Remote Sensing Inversion Study on Key Water Quality Parameters of Qinghai Lake

To select a suitable remote sensing inversion model for the concentration of chlorophyll-a, a key water quality parameter of Qinghai Lake, this study based on Landsat 8 remote sensing image data and combined with the measured chlorophyll-a concentration data, constructed an inversion model for chlorophyll-a concentration in Qinghai Lake, and explored the spatial distribution pattern of chlorophyll-a concentration in Qinghai Lake in July 2024. The results show that the bands with higher correlation with the chlorophyll-a concentration of this water body are Landsat 8's B1, B6, and B7 bands; the band combination B6-B7 has a high correlation with the natural logarithm of chlorophyll-a concentration; the root mean square error (RMSE) of the chlorophyll-a concentration inversion model constructed is 0.162 μg/L, and the mean absolute error (MAE) is 14.36%, with high accuracy and good applicability; in July 2024, the chlorophyll-a concentration in Qinghai Lake showed a characteristic of lower concentrations at the river mouths such as the Buhai River and higher concentrations in areas such as the Erliangxian coast.

Authors

Institutions

Publication Details

Journal
Architecture Engineering and Science
Published
2025-05-29
DOI
https://doi.org/10.32629/aes.v6i2.3819
Primary Topic
Environmental Changes in China
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Remote Sensing Inversion Study on Key Water Quality Parameters of Qinghai Lake

Jing Shi, Zhaoyang Xie, Hailin Niu
Architecture Engineering and Science
Environmental Changes in China
article

Remote Sensing Inversion Study on Key Water Quality Parameters of Qinghai Lake

Jing Shi, Zhaoyang Xie, Hailin Niu
article en

Abstract

To select a suitable remote sensing inversion model for the concentration of chlorophyll-a, a key water quality parameter of Qinghai Lake, this study based on Landsat 8 remote sensing image data and combined with the measured chlorophyll-a concentration data, constructed an inversion model for chlorophyll-a concentration in Qinghai Lake, and explored the spatial distribution pattern of chlorophyll-a concentration in Qinghai Lake in July 2024. The results show that the bands with higher correlation with the chlorophyll-a concentration of this water body are Landsat 8's B1, B6, and B7 bands; the band combination B6-B7 has a high correlation with the natural logarithm of chlorophyll-a concentration; the root mean square error (RMSE) of the chlorophyll-a concentration inversion model constructed is 0.162 μg/L, and the mean absolute error (MAE) is 14.36%, with high accuracy and good applicability; in July 2024, the chlorophyll-a concentration in Qinghai Lake showed a characteristic of lower concentrations at the river mouths such as the Buhai River and higher concentrations in areas such as the Erliangxian coast.

Architecture Engineering and ScienceVol. 6(2)
Qinghai University (CN)
Openalex Percentile: Top 82%
Environmental Changes in China
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Remote Sensing Inversion Study on Key Water Quality Parameters of Qinghai Lake — Jing Shi, Zhaoyang Xie, et al. · Architecture Engineering and Science (2025) | TGRS Research Map | TGRS