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[1]Leyan X, Hongjian T, Zhang J*, et al. Remote Sensing and Machine Learning Uncover Dominant Drivers of Carbon Sink Dynamics in Subtropical Mountain Ecosystems[J]. Remote Sensing, 2025, 17(16): 2843.
[2]Peng M, Xu M, Zhang J*, et al. Mapping forest aboveground carbon stock of combined stratified sampling and RFRK model with mean annual temperature and precipitation[J]. Scientific Reports, 2025, 15(1): 17410.
[3]Huang K, Teng C, Zhang J*, et al. A New Spatiotemporal Filtering Method to Reconstruct Landsat Time-Series for Improving Estimation Accuracy of Forest Aboveground Carbon Stock[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2025.
[4]Yang K, Luo K, Zhang J*, et al. Estimating forest aboveground carbon sink based on landsat time series and its response to climate change[J]. Scientific Reports, 2025, 15(1): 589.
[5]Qiu B, Li S, Cao J, et al. Uncertainty Analysis of Forest Aboveground Carbon Stock Estimation Combining Sentinel-1 and Sentinel-2 Images[J]. Forests, 2024, 15(12): 2134.
[6]Xu M, Han X, Zhang J*, et al. Integrating ward’s clustering stratification and spatially correlated poisson disk sampling to enhance the accuracy of forest aboveground carbon stock estimation[J]. Forests, 2024, 15(12): 2111.
[7]Luo K, Feng Y, Liao Y, et al. Developing a method to estimate above-ground carbon stock of forest tree species Pinus densata using remote sensing and climatic data[J]. Forests, 2024, 15(11): 2023.
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