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Research progress on Smart Forestry and Grassland in China
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Changzhi Han1, 3, *, Yinling Huang1, 2, Qingjiang Cui4
Tree Health | 2026, 3(2) : 24 - 33
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Tree Health | 2026, 3(2): 24-33
Thematic review
Research progress on Smart Forestry and Grassland in China
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Changzhi Han1, 3, *, Yinling Huang1, 2, Qingjiang Cui4
Affiliations
  • College of Forestry,Southwest Forestry University,Kunming 650224,China
  • Graduate School of Southwest Forestry University,Kunming 650224,China
  • Yunnan Key Laboratory of Forest Disaster Warning and Control,Kunming 650224,China
  • Yunnan Forestry Technological College,Kunming 650224,China
Published: 2026-04-25 doi: 10.27035/j.cnki.issn2097-5279.20260203
Outline
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As a new ecological management model that integrates modern information technology, Smart Forestry and Grassland relies on intelligent sensors and information network systems to enable dynamic monitoring, precise management, scientific decision-making, and efficient utilization of forest and grassland resources. It has achieved significant results in enhancing resource utilization efficiency, strengthening biodiversity conservation, improving disaster prevention and recovery capabilities, and promoting the sustainable development of forestry and grassland sectors, and has gradually become an important technological pillar for China’s ecological civilization construction. However, systematic reports on the development of Smart Forestry and Grassland are currently scarce, which hinders further innovation and promotion of this model. Based on a systematic review of the development history of Smart Forestry and Grassland both domestically and internationally, combined with an analysis of its key technologies and scope of application, this paper points out that the development of Smart Forestry and Grassland in China still faces prominent issues such as insufficient automation, low levels of intelligence, and weak precision capabilities. To address these bottlenecks, this paper proposes future research priorities and development directions for China’s Smart Forestry and Grassland sector across three dimensions: automation, intelligence, and precision.

Smart Forestry and Grassland  /  informatization  /  automatization  /  productivity
Changzhi Han, Yinling Huang, Qingjiang Cui. Research progress on Smart Forestry and Grassland in China[J]. Tree Health, 2026 , 3 (2) : 24 -33 . DOI: 10.27035/j.cnki.issn2097-5279.20260203
Year 2026 volume 3 Issue 2
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doi: 10.27035/j.cnki.issn2097-5279.20260203
  • Receive Date:2024-10-22
  • Online Date:2026-07-30
  • Published:2026-04-25
Article Data
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History
  • Received:2024-10-22
  • Revised:2025-02-21
  • Accepted:2025-02-21
Affiliations
    College of Forestry,Southwest Forestry University,Kunming 650224,China
    Graduate School of Southwest Forestry University,Kunming 650224,China
    Yunnan Key Laboratory of Forest Disaster Warning and Control,Kunming 650224,China
    Yunnan Forestry Technological College,Kunming 650224,China
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表12种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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