Construction and application of a comprehensive urban water ecological index based on landsat 8-9 OLI remote sensing data: a case study of the Hefei urban area
The urban aquatic ecosystem is closely related to human life, and accurate, rapid, and objective monitoring of it has become an important part of urban ecological research. Remote sensing has great potential for use in urban aquatic ecosystem monitoring. In this paper, indexes related to remote sensing inversion of aquatic ecosystems, namely the normalized difference water index, impervious surface index, normalized difference vegetation index and normalized difference moisture index were selected as baseline data. A remote sensing-based urban water ecological index (RSUWEI) was established to rapidly monitor and evaluate urban aquatic ecosystems. Application of the proposed index in the central urban area of Hefei demonstrates that RSUWEI can quantitatively evaluate and compare the quality of the aquatic ecosystems in the city. In addition, it allows convenient analysis of the temporal and spatial variations of the ecosystems. RSUWEI is entirely based on remote sensing data which are easily accessible. The calculation process is objective, rapid, and highly comparable. Evaluation of the monitoring results shows that in the period from 2013 - 2022, the proportion of the index class representing development expansion in the central urban area of Hefei increased by 6.4 % while the proportion of the class representing water body presence has increased by 0.94 %. The overall quality of aquatic ecosystems has decreased due to the expansion of urban land development.
Authors
- Jinglin Zhou (ORCID: https://orcid.org/0000-0003-1589-7423)
- Jingang Jiang (ORCID: https://orcid.org/0000-0003-0491-9236)
- Pu Zhang (ORCID: https://orcid.org/0009-0004-2429-4637)
- Yuandong Min
- Zhiyang Guo (ORCID: https://orcid.org/0000-0001-9426-0417)
- Wen Zou
- L. D. Liu (ORCID: https://orcid.org/0009-0007-2601-4557)
Institutions
- Hefei Institutes of Physical Science (CN)
- Institute of Intelligent Machines (CN)
- Anhui Academy of Agricultural Sciences (CN)
- Hubei Provincial Water Resources and Hydropower Planning Survey and Design Institute (CN)
- Anhui Water Conservancy and Hydropower Survey and Design Institute (CN)
- Anhui and Huaihe River Institute of Hydraulic Research (CN)
Publication Details
- Published
- 2025-07-16
- DOI
- https://doi.org/10.1117/12.3070615
- Primary Topic
- Remote Sensing and Land Use
- Type
- article
- Field-Weighted Citation Impact
- 0.00