Research on Small Water Body Extraction Method Based on Sentinel-2 Satellite Multi-spectral Remote Sensing Image[J/OL]. Journal of Remote Sensing, 2021.
Research on Small Water Body Extraction Method Based on Sentinel-2 Satellite Multi-spectral Remote Sensing Image[J/OL]. Journal of Remote Sensing, 2021.DOI:
基于卫星遥感的水体提取算法主要针对大中型湖库或者是大型河流,应用于细小水体时容易出现误判。哨兵二号卫星多光谱遥感数据空间分辨率为10、20、60米,双星时间分辨率5天,时间和空间分辨率较高,因此本文采用了哨兵2绿光波段(560nm)、红边波段(705nm)、近红外波段(842nm、865nm)和短波红外波段(2190nm)的遥感反射率,提出了一种新的水体指数算法(Vegetation Red Edge based Water Index,简称RWI)。对比分析了植被、阴影、建筑物、混合像元、裸土、水体6种地物的归一化遥感反射率,从机理上解释了为什么RWI比其他水体指数具有更好的提取细小水体的效果。本文对比了常用的几种水体提取算法,包括改进的归一化差异水体指数MNDWI(Modified Normalized Difference Water Index)、多波段水体指数MBWI(Multi-Band Water Index)、自动水提取指数AWEI(Automated Water Extraction Index),以人工目视解译的水体结果为准,对比以上几种算法得到的水体提取结果,得出RWI、MNDWI、MBWI、AWEIsh、AWEInsh的误差分别为3.6%
The water body extraction algorithm based on satellite remote sensing is mainly aimed at large and medium-sized lakes or large rivers. When applied to small water bodies
it is easy to misjudge. Sentinel 2 satellite multi-spectral remote sensing data spatial resolution of 10
20
60 meters
a double star time resolution of 5 days
and high temporal and spatial resolution. Therefore
this paper uses the sentinel-2 green light band (560nm)
red edge band (705nm)
near infrared band (842nm
865nm) and short wave infrared band (2190) for remote sensing reflectance. A new water index algorithm (Red Edge based Water Index
RWI for short) is proposed for the extraction of finely water. The normalized remote sensing reflectivity of vegetation
shadow
building
mixed pixel
bare soil and water body is compared and analyzed. The mechanism explains why RWI has better effect of extracting fine water body than other water body indexes.