Similarities in ground- and satellite-based NDVI time series and their relationship to physiological activity of a Scots pine forest in Finland

Wang, Quan; Tenhunen, John; Dinh, Nguyen Quoc; Reichstein, Markus; Vesala, Timo; Keronen, Petri

doi:10.1016/j.rse.2004.07.006

Cited by 125 publications

(86 citation statements)

References 47 publications

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“…This latter conclusion matches the observations of other researchers based on the comparison of NDVI and NEE data (e.g. Wang et al, 2004;Nagy et al, 2007).…”

Section: Dependence Of Nee On Leaf Areasupporting

confidence: 93%

“…The extent of linear relation is slightly stronger in the grazed grassland which indicates the adaptation of the vegetation to the pressure of extensive grazing. Further accordance can be found in the two types: the correlation between NEE and LAI is the strongest in the wet year as well as if not including data from drought stressed or autumn regrowth periods when vegetation was less active then during intensive growth (Wang et al, 2004). This latter conclusion matches the observations of other researchers based on the comparison of NDVI and NEE data (e.g.…”

Section: Dependence Of Nee On Leaf Areasupporting

confidence: 89%

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Dependence of Co2 Flux on the Key Abiotic and Biotic Parameters in Semi-Natural Grasslands Either Traditionally Grazed or Excluded From Grazing

Czóbel¹

2017

Appl Ecol Env Res

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Abstract. Traditional farming has been ceased in large areas regarding several Central-European countries during the last decades. Nevertheless, only minimal knowledge is available about the impacts of these land use changes on the fluxes of grasslands. Within the framework of this research the dependence of stand level CO 2 flux (NEE) on temperature, light (PPFD), leaf area (LAI), evapotranspiration and soil moisture has been examined in a dry sandy pasture grazed by grey cattle for decades. The examinations have been completed both in a grazed area and in a 6 hectare patch excluded from grazing. Measurements have been taken for 3 years during the vegetation periods in the area of the Kiskunság National Park by a mobile Plexiglas chamber as well as infrared gas analysers. Among the examined abiotic and biotic parameters the dependence of NEE on PPFD and LAI has been significant in both areas. Exponential and linear correlation turned out to be the strongest in both grassland types between CO 2 fixation and light dependence and CO 2 fixation and leaf area, respectively. The strongest correlation has been observed between the PPFD and NEE in both types of grassland. The dependence of CO 2 flux on light and leaf area has been stronger in the extensively grazed area compared to the other examined grass excluded from grazing. Based on this fact it can be assumed that the conversion of land use in traditionally grazed grasslands has negative influence on the relation among NEE and the key abiotic and biotic parameters. It can be explained, beside the accumulation of litter, by the altered vegetation dynamic processes. Extreme dry periods effect, in a negative way, the dependence of CO 2 flux on temperature, soil moisture and evapotranspiration. It calls the attention to the impacts of weather extremities on the mechanisms in seminatural sandy grasslands.

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“…This latter conclusion matches the observations of other researchers based on the comparison of NDVI and NEE data (e.g. Wang et al, 2004;Nagy et al, 2007).…”

Section: Dependence Of Nee On Leaf Areasupporting

confidence: 93%

Section: Dependence Of Nee On Leaf Areasupporting

confidence: 89%

Dependence of Co2 Flux on the Key Abiotic and Biotic Parameters in Semi-Natural Grasslands Either Traditionally Grazed or Excluded From Grazing

Czóbel¹

2017

Appl Ecol Env Res

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“…Numerous studies have employed similar methods linking NDVI time series with flux tower measurements [9,44]; however, there is currently very limited research published on the use of satellite-derived PRI for estimating phenology.…”

Section: Discussionmentioning

confidence: 99%

“…In accordance with previous studies [10,44], the single pixel centered on the tower was assessed to be representative of the tower footprint.…”

Section: Flux Tower Datamentioning

confidence: 99%

“…The surrounding terrain is dominated by Scots pine (Pinus sylvestris) planted in 1962 [43]. The forest area is homogenous with less than 10% of the canopy made up of other species within 200 m of the flux tower [44]. The flux tower at the site is equipped with instrumentation to measure several gas concentrations, atmosphere-biosphere exchange of energy and matter and meteorological parameters since 1996.…”

