Peñuelas, J., Sardans, J., Filella, I., Estiarte, M., Llusià, J., Ogaya, R., Carnicer, J., Bartrons, M., Rivas-Ubach, A., Grau, O., Peguero, G., Margalef, O., Pla-Rabés, S., Stefanescu, C., Asensio, D., Preece, C., Liu, L., Verger, A., Rico, L., Barbeta, A., Achotegui-Castells, A., Gargallo-Garriga, A., Sperlich, D., Farré-Armengol, G., Fernández-Martínez, M., Liu, D., Zhang, C., Urbina, I., Camino, M., Vives, M., Nadal-Sala, D., Sabaté, S., Gracia, C., Terradas, J. (2016) Assessment of the impacts of climate change on Mediterranean terrestrial ecosystems based on data from field experiments and long-term monitored field gradients in Catalonia. Environmental and Experimental Botany. : 0-0.LinkDoi: 10.1016/j.envexpbot.2017.05.012
Tian F., Brandt M., Liu Y.Y., Verger A., Tagesson T., Diouf A.A., Rasmussen K., Mbow C., Wang Y., Fensholt R. (2016) Remote sensing of vegetation dynamics in drylands: Evaluating vegetation optical depth (VOD) using AVHRR NDVI and in situ green biomass data over West African Sahel. Remote Sensing of Environment. 177: 265-276.LinkDoi: 10.1016/j.rse.2016.02.056
Monitoring long-term biomass dynamics in drylands is of great importance for many environmental applications including land degradation and global carbon cycle modeling. Biomass has extensively been estimated based on the normalized difference vegetation index (NDVI) as a measure of the vegetation greenness. The vegetation optical depth (VOD) derived from satellite passive microwave observations is mainly sensitive to the water content in total aboveground vegetation layer. VOD therefore provides a complementary data source to NDVI for monitoring biomass dynamics in drylands, yet further evaluations based on ground measurements are needed for an improved understanding of the potential advantages. In this study, we assess the capability of a long-term VOD dataset (1992-2011) to capture the temporal and spatial variability of in situ measured green biomass (herbaceous mass and woody plant foliage mass) in the semi-arid Senegalese Sahel. Results show that the magnitude and peak time of VOD are sensitive to the woody plant foliage whereas NDVI seasonality is primarily governed by the green herbaceous vegetation stratum in the study area. Moreover, VOD is found to be more robust against typical NDVI drawbacks of saturation effect and dependence on plant structure (herbaceous and woody compositions) across the study area when used as a proxy for vegetation productivity. Finally, both VOD and NDVI well reflect the spatial and inter-annual dynamics of the in situ green biomass data; however, the seasonal metrics showing the highest degree of explained variance differ between the two data sources. While the observations in October (period of in situ data collection) perform best for VOD (r2 = 0.88), the small growing season integral (sensitive to recurrent vegetation) have the highest correlations for NDVI (r2 = 0.90). Overall, in spite of the coarse resolution, the study shows that VOD is an efficient proxy for estimating green biomass of the entire vegetation stratum in the semi-arid Sahel and likely also in other dryland areas. © 2016 Elsevier Inc.
Verger A., Filella I., Baret F., Peñuelas J. (2016) Vegetation baseline phenology from kilometric global LAI satellite products. Remote Sensing of Environment. 178: 1-14.LinkDoi: 10.1016/j.rse.2016.02.057
Land surface phenology derived from remotely sensed satellite data can substantially improve our macroecological knowledge and the representation of phenology in earth system models. We characterized the baseline phenology of the vegetation at the global scale from the GEOCLIM climatology of leaf area index (LAI) estimated from 1-km SPOT-VEGETATION time series for 1999-2010. The phenological metrics were calibrated over an ensemble of ground observations of the timing of leaf unfolding and autumnal colouring of leaves. The start and end of season were best identified using respectively 30% and 40% threshold of LAI amplitude values. The accuracy of the derived phenological metrics, evaluated using available ground observations for birch forests over Europe (and lilac shrubs over North America), improved as compared to those derived from MODIS-EVI and produced an overall root mean square error of 7 days (19 days) for the timing of the start of season, 15 for the end of season, and 16 for the length of season. The spatial patterns of the derived LAI phenology agreed well with those from MODIS-EVI and -NDVI, although the timing of the start, end, and length of season differed by about one month at the global scale, with higher uncertainties in areas of limited seasonality of the satellite signal and systematic biases due to the differences in the methodologies and datasets. The baseline LAI phenology was spatially consistent with the global distributions of climatic drivers and biome land cover. © 2016 Elsevier Inc.
