Arid
DOI10.3390/rs10081279
A New Method for Mapping Aquatic Vegetation Especially Underwater Vegetation in Lake Ulansuhai Using GF-1 Satellite Data
Chen, Qi; Yu, Ruihong1; Hao, Yanling1; Wu, Linhui; Zhang, Wenxing; Zhang, Qi; Bu, Xunan
通讯作者Yu, Ruihong ; Hao, Yanling
来源期刊REMOTE SENSING
ISSN2072-4292
出版年2018
卷号10期号:8
英文摘要

It is difficult to accurately identify and extract bodies of water and underwater vegetation from satellite images using conventional vegetation indices, as the strong absorption of water weakens the spectral feature of high near-infrared (NIR) reflected by underwater vegetation in shallow lakes. This study used the shallow Lake Ulansuhai in the semi-arid region of China as a research site, and proposes a new concave-convex decision function to detect submerged aquatic vegetation (SAV) and identify bodies of water using Gao Fen 1 (GF-1) multi-spectral satellite images with a resolution of 16 meters acquired in July and August 2015. At the same time, emergent vegetation, Huangtai algae bloom, and SAV were classified simultaneously by a decision tree method. Through investigation and verification by field samples, classification accuracy in July and August was 92.17% and 91.79%, respectively, demonstrating that GF-1 data with four-day short revisit period and high spatial resolution can meet the standards of accuracy required by aquatic vegetation extraction. The results indicated that the concave-convex decision function is superior to traditional classification methods in distinguishing water and SAV, thus significantly improving SAV classification accuracy. The concave-convex decision function can be applied to waters with SAV coverage greater than 40% above 0.3 m and SAV coverage 40% above 0.1 m under 1.5 m transparency, which can provide new methods for the accurate extraction of SAV in other regions.


英文关键词aquatic vegetation concave-convex decision function remote sensing extraction GF-1 satellite Lake Ulansuhai China
类型Article
语种英语
国家Peoples R China
收录类别SCI-E
WOS记录号WOS:000443618100115
WOS关键词REMOTE-SENSING DATA ; ALGAE-BLOOM ; WATER-DEPTH ; TAIHU LAKE ; IMAGERY ; MACROPHYTES ; CHINA ; IDENTIFICATION ; AGREEMENT ; CANOPIES
WOS类目Remote Sensing
WOS研究方向Remote Sensing
资源类型期刊论文
条目标识符http://119.78.100.177/qdio/handle/2XILL650/212641
作者单位1.Inner Mongolia Univ, Inner Mongolia Key Lab River & Lake Ecol, Sch Ecol & Environm, Hohhot 010021, Peoples R China;
2.Inner Mongolia Univ, Minist Educ, Sch Ecol & Environm, Key Lab Ecol & Resource Use Mongolian Plateau, Hohhot 010021, Peoples R China
推荐引用方式
GB/T 7714
Chen, Qi,Yu, Ruihong,Hao, Yanling,et al. A New Method for Mapping Aquatic Vegetation Especially Underwater Vegetation in Lake Ulansuhai Using GF-1 Satellite Data[J],2018,10(8).
APA Chen, Qi.,Yu, Ruihong.,Hao, Yanling.,Wu, Linhui.,Zhang, Wenxing.,...&Bu, Xunan.(2018).A New Method for Mapping Aquatic Vegetation Especially Underwater Vegetation in Lake Ulansuhai Using GF-1 Satellite Data.REMOTE SENSING,10(8).
MLA Chen, Qi,et al."A New Method for Mapping Aquatic Vegetation Especially Underwater Vegetation in Lake Ulansuhai Using GF-1 Satellite Data".REMOTE SENSING 10.8(2018).
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