摘要
湿地是地球上最重要的生态系统之一,具有净化水质、维持生物多样性等重要功能。由于湿地具有特殊的水文和植被特征,传统的监测方法难以对其进行测绘和管理。随着大数据和云计算的兴起,GEE(Google Earth Engine)为长时间序列的数据处理提供了可能。本研究基于GEE平台,结合Sentinel-1雷达影像和Sentinel-2光学影像,利用随机森林分类算法对天津北大港湿地进行信息提取,探讨多源遥感数据和时间序列特征对天津北大港湿地分类的重要性,并最终得到2019–2022年天津北大港湿地遥感分类数据集。经实测数据验证,分类结果的总体精度为95.35%,符合精度要求。本数据集可为天津北大港湿地保护和管理提供科学依据。
As one of the most important ecosystems on Earth,Wetlands play a vital role in water purification and biodiversity preservation.However,the special hydrological and vegetation characteristics of coastal wetlands make them challenging to map and manage them using traditional monitoring methods.With the advancement of big data and cloud computing,Google Earth Engine(GEE)enables long-term data processing.This study uses the GEE platform to integrate Sentinel-1 synthetic aperture radar data with Sentinel-2 optical data,employing random forest(RF)to extract information about Beidagang Wetland in Tianjin.We explored the significance of multi-source data and time series characteristics for the classification for Beidagang Wetland in Tianjin,and finally obtained a dataset of remote sensing classification of Beidagang wetlands in Tianjin from 2019 to 2022.Validated by measured data,the overall accuracy of the classification results is 95.35%,meeting the accuracy requirements.This dataset can provide scientific basis for the protection and management of Beidagang Wetland.
作者
张心悦
韩杏杏
王铁军
李攀
黄辉
陈楚
ZHANG Xinyue;HAN Xingxing;WANG Tiejun;LI Pan;HUANG Hui;HEN Chu(Institute of Surface-Earth System Science,School of Earth System Science,Tianjin University,Tianjin 300072,P.R.China;Tianjin Bohai Rim Coastal Earth Critical Zone National Observation and Research Station,Tianjin University,Tianjin 300072,P.R.China;Key Laboratory of Tree Breeding and Cultivation,National Forestry and Grassland Administration,Research Institute of Forestry,Chinese Academy of Forestry Sciences,Beijing 100091,P.R.China;Collaborative Innovation Center of Sustainable Forestry in Southern China,Nanjing Forest University,Nanjing 210037,P.R.China;Henan Xiaolangdi Earth Critical Zone National Research Station on the Middle Yellow River,Jiyuan 454650,P.R.China;Tianjin Institute of Surveying and Mapping,Tianjin 300201,P.R.China)
基金
科技部基础性工作专项(2021FY100701)
武汉大学测绘遥感信息工程国家重点实验室开放研究基金资助(21R01)。
