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Land use following deforestation for Africa

Domaine:

geospatialenvironment and energy

Type de record:

datasetmodel
Créateur:
Masolele, Robert N.Marcos, DiegoDe Sy, VeroniqueAbu, Itohan-Osa
Éditeur:
Zenodo
Hôte:avatar

Data Description

These datasets were generated from the research article "Mapping the diversity of land uses following deforestation across Africa".

Here we publish the yearly time series maps showing land use following deforestation across Africa at 30 m resolution covering the year 2001 to 2020 (20 years). The maps are derived from Planet-NICFI images using  U-Net deep neural network architecture enhanced with attention.

The original landuse maps are derived from 5 m resolution Planet-NICFI imagery (research license with Planet Labs Inc) of 2022. The Planet-NICFI imagery are accessible upon sign up at planet.com  or developers.planet.com

The landuse dataset has fifteen classes with values ranging from 1 -15, where 1: Larger-scale cropland, 2: Pasture, 3: Mining, 4: Small-scale cropland, 5: Roads, 6: Other land with tree cover, 7: Plantation forest, 8: Coffee, 9: Settlement, 10: Tea plantation, 11: Water, 12: Oil palm, 13: Rubber, 14: Cashew, 15: Cacao

The data is accompanied by the sld  and qml file (Visualisation_layer_descriptor_sld_and_qml) to aid in visualisation or legend creation.

 

Data Visualisation at 5 m resolution: https://robertnag82.users.e…

File Naming:  LandUseFollowingDeforestation_dl_30m_20010101_20201231_af_epsg.4326_v1.tif

  • Generic variable name: LandUseFollowingDeforestation
  • Method of data production: dl (Deep learning)
  • Spatial support in m: 30m
  • Time reference begin time (YYYYMMDD):  i.e. 20010101
  • Time reference end time: 20201230
  • Bounding box (2 letters max): af (Refering to Africa)
  • EPSG code: epsg.4326
  • Version code: v1

JSON field representing the legend. This is important for the visualization of the legend. 

[ { "Large-scale cropland": "1", "color": "#FFFF00" }, { "Pasture": "2", "color": "#808080" }, { "Mining": "3", "color": "#FFC0CB" }, { "Small-scale cropland": "4", "color": "#F39C12" }, { "Roads": "5", "color": "#800000" }, { "Other land with tree cover/Regrowth ": "6", "color": "#008000" }, { "Plantation forest": "7", "color": "#808000" }, { "Coffee": "8", "color": "#008080" }, { "Settlement": "9", "color": "#FF0000" }, { "Tea plantation": "10", "color": "#3CB371" }, { "Water": "11", "color": "#0000FF" }, { "Oil palm": "12", "color": "#FF00FF" }, { "Rubber": "13", "color": "#4B0082" }, { "Cashew": "14", "color": "#00FF00" }, { "Cocoa": "15", "color": "#00FFFF" } ]

Data Use Agreement

The datasets are restricted to non-commercial purposes or purposes indicated in the licence document. This include the rights to: (i) use, access, and view Content through the Platform; (ii) download, reproduce, store, display, and print Content; and (iii) create Derivative Products; all for Licensee's own internal, non-commercial business purposes and those are the only rights that are extended. More information on the licence can be accessed here: assets.planet.com

The user agrees to assume all risks and liabilities associated with the interpretation and use of any data or results obtained from the datasets. Wageningen University, Planet-NICFI, Planet Labs Inc, and any affiliated parties shall not be held liable for any consequences arising from the misuse of the data. 

Visit

doi.org

Tasks

computer visionimage classification

Licenses

info:eu-repo/semantics/openAccessPlanet-NICFI licencehttps://assets.planet.com/docs/ToS_NICFI_GeneralPartners_level2.pdf

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