Green Chlorophyll Vegetation Index (GCI) - Switzerland [2010-2019, Landsat]

This dataset is an time-serie of Landsat Analysis Ready Data (ARD)- derived Green Chlorophyll Vegetation Index (GCI) computed from Landsat 5-7-8 data. GCI is used to estimate the content of leaf chlorophyll in various species of plants using the forumla GCI=(NIR/Green) – 1. See Gitelson et al. (2003) DOI: 10.1029/2002gl016450 The chlorophyll content reflects the physiological state of vegetation; it decreases in stressed plants and can therefore be used as a measurement of vegetation health. GCI values ranges from -1 to +1. Values are provided as integer and multiplied by 1000 Metrics: annual (_annual) and seasonal (_spring; _summer; _autumn; _winter) mean (_nanmean), standard dev (_nanstd), min (_nanmin), max (_nanmax), median (_nanmedian), and amplitude (_range) Data format: GeoTiff This dataset has been genereated with the Swiss Data Cube (http://www.swissdatacube.ch) in the frame of the ValPar.CH project

    Organizational unit
    Swiss Data Cube
    Type
    Dataset
    DOI
    10.26037/yareta:ml2gqzy5nbf3vnksfvym2kvcam
    License
    Creative Commons Attribution 4.0 International
    Keywords
    vegetation, landsat, chlorophyll, valpar
Publication date20/09/2022
Retention date17/09/2032
accessLevelPublicAccess levelPublic
SensitivityBlue
licenseContract on the use of data
License
Contributors
  • Chatenoux, Bruno orcid
  • Giuliani, Gregory orcid
  • Rodila, Denisa
  • Schweiger, Anna
34
2
  • Quality (0 Reviews)
  • Usefulness (0 Reviews)

Datacite metadata

Packages information

Similar archives

Swiss Data Cube
Landsat 8 Surface Reflectance Analysis Ready Data 2018
2020 accessLevelPublic Public 48.5 GB
Swiss Data Cube
Landsat 7 Surface Reflectance Analysis Ready Data 2005
2020 accessLevelPublic Public 14.5 GB
Swiss Data Cube
Landsat 7 Surface Reflectance Analysis Ready Data 2006
2020 accessLevelPublic Public 12.6 GB
Swiss Data Cube
Landsat 7 Surface Reflectance Analysis Ready Data 2016
2020 accessLevelPublic Public 24.7 GB
All rights reserved by DLCM and the University of GenevaunigeBlack