| 基于TM影像的广州市主城区城市绿地的提取和分析 |
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| 引用本文： | 邢玮,刘金然,徐少雄.基于TM影像的广州市主城区城市绿地的提取和分析[J].测绘与空间地理信息,2020(6):123-125. |
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| 作者姓名： | 邢玮 刘金然 徐少雄 |
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| 作者单位： | 兰州交通大学测绘与地理信息学院;甘肃省地理国情检测工程实验室;山东师范大学地理与环境学院 |
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| 摘 要： | 利用遥感技术能够实现快速提取城市绿地信息,准确地计算出城市绿地面积及覆盖情况等。本文以广州市TM遥感影像为数据源,进行一系列预处理,对监督分类和先计算NDVI再采用非监督分类这两种提取方法进行比较分析。结果表明,先计算NDVI再采用非监督分类法精度较高,说明该方法是一种有效的绿地信息提取方法。
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| 关 键 词： | 城市绿地 NDVI 非监督分类 |
Extraction and Analysis of City Green Space Information Based on TM Image of Guangzhou |
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| XING Wei,LIU Jinran,XU Shaoxiong.Extraction and Analysis of City Green Space Information Based on TM Image of Guangzhou[J].Geomatics & Spatial Information Technology,2020(6):123-125. |
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| Authors: | XING Wei LIU Jinran XU Shaoxiong |
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| Institution: | (Faculty of Geomatics,Lanzhou Jiaotong University,Lanzhou 730070,China;Gansu Provincial Engineering Laboratory for National Geographic State Monitoring,Lanzhou 730070,China;College of Geography and Environment,Shandong Normal University,Ji'nan 250358,China) |
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| Abstract: | Remote sensing technology can be used to quickly extract urban green space information and accurately calculate the area and coverage of urban green space.TM remote sensing image of Guangzhou city was taken as the data source,and a series of prepro-cessing was carried out to compare and analyze the two extraction methods of supervised classification and NDVI calculation before un-supervised classification.The results show that the accuracy of NDVI classification is higher than that of unsupervised classification,indicating that this method is an effective method to extract green space information. |
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| Keywords: | urban green space NDVI unsupervised classification |
| 本文献已被 CNKI 维普 等数据库收录！ |
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