| Cite this article: | 陈永贵,朱玉香.黄河流域典型内陆湖泊水生植被类群和藻华遥感监测[J].灌溉排水学报,2022,(12):-. |
| chenyonggui,zhuyuxiang.黄河流域典型内陆湖泊水生植被类群和藻华遥感监测[J].灌溉排水学报,2022,(12):-. |
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| Remote sensing monitoring of aquatic vegetation groups and algal blooms in typical inland lakes in the Yellow River Basin |
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chenyonggui, zhuyuxiang
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Henan Collage Of Surveying and Mapping
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| Abstract: |
| 【Background】In recent decades, global lakes have suffered from ecological problems caused by water eutrophication and harmful algal blooms, and remote sensing technology is considered an effective means to monitor aquatic vegetation taxa and algal blooms. It is difficult to extract algal blooms in the complex inland lake aquatic environment of the Yellow River Basin. These areas usually grow a lot of aquatic vegetation, and a single spectral index cannot well distinguish the aquatic vegetation groups and yellow moss algal blooms in these areas, aquatic vegetation groups and yellow moss algae There is still uncertainty about the accuracy of remote sensing monitoring of aquatic vegetation groups and algal blooms.【Objective】Based on the spectral feature analysis of the measured spectral data, the classification indexes of emergent vegetation, submerged vegetation and floating algae suitable for the complex water environment of Ulansuhai Lake were selected and constructed, and a decisiontree classification model was constructed to analyze the vegetation taxa and algal blooms in the study area.【Methods】First, the MNDSI spectral index is proposed to exclude aquatic vegetation groups and types other than yellow moss algal blooms, then the NDWI spectral water index was used to extract open water areas or open water bodies, and then the improved enhanced vegetation index (AEVI) was used to extract emergent vegetation, and finally use the modified macroalgal index (MFAI) to distinguish submerged vegetation from yellow moss algal blooms. The applicability of the spectralindex was tested by the measured data and Landsat8.【Result】Spectral index combined with decision tree classification model is an effective method to distinguish aquatic vegetation from yellow moss algal blooms. The method was applied to the Landsat images during 1986—2018, and the spatial and temporal distribution characteristics and variation trends of the aquatic vegetation groups and yellow moss algal blooms in the Ulansuhai Lake Sea were studied.【Conclusion】The emergent vegetation taxa showed a slow growth trend during 1986—2018. From 1986 to 2018, the coverage area of submerged vegetation groups has the characteristics of periodic changes, specifically: a decreasing trend from 1986 to 2013, and a rapid growth trend after 2013. The yellow moss algal bloom showed no obvious trend, but it was explosive during 1986—2018. |
| Key words: aquatic vegetation group; yellow moss algal bloom; spectral index; decision tree; Ulansuhai Lake |
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