Section: Study Sitementioning

confidence: 99%

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Detecting Inter-Annual Variations in the Phenology of Evergreen Conifers Using Long-Term MODIS Vegetation Index Time Series

et al. 2017

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Long-term observations of vegetation phenology can be used to monitor the response of terrestrial ecosystems to climate change. Satellite remote sensing provides the most efficient means to observe phenological events through time series analysis of vegetation indices such as the Normalized Difference Vegetation Index (NDVI). This study investigates the potential of a Photochemical Reflectance Index (PRI), which has been linked to vegetation light use efficiency, to improve the accuracy of MODIS-based estimates of phenology in an evergreen conifer forest. Timings of the start and end of the growing season (SGS and EGS) were derived from a 13-year-long time series of PRI and NDVI based on a MAIAC (multi-angle implementation of atmospheric correction) processed MODIS dataset and standard MODIS NDVI product data. The derived dates were validated with phenology estimates from ground-based flux tower measurements of ecosystem productivity. Significant correlations were found between the MAIAC time series and ground-estimated SGS (R 2 = 0.36-0.8), which is remarkable since previous studies have found it difficult to observe inter-annual phenological variations in evergreen vegetation from satellite data. The considerably noisier NDVI product could not accurately predict SGS, and EGS could not be derived successfully from any of the time series. While the strongest relationship overall was found between SGS derived from the ground data and PRI, MAIAC NDVI exhibited high correlations with SGS more consistently (R 2 > 0.6 in all cases). The results suggest that PRI can serve as an effective indicator of spring seasonal transitions, however, additional work is necessary to confirm the relationships observed and to further explore the usefulness of MODIS PRI for detecting phenology.

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Simple regression models to estimate light interception in wheat crops with Sentinel‐2 and a handheld sensor

et al. 2020

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Capture of radiation by crop canopies drives growth rate, grain set, and yield. Since the fraction of photosynthetically active radiation absorbed by green area (fAPAR g ) correlates with normalized difference vegetation index (NDVI), remote sensors have been used to monitor vegetation. With a 10-m spatial resolution and 5-d revisiting time, the recently launched Sentinel-2 satellite is a promising tool for fAPAR g monitoring. However, the available algorithm to estimate fAPAR g is based on simulations of canopy interception of several vegetation types and was never tested in field crops. Handheld sensors, such as GreenSeeker, are another alternative to estimate fAPAR g . Our objectives were (a) to test the ability of indices derived from Sentinel-2 and GreenSeeker NDVI to capture fAPAR g of wheat (Triticum aestivum L.) crops, (b) to compare these sensors' performance against the moderate resolution imaging spectroradiometer (MODIS), and (c) to compare our Sentinel-2 model estimations with the available algorithm. In wheat fields in the southwest Argentinean Pampas, on several sampling dates, we measured fAPAR g with a quantum light sensor and NDVI with a GreenSeeker. We regressed fAPAR g measurements with vegetation indices from the different sources and selected the best models. Sentinel-2 and GreenSeeker NDVI precisely estimated fAPAR g , with a performance similar to MODIS (p < .05; RMSD = 0.09, 0.11, and 0.08; R 2 = .89, .88, and .95, respectively). The available algorithm to estimate fAPAR g with Sentinel-2 yielded biased estimations, mainly in the lower range of fAPAR g . These results suggest that simple models may provide fAPAR g estimations with Sentinel-2 and GreenSeeker in wheat crops with an accuracy suitable for agricultural applications.Abbreviations: fAPAR g , fraction of photosynthetically active radiation absorbed by green area; MODIS, moderate resolution imaging spectroradiometer; mSR, modified simple ratio; mSR2, modified simple ratio 2; ND705, red-edge normalized difference; NDVI, normalized difference vegetation index; NIR, near-infrared; PAR, photosynthetically active radiation; WDRVI, wide dynamic range vegetation index.

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Similarities in ground- and satellite-based NDVI time series and their relationship to physiological activity of a Scots pine forest in Finland

Cited by 125 publications

References 47 publications

Dependence of Co2 Flux on the Key Abiotic and Biotic Parameters in Semi-Natural Grasslands Either Traditionally Grazed or Excluded From Grazing

Dependence of Co2 Flux on the Key Abiotic and Biotic Parameters in Semi-Natural Grasslands Either Traditionally Grazed or Excluded From Grazing

Detecting Inter-Annual Variations in the Phenology of Evergreen Conifers Using Long-Term MODIS Vegetation Index Time Series

Simple regression models to estimate light interception in wheat crops with Sentinel‐2 and a handheld sensor

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