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Indexing and segment-level mapping of soil quality in a spatially complex watershed in northern Iran

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Abstract

Soil quality (SQ) modeling and mapping is a leading research field aiming to provide reproducible and cost-effective yet accurate SQ predictions at the landscape level. This endeavor was conducted in a complex watershed in northern Iran. We classified the region into spectrally and topographically homogenous land units (average area of 48 ± 23 ha) using object-based segmentation analysis. Following the physicochemical analysis of soil samples from 98 stations, the Nemoro soil quality index (SQIn) was produced using the minimum dataset procedure and a non-linear sigmoid scoring function. SQIn values averaged 0.21 ± 0.06 and differed statistically between major land uses. To predict and map SQIn for each land unit, the best-performing regression model (F(3, 84) = 45.57, p = 0.00, R2 = 0.62) was built based on the positive contribution of the mean Landsat 8-OLI band 5, and negative influence of land surface temperature retrieved from Landsat 8-OLI band 10 and surface slope (t-test p-values < 0.01). Results showed that dense-canopy woodlands located in low-slope land units exhibit higher SQIn while regions characterized by either low-vegetation or steep-sloped land units had SQ deficits. This study provides insights into SQ prediction and mapping across spatially complex large-scale landscapes.

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Authors and Affiliations

  1. Department of Soil Science, College of Agriculture, Isfahan (Khorasgan) Branch, Islamic Azad University, Isfahan, Iran

    Fatemeh Aghalari & Elham Chavoshi

  2. Soil Conservation and Watershed Management Research Department, Isfahan Agricultural and Natural Resources Research and Education Center, AREEO, Isfahan, 19395-1113, Iran

    Sattar Chavoshi Borujeni

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  1. Fatemeh Aghalari
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  2. Elham Chavoshi
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Contributions

Fatemeh Aghalari: Conceptualization, Contributor to data interpretation, Contributor to manuscript preparation.

Elham Chavoshi: Methodology, Data interpretation, Writing-Original draft preparation.

Sattar Chavoshi Borujeni: Contributor in data interpretation, Data Validation.

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Correspondence to Elham Chavoshi.

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Aghalari, F., Chavoshi, E. & Borujeni, S.C. Indexing and segment-level mapping of soil quality in a spatially complex watershed in northern Iran. Environ Monit Assess 196, 51 (2024). https://doi.org/10.1007/s10661-023-12212-7

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