The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Classification of riparian forest species and health condition using multi-temporal and hyperspatial imagery from unmanned aerial system
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Cites
Textural Features for Image Classification
Haralick, R. M., Shanmugam, K., & Dinstein, I. (1973) · IEEE Transactions on Systems, Man, and Cybernetics · doi:10.1109/tsmc.1973.4309314 · Cited by 22,886
Random forests for classification in ecology
Cutler, D. R., Edwards, T. C., Beard, K. H., Cutler, A., Hess, K. T., Gibson, J., & Lawler, J. J. (2007) · Ecology · doi:10.1890/07-0539.1 · Cited by 4,950
Variable selection using random forests
Genuer, R., Poggi, J.-M., & Tuleau-Malot, C. (2010) · Pattern Recognition Letters · doi:10.1016/j.patrec.2010.03.014 · Cited by 2,619
Cited by
Remote sensing in forestry: current challenges, considerations and directions
Fassnacht, F. E., White, J. C., Wulder, M. A., & Næsset, E. (2024) · Forestry: An International Journal of Forest Research · doi:10.1093/forestry/cpad024 · Cited by 353
Drones for Conservation in Protected Areas: Present and Future
Jiménez López, J., & Mulero-Pázmány, M. (2019) · Drones · doi:10.3390/drones3010010 · Cited by 300
UAV-Based Forest Health Monitoring: A Systematic Review
Ecke, S., Dempewolf, J., Frey, J., Schwaller, A., Endres, E., Klemmt, H.-J., Tiede, D., & Seifert, T. (2022) · Remote Sensing · doi:10.3390/rs14133205 · Cited by 284
Networked Unmanned Aerial Vehicles for Surveillance and Monitoring: A Survey
Li, X., & Savkin, A. V. (2021) · Future Internet · doi:10.3390/fi13070174 · Cited by 107
Evaluating the Forest Ecosystem through a Semi-Autonomous Quadruped Robot and a Hexacopter UAV
Idrissi, M., Hussain, A., Barua, B., Osman, A., Abozariba, R., Aneiba, A., & Asyhari, T. (2022) · Sensors · doi:10.3390/s22155497 · Cited by 25
Metadata
- Authors
- Michez, A., Piégay, H., Lisein, J., Claessens, H., & Lejeune, P.
- Venue
- Environmental Monitoring and Assessment
- Published
- 2016-02-05
- Volume
- 188
- Issue
- 3
- Pages
- 146-146
- ISSN
- 0167-6369 (ISSN-L)
- 1573-2959
- OpenAlex
- W2257554162
- Cited by
- 241
- References
- 3
- FWCI
- 28.82
- Type
- journal article
- Language
- en
- Open access
- green
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- The paper
- Michez, A., Piégay, H., Lisein, J., Claessens, H., & Lejeune, P. (2016). Classification of riparian forest species and health condition using multi-temporal and hyperspatial imagery from unmanned aerial system. Environmental Monitoring and Assessment. https://doi.org/10.1007/s10661-015-4996-2
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
