Multi-year global land cover mapping at 300 m and characterization for climate modelling: achievements of the Land Cover component of the ESA Climate Change Initiative

40 citations as recorded by crossref.

1. Spatiotemporal and Driving Factors of Land-Cover Change in the Heilongjiang (Amur) River Basin S. Jia & Y. Yang 10.3390/rs15153730
2. A machine learning-based classification of LANDSAT images to map land use and land cover of India R. Singh et al. 10.1016/j.rsase.2021.100624
3. Mapping Wetlands in Zambia Using Seasonal Backscatter Signatures Derived from ENVISAT ASAR Time Series S. Schlaffer et al. 10.3390/rs8050402
4. Fire foci dynamics and their relationship with socioenvironmental factors and meteorological systems in the state of Alagoas, Northeast Brazil J. de Oliveira-Júnior et al. 10.1007/s10661-020-08588-5
5. 1 km land use/land cover change of China under comprehensive socioeconomic and climate scenarios for 2020–2100 M. Luo et al. 10.1038/s41597-022-01204-w
6. Consistent yet adaptive global geospatial identification of urban–rural patterns: The iURBAN model C. Aubrecht et al. 10.1016/j.rse.2016.10.031
7. Fires in the South American Chaco, from dry forests to wetlands: response to climate depends on land cover R. San Martín et al. 10.1186/s42408-023-00212-4
8. Mapping global urban land for the 21st century with data-driven simulations and Shared Socioeconomic Pathways J. Gao & B. O’Neill 10.1038/s41467-020-15788-7
9. Patch-Based Local Climate Zones Mapping and Population Distribution Pattern in Provincial Capital Cities of China L. Zhou et al. 10.3390/ijgi11080420
10. Generating a series of land covers by assimilating the existing land cover maps G. Xu & B. Chen 10.1016/j.isprsjprs.2018.11.018
11. Satellite Observations of the Recovery of Forests and Grasslands in Western China C. Gang et al. 10.1029/2019JG005198
12. Variations of Annual Minimum Snow and Ice Extent over Canada and Neighboring Landmass Derived from MODIS 250-m Imagery for 2000–2014 A. Trishchenko et al. 10.1080/07038992.2016.1166043
13. A High-Resolution Cropland Map for the West African Sahel Based on High-Density Training Data, Google Earth Engine, and Locally Optimized Machine Learning K. Samasse et al. 10.3390/rs12091436
14. Improved Near‐Surface Continental Climate in IPSL‐CM6A‐LR by Combined Evolutions of Atmospheric and Land Surface Physics F. Cheruy et al. 10.1029/2019MS002005
15. The assessment of climatic, environmental, and socioeconomic aspects of the Brazilian Cerrado W. Correia Filho et al. 10.1186/s13717-023-00433-0
16. Investigating the Use of Street-Level Imagery and Deep Learning to Produce In-Situ Crop Type Information F. Orduna-Cabrera et al. 10.3390/geographies3030029
17. Combining Multi-Source Data and Feature Optimization for Plastic-Covered Greenhouse Extraction and Mapping Using the Google Earth Engine: A Case in Central Yunnan Province, China J. Li et al. 10.3390/rs15133287
18. Machine learning based combinatorial analysis for land use and land cover assessment in Kyiv City (Ukraine) V. Belenok et al. 10.1117/1.JRS.17.014506
19. The impacts of land conversion and management measures on the grassland net primary productivity over the Loess Plateau, Northern China C. Gang et al. 10.1016/j.scitotenv.2018.07.161
20. Daily Simulation of the Rainfall–Runoff Relationship in the Sirba River Basin in West Africa: Insights from the HEC-HMS Model I. Souley Tangam et al. 10.3390/hydrology11030034
21. A patch-based algorithm for global and daily burned area mapping M. Campagnolo et al. 10.1016/j.rse.2019.111288
22. Substantial terrestrial carbon emissions from global expansion of impervious surface area L. Qiu et al. 10.1038/s41467-024-50840-w
23. Divergent Performances of Vegetation Indices in Extracting Photosynthetic Phenology for Northern Deciduous Broadleaf Forests Y. Yang et al. 10.1109/LGRS.2022.3182405
24. Automatic Multi-Temporal Land Cover Mapping with Medium Spatial Resolution Using the Model Migration Method R. Chen et al. 10.3390/rs17010037
25. Investigating the spatiotemporal changes and driving factors of nighttime light patterns in RCEP Countries based on remote sensed satellite images J. Li et al. 10.1016/j.jclepro.2022.131944
26. Mapping High-Resolution Global Impervious Surface Area: Status and Trends H. Ren et al. 10.1109/JSTARS.2022.3201380
27. Utilizing Artificial Intelligence and Remote Sensing to Detect Prosopis juliflora Invasion: Environmental Drivers and Community Insights in Rangelands of Kenya A. Paliwal et al. 10.3390/plants13131868
28. Modeling subgrid lake energy balance in ORCHIDEE terrestrial scheme using the FLake lake model A. Bernus & C. Ottlé 10.5194/gmd-15-4275-2022
29. Continued Increases of Gross Primary Production in Urban Areas during 2000–2016 Y. Cui et al. 10.34133/2022/9868564
30. Evaluation and analysis of upscaling of different land use/land cover products (FORM-GLC30, GLC_FCS30, CCI_LC, MCD12Q1 and CNLUCC): a case study in China S. He et al. 10.1080/10106049.2022.2127926
31. A multinomial logistic model-based land use and land cover classification for the South Asian Association for Regional Cooperation nations using Moderate Resolution Imaging Spectroradiometer product R. Singh et al. 10.1007/s10668-020-00864-1
32. Change of permanent grasslands extent (1996-2015) and national grassland dataset of Switzerland S. Schmidt et al. 10.1016/j.dib.2018.09.039
33. Spatial mapping and driving factor Identification for salt-affected soils at continental scale using Machine learning methods Y. Liu et al. 10.1016/j.jhydrol.2024.131589
34. Confronting Soil Moisture Dynamics from the ORCHIDEE Land Surface Model With the ESA-CCI Product: Perspectives for Data Assimilation N. Raoult et al. 10.3390/rs10111786
35. Choosing pasture maps: An assessment of pasture land classification definitions and a case study of Brazil J. Oliveira et al. 10.1016/j.jag.2020.102205
36. Satellite-derived multivariate world-wide lake physical variable timeseries for climate studies L. Carrea et al. 10.1038/s41597-022-01889-z
37. Soil and Water Bioengineering in Fire-Prone Lands: Detecting Erosive Areas Using RUSLE and Remote Sensing Methods M. Maxwald et al. 10.3390/fire7090319
38. Quantitative evidence for leapfrogging in urban growth M. Glockmann et al. 10.1177/2399808321998713
39. Validation of MCD64A1 and FireCCI51 cropland burned area mapping in Ukraine J. Hall et al. 10.1016/j.jag.2021.102443
40. Land system changes of terrestrial tipping elements on Earth under global climate pledges: 2000–2100 J. Lv et al. 10.1038/s41597-025-04444-8