30 citations as recorded by crossref.

1. Mapping and classification of Liao River Delta coastal wetland based on time series and multi-source GaoFen images using stacking ensemble model H. Qian et al. 10.1016/j.ecoinf.2024.102488
2. A Satellite View of the Wetland Transformation Path and Associated Drivers in the Greater Bay Area of China during the Past Four Decades K. Sun & W. Yu 10.3390/rs16061047
3. Analysis of mangrove dynamics and its protection effect in the Guangdong-Hong Kong-Macao Coastal Area based on the Google Earth Engine platform J. Zeng et al. 10.3389/fmars.2023.1170587
4. Coastal wetland degradation and ecosystem service value change in the Yellow River Delta, China J. Yan et al. 10.1016/j.gecco.2023.e02501
5. An improved global land cover mapping in 2015 with 30 m resolution (GLC-2015) based on a multisource product-fusion approach B. Li et al. 10.5194/essd-15-2347-2023
6. Exploring the impact of urbanization on flood characteristics with the SCS-TRITON method H. Yu et al. 10.1007/s11069-023-06324-z
7. Policy instruments as a trigger for urban sprawl deceleration: monitoring the stability and transformations of green areas K. Filepné Kovács et al. 10.1038/s41598-024-52637-9
8. GLC_FCS30D: the first global 30 m land-cover dynamics monitoring product with a fine classification system for the period from 1985 to 2022 generated using dense-time-series Landsat imagery and the continuous change-detection method X. Zhang et al. 10.5194/essd-16-1353-2024
9. Global annual wetland dataset at 30 m with a fine classification system from 2000 to 2022 X. Zhang et al. 10.1038/s41597-024-03143-0
10. National Scale Land Cover Classification Using the Semiautomatic High-Quality Reference Sample Generation (HRSG) Method and an Adaptive Supervised Classification Scheme A. Naboureh et al. 10.1109/JSTARS.2023.3241620
11. A review of regional and Global scale Land Use/Land Cover (LULC) mapping products generated from satellite remote sensing Y. Wang et al. 10.1016/j.isprsjprs.2023.11.014
12. Mapping Phenology of Complicated Wetland Landscapes through Harmonizing Landsat and Sentinel-2 Imagery C. Fan et al. 10.3390/rs15092413
13. Agreement Analysis and Accuracy Assessment of Multiple Mangrove Datasets in Guangxi Beibu Gulf and Guangdong-Hong Kong-Macau Greater Bay, China, for 2000–2020 Z. Xiao et al. 10.1109/JSTARS.2024.3353251
14. Land cover dataset of the China Central-Asia West-Asia Economic Corridor from 1993 to 2018 A. Naboureh et al. 10.1038/s41597-023-02623-z
15. Remote Data for Mapping and Monitoring Coastal Phenomena and Parameters: A Systematic Review R. Cavalli 10.3390/rs16030446
16. Automated and refined wetland mapping of Dongting Lake using migrated training samples based on temporally dense Sentinel 1/2 imagery Y. Deng et al. 10.1080/17538947.2023.2241428
17. Assessing urban wetlands dynamics in Wuhan and Nanchang, China Y. Deng et al. 10.1016/j.scitotenv.2023.165777
18. Distribution and Storage Characteristics of Soil Organic Carbon in Tidal Wetland of Dandou Sea, Guangxi M. Wang et al. 10.3390/atmos15040431
19. Evaluation of Remote Sensing Products for Wetland Mapping in the Irtysh River Basin K. Luo et al. 10.3390/geosciences14010014
20. A New Method for Bare Permafrost Extraction on the Tibetan Plateau by Integrating Machine Learning and Multi-Source Information X. Li et al. 10.3390/rs15225328
21. Mapping global non-floodplain wetlands C. Lane et al. 10.5194/essd-15-2927-2023
22. Automated Mapping of Global 30-m Tidal Flats Using Time-Series Landsat Imagery: Algorithm and Products X. Zhang et al. 10.34133/remotesensing.0091
23. Mapping wetlands in Northeast China by using knowledge-based algorithms and microwave (PALSAR-2, Sentinel-1), optical (Sentinel-2, Landsat), and thermal (MODIS) images C. Zhang et al. 10.1016/j.jenvman.2023.119618
24. Characterizing the Accelerated Global Carbon Emissions from Forest Loss during 1985–2020 Using Fine-Resolution Remote Sensing Datasets W. Liu et al. 10.3390/rs16060978
25. Vegetation Classification and Evaluation of Yancheng Coastal Wetlands Based on Random Forest Algorithm from Sentinel-2 Images Y. Wang et al. 10.3390/rs16071124
26. The Wetland Intrinsic Potential tool: mapping wetland intrinsic potential through machine learning of multi-scale remote sensing proxies of wetland indicators M. Halabisky et al. 10.5194/hess-27-3687-2023
27. Fine Extraction of Plateau Wetlands Based on a Combination of Object-Oriented Machine Learning and Ecological Rules: A Case Study of Dianchi Basin F. Cai et al. 10.1109/JSTARS.2024.3356656
28. Using Multisource High-Resolution Remote Sensing Data (2 m) with a Habitat–Tide–Semantic Segmentation Approach for Mangrove Mapping Z. Sun et al. 10.3390/rs15225271
29. Fine-grained wetland classification for national wetland reserves using multi-source remote sensing data and Pixel Information Expert Engine (PIE-Engine) H. Liu et al. 10.1080/15481603.2023.2286746
30. GWL_FCS30: a global 30 m wetland map with a fine classification system using multi-sourced and time-series remote sensing imagery in 2020 X. Zhang et al. 10.5194/essd-15-265-2023