This website uses cookies. By continuing to use this website you are agreeing to our use of cookies. 

Dataset

 

ESA Land Cover Climate Change Initiative (Land_Cover_cci): Global Plant Functional Types (PFT) Dataset, v2.0.8

Update Frequency: Annually
Latest Data Update: 2023-01-26
Status: Ongoing
Online Status: ONLINE
Publication State: Citable
Publication Date: 2023-01-26
DOI Publication Date: 2023-01-26
Download Stats: last 12 months
Dataset Size: 30 Files | 92GB

Abstract

This dataset contains Global Plant Functional Types (PFT) data, from the ESA Medium Resolution Land Cover (MRLC) Climate Change Initiative project. The data provides yearly data, and initially covers the time period from 1992 to 2020. It is anticipated that the dataset will be updated annually going forward.

The PFT v2.0.8 global dataset has 14 layers, each describing the percentage cover (0-100%) of a plant functional type at a spatial resolution of 300 m: broadleaved evergreen trees, broadleaved deciduous trees, needleleaved evergreen trees, needleleaved deciduous trees, broadleaved evergreen shrubs, broadleaved deciduous shrubs, needleleaved evergreen shrubs, needleleaved deciduous shrubs, natural grasses, herbaceous cropland (i.e., managed grasses), built, water, bare areas, and snow and ice.

"Plant Functional Types” (PFTs) refer to globally representative and similarly behaving plant types. PFTs can be related to physiognomy and phenology, climate (which defines the geographical ranges in which a plant type can grow and reproduce under natural conditions, and physiological activity (e.g., C3/C4 photosynthetic pathways).

All terrestrial zones of the Earth between the parallels 90°N and 90°S are covered. The PFT dataset has a regular latitude-longitude grid with a grid spacing of 0.002777777777778°, corresponding to ~300 m at the equator and ~200 m in the midlatitudes. The Coordinate Reference System used for the global land cover database is a geographic coordinate system (GCS) based on the World Geodetic System 84 (WGS84) reference ellipsoid.

The plant functional type (PFT) distribution was created by combining auxiliary data products with the CCI MRLC map series. The LC classification provides the broad characteristics of the 300 m pixel, including the expected vegetation form(s) (tree, shrub, grass) and/or abiotic land type(s) (water, bare area, snow and ice, built-up) in the pixel. For some classes, the class legend specifies an expected range for the fractional covers of the contributing PFTs and broadly differentiates between natural and cultivated vegetation. We used a quantitative, globally consistent method that fuses the 300-metre MRLC product with a suite of existing high-resolution datasets to develop spatially explicit annual maps of PFT fractional composition at 300 metres. The new PFT product exhibits intraclass spatial variability in PFT fractional cover at the 300-metre pixel level and is complementary to the MRLC maps since the derived PFT fractions maintain consistency with the original LC class legend.

This dataset was generated to reduce the cross-walking component of uncertainty by adding spatial variability to the PFT composition within a LC class. This work moved beyond fine-tuning the cross-walking approach for specific LC classes or regions and, instead, separately quantifies the PFT fractional composition for each 300 m pixel globally. The result is a dataset representing the cover fractions of 14 PFTs at 300 m for each year within the time range, consistent with the CCI MRLC LC maps for the corresponding year.

This study was carried out with the continued support of the European Space Agency Climate Change Initiative under the contract ESA/No.4000126564 Land_Cover_cci.

Citable as:  Harper, K.L.; Lamarche, C.; Hartley, A.; Peylin, P.; Ottlé, C.; Bastrikov, V.; San Martín, R.; Bohnenstengel, S.I.; Kirches, G.; Boettcher, M.; Shevchuk, R.; Brockmann, C.; Defourny, P. (2023): ESA Land Cover Climate Change Initiative (Land_Cover_cci): Global Plant Functional Types (PFT) Dataset, v2.0.8. NERC EDS Centre for Environmental Data Analysis, 26 January 2023. doi:10.5285/26a0f46c95ee4c29b5c650b129aab788. https://dx.doi.org/10.5285/26a0f46c95ee4c29b5c650b129aab788
Abbreviation: Not defined
Keywords: Land Cover, CCI, PFT

