Articles | Volume 12, issue 2
Earth Syst. Sci. Data, 12, 1217–1243, 2020
https://doi.org/10.5194/essd-12-1217-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Earth Syst. Sci. Data, 12, 1217–1243, 2020
https://doi.org/10.5194/essd-12-1217-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper 03 Jun 2020
Data description paper | 03 Jun 2020
Annual dynamics of global land cover and its long-term changes from 1982 to 2015
Han Liu et al.
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Cited
21 citations as recorded by crossref.
- Spatiotemporal variation of enhanced vegetation index in the Amazon Basin and its response to climate change R. Zhong et al. 10.1016/j.pce.2021.103024
- Changes in different land cover areas and NDVI values in northern latitudes from 1982 to 2015 S. Xue et al. 10.1016/j.accre.2021.04.003
- Effects of Cropland Expansion on Temperature Extremes in Western India from 1982 to 2015 J. Liu et al. 10.3390/land10050489
- Decreasing control of precipitation on grassland spring phenology in temperate China Y. Fu et al. 10.1111/geb.13234
- The land–energy–water nexus of global bioenergy potentials from abandoned cropland J. Næss et al. 10.1038/s41893-020-00680-5
- Spatio-temporal analysis and simulation of land cover changes and their impacts on land surface temperature in urban agglomeration of Bisha Watershed, Saudi Arabia J. Mallick et al. 10.1080/10106049.2021.1980616
- Gradient Boosting Machine and Object-Based CNN for Land Cover Classification Q. Bui et al. 10.3390/rs13142709
- The 30 m annual land cover dataset and its dynamics in China from 1990 to 2019 J. Yang & X. Huang 10.5194/essd-13-3907-2021
- An integrated assessment of runoff dynamics in the Amu Darya River Basin: Confronting climate change and multiple human activities, 1960–2017 Y. Hu et al. 10.1016/j.jhydrol.2021.126905
- Mapping Land Use/Cover Dynamics of the Yellow River Basin from 1986 to 2018 Supported by Google Earth Engine Q. Ji et al. 10.3390/rs13071299
- Implementation of an Improved Water Change Tracking (IWCT) Algorithm: Monitoring the Water Changes in Tianjin over 1984–2019 Using Landsat Time-Series Data X. Han et al. 10.3390/rs13030493
- Shifts in global bat diversity suggest a possible role of climate change in the emergence of SARS-CoV-1 and SARS-CoV-2 R. Beyer et al. 10.1016/j.scitotenv.2021.145413
- Future land-use changes and its impacts on terrestrial ecosystem services: A review E. Gomes et al. 10.1016/j.scitotenv.2021.146716
- Production of global daily seamless data cubes and quantification of global land cover change from 1985 to 2020 - iMap World 1.0 H. Liu et al. 10.1016/j.rse.2021.112364
- Soil Moisture Mapping Based on Multi-Source Fusion of Optical, Near-Infrared, Thermal Infrared, and Digital Elevation Model Data via the Bayesian Maximum Entropy Framework L. Han et al. 10.3390/rs12233916
- Evaluation of the influence of ENSO on tropical vegetation in long time series using a new indicator Y. Yan et al. 10.1016/j.ecolind.2021.107872
- Intra-annual land cover mapping and dynamics analysis with dense satellite image time series: a spatiotemporal cube based spatiotemporal contextual method W. Xi et al. 10.1080/15481603.2021.1973216
- Global land use changes are four times greater than previously estimated K. Winkler et al. 10.1038/s41467-021-22702-2
- New insights of global vegetation structural properties through an analysis of canopy clumping index, fractional vegetation cover, and leaf area index H. Fang et al. 10.1016/j.srs.2021.100027
- Spatial resolution enhancement method for Landsat imagery using a Generative Adversarial Network V. Pham & Q. Bui 10.1080/2150704X.2021.1918789
- Developing Long Time Series 1-km Land Cover Maps From 5-km AVHRR Data Using a Super-Resolution Method H. Wang et al. 10.1109/TGRS.2020.3018109
21 citations as recorded by crossref.
