25 citations as recorded by crossref.

1. Using visible-near-infrared spectroscopy to classify lichens at a Neotropical Dry Forest J. Guzmán Q. et al. 10.1016/j.ecolind.2019.105999
2. Discrimination of liana and tree leaves from a Neotropical Dry Forest using visible-near infrared and longwave infrared reflectance spectra J. Guzmán Q. et al. 10.1016/j.rse.2018.10.014
3. Terrestrial Laser Scanning to Detect Liana Impact on Forest Structure S. Krishna Moorthy et al. 10.3390/rs10060810
4. On the relationship of fractal geometry and tree–stand metrics on point clouds derived from terrestrial laser scanning J. Guzmán Q. et al. 10.1111/2041-210X.13437
5. Semi-automatic extraction of liana stems from terrestrial LiDAR point clouds of tropical rainforests S. Krishna Moorthy et al. 10.1016/j.isprsjprs.2019.05.011
6. Mapping tropical dry forest age using airborne waveform LiDAR and hyperspectral metrics C. Sun et al. 10.1016/j.jag.2019.101908
7. Bird Assemblage Recovery in a Chronosequence of Tropical Dry Forests in Costa Rica B. Hilje et al. 10.3390/f11060629
8. Extraction of Liana Stems Using Geometric Features from Terrestrial Laser Scanning Point Clouds T. Han & G. Sánchez-Azofeifa 10.3390/rs14164039
9. Prediction of leaf traits of lianas and trees via the integration of wavelet spectra in the visible-near infrared and thermal infrared domains J. Guzmán Q. & G. Sanchez-Azofeifa 10.1016/j.rse.2021.112406
10. Lianas Abundance is Positively Related with the Avian Acoustic Community in Tropical Dry Forests B. Hilje et al. 10.3390/f8090311
11. On the estimation of tree mortality and liana infestation using a deep self-encoding network W. Li et al. 10.1016/j.jag.2018.05.025
12. Twenty‐first century remote sensing technologies are revolutionizing the study of tropical forests A. Sanchez‐Azofeifa et al. 10.1111/btp.12454
13. Using LiDAR waveform metrics to describe and identify successional stages of tropical dry forests Z. Gu et al. 10.1016/j.jag.2018.07.010
14. Can terrestrial laser scanners (TLSs) and hemispherical photographs predict tropical dry forest succession with liana abundance? G. Sánchez-Azofeifa et al. 10.5194/bg-14-977-2017
15. Unmanned Aerial System and Machine Learning Techniques Help to Detect Dead Woody Components in a Tropical Dry Forest C. Campos-Vargas et al. 10.3390/f11080827
16. Structure, environmental patterns and impact of expected climate change in natural beech-dominated forests in the Cantabrian Range (NW Spain) J. Castaño-Santamaría et al. 10.1016/j.foreco.2021.119512
17. Lianas research in the Neotropics: overview, interaction with trees, and future perspectives B. da Cunha Vargas et al. 10.1007/s00468-020-02056-w
18. Characterizing Transitions between Successional Stages in a Tropical Dry Forest Using LiDAR Techniques M. Duan et al. 10.3390/rs15020479
19. Modeling seasonal surface temperature variations in secondary tropical dry forests S. Cao & A. Sanchez-Azofeifa 10.1016/j.jag.2017.06.008
20. Identifying tropical dry forests extent and succession via the use of machine learning techniques W. Li et al. 10.1016/j.jag.2017.08.003
21. Conceptualising the Global Forest Response to Liana Proliferation A. Marshall et al. 10.3389/ffgc.2020.00035
22. Spatial Estimation of the Latent Heat Flux in a Tropical Dry Forest by Using Unmanned Aerial Vehicles P. Marzahn et al. 10.3390/f11060604
23. Hyperspectral and Full-Waveform LiDAR Improve Mapping of Tropical Dry Forest’s Successional Stages G. Zhao et al. 10.3390/rs13193830
24. MODIS and PROBA-V NDVI Products Differ when Compared with Observations from Phenological Towers at Four Tropical Dry Forests in the Americas J. Guzmán Q. et al. 10.3390/rs11192316
25. Terrestrial Laser Scanning to Detect Liana Impact on Forest Structure S. Krishna Moorthy et al. 10.3390/rs10060810