Landsat MSS-derived land-cover map of northern Alaska: Extrapolation methods and a comparison with photo-interpreted and AVHRR-derived maps

Müller, Sven; Racoviteanu, A.; Walker, Donald A.

doi:10.1080/014311699211543

Cited by 91 publications

(102 citation statements)

References 30 publications

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“…Past studies have mapped vegetation changes at high northern latitudes using aerial photography [2], coarse-scale satellite imagery such as that from the Advanced Very High Resolution Radiometer (AVHRR) [3], and moderate-scale satellite imagery such as that from Landsat platforms [4,5]. The Normalized Difference Vegetation Index (NDVI), a remotely sensed indicator of photosynthetic capacity [6], is one of the most commonly used spectral vegetation indices (SVIs), and is widely available from satellite sensors, such as the AVHRR, the Moderate-Resolution Imaging Spectroradiometer (MODIS), and the various Landsat sensors that capture spectral information in a few broad spectral bands.…”

Section: Introductionmentioning

confidence: 99%

“…The North Slope of Alaska extends from the Brooks Mountain Range to the Arctic Ocean [45] and is largely dominated by either moist acidic tundra (MAT) or moist nonacidic tundra (MNT) [5]. Soil acidity differentiates MAT from MNT communities, with MAT occurring on soils with pH < 5.0-5.5, and MNT occurring on soils with pH ě 5.0-5.5 [16,46].…”

Section: Vegetation Types Throughout the North Slope Of Alaskamentioning

confidence: 99%

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Differentiating among Four Arctic Tundra Plant Communities at Ivotuk, Alaska Using Field Spectroscopy

et al. 2016

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Warming in the Arctic has resulted in changes in the distribution and composition of vegetation communities. Many of these changes are occurring at fine spatial scales and at the level of individual species. Broad-band, coarse-scale remote sensing methods are commonly used to assess vegetation changes in the Arctic, and may not be appropriate for detecting these fine-scale changes; however, the use of hyperspectral, high resolution data for assessing vegetation dynamics remains scarce. The aim of this paper is to assess the ability of field spectroscopy to differentiate among four vegetation communities in the Low Arctic of Alaska. Primary data were collected from the North Slope site of Ivotuk, Alaska (68.49˝N, 155.74˝W) and analyzed using spectrally resampled hyperspectral narrowbands (HNBs). A two-step sparse partial least squares (SPLS) and linear discriminant analysis (LDA) was used for community separation. Results from Ivotuk were then used to predict community membership at five other sites along the Dalton Highway in Arctic Alaska. Overall classification accuracy at Ivotuk ranged from 84%-94% and from 55%-91% for the Dalton Highway test sites. The results of this study suggest that hyperspectral data acquired at the field level, along with the SPLS and LDA methodology, can be used to successfully discriminate among Arctic tundra vegetation communities in Alaska, and present an improvement over broad-band, coarse-scale methods for community classification.

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Section: Introductionmentioning

confidence: 99%

Section: Vegetation Types Throughout the North Slope Of Alaskamentioning

confidence: 99%

Differentiating among Four Arctic Tundra Plant Communities at Ivotuk, Alaska Using Field Spectroscopy

et al. 2016

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“…Therefore, we decided to generate our own dataset of recent and high-resolution land cover using high-resolution multispectral data of the Landsat-7 ETM+ sensor for our study area. Within the last 15 years, some studies on land cover classifications utilizing Landsat remote sensing data with different thematic focus have been conducted in Alaska and Canada (Ferguson, 1991;Gross et al, 1990;Joria & Jorgenson, 1996;Muller et al, 1999;Stow et al, 1998;Brook & Kenkel, 2002). Land cover classifications of Arctic areas in Russia are rare and most of them have been accomplished within the last years (Rees et al, 2003;Takeuchi et al, 2003;Virtanen et al, 2004;Grosse et al, 2006).…”

Section: Introductionmentioning

confidence: 99%

Land cover classification of tundra environments in the Arctic Lena Delta based on Landsat 7 ETM+ data and its application for upscaling of methane emissions

Schneider

Grosse

Wagner

2009

Remote Sensing of Environment

144

154

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The Lena River Delta, situated in Northern , is the largest Arctic delta and covers 29,000 km 2 . Since natural deltas are characterised by complex geomorphological patterns and various types of ecosystems, high spatial resolution information on the distribution and extent of the delta environments is necessary for a spatial assessment and accurate quantification of biogeochemical processes as drivers for the emission of greenhouse gases from tundra soils. In this study, the first land cover classification for the entire Lena Delta based on Landsat 7 Enhanced Thematic Mapper (ETM+) images was conducted and used for the quantification of methane emissions from the delta ecosystems on the regional scale. Nine land cover classes of aquatic and terrestrial ecosystems in the wetland dominated (72%) Lena Delta could be defined by this classification approach. The mean daily methane emission of the entire Lena Delta was calculated with 10.35 mg CH 4 m. Taking our multi-scale approach into account we find that the methane source strength of certain tundra wetland types is lower than calculated previously on coarser scales.

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“…Meteorological records from north-western Canada also indicate that these predicted temperature and precipitation changes might already be occurring [4]. Although it is known that vegetation ecosystems in northern high latitudes are sensitive to global changes, how they will respond remains unclear [5][6][7].…”

Section: Introductionmentioning

confidence: 99%

AVHRR NDVI Baseline for Natural Vegetation Ecosystems in Northern Canadian National Parks

He¹,

Dixon²,

Wilmshurst³

et al. 2012

J Geophys Remote Sensing

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The establishment of a set of vegetation baseline values for the sub-arctic protected ecosystems would permit the identification of ecosystem change in the context of global change. A common satellite-based index, the Normalized Difference Vegetation Index (NDVI), has a long history of use and can be averaged to establish a "normal" vegetation condition in a given region for a given time. Based on an analysis of 23-year NDVI time series data derived from the Advanced Very High Resolution Radiometer (AVHRR) satellite imagery, this study investigated a simple method to establish a set of NDVI baseline for the sub-arctic natural ecosystems in the 12 Canadian northern National Parks. The key result of this study is that a set of annual and monthly NDVI baseline for each area of interest has been established. The NDVI baseline was further compared to a warm and a cool year to assess vegetation conditions. Comparison results indicated better vegetation conditions in warm years and worse vegetation conditions in cool year. The different deviation patterns over the years occurred in different parks, probably as the result of regional climatic properties, vegetation types, and elevations. The implication of this study is that newly-acquired NDVI values can be compared to this established baseline, both in a temporal and spatial dimension, to allow policy maker, land managers and other sub-arctic researchers to gauge the current conditions against those of previous years.

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Landsat MSS-derived land-cover map of northern Alaska: Extrapolation methods and a comparison with photo-interpreted and AVHRR-derived maps

Cited by 91 publications

References 30 publications

Differentiating among Four Arctic Tundra Plant Communities at Ivotuk, Alaska Using Field Spectroscopy

Differentiating among Four Arctic Tundra Plant Communities at Ivotuk, Alaska Using Field Spectroscopy

Land cover classification of tundra environments in the Arctic Lena Delta based on Landsat 7 ETM+ data and its application for upscaling of methane emissions

AVHRR NDVI Baseline for Natural Vegetation Ecosystems in Northern Canadian National Parks

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