11 citations as recorded by crossref.

1. Mapping Uzon caldera vegetation using remote sensing data and machine learning N. Maksimovich et al. https://doi.org/10.35595/2414-9179-2025-2-31-83-99
2. Satellite Microwave Radiometry at L-Band for Monitoring Earth’s Essential Climate Variables: From Fundamental Physics to Sixteen Years of Global Climate Observations and Beyond Y. Zhou et al. https://doi.org/10.1109/MGRS.2026.3665669
3. Spatial Nonuniqueness in the Pan-Tropical LVOD–AGB Relationship: Implications for Biomass Retrieval J. Salazar-Neira et al. https://doi.org/10.1109/LGRS.2026.3687934
4. Decadal sink-source shifts of forest aboveground carbon since 1988 Z. Qian et al. https://doi.org/10.1038/s41467-026-76093-3
5. From observation to state variable: embedding microwave-constrained biomass into Big Earth Data system dynamics C. Varotsos & F. Mkrtchyan https://doi.org/10.1080/20964471.2026.2718651
6. Spatial Imbalance Patterns of Forest Carbon Density and Their Driving Mechanisms in the Xiuhe River Basin D. Zha et al. https://doi.org/10.3390/f17030312
7. Sentinel-1 vegetation optical depth retrievals over the international soil moisture network Z. Lu et al. https://doi.org/10.1080/17538947.2025.2555412
8. Multi-Source Remote Sensing Data Fusion for Aboveground Biomass Estimation in Tropical Forests: Recent Advances, Challenges, and Future Trends Q. Meng et al. https://doi.org/10.1109/ACCESS.2025.3649092
9. A long-term (2000–2022), high-resolution (0.005°) aboveground biomass dataset of global grasslands P. Wu et al. https://doi.org/10.1038/s41597-026-07544-1
10. Asymmetric responses of AGB and fAPAR in northern forest to climate condition Q. Liu et al. https://doi.org/10.1007/s11676-026-01991-7
11. Improving the Spatial Continuity of GEDI Aboveground Biomass Density Products Using Multisource Remote Sensing Data With Consideration of Spatial Correlation and Heterogeneity W. Min et al. https://doi.org/10.1109/JSTARS.2025.3611427