421 citations as recorded by crossref.

1. The Verification of Land Cover Datasets with the Geo-Tagged Natural Scene Images L. Cui et al. 10.3390/ijgi11110567
2. Improved Fine-Scale Tropical Forest Cover Mapping for Southeast Asia Using Planet-NICFI and Sentinel-1 Imagery F. Yang et al. 10.34133/remotesensing.0064
3. Deep-learning spatial principles from deterministic chemical transport models for chemical reanalysis: an application in China for PM<sub>2.5</sub> B. Lyu et al. 10.5194/gmd-15-1583-2022
4. Mapping annual center-pivot irrigated cropland in Brazil during the 1985–2021 period with cloud platforms and deep learning X. Liu et al. 10.1016/j.isprsjprs.2023.10.007
5. Runoff changes in the major river basins of China and their responses to potential driving forces L. Yang et al. 10.1016/j.jhydrol.2022.127536
6. Fine-Resolution Forest Height Estimation by Integrating ICESat-2 and Landsat 8 OLI Data with a Spatial Downscaling Method for Aboveground Biomass Quantification Y. Wang et al. 10.3390/f14071414
7. Spatio-Temporal Heterogeneity of the Ecological Environment and Its Response to Land Use Change in the Chushandian Reservoir Basin Y. Fang et al. 10.3390/su16041385
8. Water Deficit Caused by Land Use Changes and Its Implications on the Ecological Protection of the Endorheic Dalinor Lake Watershed in Inner Mongolia, China L. Wang et al. 10.3390/w15162882
9. Spatiotemporal Patterns of Heavy-Metal Pollution in Coastal Pinqing Lagoon (Southern China): Anthropogenic and Hydrological Effect G. Huang et al. 10.3390/w15173126
10. Spatial and temporal variation of multiple eco-environmental indicators in Erhai Lake Basin of China under land use transitions Y. Dong et al. 10.1007/s11356-022-23279-z
11. The potential of optical and SAR time-series data for the improvement of aboveground biomass carbon estimation in Southwestern China’s evergreen coniferous forests Y. Zhang et al. 10.1080/15481603.2024.2345438
12. Spatial-Temporal Pattern and Driving Forces of Fractional Vegetation Coverage in Xiong’an New Area of China from 2005 to 2019 Z. Huang et al. 10.3390/su151511985
13. Urban heat vulnerability: A dynamic assessment using multi-source data in coastal metropolis of Southeast China C. Wu et al. 10.3389/fpubh.2022.989963
14. The Association between Carbon Emission and Urban Spatial Form—A Study of Zhuhai, China Y. Zhang et al. 10.3390/land12030720
15. Assessing urban wetlands dynamics in Wuhan and Nanchang, China Y. Deng et al. 10.1016/j.scitotenv.2023.165777
16. Different Urbanization Levels Lead to Divergent Responses of Spring Phenology C. Dang et al. 10.14358/PERS.23-00008R2
17. A Comparison of Seven Medium Resolution Impervious Surface Products on the Qinghai–Tibet Plateau, China from a User’s Perspective K. Zheng et al. 10.3390/rs15092366
18. Using Eco-Geographical Zoning Data and Crowdsourcing to Improve the Detection of Spurious Land Cover Changes L. Zhu et al. 10.3390/rs13163244
19. Driving forces behind the spatiotemporal heterogeneity of land-use and land-cover change: A case study of the Weihe River Basin, China J. Wu et al. 10.1007/s40333-023-0052-1
20. Evaluation of Remote Sensing Products for Wetland Mapping in the Irtysh River Basin K. Luo et al. 10.3390/geosciences14010014
21. Are there suitable global datasets for monitoring of land use and land cover in the tropics? Evidences from mainland Southeast Asia J. Zhai et al. 10.1016/j.gloplacha.2023.104233
22. Regional organic matter and mineral dust are the main components of atmospheric aerosols over the Nam Co station on the central Tibetan Plateau in summer H. Zhang et al. 10.3389/fenvs.2022.1055673
23. Warming lake surface water temperatures in Lake Qiandaohu, China: Spatiotemporal variations, influencing factors and implications for the thermal structure Y. Li et al. 10.3389/fenvs.2022.995862
24. Regional estimation of dead fuel moisture content in southwest China based on a practical process-based model C. Fan et al. 10.1071/WF22209
25. Globe230k: A Benchmark Dense-Pixel Annotation Dataset for Global Land Cover Mapping Q. Shi et al. 10.34133/remotesensing.0078
26. Assessing the Accuracy and Consistency of Six Fine-Resolution Global Land Cover Products Using a Novel Stratified Random Sampling Validation Dataset T. Zhao et al. 10.3390/rs15092285
27. Identifying Grassland Distribution in a Mountainous Region in Southwest China Using Multi-Source Remote Sensing Images Y. Yuan et al. 10.3390/rs14061472
28. Impact of road network expansion on landscape ecological risk and soil erosion sensitivity on the Luochuan Tableland of the Chinese Loess Plateau S. Yang & Z. Jin 10.1007/s10113-024-02202-x
29. Dynamic multiobjective two-stage fuzzy stochastic strategy for optimal water allocation in inter-basin water division under changing environment: A case study of Hanjiang-to-Weihe water division in Shaanxi Province, China H. Zhang et al. 10.1016/j.jclepro.2024.142175
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31. 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
32. HiLPD-GEE: high spatial resolution land productivity dynamics calculation tool using Landsat and MODIS data T. Shen et al. 10.1080/17538947.2023.2179675
33. Spatial-temporal pattern of desertification in the Selenge River Basin of Mongolia from 1990 to 2020 S. Xu et al. 10.3389/fenvs.2023.1125583
34. A Study on Urban-Scale Building, Tree Canopy Footprint Identification and Sky View Factor Analysis with Airborne LiDAR Remote Sensing Data S. An 10.3390/rs15153910
35. Urban water bodies in China: Spatial distribution patterns, temporal change characteristics, and relationship with economic development Y. Deng et al. 10.1016/j.ecolind.2023.111139
36. Prediction of the joint impacts of sea level rise and land development on distribution patterns of mangrove communities S. Liang et al. 10.1016/j.fecs.2023.100100
37. Satellite data-driven multi-objective simulation-optimization modeling for water-environment-agriculture nexus in an arid endorheic lake basin J. Song et al. 10.1016/j.jhydrol.2022.128207
38. Breaking the resolution barrier: A low-to-high network for large-scale high-resolution land-cover mapping using low-resolution labels Z. Li et al. 10.1016/j.isprsjprs.2022.08.008
39. Decline in Planting Areas of Double-Season Rice by Half in Southern China over the Last Two Decades W. Zhu et al. 10.3390/rs16030440
40. Mapping evergreen forests using new phenology index, time series Sentinel-1/2 and Google Earth Engine R. Li et al. 10.1016/j.ecolind.2023.110157
41. Regimes of global and national oil palm cultivations from 2001 to 2018 H. Yu et al. 10.1016/j.gloenvcha.2024.102845
42. A spatiotemporal ensemble machine learning framework for generating land use/land cover time-series maps for Europe (2000–2019) based on LUCAS, CORINE and GLAD Landsat M. Witjes et al. 10.7717/peerj.13573
43. Spatiotemporal variation in ecosystem health caused by land use and land cover change in Pakistan H. Zhao & X. Deng 10.34133/ehs.0161
44. Evaluation of six global high-resolution global land cover products over China Y. Wang et al. 10.1080/17538947.2023.2301673
45. Very Rapid Forest Cover Change in Sichuan Province, China: 40 Years of Change Using Images From Declassified Spy Satellites and Landsat D. Song et al. 10.1109/JSTARS.2021.3121260
46. Changes in the global fine composition of forests from 2001 to 2020. H. Xu et al. 10.34133/remotesensing.0119
47. Contrastive Analysis and Accuracy Assessment of Three Global 30 m Land Cover Maps Circa 2020 in Arid Land Q. Bie et al. 10.3390/su15010741
48. A platform for land use and land cover data integration and trajectory analysis F. Zioti et al. 10.1016/j.jag.2021.102655
49. An optimal method for validating satellite-derived land surface phenology using in-situ observations from national phenology networks Y. Ye et al. 10.1016/j.isprsjprs.2022.09.018
50. Assessment of vegetation restoration impacts on soil erosion control services based on a biogeochemical model and RUSLE P. Li et al. 10.1016/j.ejrh.2024.101830
51. Comparison and Assessment of Different Land Cover Datasets on the Cropland in Northeast China P. Cui et al. 10.3390/rs15215134
