Comprehensive Soil Quality Index Computation and Visualization in R
SQIpro provides a complete, modular framework for computing the
Soil Quality Index (SQI) — a single numeric score (0–1) integrating
physical, chemical, and biological soil properties.
| Method | Reference | Key feature |
|---|---|---|
| Linear Scoring | Doran & Parkin (1994) | Simple, equal-weight additive |
| Regression-based | Masto et al. (2008) | Weights by regression coefficients |
| PCA-based | Andrews et al. (2004) | Data-driven, variance-explained weights |
| Fuzzy Logic | Zhu et al. (2010) | Handles uncertainty; geometric mean option |
| Entropy Weighting | Shannon (1948) | Objective weights from information content |
| TOPSIS | Hwang & Yoon (1981) | Multi-criteria ideal-solution distance |
"more" — Higher is better ▁▃▅▇█ (e.g., organic carbon)
"less" — Lower is better █▇▅▃▁ (e.g., bulk density)
"opt" — Optimum range ▁▅█▅▁ (e.g., pH 6.0–7.0)
"trap" — Trapezoidal ▁▅███▅▁ (explicit boundaries)
# Install from CRAN
install.packages("SQIpro")library(SQIpro)
# 1. Load data
data(soil_data)
# 2. Define variable configuration
cfg <- make_config(
variable = c("pH", "EC", "BD", "OC", "MBC", "Clay"),
type = c("opt", "less", "less", "more", "more", "opt"),
opt_low = c(6.0, NA, NA, NA, NA, 20),
opt_high = c(7.0, NA, NA, NA, NA, 35)
)
# 3. Score variables (0–1 transformation)
scored <- score_all(soil_data, cfg, group_cols = c("LandUse", "Depth"))
# 4. Select Minimum Data Set
mds <- select_mds(scored, group_cols = c("LandUse", "Depth"))
# 5. Compute and compare all methods
results <- sqi_compare(scored, cfg,
group_cols = c("LandUse", "Depth"),
dep_var = "OC", mds = mds)
print(results)validate_data() → make_config() → plot_scoring_curves()
↓
score_all() → select_mds()
↓
sqi_linear() sqi_pca() sqi_regression()
sqi_fuzzy() sqi_entropy() sqi_topsis()
↓
sqi_compare() → sqi_anova() → sqi_sensitivity()
↓
plot_sqi() plot_scores() plot_radar() plot_sensitivity()
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Doran, J.W., & Parkin, T.B. (1994). Defining and assessing soil quality. In: Doran, J.W., Coleman, D.C., Bezdicek, D.F., & Stewart, B.A. (Eds.), Defining Soil Quality for a Sustainable Environment (pp. 3–21). SSSA Special Publication No. 35. doi:10.2136/sssaspecpub35.c1
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Andrews, S.S., Karlen, D.L., & Cambardella, C.A. (2004). The soil management assessment framework: A quantitative soil quality evaluation method. Soil Science Society of America Journal, 68(6), 1945–1962. doi:10.2136/sssaj2004.1945
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Bastida, F., Zsolnay, A., Hernández, T., & García, C. (2008). Past, present and future of soil quality indices: A biological perspective. Geoderma, 147(3), 159–171. doi:10.1016/j.geoderma.2008.08.007
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Masto, R.E., Chhonkar, P.K., Purakayastha, T.J., Patra, A.K., & Singh, D. (2008). Soil quality indices for evaluation of long-term land use and soil management practices in semi-arid sub-tropical India. Land Degradation & Development, 19(5), 516–529. doi:10.1002/ldr.528
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Hwang, C.L., & Yoon, K. (1981). Multiple Attribute Decision Making: Methods and Applications. Springer-Verlag. doi:10.1007/978-3-642-48318-9
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Shannon, C.E. (1948). A mathematical theory of communication. Bell System Technical Journal, 27(3), 379–423. doi:10.1002/j.1538-7305.1948.tb01338.x
citation("SQIpro")GPL-3 © Sadikul Islam