Characteristics of vegetation phenology over the Alaskan landscape using AVHRR time-series data

Markon, Carl J.; Fleming, Michael D.; Binnian, Emily F.

doi:10.1017/s0032247400013681

Cited by 88 publications

(54 citation statements)

References 38 publications

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“…Some authors use single arbitrary thresholds, e.g. 0.17 (Fischer, 1994), 0.09 (Markon et al, 1995), and 0.099 (Lloyd, 1990), whereas some use threshold specifiers like the long-term average (Karlsen et al, 2006) or % peak amplitude of vegetation indices (Jonsson and Eklundh, 2002).…”

Section: Vegetation Phenologymentioning

confidence: 99%

Relating seasonal dynamics of enhanced vegetation index to the recycling of water in two endorheic river basins in north-west China

Matin

Bourque

2015

Hydrol. Earth Syst. Sci.

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Abstract. This study associates the dynamics of enhanced vegetation index in lowland desert oases to the recycling of water in two endorheic (hydrologically closed) river basins in Gansu Province, north-west China, along a gradient of elevation zones and land cover types. Each river basin was subdivided into four elevation zones representative of (i) oasis plains and foothills, and (ii) low-, (iii) mid-, and (iv) highmountain elevations. Comparison of monthly vegetation phenology with precipitation and snowmelt dynamics within the same basins over a 10-year period (2000)(2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009) suggested that the onset of the precipitation season (cumulative % precipitation > 7-8 %) in the mountains, typically in late April to early May, was triggered by the greening of vegetation and increased production of water vapour at the base of the mountains. Seasonal evolution of in-mountain precipitation correlated fairly well with the temporal variation in oasisvegetation coverage and phenology characterised by monthly enhanced vegetation index, yielding coefficients of determination of 0.65 and 0.85 for the two basins. Convergent cross-mapping of related time series indicated bi-directional causality (feedback) between the two variables. Comparisons between same-zone monthly precipitation amounts and enhanced vegetation index provided weaker correlations. Start of the growing season in the oases was shown to coincide with favourable spring warming and discharge of meltwater from low-to mid-elevations of the Qilian Mountains (zones 1 and 2) in mid-to-late March. In terms of plant requirement for water, mid-seasonal development of oasis vegetation was seen to be controlled to a greater extent by the production of rain in the mountains. Comparison of water volumes associated with in-basin production of rainfall and snowmelt with that associated with evaporation seemed to suggest that about 90 % of the available liquid water (i.e. mostly in the form of direct rainfall and snowmelt in the mountains) was recycled locally.

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Section: Vegetation Phenologymentioning

confidence: 99%

Relating seasonal dynamics of enhanced vegetation index to the recycling of water in two endorheic river basins in north-west China

Matin

Bourque

2015

Hydrol. Earth Syst. Sci.

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“…NDVI integrates the composition of species within the plant community, vegetation form, vigour, and structure, the vegetation density in vertical and horizontal directions, reflection, absorption, and transmission within and on the surface of the vegetation or ground, and the reflection, absorption, and transmission by the atmosphere, clouds, and atmospheric contaminants (Markon et al 1995). The ability of NDVI to monitor variations in primary productivity can, however, be negatively affected (Markon & Peterson 2002).…”

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confidence: 99%

The Normalized Difference Vegetation Index (NDVI): unforeseen successes in animal ecology

Pettorelli¹,

Ryan²,

Mueller³

et al. 2011

Clim. Res.

621

508

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This review highlights the latest developments associated with the use of the Normalized Difference Vegetation Index (NDVI) in ecology. Over the last decade, the NDVI has proven extremely useful in predicting herbivore and non-herbivore distribution, abundance and life history traits in space and time. Due to the continuous nature of NDVI since mid-1981, the relative importance of different temporal and spatial lags on population performance can be assessed, widening our understanding of population dynamics. Previously thought to be most useful in temperate environments, the utility of this satellite-derived index has been demonstrated even in sparsely vegetated areas. Climate models can be used to reconstruct historical patterns in vegetation dynamics in addition to anticipating the effects of future environmental change on biodiversity. NDVI has thus been established as a crucial tool for assessing past and future population and biodiversity consequences of change in climate, vegetation phenology and primary productivity.

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“…As NDVI values can be affected by several site-and land cover-specific factors (Pinter et al 1985;Markon et al 1995;Thomas 1997;Mbow et al 2013), different locations with the same NDVI value are not necessarily have the same biomass productivity. Thus, comparison of biomass productivity between pixels using NDVI is a pitfall that should be avoided (Pettorelli et al 2005).…”

Section: Literature Reviewmentioning

confidence: 99%

Biomass Productivity-Based Mapping of Global Land Degradation Hotspots

Nkonya

Mirzabaev

2014

SSRN Journal

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CitationLe Abstract Land degradation affects negatively the livelihoods and food security of global population. There have been recurring efforts by the international community to identify the global extent and severity of land degradation. Using the long-term trend of biomass productivity as a proxy of land degradation at global scale, we identify the degradation hotspots in the world across major land cover types. We correct factors confounding the relationship between the remotely sensed vegetation index and land-based biomass productivity, including the effects of inter-annual rainfall variation, atmospheric fertilization and intensive use of chemical fertilizers. Our findings show that land degradation hotpots cover about 29 % of global land area and are happening in all agro-ecologies and land cover types. This figure does not include all areas of degraded lands, it refers to areas where land degradation is most acute and requires priority actions in both in-depth research and management measures to combat land degradation. About 3.2 billion people reside in these degrading areas. However, the number of people affected by land degradation is likely to be higher as more people depend on the continuous flow of ecosystem goods and services from these affected areas. Land improvement has occurred in about 2.7 % of global land area during the last three decades, suggesting that with appropriate actions land degradation trend could be reversed. We also identify concrete aspects in which these results should be interpreted with cautions, the limitations of this work and the key areas for future research. (Oldeman et al. 1990;USDA-NRCS 1998;Eswaran et al. 2001). The earlier generation of these studies had been constrained by lack of global level quantitative data which could be used for mapping soil and land degradation, and therefore were based on expert opinions. The developments in the remote sensing and satellite technologies allowed the later studies to be based on quantitative satellite data, such as Global Inventory Modelling and Mapping Studies (GIMMS) dataset of 64 km 2 -resolution of Normalized Difference Vegetation Index (NDVI) data, however, several methodological challenges still exist on more accurately estimating the land degradation hotspots (Vlek et al. 2010;Le et al. 2012).In this context, addressing land degradation may require channeling substantial amounts of scarce resources and making long-term investments. These investments are likely to yield high levels of social returns and welfare improvements. However, all countries in the world have budgetary constraints, necessitating the prioritization of such investments. To combat land degradation, both on the international and national levels, policy makers often need information about areas of severe degradation in order to prioritize national budgets and plan strategic interventions (Vlek et al. 2010;Vogt et al. 2011;Le et al. 2012). To achieve this, accurate maps of land degradation hotspots-where land degradation is most acute, are needed. T...

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Characteristics of vegetation phenology over the Alaskan landscape using AVHRR time-series data

Cited by 88 publications

References 38 publications

Relating seasonal dynamics of enhanced vegetation index to the recycling of water in two endorheic river basins in north-west China

Relating seasonal dynamics of enhanced vegetation index to the recycling of water in two endorheic river basins in north-west China

The Normalized Difference Vegetation Index (NDVI): unforeseen successes in animal ecology

Biomass Productivity-Based Mapping of Global Land Degradation Hotspots

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