Vegetation mapping in central Asian dry eco-systems using Landsat ETM+. A case study on the Gobi Gurvan Sayhan National Park

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Vegetation mapping in central Asian dry eco-systems using Landsat ETM+. A case study on the Gobi Gurvan Sayhan National Park. / von Wehrden, H.; Wesche, Karsten; Miehe, Georg et al.
in: Erdkunde, Jahrgang 60, Nr. 3, 01.09.2006, S. 261-272.

Publikation: Beiträge in ZeitschriftenZeitschriftenaufsätzeForschungbegutachtet

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von Wehrden H, Wesche K, Miehe G, Reudenbach C. Vegetation mapping in central Asian dry eco-systems using Landsat ETM+. A case study on the Gobi Gurvan Sayhan National Park. Erdkunde. 2006 Sep 1;60(3):261-272. doi: 10.3112/erdkunde.2006.03.05

Bibtex

@article{f49f2cef5189484e8ed38e96fd388368,
title = "Vegetation mapping in central Asian dry eco-systems using Landsat ETM+.: A case study on the Gobi Gurvan Sayhan National Park",
abstract = "This paper presents a vegetation map of the Gobi Gurvan Sayhan National Park, a large protected area in the semi-arid parts of southern Mongolia. The map was compiled in order to provide spatially explicit baseline data that were required for conservation management. The study area was covered by five partly overlapping Landsat ETM+ scenes. Vegetation was sampled at more than 600 sites using a modified Braun-Blanquet approach; locations were selected with the help of unsupervised classifications of the satellite scenes. Vegetation samples were initially classified with a phytosociological approach yielding four main groups of plant communities: mountain steppes, moist desert steppes of the upper pediments, dry desert steppes and extra-zonal vegetation. These groups comprised a total of 18 plant communities, which were subsequently used for the supervised classification of satellite images. Difficulties were expected due to the sparse vegetation cover typical for semi-deserts and steppe ecosystems, resulting in minor spectral differences among the different communities. However, independent validation of the map yielded an overall accuracy above 93%. Thus, the chosen set of methods proved suitable for the study region, and is currently employed for similar surveys in other southern Mongolian nature reserves.",
keywords = "Biology, Gurvan Sayhan national park, remote sensing, Asia, Mongolia, vegetation mapping, semi-arid regions, vegetation, Ecosystems Research",
author = "{von Wehrden}, H. and Karsten Wesche and Georg Miehe and Christoph Reudenbach",
year = "2006",
month = sep,
day = "1",
doi = "10.3112/erdkunde.2006.03.05",
language = "English",
volume = "60",
pages = "261--272",
journal = "Erdkunde",
issn = "0014-0015",
publisher = "Verlag B.o.s.s Druck und Medien GmbH",
number = "3",

}

RIS

TY - JOUR

T1 - Vegetation mapping in central Asian dry eco-systems using Landsat ETM+.

T2 - A case study on the Gobi Gurvan Sayhan National Park

AU - von Wehrden, H.

AU - Wesche, Karsten

AU - Miehe, Georg

AU - Reudenbach, Christoph

PY - 2006/9/1

Y1 - 2006/9/1

N2 - This paper presents a vegetation map of the Gobi Gurvan Sayhan National Park, a large protected area in the semi-arid parts of southern Mongolia. The map was compiled in order to provide spatially explicit baseline data that were required for conservation management. The study area was covered by five partly overlapping Landsat ETM+ scenes. Vegetation was sampled at more than 600 sites using a modified Braun-Blanquet approach; locations were selected with the help of unsupervised classifications of the satellite scenes. Vegetation samples were initially classified with a phytosociological approach yielding four main groups of plant communities: mountain steppes, moist desert steppes of the upper pediments, dry desert steppes and extra-zonal vegetation. These groups comprised a total of 18 plant communities, which were subsequently used for the supervised classification of satellite images. Difficulties were expected due to the sparse vegetation cover typical for semi-deserts and steppe ecosystems, resulting in minor spectral differences among the different communities. However, independent validation of the map yielded an overall accuracy above 93%. Thus, the chosen set of methods proved suitable for the study region, and is currently employed for similar surveys in other southern Mongolian nature reserves.

AB - This paper presents a vegetation map of the Gobi Gurvan Sayhan National Park, a large protected area in the semi-arid parts of southern Mongolia. The map was compiled in order to provide spatially explicit baseline data that were required for conservation management. The study area was covered by five partly overlapping Landsat ETM+ scenes. Vegetation was sampled at more than 600 sites using a modified Braun-Blanquet approach; locations were selected with the help of unsupervised classifications of the satellite scenes. Vegetation samples were initially classified with a phytosociological approach yielding four main groups of plant communities: mountain steppes, moist desert steppes of the upper pediments, dry desert steppes and extra-zonal vegetation. These groups comprised a total of 18 plant communities, which were subsequently used for the supervised classification of satellite images. Difficulties were expected due to the sparse vegetation cover typical for semi-deserts and steppe ecosystems, resulting in minor spectral differences among the different communities. However, independent validation of the map yielded an overall accuracy above 93%. Thus, the chosen set of methods proved suitable for the study region, and is currently employed for similar surveys in other southern Mongolian nature reserves.

KW - Biology

KW - Gurvan Sayhan national park

KW - remote sensing

KW - Asia

KW - Mongolia

KW - vegetation mapping

KW - semi-arid regions

KW - vegetation

KW - Ecosystems Research

UR - http://www.scopus.com/inward/record.url?scp=33750290973&partnerID=8YFLogxK

UR - https://www.mendeley.com/catalogue/20d3820c-f9b7-3d33-a960-db125a253a75/

U2 - 10.3112/erdkunde.2006.03.05

DO - 10.3112/erdkunde.2006.03.05

M3 - Journal articles

AN - SCOPUS:33750290973

VL - 60

SP - 261

EP - 272

JO - Erdkunde

JF - Erdkunde

SN - 0014-0015

IS - 3

ER -

DOI