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Remote Sensing-Based Assessment of Hayfield Productivity and Forage Quality in Mongolia’s Steppe Ecosystems Cover

Remote Sensing-Based Assessment of Hayfield Productivity and Forage Quality in Mongolia’s Steppe Ecosystems

Open Access
|Jun 2026

Figures & Tables

Fig. 1.

Flowchart of research

Source: own elaboration.

Fig. 2.

Research study area of Bornuur sub-province, Tuv province

Source: own elaboration.

Fig. 3.

Field work points location

Source: own elaboration.

Table 1.

Summary of hayfield yield and forage quality (Bornuur)

VariableMinMaxMean (approx.)
Area (ha)10.36 000
Yield (g/m2)54.1132.993
Moisture (%)4.927.695.9
Dry matter (%)92.3195.0894.1
Crude protein (%)9.1216.5611.9
Fibre (%)22.836.9630.1
Digestibility (%)55.6668.5961.7
Energy (MJ)8.029.878.8

[i] Source: own elaboration. Across all sampling sites, the mean forage yield was 9.34 c/ha (SD = 2.52), indicating moderate spatial variability. Nutritional quality exhibited a mean value of 8.80 (SD = 0.55) with low dispersion and near-normal distribution, suggesting relatively stable forage quality conditions across the study area.

Fig. 4.

Land surface factors map of Bornuur sub-province. a – elevation, b – slope, c – aspect

Source: own elaboration.

Table 2.

Descriptive statistical results of Land surface factors

Land surface factorMeanStdVarMedianSkewnessKurtosisQ25Q75
Elevation1 114.784.17 060.91133.0–0.63.31 050.81 159.5
Aspect166.6118.614 076.4160.20.11.858.3250.1
Slope7.12.45.56.9–0.22.95.78.7

[i] Source: own elaboration.

Table 3.

Descriptive statistical results of vegetation indices

IndicesMeanStdVarMedianSkewnessKurtosisQ25Q75
NDVI0.7020380.0832450.0069300.723672–0.0713652.0454540.6424600.756097
NDWI–0.5386840.0269570.000727–0.5490651.0815113.079622–0.554977–0.531618
SAVI0.9407310.1209260.0146230.986801–1.5291004.2644920.9296601.006785
EVI0.5055700.0888880.0079010.491353–0.6985894.1824470.4601480.579817

[i] Source: own elaboration.

Fig. 5.

Vegetation indices map of Bornuur sub-province. a – EVI, b – NDWI, c – NDVI, d – SAVI

Source: own elaboration.

Fig. 6.

Correlation matrix of variables *p < 0.05, **p < 0.01, ***p < 0.001. Values without asterisks are not statistically significant

Source: own elaboration.

Fig. 7.

Linear regression plots of forage yield versus vegetation indices (NDVI, EVI, SAVI, NDWI)

Source: own elaboration.

Fig. 8.

Linear regression analysis: Yield and land surface factors

Source: own elaboration.

Table 4.

Model comparison results

ModelRMSEMAER2
FULL0.8530.6530.879
LASSO0.8890.6770.869

[i] Source: own elaboration.

Table 5.

Variable importance estimates from multivariate analysis

VariableEstimateStd. errorp-value95% CI
NDVI18.8276.6590.022*(3.470, 34.184)
EVI7.8558.2270.368(–11.115, 26.826)
NDWI7.79716.3490.646(–29.905, 45.499)
Slope–0.2890.2420.266(–0.846, 0.268)

* p < 0.05, CI – Confidence Interval.

Source: own elaboration.

Table 6.

SHAP variable importance

VariableMean (SHAP)Direction
NDVI1.567Positive
EVI0.698Positive
Slope0.680Negative
NDWI0.210Positive
Elevation0.186Positive
Total. protein0.173Positive

[i] Source: own elaboration.

DOI: https://doi.org/10.17306/j.jard.2026.2.00013r1 | Journal eISSN: 1899-5772 | Journal ISSN: 1899-5241
Language: English
Page range: 195 - 204
Accepted on: May 27, 2026
Published on: Jun 30, 2026
Published by: Poznań University of Life Science
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year

© 2026 Buyanbaatar Avirmed, Erdenetuya Boldbaatar, Dambadarjaa Naranbat, Sainbayar Surenkhuu, Ariunsuren Purevee, Oyuntuya Sharavjamts, published by Poznań University of Life Science
This work is licensed under the Creative Commons Attribution 4.0 License.