In this individual tree and forest stand based research, the solutions searched with using very high-resolution (VHR) satellite images for time-consuming problems in forestry applications.
📌 3 Key Takeaways
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Objective & Hypothesis:Remote Sensing technologies have been used quite a long time in forestry applications.
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Key Findings & Data:The most important characteristics of this research will bring the new opportunities for forestry applications by using the object-based classification methods with multispectral satellite images that have high spatial resolution (<1meter).
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Conclusion & Impact:In this individual tree and forest stand based research, the solutions searched with using very high-resolution (VHR) satellite images for time-consuming problems in forestry applications.
🔬Design:Survey & Empirical Study
📍Scope:Comprehensive Sample
⚙️Variables:Worldview-2 · Object-based image analysis · Tree crown
Abstract
Remote Sensing technologies have been used quite a long time in forestry applications. While the more acquired data can be obtained with traditional survey and photogrammetric techniques, they required relatively more manpower and time consuming. The most important characteristics of this research will bring the new opportunities for forestry applications by using the object-based classification methods with multispectral satellite images that have high spatial resolution (<1meter). In this individual tree and forest stand based research, the solutions searched with using very high-resolution (VHR) satellite images for time-consuming problems in forestry applications.
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