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林业资源管理 ›› 2021, Vol. 0 ›› Issue (3): 154-159.doi: 10.13466/j.cnki.lyzygl.2021.03.024

• 技术应用 • 上一篇    下一篇

中分卫星遥感技术在森林资源动态监测中的应用

兰玉芳1(), 石小华1, 马胜利1, 王照利1, 靳新2   

  1. 1.国家林业和草原局西北调查规划设计院,西安 710048
    2.西安绿环林业技术服务公司,西安 710048
  • 收稿日期:2021-05-20 修回日期:2021-05-24 出版日期:2021-06-28 发布日期:2021-08-04
  • 作者简介:兰玉芳(1987-),女,陕西神木人,工程师,主要从事“3S”技术在林业调查规划设计和森林资源监测应用方面的工作。Email: 715489923@qq.com
  • 基金资助:
    青海省森林生态效益补偿基金项目(2020)

Application of Middle-Resolution Satellite Remote Sensing Technology in Dynamic Monitoring of Forest Resources

LAN Yufang1(), SHI Xiaohua1, MA Shengli1, WANG Zhaoli1, JIN Xin2   

  1. 1. Northwest Surveying,Planning and Designing Institute of National Forestry and Grassland Administration,Xi'an,Shaanxi 710048,China
    2. Xi'an Lvhuan Forestry Technical Service Company,Xi'an 710048,China
  • Received:2021-05-20 Revised:2021-05-24 Online:2021-06-28 Published:2021-08-04

摘要:

以青海省8个县为试点区,利用Sentinel-2A和Landsat-8中分辨率遥感数据,结合2018—2020年试点单位的森林督查成果及森林资源管理“一张图”年度更新数据,协同运用LSMA光谱混合分析模型、Li-Strahler几何光学模型,对试点县2020年森林资源变化情况进行动态监测和实证研究。结果显示:在15个月的时间跨度中,共监测疑似林地变化图斑693个,总面积1 286.382 7 hm2,主要发生在公益林地范围内,占疑似变化图斑总面积97.48%,总体准确率达到87.30%,满足森林资源动态监管要求;10m分辨率的中分卫星影像能检测到的最小图斑面积达到0.1 hm2,但主要集中在郁闭度较大的林区;在计算机自动检测的基础上,加入人工识别,能进一步提高变化检测的准确率。

关键词: 中分辨率遥感数据, 森林资源动态监测, 变化检测模型, 精度控制

Abstract:

Based on Sentinel-2A and Landsat-8 middle-resolution remote sensing data,combined with the three-phase forest inspection results and the annual update data of the "one map" of forest resources man-agement from 2018 to 2020,LSMA spectral hybrid analysis model and Li-Strahler geometric optics model were used to study the dynamic monitoring and empirical research on the changes of forest resources in 8 pilot counties of Qinghai Province.The results showed that,in the 15-month time span,a total of 693 change patterns with total area of 1286.3827 hm2 of forest land were monitored,which mainly occurred within the public welfare woodland and accounted for 97.48% of the total area.And the overall accuracy rate reached 87.30%,which met the requirements for dynamic monitoring of forest resources;Also,the smallest patch area that could be detected by the 10-m resolution satellite image was 0.1 hm2,but it was mainly concentrated in forest areas with greater canopy closure;Furthermore,on the basis of computer automatic detection,adding manual recognition could further improve the accuracy of change detection.

Key words: middle-resolution remote sensing data, dynamic monitoring of forest resources, change detection model, precision control

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