基于景观分维度的海岸带景观时空演变量化评价研究——以泉州湾为例
Quantitative Evaluation of Spatial and Temporal Evolution of Coastal Zone Landscape Based on Landscape Sub-Dimensions:Quanzhou Bay as an Example
陶楠 1庄晓平 2陈丽花3
作者信息
- 1. 昆明理工大学(昆明650000)
- 2. 昆明市土地开发整理中心(昆明362000)
- 3. 同济大学建筑与城市规划学院;井冈山大学(吉安343000)
- 折叠
摘要
海岸带是海陆统筹战略实施及国土空间规划的重点区域,利用遥感影像处理和GIS相结合的技术方式,基于生态学理论中的景观分维度因子,以泉州湾为实证研究典型,对多时相遥感影像的土地利用现状的数据进行统计对比,利用1973年以来7个时相的MSS/TM/ETM遥感资料,监测调查泉州湾入海口围垦后的景观变化,引入景观分维度指标,量化评估围垦后入海口 50年的景观时空变化特征,探讨影响海岸线变化的主要原因,为理解海岸带潜在问题提供决策支持,并总结量化评价方式与路径,提出一种国土空间自然资源的监测与量化评价的参考方法.
Abstract
The coastal zone is a key area for implementing the strategy of land-sea integration and land space planning.This study utilizes the technical approach of combining remote sensing image processing and GIS,based on the landscape sub-dimension factor in the theory of ecology,and takes Quanzhou Bay as a typical empirical study to statistically compare the data of land use status of multi-temporal remote sensing images,and utilizes the MSS/TM/ETM remote sensing data of seven temporal phases since 1973 to monitor and investigate the landscape changes after the reclamation of Quanzhou Bay.Using the MSS/TM/ETM remote sensing data of seven-time phases since 1973,the study monitors and investigates the landscape changes after the reclamation of Quanzhou Bay estuary,introduces landscape sub-dimension indicators,quantitatively evaluates the landscape spatial and temporal change characteristics of the estuary after reclamation for 50 years,explore the main reasons affecting the changes of the coastline,and provide decision-making support for the understanding of the potential problems of the coastal zone,as well as summarize the quantitative evaluation methods and paths,and put forward a reference method of monitoring and quantitative evaluation of the natural resources of the national land space.
关键词
海岸带景观/景观分维度/国土空间规划"一张图"/泉州湾Key words
Coastal zone landscape/Landscape sub-dimension/One map for national spatial planning/Quanzhou Bay引用本文复制引用
基金项目
云南省基础研究计划面上项目(202401CF070132)
出版年
2024
NETL
NSTL
维普
万方数据