Global‐scale mapping of changes in ecosystem functioning from earth observation‐based trends in total and recurrent vegetation

Fensholt, Rasmus; Horion, Stéphanie; Tagesson, Torbern; Ehammer, Andrea; Ivits, Éva; Rasmussen, Kjeld

doi:10.1111/geb.12338

Cited by 30 publications

(25 citation statements)

References 39 publications

(47 reference statements)

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“…They also employed the TIMESAT approach, but with different parameter settings as compared to this study, indicating the robustness of the method for phenology retrieval and consequently the results obtained in this study. Moreover, the calculated trends in GSI ( Figure 2D) are in agreement with the result from Fensholt et al [53], although their study period (1982-2011) was two years shorter than this study.…”

Section: Trends In Vegetation Phenology and Growing Season Integralsupporting

confidence: 92%

“…This is further supported by Xia [69] et al who revealed that the inter-biome variations in annual GPP can be better explained by the variations in seasonal maximal photosynthetic capacity than LOS. In addition to the impact from ongoing global warming and natural climate variability, the relationship between vegetation phenology and productivity could also be affected by changes in both/either vegetation metrics induced by anthropogenic land use/cover changes (e.g., deforestation/afforestation, land clearing, irrigation and fertilization, and changes in land management practices) [53,60,[74][75][76]. Whereas, it could be assumed that changes in land management may also cause divergence between LOS and GSI (e.g., a change from one crop-type to another with different LOS/GSI characteristics), it is noteworthy that both converging trends and pixels with significant positive correlations between LOS and GSI are more pronounced for mixed forest than for the three natural forest biomes, which is also the case for croplands as compared to the three natural non-forest biomes ( Figures 4A and 6B).…”

Section: Converging/diverging Trends and Correlations Between Los Andmentioning

confidence: 99%

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Temporal Changes in Coupled Vegetation Phenology and Productivity are Biome-Specific in the Northern Hemisphere

Wang

Fensholt

2017

Remote Sensing

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Global warming has greatly stimulated vegetation growth through both extending the growing season and promoting photosynthesis in the Northern Hemisphere (NH). Analyzing the combined dynamics of such trends can potentially improve our current understanding on changes in vegetation functioning and the complex relationship between anthropogenic and climatic drivers. This study aims to analyze the relationships (long-term trends and correlations) of length of vegetation growing season (LOS) and vegetation productivity assessed by the growing season NDVI integral (GSI) in the NH (>30 • N) to study any dependency of major biomes that are characterized by different imprint from anthropogenic influence. Spatial patterns of converging/diverging trends in LOS and GSI and temporal changes in the coupling between LOS and GSI are analyzed for major biomes at hemispheric and continental scales from the third generation Global Inventory Monitoring and Modeling Studies (GIMMS) Normalized Difference Vegetation Index (NDVI) dataset for a 32-year period . A quarter area of the NH is covered by converging trends (consistent significant trends in LOS and GSI), whereas diverging trends (opposing significant trends in LOS and GSI) cover about 6% of the region. Diverging trends are observed mainly in high latitudes and arid/semi-arid areas of non-forest biomes (shrublands, savannas, and grasslands), whereas forest biomes and croplands are primarily characterized by converging trends. The study shows spatially-distinct and biome-specific patterns between the continental land masses of Eurasia (EA) and North America (NA). Finally, areas of high positive correlation between LOS and GSI showed to increase during the period of analysis, with areas of significant positive trends in correlation being more widespread in NA as compared to EA. The temporal changes in the coupled vegetation phenology and productivity suggest complex relationships and interactions that are induced by both ongoing climate change and increasingly intensive human disturbances.

