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[dataset] GAEZ Global Agro-ecological Zones v3.0

"The Agro‐Ecological Zones (AEZ) approach is based on principles of land evaluation (FAO 1976, 1984 and 2007). The AEZ concept was originally developed by the Food and Agriculture organization of the United Nations (FAO). FAO, with the collaboration of IIASA has over time, further developed and applied the AEZ methodology, supporting databases and software packages. The current Global AEZ (GAEZ v 3.0) provides a major update of data and extension of the methodology compared to the release of GAEZ in 2002 (Fischer, et. al., 2002). GAEZ v 3.0 incorporates two important new global data sets on “Actual Yield and Production’ and “Yield and Production Gaps” between potentials and actual yield and production. Geo‐referenced global climate, soil and terrain data are combined into a land resources database, commonly assembled on the basis of global grids, typically at 5 arc‐minute and 30 arc‐second resolutions. Climatic data comprises precipitation, temperature, wind speed, sunshine hours and relative humidity, which are used to compile agronomically meaningful climate resources inventories including quantified thermal and moisture regimes in space and time."
Fischer, G.; Nachtergaele, F. O.; Prieler, S.; Teixeira, E.; Toth, G.; van Velthuizen, H. et al. (2016): Global Agro-ecological Zones (GAEZ v3.0) - Model Documentation.

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Data and Resources

Additional Info

Field Value
Identifier potyield
Documentation https://webarchive.iiasa.ac.at/Research/LUC/GAEZv3.0/docs/GAEZ_Model_Documentation.pdf
Contact Point Food and Agriculture Organization of the United Nations (FAO)
Contact Point - ORCID iD or e-mail adress
Dataset DOI
Information Website https://webarchive.iiasa.ac.at/Research/LUC/GAEZv3.0/
Theme / Vocabulary / Ontology https://inspire.ec.europa.eu/theme/af
Coordinate Reference System http://www.opengis.net/def/crs/EPSG/0/4326
Spatial Resolution 0.08333
Spatial Resolution Measured As angular distance
Temporal Coverage 1961-01-01 to 2000-01-01
Temporal Resolution
Data Quality Metric

Completeness Ommission as Number of Missing Items

https://geokur-dmp.geo.tu-dresden.de/pages/quality-elements#completenessOmmissionAsNumberOfMissingItems

  • value of quality metric:8713437
  • ground truth dataset:
  • confidence term:
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  • thematic representativity:
  • spatial representativity:global
  • temporal representativity:
  • name of quality source:MetadataFromGeodata Extraction Tool
  • type of quality source:software
  • link to quality source:https://github.com/GeoinformationSystems/MetadataFromGeodata

Completeness Ommission as Rate of Missing Items

https://geokur-dmp.geo.tu-dresden.de/pages/quality-elements#completenessOmmissionAsRateOfMissingItems

  • value of quality metric:96.8074
  • ground truth dataset:
  • confidence term:
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  • thematic representativity:
  • spatial representativity:global
  • temporal representativity:
  • name of quality source:MetadataFromGeodata Extraction Tool
  • type of quality source:software
  • link to quality source:https://github.com/GeoinformationSystems/MetadataFromGeodata

Format Consistency as Value Physical Structure Conflicts Number

https://geokur-dmp.geo.tu-dresden.de/pages/quality-elements#formatConsistencyAsValuePhysicalStructureConflictsNumber

  • value of quality metric:true
  • ground truth dataset:
  • confidence term:
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  • thematic representativity:
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  • temporal representativity:
  • name of quality source:MetadataFromGeodata Extraction Tool
  • type of quality source:software
  • link to quality source:https://github.com/GeoinformationSystems/MetadataFromGeodata

Temporal Consistency as Value

https://geokur-dmp.geo.tu-dresden.de/pages/quality-elements#temporalConsistencyAsValue

  • value of quality metric:false
  • ground truth dataset:
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  • name of quality source:
  • type of quality source:manual analysis
  • link to quality source:

Quantitative Attribute Accuracy as Coefficient of Determination (R²)

https://geokur-dmp.geo.tu-dresden.de/quality-register#QuantitativeAttributeAccuracyasCoefficientofDetermination

  • value of quality metric:0.75
  • ground truth dataset:
  • confidence term:
  • confidence value:
  • thematic representativity:
  • spatial representativity:global
  • temporal representativity:
  • name of quality source:Spatio-Temporal Dynamics of Maize Potential Yield and Yield Gaps in Northeast China from 1990 to 2015
  • type of quality source:publication
  • link to quality source:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6480490/

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Last Updated October 5, 2021, 13:14 (UTC)
Created April 30, 2021, 13:59 (UTC)

Dataset extent