribution we review theoretical and methodological aspects of potential synergies between optical IS 24 and other remote sensing techniques. The focus is put on the evaluation of synergies between spaceborne 25 optical IS and MS systems because of the expected availability of the two types of data in the next years.

Mitigating the impact of atmospheric effects on optical data is a critical for monitoringland pro... more Mitigating the impact of atmospheric effects on optical data is a critical for monitoringland processes. Consistent approaches to different sensors, which also quantify uncertainty, are required to combine surface reflectance observations from heterogeneous sensors. This paper provides a sensor agnostic approach to atmospheric correction, called SIAC. It exploits operational global datasets on (i) coarse resolution spectral surface bi-directional reflectance distribution function (BRDF) and (ii) coarse resolution atmospheric composition. The method infers aerosol optical thickness (AOT) and total columnar water vapour (TCWV) from top of atmosphere (TOA) reflectance observations, using a Bayesian framework that exploits the MODIS MCD43 BRDF descriptor product and the Copernicus Atmosphere Monitoring Service (CAMS) operational forecasts of AOT and TCWV to provide an \emph{a priori} estimate. Spatial smoothness constraints are assumed for AOT and TCWV, and efficient statistical approxi...

This MS describes a sensitivity analysis of the SPITFIRE fire model coupled to the Lund-Potsdam-J... more This MS describes a sensitivity analysis of the SPITFIRE fire model coupled to the Lund-Potsdam-Jena (LPJ) dynamic global vegetation model (DGVM). The study aims to investigate the parameters that control how the fire model calculates burnt area across different ecosystems. In different fire systems, different parameters are found to have higher sensitivity to burnt area, but in general, parameters controlling rate of spread and ignitions.

Scientific reports, Jan 31, 2018

Accurate terrestrial biosphere model (TBM) simulations of gross carbon uptake (gross primary prod... more Accurate terrestrial biosphere model (TBM) simulations of gross carbon uptake (gross primary productivity - GPP) are essential for reliable future terrestrial carbon sink projections. However, uncertainties in TBM GPP estimates remain. Newly-available satellite-derived sun-induced chlorophyll fluorescence (SIF) data offer a promising direction for addressing this issue by constraining regional-to-global scale modelled GPP. Here, we use monthly 0.5° GOME-2 SIF data from 2007 to 2011 to optimise GPP parameters of the ORCHIDEE TBM. The optimisation reduces GPP magnitude across all vegetation types except C4 plants. Global mean annual GPP therefore decreases from 194 ± 57 PgCyr to 166 ± 10 PgCyr, bringing the model more in line with an up-scaled flux tower estimate of 133 PgCyr. Strongest reductions in GPP are seen in boreal forests: the result is a shift in global GPP distribution, with a ~50% increase in the tropical to boreal productivity ratio. The optimisation resulted in a greater...

Remote Sensing

Biomass burning is a global phenomenon and systematic burned area mapping is of increasing import... more Biomass burning is a global phenomenon and systematic burned area mapping is of increasing importance for science and applications. With high spatial resolution and novelty in band design, the recently launched Sentinel-2A satellite provides a new opportunity for moderate spatial resolution burned area mapping. This study examines the performance of the Sentinel-2A Multi Spectral Instrument (MSI) bands and derived spectral indices to differentiate between unburned and burned areas. For this purpose, five pairs of pre-fire and post-fire top of atmosphere (TOA reflectance) and atmospherically corrected (surface reflectance) images were studied. The pixel values of locations that were unburned in the first image and burned in the second image, as well as the values of locations that were unburned in both images which served as a control, were compared and the discrimination of individual bands and spectral indices were evaluated using parametric (transformed divergence) and non-parametric (decision tree) approaches. Based on the results, the most suitable MSI bands to detect burned areas are the 20 m near-infrared, short wave infrared and red-edge bands, while the performance of the spectral indices varied with location. The atmospheric correction only significantly influenced the separability of the visible wavelength bands. The results provide insights that are useful for developing Sentinel-2 burned area mapping algorithms.

IEEE Geoscience and Remote Sensing Magazine, 2016

Gaussian Process (GP) has experienced tremendous success in bio-geophysical parameter retrieval i... more Gaussian Process (GP) has experienced tremendous success in bio-geophysical parameter retrieval in the last years. It goes without saying that GPs constitute a solid Bayesian framework to formulate many function approximation problems consistently. This paper reviews the main theoretical GP developments in the field. We review new algorithms that respect the signal and noise characteristics, that extract knowledge via automatic relevance kernels to yield feature rankings automatically, that allow applicability of associated uncertainty intervals to transport GP models in space and time, that can be used to uncover causal relations between variables, and that can encode physicallymeaningful prior knowledge via radiative transfer model emulation. We will treat the important issue of computational efficiency as well. All these developments are illustrated in the field of geosciences and remote sensing at a local and global scales through a set of illustrative examples. In particular, we treat important problems for land, ocean and atmosphere monitoring: from accurate estimation of oceanic chlorophyll content and pigments, to vegetation properties retrieval from multi-and hyperspectral sensors, as well as the estimation of atmospheric parameters (such as temperature, moisture and ozone) from infrared sounders. We conclude the survey with a discussion on the upcoming challenges and research directions.

