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基于RS/GIS的泉州湾红树林湿地时空动态变化分析 被引量:17

Dynamic change analysis of mangrove swamps based on RS/GIS in Quanzhou Bay
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摘要 红树林湿地具有重要的生态服务功能,明确其时空动态变化特征对于保护和管理红树林湿地具有重要意义。本研究在野外实地调查与不同季相红树林、滩涂和米草光谱特征对比分析的基础上,基于Landsat TM/OLI RS影像,利用面向对象分类方法得到1990、1997、2005、2010和2017年泉州湾河口湿地自然保护区土地覆盖空间分布数据,并结合动态度、空间叠置分析、质心迁移等方法分析红树林时空动态变化特征及其驱动力因素。结果表明:1990—2017年,红树林面积整体呈大幅度增加,仅在1997—2005年间呈现小面积减少,其中在2010—2017年间面积增加最为剧烈,动态度为32.78%。相对于其他土地覆盖类型,米草和滩涂与红树林的面积转化最大,其中1997—2005年共有4.70 hm2红树林转出为米草和滩涂,而2010—2017年间共有178.60 hm2滩涂和米草转入为红树林。1990—2017年,红树林与米草质心均向海迁移,且彼此间的距离逐渐增大。红树林面积时空变化的驱动力因素涉及多个方面,其中自然环境变化、外来植被入侵和养殖业发展对红树林的存在与繁衍具有一定的消极作用,而人工造林工程与入侵植被治理对其具有积极作用,且作用大于前者。继续实施和深入研究红树林人工造林工程、米草治理方法和建立健全红树林生态系统监测体系是保护和管理红树林湿地的重要手段和措施。 Mangrove swamps are ecologically important ecosystems.Discerning the spatiotemporal dynamics of mangrove swamps is of great significance to their protection and management.Considering the tidal information,suitable Landsat TM/OLI images were selected as the base remote sensing data.Based on field investigation and comparison analysis of the spectral characteristics of mangrove forests,mudflats,and Spartina in different seasons,the spatial distribution data of land cover type in the Quanzhou Bay Estuary Wetland Nature Reserve in 1990,1997,2005,2010,and 2017 were obtained by an object-oriented classification method.The spatial and temporal dynamic characteristics and driving factors of mangrove forests were analyzed through a combination of dynamic degree,spatial overlay analysis,and centroid migration methods.The results showed that the classification accuracy and efficiency of the mangrove forest information extraction were improved based on the method used in the study,which had certain advantages and potential in mangrove forest information extraction.The area of mangrove forests increased significantly from 1990 to 2017 as a whole,despite a slight reduction from 1997 to 2005.During 2010—2017,the mangrove forest area increased the most,with a dynamic degree of 32.78%.Compared with other land cover types,the conversion area between Spartina as well as mudflat and mangrove forests was the largest,of which 4.70 hm2 mangrove forests was transferred to Spartina and mudflat from 1997 to 2005,and 178.60 hm2 Spartina and mudflat were converted into mangrove forests from 2010 to 2017.From 1990 to 2017,the centroids of mangrove forests and Spartina migrated to the sea,and the distance between them increased.The threat of Spartina to mangrove forests gradually decreased.The driving factors of spatial and temporal variation in mangrove forest area were related to many aspects,among which natural environment change,exotic vegetation invasion,and development of the aquaculture industry negatively affected the existence and reproduction of mangrove forests,while the mangrove forest artificial afforestation project and invasive vegetation management positively affected it.The positive effects can neutralize or offset the negative effects to a large extent.Anthropogenic activities significantly affect mangrove swamp ecosystems via active protection.Thus,it is important to protect and manage mangrove swamps by continuing to carry out the mangrove forest artificial afforestation project,by controlling Spartina,and by establishing and perfecting the mangrove forest ecosystem monitoring system.
作者 路春燕 高弋斌 陈远丽 贾明明 傅玮韦华 熊怡林 LU Chunyan;GAO Yibin;CHEN Yuanli;JIA Mingming;FU Weiwei;XIONG Yilin(College of Computer and Information Sciences,Fujian Agriculture and Forestry University,Fuzhou,Fujian 350002,China;Key Laboratory of Wetland Ecology and Environment,Northeast Institute of Geography and Agroecology,Chinese Academy of Sciences,Changchun,Jilin 130102,China;College of Forestry,Fujian Agriculture and Forestry University,Fuzhou,Fujian 350002,China)
出处 《森林与环境学报》 CSCD 北大核心 2019年第2期143-152,共10页 Journal of Forest and Environment
基金 福建省自然科学基金面上项目"基于国产多源遥感数据的红树林植物群落分类及其碳储量估算"(2017J01457) 福建省林业科学研究项目"泉州湾红树林湿地时空动态监测及其碳储量估算研究"(闽林科2016035) 国家自然科学基金项目"基于高分和高光谱卫星数据的红树林植物群落分类研究"(41601470)
关键词 红树林湿地 面向对象分类 质心迁移 泉州湾 遥感 mangrove swamp object-oriented classification centroid migration Quanzhou Bay remote sensing
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