Page 117 - Çevre Şehir ve İklim Dergisi İngilizce - Özel Sayı

Zehra Kavakli Karataş

2.3. Desertification in Türkiye

2.3.1. The Studies Conducted on Desertification in Türkiye
According to Cangir and Boyraz (2008), the causes of desertification
in Türkiye are as follows: natural causes, technical and socioeconomic,
administrative and statutory causes. Natural causes include soil erosion,
changes in soil quality and fertility, and climatic changes. Technical causes are
deforestation, misuse of land, mismanagement of agricultural lands and etc.
Consequently, the examples of socioeconomic, administrative and statutory
causes include migration, inability to catch up with the age in terms of science
and technology, and powers in land management (Cangir and Boyraz, 2008).
DIS4ME, MEDALUS, AHP and Fuzzy-AHP methods are used in the
studies on desertification in Türkiye. The Desertification Indicator System for
Mediterranean Europe (DIS4ME) has identified 148 indicators for desertification
in the Mediterranean Regions, and it is a method to better understand where
there is a problem with desertification, how critical the problem is and how to
better comprehend this process (DIS4ME, 2024). MEDALUS Analytic Hierarchy
Process (AHP) is a method that was developed in 1977, allowing the assessment
of qualitative and quantitative variables together depending on expert opinion
in multi-criteria decision making (Dengiz et al., 2023; Dağdeviren et al., 2004).
However, this method does not deal with uncertainty and decision-making
situations (Dengiz et al., 2023). Based on this method, another method called
fuzzy analytic hierarchy process was developed, where triangular fuzzy numbers
were used to compare fuzzy ratios (Van Laarhoven and Pedrycz, 1983).
Furthermore, in line with the developing science and technology,
Geographic Information Systems (GIS) such as artificial neural networks
and machine learning have started to be used in the field of desertification
and land degradation. Using MEDALUS methodology, Everest et al. (2019)
assessed the Soil Quality Index of Karacabey State Farm. They calculated
the Soil Quality Index based on parent material, texture, depth, drainage
and education parameters. At the end of the study, the land status of the
State Farm and its quality classes in terms of desertification were presented.
According to the results of this study, 8.28% of the lands of the State Farm
were classified as high quality, 49.17% as moderate quality and 42.55% as
low quality (Everest et al., 2019). Dengiz and Demirağ Turan (2023) presented
the correlation between soil quality and RE-OSAVI and NDVI produced from
Sentinel-2A satellite images for various time series in Çorum Basin. In the study
conducted by Özşahin et al. (2017), an analysis was performed with the help
of GIS according to the Soil Quality Index. In this analysis, soil samples taken
randomly from the study area were analyzed according to soil sub-indicators,

104 Journal of Environment, Urban and Climate