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2021 Vol. 33, No. 3
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WANG Yifei,, GONG Zhaoning, ZHANG Yuan, SU Shuo,, . 2021. Extraction and application of Forel-Ule index based on images from multiple sensors. Remote Sensing for Natural Resources, 33(3): 262-271. doi: 10.6046/zrzyyg.2020324
Citation: WANG Yifei,, GONG Zhaoning, ZHANG Yuan, SU Shuo,, . 2021. Extraction and application of Forel-Ule index based on images from multiple sensors. Remote Sensing for Natural Resources, 33(3): 262-271. doi: 10.6046/zrzyyg.2020324

Extraction and application of Forel-Ule index based on images from multiple sensors

  • The quantitative characterization of water body color can provide important reference data for the comprehensive water quality assessment of inland lakes and reservoirs. The Guanting Reservoir is a large inland lake in North China. Based on FUI inversion using the seasonal-scale Sentinel-2 and Landsat 8 OLI reflectance data during 2016—2020, this study quantitatively analyzed the heterogeneous characteristics of Forel-Ule Index (FUI) of the Guanting Reservoir on the spatial, intra-annual, and inter-annual scales. To explore the coupling relationship between the FUI and the nutrient status of the water body, models were built using both hue angle α and FUI and the trophic status index (TSI). Moreover, this study demonstrated the comparability of FUI among different sensors and its application potential. The results are as follows. ① On the spatial scale, the FUI value was low at the center but high on the edge of the reservoir. ② On the seasonal scale within a year, the FUI value showed a trend of reaching the highest in winter, slightly decreasing in spring, reaching the lowest in summer, and rising again in autumn. ③ On the interannual scale, the FUI value in the latest three years was lower than that in the first two years during 2016—2020 and the water color changed accordingly from yellowish brown to yellowish green. These may be attributable to the effective governance of the Guanting Reservoir by the Beijing Municipal Government. ④ The Pearson correlation coefficient between TSI and α and that between TSI and FUI were -0.85 and 0.80, respectively, indicating a strong correlation between FUI and TSI. ⑤ The FUI values obtained through the inversion based on the Sentinel-2 and Landsat 8 OLI images of the same day were very approximate and were 13.04 and 13.16, respectively. This indicates that FUI is comparable between the images from different sensors. Therefore, the inversion of FUI can be achieved using the long time-series remote sensing data from multiple sensors. Meanwhile, FUI possesses notable application potential and advantages in the assessment of water quality and trophic status.
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