Saved in:
| Main Authors: | , , , , , |
|---|---|
| Format: | Dataset Open Access |
| Language: | en |
| Published: |
PANGAEA
2019
|
| Subjects: | |
| Online Access: | https://doi.org/10.1594/PANGAEA.898096 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1867170089738960896 |
|---|---|
| author | Liu, Han Gong, Peng Wang, Jie Clinton, Nicholas Bai, Yuqi Liang, Shunlin |
| author_facet | Liu, Han Gong, Peng Wang, Jie Clinton, Nicholas Bai, Yuqi Liang, Shunlin |
| collection | Datos científicos de ciencias marinas y ambientales |
| contents | Land cover (LC) is an important terrestrial variable and key information for understanding the interaction between human activities and global change. As the cause and result of global environmental change, land cover change (LCC) influences the global energy balance and biogeochemical cycles. Continuous and dynamic monitoring of global LC is urgently needed. Effective monitoring and comprehensive analysis of LCC at the global scale is rare. Using the latest version of GLASS (The Global Land Surface Satellite) CDRs (Climate Data Records) from 1982 to 2015, we built the first set of CDRs to record the annual dynamics of global land cover (GLASS-GLC) at 5 km resolution using the Google Earth Engine (GEE) platform. Compared to earlier global LC products, GLASS-GLC is characterized by high consistency, more detailed classes, and longer temporal coverage. The average overall accuracy is 85 %. We implemented a systematic uncertainty analysis at the global scale. In addition, we carried out a comprehensive spatiotemporal pattern analysis. Significant changes and patterns at various scales were found, including deforestation and agricultural land expansion in the tropics, afforestation and forest expansion in northern high latitudes, land degradation in Asian grassland and reclamation in northeast China, etc. A global quantitative analysis of human factors showed that the average human impact level in areas with significant LCC was about 25.49 %. The anthropogenic influence has a strong correlation with the noticeable Earth greening. Based on GLASS-GLC, we can conduct long-term LCC analysis, improve our understanding of global environmental change, and mitigate its negative impact. GLASS-GLC will be further applied in Earth system modeling in order to facilitate research on global carbon and water cycling, vegetation dynamics and climate change. |
| format | Dataset Open Access |
| id | pangaea_https___doi_org_10_1594_PANGAEA_898096 |
| institution | PANGAEA |
| language | en |
| publishDate | 2019 |
| publisher | PANGAEA |
| record_format | pangaea |
| spellingShingle | Annual dynamics of global land cover and its long-term changes from 1982 to 2015, link to GeoTIFF files Liu, Han Gong, Peng Wang, Jie Clinton, Nicholas Bai, Yuqi Liang, Shunlin Classification; Climate data records; Earth system model; GLASS; Global land cover; Google Earth Engine; Land cover; Land cover change; Land cover mapping; Long-term changes; Spatiotemporal pattern; Time series Land cover (LC) is an important terrestrial variable and key information for understanding the interaction between human activities and global change. As the cause and result of global environmental change, land cover change (LCC) influences the global energy balance and biogeochemical cycles. Continuous and dynamic monitoring of global LC is urgently needed. Effective monitoring and comprehensive analysis of LCC at the global scale is rare. Using the latest version of GLASS (The Global Land Surface Satellite) CDRs (Climate Data Records) from 1982 to 2015, we built the first set of CDRs to record the annual dynamics of global land cover (GLASS-GLC) at 5 km resolution using the Google Earth Engine (GEE) platform. Compared to earlier global LC products, GLASS-GLC is characterized by high consistency, more detailed classes, and longer temporal coverage. The average overall accuracy is 85 %. We implemented a systematic uncertainty analysis at the global scale. In addition, we carried out a comprehensive spatiotemporal pattern analysis. Significant changes and patterns at various scales were found, including deforestation and agricultural land expansion in the tropics, afforestation and forest expansion in northern high latitudes, land degradation in Asian grassland and reclamation in northeast China, etc. A global quantitative analysis of human factors showed that the average human impact level in areas with significant LCC was about 25.49 %. The anthropogenic influence has a strong correlation with the noticeable Earth greening. Based on GLASS-GLC, we can conduct long-term LCC analysis, improve our understanding of global environmental change, and mitigate its negative impact. GLASS-GLC will be further applied in Earth system modeling in order to facilitate research on global carbon and water cycling, vegetation dynamics and climate change. |
| title | Annual dynamics of global land cover and its long-term changes from 1982 to 2015, link to GeoTIFF files |
| topic | Classification; Climate data records; Earth system model; GLASS; Global land cover; Google Earth Engine; Land cover; Land cover change; Land cover mapping; Long-term changes; Spatiotemporal pattern; Time series |
| url | https://doi.org/10.1594/PANGAEA.898096 |