Vegetation greening in Spain detected from long term data (1981–2015)

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PID https://www.doi.org/10.6084/m9.figshare.9994202
PID https://www.doi.org/10.1080/01431161.2019.1674460
PID https://www.doi.org/10.6084/m9.figshare.9994202.v1
PID handle:10261/210730
URL http://digital.csic.es/bitstream/10261/210730/1/accesoRestringido.pdf
URL https://digital.csic.es/handle/10261/210730
URL https://academic.microsoft.com/#/detail/2980621230
URL https://ui.adsabs.harvard.edu/abs/2020IJRS...41.1709V/abstract
URL http://dx.doi.org/10.6084/m9.figshare.9994202.v1
URL http://dx.doi.org/10.6084/m9.figshare.9994202
URL http://hdl.handle.net/10261/210730
URL https://doi.org/10.1080/01431161.2019.1674460
URL https://www.tandfonline.com/doi/pdf/10.1080/01431161.2019.1674460
URL http://dx.doi.org/10.1080/01431161.2019.1674460
URL https://www.tandfonline.com/doi/full/10.1080/01431161.2019.1674460
URL https://pubag.nal.usda.gov/catalog/6775965
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Access Right Open Access
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Author Ivan Noguera, 0000-0002-0696-9504
Author Sergio M. Vicente-Serrano, 0000-0003-2892-518X
Author Natalia Martín, 0000-0002-6995-4625
Author Marina Peña-Gallardo, 0000-0002-1857-2504
Author Fernando Dominguez-Castro, 0000-0003-3085-7040
Author Monica Garcia, 0000-0002-4587-8920
Author Ahmed Kenawy, 0000-0001-6639-6253
Contributor Comisión Interministerial de Ciencia y Tecnología, CICYT (España)
Contributor European Commission
Contributor Ministerio de Agricultura, Alimentación y Medio Ambiente (España)
Contributor Beguería, Santiago
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Collected From Digital.CSIC; ORCID; Datacite; figshare; Crossref; Microsoft Academic Graph
Hosted By Digital.CSIC; figshare; International Journal of Remote Sensing
Publication Date 2019-10-16
Publisher Taylor & Francis
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Country Spain
Description This study describes a newly developed high-resolution (1.1 km) Normalized Difference Vegetation Index dataset for the peninsular Spain and the Balearic Islands (Sp_1km_NDVI). This dataset is developed based on National Oceanic and Atmospheric Administration–Advanced Very High Resolution Radiometer (NOAA–AVHRR) afternoon images, spanning the past three decades (1981–2015). After a careful pre-processing procedure, including calibration with post-launch calibration coefficients, geometric and topographic corrections, cloud removal, temporal filtering, and bi-weekly composites by maximum NDVI-value, we assessed changes in vegetation greening over the study domain using Mann-Kendall and Theil-Sen statistics. Our trend results were compared with those derived from some widely recognized global NDVI datasets [e.g. the Global Inventory Modelling and Mapping Studies 3rd generation (GIMMS3g), Smoothed NDVI (SMN) and Moderate-Resolution Imaging Spectroradiometer (MODIS)]. Results demonstrate that there is a good agreement between the annual trends based on Sp_1km_NDVI product and other datasets. Nonetheless, we found some differences in the spatial patterns of the NDVI trends at the seasonal scale. Overall, in comparison to the available global NDVI datasets, Sp_1km_NDVI allows for characterizing changes in vegetation greening at a more-detailed spatial and temporal scale. In specific, our dataset provides relatively long-term corrected satellite time series (>30 years), which are crucial to understand the response of vegetation to climate change and human-induced activities. Also, given the complex spatial structure of NDVI changes over the study domain, particularly due to the rapid land intensification processes, the spatial resolution (1.1 km) of our dataset can provide detailed spatial information on the inter-annual variability of vegetation greening in this Mediterranean region and assess its links to climate change and variability.
Description This work was supported by the research projects PCIN-2015-220, PCIN-2017-020, CGL2014-52135-C03-01, CGL2017-83866-C3-3-R and CGL2017-82216-R financed by the Spanish Commission of Science and Technology and FEDER ECOHIDRO (1550/2015, funded bythe Natural Parks-Ministry of Agriculture and Environment), IMDROFLOOD financed by the WaterWorks 2014 co-funded call of the European Commission, CROSSDRO financed by the Assessment of Cross(X) - sectoral climate Impacts and pathways for Sustainable transformation JPI Climate co-funded call of the European Commission and INDECIS, which is part of ERA4CS, an ERA-NET initiated by JPI Climate, and funded by FORMAS (SE), DLR (DE), BMWFW (AT), IFD (DK), MINECO (ES), ANR (FR) with co-funding by the European Union (Grant 690462).
Description Peer reviewed
Language UNKNOWN
Resource Type Other literature type; Article
keyword FOS: Biological sciences
keyword FOS: Computer and information sciences
keyword FOS: Earth and related environmental sciences
system:type publication
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Source https://science-innovation-policy.openaire.eu/search/publication?articleId=dedup_wf_001::0f7382819e89377d3c7848cd0c7a7698
Author jsonws_user
Last Updated 21 December 2020, 18:01 (CET)
Created 21 December 2020, 18:01 (CET)