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作 者:张侨洪 靳晟[1] 刘杰 ZHANG Qiaohong;JIN Sheng;LIU Jie(College of Computer and Information Engineering,Xinjiang Agricultural University,Urumqi Xinjiang 830052,China)
机构地区:[1]新疆农业大学计算机与信息工程学院,新疆乌鲁木齐830052
出 处:《农业工程》2024年第3期16-22,共7页AGRICULTURAL ENGINEERING
摘 要:以新疆维吾尔自治区(简称新疆)昌吉回族自治州(以下简称昌吉州)三屯河灌区为研究区域,利用ArcGIS的水文分析模块对GDEMV3 30 m分辨率数字高程模型(digital elevation model,DEM)进行河网水系的提取,从而得出水流方向、汇流累计量、分级河网和子流域边界等河网信息,利用AI Earth深度学习算法对Sentinel-1 SAR GRD遥感影像进行水体分类提取。不同于用遥感影像处理软件(environment for visualizing images,ENVI)对研究区影像进行地物识别分类的传统操作,该研究更倾向于通过AI Earth使用监督分类算法对Sentinel-2 L2A影像数据进行地物分类,进而绘制出渠系一张图,清晰生动地展现研究区域复杂的水系结构,对GDEMV3 30 m分辨率数字高程数据、野外采样点数据、天地图所选区域0.862 m/像素与672瓦片数量的17级Tiff数据进行处理制作采样点的渠系地形三维图,从立体的角度深入探索了水系地貌的特征,为研究提供更全面的视角,并探讨在试验过程中遇到的难点及解决办法。Taking Santun River irrigation district of Changji Hui Autonomous Prefecture(hereinafter referred to as Changji Prefecture)in Xinjiang Uygur Autonomous Region(referred to as Xinjiang)as research area,hydrological analysis module of ArcGIS was used to extract river network water system of GDEMV330 m resolution digital elevation model,so as to obtain river network information such as flow direction,cumulative amount of confluence,hierarchical river network and sub-basin boundary.AI Earth deep learning algorithm was used to classify and extract Sentinel-1 SAR GRD remote sensing images.Different from traditional operation of using ENVI remote sensing image processing software to identify and classify surface objects of images in study area,this study prefered to use AI Earth to classify surface objects of Sentinel-2 L2A image data by using supervised classification algorithm,and then draw a canal system map to clearly and vividly show complex water structure of study area.The 17-grade Tiff data of GDEMV330 m resolution digital elevation data,field sampling point data,and selected area of earth map with 0.862 m/pixel and 672 tiles were processed to make canal system topo-graphy three-dimensional map of sampling point,and to deeply explore features of drainage geomorphology from a three-dimensional perspective to provide a more comprehensive perspective for the study.Difficulties encountered in course of experiment and solutions were discussed.
关 键 词:GIS 深度学习 遥感 水系特征 水利信息化 三屯河灌区
分 类 号:S126[农业科学—农业基础科学]
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