PloS one, 2016

Recent studies show widespread encroachment of forest into savannas with important consequences f... more Recent studies show widespread encroachment of forest into savannas with important consequences for the global carbon cycle and land-atmosphere interactions. However, little research has focused on in situ measurements of the successional sequence of savanna to forest in Africa. Using long-term inventory plots we quantify changes in vegetation structure, above-ground biomass (AGB) and biodiversity of trees ≥10 cm diameter over 20 years for five vegetation types: savanna; colonising forest (F1), monodominant Okoume forest (F2); young Marantaceae forest (F3); and mixed Marantaceae forest (F4) in Lopé National Park, central Gabon, plus novel 3D terrestrial laser scanning (TLS) measurements to assess forest structure differences. Over 20 years no plot changed to a new stage in the putative succession, but F1 forests strongly moved towards the structure, AGB and diversity of F2 forests. Overall, savanna plots showed no detectable change in structure, AGB or diversity using this method, w...

2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 2015

ABSTRACT

The Earth Observation Land Data Assimilation System (EO-LDAS) is a system that allows interpretin... more The Earth Observation Land Data Assimilation System (EO-LDAS) is a system that allows interpreting spectral observations of the land surface to provide an optimal estimate of the Earth surface state. It allows a consistent combination of observations from different sensors despite the difference in spatial and spectral resolution and acquisition frequencies. The system is based on variational data assimilation (DA) scheme, and uses physically-based radiative transfer models (RTM) to map from state to observation. In addition the system takes into account observational uncertainty, prior information and a model of spatial/temporal evolution of the state. Such approach is very useful for the future satellite constellations as well as for reanalysis of historical data. In this study synergy of MISR and Landsat information in EO-LDAS was validated. Data of the ESA SPARC 2004 field campaign was used. The validation was made by reconstruction of CHRIS/PROBA spectral bands. In turn the rec...

Fire is arguably the most important and widespread agent of ecosystem disturbance worldwide. It a... more Fire is arguably the most important and widespread agent of ecosystem disturbance worldwide. It affects the Carbon cycle, is a control on ecosystem structure, and can potentially impact humans both directly and indirectly. There is a long history of using Earth Observation (EO) data in monitoring wildfires that has led to the development of operational products measuring fire occurrence. These tend to use thermal and/or optical observations to denote an area as being affected by fire if, for instance, the thermal signature is high or the reflectance in near infrared (NIR) or middle infrared (MIR) follows the patterns expected of fire impacts. In recent years, more refined information from time series of thermal observations has allowed the calculation of Fire Radiative Energy that can be related to Carbon release due to fire. Various researchers have attempted to characterise fire ‘severity’ from optical data — usually focusing on a change in a normalised ‘burn ratio’ (NBR) from sa...

Fire is the most important ecological and forest disturbance agent worldwide, is a major way by w... more Fire is the most important ecological and forest disturbance agent worldwide, is a major way by which carbon is transferred from the land to the atmosphere, and is globally a significant source of greenhouse gases and aerosols. Wildfires across all major biome types globally consume about 5% of net annual terrestrial primary production per annum, and release about 2-4 Pg C per annum, of which approximately 0.6 Pg C comes from tropical deforestation and below-ground peat fires. The global figure is equivalent to about 20-30% of global emissions from fossil fuels. Tropical savannas comprise the largest areas burned and greatest emissions sources from vegetation wildfires. Fires in Mediterranean forests and shrublands, tropical forests and boreal forests are also significant sources of emissions because they are generally characterised by much higher fuel loads per unit area compared with grasslands. Improved satellite data and sophisticated biogeochemical modeling enables emis-sions a...

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In this paper, we argue that the exploitation of EO land surface data for modelling and monitorin... more In this paper, we argue that the exploitation of EO land surface data for modelling and monitoring would be greatly facilitated by the routine generation of interoperable low-level surface bidirectional reflectance factor (BRF) products. We consider evidence from a range of ESA, NASA and other products and studies as well as underlying research to outline the features such a processing system might have, and to define initial research priorities.