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植物生态学报 >

2024 , Vol. 48 >Issue 11: 1471 - 1485

DOI: https://doi.org/10.17521/cjpe.2023.0371

研究论文

基于高精度遥感影像和精细植被踏查的金华北山植被制图

  • 郑亚纹 ,
  • 樊海东 ,
  • 刘立斌 ,
  • 倪健
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  • 1浙江师范大学生命科学学院, 浙江金华 321004
    2浙江金华山亚热带森林生态系统野外科学观测研究站, 浙江金华 321004
*倪健(nijian@zjnu.edu.cn); ORCID: 0000-0001-5411-7050

收稿日期: 2023-12-11

  录用日期: 2024-09-28

  网络出版日期: 2024-09-29

基金资助

国家自然科学基金(31870462)

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Vegetation mapping of Beishan Mountain in Jinhua, Zhejiang, based on high-resolution remote sensing image and intensive vegetation survey

  • ZHENG Ya-Wen ,
  • FAN Hai-Dong ,
  • LIU Li-Bin ,
  • NI Jian
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  • 1College of Life Sciences, Zhejiang Normal University, Jinhua, Zhejiang 321004, China
    2Jinhua Mountain Observation and Research Station for Subtropical Forest Ecosystems, Jinhua, Zhejiang 321004, China

Received date: 2023-12-11

  Accepted date: 2024-09-28

  Online published: 2024-09-29

Supported by

National Natural Science Foundation of China(31870462)

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摘要

植被图展示一个地区的植被类型及其空间分布格局, 是研究植被和生物多样性等基础生态学, 以及植被恢复和管理等应用生态学的重要依据。以中亚热带常绿阔叶林区域的浙江省金华北山为研究对象, 基于高分二号(GF-2)高精度遥感图像, 结合大批量野外植被调查, 利用地理信息系统(ArcGIS)和遥感图像处理软件(ENVI)制作了金华北山1:6万高精度现状植被图。结果表明: 1)高精度遥感图像和大批量植被记录相结合, 较好刻画了金华北山南坡的植被格局, 共划分为7个植被型组、22个植被型、25个植被亚型、60个群系组和76个群系。2)在金华北山南坡65.5 km2区域内, 植被覆盖率约为93.0%, 且以森林(66.1%)、农业植被(14.7%)和灌丛(10.5%)为主。3)分布于海拔900 m以下、面积为10.6 km2的马尾松(Pinus massoniana)林, 分布于海拔108-946 m之间、面积为7.4 km2的马尾松-落叶阔叶混交林, 以及分布于海拔100-1 037 m之间、面积为5.3 km2的木荷(Schima superba)林, 是分布范围最大的3类群系。该研究是大比例尺局域植被制图的一个案例, 能够为不同比例尺区域和全国高精度植被制图、植被生态学研究和植被经营管理提供基础资料。

关键词： 常绿阔叶林; 植被图; 遥感; 植被分类; 区域植被分布

本文引用格式

郑亚纹 , 樊海东 , 刘立斌 , 倪健 . 基于高精度遥感影像和精细植被踏查的金华北山植被制图[J]. 植物生态学报, 2024 , 48(11) : 1471 -1485 . DOI: 10.17521/cjpe.2023.0371

Abstract

Aims Vegetation map illustrates the vegetation types and their spatial distribution patterns of a given area, which is an important foundation for investigating fundamental ecology such as vegetation feature and biodiversity study, as well as applied ecology such as vegetation restoration and management. The aim of this research is to chart a high-resolution local vegetation map of Beishan Mountain in Jinhua, Zhejiang Province, a middle subtropical evergreen broadleaf forest region in eastern China.

Methods A digital vegetation map with very high spatial resolution at the 1:60 000 scale in a 65.5 km² area in the middle part of the southern slope of Beishan Mountain in Jinhua was produced, based on high-resolution of 1-4 m satellite (GF-2) remote sensing images and intensive field vegetation surveys of 3 774 sites and 24 plots. The Geographical Information System (ArcGIS) and remote sensing image processing software (ENVI) were further utilized to conduct the mapping.

Important findings 1) High-resolution remote sensing images and a large quantity of vegetation records characterized the vegetation pattern on the southern slope of Beishan Mountain in Jinhua. The vegetation was divided into 7 Vegetation Formation Groups, 22 Vegetation Formations, 25 Vegetation Subformations, 60 Alliance Groups, and 76 Alliances. 2) In the 65.5 km2area on the southern slope of Beishan Mountain in Jinhua, the vegetation coverage of mapping area is about 93.0%. Among these vegetation areas, forest (66.1%), agricultural vegetation (14.7%) and shrubland (10.5%) are the main three vegetation types. 3) The three widely distributed alliances are Pinus massoniana forest in an area of 10.6 km2 and distributed below 900 m in altitude, Pinus massoniana - deciduous broadleaf mixed forest in an area of 7.4 km2 and distributed between 108 and 946 m, and Schima superba forest in an area of 5.3 km2 and distributed in 100-1 037 m. This is a case study of vegetation mapping at a big mapping scale. Such study can provide fundamental data for the high-resolution regional and national vegetation mappings at multiple scales, research of vegetation science, and vegetation service and management.

Key words： evergreen broadleaf forest; vegetation map; remote sensing; vegetation classification; regional vegetation distribution

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