Combining satellite derived phenology with climate data for climate change impact assessment

Ivits, Éva; Michael, Cherlet; Tóth, Gergely; Sommer, Stefan; Mehl, W.; Vogt, J.; Micale, Fabio

doi:10.1016/j.gloplacha.2012.03.010

Cited by 65 publications

(44 citation statements)

References 45 publications

(54 reference statements)

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“…Especially the de-convolution of the original time series into phenological and productivity metrics yield additional information on various aspects of vegetation dynamics and ecosystem functioning [18] that can be related to land use [19]. Monitoring vegetation phenology using satellite remote sensing [20][21][22][23][24][25] offers an optimal framework for ecosystem studies because in situ phenological data are comparatively scarce in many parts of the world [26] and because long time and large spatial scales can be addressed simultaneously. Monitoring vegetation phenology has also improved the understanding of the interactions between the biosphere, the climate and biogeochemical cycles [16,[27][28][29].…”

Section: Introductionmentioning

confidence: 99%

Global Biogeographical Pattern of Ecosystem Functional Types Derived From Earth Observation Data

et al. 2013

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Abstract:The present study classified global Ecosystem Functional Types (EFTs) derived from seasonal vegetation dynamics of the GIMMS3g NDVI time-series. Rotated Principal Component Analysis (PCA) was run on the derived phenological and productivity variables, which selected the Standing Biomass (approximation of Net Primary Productivity), the Cyclic Fraction (seasonal vegetation productivity), the Permanent Fraction (permanent surface vegetation), the Maximum Day (day of maximum vegetation development) and the Season Length (length of vegetation growing season) variables, describing 98% of the variation in global ecosystems. EFTs were created based on Isodata classification of the spatial patterns of the Principal Components and were interpreted via gradient analysis using the selected remote sensing variables and climatic constraints (radiation, temperature, and water) of vegetation growth. The association of the EFTs with existing climate and land cover classifications was demonstrated via Detrended Correspondence Analysis (DCA). The ordination indicated good description of the global environmental gradient by the EFTs, supporting the understanding of phenological and productivity dynamics of global ecosystems. Climatic constraints of vegetation growth explained 50% of variation in the phenological data along the EFTs showing that part of the variation in the global phenological gradient is not climate related but is unique to the Earth Observation derived variables. DCA demonstrated good correspondence of the EFTs to global climate and also to land use classification. The results show the great potential of Earth Observation derived OPEN ACCESS Remote Sens. 2013, 5 3306 parameters for the quantification of ecosystem functional dynamics and for providing reference status information for future assessments of ecosystem changes.

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Section: Introductionmentioning

confidence: 99%

Global Biogeographical Pattern of Ecosystem Functional Types Derived From Earth Observation Data

et al. 2013

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“…We selected the eight neighbors rule within a moving window that ensures that the resulting Gi* values are normally distributed and considered the centre of the moving window as well, which is more appropriate for use in remote sensing [41]. For a detailed description see [21].…”

Section: Classification Of Ecosystem Response Typesmentioning

confidence: 99%

“…Detection of regional [18][19][20][21][22] and global vegetation dynamics [23][24][25][26] using remote sensing time-series and linking these to climate [27][28][29][30][31][32] have already improved the understanding of ecosystem dynamics. However, there are still gaps in information on how ecosystems respond to global climate fluctuations.…”

Section: Introductionmentioning

confidence: 99%

Global Ecosystem Response Types Derived from the Standardized Precipitation Evapotranspiration Index and FPAR3g Series

et al. 2014

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Abstract:Observing trends in global ecosystem dynamics is an important first step, but attributing these trends to climate variability represents a further step in understanding Earth system changes. In the present study, we classified global Ecosystem Response Types (ERTs) based on common spatio-temporal patterns in time-series of Standardized Precipitation Evapotranspiration Index (SPEI) and FPAR3g anomalies by using an extended Principal Component Analysis. The ERTs represent region specific spatio-temporal patterns of ecosystems responding to drought or ecosystems with decreasing severity in drought events as well as ecosystems where drought was not a dominant factor in a 30-year period. Highest explanatory values in the SPEI12-FPAR3g anomalies and strongest SPEI12-FPAR3g correlations were seen in the ERTs of Australia and South America whereas lowest explanatory value and lowest correlations were observed in Asia and North America. These ERTs complement traditional pixel based methods by enabling the combined assessment of the location, timing, duration, frequency and severity of climatic and vegetation anomalies with the joint assessment of wetting and drying climatic conditions. The ERTs produced here thus have potential in supporting global change studies by mapping reference conditions of long term ecosystem changes.

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“…This dataset has been widely used for regional and global scale vegetation trend analysis representing changes in vegetation phenology (Anyamba et al, 2005;Baldi et al, 2008;Julien et al, 2009;Sobrino et al, 2011). Furthermore, numerous international researches have focused on the relationship between variations of climatic variables such as rainfall and air temperature and changes in vegetation phenology (Ichii et al, 2002;Fensholt et al, 2011;Ivit et al, 2012;Fensholt et al, 2013). The objectives of this study was to identify the vegetation dynamics in relation to climate factors in the Hyrcanian forests, North of Iran.…”

Section: Introductionmentioning

confidence: 99%

Shifts of Start and End of Season in Response to Air Temperature Variation Based on Gimms Dataset in Hyrcanian Forests

Kiapasha

Darvishsefat

Zargham

et al. 2017

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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KEY WORDS: Climate change, start of season, end of season, GIMMS NDVI3g, Hyrcanian forest. ABSTRACT:Climate change is one of the most important environmental challenges in the world and forest as a dynamic phenomenon is influenced by environmental changes. The Hyrcanian forests is a unique natural heritage of global importance and we need monitoring this region. The objective of this study was to detect start and end of season trends in Hyrcanian forests of Iran based on biweekly GIMMS (Global Inventory Modeling and Mapping Studies) NDVI3g in the period 1981-2012. In order to find response of vegetation activity to local temperature variations, we used air temperature provided from I.R. Iran Meteorological Organization (IRIMO). At the first step in order to remove the existing gap from the original time series, the iterative Interpolation for Data Reconstruction (IDR) model was applied to GIMMS and temperature dataset. Then we applied significant Mann Kendall test to determine significant trend for each pixel of GIMMS and temperature datasets over the Hyrcanian forests. The results demonstrated that start and end of season (SOS & EOS respectively) derived from GIMMS3g NDVI time series increased by -0.16 and +0.41 days per year respectively. The trends derived from temperature time series indicated increasing trend in the whole of this region. Results of this study showed that global warming and its effect on growth and photosynthetic activity can increased the vegetation activity in our study area. Otherwise extension of the growing season, including an earlier start of the growing season, later autumn and higher rate of production increased NDVI value during the study period.

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Combining satellite derived phenology with climate data for climate change impact assessment

Cited by 65 publications

References 45 publications

Global Biogeographical Pattern of Ecosystem Functional Types Derived From Earth Observation Data

Global Biogeographical Pattern of Ecosystem Functional Types Derived From Earth Observation Data

Global Ecosystem Response Types Derived from the Standardized Precipitation Evapotranspiration Index and FPAR3g Series

Shifts of Start and End of Season in Response to Air Temperature Variation Based on Gimms Dataset in Hyrcanian Forests

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