•Per-pixel and per-date temporal mosaicking approaches were tested from Sentinel-2.•Mosaicking incorporated spectral indices and/or Sentinel-1 derived soil moisture.•Best trade-off was achieved from ...per-date using S1-derived moisture content.•SOC prediction accuracy was not improved compared to single date S2 image.
The spatial assessment of soil organic carbon (SOC) is a major environmental challenge, notably for evaluating soil carbon stocks. Recent works have shown the capability of Sentinel-2 to predict SOC content over temperate agroecosystems characterized with annual crops. However, because spectral models are only applicable on bare soils, the mapping of SOC is often obtained on limited areas. A possible improvement for increasing the number of pixels on which SOC can be retrieved by inverting bare soil reflectance spectra, consists of using optical images acquired at several dates. This study compares different approaches of Sentinel–2 images temporal mosaicking to produce a composite multi-date bare soil image for predicting SOC content over agricultural topsoils. A first approach for temporal mosaicking was based on a per-pixel selection and was driven by soil surface characteristics: bare soil or dry bare soil with/without removing dry vegetation. A second approach for creating composite images was based on a per-date selection and driven either by the models performance from single-date, or by average soil surface indicators of bare soil or dry bare soil. To characterize soil surface, Sentinel-1 (S1)-derived soil moisture and/or spectral indices such as normalized difference vegetation index (NDVI), Normalized Burn Ratio 2 (NBR2), bare soil index (BSI) and a soil surface moisture index (S2WI) were used either separately or in combination. This study highlighted the following results: i) none of the temporal mosaic images improved model performance for SOC prediction compared to the best single-date image; ii) of the per-pixel approaches, temporal mosaics driven by the S1-derived moisture content, and to a lesser extent, by NBR2 index, outperformed the mosaic driven by the BSI index but they did not increase the bare soil area predicted; iii) of the per-date approaches, the best trade-off between predicted area and model performance was achieved from the temporal mosaic driven by the S1-derived moisture content (R2 ~ 0.5, RPD ~ 1.4, RMSE ~ 3.7 g.kg-1) which enabled to more than double (*2.44) the predicted area. This study suggests that a number of bare soil mosaics based on several indicators (moisture, bare soil, roughness…), preferably in combination, might maintain acceptable accuracies for SOC prediction whilst extending over larger areas than single-date images.
The spatial assessment of soil organic carbon (SOC) is a major environmental challenge, notably for evaluating soil carbon stocks. Recent works have shown the capability of Sentinel-2 optical data to ...predict SOC content over temperate agroecosystems characterized by annual crops, using a single acquisition date. Considering a Sentinel-2 time series, this work intends to analyze the impact of acquisition date, and related weather and soil surface conditions on the prediction performance of topsoil SOC content (plough layer). A Sentinel-2 time-series was gathered, comprised of the dates corresponding to both the maximum of bare soil coverage and minimum of cloud coverage. Cross-validated partial least squares regression (PLSR) models were constructed between soil reflectance image spectra, and SOC content analyzed from 329 top soil samples collected over the study area. Cross-validation R2 ranged from 0.005 to 0.58, root mean square error from 5.86 to 3.02 g·kg−1 and residual prediction deviation values from 1.0 to 1.5 (without unit), according to date. The main factors influencing these differences were soil roughness, in conjunction with soil moisture, and the cloud and cloud shadow cover of the entire tile. The best performing dates were spring dates characterized by both lowest soil surface roughness and moisture content. Normalized difference vegetation index (NDVI) values below 0.35 did not influence prediction performance. This consolidates the previous results obtained during single date acquisitions and offers wider perspectives for the further use of Sentinel-2 into multidate mosaics for digital soil mapping.
Abstract
The year 2022 saw record breaking temperatures in Europe during both summer and fall. Similar to the recent 2018 drought, close to 30% (3.0 million km
2
) of the European continent was under ...severe summer drought. In 2022, the drought was located in central and southeastern Europe, contrasting the Northern-centered 2018 drought. We show, using multiple sets of observations, a reduction of net biospheric carbon uptake in summer (56-62 TgC) over the drought area. Specific sites in France even showed a widespread summertime carbon release by forests, additional to wildfires. Partial compensation (32%) for the decreased carbon uptake due to drought was offered by a warm autumn with prolonged biospheric carbon uptake. The severity of this second drought event in 5 years suggests drought-induced reduced carbon uptake to no longer be exceptional, and important to factor into Europe’s developing plans for net-zero greenhouse gas emissions that rely on carbon uptake by forests.
Diurnal fluxes of HONO above a crop rotation Laufs, Sebastian; Cazaunau, Mathieu; Stella, Patrick ...
