Abstract
Improperly grown trees may cause huge hazards to the environment and to humans, through e.g., climate change, soil erosion, etc. A proximity environmental feature-based tree health assessment (PTA) scheme is proposed to prevent these hazards by providing guidance for early warning methods of potential poor tree health. In PTA development, tree health is defined and evaluated based on proximity environmental features (PEFs). The PEF takes into consideration the seven surrounding ambient features that strongly impact tree health. The PEFs were measured by the deployed smart sensors surrounding trees. A database composed of tree health and relative PEFs was established for further analysis. An adaptive data identifying (ADI) algorithm is applied to exclude the influence of interference factors in the database. Finally, the radial basis function (RBF) neural network (NN), a machine leaning algorithm, has been identified as the appropriate tool with which to correlate tree health and PEFs to establish the PTA algorithm. One of the salient features of PTA is that the algorithm can evaluate, and thus monitor, tree health remotely and automatically from smart sensor data by taking advantage of the well-established internet of things (IoT) network and machine learning algorithm.
Highlights
As one of the most common species on earth, trees play an important role in protecting the ecological environment, and have a great impact on human activities
The results show that the adaptive data identifying (ADI) algorithm can effectively improve the performance of the evaluation model
One hundred trees distributed in parks and campus were selected to verify the effectiveness of the proposed proximity environmental feature-based tree health assessment (PTA) algorithm
Summary
As one of the most common species on earth, trees play an important role in protecting the ecological environment, and have a great impact on human activities. Improperly grown trees can cause potential hazards such as soil erosion and global warming. It is estimated that the total cost of damage and erosion prevention are 44.4 billion dollars every year [1], which could have been avoided by dedicating more resources to tree health. Global warming will intensify and cause greater harm [2]. Global warming yields dry weather and harms agricultural production. Agricultural crops will not grow well due to high temperatures and droughts. Evidence of this is shown in the fact that a direct economic loss of 5.4 billion dollars was caused in China in 2017 [3]
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