Atmospheric Correction Inter-comparison eXercise, ACIX-II Land: An assessment of atmospheric correction processors for Landsat 8 and Sentinel-2 over land

The correction of the atmospheric effects on optical satellite images is essential for quantitative and multitemporal remote sensing applications. In order to study the performance of the state-of-the-art methods in an integrated way, a voluntary and open-access benchmark Atmospheric Correction Inter-comparison eXercise (ACIX) was initiated in 2016 in the frame of Committee on Earth Observation Satellites (CEOS) Working Group on Calibration & Validation (WGCV). The first exercise was extended in a second edition wherein twelve atmospheric correction (AC) processors, a substantially larger testing dataset and additional validation metrics were involved. The sites for the inter-comparison analysis were defined by investigating the full catalogue of the Aerosol Robotic Network (AERONET) sites for coincident measurements with satellites' overpass. Although there were more than one hundred sites for Copernicus Sentinel-2 and Landsat 8 acquisitions, the analysis presented in this paper concerns only the common matchups amongst all processors, reducing the number to 79 and 62 sites respectively. Aerosol Optical Depth (AOD) and Water Vapour (WV) retrievals were consequently validated based on the available AERONET observations. The processors mostly succeeded in retrieving AOD for relatively light to medium aerosol loading (AOD 90% of the results falling within the suggested empirical specifications and with the Root Mean Square Error (RMSE) being mostly <0.25 g/cm2. Regarding Surface Reflectance (SR) validation two main approaches were followed. For the first one, a simulated SR reference dataset was computed over all of the test sites by using the 6SV (Second Simulation of the Satellite Signal in the Solar Spectrum vector code) full radiative transfer modelling (RTM) and AERONET measurements for the required aerosol variables and water vapour content. The performance assessment demonstrated that the retrievals were not biased for most of the bands. The uncertainties ranged from approximately 0.003 to 0.01 (excluding B01) for the best performing processors in both sensors' analyses. For the second one, measurements from the radiometric calibration network RadCalNet over La Crau (France) and Gobabeb (Namibia) were involved in the validation. The performance of the processors was in general consistent across all bands for both sensors and with low standard deviations (<0.04) between on-site and estimated surface reflectance. Overall, our study provides a good insight of AC algorithms' performance to developers and users, pointing out similarities and differences for AOD, WV and SR retrievals. Such validation though still lacks of ground-based measurements of known uncertainty to better assess and characterize the uncertainties in SR retrievals

Bayesian atmospheric correction over land: Sentinel-2/MSI and Landsat 8/OLI

Mitigating the impact of atmospheric effects on optical remote sensing data is critical for monitoring intrinsic land processes and developing Analysis Ready Data (ARD). This work develops an approach to this for the NERC NCEO medium resolution ARD Landsat 8 (L8) and Sentinel 2 (S2) products, called Sensor Invariant Atmospheric Correction (SIAC). The contribution of the work is to phrase and solve that problem within a probabilistic (Bayesian) framework for medium resolution multispectral sensors S2/MSI and L8/OLI and to provide per-pixel uncertainty estimates traceable from assumed top-of-atmosphere (TOA) measurement uncertainty, making progress towards an important aspect of CEOS ARD target requirements. A set of observational and a priori constraints are developed in SIAC to constrain an estimate of coarse resolution (500 m) aerosol optical thickness (AOT) and total column water vapour (TCWV), along with associated uncertainty. This is then used to estimate the medium resolution (10–60 m) surface reflectance and uncertainty, given an assumed uncertainty of 5 % in TOA reflectance. The coarse resolution a priori constraints used are the MODIS MCD43 BRDF/Albedo product, giving a constraint on 500 m surface reflectance, and the Copernicus Atmosphere Monitoring Service (CAMS) operational forecasts of AOT and TCWV, providing estimates of atmospheric state at core 40 km spatial resolution, with an associated 500 m resolution spatial correlation model. The mapping in spatial scale between medium resolution observations and the coarser resolution constraints is achieved using a calibrated effective point spread function for MCD43. Efficient approximations (emulators) to the outputs of the 6S atmospheric radiative transfer code are used to estimate the state parameters in the atmospheric correction stage. SIAC is demonstrated for a set of global S2 and L8 images covering AERONET and RadCalNet sites. AOT retrievals show a very high correlation to AERONET estimates (correlation coefficient around 0.86, RMSE of 0.07 for both sensors), although with a small bias in AOT. TCWV is accurately retrieved from both sensors (correlation coefficient over 0.96, RMSE &lt;0.32 g cm−2). Comparisons with in situ surface reflectance measurements from the RadCalNet network show that SIAC provides accurate estimates of surface reflectance across the entire spectrum, with RMSE mismatches with the reference data between 0.01 and 0.02 in units of reflectance for both S2 and L8. For near-simultaneous S2 and L8 acquisitions, there is a very tight relationship (correlation coefficient over 0.95 for all common bands) between surface reflectance from both sensors, with negligible biases. Uncertainty estimates are assessed through discrepancy analysis and are found to provide viable estimates for AOT and TCWV. For surface reflectance, they give conservative estimates of uncertainty, suggesting that a lower estimate of TOA reflectance uncertainty might be appropriate

