Remote sensing inversion study of total organic carbon concentration in Karst Plateau Lakes–Taking Pingzhai reservoir as an example

喀斯特 高原(数学) 总有机碳 反演(地质) 环境科学 水文学(农业) 遥感 自然地理学 地质学 地理 地貌学 环境化学 数学 岩土工程 构造盆地 考古 化学 数学分析
作者
Rukai Xie,Zhongfa Zhou,Jie Kong,Yan Zou,Fuqiang Zhang,Li Li,Y. F. Wang,Cui Wang,Caixia Ding
出处
期刊:Geocarto International [Taylor & Francis]
卷期号:39 (1)
标识
DOI:10.1080/10106049.2024.2343006
摘要

Currently, the inversion of remote sensing satellite images of water environment indicators mostly stays in the indicators with active optical characteristics, while there is less research on the inversion of most water quality indicators with non-optical activity properties, weak scattering and absorption of optical radiation, the size of their concentration has little effect on the spectral characteristics of the water body, such as TOC(Total Organic Carbon).In this paper, based on Pingzhai Reservoir, a dammed river in the karst mountainous area, the inversion model of TOC concentration was established based on BP neural network (BPNN) and sentinel-2 satellite remote sensing images.The results showed that the single bands with high correlation with the measured TOC concentration data were two vegetation red-edge bands B6 (740 nm) and B7 (783 nm) and one NIR band B8 (842 nm), and finally b7, b6 b7, b7 b8, b7 � b8 were selected as the input layers of BPNN for modeling through the combination of the bands, and their Pearson's coefficients were -0.667, -0.656, -0.655, -0.675.The inverse model established could reach a minimum RMSE of 0.235 mg/L and a maximum R 2 of 0.889, which was superior to that of the conventional empirical model.Demonstrate the feasibility of a TOC inversion method based on Sentinel-2 data and BPNN to monitor TOC concentrations in Pingzhai Reservoir.The study successfully established a BP neural network inversion model of TOC concentration in Pingzhai Reservoir with low error, meanwhile, we analyzed the correlation between common water quality indicators and TOC in the reservoir, in which TOC showed significant positive correlation with WT and significant negative correlation with TN and EC, with Pearson's coefficients of 0.655, -0.666, and -0.393, respectively.The article provides scientific theoretical foundation and technical support for water quality protection of water sources.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
Pomelotea发布了新的文献求助10
刚刚
刚刚
小淮发布了新的文献求助10
1秒前
mint发布了新的文献求助10
1秒前
lobster应助Lio采纳,获得30
2秒前
妳口妳口应助zzzz采纳,获得10
2秒前
2秒前
3秒前
3秒前
3秒前
4秒前
niu发布了新的文献求助10
5秒前
共享精神应助小资采纳,获得10
5秒前
青禾纪时完成签到,获得积分10
5秒前
隐形薯片发布了新的文献求助10
6秒前
7秒前
7秒前
今后应助青禾纪时采纳,获得10
7秒前
郑鹏飞发布了新的文献求助10
8秒前
zz发布了新的文献求助10
9秒前
沉静的诗云完成签到,获得积分10
9秒前
小6s完成签到,获得积分10
9秒前
真实的小刺猬完成签到,获得积分10
9秒前
艾吉完成签到,获得积分10
11秒前
11秒前
13秒前
pluto应助pmc采纳,获得40
13秒前
大鸭梨完成签到,获得积分10
15秒前
15秒前
断棍豪斯完成签到,获得积分10
16秒前
沈华炜完成签到,获得积分10
16秒前
18秒前
高大草莓完成签到,获得积分10
18秒前
SIDEsss完成签到,获得积分10
19秒前
20秒前
万鑫海发布了新的文献求助10
21秒前
慕青应助友好的东蒽采纳,获得10
21秒前
香蕉觅云应助听话的衬衫采纳,获得10
22秒前
NexusExplorer应助Steve采纳,获得10
22秒前
青禾纪时发布了新的文献求助10
23秒前
高分求助中
Markov Chain Monte Carlo 10000
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Common Foundations of American and East Asian Modernisation: From Alexander Hamilton to Junichero Koizumi 5000
悉尼大学博士学位论文,题目:Modelling and testing of one-sided stitched laminated composites. 作者:Kristopher P. Plain 700
Matrix Methods in Data Mining and Pattern Recognition Second Edition 610
Blackwell's five-minute veterinary consult clinical companion: small animal gastrointestinal diseases 500
Data book on fatigue strength of metallic materials 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7563884
求助须知:如何正确求助?哪些是违规求助? 9144322
关于积分的说明 19552391
捐赠科研通 7151278
什么是DOI,文献DOI怎么找? 3262390
关于科研通互助平台的介绍 2428651
邀请新用户注册赠送积分活动 2252109