Atmospheric chemistry and physics,
06/2017, Letnik:
17, Številka:
11
Journal Article
Recenzirano
Odprti dostop
Nitrous acid (HONO) fluxes were measured above an agricultural field site near Paris during different seasons. Above bare soil, different crops were measured using the aerodynamic gradient (AG) ...method. Two LOPAPs (LOng Path Absorption Photometer) were used to determine the HONO gradients between two heights. During daytime mainly positive HONO fluxes were observed, which showed strong correlation with the product of the NO2 concentration and the long wavelength UV light intensity, expressed by the photolysis frequency J(NO2). These results are consistent with HONO formation by photosensitized heterogeneous conversion of NO2 on soil surfaces as observed in recent laboratory studies. An additional influence of the soil temperature on the HONO flux can be explained by the temperature-dependent HONO adsorption on the soil surface. A parameterization of the HONO flux at this location with NO2 concentration, J(NO2), soil temperature and humidity fits reasonably well all flux observations at this location.
•Forests and wetlands buffer thermal fluctuation better than non-forests•Forest degradation reduces thermal buffer ability, especially at high latitudes•Canopy height is the primary impact factor ...influencing TBA of forests•Energy partitioning, water and CO2 exchange are the main drivers of non-forests TBA•Protecting mature forests mitigates thermal fluctuation under extreme events
With the increase in intensity and frequency of extreme climate events, interactions between vegetation and local climate are gaining more and more attention. Both the mean temperature and the temperature fluctuations of vegetation will exert thermal influence on local climate and the life of plants and animals. Many studies have focused on the pattern in the mean canopy surface temperature of vegetation, whereas there is still no systematic study of thermal buffer ability (TBA) of different vegetation types across global biomes. We developed a new method to measure TBA based on the rate of temperature increase, requiring only one radiometer. With this method, we compared TBA of ten vegetation types with contrasting structures, e.g. from grasslands to forests, using data from 133 sites globally. TBA ranged from 5.2 to 21.2 across these sites and biomes. Forests and wetlands buffer thermal fluctuation better than non-forests (grasslands, savannas, and croplands), and the TBA boundary between forests and non-forests was typically around 10. Notably, seriously disturbed and young planted forests displayed a greatly reduced TBA as low as that of non-forests at high latitudes. Canopy height was a primary controller of TBA of forests, while the TBA of grasslands and savannas were mainly determined by energy partition, water availability, and carbon sequestration rates. Our research suggests that both mean values and fluctuations in canopy surface temperature should be considered to predict the risk for plants under extreme events. Protecting mature forests, both at high and low latitudes, is critical to mitigate thermal fluctuation under extreme events.
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In Europe, the heterogeneous features of crop systems with majority of small to medium sized agricultural holdings, and diversity of crop rotations, require high-resolution information to estimate ...cropland Net Ecosystem Exchange (NEE) and its two main components of Gross Ecosystem Exchange (GEE) and the Ecosystem Respiration (RECO). In this context, this paper presents an assimilation of high-resolution Sentinel-2 indices with eddy covariance measurements at selected European cropland flux sites in a new modified version of Vegetation Photosynthesis Respiration Model (VPRM). VRPM is a data-driven model simulating CO2 fluxes previously applied using satellite-derived vegetation indices from the Moderate Resolution Imaging Spectroradiometer (MODIS). This study proposes a modification of the VPRM by including an explicit soil moisture stress function to the GEE and changing the equation of RECO. It also compares the model results driven by S2 indices instead of MODIS. The parameters of the VPRM model are calibrated using eddy-covariance data. All possible parameters optimization scenarios include the use of the initial version vs. the proposed modified VPRM, S2, or MODIS vegetation indices, and finally the choice of calibrating a single set of parameters against observations from all crop types, a set of parameters per crop type, or one set of parameters per site. Then, we focus the analysis on the improvement of the model with distinct parameters for different crop types vs. parameters optimized without distinction of crop types. Our main findings are: (1) the superiority of S2 vegetation indices over MODIS for cropland CO2 fluxes simulations, leading to a root mean squared error (RMSE) for NEE of less than 3.5 μmolm-2s-1 with S2 compared to 5 μmolm-2s-1 with MODIS (2) better performances of the modified VPRM version leading to a significant improvement of RECO, and (3) better performances when the parameters are optimized per crop-type instead of for all crop types lumped together, with lower RMSE and Akaike information criterion (AIC), despite a larger number of parameters. Associated with the availability of crop-type land cover maps, the use of S2 data and crop-type modified VPRM parameterization presented in this study, provide a step forward for upscaling cropland carbon fluxes at European scale.
