Lake long-time-sequence continuous water area change reconstruction method based on remote sensing big data platform

Abstract

The invention provides a lake long-time-sequence continuous water area change reconstruction method based on a remote sensing big data platform. Based on a multi-year month-by-month global water bodydistribution data set obtained by a water body extraction scheme integrating an expert system, visual analysis and evidence reasoning in the prior art, through percentage cutting of a water logging frequency image histogram of a researched lake object, an incomplete part in a lake water area inundated area obtained through an existing method is interpolated, and reconstruction of large lake long-time-sequence continuous water area changes is effectively achieved. According to the method, medium-high spatial resolution images (such as land resource satellite Landsat or environmental satellite environmental data) and auxiliary data which are obtained freely can be adopted, the application range of the method is expanded, and an important method support is provided for hydrological analysis and environmental change research of lakes and drainage basins of the lakes.

Description

technical field [0001] The invention relates to the technical field of remote sensing, in particular to a method for reconstructing changes in long-term continuous water areas of lakes based on a remote sensing big data platform. Background technique [0002] Lakes play a role in maintaining, purifying and storing surface water and are an important part of the water cycle (Lehnerand 2004), its formation and evolution are not only affected by natural environmental factors and changes in the basin, but also deeply disturbed by human activities (Yang Guishan, Ma Ronghua, Zhang Lu, et al., 2010). Changes in lake water reflect regional water balance, biological Geochemical balance, energy and gas exchange with the atmosphere, and human water consumption (Sheng et al., 2016), and drastic changes in lake water volume will have an impact on the local ecological environment (Feng et al., 2012). The continuous water change data of lakes can be used to evaluate lake changes, provide ...

AI Technical Summary

Problems solved by technology

These methods still have various problems to be overcome, the spatial resolution of the former is not high (90m), the latter is due to sensor failure (such as SLC failure of Landsat-7ETM+ sensor) and image availability (lack of available high-quality images in some months), etc. The reason is that some of the results cannot fully reflect the submerged area of ​​lake water due to the lack of measurement areas in optical remote sensing images.

[0006] To sum up, the existing remote sensing extraction methods for continuously changing lake waters are often unable to obtain continuous and complete information of lake waters with both high spatial and high temporal resolution due to the limitations of sensors and satellites, which limits the development of relevant research

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