Abstract
Leaf maturation from initiation to senescence is a phenological event of plants that results from the influences of temperature and water availability on physiological activities during a life cycle. Detection of newly grown leaves (NGL) is therefore useful for the diagnosis of tree growth, tree stress, and even climatic change. This paper applies Constrained Energy Minimization (CEM), which is a hyperspectral target detection technique to spot grown leaves in a UAV multispectral image. According to the proportion of NGL in different regions, this paper proposes three innovative CEM based detectors: Subset CEM, Sliding Window-based CEM (SW CEM), and Adaptive Sliding Window-based CEM (AWS CEM). AWS CEM can especially adjust the window size according to the proportion of NGL around the current pixel. The results show that AWS CEM improves the accuracy of NGL detection and also reduces the false alarm rate. In addition, the results of the supervised target detection depend on the appropriate signature. In this case, we propose the Optimal Signature Generation Process (OSGP) to extract the optimal signature. The experimental results illustrate that OSGP can effectively improve the stability and the detection rate.
Highlights
The persistence of forest ecosystem resources is the key to protecting wild coverage of reproductive trees in order to alleviate global warming or the impact of climate change
The results show that AWS Constrained Energy Minimization (CEM) improves the accuracy of newly grown leaves (NGL) detection and reduces the false alarm rate
The CEM only needs the spectral signature of one specific target of interest during target detection; it is free of the spectral signature of other targets or background
Summary
The persistence of forest ecosystem resources is the key to protecting wild coverage of reproductive trees in order to alleviate global warming or the impact of climate change. Using telemetry to monitor the health level of forest ecosystems has a critical effect on the subject of global warming control. Trees start to sprout once they sense the growing signals in early spring. The newly grown leaves (NGL) can be seen as the first objects of trees in response to a change in temperature, and can provide critical information for the early detection of climate changes [4]. Taking the strengths of UAV-sensed images, NGL over a forest area can be detected via appropriate remote sensing techniques
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
