Proceedings of the 2016 4th International Conference on Mechanical Materials and Manufacturing Engineering

Methods of the National Vegetation Classification Based on Vegetation Partition

Authors
Y.Y. Hao, X.B. Luo, B. Zhong, A.X. Yang
Corresponding Author
Y.Y. Hao
Available Online October 2016.
DOI
https://doi.org/10.2991/mmme-16.2016.60How to use a DOI?
Keywords
varied topography; vegetation types; land cover classification; vegetation partition
Abstract

The high precision land cover classification products has a very important significance for the study of quanti-tative remote sensing and remote sensing applications. Now there has a lot of free and global coverage land classification products, which is mostly developed by foreign research institutions and personnel. Due to the China regional complex terrain, differences in vegetation structures and in crop planting structures have not been fully studied, the classification accuracy of these products in the area of China is very low, especially the vegetation classification accuracy. Therefore, it is necessary to produce a vegetation type classification prod-uct of China region. So according to Chinese regional topography, soil and other information, and based on existing vegetation regionalization, we developed a method of Chinese vegetation classification based on veg-etation partition. This method is based on long time series, which can capture the surface information changed with time with the high time resolution, and can improve the classification accuracy by the differences in the time dimension of the object. And we complete the 2012 national land cover classification by using the meth-od. At last, the method of stratified random sampling was carried out to assess the accuracy of the classifica-tion results, found that the overall accuracy and Kappa coefficient of the classification products is greatly im-proved, which the overall accuracy was 90.78%, Kappa coefficient was 0.86.And the product was compared with the MODIS land cover data products, found that the accuracy of this product increased by61.38% in vegetation than the MODIS land cover data product.

Copyright
© 2016, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2016 4th International Conference on Mechanical Materials and Manufacturing Engineering
Series
Advances in Engineering Research
Publication Date
October 2016
ISBN
978-94-6252-221-3
ISSN
2352-5401
DOI
https://doi.org/10.2991/mmme-16.2016.60How to use a DOI?
Copyright
© 2016, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Y.Y. Hao
AU  - X.B. Luo
AU  - B. Zhong
AU  - A.X. Yang
PY  - 2016/10
DA  - 2016/10
TI  - Methods of the National Vegetation Classification Based on Vegetation Partition
BT  - Proceedings of the 2016 4th International Conference on Mechanical Materials and Manufacturing Engineering
PB  - Atlantis Press
SP  - 261
EP  - 265
SN  - 2352-5401
UR  - https://doi.org/10.2991/mmme-16.2016.60
DO  - https://doi.org/10.2991/mmme-16.2016.60
ID  - Hao2016/10
ER  -