In recent years, boxwood dieback has become one of the essential concerns of practitioners and managers of the natural resources of the country. To control the expansion of the factors contributing to the dieback of box trees, the early detection and preparation of dist More
In recent years, boxwood dieback has become one of the essential concerns of practitioners and managers of the natural resources of the country. To control the expansion of the factors contributing to the dieback of box trees, the early detection and preparation of distribution maps are required. Assessment data can play an important role in this regard. The combination of high-resolution and low-spectrum panchromatic images with low resolution is used for evaluating the extent of destruction. Also, spectral and textural features are considered simultaneously in images extracted from Landsat 8 satellite. Finally, by extracting effective features from the candidate description space with the help of genetic algorithm and using the appropriate classification in the form of simultaneous application of fuzzy clustering and maximum similarity classification of area resulted in good accuracy in 2014-2018.
The coefficients obtained from the models confirm their model validation for future estimates and the possibility it usage to assess the extent of the affected areas and the evolution of progress for all regions.
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