yasrebi, banafshe, abbasi, hamidreza, behnamfar, korosh, dinarvand, mehri (2022). Land use/ Land Cover Dynamic Modeling Using RS and GIS with Emphasis on Maximum Likelihood Rule and Transition Matrix. , 10(3), 191-202.
banafshe yasrebi; hamidreza abbasi; korosh behnamfar; mehri dinarvand. "Land use/ Land Cover Dynamic Modeling Using RS and GIS with Emphasis on Maximum Likelihood Rule and Transition Matrix". , 10, 3, 2022, 191-202.
yasrebi, banafshe, abbasi, hamidreza, behnamfar, korosh, dinarvand, mehri (2022). 'Land use/ Land Cover Dynamic Modeling Using RS and GIS with Emphasis on Maximum Likelihood Rule and Transition Matrix', , 10(3), pp. 191-202.
yasrebi, banafshe, abbasi, hamidreza, behnamfar, korosh, dinarvand, mehri Land use/ Land Cover Dynamic Modeling Using RS and GIS with Emphasis on Maximum Likelihood Rule and Transition Matrix. , 2022; 10(3): 191-202.

Land use/ Land Cover Dynamic Modeling Using RS and GIS with Emphasis on Maximum Likelihood Rule and Transition Matrix

ECOPERSIA
Article 3, Volume 10, Issue 3 - Serial Number 41, 2022, Pages 191-202    PDF (2.7 M)
Document Type: Original Research
Authors
banafshe yasrebi* 1; hamidreza abbasi2; korosh behnamfar3; mehri dinarvand1
1Natural Resources Department of Khuzestan Agricultural and Natural Resources Research and Education Center, AREEO, Ahvaz, Iran-
2Desert Department of institute of Forests and Rangelands, Agricultural Research, Education and Extension Organization (AREEO), Tehran, Iran
3Natural Resources Department of Khuzestan Agricultural and Natural Resources Research and Education Center, AREEO, Ahvaz, Iran
Abstract
Aims: Understanding the patterns of land use and land cover (LULC) change is important for efficient environmental restoration. This study focused on changes in LULC patterns of the Koupal watershed in Khouzestan Province over 22 years.

Materials and Methods: Multi temporal satellite imagery of the Landsat series (1998 and 2020) were preprocessed and used to extract LULC maps by bayes discriminant and Maximum likelihood rule. Reliability of classified maps were checked using confusion matrix.Transition matrix and change rate were computed by Change detection analysis.

Findings: The results of the change detection analysis shows that vegetation cover witness of dramatic decrease and changed from 27.6% to 0.06%, followed by water body reduction from 8.59% to 0.79% and bare land decrease from 57.9% to 51% of whole area. The results indicates a rapid expansion of cropland from 5.44% to 41.25% of total area. Sand dune increased from 1.08% of total area in 1998 to 2.75% in 2020 and build up area shows a growth from0.27% of total area. Change matrix revealed that 93% of cropland remained unchanged, followed by bare land (71%), built up (53%), water body (7%), sand dune (6%) and vegetation (0.05%). This indicates that vegetation experienced the most significant loss and highest conversion during this period, with almost 73% of its total area converted to cropland and bare land (22%) and the rest to other land uses.

Conclusion: These results establish LULC trends in past 22 years and provide crucial data useful for planning and sustainable land use management.
Keywords
Change Detection; land use land cover change; Land use management; sustainable development
References
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