Using Landscape Metrics and Remote Sensing to Analyze Land Changes and Land Degradation (Case Study: Shirin Dare Watershed Basin-North Khorasan province-Iran)

Subject Areas : ارزیابی پی آمدهای محیط زیستی

Zahra  Parvar ¹ (PhD, Department of Environmental Science, Faculty of Natural Resources and Environment, Malayer University, Malayer, Iran. *(Corresponding Author))
Kamran  Shayesteh ² (PhD, Department of Environmental Science, Faculty of Natural Resources and Environment, Malayer University, Malayer, Iran)
Morteza  Behzadfar ³ (PhD, Watershed Management Engineering and Sciences, Management and Planning Organization, North Khorasan, Iran.)

Received: 2023-08-19 Accepted : 2023-09-18 Published : 2024-02-17

Keywords: Change analysis, Landscape Metrics, Shirin Dare Watershed Basin, Fragstats 4.2, Landsat, Fragmentation,

Abstract :

Background and Objective: Land Use and Land Cover change is one of the most important factors affecting natural resources and at a worldwide scale. Analyzing and monitoring the Changes is a complex procedure. The analysis of landscape pattern as an important procedure helps researchers to realize and quantify LULC changes of the earth surface. The ability to quantify to describe landscape structure is prerequisite to the study of landscape function and change. Landscape ecology has various quantitative indices to analyze and describe the landscape structure for this purpose. Landscape metrics represent the spatial pattern of the entire landscape mosaic e.g. the proportion of each landscape type, or the shape of the component landscape elements at a set point in time. Material and Methodology: This study applied supervised classification-maximum likelihood in IDRISI Selva to detect land cover/land use changes observed in Shirin dare watershed using satellite data obtained from Landsat for the years 1996, 2005 and 2015 respectively. The watershed was classified into six major land cover/use classes viz based on our purpose. Various class-level and landscape level-landscape pattern metrics were calculated using Fragstats 4.2 in order to analyze landscape structure. Metrics include NP, MPS, LPI, SIDI, SHDI, SHEI and SIEI were used in this study. These metrics can give us a lot of information about the structure and changes of landscape components. Findings: The overall classification accuracies in land use cartographies in 1996, 2005 and 2015 were 92.96%, 87.29% and 87/45%, respectively. Our results between 2005 and 2015 were clearly showed that increased number of patches and decreased mean patch area two important fragmentation indicators and the trend of landscape degradation and fragmentation was increasing. Discussion and Conclusion: According to the current patterns of dry farm land and barren land development in the studied landscape and in order to reduce the alarming rates of land degradation and become more efficient land use managers, it is necessary to know the causes of land changes. That means with the ongoing land degradation trend, a reasonable land use plan should be made with emphasis on protecting natural forests, grasslands and the water body.

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