The role that soil, foliage, and atmospheric dynamics have on surface carbonyl sulfide (OCS) exchange in a Mediterranean forest ecosystem in southern France (the Oak Observatory at the Observatoire ...de Haute Provence, O3HP) was investigated in June of 2012 and 2013 with essentially a top-down approach. Atmospheric data suggest that the site is appropriate for estimating gross primary production (GPP) directly from eddy covariance measurements of OCS fluxes, but it is less adequate for scaling net ecosystem exchange (NEE) to GPP from observations of vertical gradients of OCS relative to CO2 during the daytime. Firstly, OCS and carbon dioxide (CO2) diurnal variations and vertical gradients show no net exchange of OCS at night when the carbon fluxes are dominated by ecosystem respiration. This contrasts with other oak woodland ecosystems of a Mediterranean climate, where nocturnal uptake of OCS by soil and/or vegetation has been observed. Since temperature, water, and organic carbon content of soil at the O3HP should favor the uptake of OCS, the lack of nocturnal net uptake would indicate that its gross consumption in soil is compensated for by emission processes that remain to be characterized. Secondly, the uptake of OCS during the photosynthetic period was characterized in two different ways. We measured ozone (O3) deposition velocities and estimated the partitioning of O3 deposition between stomatal and non-stomatal pathways before the start of a joint survey of OCS and O3 surface concentrations. We observed an increasing trend in the relative importance of the stomatal pathway during the morning hours and synchronous steep drops of mixing ratios of OCS (amplitude in the range of 60–100 ppt) and O3 (amplitude in the range of 15–30 ppb) after sunrise and before the break up of the nocturnal boundary layer. The uptake of OCS by plants was also characterized from vertical profiles. However, the time window for calculation of the ecosystem relative uptake (ERU) of OCS, which is a useful tool for partitioning measured NEE, was limited in June 2012 to a few hours after midday. This was due to the disruption of the vertical distribution of OCS by entrainment of OCS rich tropospheric air in the morning and because the vertical gradient of CO2 reverses when it is still light. Moreover, polluted air masses (up to 700 ppt of OCS) produced dramatic variation in atmospheric OCS ∕ CO2 ratios during the daytime in June 2013, further reducing the time window for ERU calculation.
Surface albedo is a fundamental radiative parameter as it controls the Earth’s energy budget and directly affects the Earth’s climate. Satellite observations have long been used to capture the ...temporal and spatial variations of surface albedo because of their continuous global coverage. However, space-based albedo products are often affected by errors in the atmospheric correction, multi-angular bi-directional reflectance distribution function (BRDF) modelling, as well as spectral conversions. To validate space-based albedo products, an in situ tower albedometer is often used to provide continuous “ground truth” measurements of surface albedo over an extended area. Since space-based albedo and tower-measured albedo are produced at different spatial scales, they can be directly compared only for specific homogeneous land surfaces. However, most land surfaces are inherently heterogeneous with surface properties that vary over a wide range of spatial scales. In this work, tower-measured albedo products, including both directional hemispherical reflectance (DHR) and bi-hemispherical reflectance (BHR), are upscaled to coarse satellite spatial resolutions using a new method. This strategy uses high-resolution satellite derived surface albedos to fill the gaps between the albedometer’s field-of-view (FoV) and coarse satellite scales. The high-resolution surface albedo is generated from a combination of surface reflectance retrieved from high-resolution Earth Observation (HR-EO) data and moderate resolution imaging spectroradiometer (MODIS) BRDF climatology over a larger area. We implemented a recently developed atmospheric correction method, the Sensor Invariant Atmospheric Correction (SIAC), to retrieve surface reflectance from HR-EO (e.g., Sentinel-2 and Landsat-8) top-of-atmosphere (TOA) reflectance measurements. This SIAC processing provides an estimated uncertainty for the retrieved surface spectral reflectance at the HR-EO pixel level and shows excellent agreement with the standard Landsat 8 Surface Reflectance Code (LaSRC) in retrieving Landsat-8 surface reflectance. Atmospheric correction of Sentinel-2 data is vastly improved by SIAC when compared against the use of in situ AErosol RObotic NETwork (AERONET) data. Based on this, we can trace the uncertainty of tower-measured albedo during its propagation through high-resolution EO measurements up to coarse satellite scales. These upscaled albedo products can then be compared with space-based albedo products over heterogeneous land surfaces. In this study, both tower-measured albedo and upscaled albedo products are examined at Ground Based Observation for Validation (GbOV) stations (https://land.copernicus.eu/global/gbov/), and used to compare with satellite observations, including Copernicus Global Land Service (CGLS) based on ProbaV and VEGETATION 2 data, MODIS and multi-angle imaging spectroradiometer (MISR).
Methane (CH4) and carbon dioxide (CO2) surface emissions from Polesgo's landfill (Ouagadougou, Burkina Faso) were measured using the static chamber technique in 2017 and 2018. The Polesgo's landfill ...was composed of four zones: Phase I, II, Phase III, and SP. The surface of Phase I was fully covered and its conditions are better for surface emission measurements. As results concerning the Phase I zone, the geospatial means flux rates of CH4 (657 mg m−2 h−1 in 2017 and 1210 mg m−2 h−1 in 2018, respectively) are measured higher than the tolerable value reported in literature. The emitted CH4 or CO2 have permitted to locate higher surface emissions which are related to the cover state. The calculated gas collection efficiency (27.4% in 2017 and 23.0% in 2018) is low compared to those reported for landfills integrating landfill gas (LFG) extraction system. The carbon footprint calculations (24,966 tCO2-eq 2017 and 40,025 tCO2-eq in 2018, respectively) shown that Polesgo's landfill is a significant source of greenhouse gases (GHG) and its important potential for organic recovery can contribute to reduce the carbon footprint.
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