Vegetation greening in Spain detected from long term data (1981–2015)
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http://data.d4science.org/ctlg/RISIS2OpenData/dedup_wf_001--0f7382819e89377d3c7848cd0c7a7698 |
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Identity
Access Modality
Field | Value |
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Access Right | Open Access |
Attribution
Field | Value |
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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 |
Publishing
Field | Value |
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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 |
Additional Info
Field | Value |
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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 |
Management Info
Field | Value |
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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) |