Analysis of land use and land cover using ecological landscape metrics (case study: Arasbaran region)

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NASIRI VAHID; DARVISHSEFAT ALI ASGHAR

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Journal: Environmental Sciences Year:2018 | Volume:16 | Issue:3 Page(s): 101-118

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Title

Analysis of land use and land cover using ecological landscape metrics (case study: Arasbaran region)

Author(s)

NASIRI VAHID | DARVISHSEFAT ALI ASGHAR | Issue Writer Certificate

Keywords

Landscape metricsQ2

Landscape ecologyQ1

Land useQ1

ArasbaranQ1

Abstract

Nasiri, V. and Darvishsefat, A. A., 2018. Analysis of Land use and land cover using ecological Landscape metrics (case study: Arasbaran region). Environmental Sciences. 16 (3), 99-116. Introduction: A landscape is a heterogeneous and vast region consisting of a set of patches, habitats, and repetitive environmental elements. In recent studies, various metrics have been used to investigate the structure, function, and landscape pattern changes. The metrics are quantitative indices that describe the structural and spatial properties of the landscape. The objective of this study was to obtain information on the current status of different Land use classes and the analysis of complex relationships among classes in Arasbaran region. Material and methods: In this regard, a Land use/land cover (LULC) map with seven classes (i. e., high-density forest, low-density forest, agriculture, grassland, barren land, water, and urban area) was produced from Landsat 8 OLI imagery (2014) and ancillary data. Eighteen different Landscape metrics including area metrics, shape metrics, isolation and proximity metrics and diversity metrics were calculated for each class and landscape level. Results and discussion: Results showed that the high-density forest and grassland form the main elements of Arasbaran landscape with 30. 76% and 30. 03% of the Percentage of landscape, respectively. The metrics of number and density of patches showed that grassland and low-density forest classes had the highest number of patches compared to other Land use classes and so are the finest grained Land use classes in the area. The largest patch index also showed that 4. 76 percent of the landscape was occupied by the largest high-density forest patch. The total edge and edge density indicated that the majority of the area is covered by high-density forest and it provides the longest border with other Land uses. Based on the shape metric, urban area and barren land have the most dispersion. In addition, the urban area and highdensity forest are the most discontinuous and continuous Land uses in the landscape, respectively. Based on the mean of Euclidean distance, the distance between the high-density forest patches is the minimum and the distance between the urban patches is the maximum metric. In total, the study area is composed of 802 LULC patches. Also, based on Shannon and Simpson diversity and uniformity metrics, the area is diverse and heterogeneous. Conclusion: Considering the fine-grained grasslands and forests with high (dis) connectivity, the dispersion of urban areas, and the extent of agricultural lands, an increasing rate of changes in the Land use can be estimated in the future. The future changes can be as removing small patches of grassland and forests, and expansion of the urban and agricultural classes.

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APA: Copy

NASIRI, VAHID, & DARVISHSEFAT, ALI ASGHAR. (2018). Analysis of land use and land cover using ecological landscape metrics (case study: Arasbaran region). ENVIRONMENTAL SCIENCES, 16(3 ), 101-118. SID. https://sid.ir/paper/117464/en

Vancouver: Copy

NASIRI VAHID, DARVISHSEFAT ALI ASGHAR. Analysis of land use and land cover using ecological landscape metrics (case study: Arasbaran region). ENVIRONMENTAL SCIENCES[Internet]. 2018;16(3 ):101-118. Available from: https://sid.ir/paper/117464/en

IEEE: Copy

VAHID NASIRI, and ALI ASGHAR DARVISHSEFAT, “Analysis of land use and land cover using ecological landscape metrics (case study: Arasbaran region),” ENVIRONMENTAL SCIENCES, vol. 16, no. 3 , pp. 101–118, 2018, [Online]. Available: https://sid.ir/paper/117464/en

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