中国滨海湿地遥感研究进展
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摘要
滨海湿地作为独特的生态系统,具有重要的生态经济和科学研究价值。遥感技术具有观测范围广、信息量大、获取信息快、可比性强等优点,近30年来已广泛应用于各种研究中。从滨海湿地遥感数据源、理论和方法,以及其在滨海湿地资源调查和管理、景观格局与动态变化、生态环境监测、生态系统质量与服务评价等方面的应用,介绍了我国滨海湿地遥感的研究现状;指出当前滨海湿地遥感存在的问题:研究区地理时空分布不均和以中小尺度为主,跨学科综合研究较少,偏重理论研究而忽视应用性,信息共享能力差,解译精度提高困难;认为未来的相关研究应该宏观与微观并重,强化多学科协同,加强综合和对比研究,建立统一的滨海湿地遥感分类系统和全国滨海湿地信息系统,发展新兴遥感技术及融合多源数据,强调新方法、新模型的运用。
Coastal wetlands as a unique ecosystems with high productivity and abundant biology diversity,has many important resource values,ecological values,economic values and scientific research values.Due to the multi-temporal,multi-platform,macroscopic,objective,informative,real-time,highly effective,comparable and so on,so the remote sensing technology has been gradually approved and widely promoted in coastal wetland research in the past three decades.Current status of coastal wetland research based on remote sensing technique in China was systematically discussed from multiple aspects,including remote sensing data sources,theories and methods,and the application of remote sensing technology to Chinese coastal wetland is reviewed from the aspects of coastal wetland resource investigation and management,landscape pattern and dynamic change,ecological environment monitoring,ecosystem quality and service evaluation.This paper also points out some shortcomings existed in Chinese coastal wetland research by remote sensing technology include the spatial and temporal distributions of the study area is uneven and dominated by small and medium scale,lack of interdisciplinary comprehensive research,focus on theoretical research and ignore application intelligent application of remote sensing technology,information sharing ability is poor,the improve of interpretation accuracy is difficulties.Related research prospects should be to carry out such as monitoring and mapping on all scale,strengthen the multidisciplinary collaboration,strengthen the comprehensive and comparative study,establish a unified classification system of coastal wetland based on remote sensing and the national coastal wetland information system,emphasis on the development of new remote sensing technology and fusion of multi-source data,emphasis on the use of new methods and new models.
Coastal wetlands as a unique ecosystems with high productivity and abundant biology diversity,has many important resource values,ecological values,economic values and scientific research values.Due to the multi-temporal,multi-platform,macroscopic,objective,informative,real-time,highly effective,comparable and so on,so the remote sensing technology has been gradually approved and widely promoted in coastal wetland research in the past three decades.Current status of coastal wetland research based on remote sensing technique in China was systematically discussed from multiple aspects,including remote sensing data sources,theories and methods,and the application of remote sensing technology to Chinese coastal wetland is reviewed from the aspects of coastal wetland resource investigation and management,landscape pattern and dynamic change,ecological environment monitoring,ecosystem quality and service evaluation.This paper also points out some shortcomings existed in Chinese coastal wetland research by remote sensing technology include the spatial and temporal distributions of the study area is uneven and dominated by small and medium scale,lack of interdisciplinary comprehensive research,focus on theoretical research and ignore application intelligent application of remote sensing technology,information sharing ability is poor,the improve of interpretation accuracy is difficulties.Related research prospects should be to carry out such as monitoring and mapping on all scale,strengthen the multidisciplinary collaboration,strengthen the comprehensive and comparative study,establish a unified classification system of coastal wetland based on remote sensing and the national coastal wetland information system,emphasis on the development of new remote sensing technology and fusion of multi-source data,emphasis on the use of new methods and new models.
引文
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