Linking vegetation heterogeneity and functional attributes of temperate grasslands through remote sensing

doi:10.3170/2007-7-18429

Cited by 2 publications

(2 citation statements)

References 42 publications

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“…fAPAR and RUE remained relatively stable throughout the year at the seasonal scale (Figure 2). The fAPAR pattern contrasts with that of other systems, like the Flooding Pampa grasslands where fAPAR is much greater in spring than in winter (Aragon & Oesterheld, 2008;Posse, Oesterheld, & Di Bella, 2005). This difference may be due to two causes.…”

Section: Fapar and Rue Explaining Changes In Forage Productivitymentioning

confidence: 81%

Variability of radiation use efficiency in mixed pastures under varying resource availability, defoliation and time scale

Grigera

Oesterheld

2020

Grassland Science

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Forage productivity is the product between incident radiation, the fraction of radiation absorbed by the canopy (fAPAR) and radiation use efficiency (RUE). The extent to which forage productivity may be estimated through remote sensing depends on the relative effects of stress and defoliation on fAPAR and RUE. In a mixed pasture, we determined the relative impact of resource availability and defoliation on forage productivity, fAPAR and RUE, and we evaluated the impact of time scale on fAPAR and RUE under stress conditions. We conducted a one‐year experiment in a temperate‐mixed pasture subjected to different resource availability treatments and defoliation management. We measured RUE and fAPAR with different temporal windows. RUE was less responsive than fAPAR to changes in resource availability and defoliation intensity. However, RUE slightly decreased under water stress and increased under severe defoliation. Additionally, RUE variability during regrowth and among treatments depended on the temporal scale of observation: RUE was more variable for 12‐day periods than 45‐ or 90‐day periods. Our results reinforce the value of fAPAR as an explanatory variable of the variations in forage productivity due to changes in resource availability and management. In addition, the temporal scale of observation affects RUE variability. Thus, most variations of forage productivity may be captured by monitoring systems based on remote sensing of fAPAR provided that the time scale is coarse enough. However, the contrasting response of RUE and fAPAR to defoliation indicates a potential weakness of such a system when situations with contrasting defoliation regime are compared.

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Section: Fapar and Rue Explaining Changes In Forage Productivitymentioning

confidence: 81%

Variability of radiation use efficiency in mixed pastures under varying resource availability, defoliation and time scale

Grigera

Oesterheld

2020

Grassland Science

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“…Extensive vegetation surveys allow the combination of floristically defined plant communities with satellite data in order to map spatial distribution of vegetation [15][16] . Over smaller extents, airborne sensors have been used successfully for the mapping of floristically defined vegetation units [17][18][19] .…”

Section: Introductionmentioning

confidence: 99%

Geospatial mapping of vegetation in the Antarctic environment using very high-resolution WorldView-2 imagery

2016

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A robust monitoring of the changes in the distribution and density of cryospheric plant species requires accurate and high-resolution baseline maps of vegetation. Mapping such change at the landscape scale is often problematic, particularly in remote areas, such as Antarctica. Vegetation mapping of plant communities at fine spatial scales is increasingly supported by remote sensing technology in cryospheric regions. Less frequent imaging with high spatial resolution satellite sensors enable more detailed analyses of vegetation change frequently. This study is the first to use high-resolution WorldView-2 (WV-2) imagery to classify vegetation communities on Antarctic oases and to provide semi-automated means to map vegetation, as an imperative indicator for environmental change. Multispectral imagery (MSI) and panchromatic imagery (PAN) from very high resolution WV-2 have been used for mapping of vegetation in different forms in Antarctic environment. A range of supervised classification methods have been executed using pansharpened WV-2 data. This study comparatively and statistically evaluates vegetation mapping results using supervised and unsupervised classification methods to extract vegetation in Larsemann Hills and Schirmacher oasis, east Antarctica. We also discuss on the use of supervised pixel-based classifiers and textural measures, in addition to standard multispectral information, to improve the classification of Antarctic vegetation communities. Classification results were validated with independent reference datasets. This work indicates that the overall accuracy of mapping vegetation using WV-2 imagery and semiautomated target extraction methods ranged from 90% to 94%.

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Linking vegetation heterogeneity and functional attributes of temperate grasslands through remote sensing

Cited by 2 publications

References 42 publications

Variability of radiation use efficiency in mixed pastures under varying resource availability, defoliation and time scale

Variability of radiation use efficiency in mixed pastures under varying resource availability, defoliation and time scale

Geospatial mapping of vegetation in the Antarctic environment using very high-resolution WorldView-2 imagery

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