Agreement Index for Burned Area Mapping: Integration of Multiple Spectral Indices Using Sentinel-2 Satellite Images

Identifying fire-affected areas is of key importance to support post-fire management strategies and account for the environmental impact of fires. The availability of high spatial and temporal resolution optical satellite data enables the development of procedures for detailed and prompt post-fire mapping. This study proposes a novel approach for integrating multiple spectral indices to generate more accurate burned area maps by exploiting Sentinel-2 images. This approach aims to develop a procedure to combine multiple spectral indices using an adaptive thresholding method and proposes an agreement index to map the burned areas by optimizing omission and commission errors. The approach has been tested for the burned area classification of four study areas in Italy. The proposed agreement index combines multiple spectral indices to select the actual burned pixels, to balance the omission and commission errors, and to optimize the overall accuracy. The results showed the spectral indices singularly performed differently in the four study areas and that high levels of commission errors were achieved, especially for wildfires which occurred during the fall season (up to 0.93) Furthermore, the agreement index showed a good level of accuracy (minimum 0.65, maximum 0.96) for all the study areas, improving the performance compared to assessing the indices individually. This suggests the possibility of testing the methodology on a large set of wildfire cases in different environmental conditions to support the decision-making process. Exploiting the high resolution of optical satellite data, this work contributes to improving the production of detailed burned area maps, which could be integrated into operational services based on the use of Earth Observation products for burned area mapping to support the decision-making process

Earth Observation for Phenological Metrics (EO4PM): Temporal Discriminant to Characterize Forest Ecosystems

Abstract: The study of vegetation phenology has great relevance in many fields since the importance of knowing timing and shifts in periodic plant life cycle events to face the consequences of global changes in issues such as crop production, forest management, ecosystem disturbances, and human health. The availability of high spatial resolution and dense revisit time satellite observations, such as Sentinel-2 satellites, allows high resolution phenological metrics to be estimated, able to provide key information from time series and to discriminate vegetation typologies. This paper presents an automated and transferable procedure that combines validated methodologies based on local curve fitting and local derivatives to exploit full satellite Earth observation time series to produce information about plant phenology. Multivariate statistical analysis is performed for the purpose of demonstrating the capacity of the generated smoothed vegetation curve, temporal statistics, and phenological metrics to serve as temporal discriminants to detect forest ecosystems processes responses to environmental gradients. The results show smoothed vegetation curve and temporal statistics able to highlight seasonal gradient and leaf type characteristics to discriminate forest types, with additional information about forest and leaf productivity provided by temporal statistics analysis. Furthermore, temporal, altitudinal, and latitudinal gradients are obtained from phenological metrics analysis, which also allows to associate temporal gradient with specific phenophases that support forest types distinction. This study highlights the importance of integrated data and methodologies to support the processes of vegetation recognition and monitoring activities

Understanding the measurements and variability of aerosol optical properties in NE Spain

