ArticleScientific reports2025
A PCA-based standardized spectral index from Sentinel-2 for modeling soil macronutrients in the Miandoab region, Iran.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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2 citing papers in PubMed.
- Optimizing environmental covariates for digital mapping of soil organic carbon in Hunan Province, China.Scientific reports · 2026Article
- Wildfire-Induced alterations in soil physical, chemical, and micromorphological properties in forest ecosystems of Yunnan, Southwestern China.Scientific reports · 2025Article
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5 authors.
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Abstract
Spatial monitoring of soil macronutrients-especially total nitrogen (TN), available phosphorus (AP), and available potassium (AK)-using remote sensing technologies is a promising approach to promote precision agriculture. The aim of this study is to evaluate the effectiveness of Sentinel-2 satellite data and selected spectral indices in modeling the concentrations of these important soil macronutrients on agricultural land. A total of 181 soil samples were collected from a depth of 0-30 cm and analyzed in the laboratory using standard methods to determine nitrogen, phosphorus, and potassium content. Twelve common spectral indices and a newly proposed index-the standardized spectral reflectance index (SSRI), derived from the first principal component of a PCA-were extracted from the Sentinel-2 data. Linear regression modeling revealed that TN provided the most accurate predictions (R
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