Verger, A., Filella, I., Baret, F., Peñuelas, J. (2016) Land surface phenology from SPOT VEGETATION time series [Caracterización de la fenología de la vegetación a escala global mediante series temporales SPOT VEGETATION]. Revista de Teledeteccion. 2016: 1-11.LinkDoi: 10.4995/raet.2016.5718
Verger, A., Kandasamy, S., Baret, F. (2016) Temporal techniques in remote sensing of global vegetation. Remote Sensing and Digital Image Processing. 20: 217-232.LinkDoi: 10.1007/978-3-319-47037-5_11
Vicca S., Balzarolo M., Filella I., Granier A., Herbst M., Knohl A., Longdoz B., Mund M., Nagy Z., Pintér K., Rambal S., Verbesselt J., Verger A., Zeileis A., Zhang C., Peñuelas J. (2016) Remotely-sensed detection of effects of extreme droughts on gross primary production. Scientific Reports. 6: 0-0.LinkDoi: 10.1038/srep28269
Severe droughts strongly impact photosynthesis (GPP), and satellite imagery has yet to demonstrate its ability to detect drought effects. Especially changes in vegetation functioning when vegetation state remains unaltered (no browning or defoliation) pose a challenge to satellite-derived indicators. We evaluated the performance of different satellite indicators to detect strong drought effects on GPP in a beech forest in France (Hesse), where vegetation state remained largely unaffected while GPP decreased substantially. We compared the results with three additional sites: a Mediterranean holm oak forest (Puéchabon), a temperate beech forest (Hainich), and a semi-arid grassland (Bugacpuszta). In Hesse, a three-year reduction in GPP following drought was detected only by the Enhanced Vegetation Index (EVI). The Photochemical Reflectance Index (PRI) also detected this drought effect, but only after normalization for absorbed light. In Puéchabon normalized PRI outperformed the other indicators, while the short-term drought effect in Hainich was not detected by any tested indicator. In contrast, most indicators, but not PRI, captured the drought effects in Bugacpuszta. Hence, PRI improved detection of drought effects on GPP in forests and we propose that PRI normalized for absorbed light is considered in future algorithms to estimate GPP from space.
Brandt M., Mbow C., Diouf A.A., Verger A., Samimi C., Fensholt R. (2015) Ground-and satellite-based evidence of the biophysical mechanisms behind the greening Sahel. Global Change Biology. 21: 1610-1620.LinkDoi: 10.1111/gcb.12807
After a dry period with prolonged droughts in the 1970s and 1980s, recent scientific outcome suggests that the decades of abnormally dry conditions in the Sahel have been reversed by positive anomalies in rainfall. Various remote sensing studies observed a positive trend in vegetation greenness over the last decades which is known as the re-greening of the Sahel. However, little investment has been made in including long-term ground-based data collections to evaluate and better understand the biophysical mechanisms behind these findings. Thus, deductions on a possible increment in biomass remain speculative. Our aim is to bridge these gaps and give specifics on the biophysical background factors of the re-greening Sahel. Therefore, a trend analysis was applied on long time series (1987-2013) of satellite-based vegetation and rainfall data, as well as on ground-observations of leaf biomass of woody species, herb biomass, and woody species abundance in different ecosystems located in the Sahel zone of Senegal. We found that the positive trend observed in satellite vegetation time series (+36%) is caused by an increment of in situ measured biomass (+34%), which is highly controlled by precipitation (+40%). Whereas herb biomass shows large inter-annual fluctuations rather than a clear trend, leaf biomass of woody species has doubled within 27 years (+103%). This increase in woody biomass did not reflect on biodiversity with 11 of 16 woody species declining in abundance over the period. We conclude that the observed greening in the Senegalese Sahel is primarily related to an increasing tree cover that caused satellite-driven vegetation indices to increase with rainfall reversal. Copyright © 2015 John Wiley & Sons Ltd214 April 2015 10.1111/gcb.12807 Primary Research Article Primary Research Articles © 2014 John Wiley & Sons Ltd.
