Assessment of forest cover changes using multi-temporal Landsat observation

Elahe Moradi and Alireza Sharifi ()
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Elahe Moradi: Shahid Rajaee Teacher Training University
Alireza Sharifi: Shahid Rajaee Teacher Training University

Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, 2023, vol. 25, issue 2, No 15, 1360 pages

Abstract: Abstract Monitoring the changes in forest cover has become an important tool for forest management due to its impact on climate change, desertification, soil erosion, and flooding. The Zagros Mountains forest-steppe is a temperate broadleaf and mixed forest ecoregion in Western Asia, and the present study analyzes the changes in Zagros forests from 1986 to 2019 using remote sensing techniques. Three Landsat images, acquired in 1986, 2002, and 2019, were used to map land cover classification in the study area. Classification kappa coefficients were 85.2, 94.1, and 94.7 for three images, respectively. Focusing on the class level, the results show that between 1986 and 2002, the primary cause of forest loss in the study area was the conversion of 7.8 thousand ha of oak forests to agricultural land. Since 2002, 0.8 thousand ha of oak forest cover have been changed to barrenlands. The decrease of Zagros forests is a main threat to the rich biodiversity found in the West of Iran. To avoid worsening soil erosion, restoration programs should prioritize planting patterns on rainfall and hill slopes, texturally dissimilar soils, and regeneration in forest gaps, particularly at high elevations and steep slopes. It is recommended that future research should use higher resolution datasets and encompass more expansive landscape units, such as the whole Zagros Mountain forests.

Keywords: Forest cover change; Landsat data; Convolutional neural networks; Change detection; Zagros forests (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s10668-021-02097-2

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