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Trend Change Detection in NDVI Time Series: Effects of Inter-Annual Variability and Methodology
2013
Remote Sensing
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Here we compare the performance of a wide range of trend estimation methods and demonstrate that performance decreases with increasing inter-annual variability in the NDVI time series. ...
Overall, our analyses demonstrate that seasonal trend methods need to be improved against inter-annual variability to quantify changing trends in ecosystem productivity with higher accuracy. ...
We thank the community of the R statistical software for providing a wealth of functionality. ...
doi:10.3390/rs5052113
fatcat:qb3wgc3tn5guxk2xe5cl6swrbe
A curve fitting procedure to derive inter-annual phenologies from time series of noisy satellite NDVI data
2007
Remote Sensing of Environment
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Annual, inter-annual and long-term trends in time series derived from remote sensing can be used to distinguish between natural land cover variability and land cover change. ...
However, the utility of using NDVI-derived phenology to detect change is often limited by poor quality data resulting from atmospheric and other effects. ...
Acknowledgements We thank Jeremy Fisher and Daniel Orenstein for constructive feedback on earlier drafts of the manuscript. ...
doi:10.1016/j.rse.2006.08.002
fatcat:jkgrfjv4ifa4joog3buiqctwae
Detecting dryland degradation using Time Series Segmentation and Residual Trend analysis (TSS-RESTREND)
2017
Remote Sensing of Environment
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When applied to Australia, this new methodology, termed Time Series Segmentation and Residual Trend analysis (TSS-RESTREND), was able to detect degradation in 5.25% of pixels compared to only 2.0% for ...
This paper presents an extended version of the RESTREND methodology that incorporates the Breaks For Additive Seasonal and Trend method to identify step changes in the time series that are related to significant ...
In order to assess the effectiveness of the TSS-RESTREND method, a standard RESTREND and a trend in the raw NDVI max time series (NDVI ts ) were calculated. ...
doi:10.1016/j.rse.2017.05.018
fatcat:bbtla54vsjafvcadbfkelecpv4
Investigation of Vegetation Dynamics using Long-Term Normalized Difference Vegetation Index Time-Series
2009
American Journal of Environmental Sciences
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in order to identify the long-term trend components of generated NDVI time-series and extract vegetation dynamics. ...
The proposed study attempted to investigate the temporal vegetation dynamics in the whole Africa using historical NDVI time-series. ...
Moreover, it can be noticed that the robust methodology applied in this study, allowing to detect and remove residual noise data in base time-series before the estimation of the trend components, guarantees ...
doi:10.3844/ajessp.2009.461.467
fatcat:sgq3zhfbcraljlylrk6pjr3hqq
Investigation of Vegetation Dynamics using Long-Term Normalized Difference Vegetation Index Time-Series
2009
American Journal of Environmental Sciences
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in order to identify the long-term trend components of generated NDVI time-series and extract vegetation dynamics. ...
The proposed study attempted to investigate the temporal vegetation dynamics in the whole Africa using historical NDVI time-series. ...
Moreover, it can be noticed that the robust methodology applied in this study, allowing to detect and remove residual noise data in base time-series before the estimation of the trend components, guarantees ...
doi:10.3844/ajessp.2009.460.466
fatcat:h372xwfkhnetbnw4nuycta7dzi
A statistical framework for the analysis of long image time series
2005
International Journal of Remote Sensing
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A contribution of the University of Nebraska Agricultural Research Division, Lincoln, NE, Journal Series No. 14454. ...
Data used by the authors include data produced through funding from the Earth Observing System Pathfinder Program of NASA's Mission to Planet Earth in cooperation with National Oceanic and Atmospheric ...
To distinguish change from variation, it is necessary to partition the variability observed in an image time series into contributions attributable to sensor artifacts, inter-annual climate variation and ...
doi:10.1080/01431160512331326657
fatcat:oiccbesgrzca5b3jvqfolbktue
Hierarchical image segmentation based on similarity of NDVI time series
2008
Remote Sensing of Environment
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The MTHIS methodology is demonstrated on the area of South Africa in an MTHIS protocol for Normalized Difference Vegetation Index (NDVI) time series. ...
Firstly, the FFT components that express the major spatio-temporal variation in the NDVI time series, the average and annual term, are selected and the segmentation is performed based on these components ...
Jonckheere is 2006 Laureate of the Belgian Stichting Roeping, and is currently a Postdoctoral fellow of the FWO Flanders. ...
doi:10.1016/j.rse.2007.05.018
fatcat:s77arfpm75h5rljzdd77mb4uti
ASSESSING IMPACTS OF CLIMATE CHANGE ON TEAK AND SAL LANDSCAPE USING MODIS TIME SERIES DATA
2018
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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The average annual NDVI of Teak and Sal forests showed an increasing trend however, no trend was observed in seasonal and monthly NDVI over the same period. ...