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Section: Trends In Vegetation Phenology and Growing Season Integralsupporting

confidence: 92%

Section: Converging/diverging Trends and Correlations Between Los Andmentioning

confidence: 99%

Temporal Changes in Coupled Vegetation Phenology and Productivity are Biome-Specific in the Northern Hemisphere

Wang

Fensholt

2017

Remote Sensing

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“…Global scale studies demonstrated the applicability of the NDVI3g, the longest available remote sensing dataset [25], in trend detection of the phenological cycle and sensitivity studies (e.g., [34,[36][37][38][40][41][42][83][84][85]). Nevertheless, evaluation of NDVI3g for regional application is necessary due to known issues and uncertainties [32][33][34][35].…”

Section: Modis Ndvi As Reference Dataset For Ndvi3g Evaluationmentioning

confidence: 99%

Evaluation of the Quality of NDVI3g Dataset against Collection 6 MODIS NDVI in Central Europe between 2000 and 2013

2016

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Abstract:Remote sensing provides invaluable insight into the dynamics of vegetation with global coverage and reasonable temporal resolution. Normalized Difference Vegetation Index (NDVI) is widely used to study vegetation greenness, production, phenology and the responses of ecosystems to climate fluctuations. The extended global NDVI3g dataset created by Global Inventory Modeling and Mapping Studies (GIMMS) has an exceptional 32 years temporal coverage. Due to the methodology that was used to create NDVI3g inherent noise and uncertainty is present in the dataset. To evaluate the accuracy and uncertainty of application of NDVI3g at regional scale we used Collection-6 data from the MODerate resolution Imaging Spectroradiometer (MODIS) sensor on board satellite Terra as a reference. After noise filtering, statistical harmonization of the NDVI3g dataset was performed for Central Europe based on MOD13 NDVI. Mean seasonal NDVI profiles, start, end and length of the growing season, magnitude and timing of peak NDVI were calculated from NDVI3g (original, noise filtered and harmonized) and MODIS NDVI and compared with each other. NDVI anomalies were also compared and evaluated using simple climate sensitivity metrics. The results showed that (1) the original NDVI3g has limited applicability in Central Europe, which was also implied by the significant disagreement between the NDVI3g and MODIS NDVI datasets; (2) the harmonization of NDVI3g with MODIS NDVI is promising since the newly created dataset showed improved quality for diverse vegetation metrics. For NDVI anomaly detection NDVI3g showed limited applicability, even after harmonization. Climate-NDVI relationships are not represented well by NDVI3g. The presented results can help researchers to assess the expected quality of the NDVI3g-based studies in Central Europe.

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“…It is an important method in vegetation change trend analysis to carry out a regression analysis of time-varying variables and to predict their trends [17,[50][51][52][53]. The slope of the equation developed using linear least square fitting of long time NDVI series shows NDVI trends over several years.…”

Section: Trend Analysis Of Vegetation Dynamicsmentioning

confidence: 99%

Vegetation Dynamics and Associated Driving Forces in Eastern China during 1999–2008

Peng

Lan

et al. 2015

Remote Sensing

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Vegetation is one of the most important components of the terrestrial ecosystem and, thus, monitoring the spatial and temporal dynamics of vegetation has become the key to exploring the basic process of the terrestrial ecosystem. Vegetation change studies have focused on the relationship between climatic factors and vegetation dynamics. However, correlations among the climatic factors always disturb the results. In addition, the impact of anthropogenic activities on vegetation dynamics was indeterminate. Here, vegetation dynamics in 14 provinces in Eastern China over a 10-year period was quantified to determine the driving mechanisms relating to climate and anthropogenic factors using partial correlation analysis. The results showed that from 1999 to 2008, the vegetation density increased in the whole, with spatial variations. The vegetation improvement was concentrated in the Yangtze River Delta, with the vegetation degradation concentrated in the other developed areas, such as Beijing-Tianjin-Hebei Region and the Pearl River Delta. The annual NDVI changes were mainly driven by temperature in Northeast China and the Pearl River Delta, and by precipitation in the Bohai Rim; while in the Yangtze River Delta, the driving forces of temperature and precipitation almost equaled each other. Furthermore, the impact of anthropogenic activities on vegetation dynamics had accumulative effects in the time series, and had a phase effect on the vegetation change trend.

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Global‐scale mapping of changes in ecosystem functioning from earth observation‐based trends in total and recurrent vegetation

Cited by 30 publications

References 39 publications

Temporal Changes in Coupled Vegetation Phenology and Productivity are Biome-Specific in the Northern Hemisphere

Temporal Changes in Coupled Vegetation Phenology and Productivity are Biome-Specific in the Northern Hemisphere

Evaluation of the Quality of NDVI3g Dataset against Collection 6 MODIS NDVI in Central Europe between 2000 and 2013

Vegetation Dynamics and Associated Driving Forces in Eastern China during 1999–2008

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