Plant functional types map in China (1 km)

Vegetation functional type (PFT) is a combination of large plant species according to the ecosystem function and resource utilization mode of plant species. Each planting functional type shares similar plant attributes, which simplifies the diversity of plant species into the diversity of plant function and structure.The concept of vegetation-functional has been advocated by ecologists especially ecosystem modelers.The basic assumption is that globally important ecosystem dynamics can be expressed and simulated through limited vegetative functional types.At present, vegetation-functional model has been widely used in biogeographic model, biogeochemical model, land surface process model and global dynamic vegetation model. For example, the land surface process model of the national center for atmospheric research (NCAR) in the United States has changed the original land cover information into the applied vegetation-functional map (Bonan et al., 2002).Functional vegetation has been used in the dynamic global vegetation model (DGVM) to predict the changes of ecosystem structure and function under the global change scenario.

1. Functional classification system of vegetation

1 Needleleaf evergreen tree, temperate

2 Needleleaf evergreen tree, boreal

3 Needleleaf deciduous tree

4 Broadleaf evergreen tree, tropical

5 Broadleaf evergreen tree, temperate

6 Broadleaf deciduous tree, tropical

7 Broadleaf deciduous tree, temperate

8 Broadleaf deciduous tree, boreal

9 Broadleaf evergreen shrub, temperate

10 Broadleaf deciduous shrub, temperate

11 Broadleaf deciduous shrub, boreal

12 C3 grass, arctic

13 C3 grass

14 C4 grass

15 Crop

16 Permanent wetlands

17 Urban and built-up lands

18 Snow and ice

19 Barren or sparsely vegetated lands

20 Bodies of water

2. Drawing method

China's 1km vegetation function map is based on the climate rules of land cover and vegetation function conversion proposed by Bonan et al. (Bonan et al., 2002).Ran et al., 2012).MICLCover land cover map is a blend of 1:100000 data of land use in China in 2000, the Chinese atlas (1:10 00000) the type of vegetation, China 1:100000 glacier map, China 1:10 00000 marshes and MODIS land cover 2001 products (MOD12Q1) released the latest land cover data, using IGBP land cover classification system.The evaluation shows that it may be the most accurate land cover map on the scale of 1km in China.Climate data is China's atmospheric driven data with spatial resolution of 0.1 and temporal resolution of 3 hours from 1981 to 2008 developed by he jie et al. (2010).The data incorporates Princeton land-surface model driven data (Sheffield et al., 2006), gewex-srb radiation data (Pinker et al., 2003), TRMM 3B42 and APHRODITE precipitation data, and observations from 740 meteorological stations and stations under the China meteorological administration.According to the evaluation results of RanYouhua et al. (2010), GLC2000 has a relatively high accuracy in the current global land cover data set, and there is no mixed forest in its classification system. Therefore, the mixed forest in the MICLCover land cover diagram USES GLC2000 (Bartholome and Belward, 2005).The information in xu wenting et al., 2005) was replaced.The data can be used in land surface process model and other related researches.

Data file naming and use method

Grid data: PFTS
Arcgis software can be used to open

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Cite as:

RAN Youhua, LI Xin. Plant functional types map in China (1 km). National Tibetan Plateau Data Center, 2019. doi: 10.11888/Ecolo.tpdc.270101. (Download the reference: RIS | Bibtex )

Related Literatures:

1. Ran, Y.H., Ma, H.Q. (2016). 1KM Plant Functional Types Map over China in 2000. Remote Sensing Technology and Application, 31(4): 827-832.( View Details | Bibtex)

Using this data, the data citation is required to be referenced and the related literatures are suggested to be cited.

References literature

1.Huang Y, Guo X, Wang Y. Historical and Ecological Factors Affecting Regional Patterns of Endemism and Species Richness: The Case of Squamates in China[J]. 2013 (View Details )

2.Qin J, Ding Y, Wu J, et al. Understanding the impact of mountain landscapes on water balance in the upper Heihe River watershed in northwestern China[J]. Journal of Arid Land. 2013: 1-18 (View Details )

3.Liu W, Zhang Q, Liu G. Influences of watershed landscape composition and configuration on lake-water quality in the Yangtze River basin of China[J]. Hydrological Processes, 2012, 26(4): 570–578. doi:10.1002/hyp.8157 (View Details )

4.Rong,Z.R,Ma,A.Q,Wang,Z.K,Yu,H,Zhang,J.X.(2012),Formation Mechanism of Landscape Pattern Based on Logistic Regression Model in the Wetland of Liaohe.Periodical of ocean university of china.42(7-8):138-143,DOI:10.16441/j.cnki.hdxb.2012.z2.021 (View Details )

5.Jin,T.T.(2012).Ecological Carrying Capacity and Coupling model Of human and Ecosystem —A Case Study of Upstream Watershed of Jinsha river.Doctoral Dissertation.Chengdu Univerisity of Technology (View Details )

6.Lin,X.Q,Huang.Y,Zuo,Z.L&Chen,Y.Y.(2012).Large-scale Geographic Pattern of Primate Species Richness in Mainland China at Different Spatial Resolution and Its Relationship to Environmental Factors and Human Activities.Chin J Appl Environ Biol.18(6), 954-963.DOI: 10.3724/SP.J.1145.2012.00954 (View Details )

7.Chen,l.X,Liang,Z.M,Zhu,J.F.(2011).Application of SWAT Model to Runoff Simulation in Huangyahe Basin.Water Resources and Power.29(10),8-11. (View Details )

8.Ran, Y.H., Li, X., Lu, L. (2009). China Land Cover Classfication at 1KM Spatial Resolution Based on a Multisource Data Fusion Approach.Advances in earth science.Issue(2), 192-203. (View Details )

Support Program

CASEarth:Big Earth Data for Three Poles(grant No. XDA19070000) (No:XDA19000000)

Pan-Third Pole Environment Study for a Green Silk Road-A CAS Strategic Priority A Program (No:XDA20000000)

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Geographic coverage
East: 135.50 West: 73.20
South: 17.80 North: 53.90
  • Spatial resolution: km
  • File size: 12 MB
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  • Updated time: 2019-08-31
Contact Information
: RAN Youhua   LI Xin  

Distributor: National Tibetan Plateau Data Center


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