- Spatiotemporal variation of enhanced vegetation index in the Amazon Basin and its response to climate change R. Zhong et al. 10.1016/j.pce.2021.103024
- Changes in different land cover areas and NDVI values in northern latitudes from 1982 to 2015 S. Xue et al. 10.1016/j.accre.2021.04.003
- Effects of Cropland Expansion on Temperature Extremes in Western India from 1982 to 2015 J. Liu et al. 10.3390/land10050489
- Decreasing control of precipitation on grassland spring phenology in temperate China Y. Fu et al. 10.1111/geb.13234
- The land–energy–water nexus of global bioenergy potentials from abandoned cropland J. Næss et al. 10.1038/s41893-020-00680-5
- Spatio-temporal analysis and simulation of land cover changes and their impacts on land surface temperature in urban agglomeration of Bisha Watershed, Saudi Arabia J. Mallick et al. 10.1080/10106049.2021.1980616
- Gradient Boosting Machine and Object-Based CNN for Land Cover Classification Q. Bui et al. 10.3390/rs13142709
- The 30 m annual land cover dataset and its dynamics in China from 1990 to 2019 J. Yang & X. Huang 10.5194/essd-13-3907-2021
- An integrated assessment of runoff dynamics in the Amu Darya River Basin: Confronting climate change and multiple human activities, 1960–2017 Y. Hu et al. 10.1016/j.jhydrol.2021.126905
- Mapping Land Use/Cover Dynamics of the Yellow River Basin from 1986 to 2018 Supported by Google Earth Engine Q. Ji et al. 10.3390/rs13071299
- Implementation of an Improved Water Change Tracking (IWCT) Algorithm: Monitoring the Water Changes in Tianjin over 1984–2019 Using Landsat Time-Series Data X. Han et al. 10.3390/rs13030493
- Shifts in global bat diversity suggest a possible role of climate change in the emergence of SARS-CoV-1 and SARS-CoV-2 R. Beyer et al. 10.1016/j.scitotenv.2021.145413
- Future land-use changes and its impacts on terrestrial ecosystem services: A review E. Gomes et al. 10.1016/j.scitotenv.2021.146716
- Production of global daily seamless data cubes and quantification of global land cover change from 1985 to 2020 - iMap World 1.0 H. Liu et al. 10.1016/j.rse.2021.112364
- Soil Moisture Mapping Based on Multi-Source Fusion of Optical, Near-Infrared, Thermal Infrared, and Digital Elevation Model Data via the Bayesian Maximum Entropy Framework L. Han et al. 10.3390/rs12233916
- Evaluation of the influence of ENSO on tropical vegetation in long time series using a new indicator Y. Yan et al. 10.1016/j.ecolind.2021.107872
- Intra-annual land cover mapping and dynamics analysis with dense satellite image time series: a spatiotemporal cube based spatiotemporal contextual method W. Xi et al. 10.1080/15481603.2021.1973216
- Global land use changes are four times greater than previously estimated K. Winkler et al. 10.1038/s41467-021-22702-2
- New insights of global vegetation structural properties through an analysis of canopy clumping index, fractional vegetation cover, and leaf area index H. Fang et al. 10.1016/j.srs.2021.100027
- Spatial resolution enhancement method for Landsat imagery using a Generative Adversarial Network V. Pham & Q. Bui 10.1080/2150704X.2021.1918789
- Developing Long Time Series 1-km Land Cover Maps From 5-km AVHRR Data Using a Super-Resolution Method H. Wang et al. 10.1109/TGRS.2020.3018109
Latest update: 19 Sep 2021
Short summary
We built the first set of 5 km resolution CDRs to record the annual dynamics of global land cover (GLASS-GLC) from 1982 to 2015. The average overall accuracy is 82 %. By conducting long-term change analysis, significant land cover changes and spatiotemporal patterns at various scales were found, which can improve our understanding of global environmental change and help achieve sustainable development goals. This will be further applied in Earth system modeling to facilitate relevant studies.
We built the first set of 5 km resolution CDRs to record the annual dynamics of global land...