52. MLC30: A New 30 m Land Cover Dataset for Myanmar From 1990 to 2020 Using Training Sample Migration Framework H. Xing et al. 10.1109/JSTARS.2023.3328309
53. Research on the sustainability of "greening" process in the Mu Us Sandy Land based on the spatiotemporal stability of ecological land Q. Zhang et al. 10.1371/journal.pone.0292469
54. An Optimal Transport Based Global Similarity Index for Remote Sensing Products Comparison Y. Tan et al. 10.3390/rs14112546
55. Monitoring Cropland Abandonment in Hilly Areas with Sentinel-1 and Sentinel-2 Timeseries S. He et al. 10.3390/rs14153806
56. Geographical Supervision Correction for Remote Sensing Representation Learning W. Li et al. 10.1109/TGRS.2022.3202499
57. User-Aware Evaluation for Medium-Resolution Forest-Related Datasets in China: Reliability and Spatial Consistency X. Peng et al. 10.3390/rs15102557
58. Testing Accuracy of Land Cover Classification Algorithms in the Qilian Mountains Based on GEE Cloud Platform Y. Yang et al. 10.3390/rs13245064
59. Distribution and Storage Characteristics of Soil Organic Carbon in Tidal Wetland of Dandou Sea, Guangxi M. Wang et al. 10.3390/atmos15040431
60. Evolution of spatiotemporal patterns in vegetation net primary productivity and the driving forces on the Loess Plateau S. Mao & Z. Shangguan 10.3389/fenvs.2023.1134917
61. 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
62. Developing a Land Continuous Variable Estimator to Generate Daily Land Products From Landsat Data H. Ma et al. 10.1109/TGRS.2021.3121272
63. Mapping Irrigated Croplands from Sentinel-2 Images Using Deep Convolutional Neural Networks W. Li et al. 10.3390/rs15164071
64. Global hydro-environmental lake characteristics at high spatial resolution B. Lehner et al. 10.1038/s41597-022-01425-z
65. Spatio-Temporal Patterns of Land-Use Changes and Conflicts between Cropland and Forest in the Mekong River Basin during 1990–2020 J. Zhai et al. 10.3390/land11060927
66. Estimation of the value of regional ecosystem services of an archipelago using satellite remote sensing technology: A case study of Zhoushan Archipelago, China L. Wang et al. 10.1016/j.jag.2021.102616
67. Mapping Cropland Abandonment in Mountainous Areas in China Using the Google Earth Engine Platform S. Xu et al. 10.3390/rs15041145
68. Soil Moisture Retrieval From Sentinel-1 and Sentinel-2 Data Using Ensemble Learning Over Vegetated Fields L. Wang & Y. Gao 10.1109/JSTARS.2023.3242264
69. The Different Impacts of Climate Variability and Human Activities on NPP in the Guangdong–Hong Kong–Macao Greater Bay Area Y. Wu et al. 10.3390/rs14122929
70. Refining historical burned area data from satellite observations V. Fernández-García & C. Kull 10.1016/j.jag.2023.103350
71. Active landslide detection using integrated remote sensing technologies for a wide region and multiple stages: A case study in southwestern China H. Lu et al. 10.1016/j.scitotenv.2024.172709
72. The urgent need to develop a new grassland map in China: based on the consistency and accuracy of ten land cover products M. Hou et al. 10.1007/s11427-021-2143-3
73. IrriMap_CN: Annual irrigation maps across China in 2000–2019 based on satellite observations, environmental variables, and machine learning C. Zhang et al. 10.1016/j.rse.2022.113184
74. Machine Learning for Global Bioclimatic Classification: Enhancing Land Cover Prediction through Random Forests M. Sparey et al. 10.3390/atmos15060700
75. Forest Landscape Model Initialization with Remotely Sensed-Based Open-Source Databases in the Absence of Inventory Data I. Bychkov & A. Popova 10.3390/f14101995
76. Rural agriculture largely reduces the urban heating effects in China: A tale of the three most developed urban agglomerations Z. Yan & D. Zhou 10.1016/j.agrformet.2023.109343
77. Water yield of the Volta Basin under future land use and climate change D. Ocloo 10.1007/s10668-023-03977-5
78. Mapping the Distribution and Dynamics of Coniferous Forests in Large Areas from 1985 to 2020 Combining Deep Learning and Google Earth Engine L. Liu et al. 10.3390/rs15051235
79. Road network expansion and its impact on landscape patterns in the Dongzhi tableland of the Chinese Loess Plateau S. Yang et al. 10.1007/s11442-023-2189-4
80. Mining Hierarchical Information of CNNs for Scene Classification of VHR Remote Sensing Images K. Xu et al. 10.1109/TBDATA.2022.3196314
81. Simulation of Land Use Based on Multiple Models in the Western Sichuan Plateau X. Yu et al. 10.3390/rs15143629
82. Spatial Simulation and Prediction of Land Use/Land Cover in the Transnational Ili-Balkhash Basin J. Kou et al. 10.3390/rs15123059
83. Land Use and Land Cover Mapping in China Using Multimodal Fine-Grained Dual Network S. Liu et al. 10.1109/TGRS.2023.3285912
84. High Resolution, Annual Maps of Field Boundaries for Smallholder-Dominated Croplands at National Scales L. Estes et al. 10.3389/frai.2021.744863
85. Ecosystem Service Flow Perspective of Urban Green Land: Spatial Simulation and Driving Factors of Cooling Service Flow Y. Zhou et al. 10.3390/land12081527
86. Spatial Heterogeneity of Vegetation Resilience Changes to Different Drought Types Y. Zhang et al. 10.1029/2022EF003108
87. Simulation of land-cover change in Jing-Jin-Ji region under different scenarios of SSP-RCP Z. Fan 10.1007/s11442-022-1955-z
88. Do more efficient transport facilities improve habitat quality? Evidence from China H. Bai & L. Weng 10.1016/j.scs.2024.105243
89. Tracking the historical urban development by classifying Landsat MSS data with training samples migrated across time and space Z. Feng et al. 10.1080/17538947.2023.2230951
90. Quantifying the influence of long-term overexploitation on deep groundwater resources across Cangzhou in the North China Plain using InSAR measurements L. Bai et al. 10.1016/j.jhydrol.2021.127368
91. Changes in Vegetation NDVI and Its Response to Climate Change and Human Activities in the Ferghana Basin from 1982 to 2015 H. Zhang et al. 10.3390/rs16071296
92. Thermal remote sensing for mapping the sub-Arctic permafrost and refining its southern limits C. Wang et al. 10.1016/j.jag.2023.103235
93. Hydro-Climatic and Vegetation Dynamics Spatial-Temporal Changes in the Great Lakes Depression Region of Mongolia B. Dorjsuren et al. 10.3390/w15213748
94. Global mapping of forest clumping index based on GEDI canopy height and complementary data X. Zhao et al. 10.1016/j.isprsjprs.2024.01.014
95. An ecologically-constrained deep learning model for tropical leaf phenology monitoring using PlanetScope satellites J. Wang et al. 10.1016/j.rse.2022.113429
96. Spatiotemporal Conflict Analysis and Prediction of Long Time Series Land Cover Changes in the Black Soil Region of Northeast China Using Remote Sensing and GIS D. Ma et al. 10.3390/ijgi12070271
97. Spatiotemporal characteristics and the national variations of borderland use change in Laos within the geopolinomical context Y. Wang & C. Xiao 10.3389/ffgc.2023.1223605
98. Generating 2m fine-scale urban tree cover product over 34 metropolises in China based on deep context-aware sub-pixel mapping network D. He et al. 10.1016/j.jag.2021.102667
99. Flood Monitoring by Integrating Normalized Difference Flood Index and Probability Distribution of Water Bodies F. Xue et al. 10.1109/JSTARS.2022.3176388
100. Annually Spatial Pattern Dynamics of Forest Types under a Rapid Expansion of Impervious Surfaces: A Case Study of Hangzhou City Y. Zhu et al. 10.3390/f15010044
101. Identification of the Spring Green-Up Date Derived from Satellite-Based Vegetation Index over a Heterogeneous Ecoregion J. Wu et al. 10.3390/rs14174349
102. Diversity and conservation of higher plants in Northwest Yunnan-Southeast Tibet W. Li et al. 10.1016/j.gecco.2023.e02396
103. Map of Land Cover Agreement: Ensambling Existing Datasets for Large-Scale Training Data Provision G. Bratic et al. 10.3390/rs15153774
104. Evaluation of neural network models for landslide susceptibility assessment Y. Yi et al. 10.1080/17538947.2022.2062467
105. A deep learning model using geostationary satellite data for forest fire detection with reduced detection latency Y. Kang et al. 10.1080/15481603.2022.2143872
