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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47 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
- Using Time Series Optical and SAR Data to Assess the Impact of Historical Wetland Change on Current Wetland in Zhenlai County, Jilin Province, China S. Shi et al. 10.3390/rs13224514
- 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
- Blue-Sky Albedo Reduction and Associated Influencing Factors of Stable Land Cover Types in the Middle-High Latitudes of the Northern Hemisphere during 1982–2015 S. Yuan et al. 10.3390/rs14040895
- Gradient Boosting Machine and Object-Based CNN for Land Cover Classification Q. Bui et al. 10.3390/rs13142709
- Effects of ecological projects on vegetation in the Three Gorges Area of Chongqing, China F. Li et al. 10.1007/s11629-021-6768-5
- Tropospheric Ozone Perturbations Induced by Urban Land Expansion in China from 1980 to 2017 X. Zhang et al. 10.1021/acs.est.1c06664
- Satellite Image Time Series Clustering via Time Adaptive Optimal Transport Z. Zhang et al. 10.3390/rs13193993
- A Modified Self-adaptive Method for Mapping Annual 30-m Land Use/Land Cover Using Google Earth Engine: A Case Study of Yangtze River Delta L. Qu et al. 10.1007/s11769-021-1226-4
- Heterogeneity of land cover data with discrete classes obscured remotely-sensed detection of sensitivity of forest photosynthesis to climate J. Jin et al. 10.1016/j.jag.2021.102567
- On the potential of documenting decadal-scale avifaunal change from before-and-after comparisons of museum and observational data across North America F. Machado-Stredel et al. 10.1016/j.avrs.2022.100005
- 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
- Recent Developments in Some Long-Term Drought Drivers A. de Jager et al. 10.3390/cli10030031
- Future land-use changes and its impacts on terrestrial ecosystem services: A review E. Gomes et al. 10.1016/j.scitotenv.2021.146716
- Did Climate Change Influence the Emergence, Transmission, and Expression of the COVID-19 Pandemic? S. Gupta et al. 10.3389/fmed.2021.769208
- 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
- An Interannual Transfer Learning Approach for Crop Classification in the Hetao Irrigation District, China Y. Hu et al. 10.3390/rs14051208
- 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
- The dataset of walled cities and urban extent in late imperial China in the 15th–19th centuries Q. Xue et al. 10.5194/essd-13-5071-2021
- Time series analysis for global land cover change monitoring: A comparison across sensors L. Xu et al. 10.1016/j.rse.2022.112905
- The Effects of Financial Development and Pandemics Prevalence on Forests: Evidence From Asia-Pacific Region J. Wang et al. 10.3389/fenvs.2022.850724
- Effects of Cropland Expansion on Temperature Extremes in Western India from 1982 to 2015 J. Liu et al. 10.3390/land10050489
- Trends in Lakeshore Zone Development: A Comparison of Polish and Hungarian Lakes over 30-Year Period G. Furgała-Selezniow et al. 10.3390/ijerph19042141
- 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
- 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
- GCI30: a global dataset of 30 m cropping intensity using multisource remote sensing imagery M. Zhang et al. 10.5194/essd-13-4799-2021
- Crop production response to soil moisture and groundwater depletion in the Nile Basin based on multi-source data Z. Nigatu et al. 10.1016/j.scitotenv.2022.154007
- Comparison of time-integrated NDVI and annual maximum NDVI for assessing grassland dynamics J. Yan et al. 10.1016/j.ecolind.2022.108611
- 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
- Land Cover and Land Use Mapping of the East Asian Summer Monsoon Region from 1982 to 2015 Y. He et al. 10.3390/land11030391
- 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
- Mapping the annual dynamics of land cover in Beijing from 2001 to 2020 using Landsat dense time series stack S. Xie et al. 10.1016/j.isprsjprs.2022.01.014
- 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
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- Buen Vivir and forest conservation in Bolivia: False promises or effective change? F. Cappelli et al. 10.1016/j.forpol.2022.102695
- 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: 25 Jun 2022
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...