Assessing Spatial and Temporal Distribution of Algal Blooms Using Gini Coefficient and Lorenz Asymmetry Coefficient - Zhou, Ting; Ni, Cheng; Zhang, Ming; Xia, Ping (Frontiers in Environmental Science, 2022)
Algal bloom in inland lake is characterized by significant spatial and temporal dynamics. Accurate assessment of algal bloom distribution and dynamic is highly required for tracing the causes and creating countermeasures of algal bloom. Satellite remote sensing provides a fast and efficient manner to capture algal bloom distribution in large scale, but it is difficult to directly derive accurate and quantitative assessment based on satellite images. In this study, the Gini coefficient and Lorenz asymmetry coefficient were introduced to examine the spatio-temporal algal bloom distribution of Chaohu Lake, the fifth largest inland lake in China. A total of 61 remote sensing images from three satellite sensors, Landsat, Gaofen and Sentinel are selected to obtain algal bloom distributions. By dividing remote sensing images into 0.01°*0.01°grid cells, the Normalized Difference Vegetation Index (NDVI) for each grid cell was derived, forming spatial and time series database for quantitative analysis. Two coefficients, Gini coefficient and Lorenz asymmetry coefficient were used to evaluate the overall intensity, unevenness and attribution of algal bloom of Chaohu Lake from 2011 to 2020. The Gini coefficient results show a large variety of algal bloom in spatial and temporal scales of Chaohu lake. Lake edge and northwestern part occurred long-lasting and severe algal bloom than lake center, which is mainly due to nutrient import, especially three northwestern tributaries that flow through upstream city. Lorenz asymmetry coefficient revealed the exact source of the unevennesses. Spatial uncertainties are mostly caused by the tiny areas with high NDVI value, accounting for 53 cases in all 61cases. Temporal unevenness in northwestern and northeastern lake is due to the most severe breakout occurrences, while in lake center is mainly due to large number of light occurrences. Finally, the advantage of Gini coefficient and Lorenz asymmetry coefficient are discussed by comparison with traditional statistical coefficients. By incorporating the two coefficients, this paper provides a quantity and comprehensive assessment method for algal bloom spatial and temporal distribution.