106. Improving Dryland Urban Land Cover Classification Accuracy Using a Classical Convolution Neural Network W. Luan et al. 10.3390/land12081616
107. Ecological Environment Evaluation Based on Remote Sensing Ecological Index: A Case Study in East China over the Past 20 Years S. Wang et al. 10.3390/su142315771
108. Adaptive Self-Paced Collaborative and 3-D Adversarial Multitask Network for Semantic Change Detection Using Zhuhai-1 Orbita Hyperspectral Remote Sensing Imagery D. Wen et al. 10.1109/JSTARS.2023.3348572
109. Evaluation of the upper lakes of the Erhai watershed in China based on water quality, land cover, and macrobenthic invertebrates W. Hu et al. 10.1007/s11356-023-29773-2
110. Oasis sustainability is related to water supply mode B. Chen et al. 10.1016/j.agwat.2023.108589
111. Mapping the ratoon rice suitability region in China using random forest and recursive feature elimination modeling Y. Wang & Y. Li 10.1016/j.fcr.2023.109016
112. Recognizing Urban Functional Zones by GF-7 Satellite Stereo Imagery and POI Data Z. Sun et al. 10.3390/app13106300
113. Urban growth scenario projection using heuristic cellular automata in arid areas considering the drought impact X. Tang et al. 10.1007/s40333-024-0097-9
114. Perspective: Monitoring global forests using only structural metrics – problems and solutions from a savanna viewpoint P. Scogings 10.1016/j.foreco.2023.121381
115. Impacts of Land Use/Land Cover Distributions on Permafrost Simulations on Tibetan Plateau Y. Pan et al. 10.3390/rs15235586
116. Performance of hyperspectral data in predicting and mapping zinc concentration in soil W. Sun et al. 10.1016/j.scitotenv.2022.153766
117. Reliability and consistency assessment of land cover products at macro and local scales in typical cities W. Shi et al. 10.1080/17538947.2023.2181992
118. Potential of solar-induced chlorophyll fluorescence (SIF) to access long-term dynamics of soil salinity using OCO-2 satellite data and machine learning method R. Du et al. 10.1016/j.geoderma.2024.116855
119. Assessment of Grassland Degradation on the Tibetan Plateau Based on Multi-Source Data S. Wang et al. 10.3390/rs14236011
120. Consistency Analysis of Multi-Source Remote Sensing Land Cover Products in Arid Regions—A Case Study of Xinjiang S. Liu et al. 10.3390/land12122178
121. A full resolution deep learning network for paddy rice mapping using Landsat data L. Xia et al. 10.1016/j.isprsjprs.2022.10.005
122. Automatic Detection and Dynamic Analysis of Urban Heat Islands Based on Landsat Images N. Na et al. 10.3390/rs15164006
123. MSCANet: multiscale context information aggregation network for Tibetan Plateau lake extraction from remote sensing images Z. Tian et al. 10.1080/17538947.2022.2159552
124. CCropLand30: High-resolution hybrid cropland maps of China created through the synergy of state-of-the-art remote sensing products and the latest national land survey L. Zhang et al. 10.1016/j.compag.2024.108672
125. A patch filling method for thematic map refinement: a case study on forest cover mapping in the Greater Mekong Subregion and Malaysia S. Meng et al. 10.1080/15481603.2023.2252225
126. Medium Spatial Resolution Mapping of Global Land Cover and Land Cover Change Across Multiple Decades From Landsat M. Friedl et al. 10.3389/frsen.2022.894571
127. Cross-resolution national-scale land-cover mapping based on noisy label learning: A case study of China Y. Liu et al. 10.1016/j.jag.2023.103265
128. A novel alpine land cover classification strategy based on a deep convolutional neural network and multi-source remote sensing data in Google Earth Engine Y. Qichi et al. 10.1080/15481603.2023.2233756
129. Assessment of Land Cover Status and Change in the World and “the Belt and Road” Region from 2016 to 2020 A. Yang et al. 10.3390/s23167158
130. Tracking annual changes of coastal aquaculture ponds in China during 1986–2021 P. Tian et al. 10.1016/j.aquaculture.2024.740965
131. Monitoring Surface Water Change in Northeast China in 1999–2020: Evidence from Satellite Observation and Refined Classification K. Liu et al. 10.1007/s11769-024-1411-3
132. Generating annual high resolution land cover products for 28 metropolises in China based on a deep super-resolution mapping network using Landsat imagery D. He et al. 10.1080/15481603.2022.2142727
133. Intercomparison and validation of five existing leaf chlorophyll content products over China X. Wang et al. 10.1016/j.jag.2024.103930
134. Contribution of Land Cover Classification Results Based on Sentinel-1 and 2 to the Accreditation of Wetland Cities X. Wang et al. 10.3390/rs15051275
135. Modification of Statistical Metric Biases in Large-Region and Long-Time-Series Landsat Dataset Due to Insufficient Observations L. Wang et al. 10.1109/TGRS.2023.3323319
136. Study on the Classification and Change Detection Methods of Drylands in Arid and Semi-Arid Regions Z. Zhu et al. 10.3390/rs14051256
137. Comparison and Evaluation of Five Global Land Cover Products on the Tibetan Plateau Y. Pan et al. 10.3390/land13040522
138. FROM-GLC Plus: toward near real-time and multi-resolution land cover mapping L. Yu et al. 10.1080/15481603.2022.2096184
139. Land use/cover and land degradation across the Eurasian steppe: Dynamics, patterns and driving factors Z. Du et al. 10.1016/j.scitotenv.2023.168593
140. Assessment of Forest Ecosystem Variations in the Lancang–Mekong Region by Remote Sensing from 2010 to 2020 J. Zhao et al. 10.3390/s23229038
141. Linking Land Use Land Cover change to global groundwater storage B. Dasgupta & P. Sanyal 10.1016/j.scitotenv.2022.158618
142. A High-Performance Automated Large-Area Land Cover Mapping Framework J. Zhang et al. 10.3390/rs15123143
143. Effects of land surface temperatures on vegetation phenology along urban–rural local climate zone gradients J. Xie et al. 10.1007/s10980-024-01856-6
144. High-resolution atmospheric mercury emission from open biomass burning in China: Integration of localized emission factors and multi-source finer resolution remote sensing data Z. Xu et al. 10.1016/j.envint.2023.108102
145. Efficacy of the SDGSAT-1 glimmer imagery in measuring sustainable development goal indicators 7.1.1, 11.5.2, and target 7.3 S. Liu et al. 10.1016/j.rse.2024.114079
146. Progress and challenges in remotely sensed terrestrial carbon fluxes T. Wang et al. 10.1080/10095020.2024.2336599
147. Canopy active fuel loads estimation with C-band PolSAR by combining polarization decomposition and vegetation scattering model: a case study in Southwestern China Y. Li & B. He 10.1080/01431161.2024.2347524
148. Urban Sprawl and Changes in Land-Use Efficiency in the Beijing–Tianjin–Hebei Region, China from 2000 to 2020: A Spatiotemporal Analysis Using Earth Observation Data M. Zhou et al. 10.3390/rs13152850
149. Do adaptive policy adjustments deliver ecosystem-agriculture-economy co-benefits in land degradation neutrality efforts? Evidence from southeast coast of China C. Jiang et al. 10.1007/s10661-023-11821-6
150. Mapping Blue and Red Color-Coated Steel Sheet Roof Buildings over China Using Sentinel-2A/B MSIL2A Images A. Samat et al. 10.3390/rs14010230
151. Automatic impervious surface mapping in subtropical China via a terrain-guided gated fusion network Z. Li et al. 10.1016/j.jag.2023.103608
152. A Novel Knowledge-Driven Automated Solution for High-Resolution Cropland Extraction by Cross-Scale Sample Transfer W. Zhang et al. 10.1109/TGRS.2023.3299956
153. Improved estimation of the underestimated GEDI footprint LAI in dense forests L. Liang et al. 10.1080/10095020.2023.2286377
154. 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
155. Mapping the terraces on the Loess Plateau based on a deep learning-based model at 1.89 m resolution Y. Lu et al. 10.1038/s41597-023-02005-5
156. Spatiotemporal variation in sensitivity of urban vegetation growth and greenness to vegetation water content: Evidence from Chinese megacities G. Dong et al. 10.1016/j.scitotenv.2023.167090
157. Dynamic and attribution analysis of sandy lands in theBeijing-Tianjin sandstorm source region during 2000–2018 X. Li et al. 10.1360/TB-2022-1213
