Proceedings of the 2026 7th International Conference on Management Science and Engineering Management (ICMSEM 2026)

2026 7th International Conference on Management Science and Engineering Management (ICMSEM 2026)

📍Shenyang, China🗓️ 22-24 May 2026

Monitoring and Ecologically Sustainable Management of Under-Forest Chinese Medicinal Planting Areas in Jilin Province Based on Multi-Source Remote Sensing

Authors
Na Qu1, *, Xueying Wang1, Haijiao Yu1, Jiaqi Guo1
1School of Medical Information, Changchun University of Chinese Medicine, Changchun, 130117, China
*Corresponding author.
Corresponding Author
Na Qu
Available Online 8 September 2026.
DOI
10.2991/978-94-6239-758-3_41How to use a DOI?
Keywords
agricultural remote sensing; under-forest Chinese medicinal materials; Changbai Mountain; NDVI; ecological suitability; sustainable management
Abstract

To accurately grasp the spatial pattern, growth status, and ecological carrying pressure of under-forest Chinese medicinal materials in the Changbai Mountain region, this study takes three core producing areas including Tonghua, Baishan, and Yanbian in Jilin Province as the research area. Multi-temporal satellite remote sensing data (Sentinel-2, Landsat-8), DEM terrain data, and field-measured samples were integrated. Vegetation indices such as NDVI, EVI, and MSAVI, support vector machine (SVM) remote sensing classification, ecological suitability evaluation, and spatial statistical methods were adopted to conduct large-scale dynamic monitoring of under-forest Chinese medicinal materials (mainly under-forest ginseng and Schisandra chinensis). The results showed that the total planting area of Chinese medicinal materials in the study area was 910 km2 (1.365 million mu), of which under-forest ginseng accounted for 75.46% (686.67 km2). The overall accuracy of SVM classification was 88.23%, with a Kappa coefficient of 0.852. Ecological suitability evaluation revealed that highly suitable planting areas accounted for 23.6% and unsuitable areas accounted for 11.0% of the total regional area, both of which were critical for ecological management and planting layout optimization. Highly suitable planting areas were mainly concentrated in regions with an altitude of 500–1000 m and a slope of 8°–25°. The average NDVI in the monitored area was 0.72±0.09, and the NDVI of GAP bases was significantly higher than that of ordinary planting areas by more than 0.11. Approximately 18.2% of the planting areas showed vegetation stress and declined ecological carrying capacity. The research indicates that remote sensing technology can effectively support the optimization of Chinese medicinal planting layout, ecological risk control, and smart agricultural supervision, providing a quantitative basis for the high-quality development of the Chinese medicinal industry and ecologically sustainable management in Jilin Province.

Copyright
© 2026 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 2026 7th International Conference on Management Science and Engineering Management (ICMSEM 2026)
Series
Advances in Economics, Business and Management Research
Publication Date
8 September 2026
ISBN
978-94-6239-758-3
ISSN
2352-5428
DOI
10.2991/978-94-6239-758-3_41How to use a DOI?
Copyright
© 2026 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

TY  - CONF
AU  - Na Qu
AU  - Xueying Wang
AU  - Haijiao Yu
AU  - Jiaqi Guo
PY  - 2026
DA  - 2026/09/08
TI  - Monitoring and Ecologically Sustainable Management of Under-Forest Chinese Medicinal Planting Areas in Jilin Province Based on Multi-Source Remote Sensing
BT  - Proceedings of the 2026 7th International Conference on Management Science and Engineering Management (ICMSEM 2026)
PB  - Atlantis Press
SP  - 428
EP  - 436
SN  - 2352-5428
UR  - https://doi.org/10.2991/978-94-6239-758-3_41
DO  - 10.2991/978-94-6239-758-3_41
ID  - Qu2026
ER  -