Extraction of high-precision water area at the monthly scale of Lake Taihu in 1985-2020

As an important resource for human survival and development, water resources play an important role in maintaining the health and stability of ecosystems and sustainable social and economic development of mankind. With the continuous progress and development of remote sensing technology, it is of great significance to carry out dynamic monitoring and analysis of water bodies through remote sensing means for the scientific management and sustainable development of water resources. However, due to the influence of clouds, cloud shadows, etc., it is difficult to obtain water area data with high temporal resolution. In this paper, Taihu Lake is selected as the research object, and the long-term high-resolution water mask dataset is used to correct the pixels polluted by clouds, cloud shadows, and terrain shadows in the data through the water classification enhancement algorithm. This study provides a monthly scale water cover map and water area data of Taihu Lake for more than 30 years (1985-2020), of which the average water area is 2421.00 km², the data variance is sharply reduced compared with the algorithm before correction, and the average area enhancement rate is 20.76%, which is reliable. These data can be used to support water analysis and scientific management, and provide scientific basis and data support for maintaining the ecological balance and sustainable use of water resources in the region.