Forest cover mapping in post-Soviet Central Asia using multi-resolution remote sensing imagery

Despite rapid advances and large-scale initiatives in forest mapping, reliable cross-border information about the status of forest resources in Central Asian countries is lacking. We produced consistent Central Asia forest cover (CAFC) maps based on a cost-efficient approach using multi-resolution s...

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Autores principales: He, Y., Pflugmacher, D., Martius, C.
Formato: Journal Article
Lenguaje:Inglés
Publicado: Springer 2017
Materias:
Acceso en línea:https://hdl.handle.net/10568/93913
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author He, Y.
Pflugmacher, D.
Martius, C.
author_browse He, Y.
Martius, C.
Pflugmacher, D.
author_facet He, Y.
Pflugmacher, D.
Martius, C.
author_sort He, Y.
collection Repository of Agricultural Research Outputs (CGSpace)
description Despite rapid advances and large-scale initiatives in forest mapping, reliable cross-border information about the status of forest resources in Central Asian countries is lacking. We produced consistent Central Asia forest cover (CAFC) maps based on a cost-efficient approach using multi-resolution satellite imagery from Landsat and MODIS during 2009–2011. The spectral-temporal metrics derived from 2009–2011 Landsat imagery (overall accuracy of 0.83) was used to predict sub-pixel forest cover on the MODIS scale for 2010. Accuracy assessment confirmed the validity of MODIS-based forest cover map with a normalized root-mean-square error of 0.63. A general paucity of forest resources in post-Soviet Central Asia was indicated, with 1.24% of the region covered by forest. In comparison to the CAFC map, a regional map derived from MODIS Vegetation Continuous Fields tended to underestimate forest cover, while the Global Forest Change product matched well. The Global Forest Resources Assessments, based on individual country reports, overestimated forest cover by 1.5 to 147 times, particularly in the more arid countries of Turkmenistan and Uzbekistan. Multi-resolution imagery contributes to regionalized assessment of forest cover in the world’s drylands while developed CAFC maps (available at https://data.zef.de/) aim to facilitate decisions on biodiversity conservation and reforestation programs in Central Asia.
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spelling CGSpace939132025-06-17T08:23:38Z Forest cover mapping in post-Soviet Central Asia using multi-resolution remote sensing imagery He, Y. Pflugmacher, D. Martius, C. forests mapping remote sensing reforestation conservation Despite rapid advances and large-scale initiatives in forest mapping, reliable cross-border information about the status of forest resources in Central Asian countries is lacking. We produced consistent Central Asia forest cover (CAFC) maps based on a cost-efficient approach using multi-resolution satellite imagery from Landsat and MODIS during 2009–2011. The spectral-temporal metrics derived from 2009–2011 Landsat imagery (overall accuracy of 0.83) was used to predict sub-pixel forest cover on the MODIS scale for 2010. Accuracy assessment confirmed the validity of MODIS-based forest cover map with a normalized root-mean-square error of 0.63. A general paucity of forest resources in post-Soviet Central Asia was indicated, with 1.24% of the region covered by forest. In comparison to the CAFC map, a regional map derived from MODIS Vegetation Continuous Fields tended to underestimate forest cover, while the Global Forest Change product matched well. The Global Forest Resources Assessments, based on individual country reports, overestimated forest cover by 1.5 to 147 times, particularly in the more arid countries of Turkmenistan and Uzbekistan. Multi-resolution imagery contributes to regionalized assessment of forest cover in the world’s drylands while developed CAFC maps (available at https://data.zef.de/) aim to facilitate decisions on biodiversity conservation and reforestation programs in Central Asia. 2017 2018-07-03T10:56:37Z 2018-07-03T10:56:37Z Journal Article https://hdl.handle.net/10568/93913 en Open Access Springer He, Y., Pflugmacher, D., Martius, C.. 2017. Forest cover mapping in post-Soviet Central Asia using multi-resolution remote sensing imagery Scientific Reports, 7 (1) : 1375. https://doi.org/10.1038/s41598-017-01582-x
spellingShingle forests
mapping
remote sensing
reforestation
conservation
He, Y.
Pflugmacher, D.
Martius, C.
Forest cover mapping in post-Soviet Central Asia using multi-resolution remote sensing imagery
title Forest cover mapping in post-Soviet Central Asia using multi-resolution remote sensing imagery
title_full Forest cover mapping in post-Soviet Central Asia using multi-resolution remote sensing imagery
title_fullStr Forest cover mapping in post-Soviet Central Asia using multi-resolution remote sensing imagery
title_full_unstemmed Forest cover mapping in post-Soviet Central Asia using multi-resolution remote sensing imagery
title_short Forest cover mapping in post-Soviet Central Asia using multi-resolution remote sensing imagery
title_sort forest cover mapping in post soviet central asia using multi resolution remote sensing imagery
topic forests
mapping
remote sensing
reforestation
conservation
url https://hdl.handle.net/10568/93913
work_keys_str_mv AT hey forestcovermappinginpostsovietcentralasiausingmultiresolutionremotesensingimagery
AT pflugmacherd forestcovermappinginpostsovietcentralasiausingmultiresolutionremotesensingimagery
AT martiusc forestcovermappinginpostsovietcentralasiausingmultiresolutionremotesensingimagery