Land suitability classification is a useful management practice to ensure planned and sustainable use of agricultural lands according to their potentials. The main purposes of this study were to analyze land suitability for bread wheat (Triticum aestivum) cultivation and generate a land suitability map for wheat by integrating the analytical hierarchy (AHP)-fuzzy algorithm with the Geographical Information System (GIS) in the Tozanlı sub-basin located in the upper part of Yeşilırmak Basin, Turkey. Topographic (elevation, slope, aspect) characteristics of the basin and some of physical and chemical properties of soils (texture, pH, electrical conductivity, lime, organic matter, and soil depth) were used as criteria in determining the suitability classes. Ninety-two disturbed soil samples were collected from 0 to 20 cm depth in October 2017 using random sampling method. Weighted overlay spatial analysis in GIS was used to combine different thematic layers to identify areas suitable for wheat production. The fuzzy-AHP suitability assessment model was adapted to determine the weights for topographic and soil properties. The highest specific weights were obtained for soil depth (0.232) and elevation (0.218), while the lowest weight was calculated for aspect (0.042). Highly, moderately, and marginally suitable lands for wheat cultivation cover 2.63, 9.85 and 32.59% of the study area, respectively. In addition, the results indicated that 54.92% of the total area is permanently unsuitable for wheat cultivation. The results revealed that integration of AHP-fuzzy algorithm and GIS techniques is a useful method for accurate evaluation of land suitability in planning for specific crop production and decreasing the negative environmental impacts of agricultural practices.

Rational planning of soil resources based on their capabilities are needed for the sustainable use of agricultural lands. Land suitability classification is an important evaluation tool for the management of soil resources. This study aimed to evaluate the land suitability for wheat (Triticum aestivum) cultivation using an approach that integrates multi-criteria decision making (MCDA) analysis and geographic information systems (GIS). The study area cover 21146 ha land and is located within the land consolidation area in the Çumra Plain, located in Central Anatolia of Turkey, The physical, chemical and fertility properties of the soil samples collected from 342 points in the study area were used as parameters in the wheat suitability assessment. The relative weight values of the soil parameters were determined by the Analytical Hierarchy Process (AHP). Literature and expert opinion were used in the creation of the AHP matrices and the determination of the sub-criteria. The criteria with the highest weight values or which have the highest impact on wheat growth were soil texture (0.30) and pH (0.16), while the lowest weight values were given for micro elements (0.02). Land Suitability Assessment was applied to the maps of soil variables using weighted overlay analysis in the GIS environment by using the relative weights. Thus, the suitability of the study area for wheat cultivation was mapped. The results revealed that 74% of the study area was highly suitable (S1) and 24% was moderately suitable (S2) for wheat cultivation. The coefficient of determination (R2) was 0.81, which indicated a successful prediction of the GIS-MCDA hybrid approach for wheat suitability assessment. Integration of land suitability analyzes specific to plant variety in land consolidation projects can provide a more detailed perspective on the land in the design of planning studies.

Soil salinity is a major land degradation process reducing biological productivity in arid and semi-arid regions. Therefore, its effective monitoring and management is inevitable. Recent developments in remote sensing technology have made it possible to accurately identify and effectively monitor soil salinity. Hence, this study determined salinity levels of surface soils in 2650 ha agricultural and natural pastureland located in an arid region of central Anatolia, Turkey. The relationship between electrical conductivity (EC) values of 145 soil samples and the dataset created using Landsat 5 TM satellite image was investigated. Remote sensing dataset for 23 variables, including visible, near infrared (NIR) and short-wave infrared (SWIR) spectral ranges, salinity, and vegetation indices were created. The highest correlation between EC values and remote sensing dataset was obtained in SWIR1 band (r = -0.43). Linear regression analysis was used to reveal the relationship between six bands and indices selected from the variables with the highest correlations. Coefficient of determination (R²= 0.19) results indicated that models obtained using satellite image did not provide reliable results in determining soil salinity. Microtopography is the major factor affecting spatial distribution of soil salinity and caused heterogeneous distribution of salts on surface soils. Differences in salt content of soils caused heterogeneous distribution of halophytes and led to spectral complexity. The dark colored slickpots in small-scale depressions are common features of sodic soils, which are responsible for spectral complexity. In addition, low spatial resolution of Landsat 5 TM images is another reason decreasing the reliability of models in determining soil salinity.

Orhan Mete KILIC - EFFECTS OF LAND USE AND LAND COVER CHANGES ON SOIL EROSION IN SEMI-ARID REGIONS OF TURKEY; A CASE STUDY IN ALMUS LAKE WATERSHED, Carpathian Journal of Earth and Environmental Sciences, February 2021, Vol. 16, No. 1, p. 129 – 138; Doi:10.26471/cjees/2021/016/161