The Influence of Vegetation Index and Spatial Resolution on a Two-Date Remote Sensing-Derived Relation to C4 Species Coverage

Davidson, Andrew; Csillag, Ferenc

doi:10.1016/s0034-4257(00)00162-0

Cited by 67 publications

(45 citation statements)

References 36 publications

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“…Each region may be deemed a mosaic, where vegetation types are found at scales ranging from 100 m to 1 km, while microsite variations (e.g., changes in relief due to hummocks and frost action in tussock tundra) may occur within centimetres to metres (McFadden et al, 1998). Second, small-scale vegetation studies may be ideal, but the harsh Arctic climate and the remote nature of field sites do not always render such studies feasible Jacobsen and Hansen, 1999), nor are they necessarily useful in extrapolating to broader expanses of land (Dungan, 1998;Lobo et al, 1998;Ostendorf and Reynolds, 1998;Davidson and Csillag, 2001). Remote sensing provides the potential to characterize surface variables that control carbon fluxes over landscapes (i.e., 100 m 2 to 100 km 2 ) or regions (i.e., > 100 km 2 ) (Hope et al, 1995).…”

Section: Introductionmentioning

confidence: 99%

Remote Sensing of Arctic Vegetation: Relations between the NDVI, Spatial Resolution and Vegetation Cover on Boothia Peninsula, Nunavut

Laidler¹,

Treitz²,

Atkinson³

2009

ARCTIC

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ABSTRACT. Arctic tundra environments are thought to be particularly sensitive to changes in climate, whereby alterations in ecosystem functioning are likely to be expressed through shifts in vegetation phenology, species composition, and net ecosystem productivity (NEP). Remote sensing has shown potential as a tool to quantify and monitor biophysical variables over space and through time. This study explores the relationship between the normalized difference vegetation index (NDVI) and percent-vegetation cover in a tundra environment, where variations in soil moisture, exposed soil, and gravel till have significant influence on spectral response, and hence, on the characterization of vegetation communities. IKONOS multispectral data (4 m spatial resolution) and Landsat 7 ETM+ data (30 m spatial resolution) were collected for a study area in the Lord Lindsay River watershed on Boothia Peninsula, Nunavut. In conjunction with image acquisition, percent cover data were collected for twelve 100 m × 100 m study plots to determine vegetation community composition. Strong correlations were found for NDVI values calculated with surface and satellite sensors, across the sample plots. In addition, results suggest that percent cover is highly correlated with the NDVI, thereby indicating strong potential for modeling percent cover variations over the region. These percent cover variations are closely related to moisture regime, particularly in areas of high moisture (e.g., water-tracks). These results are important given that improved mapping of Arctic vegetation and associated biophysical variables is needed to monitor environmental change.Key words: tundra, biophysical remote sensing, vegetation indices, NDVI, percent cover, Landsat 7 ETM+, IKONOS, Boothia Peninsula, Canadian Arctic RÉSUMÉ. On croit que les environnements de la toundra arctique sont particulièrement sensibles aux changements climatiques, en ce sens que toute altération du fonctionnement de l'écosystème est susceptible d'être exprimée dans le réarrangement de la phénologie de la végétation, de la composition des espèces et de la productivité nette de l'écosystème (PNÉ). La télédétection s'avère un outil efficace de quantification et de surveillance des variables biophysiques dans le temps et dans l'espace. Cette étude explore la relation entre l'indice d'activité végétale et le pourcentage de couverture végétale en milieu de toundra, où les variations propres à l'humidité du sol, au sol exposé et au till de gravier ont une influence considérable sur la réponse spectrale et, par conséquent, sur la caractérisation des communautés végétales.

