Climate and Ecosystem of Arid and Semi-arid Regions

Climate and Ecosystem of Arid and Semi-arid Regions

Modeling Deforestation Using Logistic Regression (Case Study: Kuhdasht, Lorestan Province)

Document Type : Original Article

Authors
zohreh bazvand 1
kamran Adeli 2
Ziaedin Badehian 3
1 literacy movement street, third culture alley
2 Assistant professor of College of Agriculture and Natural Resources,Lorestan University, Iran
3 Assistant professor of College of Agriculture and Natural Resources,Lorestan University, Iran.
10.22075/ceasr.2024.30217.1014
Abstract
Background and Objectives: This study aims to determine the forest distribution and area over the period 1993-2013 and model the possibility of changes in forest. For this purpose, the relationship of forest changes with physiographic factors and many human factors using logistic regression were studied.
Methods: After geo-correction of the images and their classification using maximum likelihood algorithm, forest land use map related to 1993-2013 period was prepared. The map of forest changes was derived from intersection of the two maps.
Findings: To investigate the spatial relationship between forest changes and physiographic and human factors, logistic regression was used with slope and elevation as topographic variables, and distance from roads and village as human variables. Forest area has been 13250 ha which has decreased about 528 ha (equal to 9.8%) during the 20 years. Relative agreement between obtained model and the map of forest changes map by Pseudo R2 and ROC coefficient was equal to 0.22 and 0.73, respectively.
Conclusion: Distance from village, elevation and slope variables had negative relationship with the rate of destruction. However, the rate of destruction increases with increasing distance from the roads. Since the population influences the process of deforestation, it is recommended to use this factor in destruction evaluation and modeling.
Subjects
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Climate and Ecosystem of Arid and Semi-arid Regions
Volume 1, Issue 1 - Serial Number 1
December 2024
Pages 155-166

  • Receive Date 17 March 2023
  • Revise Date 23 December 2023
  • Accept Date 15 January 2024