Abstract
The analysis of a series of five normalized difference vegetation index (NDVI) images produced information about a Labrador (Canada) portion of the tundra-taiga interface. The twenty-five year observation period ranges from 1983 to 2008. The series composed of Landsat, SPOT and ASTER images, provided insight into regional scale characteristics of the tundra-taiga interface that is usually monitored from coarse resolution images. The image set was analyzed by considering an ordinal classification of the NDVI to account for the cumulative effect of differences of near-infrared spectral resolutions, the temperature anomalies, and atmospheric conditions. An increasing trend of the median values in the low, intermediate and high NDVI classes is clearly marked while accounting for variations attributed to cross-sensor radiometry, phenology and atmospheric disturbances. An encroachment of the forest on the tundra for the whole study area was estimated at 0 to 60 m, depending on the period of observation, as calculated by the difference between the median retreat and advance of an estimated location of the tree line. In small sections, advances and retreats of up to 320 m are reported for the most recent four- and seven-year periods of observations.
Highlights
Background and RationaleVegetation cover mapping and monitoring are essential components of knowledge acquisition on the impact of climate changes on Arctic tundra ecosystems [1], part of which is the tundra-taiga interface (TTI), or tree line
This paper presents the changes observed in a TTI from a multisensor Normalized Difference Vegetation Index (NDVI) series
This paper presents evidence that the green biomass, represented by the Normalized Difference
Summary
Vegetation cover mapping and monitoring are essential components of knowledge acquisition on the impact of climate changes on Arctic tundra ecosystems [1], part of which is the tundra-taiga interface (TTI), or tree line. Satellite and airborne Normalized Difference Vegetation Index (NDVI) images provide green biomass distribution information in proximity to, and north of, the tree line [2,3,4,5,6]. Vegetation indices and thermal images are valuable inputs to climate change-related atmosphere constituent and air-temperature models [9,10,11,12,13,14,15]. Baseline vegetation maps must consider variable scales, or spatial resolutions, in order to benefit from multi-disciplinary data integration that helps better understand ecosystems.
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