Mapping forest types using ecological niche modeling and fuzzy accuracy assessment in Thailand

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Published: Dec 29, 2022
DOI: https://doi.org/10.14456/sehs.2022.53
Keywords:
tropical forest type ecotone forest ecological niche model fuzzy accuracy assessment

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Yaowaret Jantakat
Department of Information and Communication Technology, Faculty of Sciences and Liberal Arts, Rajamangala University of Technology Isan, Nakhon Ratchasima, Thailand. Corresponding author's e-mail: yaowaret.ja@rmuti.ac.th
Jefferson Fox
East West Center, Honolulu, Hawaii, USA
Pongpun Juntakut
Department of Civil Engineering, Chulachomklao Royal Military Academy, Nakhon Nayok, Thailand

Abstract

The forest map remains essential for investigating plant ecology and biodiversity patterns. This study proposed methods for mapping forest types based on ecological niche modeling and then used fuzzy error matrix for accuracy assessment. The upper Ping basin of northern Thailand was selected as study area. The modeled data included forest inventory, topographic, climatic, soil, and geological data. Ecological niche factor analysis was used to model and produce the best habitat suitability index of each forest type, which were then combined using hierarchically generated coding. As a result, eight classes of forest types were generated: dry dipterocarp forest (7,373.94 km2, 32.81%), evergreen ecotone or transition area (3,666.97 km2, 16.32%), mixed deciduous forest (3,440.79 km2, 15.31%), deciduous ecotone or transition area (3,225.58 km2, 14.35%), deciduous and evergreen forest (2,027.12 km2, 9.02), coniferous forest (CF; 365.28 km2, 1.63%), moist and dry evergreen forest (290.08 km2, 1.29%), and hill evergreen forest (270.56 km2, 1.21%). Four variables were found to be critical in forest type distribution: elevation, mean annual temperature, annual maximum temperatures and annual minimum temperatures. To assess map accuracy, fuzzy error matrix, which allows the recognition of ambiguous classes and does not ignore variation in the interpretation of the reference data at class boundaries, was used (75.89% of overall accuracy).

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How to Cite
Jantakat, Y., Fox, J., & Juntakut, P. (2022). Mapping forest types using ecological niche modeling and fuzzy accuracy assessment in Thailand. Science, Engineering and Health Studies, 16, 22020011. https://doi.org/10.14456/sehs.2022.53
Issue
Volume 16, 2022
Section
Physical sciences
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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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