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

Buyanbaatar Avirmed; Erdenetuya Boldbaatar; Dambadarjaa Naranbat; Sainbayar Surenkhuu; Ariunsuren Purevee; Oyuntuya Sharavjamts

doi:10.17306/j.jard.2026.2.00013r1

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

Journal of Agribusiness and Rural Development

Volume 80 (2026): Issue 2 (June 2026)

By: Buyanbaatar Avirmed , Erdenetuya Boldbaatar , Dambadarjaa Naranbat , Sainbayar Surenkhuu , Ariunsuren Purevee and Oyuntuya Sharavjamts

Open Access

|Jun 2026

Figures & Tables

Flowchart of research Source: own elaboration.

Research study area of Bornuur sub-province, Tuv province Source: own elaboration.

Field work points location Source: own elaboration.

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

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

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

Linear regression plots of forage yield versus vegetation indices (NDVI, EVI, SAVI, NDWI) Source: own elaboration.

Linear regression analysis: Yield and land surface factors Source: own elaboration.

Descriptive statistical results of vegetation indices

Indices	Mean	Std	Var	Median	Skewness	Kurtosis	Q25	Q75
NDVI	0.702038	0.083245	0.006930	0.723672	–0.071365	2.045454	0.642460	0.756097
NDWI	–0.538684	0.026957	0.000727	–0.549065	1.081511	3.079622	–0.554977	–0.531618
SAVI	0.940731	0.120926	0.014623	0.986801	–1.529100	4.264492	0.929660	1.006785
EVI	0.505570	0.088888	0.007901	0.491353	–0.698589	4.182447	0.460148	0.579817

Variable importance estimates from multivariate analysis

Variable	Estimate	Std. error	p-value	95% CI
NDVI	18.827	6.659	0.022^*	(3.470, 34.184)
EVI	7.855	8.227	0.368	(–11.115, 26.826)
NDWI	7.797	16.349	0.646	(–29.905, 45.499)
Slope	–0.289	0.242	0.266	(–0.846, 0.268)

SHAP variable importance

Variable	Mean (SHAP)	Direction
NDVI	1.567	Positive
EVI	0.698	Positive
Slope	0.680	Negative
NDWI	0.210	Positive
Elevation	0.186	Positive
Total. protein	0.173	Positive

Summary of hayfield yield and forage quality (Bornuur)

Variable	Min	Max	Mean (approx.)
Area (ha)	10.3	6 000	–
Yield (g/m²)	54.1	132.9	93
Moisture (%)	4.92	7.69	5.9
Dry matter (%)	92.31	95.08	94.1
Crude protein (%)	9.12	16.56	11.9
Fibre (%)	22.8	36.96	30.1
Digestibility (%)	55.66	68.59	61.7
Energy (MJ)	8.02	9.87	8.8

Descriptive statistical results of Land surface factors

Land surface factor	Mean	Std	Var	Median	Skewness	Kurtosis	Q25	Q75
Elevation	1 114.7	84.1	7 060.9	1133.0	–0.6	3.3	1 050.8	1 159.5
Aspect	166.6	118.6	14 076.4	160.2	0.1	1.8	58.3	250.1
Slope	7.1	2.4	5.5	6.9	–0.2	2.9	5.7	8.7

Model comparison results

Model	RMSE	MAE	R²
FULL	0.853	0.653	0.879
LASSO	0.889	0.677	0.869

References

Authors

Metrics

Articles in this issue

DOI: https://doi.org/10.17306/j.jard.2026.2.00013r1 | Journal eISSN: 1899-5772 | Journal ISSN: 1899-5241

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Language: English

Page range: 195 - 204

Accepted on: May 27, 2026

Published on: Jun 30, 2026

Published by: The University of Life Sciences in Poznań

In partnership with: Paradigm Publishing Services

Publication frequency: 4 issues per year

Keywords:

vegetation indices,

forage yield estimation,

remote sensing,

range land monitoring,

water scarcity,

terrain features

Related subjects:

Business and economics,

Political economics,

Political economics, other,

Business management,

Business management, other,

Life sciences,

Life sciences, other,

Social sciences,

Political science,

Political science, other

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

Volume 80 (2026): Issue 2 (June 2026)

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

Figures & Tables

Fig. 1.

Fig. 2.

Fig. 3.

Fig. 4.

Fig. 5.

Fig. 6.

Fig. 7.

Fig. 8.

Descriptive statistical results of vegetation indices

Variable importance estimates from multivariate analysis

SHAP variable importance

Summary of hayfield yield and forage quality (Bornuur)

Descriptive statistical results of Land surface factors

Model comparison results

Paradigm

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