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

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Abstract

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.

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Authors and Affiliations

  1. Department of Environmental Science, Gorgan University of Agricultural Sciences and Natural Resources, Gorgān, Iran

    Abdolrassoul Salmanmahiny

  2. Department of Environmental Sciences, Faculty of Natural Resources, University of Zabol, Zabol, Iran

    Malihe Erfani

  3. Department of Environmental Sciences, Faculty of Natural Resources, University of Tehran, Tehran, Iran

    Afshin Danehkar

  4. Department of Forestry and Forest Economics, Faculty of Natural Resources, University of Tehran, Tehran, Iran

    Vahid Etemad

Authors
  1. Abdolrassoul Salmanmahiny
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  2. Malihe Erfani
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  3. Afshin Danehkar
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  4. Vahid Etemad
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Correspondence to Malihe Erfani.

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Project funding: The work was funded partly by University of Zabol under Grant Number UOZ-GR-9616-145.

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Corresponding editor: Tao Xu.

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Salmanmahiny, A., Erfani, M., Danehkar, A. et al. Image texture indices and trend analysis for forest disturbance assessment under wood harvest regimes. J. For. Res. 32, 579–587 (2021). https://doi.org/10.1007/s11676-020-01117-7

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  • DOI: https://doi.org/10.1007/s11676-020-01117-7

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