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

Document Type : Research Article

Authors

• Mohammad Koohani ¹
• Javad Behmanesh ²

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

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

https://doi.org/10.22067/geoeh.2024.86229.1452

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

Main Subjects

• Biological hazards

©2024 The author(s). This is an open access article distributed under Creative Commons Attribution 4.0 International License (CC BY 4.0)

References

Alaei, N., Mustafazadeh, R., Esmaaliouri, A., Sharari, M., & Hazbavi, Z. (2020). Assessment and Comparison of Landscape Connectivity in KoozehTopraghi Watershed, Ardabil Province. Iranian Journal of Applied Ecology, 8(4),19-34.[In Persian]  http://dx.doi.org/10.47176/ijae.8.4.2572

Armenteras, D., Murcia, U., González, T. M., Barón, Ó. J., & Arias, J. E. (2019). Scenarios of land use and land cover change for NW Amazonia: Impact on forest intactness. Global Ecology and Conservation, 17, e00567. http://dx.doi.org/10.1016/j.gecco.2019.e00567

Aunap, R., Uuemaa, E., Roosaare, J., & Mander, Ü. (2006). Spatial correlograms and landscape metrics as indicators of land use changes. WIT Transactions on Ecology and the Environment, 89. http://dx.doi.org/10.2495/GEO060311

Berila, A., & Isufi, F. (2021). Two decades (2000–2020) measuring urban sprawl using GIS, RS and landscape metrics: a case study of Municipality of Prishtina (Kosovo). Journal of Ecological Engineering, 22(6),114-125. https://doi.org/10.12911/22998993/137078

Birhanu, A., Masih, I., van der Zaag, P., Nyssen, J., & Cai, X., (2019). Impacts of land use and land cover changes on hydrology of the Gumara catchment, Ethiopia. Physics and Chemistry of the Earth, Parts a/b/c, 112, 165-174. https://doi.org/10.1016/j.pce.2019.01.006

Blaschke, T. (2010). Object based image analysis for remote sensing. ISPRS Journal of Photogrammetry and Remote Sensing, 65(1), 2-16. https://doi.org/10.1016/j.isprsjprs.2009.06.004

Dezhbani, H., Mustafazadeh, R., Esmaaliouri, A., & Nazila, A. (2023). Analysis of the relationship between spatial and temporal changes in land use and landscape metric in the Kozetaparaghi watershed. Journal of Geography and Environmental Studies, 12(45), 82-99. [In Persian] https://dorl.net/dor/20.1001.1.20087845.1402.12.45.5.7 

Esfandiari darabad, F., Hamzaei, M., Alaei, N., & Mostafazadeh, R. (2021). Spatial Variations of Landscape Metrics in Riparian Area Vegetation of Gharesou River Reaches under the Effect of Different Land Uses, Ardabil Province. Geographical Planning of Space, 10(38), 219-234. [In Persian] https://www.doi.org/10.30488/gps.2020.197834.3091

Ghafari, S., Moradi, H. R., & Modares, R. (2018). Comparison of object-oriented and pixel-based classification methods for land use mapping (Case study: Isfahan-Borkhar, Najafabad and Chadegan plains). Journal of RS and GIS for Natural Resources, 9(1), 40-57. [In Persian]  http://dorl.net/dor/20.1001.1.26767082.1397.9.1.3.3

Idham, R. M., Nurul, F. J., Mohammad, F., Keiko, U., So, K., & Shunichi, K. (2017). Future projection of flood inundation considering land-use changes and land subsidence in Jakarta, Indonesia. Hydrological Research Letters, 11(2), 99-105. https://doi.org/10.3178/hrl.11.99

Irani, T., Abghari, H., & Rasouli, A. (2024). Analysis of the Relationship between Landuse Changes and Landuse Metrics: the Case Study of Godarchai Watershed. Geographical Planning of Space, 14(1), 165-188. [In Persian]   https://www.doi.org/10.30488/GPS.2024.406033.3661

Kakehmami, A., Moamari, M., Qurbani, A., & Ghaffari, S. (2020). Analysis of land use/cover changes in Ardabil province using landscape metric. Journal of RS and GIS for Natural Resources, 11, 68-86. [In Persian] https://doi.org/10.30495/girs.2020.674952

Kiyani, V., & Feghhi, J. (2015). Investigating of cover/land use structure of Sefidroud watershed by landscape ecology metrics. Journal of Environmental Science and Technology, 17(2), 131-141. [In Persian] https://sanad.iau.ir/en/Journal/jest/Article/839655

Kumar, K. S., Bhaskar, P. U., & Padmakumari, K. (2015). Application of land change modeler for prediction of future land use land cover: a case study of Vijayawada City. International Journal of  Advanced Technology in Engineering and Science, 3(1), 773-783.

Lam, N. S. N., Cheng, W., Zou, L., & Cai, H. (2018). Effects of landscape fragmentation on land loss. Remote Sensing of Environment, 209, 253-262. http://dx.doi.org/10.1016/j.rse.2017.12.034

McGarigal, K. (2002). FRAGSTATS: Spatial Pattern Analysis Prog-ram for Categorical Maps. Computer software program produced by the authors at the University of Massachuse-tts, Amherst.

McGarigal, K., Cushman, S. A., & Ene, E. (2012). FRAGSTATS v4: spatial pattern analysis program for categorical and continuous maps. Computer software program produced by the authors at the University of Massachusetts, Amherst.

Moharrami, M., & Derafshi, A. (2015). Signifying of the urmia lake changes using objected-oriented image processing techniques. Journal of Applied Hydrology, 2(2), 13-23.

Nasiri, V., & Darvishsefat, A. A. (2018). Analysis of land use and land cover using ecological landscape metrics (case study: Arasbaran region). Environmental Sciences, 16(3), 101-118. [In Persian] https://envs.sbu.ac.ir/article_97954.html

Nazar Neghad, H., Hosseine, M., & Mostafazadeh, R. (2020). Assessment of Changes in Landuse Connectivity and Pattern using Landscape Metrics in the Zolachai Watershed, Salmas. Geographical Planning of Space, 9(34), 53-66. [In Persian] https://doi.org/10.30488/gps.2020.95381.2570

Su, L., Naqui, J., Mata-Contreras, J., & Martín, F. (2014). Modeling metamaterial transmission lines loaded with pairs of coupled split-ring resonators. IEEE Antennas and Wireless Propagation Letters, 14, 68-71. https://doi.org/10.1109/LAWP.2014.2355035

Tzotsos, A., & Argialas, D. (2008). Support vector machine classification for object-based image analysis. Object-based image analysis: Spatial concepts for knowledge-driven Remote Sensing Applications, 663-677. https://doi.org/10.1007/978-3-540-77058-9_36

Uuemaa, E., Antrop, M., Roosaare, J., Marja, R., & Mander, Ü. (2009). Landscape metrics and indices: an overview of their use in landscape research. Living Reviews in Landscape Research, 3(1), 1-28. http://hdl.handle.net/1854/LU-695518