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生态学杂志 ›› 2025, Vol. 44 ›› Issue (8): 2800-2807.doi: 10.13292/j.1000-4890.202508.027

• 技术与方法 • 上一篇    下一篇

基于高分六号影像的农田防护林宽度自动识别

朱素华1,2,3,郑晓1,2*,樊俊美1,2,3,赵斓林1,2,3
  

  1. 1森林生态与保育重点实验室(中国科学院), 中国科学院沈阳应用生态研究所, 沈阳 110016; 2辽宁清原森林生态系统国家野外科学观测研究站, 沈阳 110016; 3中国科学院大学, 北京 100049)

  • 出版日期:2025-08-10 发布日期:2025-08-15

Automatic identification of the width of farmland shelterbelt based on GF-6 image.

ZHU Suhua1,2,3, ZHENG Xiao1,2*, FAN Junmei1,2,3, ZHAO Lanlin1,2,3   

  1. (1CAS Key Laboratory of Forest Ecology and Silviculture, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110016, China; 2Qingyuan Forest, National Observationand Research Station, Liaoning Province, Shenyang 110016, China; 3University of Chinese Academy of Sciences, Beijing 100049, China).

  • Online:2025-08-10 Published:2025-08-15

摘要: 农田防护林(农防林)作为农田生态系统的直接生态屏障,林带宽度直接影响农防林防护功能的发挥和后续经营。随着农防林建设不断深入,区域尺度快速准确识别林带宽度具有重要意义。本研究以黑龙江省黑土地核心区——拜泉县的富强镇、大众乡、兴农镇为研究区,选取高分六号(GF-6)影像,创建面向对象-缓冲区分割技术获取农防林斑块信息,并实现单条林带自动提取及其宽度计算。结果表明:(1)农防林对GF-6影像中的蓝波段、近红外波段和归一化植被指数比较敏感,利用以上特征能够将农防林和非农防林区分开;(2)基于面向对象-缓冲区分割技术,实现林带自动分割及其宽度计算,经地面调查验证,准确度较高(R2为0.73);(3)农防林宽度布局在拜泉县的富强镇、大众乡和兴农镇基本一致,主要集中于17~24 m,且这一宽度范围的农防林分别占各乡镇农防林总面积的32.64%、33.24%、30.29%。本研究创建的面向对象缓冲区分割技术为后续农防林构建与经营提供了方法支撑。


关键词: 遥感, 面向对象, 决策树, 缓冲区分割, 等效矩形

Abstract: Farmland shelterbelts are the direct ecological barrier of agroecosystems. The width of shelterbelts directly affects the fulfillment of the protective function and subsequent management. In the continued construction of farmland shelterbelts, it is critically needed to identify the width at the regional scale quickly and accurately. In this study, Fuqiang Town, Dazhong Town and Xingnong Town of Baiquan County, the core area of black land in Heilongjiang Province, were selected as the research area. The Gaofen6 Satellite Imagery (GF-6) data were selected to extract the patch information of farmland shelterbelt by object-oriented and buffer segmentation technology, and each shelterbelt was extracted and its width was calculated. The results showed that: (1) Farmland shelterbelt was sensitive in the blue band, near-infrared band, and normalized difference vegetation index, which can be used to separate farmland shelterbelt and non-farmland shelterbelt. (2) The automatic recognition results of the width of the farmland shelterbelts based on object-oriented and buffer segmentation technology showed a strong correlation with the measured width, with an R2 value of 0.73. (3) The width of farmland shelterbelts in Fuqiang Town, Dazhong Town, and Xingnong Town was basically the same, mainly concentrated on 17-24 m, accounting for 32.64%, 33.24% and 30.29% of the total area of farmland shelterbelts in each township, respectively. The object-oriented and buffer segmentation technology created here will provide method support for the subsequent construction and management of farmland shelterbelts.


Key words: remote sensing, object-oriented, decision tree, buffer segmentation, equivalent rectangle