UAV Hyperspectral Imaging Identifying Urban Black Water
UAV Hyperspectral Imaging Identifying Urban Black Water
Introduction
Urban black and odorous water bodies are those within urban areas exhibiting undesirable colors and odors. These water bodies are categorized into "mildly black and odorous" and "severely black and odorous." Rapid urbanization and excessive wastewater discharge have led to an influx of organic materials into rivers, overwhelming their natural self-purification capacity. This imbalance causes oxygen depletion and hypoxic conditions, resulting in water quality degradation and the formation of black and odorous water bodies. This issue has become a significant challenge for urban development and water ecological management.
Satellite remote sensing technology has been used for the preliminary identification of urban black and odorous water bodies, supporting pollution monitoring and remediation projects. However, satellite imagery often faces challenges such as long acquisition cycles, limited spectral channels, and cloud interference. In contrast, UAV (Unmanned Aerial Vehicle) remote sensing offers higher temporal, spatial, and spectral resolution, making it an ideal tool for providing detailed spectral data to support water quality monitoring models. Additionally, fluorescence spectroscopy enables the identification of organic pollutants in water, offering further insights into pollution sources.
Materials and Methods
Study Area Overview
Jiangsu Province, a major industrial hub in China, includes cities like Nanjing, Wuxi, Changzhou, and Yangzhou, which have experienced rapid industrialization and high population densities. Prior to 2016, many rivers in these cities were affected by black and odorous water due to heavy pollution. Despite ongoing remediation efforts, some rivers continue to face recurring pollution problems. Identifying pollution sources and informing pollution control decisions are now critical tasks.
Indicators and Data
Criteria for Identifying Black and Odorous Water Bodies
Identification of black and odorous water bodies is based on field observations and water quality indicators set by the Ministry of Housing and Urban-Rural Development. Key indicators include water transparency, dissolved oxygen (DO), oxidation-reduction potential (ORP), and ammonia nitrogen levels.
| Parameter | Mild Black Odor | Severe Black Odor | Measurement Method | Remarks |
| Transparency(cm) | 10-25 | <10 | Secchi Disk | In-situ Measurement |
| Dissolved Oxygen(mg/L) | 0.2-2.0 | <0.2 | Electrochemical Method | In-situ Measurement |
| Oxidation-Reduction Potential(mV) | -200-50 | <-200 | Electrode Method | In-situ Measurement |
| Ammonia Nitrogen | 8.0-15 | >15 | Nessler's Reagent | Post-Filtration Measurement |
Ground Data Collection
Data was collected from 144 sampling points across urban areas, with a focus on locations near residential and industrial areas, which are typically more polluted. Field measurements included DO, ORP, and remote sensing reflectance. Laboratory tests assessed parameters such as dissolved organic carbon (DOC), sulfides, and ammonia nitrogen.
UAV Hyperspectral Data
An aiSPEK hyperspectral camera was used to capture images of a river section in Nanjing. The camera covered the spectral range of 400–1000 nm with a spectral resolution of 2.8 nm. The collected data underwent preprocessing for spectral calibration, reflectance calculation, and geometric correction.
Experimental Methodology
Fluorescence Index Calculation
Fluorescence parameters, including the Biological Source Index (BIX), Humification Index (HIX), Fluorescence Index (FI), and Fluorescence Peak Ratio (IA:IT), were calculated to assess the fluorescence characteristics of dissolved organic matter (DOM) in the water. These indices help determine the origin and complexity of DOM, providing insights into pollution sources.
Conclusion
This study explores the use of UAV hyperspectral imaging and fluorescence spectroscopy to identify pollution sources in urban black and odorous water bodies. By analyzing the optical and fluorescence properties of dissolved organic matter, the research contributes to developing more effective methodologies for pollution source identification and improving water quality monitoring. The integration of these technologies offers valuable insights for urban water management and pollution control.