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Relationship between Spatiotemporal Variations of Climate, Snow Cover and Plant Phenology over the Alps - An Earth Observation-Based Analysis

Asam, Sarah and Callegari, Mattia and Matiu, Michael and Fiore, Giuseppe and De Gregorio, Ludovica and Jacob, Alexander and Menzel, Annette and Zebisch, Marc and Notarnicola, Claudia (2018) Relationship between Spatiotemporal Variations of Climate, Snow Cover and Plant Phenology over the Alps - An Earth Observation-Based Analysis. Remote Sensing, 10 (11), pp. 1-26. Multidisciplinary Digital Publishing Institute (MDPI). DOI: 10.3390/rs10111757 ISSN 2072-4292

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Official URL: https://www.mdpi.com/2072-4292/10/11/1757

Abstract

Alpine ecosystems are particularly sensitive to climate change, and therefore it is of significant interest to understand the relationships between phenology and its seasonal drivers in mountain areas. However, no alpine-wide assessment on the relationship between land surface phenology (LSP) patterns and its climatic drivers including snow exists. Here, an assessment of the influence of snow cover variations on vegetation phenology is presented, which is based on a 17-year time-series of MODIS data. From this data snow cover duration (SCD) and phenology metrics based on the Normalized Difference Vegetation Index (NDVI) have been extracted at 250 m resolution for the entire European Alps. The combined influence of additional climate drivers on phenology are shown on a regional scale for the Italian province of South Tyrol using reanalyzed climate data. The relationship between vegetation and snow metrics strongly depended on altitude. Temporal trends towards an earlier onset of vegetation growth, increasing monthly mean NDVI in spring and late summer, as well as shorter SCD were observed, but they were mostly non-significant and the magnitude of these tendencies differed by altitude. Significant negative correlations between monthly mean NDVI and SCD were observed for 15-55% of all vegetated pixels, especially from December to April and in altitudes from 1000-2000 m. On the regional scale of South Tyrol, the seasonality of NDVI and SCD achieved the highest share of correlating pixels above 1500 m, while at lower elevations mean temperature correlated best. Examining the combined effect of climate variables, for average altitude and exposition, SCD had the highest effect on NDVI, followed by mean temperature and radiation. The presented analysis allows to assess the spatiotemporal patterns of earth-observation based snow and vegetation metrics over the Alps, as well as to understand the relative importance of snow as phenological driver with respect to other climate variables

Item URL in elib:https://elib.dlr.de/123049/
Document Type:Article
Title:Relationship between Spatiotemporal Variations of Climate, Snow Cover and Plant Phenology over the Alps - An Earth Observation-Based Analysis
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Asam, Sarahsarah.asam (at) dlr.dehttps://orcid.org/0000-0002-7302-6813
Callegari, Mattiamattia.callegari (at) eurac.eduUNSPECIFIED
Matiu, Michaelmichaelmatiu (at) gmail.comUNSPECIFIED
Fiore, GiuseppeUNSPECIFIEDUNSPECIFIED
De Gregorio, LudovicaLudovica.DeGregorio (at) eurac.eduUNSPECIFIED
Jacob, Alexanderalexander.jacob (at) eurac.eduUNSPECIFIED
Menzel, Annetteamenzel (at) wzw.tum.deUNSPECIFIED
Zebisch, Marcmarc.zebisch (at) eurac.eduUNSPECIFIED
Notarnicola, Claudiaclaudia.notarnicola (at) eurac.eduUNSPECIFIED
Date:7 November 2018
Journal or Publication Title:Remote Sensing
Refereed publication:Yes
Open Access:Yes
Gold Open Access:Yes
In SCOPUS:Yes
In ISI Web of Science:No
Volume:10
DOI :10.3390/rs10111757
Page Range:pp. 1-26
Publisher:Multidisciplinary Digital Publishing Institute (MDPI)
ISSN:2072-4292
Status:Published
Keywords:mountains; phenology; NDVI; snow cover; climate variability; impact of climate change; MODIS; Alps
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Earth Observation
DLR - Research area:Raumfahrt
DLR - Program:R EO - Erdbeobachtung
DLR - Research theme (Project):R - Remote sensing and geoscience
Location: Oberpfaffenhofen
Institutes and Institutions:German Remote Sensing Data Center > Land Surface Dynamics
Deposited By: Asam, Dr. Sarah
Deposited On:13 Nov 2018 13:33
Last Modified:21 Sep 2019 05:06

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