Image texture indices and trend analysis for forest disturbance assessment under wood harvest regimes

Effective disturbance indices for Hyrcanian forests in Kheyroud, Nowshahr, Iran were determined. The study area was divided into landscape mosaics based on ecosystem parameters including profile type, slope and elevation. Co-occurrence texture indices were derived as forest disturbance factors on th...

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Bibliographic Details
Published in:Journal of forestry research 2021-04, Vol.32 (2), p.579-587
Main Authors: Salmanmahiny, Abdolrassoul, Erfani, Malihe, Danehkar, Afshin, Etemad, Vahid
Format: Article
Language:English
Subjects:
Analysis
Artificial neural networks
Biomedical and Life Sciences
Disturbance
Earth resources technology satellites
Forest management
Forestry
Landsat
Landsat satellites
Life Sciences
Mosaics
Neural networks
Original Paper
Remote sensing
Satellite imagery
Texture
Trend analysis
Wood
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Summary:Effective disturbance indices for Hyrcanian forests in Kheyroud, Nowshahr, Iran were determined. The study area was divided into landscape mosaics based on ecosystem parameters including profile type, slope and elevation. Co-occurrence texture indices were derived as forest disturbance factors on the first five bands of Landsat TM, ETM+ and OLI images for the prevailing wood harvest disturbance regimes. These indices were screened using ten types of trend analyses and used for modeling disturbance of the harvesting regime through artificial neural networks. The results show that the selected indices can be useful in distinguishing areas with different disturbance intensities and as such, used in the context of health assessment through the health distance method. The accuracy of the health maps derived from the indices [increasing disturbance] led to give rise higher disturbance classification accuracy.
ISSN:1007-662X
1993-0607
DOI:10.1007/s11676-020-01117-7