13 citations as recorded by crossref.

1. A Conceptual Model for Detecting Small-Scale Forest Disturbances Based on Ecosystem Morphological Traits J. Stoddart et al. 10.3390/rs14040933
2. Using machine learning algorithms to predict groundwater levels in Indonesian tropical peatlands I. Hikouei et al. 10.1016/j.scitotenv.2022.159701
3. Qualifying the Information Detected from Airborne Laser Scanning to Support Tropical Forest Management Operational Planning C. Reis et al. 10.3390/f12121724
4. Remote sensing of selective logging in tropical forests: current state and future directions C. Jackson & E. Adam 10.3832/ifor3301-013
5. Structural Recovery of Logged Forests in the Solomon Islands: Implications for Conservation and Management E. Katovai et al. 10.1177/19400829211028125
6. Logging leaves a fingerprint on the number, size, spatial configuration and geometry of tropical forest canopy gaps B. Zhang et al. 10.1111/btp.13190
7. Indicators for monitoring reduced impact logging in the Brazilian amazon derived from airborne laser scanning technology Q. Barros et al. 10.1016/j.ecoinf.2024.102654
8. Dynamics of a human‐modified tropical peat swamp forest revealed by repeat lidar surveys B. Wedeux et al. 10.1111/gcb.15108
9. Effects of distance from canal and degradation history on peat bulk density in a degraded tropical peatland A. Sinclair et al. 10.1016/j.scitotenv.2019.134199
10. Wavelet Based Analysis of TanDEM-X and LiDAR DEMs across a Tropical Vegetation Heterogeneity Gradient Driven by Fire Disturbance in Indonesia E. De Grandi et al. 10.3390/rs8080641
11. Long-Term Impacts of Selective Logging on Amazon Forest Dynamics from Multi-Temporal Airborne LiDAR E. Rangel Pinagé et al. 10.3390/rs11060709
12. Can we set a global threshold age to define mature forests? P. Martin et al. 10.7717/peerj.1595
13. Deciphering the fingerprint of disturbance on the three‐dimensional structure of the world’s forests T. Jucker 10.1111/nph.17729