158. Spatial and temporal changes and development predictions of urban green spaces in Jinan City, Shandong, China J. Wang et al. 10.1016/j.ecolind.2023.110373
159. Temporal and Spatial Evolution Characteristics and Its Driving Mechanism of Land Use/Land Cover Change in Laos from 2000 to 2020 Y. Zhang et al. 10.3390/land11081188
160. RUSLE Model Evaluation of the Soil and Water Conservation Ratio of the Guizhou Province in China between 2000 and 2019 F. Fang et al. 10.3390/su14138219
161. 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
162. Long-Term Changes of Land Use and Land Cover in the Yangtze River Basin from 1990–2020 Landsat Data J. Yao & S. Jin 10.14358/PERS.22-00050R2
163. Spatial Relationship between Land Use Patterns and Ecosystem Services Value—Case Study of Nanjing M. Lu et al. 10.3390/land11081168
164. Process-based and geostationary meteorological satellite-enhanced dead fuel moisture content estimation C. Fan et al. 10.1080/15481603.2024.2324556
165. Mapping High-Resolution Global Impervious Surface Area: Status and Trends H. Ren et al. 10.1109/JSTARS.2022.3201380
166. Trend of Vegetation and Environmental Factors and Their Feedback in the Karst Regions of Southwestern China K. Huang et al. 10.3390/su142315941
167. Satellite-Observed Spatio-Temporal Variation in Spring Leaf Phenology of Subtropical Forests across the Nanling Mountains in Southern China over 1999–2019 C. Ding et al. 10.3390/f13091486
168. Classification and Transition of Grassland in Qinghai, China, from 1986 to 2020 with Landsat Archives on Google Earth Engine P. He et al. 10.3390/land12091686
169. Land cover changes in grassland landscapes: combining enhanced Landsat data composition, LandTrendr, and machine learning classification in google earth engine with MLP-ANN scenario forecasting C. Parracciani et al. 10.1080/15481603.2024.2302221
170. Vegetation coverage changes driven by a combination of climate change and human activities in Ethiopia, 2003–2018 S. Yang et al. 10.1016/j.ecoinf.2022.101776
171. Solar-Induced Chlorophyll Fluorescence Trends and Mechanisms in Different Ecosystems in Northeastern China M. Guo et al. 10.3390/rs14061329
172. Estimation of National Forest Aboveground Biomass from Multi-Source Remotely Sensed Dataset with Machine Learning Algorithms in China Z. Tang et al. 10.3390/rs14215487
173. Forestation at the right time with the right species can generate persistent carbon benefits in China H. Xu et al. 10.1073/pnas.2304988120
174. A simple approach to enhance the TROPOMI solar-induced chlorophyll fluorescence product by combining with canopy reflected radiation at near-infrared band X. Liu et al. 10.1016/j.rse.2022.113341
175. Quantifying morphology evolutions of urban heat islands and assessing their heat exposure in a metropolis H. Zhao et al. 10.1016/j.scs.2024.105244
176. Assessment of ensemble learning for object-based land cover mapping using multi-temporal Sentinel-1/2 images S. Xu et al. 10.1080/10106049.2023.2195832
177. An Erosion-Based Approach Using Multi-Source Remote Sensing Imagery for Grassland Restoration Patterns in a Plateau Mountainous Region, SW China G. Chen et al. 10.3390/rs15082047
178. Toward accurate mapping of 30-m time-series global impervious surface area (GISA) X. Huang et al. 10.1016/j.jag.2022.102787
179. Spatiotemporal analysis of land use changes and their trade-offs on the northern slope of the Tianshan Mountains, China H. Ma 10.3389/fevo.2022.1016774
180. Automated in-season mapping of winter wheat in China with training data generation and model transfer G. Yang et al. 10.1016/j.isprsjprs.2023.07.004
181. Upscaling remote sensing inversion and dynamic monitoring of soil salinization in the Yellow River Delta, China Y. Li et al. 10.1016/j.ecolind.2023.110087
182. Feature Optimization-Based Machine Learning Approach for Czech Land Cover Classification Using Sentinel-2 Images C. Wang et al. 10.3390/app14062561
183. Land Use/Cover Change and Its Driving Mechanism in Thailand from 2000 to 2020 Y. Wang et al. 10.3390/land11122253
184. A robust and unified land surface phenology algorithm for diverse biomes and growth cycles in China by using harmonized Landsat and Sentinel-2 imagery J. Yang et al. 10.1016/j.isprsjprs.2023.07.017
185. A super-ensemble approach to map land cover types with high resolution over data-sparse African savanna landscapes L. Song et al. 10.1016/j.jag.2022.103152
186. Temporal Activity Patterns of Sympatric Species in the Temperate Coniferous Forests of the Eastern Qinghai-Tibet Plateau J. Jia et al. 10.3390/ani13071129
187. Consistency Analysis and Accuracy Evaluation of Multi-Source Land Cover Data Products in the Eastern European Plain G. Jiang et al. 10.3390/rs15174254
188. Abandoned cropland mapping and its influencing factors analysis: A case study in the Beijing-Tianjin-Hebei region T. Zhang et al. 10.1016/j.catena.2024.107876
189. Mapping Paddy Rice in Rice–Wetland Coexistence Zone by Integrating Sentinel-1 and Sentinel-2 Data D. Huang et al. 10.3390/agriculture14030345
190. A systematic review of studies involving canopy layer urban heat island: Monitoring and associated factors Y. Li et al. 10.1016/j.ecolind.2023.111424
191. FieldSeg-DA2.0: Further enhancing the spatiotemporal transferability of an individual arable field (IAF) extraction network using multisource remote sensing and land cover data C. Tian et al. 10.1016/j.compag.2024.109050
192. Identifying core driving factors of urban land use change from global land cover products and POI data using the random forest method H. Wu et al. 10.1016/j.jag.2021.102475
193. The spatiotemporal change of cropland and its impact on vegetation dynamics in the farming-pastoral ecotone of northern China D. Wuyun et al. 10.1016/j.scitotenv.2021.150286
194. Toward sustainable land use in China: A perspective on China’s national land surveys X. Chen et al. 10.1016/j.landusepol.2022.106428
195. Refined assessment of space-time changes, influencing factors and socio-economic impacts of the terrestrial ecosystem quality: A case study of the GBA Y. Wen et al. 10.1016/j.jenvman.2023.118869
196. Data mining of urban soil spectral library for estimating organic carbon Y. Hong et al. 10.1016/j.geoderma.2022.116102
197. The Associations of Green Spaces with Older Adults' Mental Health in Perspective of Spatiality, Sociality and Historicality Y. Yafei et al. 10.5814/j.issn.1674-764x.2023.02.008
198. The role of satellite remote sensing in mitigating and adapting to global climate change S. Zhao et al. 10.1016/j.scitotenv.2023.166820
199. Improving Reliability in Reconstruction of Landsat EVI Seasonal Trajectory over Cloud-Prone, Fragmented, and Mosaic Agricultural Landscapes W. Xue et al. 10.3390/rs15194673
200. Linearly interpolating missing values in time series helps little for land cover classification using recurrent or attention networks X. Che et al. 10.1016/j.isprsjprs.2024.04.021
201. Dynamic simulation and projection of ESV changes in arid regions caused by urban growth under climate change scenarios X. Tang et al. 10.1007/s10661-024-12559-5
202. A novel index combining temperature and vegetation conditions for monitoring surface mining disturbance using Landsat time series T. He et al. 10.1016/j.catena.2023.107235
203. SinoLC-1: the first 1 m resolution national-scale land-cover map of China created with a deep learning framework and open-access data Z. Li et al. 10.5194/essd-15-4749-2023
204. Temporal—Spatial Changes in Vegetation Coverage under Climate Change and Human Activities: A Case Study of Central Yunnan Urban Agglomeration, China Y. Li et al. 10.3390/su16020661
205. Application of Transformer Models to Landslide Susceptibility Mapping S. Bao et al. 10.3390/s22239104
206. Measuring the cooling effects of green cover on urban heat island effects using Landsat satellite imagery N. Na et al. 10.1080/17538947.2024.2358867
207. The rapid vegetation line shift in response to glacial dynamics and climate variability in Himalaya between 2000 and 2014 D. Bandyopadhyay et al. 10.1007/s10661-022-10577-9
208. A Framework for Fine-Grained Land-Cover Classification Using 10 m Sentinel-2 Images W. Zhang et al. 10.3390/rs16020390
