Toward a new arctic vegetation map: a review of existing maps

Walker, Donald A.; Bay, Christian; Daniëls, Fred J.A.; Einarsson, Eyþór; Elvebakk, Arve; Johansen, Bernt; Kapitsa, A. P.; Kholod, S.S.; Murray, David F.; Talbot, Stephen S.; Yurtsev, B. A.; Zoltai, S. C.

doi:10.2307/3236242

Cited by 20 publications

(13 citation statements)

References 27 publications

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“…The problem with the validity of character species and the poor extrapolation power of local syntaxonomic hierarchies call for more flexibility in choosing classification criteria. The pragmatists argue for more flexibility by choosing classification of the USA and the Vegetation classification of Canada (both in progress), the Arctic vegetation map (Walker et al 1995), the Vegetation map of South Africa (Low & Rebelo 1996) and many others are direct answers to these needs. The expected progress of these and other initiatives envisage a great contribution to normalization of concepts, sampling standards, data storage and presentation of results of vegetation classifications.…”

Section: Pragmatismmentioning

confidence: 99%

Classification of vegetation: Past, present and future

Mucina

1997

J Vegetation Science

130

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This paper is a report on the past, status-quo and perspectives of vegetation classification, still a major occupation of many vegetation scientists. The history of vegetation classification is discussed against a background of several controversial issues such as the problem of continuum vs. discontinuum, naturalness vs. arbitrariness of the nature of plant communities, universality vs. ad hoc character of syntaxonomic schemes, as well as classical versus numerical approaches to data analysis for classification purposes.The development of the methodology of vegetation science and the present image of vegetation classification is documented by a bibliometric analysis of the publication record of four major journals: Journal of Vegetation Science, Vegetatio, Phytocoenologia and Tuexenia. This analysis revealed a persisting controversy between traditional and numerical approaches to vegetation classification. A series of important changes in vegetation science (foundation of new journals, change of editorial policy by the established, important meetings) punctuate a period called the 'Innovation period'.Several trends in the development of methods of vegetation systematics are summarized under the headings formalism, pluralism, functionalism, pragmatism and indeterminism. Some new features, such as the development and improvement of numerical tools, use of large data banks and attempts to summarize the theory of vegetation classification are discussed. The new growth-form system of Barkman initiated a revival of physiognomy-based vegetation classification. Within this framework the use of the character-type concept and the development of new numerical methods for studying the hierarchical structure of character-set types seems to be a promising approach. The achievements of population biology and ecophysiology have affected vegetation science by emphasizing the functionality of species within plant communities. The use of guilds and other functional groups has experienced an increasing interest from vegetation scientists. Applied in vegetation science, fuzzy-set theory has bridged the techniques of classification and ordination of plant communities.

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Section: Pragmatismmentioning

confidence: 99%

Classification of vegetation: Past, present and future

Mucina

1997

J Vegetation Science

130

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“…It has been pointed out by a range of studies (e.g., Westermann et al [1] and Ottle et al [3]) that there is a need for accurate land cover description in the northern high latitudes. A suitable circumpolar map does not yet exist to date, although a range of studies demonstrated the suitability of satellite data for this purpose on local and regional scales.A first review on traditional Arctic land cover maps as a baseline for the development of a circumpolar map was already published in 1995 by Walker et al [4]. The Circum-Arctic Vegetation Map (CAVM) has in the following been developed using satellite data (Advanced Very High Resolution Radiometer (AVHRR)) and published [5].…”

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confidence: 99%

“…A first review on traditional Arctic land cover maps as a baseline for the development of a circumpolar map was already published in 1995 by Walker et al [4]. The Circum-Arctic Vegetation Map (CAVM) has in the following been developed using satellite data (Advanced Very High Resolution Radiometer (AVHRR)) and published [5].…”

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Land Cover Mapping in Northern High Latitude Permafrost Regions with Satellite Data: Achievements and Remaining Challenges

