Showing 1,521 - 1,540 results of 4,451 for search '"forest"', query time: 0.04s Refine Results
  1. 1521

    City of Tampa Urban Ecological Analysis by Michael G. Andreu, Melissa H. Friedman, Shawn M. Landry, Robert J. Northrop

    Published 2009-01-01
    “…Northrop, summarizes a report of an ecological assessment of the city of Tampa’s urban forest resources. Published by the UF School of Forest Resources and Conservation, December 2008. …”
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    Article
  2. 1522

    Thinning Southern Pines - A Key to Greater Returns by Chris Demers, Alan Long, Jarek Nowak

    Published 2007-01-01
    “…Published by the UF School of Forest Resources and Conservation, December 2006. …”
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    Article
  3. 1523

    Wildland-Urban Interface: Key Issues by L. Annie Hermansen-Baez, Jennifer Seitz, Martha C. Monroe

    Published 2009-04-01
    “…Published by the UF School of Forest Resources and Conservation, October 2008. …”
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    Article
  4. 1524

    Wind and Trees: Lessons Learned from Hurricanes by Mary L. Duryea, Eliana Kampf

    Published 2007-11-01
    “…Published by the UF School of Forest Resources and Conservation, September 2007. …”
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    Article
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    Fire-driven disruptions of global soil biochemical relationships by Guiyao Zhou, Nico Eisenhauer, Zhenggang Du, Manuel Esteban Lucas-Borja, Kaiyan Zhai, Miguel Berdugo, Huimin Duan, Han Wu, Shengen Liu, Daniel Revillini, Tadeo Sáez-Sandino, Hua Chai, Xuhui Zhou, Manuel Delgado-Baquerizo

    Published 2025-01-01
    “…The impacts of fire are most strongly negative in cold climates, conifer forests, and under wildfires with high intensity and frequency. …”
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    Article
  8. 1528

    Comparative analysis of Sentinel-2 and PlanetScope imagery for chlorophyll-a prediction using machine learning models by Eden T. Wasehun, Leila Hashemi Beni, Courtney A. Di Vittorio, Christopher M. Zarzar, Kyana R.L. Young

    Published 2025-03-01
    “…Utilizing five machine learning models, namely linear regression (LR), least absolute shrinkage and selection operator (LASSO), extreme gradient boosting (XGBoost), random forest (RF), and support vector regression (SVR), we constructed inversion models. …”
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    Article
  9. 1529
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  12. 1532

    Butterfly Abundance and Diversity in Different Habitat Types in the Usangu Area, Ruaha National Park by Evaline J. Munisi, Emmanuel H. Masenga, Ally K. Nkwabi, Halima R. Kiwango, Eblate E. Mjingo

    Published 2024-01-01
    “…This study clearly shows the importance of Miombo woodland and riverine forest habitats in sustaining rich butterfly diversity and abundance in Usangu area. …”
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    Article
  13. 1533

    Early Root Development of Eucalyptus pellita F. Muell. Seedlings from Seed and Stem Cutting Propagation Methods at Nursery Stage by Affendy Hassan, Parveena Balachandran, Khairiyyah R. Khamis

    Published 2021-01-01
    “…With such information, it is useful for forest plantation company management in enhancing the understanding of strategies to optimize yield production with the appropriate agronomic or silvicultural approach in the field of planting. …”
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    Article
  14. 1534
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  16. 1536

    Hyperdominance of Tree Species and Biomass in Mount Gede Pangrango National Park, Indonesia by Andes Hamuraby Rozak, Sri Astutik, Zaenal Mutaqien, Didik Widyatmoko, Endah Sulistyawati

    Published 2017-01-01
    “…The hyperdominance of tree species and biomass is a concept explaining the importance of a small portion of species and biomass relative to the average of biomass in a forested area. Understanding this concept has important implication on forest monitoring, especially to monitor the most significant species that show high contributes on biomass and its ecological restoration. …”
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    Article
  17. 1537
  18. 1538

    A two-step machine learning approach for predictive maintenance and anomaly detection in environmental sensor systems by Saiprasad Potharaju, Ravi Kumar Tirandasu, Swapnali N. Tambe, Devyani Bhamare Jadhav, Dudla Anil Kumar, Shanmuk Srinivas Amiripalli

    Published 2025-06-01
    “…This research is novel in seamlessly blending unsupervised anomaly detection using Isolation Forest to create labels for data points that were previously unlabeled. …”
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    Article
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