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Remote Sensing for Land & Resources    2019, Vol. 31 Issue (3) : 157-165     DOI: 10.6046/gtzyyg.2019.03.20
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Comparison of Sentinel-2 imagery with Landsat8 imagery for surface water extraction using four common water indexes
Dazhao WANG, Simeng WANG, Chang HUANG()
Shaanxi Key Laboratory of Earth Surface System and Environmental Carrying Capacity, Northwest University, Xi’an 710127, China
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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 (AWEIsh) 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, AWEIsh 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.

Keywords Sentinel-2      Landsat8      NDWI      MNDWI      AWEIsh      WI2015     
:  TP79  
Corresponding Authors: Chang HUANG     E-mail: changh@nwu.edu.cn
Issue Date: 30 August 2019
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Dazhao WANG
Simeng WANG
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Dazhao WANG,Simeng WANG,Chang HUANG. Comparison of Sentinel-2 imagery with Landsat8 imagery for surface water extraction using four common water indexes[J]. Remote Sensing for Land & Resources, 2019, 31(3): 157-165.
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https://www.gtzyyg.com/EN/10.6046/gtzyyg.2019.03.20     OR     https://www.gtzyyg.com/EN/Y2019/V31/I3/157
Fig.1  Landsat8 composite image of Poyang Lake with B5(R),B4(G),B3(B)
Fig.2  Comparison of reflectance of six corresponding bands between Landsat8 and Sentinel-2
Fig.3  Water index images of Landsat8 and Sentinel-2
Fig.4  Water distribution derived from Landsat8 and Sentinel-2 using 0 as the threshold
Fig.5  Water distribution derived from Landsat8 and Sentinel-2 using customized threshold
Fig.6  Overlapping maps of water distribution of Landsat8 and Sentinel-2
水体指数 L非水S非水 L水S水 L非水S水 L水S非水
NDWI 79.74 16.87 2.33 1.06
MNDWI 78.77 17.88 2.25 1.10
AWEIsh 75.45 20.52 2.73 1.30
WI2015 76.00 19.91 2.72 1.37
Tab.1  Superimposed image percentage of various types of pixels(%)
Fig.7  Overlapping maps of four water indices from Landsat8 and Sentinel-2
影像 无指数探
测为水
1种指数
探测为水
2种指数
探测为水
3种指数
探测为水
4种指数
探测为水
Landsat8 76.62 0.85 1.84 2.10 18.60
Sentinel-2 78.18 0.54 1.93 1.82 17.53
Tab.2  Statistics of superimposed pixel number for four indices from Landsat8 and Sentinel-2 (%)
影像 水体指数 错分
率/%
漏分
率/%
总体精
度/%
Kappa
系数
Landsat8 NDWI 0.02 9.17 90.81 0.813 3
MNDWI 0.04 6.71 93.24 0.861 0
AWEIsh 0.36 5.13 94.52 0.886 2
WI2015 0.27 5.56 94.48 0.885 5
Sentinel-2 NDWI 0.08 5.68 94.24 0.880 9
MNDWI 0.07 3.19 96.74 0.931 7
AWEIsh 0.16 1.83 98.01 0.958 0
WI2015 0.14 1.80 98.06 0.959 1
Tab.3  Accuracy evaluation of four water extraction results based on Landsat8 and Sentinel-2 images using four water indices
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