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Soil quality assessment for desertification based on multi-indicators with the best-worst method in a semi-arid ecosystem

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Abstract

Since there are some signs of land degradation and desertification showing how soil sustainability is threatened, it is crucial to create a soil quality index (SQI) model in the semi-arid Çorum Basin, situated between the Black Sea and Anatolia Region, Central Turkey. The primary aims of the study are: (1) to determine SQI values of the micro-basin in terms of land degradation and desertification. Moreover, the best-worst method (BWM) was used to determine the weighting score for each parameter; (2) to produce the soils’ spatial distribution by utilizing different geostatistical models and GIS (geographic information system) techniques; and (3) to validate the obtained SQI values with biomass reflectance values. Therefore, the relationship of RE-OSAVI (red-edge optimized soil-adjusted vegetation index) and NDVI (normalized difference vegetation index) generated from Sentinel-2A satellite images at different time series with soil quality was examined. Results showed that SQI values were high in the areas that had almost a flat and slight slope. Moreover, the areas with high clay content and thick soil depth did not have salinity problems, and were generally distributed in the middle parts of the basin. However, the areas with a high slope, poor vegetation, high sand content, and low water holding capacity had low SQI values. Furthermore, a statistically high positive correlation of RE-OSAVI and NDVI indices with soil quality was found, and NDVI had the highest correlative value for June (R2=0.802) compared with RE-OSAVI.

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Conceptualization: Orhan DENGİZ, İnci DEMİRAĞ TURAN; Methodology: Orhan DENGİZ, İnci DEMİRAĞ TURAN; Formal analysis: Orhan DENGİZ, İnci DEMİRAĞ TURAN; Writing - original draft preparation: Orhan DENGİZ, İnci DEMİRAĞ TURAN; Writing - review and editing: Orhan DENGİZ, İnci DEMİRAĞ TURAN.

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Correspondence to Orhan Dengiz.

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Dengiz, O., Demirağ Turan, İ. Soil quality assessment for desertification based on multi-indicators with the best-worst method in a semi-arid ecosystem. J. Arid Land 15, 779–796 (2023). https://doi.org/10.1007/s40333-023-0020-9

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