209. Simulating the hydrological impacts of intensive soil and water conservation measures in the Yellow River basin using a distributed physically-based model Z. Yan et al. 10.1016/j.jhydrol.2023.129936
210. The future of global land change monitoring X. Song 10.1080/17538947.2023.2224586
211. A non‐grain production on cropland spatiotemporal change detection method based on Landsat time‐series data T. He et al. 10.1002/ldr.5113
212. Improving the Interpretability and Reliability of Regional Land Cover Classification by U-Net Using Remote Sensing Data X. Wang et al. 10.1007/s11769-022-1315-z
213. Mapping open-pit mining area in complex mining and mixed land cover zone using Landsat imagery Y. Wang et al. 10.1016/j.jag.2024.103782
214. Long-Term Analysis of Regional Vegetation Correlation with Climate and Phenology in the Midsection of Maowusu Sandland Z. Li et al. 10.3390/w16050623
215. A national extent map of cropland and grassland for Switzerland based on Sentinel-2 data R. Pazúr et al. 10.5194/essd-14-295-2022
216. Quantifying the accuracies of six 30-m cropland datasets over China: A comparison and evaluation analysis C. Zhang et al. 10.1016/j.compag.2022.106946
217. Trend in Satellite-Observed Vegetation Cover and Its Drivers in the Gannan Plateau, Upper Reaches of the Yellow River, from 2000 to 2020 Y. Liang et al. 10.3390/rs14163849
218. A Framework to Calculate Annual Landscape Ecological Risk Index Based on Land Use/Land Cover Changes: A Case Study on Shengjin Lake Wetland P. Wu et al. 10.1109/JSTARS.2021.3129183
219. A Reconstruction of Irrigated Cropland Extent in China from 2000 to 2019 Using the Synergy of Statistics and Satellite-Based Datasets M. Bai et al. 10.3390/land11101686
220. Evaluation and Intercomparison of Topographic Correction Methods Based on Landsat Images and Simulated Data Y. Ma et al. 10.3390/rs13204120
221. Urban vegetation cooling potential during heatwaves depends on background climate J. Zhao et al. 10.1088/1748-9326/acaf0f
222. Study of Land Cover Change in the City with the Fastest Economic Growth in China (Hefei) from 2000 to 2020 Based on Google Earth Engine Platform J. Geng et al. 10.3390/rs15061604
223. Multi-Category Segmentation of Sentinel-2 Images Based on the Swin UNet Method J. Yao & S. Jin 10.3390/rs14143382
224. Landslide Susceptibility Mapping by Fusing Convolutional Neural Networks and Vision Transformer S. Bao et al. 10.3390/s23010088
225. Forest Phenology under Differing Topographic Conditions: A Case Study of Changbai Mountain in Northeast China J. Jiang et al. 10.3390/f14071466
226. Automated Mapping of Global 30-m Tidal Flats Using Time-Series Landsat Imagery: Algorithm and Products X. Zhang et al. 10.34133/remotesensing.0091
227. Identifying Urban Wetlands through Remote Sensing Scene Classification Using Deep Learning: A Case Study of Shenzhen, China R. Yang et al. 10.3390/ijgi11020131
228. Consistency and Accuracy of Four High-Resolution LULC Datasets—Indochina Peninsula Case Study H. Wang et al. 10.3390/land11050758
229. Evaluation of Global Land Use–Land Cover Data Products in Guangxi, China X. Hao et al. 10.3390/rs15051291
230. The impact of global cropland irrigation on soil carbon dynamics X. Yao et al. 10.1016/j.agwat.2024.108806
231. Comparison of hybrid data-driven and physical models for landslide susceptibility mapping at regional scales X. Wei et al. 10.1007/s11440-023-01841-4
232. A Reference-Free Method for the Thematic Accuracy Estimation of Global Land Cover Products Based on the Triple Collocation Approach P. Chen et al. 10.3390/rs15092255
233. 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
234. Mangrove Biodiversity Assessment Using UAV Lidar and Hyperspectral Data in China’s Pinglu Canal Estuary Y. Tian et al. 10.3390/rs15102622
235. Remotely Sensed Changes in Qinghai–Tibet Plateau Wetland Ecosystems and Their Response to Drought A. Fu et al. 10.3390/su16114738
236. Influence of Image Compositing and Multisource Data Fusion on Multitemporal Land Cover Mapping of Two Philippine Watersheds N. Almarines et al. 10.3390/rs16122167
237. Land use and cover in subtropical East Asia and Southeast Asia from 1700 to 2018 F. Mao et al. 10.1016/j.gloplacha.2023.104157
238. Time-series land cover mapping and urban expansion analysis using OpenStreetMap data and remote sensing big data: A case study of Guangdong-Hong Kong-Macao Greater Bay Area, China Q. Ding et al. 10.1016/j.jag.2022.103001
239. Land-Cover-Change Detection with Aerial Orthoimagery Using SegNet-Based Semantic Segmentation in Namyangju City, South Korea S. Son et al. 10.3390/su141912321
240. Future urban ecological land transition and its implications for high-heat exposure in China R. Feng et al. 10.1016/j.scs.2024.105590
241. Addressing validation challenges for TROPOMI solar-induced chlorophyll fluorescence products using tower-based measurements and an NIRv-scaled approach S. Du et al. 10.1016/j.rse.2023.113547
242. Urban greenspace and mental health in Chinese older adults: Associations across different greenspace measures and mediating effects of environmental perceptions Y. Yue et al. 10.1016/j.healthplace.2022.102856
243. “Skylights” increase exposure levels and reduce the maximum depth of nature reserves H. Gao & D. Zhu 10.1002/inc3.45
244. Comparative Analysis of the Impact of Two Common Residue Burning Parameters on Urban Air Quality Indicators J. Du et al. 10.3390/rs15153911
245. Mapping Spatially Seamless Fractional Vegetation Cover over China at a 30-m Resolution and Semimonthly Intervals in 2010–2020 Based on Google Earth Engine T. Zhao et al. 10.34133/remotesensing.0101
246. Difference and consistency of multi-sources land cover products in global large river estuaries J. Zhong et al. 10.1016/j.ocecoaman.2023.106803
247. The Retrieval of Forest and Grass Fractional Vegetation Coverage in Mountain Regions Based on Spatio-Temporal Transfer Learning Y. Huang et al. 10.3390/rs15194857
248. The land-sea interface mapping: China’s coastal land covers at 10 m for 2020 M. Li et al. 10.1016/j.scib.2022.07.012
249. Assessing and Characterizing Carbon Storage in Wetlands of the Guangdong–Hong Kong–Macau Greater Bay Area, China, During 1995–2020 Y. Deng et al. 10.1109/JSTARS.2022.3192267
250. A new cropland area database by country circa 2020 F. Tubiello et al. 10.5194/essd-15-4997-2023
251. Deciphering the evolving trajectories of China's megaregions from 1992 to 2020: A novel morphological approach based on global land cover products H. Cao et al. 10.1016/j.apgeog.2024.103205
252. 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
253. Advancing Agricultural Crop Recognition: The Application of LSTM Networks and Spatial Generalization in Satellite Data Analysis A. Gafurov et al. 10.3390/agriculture13091672
254. Climate change effects on the global distribution and range shifts of citrus longhorned beetle Anoplophora chinensis Y. Zhou et al. 10.1111/jen.12996
255. Climate overtakes vegetation greening in regulating spatiotemporal patterns of soil moisture in arid Central Asia in recent 35 years N. Amantai et al. 10.1080/15481603.2023.2286744
256. UGS-1m: fine-grained urban green space mapping of 31 major cities in China based on the deep learning framework Q. Shi et al. 10.5194/essd-15-555-2023
257. Decoding the inconsistency of six cropland maps in China Y. Cui et al. 10.1016/j.cj.2023.11.011
258. Building hybrid global annual 1 km IGBP land cover maps for the period 2000 – 2020 Y. Luo et al. 10.34133/remotesensing.0122
259. Extraction of Abandoned Land in Hilly Areas Based on the Spatio-Temporal Fusion of Multi-Source Remote Sensing Images S. He et al. 10.3390/rs13193956
260. Spatial and Temporal Evolution Characteristics of Land Use/Cover and Its Driving Factor in Cambodia during 2000–2020 X. Niu et al. 10.3390/land11091556
261. Spatio-temporal variation in leaf area index in the Yan Mountains over the past 40 years and its relationship to hydrothermal conditions D. Guo et al. 10.1016/j.ecolind.2023.111291
262. Systematic method for mapping fine-resolution water cover types in China based on time series Sentinel-1 and 2 images Y. Li & Z. Niu 10.1016/j.jag.2021.102656
