Global MVL loss map-induced by human expansions and natural disasters; Global mountain-PAs; Global AHRTMS
<p><span lang="EN-US">(1) Global MVL loss map-induced by human expansions and natural disasters</span></p> <p><span lang="EN-US">Global MVL loss map: a global mountain vegetated landscapes (MVL) loss map (during 2000-2020) at 30-m resolution was developed using global datasets on mountain boundaries, human land use, natural disasters together with Landsat imageries-derived NDVI. This map includes seven drivers that cause MVL loss (i.e. human expansions and natural disasters). The losses of MVL caused by human expansions include (i) human settlement growth, (ii) agriculture expansion, and (iii) mining. The losses of MVL caused by natural disasters (i.e. a net loss after deducting restored areas in disaster areas) include (vi) wildfires, (v) floods, (vi) landslides, and (xii) droughts. The data was stored in Global MVL loss map.gdb and can be opened through mxd file in ArcGIS software.</span></p> <p><span lang="EN-US">(2) Global mountain-PAs; </span></p> <p><span lang="EN-US">Global mountain PAs: the mountain-protected areas (PAs) was mapped using World Database of Protected Areas (WDPA) and GMBA mountain boundaries (<a name="OLE_LINK1"></a>v2.0 standard). The data was stored in</span><span lang="EN-US"> </span><span lang="EN-US">Global mountain-PAs.gdb and can be opened through ArcGIS software.</span></p> <p><span lang="EN-US">(3) Global AHRTMS</span></p> <p><span lang="EN-US">Global AHRTMS: the areas with high richness of threatened mountain-occurring species (AHRTMS) was produced with IUCN Red List threatened species (including mammals, amphibians, reptiles, birds and plants) and GMBA mountain boundaries (v2.0 standard). The data was stored in</span><span lang="EN-US"> </span><span lang="EN-US">Global AHRTMS.gdb and can be opened through ArcGIS software.</span></p> <p><strong><span lang="EN-US">A manuscript related to above data analysis has submitted to a journal.</span></strong></p>
ShareScore
40/100
Overall dataset sharing score
Score breakdown
These five areas show where the dataset supports — or may limit — practical reuse.
- Stewardship
- 8
- Harmonization
- 8
- Access
- 16
- Reuse readiness
- 8
- Engagement
- 0
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