Analysis of the Relationship between Land Use Changes and Land Cover Metrics: The Case of Barandozchay Watershed

جغرافیا و مخاطرات محیطی

Article 14, Volume 13, Issue 3 - Serial Number 51, November 2024, Pages 367-392   

Document Type: Research Article

DOI: 10.22067/geoeh.2024.86229.1452

Authors

Mohammad Koohani¹; Javad Behmanesh^{* 2}

¹Ph.D. Student in Water Engineering , Department of Water Engineering, University of Urmia, Urmia, Iran.

²Professor in Water Engineering, Department of Water Engineering, University of Urmia, Urmia, Iran.

Abstract

This study analyzes the relationship between land use changes over different time periods and land cover metrics using data from the Barandozchay watershed in West Azerbaijan Province, Iran. To achieve this goal, Sentinel-2 satellite images for the years 2016 and 2022 were obtained from the European Union's Copernicus website. Pre-processing techniques were applied using various software tools, and the images were classified through knowledge-based and object-oriented methods in the eCognition software environment. Land use maps were generated, and land cover metrics were quantified and calculated at landscape and class levels using Fragstats 8.2 software.
The results at the class level showed that the split index (SPLIT) had the highest value for the blue area, while the cohesion index (COHESION) had the lowest value in both years. The grassland class exhibited the highest SHAPE-MN and LSI indices, indicating patch disorder. If protective measures are not implemented, further degradation of grasslands in the Barandozchay watershed could occur in the coming years.
At the landscape level, the results revealed a decreasing trend in most indices related to watershed connectivity. The ENN_MN index, representing the mean Euclidean distance between nearest neighbors, the CONTAG index, representing contagion, and the COHESION index, representing patch cohesion, all showed a decline from 2016 to 2022. Conversely, the LSI and NP indices displayed an increasing trend, indicating greater irregularity within the area.
The findings also showed that the blue area experienced the highest level of fragmentation, whereas dry farming exhibited the least. Additionally, grassland patches demonstrated the highest connectivity, while dry farming patches had the lowest. At the landscape level, the results indicated a uniform distribution of patches in the Barandozchay watershed. The increasing number of patches, extended margins, and reduced patch size led to fragmentation and the formation of smaller, isolated patches.These outcomes highlight the ongoing land use changes and their impact on the structure and connectivity of the landscape. They provide valuable insights for land use management and conservation efforts in the study area, ensuring the sustainability of natural resources for future generations.

Keywords

Land Use Change; Landscape Metrics; Sentinel-2 Satellite Imagery; Object-Oriented Classification; Fragmentation Analysis; Ecosystem Degradation

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