263. Dataset of building locations in Poland in the 1970s and 1980s P. Szubert et al. 10.1038/s41597-024-03179-2
264. Reservoir inventory for China in 2016 and 2021 H. Zhang et al. 10.1038/s41597-023-02515-2
265. Spatial domain transfer: Cross-regional paddy rice mapping with a few samples based on Sentinel-1 and Sentinel-2 data on GEE L. Sun et al. 10.1016/j.jag.2024.103762
266. Consistency Analysis and Accuracy Assessment of Eight Global Forest Datasets over Myanmar H. Xing et al. 10.3390/app112311348
267. A Prior Semantic Network for Large-Scale Landcover Change of Landsat Imagery X. Yang et al. 10.3390/su142013167
268. Dynamic surface water maps of Canada from 1984 to 2019 Landsat satellite imagery I. Olthof & T. Rainville 10.1016/j.rse.2022.113121
269. Monitoring of Cropland Abandonment and Land Reclamation in the Farming–Pastoral Zone of Northern China J. Ye et al. 10.3390/rs16061089
270. Dynamics of land cover changes and driving forces in China’s drylands since the 1970 s B. Wu et al. 10.1016/j.landusepol.2024.107097
271. Shifts in plant ecological strategies in remnant forest patches along urbanization gradients J. Yang et al. 10.1016/j.foreco.2022.120540
272. Land use and cover change and influencing factor analysis in the Shiyang River Basin, China Y. Zhao et al. 10.1007/s40333-024-0071-6
273. Assessment of Remote Sensing Ecological Quality by Introducing Water and Air Quality Indicators: A Case Study of Wuhan, China Y. Pan et al. 10.3390/land11122272
274. Incorporating Multi-Temporal Remote Sensing and a Pixel-Based Deep Learning Classification Algorithm to Map Multiple-Crop Cultivated Areas X. Wang et al. 10.3390/app14093545
275. Comparative Habitat Divergence and Fragmentation Analysis of Two Sympatric Pheasants in the Qilian Mountains, China W. Xie et al. 10.3390/land11122104
276. NPP Variability Associated with Natural and Anthropogenic Factors in the Tropic of Cancer Transect, China Y. Wu & Z. Wu 10.3390/rs15041091
277. Automatic training sample collection utilizing multi-source land cover products and time-series Sentinel-2 images Y. Wang et al. 10.1080/15481603.2024.2352957
278. Mapping China’s coastal aquaculture ponds expansion with sentinel-2 images during 2017–2021 W. Sun et al. 10.1080/17538947.2023.2297943
279. Monitoring and Assessing Urbanization Progress in Thailand between 2000 and 2020 Using SDG Indicator 11.3.1 R. Bhandari et al. 10.3390/su15129794
280. Classifying Mountain Vegetation Types Using Object-Oriented Machine Learning Methods Based on Different Feature Combinations X. Fu et al. 10.3390/f14081624
281. Geographical Knowledge-Driven Representation Learning for Remote Sensing Images W. Li et al. 10.1109/TGRS.2021.3115569
282. Mapping planted forest age using LandTrendr algorithm and Landsat 5–8 on the Loess Plateau, China P. Li et al. 10.1016/j.agrformet.2023.109795
283. Regional Accuracy Assessment of 30-Meter GLC_FCS30, GlobeLand30, and CLCD Products: A Case Study in Xinjiang Area J. Liu et al. 10.3390/rs16010082
284. Spatiotemporal and Driving Factors of Land-Cover Change in the Heilongjiang (Amur) River Basin S. Jia & Y. Yang 10.3390/rs15153730
285. Estimation of soil lead content based on GF-5 hyperspectral images, considering the influence of soil environmental factors S. Ding et al. 10.1007/s11368-022-03169-0
286. Development of a 30 m resolution global sand dune/sheet classification map (GSDS30) using multi-source remote sensing data Z. Zheng et al. 10.1016/j.rse.2023.113973
287. Wildfire risk for global wildland–urban interface areas B. Chen et al. 10.1038/s41893-024-01291-0
288. Scale dependence of forest fragmentation and its climate sensitivity in a semi-arid mountain: Comparing Landsat, Sentinel and Google Earth data Y. Xie et al. 10.1016/j.geosus.2023.11.008
289. High-Confidence Sample Generation Technology and Application for Global Land-Cover Classification X. Xi et al. 10.1109/JSTARS.2022.3227911
290. Seeded Classification of Satellite Image Time Series with Lower-Bounded Dynamic Time Warping Z. Zhang et al. 10.3390/rs14122778
291. Rapid method for yearly LULC classification using Random Forest and incorporating time-series NDVI and topography: a case study of Thanh Hoa province, Vietnam T. Le et al. 10.1080/10106049.2022.2123959
292. Identifying the Effects of Vegetation on Urban Surface Temperatures Based on Urban–Rural Local Climate Zones in a Subtropical Metropolis S. Zhou et al. 10.3390/rs15194743
293. Fusing Multiple Land Cover Products Based on Locally Estimated Map-Reference Cover Type Transition Probabilities W. Zhang et al. 10.3390/rs15020481
294. High-resolution land cover classification: cost-effective approach for extraction of reliable training data from existing land cover datasets G. Bratic et al. 10.1080/17538947.2023.2253784
295. Forest height mapping using inventory and multi-source satellite data over Hunan Province in southern China W. Huang et al. 10.1016/j.fecs.2022.100006
296. The reliability of categorical triple collocation for evaluating soil freeze/thaw datasets H. Li et al. 10.1016/j.rse.2022.113240
297. Evaluating the Dynamic Changes of Urban Land and Its Fractional Covers in Africa from 2000–2020 Using Time Series of Remotely Sensed Images on the Big Data Platform Z. Yin et al. 10.3390/rs13214288
298. Classification of Wetland Vegetation Based on NDVI Time Series from the HLS Dataset Y. Ju & G. Bohrer 10.3390/rs14092107
299. Urban flooding risk assessment based on FAHP–EWM combination weighting: a case study of Beijing N. Sun et al. 10.1080/19475705.2023.2240943
300. Reconstructing Long‐Term Forest Cover in China by Fusing National Forest Inventory and 20 Land Use and Land Cover Data Sets X. Xia et al. 10.1029/2022JG007101
301. Monitoring Mining Activity and Vegetation Recovery in Rare Earth Element Mining Areas Y. Liu & R. Zuo 10.1007/s11004-023-10113-6
302. Disentangling the Influential Factors Driving NPP Decrease in Shandong Province: An Analysis from Time Series Evaluation Using MODIS and CASA Model G. Lv et al. 10.3390/rs16111966
303. Validation and refinement of cropland map in southwestern China by harnessing ten contemporary datasets Y. Cui et al. 10.1038/s41597-024-03508-5
304. Characteristics and effects of global sloping land urbanization from 2000 to 2020 J. Lu et al. 10.1016/j.scitotenv.2024.173348
305. Coupling Changes in Runoff and Sediment and Their Relationships with Erosion Energy and Underlying Surface in the Wuding River Basin, China Q. Yang et al. 10.3390/land13040496
306. Sub-continental-scale mapping of tidal wetland composition for East Asia: A novel algorithm integrating satellite tide-level and phenological features Z. Zhang et al. 10.1016/j.rse.2021.112799
307. Land use/land cover prediction and analysis of the middle reaches of the Yangtze River under different scenarios S. Zhang et al. 10.1016/j.scitotenv.2022.155238
308. High-Resolution Land-Cover Mapping Based on a Cross-Resolution Deep Learning Framework and Available Low-Resolution Labels X. Qi et al. 10.1109/JSTARS.2023.3342994
309. Forest foliage fuel load estimation from multi-sensor spatiotemporal features Y. Li et al. 10.1016/j.jag.2022.103101
310. Dominance of Influencing Factors on Cooling Effect of Urban Parks in Different Climatic Regions S. Zheng et al. 10.3390/ijerph192315496
311. Application of geospatial technology for the land use/land cover change assessment and future change predictions using CA Markov chain model S. Shivappa Masalvad et al. 10.1007/s10668-023-03657-4
312. Vertical Accuracy Assessment of the ASTER, SRTM, GLO-30, and ATLAS in a Forested Environment J. Huang & Y. Yu 10.3390/f15030426
313. Mapping China’s planted forests using high resolution imagery and massive amounts of crowdsourced samples K. Cheng et al. 10.1016/j.isprsjprs.2023.01.005
314. Effect of leaf-on and leaf-off canopy conditions on forest height retrieval and modelling with ICESat-2 data J. Zhou et al. 10.1080/17538947.2023.2285807
315. An Open Data Approach for Estimating Vegetation Gross Primary Production at Fine Spatial Resolution S. Lin et al. 10.3390/rs14112651
