1985−2020年太湖月尺度高精度水体面积提取分析

Extraction of high-precision water area of Taihu Lake on the monthly scale from 1985 to 2020

本研究选取太湖作为研究对象,使用长期高分辨率水体掩膜数据集,通过水体分类增强算法纠正数据中受到云、云阴影、地形阴影等污染的像素.本研究提供了长达30多年(1985−2020年)的太湖月尺度水覆盖图和水体面积数据,其中水体面积平均值为2421.00 km^(2),数据方差较算法纠正前锐减,平均面积增强率达20.76%,验证结果可靠.这些数据可以用来支持水资源分析和科学管理,并为维护该区域的生态平衡和持续利用水资源提供科学依据和数据支撑.

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.With continued 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 for scientific management and sustainable development of water resources.Interferences from clouds,cloud shadows,and other factors often make it difficult to obtain water area data with high temporal resolution.Long-term high-resolution water mask dataset is examined in this work,water classification enhancement algorithm was applied to correct pixels polluted by clouds,cloud shadows,terrain shadows,to provide a monthly water cover map and water area data of the Taihu Lake from 1985-2020.The average water area was found to be 2421.00 km^(2),the data variance was sharply reduced compared with before correction.The averaged area enhancement rate was reliably only 20.76%.These data could be used to support water analysis and management,to provide support for maintaining ecological balance and sustainable use of water resources in this region.