ArticleEnvironmental monitoring and assessment2024
Evaluation of soil fertility using combination of Landsat 8 and Sentinel‑2 data in agricultural lands.
Article in Environmental monitoring and assessment, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Data fusion of EnMAP and sentinel-2 for high-resolution soil fertility assessment in wheat cultivation of central Khuzestan plain.Scientific reports · 2026Article
- Integrated assessment of iron status in peach leaves in the Pinggu region of China.Scientific reports · 2025Article
- A PCA-based standardized spectral index from Sentinel-2 for modeling soil macronutrients in the Miandoab region, Iran.Scientific reports · 2025Article
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Authors and funding
7 authors.
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Abstract
Today, remote sensing is widely used to estimate soil properties. Because it is an easy and accessible way to estimate soil properties that are difficult to estimate in the field. Based on this, to evaluate the soil fertility (SF), soil sampling was performed irregularly from the surface depth of 0-30 cm in 216 points, 11 soil properties were measured, and the soil fertility index (SFI) was calculated by soil properties. Simultaneously, we combined satellite images of Landsat 8 and Sentinel-2 using the Gram-Schmidt algorithm. Finally, multiple linear regression SFI was calculated using satellite data, as well as the spatial distribution of SFI was obtained in very low, low, moderate, high, and very high classes. Our findings showed that the combination of Landsat 8 and Sentinel-2 data using the Gram-Schmidt algorithm has a higher correlation with SFI than when these data are individually. Therefore, combined Landsat 8 and Sentinel 2 data were used for SFI modeling. Using model selection procedure indices (including Cp, AIC, and ρc criteria), the visible range bands, notably blue (r = 0.65), green (r = 0.63), and red (r = 0.61), provide the best model for estimating SFI (R
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