[eng] Atmospheric aerosol particles are key for regulating Earth’s atmosphere processes, and are estimated to present an overall cooling effect on the Earth’s climate. Given the current climate change crisis, and the need for precise mitigation measures on anthropogenic emissions, it is paramount to reduce the uncertainties related to the actual degree of this cooling effect and the impact that the reduction on the aerosol particles emissions will have on the Earth’s radiative forcing and global temperature. The main sources of uncertainty of the contribution of aerosol particles to the radiative balance are associated to their highly variable and heterogeneous spatial and temporal distribution, to the large array of aerosol species with varying physico-chemical properties, and to the measurement associated errors. In particular, the most important aerosol species with regards to their absorption properties and effect on climate as warming agents are black carbon (BC), the organic aerosols (OA) absorbing fraction, referred to as brown carbon (BrC), and, potentially, mineral dust. The Mediterranean basin is a region in Southern Europe heavily affected by large anthropogenic emission sources, as well as from natural sources such as wildfires, Saharan dust mineral outbreaks and other biogenic processes. The multiple sources coupled with the meteorological conditions and the abrupt topography favour the accumulation and recirculation of air masses, especially during summer, which onsets the ageing of particles at several layers above ground, giving place to a complex mixture of aerosol particles. In this context, this PhD thesis main focus is on the characterization of the optical properties of the BC, BrC and mineral dust particles, and its variations under different meteorological scenarios over an area on the Western Mediterranean Basin (NE of Spain). More specifically, this thesis addresses improvements in i) the determination of the absorption coefficients from a highly deployed instrument, the dual-spot multi- wavelength AE33 aethalometer, via a novel approach; ii) the characterization of the horizontal and vertical distribution of the aerosol particles physico-chemical properties at a regional recirculation event and a Saharan dust event; and iii) the analysis of the effects on the absorption enhancement of the BC particles by its mixing with BrC and other non- absorbing organic and inorganic aerosols. Finally, this thesis describes the optical properties of mineral dust at an emission source in a Saharan arid region and introduces the variations related to the types of events and the strength of the emission processes. With this aim, this thesis combines datasets from monitoring stations at three different backgrounds and an intensive measurement campaign with instrumented flights in the NE of Spain, in addition to an intensive campaign in a mineral dust emission area in the Saharan outskirts. The monitoring stations in the NE of Spain are operated by the EGAR group (IDAEA-CSIC) at an urban background in Barcelona (BCN), a regional background in Montseny natural park (MSY), and a remote mountain-top station in Montsec d’Ares mountain range (MSA).[spa] Los aerosoles atmosféricos resultan claves a la hora de regular el clima de la Tierra, con un efecto sobre el clima estimado de enfriamiento a nivel global, si bien con una alta incertidumbre en su valor exacto. Es por ello necesario reducir dichas incertidumbres, principalmente asociadas a la alta variabilidad y heterogeneidad de su distribución espacial y temporal, las múltiples especies de aerosoles con diferentes propiedades físico-químicas, y los errores de medida. Las especies de aerosoles más relevantes debido a su efecto en el calentamiento del clima son el carbono negro (BC), la fracción absorbente de los aerosoles orgánicos (OA), i.e. carbono marrón (BrC), y, potencialmente, el polvo mineral. Para el estudio de las propiedades ópticas de los aerosoles, esta tesis se ha centrado en un área con una gran variabilidad de fuentes de emisión de aerosoles de origen natural (biogénicos, incendios, polvo mineral, sal marina) y antropogénico (tráfico, industria, viviendas, portuario, etc.) en el Mediterráneo, en el NE de España. Esta área presenta una orografía compleja que en combinación con patrones atmosféricos que promueven los sistemas de brisas favorece la recirculación de los aerosoles, generando múltiples capas de aerosoles. Además, dichos escenarios pueden verse también influidos por la presencia de advección de polvo mineral desde el N de África, contribuyendo significativamente a la concentración de material particulado y afectando las propiedades ópticas. Con el fin de mejorar la caracterización de las propiedades ópticas del BC, el BrC y el polvo mineral en el NE de España, esta tesis ha llevado a cabo una serie de estudios centrada en: i) la mejora de la medida de la absorción analizando a través de un método novedoso el comportamiento de un parámetro clave para su obtención mediante el aethalometro AE33, ii) la descripción de la variación vertical de las propiedades físico- químicas de los aerosoles atmosféricos durante eventos de recirculación e intrusiones de polvo mineral el verano de 2015 a través de la combinación de vuelos instrumentados y medidas en las estaciones de medida, iii) el efecto de la mezcla de OA y aerosoles inorgánicos con partículas de BC en su absorción, y iv) las propiedades ópticas del polvo mineral en una fuente de emisión en el Sahara según la intensidad de emisión

