| 基于Sentinel-2的潮间红树林提取方法 |
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| 引用本文： | 徐芳,张英,翟亮,刘佳,谷祥辉.基于Sentinel-2的潮间红树林提取方法[J].测绘通报,2020,0(2):49-54. |
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| 作者姓名： | 徐芳 张英 翟亮 刘佳 谷祥辉 |
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| 作者单位： | 1. 兰州交通大学测绘与地理信息学院, 甘肃 兰州 730070;2. 地理国情监测技术应用国家地方联合 工程研究中心, 甘肃 兰州 730070;3. 甘肃省地理国情监测工程实验室, 甘肃 兰州 730070;4. 中国 测绘科学研究院, 北京 100830;5. 地球观测与时空信息科学自然资源部重点实验室, 北京 100830;6. 山东科技大学测绘科学与工程学院, 山东 青岛 266590 |
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| 基金项目： | 国家自然科学基金（41701213）；中国测绘科学研究院基本科研业务费（7771728；7771820；AR1928；AR1931）；自然资源部地球观测与时空信息科学重点实验室开放基金（AR191902）；兰州交通大学优秀平台支持项目（201806） |
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| 摘 要： | 位于潮间带的红树林可能在高潮时被海水淹没的特点，使得传统的植被提取方法在红树林信息提取方面存在局限性。本文在对比分析了出露的红树林、高潮水位淹没的红树林、海水水体的光谱特征后，提出了一种利用归一化潮间红树林指数（NIMI）提取潮间带红树林的方法。该指数是由植被强吸收的红波段，强反射的两个红边波段和近红外波段组成的归一化表达式。利用该指数对福建省龙海九龙江口湿地的红树林进行了分类提取，提取结果与高分二号影像目视验证和现场调查结果进行了对照。结果显示，该方法提取红树林的用户精度达到93.98%，并显著优于利用归一化水体指数（NDWI）、归一化植被指数（NDVI）及随机森林的结果。
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| 关 键 词： | 红树林 淹没 提取 Sentinel-2影像 归一化潮间红树林指数 |
| 收稿时间： | 2019-09-09 |
Extraction method of intertidal mangrove by using Sentinel-2 images |
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| XU Fang,ZHANG Ying,ZHAI Liang,LIU Jia,GU Xianghui.Extraction method of intertidal mangrove by using Sentinel-2 images[J].Bulletin of Surveying and Mapping,2020,0(2):49-54. |
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| Authors: | XU Fang ZHANG Ying ZHAI Liang LIU Jia GU Xianghui |
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| Abstract: | Mangroves located in intertidal zone may be submerged by sea water at high tide, which makes the traditional vegetation extraction methods are limited at mangrove information extraction. After comparing and analyzing the spectral characteristics of mangroves exposed, mangroves submerged at high tide level and seawater bodies, a method of extracting intertidal Mangroves by using normalized intertidal mangrove index (NIMI) is proposed in this paper. The index is normalized expressions for the composition of a red band strongly absorbed by vegetation and two red-edge bands as well as a near-infrared band strongly reflected by vegetation. The index is used to classify and extract mangroves from Jiulongjiang Estuary wetland in Longhai, Fujian Province. The results are compared with the results of visual verification of GF-2 and field investigation. The results shows that the user accuracy of this method reaches 93.98%, and is significantly better than that of using normalized water index (NDWI), normalized vegetation index (NDVI) and the results of random forest. |
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| Keywords: | mangrove submerge extraction Sentinel-2 image normalized intertidal mangrove index |
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