Diouf A.A., Brandt M., Verger A., El Jarroudi M., Djaby B., Fensholt R., Ndione J.A., Tychon B. (2015) Fodder biomass monitoring in Sahelian rangelands using phenological metrics from FAPAR time series. Remote Sensing. 7: 9122-9148.LinkDoi: 10.3390/rs70709122
Timely monitoring of plant biomass is critical for the management of forage resources in Sahelian rangelands. The estimation of annual biomass production in the Sahel is based on a simple relationship between satellite annual Normalized Difference Vegetation Index (NDVI) and in situ biomass data. This study proposes a new methodology using multi-linear models between phenological metrics from the SPOT-VEGETATION time series of Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) and in situ biomass. A model with three variables-large seasonal integral (LINTG), length of growing season, and end of season decreasing rate-performed best (MAE = 605 kg·DM/ha; R2 = 0.68) across Sahelian ecosystems in Senegal (data for the period 1999-2013). A model with annual maximum (PEAK) and start date of season showed similar performances (MAE = 625 kg·DM/ha; R2 = 0.64), allowing a timely estimation of forage availability. The subdivision of the study area in ecoregions increased overall accuracy (MAE = 489.21 kg·DM/ha; R2 = 0.77), indicating that a relation between metrics and ecosystem properties exists. LINTG was the main explanatory variable for woody rangelands with high leaf biomass, whereas for areas dominated by herbaceous vegetation, it was the PEAK metric. The proposed approach outperformed the established biomass NDVI-based product (MAE = 818 kg·DM/ha and R2 = 0.51) and should improve the operational monitoring of forage resources in Sahelian rangelands. © 2015 by the authors.
Verger A., Baret F., Weiss M., Filella I., Penuelas J. (2015) GEOCLIM: A global climatology of LAI, FAPAR, and FCOVER from VEGETATION observations for 1999-2010. Remote Sensing of Environment. 166: 126-137.LinkDoi: 10.1016/j.rse.2015.05.027
Land-surface modelling would benefit significantly from improved characterisation of the seasonal variability of vegetation at a global scale. GEOCLIM, a global climatology of leaf area index (LAI), fraction of absorbed photosynthetically active radiation (FAPAR)-both essential climate variables-and fraction of vegetation cover (FCOVER), is here derived from observations from the SPOT VEGETATION programme. Interannual average values from the GEOV1 Copernicus Global Land time series of biophysical products at 1-km resolution and 10-day frequency are computed for 1999 to 2010. GEOCLIM provides the baseline characteristics of the seasonal cycle of the annual vegetation phenology for each 1-km. pixel on the globe. The associated standard deviation characterises the interannual variability. Temporal consistency and continuity is achieved by the accumulation of multi-year observations and the application of techniques for temporal smoothing and gap filling. Specific corrections are applied over cloudy tropical regions and high latitudes in the Northern Hemisphere where the low number of available observations compromises the reliability of estimates. Artefacts over evergreen broadleaf forests and areas of bare soil are corrected based on the expected limited seasonality. The GEOCLIM data set is demonstrated to be consistent, both spatially and temporally. GEOCLIM shows absolute differences lower than 0.5 compared with MODIS (GIMMS3g) climatology of LAI for more than 80% (90%) of land pixels, with higher discrepancies in tropical and boreal latitudes. ECOCLIMAP systematically produces higher LAI values. The phenological metric for the date of maximum foliar development derived from GEOCLIM is spatially consistent (correlation higher than 0.9) with those of MODIS, GIMMS3g, ECOCLIMAP and MCD12Q2 with average differences within 14. days at the global scale. © 2015 Elsevier Inc.
Brandt M., Verger A., Diouf A.A., Baret F., Samimi C. (2014) Local vegetation trends in the sahel of mali and senegal using long time series FAPAR satellite products and field measurement (1982-2010). Remote Sensing. 6: 2408-2434.LinkDoi: 10.3390/rs6032408
Local vegetation trends in the Sahel of Mali and Senegal from Geoland Version 1 (GEOV1) (5 km) and the third generation Global Inventory Modeling and Mapping Studies (GIMMS3g) (8 km) Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) time series are studied over 29 years. For validation and interpretation of observed greenness trends, two methods are applied: (1) a qualitative approach using in-depth knowledge of the study areas and (2) a quantitative approach by time series of biomass observations and rainfall data. Significant greening trends from 1982 to 2010 are consistently observed in both GEOV1 and GIMMS3g FAPAR datasets. Annual rainfall increased significantly during the observed time period, explaining large parts of FAPAR variations at a regional scale. Locally, GEOV1 data reveals a heterogeneous pattern of vegetation change, which is confirmed by long-term ground data and site visits. The spatial variability in the observed vegetation trends in the Sahel area are mainly caused by varying tree-and land-cover, which are controlled by human impact, soil and drought resilience. A large proportion of the positive trends are caused by the increment in leaf biomass of woody species that has almost doubled since the 1980s due to a tree cover regeneration after a dry-period. This confirms the re-greening of the Sahel, however, degradation is also present and sometimes obscured by greening. GEOV1 as compared to GIMMS3g made it possible to better characterize the spatial pattern of trends and identify the degraded areas in the study region. © 2014 by the authors; licensee MDPI, Basel, Switzerland.
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