316. Global conservation priorities for wetlands and setting post-2025 targets Q. Yi et al. 10.1038/s43247-023-01195-5
317. Estimating the Past and Future Trajectory of LUCC on Wetland Ecosystem Service Values in the Yellow River Delta Region of China Z. Zhang et al. 10.3390/su16020619
318. Consistency Assessments of the Land Cover Products on the Tibetan Plateau L. Cai et al. 10.1109/JSTARS.2022.3188650
319. Automatically Monitoring Impervious Surfaces Using Spectral Generalization and Time Series Landsat Imagery from 1985 to 2020 in the Yangtze River Delta X. Zhang et al. 10.34133/2021/9873816
320. Using a water index approach to mapping periodically inundated saltmarsh land-cover vegetation and eco-zonation using multi-temporal Landsat 8 imagery S. Alam & M. Hossain 10.1007/s11852-023-01019-w
321. Time‐series InSAR monitoring of surface deformation in Yakutsk, a city located on continuous permafrost X. Li et al. 10.1002/esp.5736
322. Global land surface evapotranspiration monitoring by ETMonitor model driven by multi-source satellite earth observations C. Zheng et al. 10.1016/j.jhydrol.2022.128444
323. 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
324. Spatiotemporal Evaluation of Regional Land Use Dynamics and Its Potential Ecosystem Impact under Carbon Neutral Pathways in the Guangdong–Hong Kong–Macao Greater Bay Area H. Chen et al. 10.3390/rs15245749
325. An Improved Framework for Airport Detection Under the Complex and Wide Background N. Li et al. 10.1109/JSTARS.2022.3217040
326. Local carbon emission zone construction in the highly urbanized regions: Application of residential and transport CO2 emissions in Shanghai, China Y. Tian et al. 10.1016/j.buildenv.2023.111007
327. Mapping irrigated croplands in China using a synergetic training sample generating method, machine learning classifier, and Google Earth Engine C. Zhang et al. 10.1016/j.jag.2022.102888
328. Urbanization strengthens the edge effects on species diversity and composition of woody plants in remnant forests Z. Wang & J. Yang 10.1016/j.fecs.2022.100063
329. Identifying and quantifying local uncertainty and discrepancy in the comparison of global cropland extent through a synergistic approach X. Liu et al. 10.1016/j.apgeog.2023.103164
330. Improving pixel-based regional landslide susceptibility mapping X. Wei et al. 10.1016/j.gsf.2024.101782
331. A Comparison of Random Forest Algorithm-Based Forest Extraction with GF-1 WFV, Landsat 8 and Sentinel-2 Images X. Peng et al. 10.3390/rs14215296
332. 10 m crop type mapping using Sentinel-2 reflectance and 30 m cropland data layer product K. Tran et al. 10.1016/j.jag.2022.102692
333. Attributing trend in naturalized streamflow to temporally explicit vegetation change and climate variation in the Yellow River basin of China Z. Wang et al. 10.5194/hess-26-5291-2022
334. AGTML: A novel approach to land cover classification by integrating automatic generation of training samples and machine learning algorithms on Google Earth Engine Y. Cui et al. 10.1016/j.ecolind.2023.110904
335. Detailed wetland-type classification using Landsat-8 time-series images: a pixel- and object-based algorithm with knowledge (POK) K. Peng et al. 10.1080/15481603.2023.2293525
336. Mapping the Complex Crop Rotation Systems in Southern China Considering Cropping Intensity, Crop Diversity, and Their Seasonal Dynamics Y. Liu et al. 10.1109/JSTARS.2022.3218881
337. Analysis of desertification combating needs based on potential vegetation NDVI—A case in the Hotan Oasis L. Zhang et al. 10.3389/fpls.2022.1036814
338. Assessing Temporal Trade-Offs of Ecosystem Services by Production Possibility Frontiers W. Jiang et al. 10.3390/rs15030749
339. Drastic water volume changes in mega lakes can pose considerable impacts on regional water storage Z. Gao et al. 10.1016/j.ecolind.2024.112150
340. Continued Increases of Gross Primary Production in Urban Areas during 2000–2016 Y. Cui et al. 10.34133/2022/9868564
341. Ecosystem health assessment and approaches to improve Sichuan Province based on an improved vigor organization resilience model J. Lei et al. 10.1016/j.ecolind.2023.110925
342. Donor-side valuation of forest ecosystem services in China during 1990–2020 Y. Xie et al. 10.1007/s40974-023-00294-5
343. Identification of Ecological Sources Using Ecosystem Service Value and Vegetation Productivity Indicators: A Case Study of the Three-River Headwaters Region, Qinghai–Tibetan Plateau, China X. Feng et al. 10.3390/rs16071258
344. PRISI: A novel piecewise radar impervious surface index for urban monitoring using Sentinel-1 data Y. Ding et al. 10.1016/j.jag.2022.103033
345. Machine learning in modelling land-use and land cover-change (LULCC): Current status, challenges and prospects J. Wang et al. 10.1016/j.scitotenv.2022.153559
346. Rapid early-season maize mapping without crop labels N. You et al. 10.1016/j.rse.2023.113496
347. Implementation of the CCDC algorithm to produce the LCMAP Collection 1.0 annual land surface change product G. Xian et al. 10.5194/essd-14-143-2022
348. A hierarchical category structure based convolutional recurrent neural network (HCS-ConvRNN) for Land-Cover classification using dense MODIS Time-Series data J. Li et al. 10.1016/j.jag.2022.102744
349. Mapping 20 years of irrigated croplands in China using MODIS and statistics and existing irrigation products C. Zhang et al. 10.1038/s41597-022-01522-z
350. Impact of Land Transition on Landscape and Ecosystem Service Value in Northeast Region of China from 2000–2020 X. Wang et al. 10.3390/land11050696
351. Effect of Urban Built-Up Area Expansion on the Urban Heat Islands in Different Seasons in 34 Metropolitan Regions across China W. Han et al. 10.3390/rs15010248
352. 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
353. 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
354. Classification Feature Optimization for Global Wetlands Mapping X. Yan & Z. Niu 10.1109/JSTARS.2024.3382580
355. Temporal and Spatial Evolution Characteristics and Its Driving Mechanism of Land Use/Cover in Vietnam from 2000 to 2020 X. Niu et al. 10.3390/land11060920
356. Mapping the habitat for the moose population in Northeast China by combining remote sensing products and random forests X. Zhi et al. 10.1016/j.gecco.2022.e02347
357. Improved forest cover mapping by harmonizing multiple land cover products over China S. Meng et al. 10.1080/15481603.2022.2124044
358. LUCC Simulation Based on RF-CNN-LSTM-CA Model with High-Quality Seed Selection Iterative Algorithm M. Liu et al. 10.3390/app13063407
359. Large-Area Full-Coverage Remote Sensing Image Collection Filtering Algorithm for Individual Demands B. Chu et al. 10.3390/su132313475
360. 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
361. A simple, fast, and accurate method for land cover mapping in Mongolia T. Phan et al. 10.1080/10106049.2022.2087759
362. Fusing Retrievals of High Resolution Aerosol Optical Depth from Landsat-8 and Sentinel-2 Observations over Urban Areas H. Lin et al. 10.3390/rs13204140
363. Improved Mapping of Regional Forest Heights by Combining Denoise and LightGBM Method M. Sang et al. 10.3390/rs15235436
364. Impacts of landscape patterns on plant species diversity at a global scale H. Jin et al. 10.1016/j.scitotenv.2023.165193
365. Tracking spatiotemporal dynamics of irrigated croplands in China from 2000 to 2019 through the synergy of remote sensing, statistics, and historical irrigation datasets C. Zhang et al. 10.1016/j.agwat.2022.107458
366. Exploring the InSAR Deformation Series Using Unsupervised Learning in a Built Environment M. Yang et al. 10.3390/rs16081375
367. A framework for fine classification of urban wetlands based on random forest and knowledge rules: taking the wetland cities of Haikou and Yinchuan as examples X. Wang et al. 10.1080/15481603.2022.2152926
368. Spatiotemporal dynamic of subtropical forest carbon storage and its resistance and resilience to drought in China M. Yan et al. 10.3389/fpls.2023.1067552
369. Extracting Shrubland in Deserts from Medium-Resolution Remote-Sensing Data at Large Scale B. Zhong et al. 10.3390/rs16020374
