测绘通报 ›› 2022, Vol. 0 ›› Issue (3): 23-27.doi: 10.13474/j.cnki.11-2246.2022.0071

• 生态环境动态监测 • 上一篇    下一篇

基于卫星遥感的城市绿地景观格局变化研究进展

叶俊, 康思奇, 傅根深, 吕海燕, 钱文祺, 唐雪海   

  1. 安徽农业大学林学与园林学院, 安徽 合肥 230061
  • 收稿日期:2021-04-14 出版日期:2022-03-25 发布日期:2022-04-01
  • 通讯作者: 唐雪海。E-mail:tangxuehai@ahau.edu.cn
  • 作者简介:叶俊(1997-),女,硕士,主要研究方向为城市林业3S技术应用。E-mail:junye9085@163.com
  • 基金资助:
    安徽省自然科学基金(1808085QC74);国家自然科学基金(32071600)

Research progress of urban green space landscape pattern change based on satellite remote sensing

YE Jun, KANG Siqi, FU Genshen, LÜ Haiyan, QIAN Wenqi, TANG Xuehai   

  1. School of Forestry and Landscape Architecture, Anhui Agricultural University, Hefei 230061, China
  • Received:2021-04-14 Online:2022-03-25 Published:2022-04-01

摘要: 城市绿地景观是城市景观自然要素和社会经济可持续发展的生态基础,在城市景观结构、功能及其变化中起重要作用。利用卫星遥感技术开展城市绿地格局研究已成为热点。本文通过梳理相关研究成果,阐述了城市绿地景观遥感分类方法、景观格局指数的选择及城市绿地景观格局动态变化驱动力分析的具体内容,分析出基于遥感技术的城市绿地景观格局研究在数据源和景观格局指数选择时所存在的不足,并且从遥感数据源、分类方法、景观指数筛选和多学科、多角度交叉综合的研究方法等方面对城市绿地景观格局分析提出展望。

关键词: 城市绿地;遥感;景观格局;动态变化;驱动力分析

Abstract: Urban green space landscape is the ecological basis for the natural elements of urban landscape and the sustainable development of social economy,which plays an important role in the structure,function and change of urban landscape.Using satellite remote sensing technology to study urban green space pattern has become a hot spot.By reading and organizing the relevant literatures,this study expounds the remote sensing classification method of urban green space landscape,the selection of landscape pattern index,and the specific content of driving force analysis of urban green space landscape pattern dynamic change.The results shows that there are some deficiencies in the data source and landscape pattern index selection of urban green space landscape pattern research based on remote sensing technology.This study puts forward to the prospect of urban green space landscape pattern analysis from the aspects of remote sensing data sources,classification methods,landscape index selection,and multidisciplinary and multi-angle cross-synthesis research method

Key words: urban green;remote sensing;landscape pattern;dynamic change;driving force analysis

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