Sentinel-2和Landsat8影像的四种常用水体指数地表水体提取对比

doi:10.6046/gtzyyg.2019.03.20

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摘要

利用卫星影像快速准确地提取湖泊等地表水体范围一直是一个重要的研究课题,其对洪涝灾害监测、水资源管理与利用等具有重要意义。Sentinel-2 MSI和Landsat8 OLI数据是目前主流的开放获取的中高空间分辨率遥感影像。以鄱阳湖区为研究对象,首先,分别使用归一化差异水体指数(normalized difference water index,NDWI)、改进的归一化差异水体指数(modified normalized difference water index,MNDWI)、自动水体提取指数(automated water extraction index,AWEI_sh)和基于线性判别分析的水体指数(water index,WI₂₀₁₅)等4种常用的水体指数从2种影像中提取湖泊水体的分布信息; 然后,分析了在同种水体指数之下2种影像提取结果的差异性和同一幅影像中4种水体指数提取结果的不同; 最后,利用同期的高分一号影像目视解译的结果对水体提取结果进行了精度验证。结果表明,对于2种遥感影像,4种水体指数均能成功地提取出研究区的大部分水体; AWEI_sh和WI₂₀₁₅的提取精度最高,在Sentinel-2和Landsat8影像上分别达到了98%和94%以上,MNDWI次之,NDWI的提取精度最低; 相对而言,Sentinel-2影像提取的水体细部信息更为明显,整体提取效果优于Landsat8影像。

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	王大钊
	王思梦
	黄昌

关键词 ： Sentinel-2, Landsat8, NDWI, MNDWI, AWEI_sh, WI₂₀₁₅

Abstract：

Extracting surface water like lake water areas from satellite images quickly and accurately has been an important research topic, which is of great significance to the water disaster monitoring and water resource management. Sentinel-2 multi spectral imager (MSI) and Landsat8 operational land imager (OLI) data are two popular medium- to high- resolution data sources that are freely available. Using the Poyang Lake as the study area and employing four popular water indices, i.e., normalized difference water index (NDWI), modified normalized difference water index (MNDWI), automatic water extraction index (AWEI_sh) and water index created with linear discriminant analysis (WI₂₀₁₅), the authors extracted water distribution from two types of images respectively. Water extraction results derived from different images and different water indices were analyzed. The accuracy of the water extraction results was evaluated by visual interpretation results of corresponding GF-1 images. The results reveal that, for these two remote sensing images, all water indices can detect most water body successfully. Among these indices, AWEI_sh and WI₂₀₁₅ have relatively higher extraction accuracy, reaching 98% and 94% respectively on Sentinel-2 and Landsat8 images. Compared with Landsat8 images, Sentinel-2 images are capable of reflecting more detailed water body information, and the overall extraction accuracy is higher.

Key words： Sentinel-2 Landsat8 NDWI MNDWI AWEI_sh WI₂₀₁₅

收稿日期: 2018-08-03 出版日期: 2019-08-30

TP79

基金资助:国家重点研发计划项目“山区暴雨洪水时空演变特征及山洪成灾暴雨阈值研究”(2017YFC1502501);国家自然科学基金项目“基于多时相遥感影像的亚像元级地表水变化检测研究”共同资助(41501460)

通讯作者: 黄昌

作者简介: 王大钊(1995-),男,硕士研究生,主要从事遥感技术应用研究。Email: 1597237873@qq.com.。

引用本文:

王大钊, 王思梦, 黄昌. Sentinel-2和Landsat8影像的四种常用水体指数地表水体提取对比[J]. 国土资源遥感, 2019, 31(3): 157-165.
Dazhao WANG, Simeng WANG, Chang HUANG. Comparison of Sentinel-2 imagery with Landsat8 imagery for surface water extraction using four common water indexes. Remote Sensing for Land & Resources, 2019, 31(3): 157-165.

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https://www.gtzyyg.com/CN/10.6046/gtzyyg.2019.03.20 或 https://www.gtzyyg.com/CN/Y2019/V31/I3/157

Fig.1 鄱阳湖Landsat8 B5(R),B4(G),B3(B)合成影像
(绿框为使用GF-1影像进行精度验证的区域)

Fig.2 Landsat8和Sentinel-2影像的6个对应波段的反射率对比

Fig.3 Landsat8和Sentinel-2的水体指数图像

Fig.4 Landsat8和sentinel-2使用阈值0得到的水体分布

Fig.5 Landsat8和Sentinel-2使用自定义阈值得到的水体分布

Fig.6 Landsat8与Sentinel-2的水体分布叠加结果

Tab.1 叠加图像各类像元所占百分比

Fig.7 Landsat8和Sentinel-2影像4种指数得到的水体分布的叠加结果

Tab.2 Landsat8和Sentinel-2影像4种水体分布叠加后的像元统计

Tab.3 基于Landsat8和Sentinel-2影像的4种水体指数水体提取结果精度指标

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