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
刚刚
风趣的南霜完成签到,获得积分10
1秒前
1秒前
高小航完成签到,获得积分10
1秒前
望天发布了新的文献求助10
2秒前
2秒前
2秒前
甜美幻露完成签到,获得积分20
2秒前
小豆豆完成签到,获得积分10
4秒前
可爱的函函应助Wendy采纳,获得10
5秒前
呵呵举报愉快的自行车求助涉嫌违规
5秒前
6秒前
甜美幻露发布了新的文献求助10
8秒前
余华发布了新的文献求助10
9秒前
满意绮彤发布了新的文献求助10
9秒前
9秒前
纯情的咖啡豆完成签到,获得积分10
9秒前
英俊的铭应助Robert采纳,获得10
10秒前
10秒前
staryf发布了新的文献求助10
10秒前
CipherSage应助科研通管家采纳,获得10
11秒前
我是老大应助科研通管家采纳,获得10
11秒前
ding应助科研通管家采纳,获得10
11秒前
369ninja应助科研通管家采纳,获得10
11秒前
11秒前
cdercder应助科研通管家采纳,获得10
11秒前
大模型应助科研通管家采纳,获得10
12秒前
CodeCraft应助科研通管家采纳,获得10
12秒前
汉堡包应助科研通管家采纳,获得10
12秒前
12秒前
13秒前
张兔子完成签到 ,获得积分10
13秒前
13秒前
13秒前
13秒前
淡定的以寒完成签到,获得积分10
16秒前
bkagyin应助余华采纳,获得10
16秒前
小橙子发布了新的文献求助10
16秒前
甄幻梦发布了新的文献求助10
16秒前
17秒前
高分求助中
(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
Cronologia da história de Macau 5000
Merrill's Atlas of Radiographic Positioning and Procedures - 3-Volume Set, 16th Edition 2000
Matrix Methods in Data Mining and Pattern Recognition 540
Interactions of Vowel Quality and Prosody in East Slavic 500
Vander's Renal Physiology第10版 500
Materials Informatics Molecules, Crystals and Beyond A volume in Acta Materialia Book Series 400
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 7068332
求助须知:如何正确求助?哪些是违规求助? 8729517
关于积分的说明 18473966
捐赠科研通 6600104
什么是DOI,文献DOI怎么找? 3126755
关于科研通互助平台的介绍 2223206
邀请新用户注册赠送积分活动 2102157