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Section: Introductionmentioning

confidence: 99%

Remote Sensing of Arctic Vegetation: Relations between the NDVI, Spatial Resolution and Vegetation Cover on Boothia Peninsula, Nunavut

Laidler¹,

Treitz²,

Atkinson³

2009

ARCTIC

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“…Field investigations are usually limited to short-term, plot scale studies that lack both the temporal and spatial coverage needed to characterize grass dynamics directly in a comprehensive manner. Recently, this data deficit has been addressed through remote sensing methods to quantify grass cover in space and time [16,46,47]. Observations from satellite data, in fact, motivated the present analysis and are used to characterize vegetation cover for the regional-scale land surface hydrological model presented herein.…”

Section: Introductionmentioning

confidence: 99%

Dynamic response of grass cover to rainfall variability: implications for the function and persistence of savanna ecosystems

Scanlon

Caylor

Manfreda

et al. 2005

Advances in Water Resources

110

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“…Depending on the objective and scale of the research, both ground-based radiometers and satellite imagery have been widely utilized within grassland research to estimate plant biophysical parameters such as ALB (Davidson and Csillag 2001;Flombaum and Sala 2007). Typically, ALB is estimated by establishing an empirical relationship between the destructively measured biomass and the transformations of 2 or more remotely sensed spectral bands.…”

Section: Alb Estimationmentioning

confidence: 99%

Effect of Different Grazing Intensities on the Spatial-Temporal Variability in Above-Ground Live Plant Biomass in North American Mixed Grasslands

Virk

Mitchell

2014

Canadian Journal of Remote Sensing

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Areas with relatively high spatial heterogeneity generally have more biodiversity than those that are spatially homogeneous areas due to increased potential as habitat. Management practices such as controlled grazing also affect the biodiversity in grasslands, and we hypothesize that this is due in part to the impacts of variation in grazing on plant heterogeneity and its spatial patterns. Understanding these mechanisms is important for designing an effective grazing system from a livestock management point of view. We used satellite-based, above-ground, live plant biomass (ALB) estimates at a pasture scale, in an experimental area located across the border of the East Block of Grasslands National Park (GNP) and an adjacent community pasture, to assess the effects of 5 intensities of grazing on the spatiotemporal pattern of ALB in mixed grasslands. Overall, heterogeneity increased with grazing intensity, whereas the spatial range decreased, except at the highest intensity, which had no impact on heterogeneity. Résumé. Les zonesà relativement forte hétérogénéité spatiale ont généralement une plus grande biodiversité que les zones spatialement homogènes en raison de l'habitat potentiel accru. Les pratiques de gestion telles que le pâturage contrôlé influencent egalement la biodiversité dans les prairies. Nousémettons l'hypothèse que cela est dû en partieà l'impact des variations du pâturage sur l'hétérogénéité de la végétation et ses structures spatiales. La compréhension de ces mécanismes est importantepour la conception d'un système de pâturage efficace d'un point de vue de la gestion du bétail. Nous avons utilisé des estimations satellitaires de la biomasse végétale vivante aérienneà l'échelle du pâturage dans une zone expérimentale situéeà la frontière du bloc Est du parc national des Prairies «GNP» et un pâturage communautaire adjacent pourévaluer les effets de 5 intensités de pâturage sur la structure spatio-temporelle de la biomasse végétale vivante aérienne dans les prairies mixtes. Dans l'ensemble, l'hétérogénéité a augmenté avec l'intensité du pâturage tandis que la portée spatiale a diminué, saufà la plus haute intensité qui n'a eu aucune incidence sur l'hétérogénéité.

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The Influence of Vegetation Index and Spatial Resolution on a Two-Date Remote Sensing-Derived Relation to C4 Species Coverage

Cited by 67 publications

References 36 publications

Remote Sensing of Arctic Vegetation: Relations between the NDVI, Spatial Resolution and Vegetation Cover on Boothia Peninsula, Nunavut

Remote Sensing of Arctic Vegetation: Relations between the NDVI, Spatial Resolution and Vegetation Cover on Boothia Peninsula, Nunavut

Dynamic response of grass cover to rainfall variability: implications for the function and persistence of savanna ecosystems

Effect of Different Grazing Intensities on the Spatial-Temporal Variability in Above-Ground Live Plant Biomass in North American Mixed Grasslands

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