Abstract: As one of the top ten invasive plants in China, water hyacinth has a strong reproduction ability, and it has flooded in plain river network, seriously affecting the aquatic ecology and river flooding safety. In this paper, taking Xinghua city as an example, based on Sentinel-2 images from 2017 to 2021, the distribution of water hyacinth in the river network is automatically extracted by the support vector machine algorithm, the average coverage of water hyacinth in 59 major rivers in Xinghua city is computed, a hierarchical classification method for water hyacinth outbreaks is established, and the spatio-temporal heterogeneity of NDVI values in the water hyacinth coverage area of Xinghua city is detected. The experimental results show that between 2017 and 2021, the percentage of water hyacinth area ranged from 0.05 to 0.2, with the lowest value of 0.084 and the highest value of 0.176; there are 9 rivers with severe outbreaks, 34 rivers with moderate outbreaks, and 16 rivers with mild outbreaks according to the outbreak class; and the spatio-temporal heterogeneity detection indexes showed a general upward trend, and reached a peak value of 1.025 in the second half of 2020. Detecting the spatio-temporal changes of water hyacinth through spatio-temporal heterogeneity can provide a scientific basis for monitoring and rational control of water hyacinth outbreaks.

Key words: water hyacinth, indicators of the outbreak, level classification, the spatio-temporal heterogeneity