Lightweight Transformer Model for Agricultural Land Use and Land Cover Classification

Kemal Çelik

doi:10.15832/ankutbd.1624812

Lightweight Transformer Model for Agricultural Land Use and Land Cover Classification

Abstract

Observing agricultural land use via remote sensing images is essential for ensuring food security, estimating yields and planning efficient exports nonetheless precise classification continues to be difficult because of the varied and evolving characteristics of agricultural environments. This research aims to evaluate and optimize advanced deep learning architectures particularly Vision Transformer (ViT) models for agricultural land-use classification tasks. Specifically, we employed ViTBase-16 and other lightweight models DeiT-Tiny and EfficientNet-B0 applying techniques such as model layer compression and advanced data augmentation CutMix and Cutout to achieve high accuracy while significantly reducing computational complexity. Evaluation was performed using three benchmark remote sensing datasets EuroSAT, NWPU-RESISC45 and SIRI-WHU which include diverse spatial resolutions and agricultural classes relevant for practical monitoring. Findings indicate that the optimized ViT algorithm is highly effective in recognizing global spatial connections, consistently achieving remarkable classification accuracy exceeding 99% on a newly assembled dataset containing around 200 samples of Google Earth imagery. Furthermore, the first time in agricultural image classification compressing the ViTBase model by pruning 50% of its layers significantly reduced complexity maintainingcompetitive accuracy 97.9% on SIRI-WHU. The resulting models are particularly suitable for deployment on devices with limited computational resources supporting real-world operational agricultural monitoring systems. This study emphasizes the revolutionary possibilities and practical use of optimized transformer-based models that offer scalable and efficient solutions specifically designed for precision agriculture applications.

Keywords

References

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Details

Primary Language

English

Subjects

Agricultural Land Management

Journal Section

Research Article

Authors

Kemal Çelik ^*
0000-0003-0662-5901
Türkiye

Publication Date

September 30, 2025

Submission Date

January 22, 2025

Acceptance Date

May 12, 2025

Published in Issue

Year 2025 Volume: 31 Number: 4

DOI

https://doi.org/10.15832/ankutbd.1624812

IZ

https://izlik.org/JA58UC94TR

Cite

RIS / Bibtex

APA

Çelik, K. (2025). Lightweight Transformer Model for Agricultural Land Use and Land Cover Classification. Journal of Agricultural Sciences, 31(4), 941-959. https://doi.org/10.15832/ankutbd.1624812

AMA

1.Çelik K. Lightweight Transformer Model for Agricultural Land Use and Land Cover Classification. J Agr Sci-Tarim Bili. 2025;31(4):941-959. doi:10.15832/ankutbd.1624812

Chicago

Çelik, Kemal. 2025. “Lightweight Transformer Model for Agricultural Land Use and Land Cover Classification”. Journal of Agricultural Sciences 31 (4): 941-59. https://doi.org/10.15832/ankutbd.1624812.

EndNote

Çelik K (September 1, 2025) Lightweight Transformer Model for Agricultural Land Use and Land Cover Classification. Journal of Agricultural Sciences 31 4 941–959.

IEEE

[1]K. Çelik, “Lightweight Transformer Model for Agricultural Land Use and Land Cover Classification”, J Agr Sci-Tarim Bili, vol. 31, no. 4, pp. 941–959, Sept. 2025, doi: 10.15832/ankutbd.1624812.

ISNAD

Çelik, Kemal. “Lightweight Transformer Model for Agricultural Land Use and Land Cover Classification”. Journal of Agricultural Sciences 31/4 (September 1, 2025): 941-959. https://doi.org/10.15832/ankutbd.1624812.

JAMA

1.Çelik K. Lightweight Transformer Model for Agricultural Land Use and Land Cover Classification. J Agr Sci-Tarim Bili. 2025;31:941–959.

MLA

Çelik, Kemal. “Lightweight Transformer Model for Agricultural Land Use and Land Cover Classification”. Journal of Agricultural Sciences, vol. 31, no. 4, Sept. 2025, pp. 941-59, doi:10.15832/ankutbd.1624812.

Vancouver

1.Kemal Çelik. Lightweight Transformer Model for Agricultural Land Use and Land Cover Classification. J Agr Sci-Tarim Bili. 2025 Sep. 1;31(4):941-59. doi:10.15832/ankutbd.1624812