The effect of the temporal resolution of NDVI data on season onset dates and trends across Canadian broadleaf forests

Kross, Angela; Fernandes, Richard; Seaquist, Jonathan; Beaubien, Elisabeth

doi:10.1016/j.rse.2011.02.015

Cited by 77 publications

(53 citation statements)

References 42 publications

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“…It was reported that, through the use of ground observation data as well as NVDI datasets of Landsat and MODIS, different sources of remote sensing results could be used to describe the observation data of ground phenology in an area. 12 A study by Kross et al 13 indicated that an NDVI dataset with a time resolution of 10 or 15 days was suitable for extracting phenological information from ground vegetation. Atkinson et al…”

Section: Introductionmentioning

confidence: 99%

Spatiotemporal variations of forest phenology in the Qinling Mountains and its response to a critical temperature of 10°C

Zhao

Xue

Quan

et al. 2018

J. Appl. Rem. Sens.

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Abstract. Based on the fifth version MOD09A1 product of NASA LP DAAC (Land Processes Distributed Active Center) from 2001 to 2016, an enhanced vegetation index (EVI) time series dataset in the Qinling Mountains was reconstructed; it was used to extract the plant phenological parameters of the region by employing the maximal slopes of the alteration method and threshold method. The results show that the Whittaker filter method was better than other methods for the reconstruction of shrubland, farmland, and forest in the Qinling Mountains. Based on the reconstructed EVI, the characteristics of vegetation coverage, the start of growth season (SOG), the end of growth season (EOG), and the length of growth season (LOG) in the Qinling Mountains were all analyzed. There was an increasing trend of vegetation coverage in most regions (about 89.93% of the monitored areas) over the Qinling Mountains in the past decades, and the average phenological distribution pattern in the Qinling Mountains was closely related to the local hydrothermal conditions. From the high altitude mountainous areas to the farming areas, the SOG was gradually postponed, the EOG was gradually earlier, and the LOG gradually shortened. Furthermore, the time series variation of SOG, EOG, and LOG from 2001 to 2016 in the Qinling Mountains was also studied. The variation showed that the SOG shifted earlier, which was more prominent in high-altitude areas, while, for some southern and northern foothills altitude below 500 m and a few areas of the eastern Funiu Mountains, the SOG was delayed. The EOG shifted later, which was more apparent in the northern Qinling foothills and mid-to low-altitude areas of the eastern ranges, and the LOG was extended. Finally, the studies of correlation analysis between the plant phenology and a temperature threshold of 10°C showed that global warming was the major factor affecting the phytophenology of the Qinling Mountains, and the effects were concentrated mainly in the 1000-to 2000-m zones of the southern and northern Qinling Mountains. Moreover, the northern Qinling foothills showed a greater response to accumulated temperature than the southern foothills, and the low-altitude area of the eastern Funiu Mountains exhibited the lowest correlation with the accumulated temperature.

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Section: Introductionmentioning

confidence: 99%

Spatiotemporal variations of forest phenology in the Qinling Mountains and its response to a critical temperature of 10°C

Zhao

Xue

Quan

et al. 2018

J. Appl. Rem. Sens.

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“…Although phenological information derived from satellite data, commonly referred to as land surface phenology (LSP) [15,16], is not identical to plant phenology, it is generally considered to be closely related [17][18][19][20]. Phenological metrics, i.e., SOS derived from time series of satellite vegetation indices are therefore used as proxy measures of plant phenology.…”

Section: Introductionmentioning

confidence: 99%

Trends in Spring Phenology of Western European Deciduous Forests

et al. 2013

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Plant phenology is changing because of recent global warming, and this change may precipitate changes in animal distribution (e.g., pests), alter the synchronization between species, and have feedback effects on the climate system through the alteration of biogeochemical and physical processes of vegetated land surface. Here, ground observations (leaf unfolding/first leaf separation of six deciduous tree species) and satellite-derived start-of-growing season (SOS) are used to assess how the timing of leafing/SOS in Western European deciduous forest responded to climate variability between 2001 and 2011 and evaluate the reliability of satellite SOS estimates in tracking the response of forest leafing to climate variability in this area. Satellite SOS estimates are derived from the Normalized Difference Vegetation Index (NDVI) time series of the Moderate Resolution Imaging Spectroradiometer (MODIS). Temporal trends in the SOS are quantified using linear regression, expressing SOS as a function of time. We demonstrated that the growing season was starting earlier between 2001 and 2011 for the majority of temperate deciduous forests in Western Europe, possibly influenced by regional spring warming effects experienced during the same period. A significant shift of up to 3 weeks to early leafing was found in both ground observations and satellite SOS estimates. We also show that the magnitude and trajectory of shifts in satellite SOS estimates are well comparable to that of in situ observations, hence highlighting the importance of satellite imagery in monitoring leaf phenology under a changing climate.

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“…Therefore, time-series data from satellite remote sensing have been widely used for studying vegetation phenology at the landscape, regional and global levels (Myneni et al, 1997;Zhou et al, 2001;Jeong et al, 2011;Sobrino and Julien, 2011), given that there is a strong coincidence between satellite-derived metrics and ground-observed phenological characteristics (Reed et al, 1994). In recent years, several different methods have been developed to convert satellite signals to vegetation phenological phases (Moulin et al, 1997;Myneni et al, 1997;White et al, 2002;Zhang et al, 2003;Jeong et al, 2011;Kross et al, 2011).…”

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Start of vegetation growing season on the Tibetan Plateau inferred from multiple methods based on GIMMS and SPOT NDVI data

Ding

Zhang

et al. 2015

J. Geogr. Sci.

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Abstract:In this study, we have used four methods to investigate the start of the growing season (SGS) on the Tibetan Plateau (TP) from 1982 to 2012, using Normalized Difference Vegetation Index (NDVI) data obtained from Global Inventory Modeling and Mapping Studies (GIMSS, 1982(GIMSS, -2006 and SPOT VEGETATION (SPOT-VGT, 1999. SGS values estimated using the four methods show similar spatial patterns along latitudinal or altitudinal gradients, but with significant variations in the SGS dates. The largest discrepancies are mainly found in the regions with the highest or the lowest vegetation coverage. Between 1982 and 1998, the SGS values derived from the four methods all display an advancing trend, however, according to the more recent SPOT VGT data (1999, there is no continuously advancing trend of SGS on the TP. Analysis of the correlation between the SGS values derived from GIMMS and SPOT between 1999 and 2006 demonstrates consistency in the tendency with regard both to the data sources and to the four analysis methods used. Compared with other methods, the greatest consistency between the in situ data and the SGS values retrieved is obtained with Method 3 (Threshold of NDVI ratio). To avoid error, in a vast region with diverse vegetation types and physical environments, it is critical to know the seasonal change characteristics of the different vegetation types, particularly in areas with sparse grassland or evergreen forest.

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The effect of the temporal resolution of NDVI data on season onset dates and trends across Canadian broadleaf forests

Cited by 77 publications

References 42 publications

Spatiotemporal variations of forest phenology in the Qinling Mountains and its response to a critical temperature of 10°C

Spatiotemporal variations of forest phenology in the Qinling Mountains and its response to a critical temperature of 10°C

Trends in Spring Phenology of Western European Deciduous Forests

Start of vegetation growing season on the Tibetan Plateau inferred from multiple methods based on GIMMS and SPOT NDVI data

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