Details

Previous Info:
No news update for this record
Previously used record identifiers:
No related previous identifiers.
Access rules:
Public data: access to these data is available to both registered and non-registered users.
Use of these data is covered by the following licence: https://artefacts.ceda.ac.uk/licences/specific_licences/esacci_landcover_terms_and_conditions_v2.pdf. When using these data you must cite them correctly using the citation given on the CEDA Data Catalogue record.
Data lineage:

Data were processed by the ESA CCI Medium Resolution Land Cover project and catalogued here as part of the CCI Open Data Portal Project

Data Quality:
For more information on the data quality see the documentation from the ESA Land Cover project
File Format:
Data are in NetCDF format

Process overview

This dataset was generated by the computation detailed below.
Title

Derivation of the ESA Land Cover Climate Change Initiative (Land_Cover_cci): Global Plant Function Types (PFT) Dataset

Abstract

The plant functional type (PFT) distribution was created by combining auxiliary data products with the CCI Medium Resolution Land Cover (MRLC) map series. The land cover (LC) classification provides the broad characteristics of the 300 m pixel, including the expected vegetation form(s) (tree, shrub, grass) and/or abiotic land type(s) (water, bare area, snow and ice, built-up) in the pixel. For some classes, the class legend specifies an expected range for the fractional covers of the contributing PFTs and broadly differentiates between natural and cultivated vegetation. We used a quantitative, globally consistent method that fuses the 300-metre MRLC product with a suite of existing high-resolution datasets to develop spatially explicit annual maps of PFT fractional composition at 300 metres. The new PFT product exhibits intraclass spatial variability in PFT fractional cover at the 300-metre pixel level and is complementary to the MRLC maps since the derived PFT fractions maintain consistency with the original LC class legend.

This dataset was generated to reduce the cross-walking component of uncertainty by adding spatial variability to the PFT composition within a LC class. This work moved beyond fine-tuning the cross-walking approach for specific LC classes or regions and, instead, separately quantifies the PFT fractional composition for each 300 m pixel globally. The result is a dataset representing the cover fractions of 14 PFTs at 300 m for each year within the time range, consistent with the CCI MRLC LC maps for the corresponding year.

Input Description

None

Output Description

None

Software Reference

None

  • var_id: BARE
  • long_name: Bare
  • var_id: SHRUBS-BD
  • long_name: Broadleaved deciduous shrubs
  • var_id: TREES-BD
  • long_name: Broadleaved deciduous trees
  • var_id: SHRUBS-BE
  • long_name: Broadleaved evergreen shrubs
  • var_id: TREES-BE
  • long_name: Broadleaved evergreen trees
  • var_id: BUILT
  • long_name: Built
  • var_id: WATER_INLAND
  • long_name: Inland Water
  • long_name: Land
  • var_id: LAND
  • var_id: GRASS-MAN
  • long_name: Managed grasses
  • var_id: GRASS-NAT
  • long_name: Natural grasses
  • var_id: SHRUBS-ND
  • long_name: Needleleaved deciduous shrubs
  • var_id: TREES-ND
  • long_name: Needleleaved deciduous trees
  • var_id: SHRUBS-NE
  • long_name: Needleleaved evergreen shrubs
  • var_id: TREES-NE
  • long_name: Needleleaved evergreen trees
  • var_id: WATER_OCEAN
  • long_name: Oceanic water
  • var_id: SNOWICE
  • long_name: Permanent snow and ice
  • var_id: WATER
  • long_name: Water
  • var_id: lat_bounds
  • var_id: lon_bounds
  • var_id: time_bounds

Co-ordinate Variables

  • units: degrees_north
  • standard_name: latitude
  • long_name: latitude
  • var_id: lat
  • units: degrees_east
  • standard_name: longitude
  • long_name: longitude
  • var_id: lon
  • long_name: time
  • standard_name: time
  • var_id: time
  • units: days
Coverage
Temporal Range
Start time:
1992-01-01T00:00:00
End time:
2020-12-31T23:59:59
Geographic Extent

 
90.0000°
 
-180.0000°
 
180.0000°
 
-90.0000°