Simulating urban soil carbon decomposition using local weather input from a surface model

Non peer reviewe

Directory of research projects: Planetary geology and geophysics program

Information about currently funded scientific research within the Planetary Geology and Geophysics Program is provided, including the proposal summary sheet from each proposal funded under the program during fiscal year 1990. Information about the research project, including title, principal investigator, institution, summary of research objectives, past accomplishments, and proposed new investigations is also provided

Land Degradation Assessment with Earth Observation

This Special Issue (SI) on “Land Degradation Assessment with Earth Observation” comprises 17 original research papers with a focus on land degradation in arid, semiarid and dry-subhumid areas (i.e., desertification) in addition to temperate rangelands, grasslands, woodlands and the humid tropics. The studies cover different spatial, spectral and temporal scales and employ a wealth of different optical and radar sensors. Some studies incorporate time-series analysis techniques that assess the general trend of vegetation or the timing and duration of the reduction in biological productivity caused by land degradation. As anticipated from the latest trend in Earth Observation (EO) literature, some studies utilize the cloud-computing infrastructure of Google Earth Engine to cope with the unprecedented volume of data involved in current methodological approaches. This SI clearly demonstrates the ever-increasing relevance of EO technologies when it comes to assessing and monitoring land degradation. With the recently published IPCC Reports informing us of the severe impacts and risks to terrestrial and freshwater ecosystems and the ecosystem services they provide, the EO scientific community has a clear obligation to increase its efforts to address any remaining gaps—some of which have been identified in this SI—and produce highly accurate and relevant land-degradation assessment and monitoring tools

Using Copernicus Atmosphere Monitoring Service Products to Constrain the Aerosol Type in the Atmospheric Correction Processor MAJA

International audienceThe quantitative use of space-based optical imagery requires atmospheric correction to separate the contributions from the surface and the atmosphere. The MACCS (Multi-sensor Atmospheric Correction and Cloud Screening)-ATCOR (Atmospheric and Topographic Correction) Joint Algorithm, called MAJA, is a numerical tool designed to perform cloud detection and atmospheric correction. For the correction of aerosols effects, MAJA makes an estimate of the aerosol optical thickness (AOT) based on multi-temporal and multi-spectral criteria, but there is insufficient information to infer the aerosol type. The current operational version of MAJA uses an aerosol type which is constant with time, and this assumption impacts the quality of the atmospheric correction. In this study, we assess the potential of using an aerosol type derived from the Copernicus Atmosphere Monitoring Service (CAMS) operational analysis. The performances, with and without the CAMS information, are evaluated. Firstly, in terms of the aerosol optical thickness retrievals, a comparison against sunphotometer measurements over several sites indicates an improvement over arid sites, with a root-mean-square error (RMSE) reduced by 28% (from 0.095 to 0.068), although there is a slight degradation over vegetated sites (RMSE increased by 13%, from 0.054 to 0.061). Secondly, a direct validation of the retrieved surface reflectances at the La Crau station (France) indicates a reduction of the relative bias by 2.5% on average over the spectral bands. Thirdly, based on the assumption that surface reflectances vary slowly with time, a noise criterion was set up, exhibiting no improvement over the spectral bands and the validation sites when using CAMS data, partly explained by a slight increase in the surface reflectances themselves. Finally, the new method presented in this study provides a better way of using the MAJA processor in an operational environment because the aerosol type used for the correction is automatically inferred from CAMS data, and is no longer a parameter to be defined in advance