The current study aims to understand the impact of climate change on Teak and Sal forest of STR (Satpura tiger reserve) in central India by using Landsat and MODIS time series data. ...
Fig.2 Flowchart of steps used in LULC and NDVI based change detection analysis
MODIS Time series extraction In order to monitor the vegetation health, the consistent time series data available from MODIS ...
doi:10.5194/isprs-archives-xlii-5-305-2018
fatcat:6yqytrcp5rgxtlqwrpudxmlvei
Monitoring Urban Dynamics in the Southeast U.S.A. Using Time-Series DMSP/OLS Nightlight Imagery
2016
Remote Sensing
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In this study, we first preprocessed the time series of annual DMSP-OLS NTL data and NDVI data. The annual VANUI values were then calculated. ...
The newly built urban areas were effectively detected based on the trend analysis. ...
Conflicts of Interest: The authors declare no conflict of interest. ...
doi:10.3390/rs8070578
fatcat:36v5jtspfnfpbg7jsjtlia3uiy
Estimation of vegetation cover resilience from satellite time series
2008
Hydrology and Earth System Sciences
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In order to characterize resilience, we analyzed the time series 1982-2003 of 8 km GIMMS AVHRR-NDVI maps of the Italian territory. ...
Generally, mean recovery times from negative trends were shorter than those estimated for positive trends, as expected for vegetation of healthy status. ...
This work was supported by the Italian Ministry of University and Research (MiUR) within the framework of the "TeRN" project (Tecnologie per le Osservazioni della Terra e i Rischi Naturali) (Rif. ...
doi:10.5194/hess-12-1053-2008
fatcat:7xxdjuhiivdard3hlocjmtp2ua
Estimation of vegetation cover resilience from satellite time series
2008
Hydrology and Earth System Sciences Discussions
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In order to characterize resilience, we analyzed the time series 1982-2003 of 8 km GIMMS AVHRR-NDVI maps of the Italian territory. ...
Generally, mean recovery times from negative trends were shorter than those estimated for positive trends, as expected for vegetation of healthy status. ...
This work was supported by the Italian Ministry of University and Research (MiUR) within the framework of the "TeRN" project (Tecnologie per le Osservazioni della Terra e i Rischi Naturali) (Rif. ...
doi:10.5194/hessd-5-511-2008
fatcat:4a3cq4igljfwtk2sms2oz4rz4i
Human induced dryland degradation in Ordos Plateau, China, revealed by multilevel statistical modeling of normalized difference vegetation index and rainfall time-series
2013
Journal of Arid Land
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Land degradation causes serious environmental problems in many regions of the world, and although it can be effectively assessed and monitored using a time series of rainfall and a normalized difference ...
statistical modeling could be used to analyze the relationship between the NDVI and rainfall and improve the accuracy of detecting the effect of human activities. ...
Acknowledgements This study was supported by the National Basic Research Program of China (2012CB722201), the National Natural Science Foundation of China (30970504, 31060320), and the National Science ...
doi:10.1007/s40333-013-0203-x
fatcat:2p6kvx77azfjhikddgzh4mk6bm
Length of Growing Period over Africa: Variability and Trends from 30 Years of NDVI Time Series
2013
Remote Sensing
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Our LGP analysis provides useful information for the mapping of farming systems, and to study the effects of climate variability and other drivers of change on vegetation and crop suitability. ...
High LGP variability is dominant in arid and semi-arid areas, and is indicative of crop failure risk. ...
We acknowledge the valuable contribution of four anonymous reviewers in improving the manuscript, and the explanations provided on the agro-ecological zoning (AEZ) method by Harry van Velthuizen of IIASA ...
doi:10.3390/rs5020982
fatcat:fraq5ojdsza3zli272sild5kpa
Analysis of vegetation and land cover dynamics in north-western Morocco during the last decade using MODIS NDVI time series data
2011
Biogeosciences
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Statistically significant inter-annual trends in vegetation dynamics during the last decade could however not be discovered. ...
improved using multi-year MODIS NDVI time series data. ...
Vincent Simonneaux for his advice in terms of landscape classification in Morocco, Mr. Marco Otto and Mr. Christopher Brown for revisions and Mr. Jens Rogée for preparing NCDC station data. ...
doi:10.5194/bg-8-3359-2011
fatcat:qb4wje4gqnevtn47e5vi3chlhy
Reconstructing pathfinder AVHRR land NDVI time-series data for the Northwest of China
2006
Advances in Space Research
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But some PAL NDVI time series remain significant residual effects and noise levels. ...
tool for reconstructing high-quality time series of PAL NDVI time series. ...
Acknowledgements This work is supported by the project of National Natural Science Foundation of China (40401062) and the innovation project of the Cold and Arid Regions Environmental and Engineering Research ...
doi:10.1016/j.asr.2005.08.037
fatcat:hlk7ciazt5d4doeqvezyswliuy
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