Analysis of monotonic greening and browning trends from global NDVI time-series

R. de Jong, S. de Bruin, A.J.W. de Wit, M.E. Schaepman, D.L. Dent

Research output: Contribution to journalArticleAcademicpeer-review

288 Citations (Scopus)

Abstract

Remotely sensed vegetation indices are widely used to detect greening and browning trends; especially the global coverage of time-series normalized difference vegetation index (NDVI) data which are available from 1981. Seasonality and serial auto-correlation in the data have previously been dealt with by integrating the data to annual values; as an alternative to reducing the temporal resolution, we apply harmonic analyses and non-parametric trend tests to the GIMMS NDVI dataset (1981–2006). Using the complete dataset, greening and browning trends were analyzed using a linear model corrected for seasonality by subtracting the seasonal component, and a seasonal non-parametric model. In a third approach, phenological shift and variation in length of growing season were accounted for by analyzing the time-series using vegetation development stages rather than calendar days. Results differed substantially between the models, even though the input data were the same. Prominent regional greening trends identified by several other studies were confirmed but the models were inconsistent in areas with weak trends. The linear model using data corrected for seasonality showed similar trend slopes to those described in previous work using linear models on yearly mean values. The non-parametric models demonstrated the significant influence of variations in phenology; accounting for these variations should yield more robust trend analyses and better understanding of vegetation trends.
Original languageEnglish
Pages (from-to)692-702
JournalRemote Sensing of Environment
Volume115
Issue number2
DOIs
Publication statusPublished - 2011

Fingerprint

NDVI
Time series
time series analysis
time series
linear models
seasonality
vegetation
autocorrelation
phenology
growing season
trend
analysis
normalized difference vegetation index
Autocorrelation
vegetation index
testing

Keywords

  • avhrr vegetation index
  • land degradation
  • spot-vegetation
  • growing-season
  • photosynthetic trends
  • primary productivity
  • deciduous forest
  • plant phenology
  • carbon-dioxide
  • high-latitudes

Cite this

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title = "Analysis of monotonic greening and browning trends from global NDVI time-series",
abstract = "Remotely sensed vegetation indices are widely used to detect greening and browning trends; especially the global coverage of time-series normalized difference vegetation index (NDVI) data which are available from 1981. Seasonality and serial auto-correlation in the data have previously been dealt with by integrating the data to annual values; as an alternative to reducing the temporal resolution, we apply harmonic analyses and non-parametric trend tests to the GIMMS NDVI dataset (1981–2006). Using the complete dataset, greening and browning trends were analyzed using a linear model corrected for seasonality by subtracting the seasonal component, and a seasonal non-parametric model. In a third approach, phenological shift and variation in length of growing season were accounted for by analyzing the time-series using vegetation development stages rather than calendar days. Results differed substantially between the models, even though the input data were the same. Prominent regional greening trends identified by several other studies were confirmed but the models were inconsistent in areas with weak trends. The linear model using data corrected for seasonality showed similar trend slopes to those described in previous work using linear models on yearly mean values. The non-parametric models demonstrated the significant influence of variations in phenology; accounting for these variations should yield more robust trend analyses and better understanding of vegetation trends.",
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Analysis of monotonic greening and browning trends from global NDVI time-series. / de Jong, R.; de Bruin, S.; de Wit, A.J.W.; Schaepman, M.E.; Dent, D.L.

In: Remote Sensing of Environment, Vol. 115, No. 2, 2011, p. 692-702.

Research output: Contribution to journalArticleAcademicpeer-review

TY - JOUR

T1 - Analysis of monotonic greening and browning trends from global NDVI time-series

AU - de Jong, R.

AU - de Bruin, S.

AU - de Wit, A.J.W.

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AU - Dent, D.L.

PY - 2011

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KW - deciduous forest

KW - plant phenology

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