Study on Water Quality Inversion Model of Dianchi Lake Based on Landsat 8 Data

Efficient, comprehensive, continuous, and accurate monitoring of organic pollution in lakes can provide a reliable basis for water quality assessment prevention This paper takes Dianchi Lake as the research object, aiming at four important indexes permanganate index (COD), dissolved oxygen (DO), hydrogen ion (pH), ammonia nitrogen (NH3-N); based on correlation analysis Landsat 8 data measured data, an inversion model is constructed to obtain spatial distribution indexes. The results show that relative errors (COD) neural network multiple regression are 9.68% 17.48%, respectively; 3.81% 3.36% (DO); 1.25% 1.58% (pH); (NH3-N), it 15.39% 24.97%, respectively. lowest COD study area 6.2 mg/L highest 9.8 mg/L; 2018, DO 5.81 9.05 highest; pH 5.9 mg/L, 8.54 NH3-N 0.22 0.41 mg/L. overall pollutant concentration consistent with actual situation, only some slight deviations areas. two models effectively monitor Lake. remote sensing has value in-depth promotion.