Remote Sensing Evaluation of Trophic Status in the Daihai Lake Based on Fuzzy Classification
Year: 2024
Type: article
Abstract: Trophic status is a crucial ecological and environmental concern in the field of water resource management and has garnered widespread attention. Owing to the complexity of optical characteristics in aquatic environments, we employed a fuzzy classification approach and a composite nutrient status index to categorize in situ remote sensing reflectance data. This enabled the establishment of nutrient status assessment models for distinct classes, facilitating the evaluation of Daihai Lake in the Inner Mongolia Autonomous Region of China. Subsequently, the model was applied to MSI data to determine the trophic status of Daihai Lake during the period 2016–2021. We conducted an analysis using a structural equation model (SEM) to identify the primary drivers. The results indicated that the water bodies in Dai Lake can be broadly classified into three categories, with the nutrient status models demonstrating robust performance for each category (R2=0.80, R2=0.83, and R2=0.74). Comparisons were made between nutrient status accuracies obtained through the NCM and FCM based on measured data, yielding R2 values of 0.74 and 0.85, respectively. Furthermore, the TSI results derived from MSI inversion were validated, with NCM achieving an R2 of 0.49, RMSE of 6.88, and MAPE of 10.36%, while FCM exhibited an R2 of 0.55, RMSE of 8.89, and MAPE of 13.18%. An SEM-based analysis revealed that over the long term, human activities exerted a more substantial impact on eutrophication in Daihai Lake, while climatic factors played an accelerating and reinforcing role.
Source: Water
DOI: 10.3390/w16213032
Authors: Fang Wang, Song Qing, Chula Sa, Lai Quan, An Chang
Institution: Inner Mongolia Normal University
Language: English
Subfield: Environmental Chemistry
Field: Environmental Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $2,955
OpenAlex ID: W4403690931