370. CALC-2020: a new baseline land cover map at 10 m resolution for the circumpolar Arctic C. Liu et al. 10.5194/essd-15-133-2023
371. Optimal parameters of random forest for land cover classification with suitable data type and dataset on Google Earth Engine J. Sun & S. Ongsomwang 10.3389/feart.2023.1188093
372. Large-scale land use/land cover extraction from Landsat imagery using feature relationships matrix based deep-shallow learning P. Dou et al. 10.1016/j.jag.2024.103866
373. Assessing Spatial Representativeness of Global Flux Tower Eddy-Covariance Measurements Using Data from FLUXNET2015 J. Fang et al. 10.1038/s41597-024-03291-3
374. Development of a Pixel-Wise Forest Transmissivity Model at Frequencies of 19 GHz and 37 GHz for Snow Depth Inversion in Northeast China G. Wang et al. 10.3390/rs14215483
375. Classifying Forest Types over a Mountainous Area in Southwest China with Landsat Data Composites and Multiple Environmental Factors R. Li et al. 10.3390/f13010135
376. Quantifying the environmental synergistic effect of cooling-air purification-carbon sequestration from urban forest in China R. Feng et al. 10.1016/j.jclepro.2024.141514
377. Water-carbon-sediment synergies and trade-offs: Multi-faceted impacts of large-scale ecological restoration in the Middle Yellow River Basin Z. Yan et al. 10.1016/j.jhydrol.2024.131099
378. Enhancing Land Cover Mapping in Mixed Vegetation Regions Using Remote Sensing Evapotranspiration J. Wang et al. 10.1109/TGRS.2024.3383217
379. Vegetation Subtype Classification of Evergreen Broad-Leaved Forests in Mountainous Areas Using a Hierarchy-Based Classifier S. Zhang et al. 10.3390/rs15123053
380. Mapping Cropland Abandonment in the Cloudy Hilly Regions Surrounding the Southwest Basin of China Y. Wei et al. 10.3390/land13050586
381. Regional matters: On the usefulness of regional land‐cover datasets in times of global change M. Tulbure et al. 10.1002/rse2.248
382. Spatiotemporal Monitoring of a Grassland Ecosystem and Its Net Primary Production Using Google Earth Engine: A Case Study of Inner Mongolia from 2000 to 2020 R. Ji et al. 10.3390/rs13214480
383. MaxEnt Modeling for Predicting Suitable Habitats of Snow Leopard (Panthera uncia) in the Mid-Eastern Tianshan Mountains G. Jianhui et al. 10.5814/j.issn.1674-764x.2023.05.018
384. GISD30: global 30 m impervious-surface dynamic dataset from 1985 to 2020 using time-series Landsat imagery on the Google Earth Engine platform X. Zhang et al. 10.5194/essd-14-1831-2022
385. Mapping Cropland Burned Area in Northeastern China by Integrating Landsat Time Series and Multi-Harmonic Model J. Liu et al. 10.3390/rs13245131
386. Recent intensified erosion and massive sediment deposition in Tibetan Plateau rivers J. Li et al. 10.1038/s41467-024-44982-0
387. Urban flooding risk assessment based on GIS- game theory combination weight: A case study of Zhengzhou City J. Peng & J. Zhang 10.1016/j.ijdrr.2022.103080
388. Evaluating the conservation priority of key biodiversity areas based on ecosystem conditions and anthropogenic threats in rapidly urbanizing areas Y. Wang et al. 10.1016/j.ecolind.2022.109245
389. 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
390. Current state and challenges in producing large-scale land cover maps: review based on recent land cover products F. Gilić et al. 10.1080/10106049.2023.2242693
391. Simultaneous Update of High-Resolution Land-Cover Mapping Attempt: Wuhan and the Surrounding Satellite Cities Cartography Using L2HNet Y. Huang et al. 10.1109/JSTARS.2023.3243281
392. 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
393. A novel method for identification of disturbance from surface coal mining using all available Landsat data in the GEE platform T. He et al. 10.1016/j.isprsjprs.2023.09.026
394. Learning spectral-indices-fused deep models for time-series land use and land cover mapping in cloud-prone areas: The case of Pearl River Delta Z. Li et al. 10.1016/j.rse.2024.114190
395. Human expansion into Asian highlands in the 21st Century and its effects C. Yang et al. 10.1038/s41467-022-32648-8
396. Mapping Coniferous Forest Distribution in a Semi-Arid Area Based on Multi-Classifier Fusion and Google Earth Engine Combining Gaofen-1 and Sentinel-1 Data: A Case Study in Northwestern Liaoning, China L. Liu et al. 10.3390/f15020288
397. Effects of hydraulic conductivity on simulating groundwater–land surface interactions over a typical endorheic river basin Z. Lu et al. 10.1016/j.jhydrol.2024.131542
398. An Application of Machine-Learning Model for Analyzing the Impact of Land-Use Change on Surface Water Resources in Gauteng Province, South Africa E. Gidey & P. Mhangara 10.3390/rs15164092
399. Myanmar’s Land Cover Change and Its Driving Factors during 2000–2020 Y. Wang et al. 10.3390/ijerph20032409
400. Dynamics and Drivers of Water Clarity Derived from Landsat and In-Situ Measurement Data in Hulun Lake from 2010 to 2020 C. Zhao et al. 10.3390/w14081189
401. Land potential assessment and trend-analysis using 2000–2021 FAPAR monthly time-series at 250 m spatial resolution J. Hackländer et al. 10.7717/peerj.16972
402. Spatiotemporal Analysis and War Impact Assessment of Agricultural Land in Ukraine Using RS and GIS Technology Y. Ma et al. 10.3390/land11101810
403. Spatially explicit subpixel-based study on the expansion of impervious surfaces and its impacts on soil organic carbon Y. Yan et al. 10.1007/s11252-022-01322-8
404. Time Series Remote Sensing Image Classification Using Feature Relationship Learning P. Dou et al. 10.1109/TGRS.2024.3386171
405. Accuracy Performance of Three 10-m Global Land Cover Products Around 2020 in an Arid Region of Northwestern China Q. Bie et al. 10.1109/ACCESS.2023.3336733
406. Assessing the applicability of binary land-cover variables to species distribution models across multiple grains L. Gábor et al. 10.1007/s10980-024-01813-3
407. Mountain Forest Type Classification Based on One-Dimensional Convolutional Neural Network M. Bai et al. 10.3390/f14091823
408. Improving spectral estimation of soil inorganic carbon in urban and suburban areas by coupling continuous wavelet transform with geographical stratification Y. Hong et al. 10.1016/j.geoderma.2022.116284
409. Deep learning empowers the Google Earth Engine for automated water extraction in the Lake Baikal Basin K. Li et al. 10.1016/j.jag.2022.102928
410. Study on Relationship of Land Cover Changes and Ecohydrological Processes of the Tuul River Basin B. Dorjsuren et al. 10.3390/su13031153
411. Leaf area index retrieval with ICESat-2 photon counting LiDAR J. Zhang et al. 10.1016/j.jag.2021.102488
412. Spatio-temporal land use/land cover dynamics and its driving forces in the Mekong Basin using Landsat imageries from 1988 to 2017 H. Li & L. Hong 10.1080/10106049.2022.2089736
413. Consistency Analysis and Accuracy Assessment of Three Global 30-m Land-Cover Products over the European Union using the LUCAS Dataset Y. Gao et al. 10.3390/rs12213479
414. Which land cover product provides the most accurate land use land cover map of the Yellow River Basin? W. Zhang et al. 10.3389/fevo.2023.1275054
415. Long Time Series High-Quality and High-Consistency Land Cover Mapping Based on Machine Learning Method at Heihe River Basin B. Zhong et al. 10.3390/rs13081596
416. The consequences of urbanization on vegetation photosynthesis in the Yangtze River Delta, China H. Yu et al. 10.3389/ffgc.2022.996197
417. Finer-Resolution Mapping of Global Land Cover: Recent Developments, Consistency Analysis, and Prospects L. Liu et al. 10.34133/2021/5289697
418. GLC_FCS30: global land-cover product with fine classification system at 30 m using time-series Landsat imagery X. Zhang et al. 10.5194/essd-13-2753-2021
419. Prolonged Drought Enhances Northwest China Dust Storm Activity J. Zhang et al. 10.1029/2022JD037088
420. Anthropogenic Land Use and Land Cover Changes—A Review on Its Environmental Consequences and Climate Change P. Roy et al. 10.1007/s12524-022-01569-w
421. Study of the Ecosystem Service Value Gradient at the Land–Water Interface Zone of the Xijiang River Mainstem Y. Huang et al. 10.3390/app131810485