et al. 2016

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Most applications of land cover maps that have been derived from satellite data over the Arctic require higher thematic detail than available in current global maps. A range of application studies has been reviewed, including up-scaling of carbon fluxes and pools, permafrost feature mapping and transition monitoring. Early land cover mapping studies were driven by the demand to characterize wildlife habitats. Later, in the 1990s, up-scaling of in situ measurements became central to the discipline of land cover mapping on local to regional scales at several sites across the Arctic. This includes the Kuparuk basin in Alaska, the Usa basin and the Lena Delta in Russia. All of these multi-purpose land cover maps have been derived from Landsat data. High resolution maps (from optical satellite data) serve frequently as input for the characterization of periglacial features and also flux tower footprints in recent studies. The most used map to address circumpolar issues is the CAVM (Circum Arctic Vegetation Map) based on AVHRR (1 km) and has been manually derived. It provides the required thematic detail for many applications, but is confined to areas north of the treeline, and it is limited in spatial detail. A higher spatial resolution circumpolar land cover map with sufficient thematic content would be beneficial for a range of applications. Such a land cover classification should be compatible with existing global maps and applicable for multiple purposes. The thematic content of existing global maps has been assessed by comparison to the CAVM and regional maps. None of the maps provides the required thematic detail. Spatial resolution has been compared to used classes for local to regional applications. The required thematic detail increases with spatial resolution since coarser datasets are usually applied over larger areas covering more relevant landscape units. This is especially of concern when the entire Arctic is addressed. A spatial resolution around 30 m has been shown to be suitable for a range of applications. This implies that the current Landsat-8, as well as Sentinel-2 missions would be adequate as input data. Recent studies have exemplified the value of Synthetic Aperture Radar (SAR) in tundra regions. SAR missions may be therefore of added value for large-scale high latitude land cover mapping. Remote Sens. 2016, 8, 979 2 of 27with climate change in the upcoming decades [2]. It has been pointed out by a range of studies (e.g., Westermann et al. [1] and Ottle et al. [3]) that there is a need for accurate land cover description in the northern high latitudes. A suitable circumpolar map does not yet exist to date, although a range of studies demonstrated the suitability of satellite data for this purpose on local and regional scales.A first review on traditional Arctic land cover maps as a baseline for the development of a circumpolar map was already published in 1995 by Walker et al. [4]. The Circum-Arctic Vegetation Map (CAVM) has in the following been developed using satellite data (Advanced Very Hi...

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“…Regional and global environmental changes can be studied effectively by combining spatially explicit data sets on vegetation and other landscape properties with process models (Levin 1992;Running et al 1994;Kittel et al 2000;Plummer 2000;Rupp et al 2000;Ranson et al 2001;Van der Linden et al 2003). However, present knowledge of the detailed vegetation distribution of the remote Arctic areas is relatively scarce (Walker et al 1995;Rees et al 2002). Remote sensing images and their classification provide possibilities to cover large areas at relatively low costs compared to traditional fi eld Satellite image based vegetation classifi cation of a large area using limited ground reference data: a case study in the Usa Basin, north-east European Russia Tarmo Virtanen, Kari Mikkola & Ari Nikula Predicted global changes can be studied effectively by combining spatially explicit data sets on vegetation and other landscape properties with process models.…”

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“…of Biological and Environmental Sciences,University of Helsinki,Box 65,Finland,tarmo.virtanen@helsinki.fi ;K. Mikkola & A. Nikula,Rovaniemi Research Station,Finnish Forest Research Institute;Box 16;Finland. inventory based vegetation mapping (Walker et al 1995;Barnsley et al 1997;Cihlar 2000;Franklin & Wulder 2002;Rees et al 2002).…”

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confidence: 99%

Satellite image based vegetation classification of a large area using limited ground reference data: a case study in the Usa Basin, north-east European Russia

Virtanen¹,

Mikkola²,

Nikula³

2004

Polar Research

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Predicted global changes can be studied effectively by combining spatially explicit data sets on vegetation and other landscape properties with process models. However, detailed knowledge of the vegetation distribution of remote Arctic areas is relatively scarce. This paper shows how a mesoscale vegetation and land cover classification of a large, remote Arctic area can be conducted at a fine spatial resolution (30 m cell size) using a limited ground reference data set. The study area is the catchment of the River Usa (93 500 km2) in north‐eastern European Russia. Vegetation zones in the Usa Basin range from taiga in the south to forest‐tundra and tundra in the north, and to alpine in the Ural mountains in the east. Classification was done using a mosaic of spectrally adjusted Landsat TM5 images from five different dates and a semi‐supervised method. Ground reference data were collected during the summers of 1998, 1999 and 2000. Accuracy of the 21‐class vegetation type/land cover classification produced was tested against test points interpreted from oblique aerial photographs taken from a helicopter (logistic limitations prohibited the collection of representative ground reference data). The main vegetation types (forests, willow dominated stands and meadows, peatlands, tundra heaths, mainly unvegetated areas, and water bodies) were distinguished with relatively high accuracy: 84% of the test points were classified correctly. Spatially detailed land cover data sets like the one described here allow detailed landscape‐level analysis and process modelling on many different subjects.

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Toward a new arctic vegetation map: a review of existing maps

Cited by 20 publications

References 27 publications

Classification of vegetation: Past, present and future

Classification of vegetation: Past, present and future

Land Cover Mapping in Northern High Latitude Permafrost Regions with Satellite Data: Achievements and Remaining Challenges

Satellite image based vegetation classification of a large area using limited ground reference data: a case study in the Usa Basin, north-east European Russia

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