GlobeLand30 as an alternative fine-scale global land cover map: challenges, possibilities, and implications for developing countries
Global land cover maps are a vital source for mapping our globe into a set of thematic types. They have been extensively used as a basis layer for a large number of applications including ecosystem services, environmental planning, climate change, hydrological processes and policy making. While regi...
Gespeichert in:
| Hauptverfasser: | , , |
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| Dokumenttyp: | Article (Journal) |
| Sprache: | Englisch |
| Veröffentlicht: |
2 March 2016
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| In: |
Habitat international
Year: 2016, Jahrgang: 55, Pages: 25-31 |
| DOI: | 10.1016/j.habitatint.2016.02.003 |
| Online-Zugang: | Verlag, lizenzpflichtig, Volltext: https://doi.org/10.1016/j.habitatint.2016.02.003 Verlag, lizenzpflichtig, Volltext: http://www.sciencedirect.com/science/article/pii/S0197397515301521 
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| Verfasserangaben: | Jamal Jokar Arsanjani, Amin Tayyebi, Eric Vaz |
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| 520 | |a Global land cover maps are a vital source for mapping our globe into a set of thematic types. They have been extensively used as a basis layer for a large number of applications including ecosystem services, environmental planning, climate change, hydrological processes and policy making. While regional land cover maps for some areas such as Europe and North America has been greatly developed and very few temporal datasets exist, lack of such data for some regions specifically developing countries is evident. Although it seems global land cover maps such as MODIS could be a solution for mapping these regions, their coarse spatial resolution e.g., 500 m as well as their accuracy are very challenging. Recently, GlobeLand30 a global land cover with a relatively fine resolution at 30 m extracted from Landsat images has been released, which seems to be a potential dataset for mapping areas with limited land cover information such as developing countries. In this study, we look at GlobeLand30 of 2010 for Iran in order to find out the accuracy of this dataset as well as its implications. By having looked at 6 selected study sites around larger cities representing dissimilar eco-regions covering rural and urban areas, we conclude that the overall accuracy of GlobeLand30 with 77.9% was satisfactory for entire Iran. We also define six representative eco-regions dominated by diverse land type mixtures considering the administrative boundaries. The detailed implications of this dataset for developing different applications as well as informing regional policy makers are discussed. | ||
| 650 | 4 | |a Accuracy assessment | |
| 650 | 4 | |a Eco-region | |
| 650 | 4 | |a GlobeLand30 | |
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| 650 | 4 | |a Land cover mapping | |
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