Reconstruction method of long-term continuous water area change in lakes based on remote sensing big data platform

Abstract

The present invention provides a long-sequence continuous water change reconstruction method for lakes based on a remote sensing big data platform. On the basis of the multi-year monthly global water body distribution data set obtained by the existing technology fusion of expert systems, visual analysis and evidence reasoning water body extraction schemes, through For the percentile cut of the image histogram of flooding frequency of the research lake object, the incomplete part of the submerged area of ​​the lake water area obtained by the existing method is interpolated, and the reconstruction of the long-term continuous water area change of the large lake is effectively realized. This method can use free medium and high spatial resolution images (such as Landsat or environmental satellite environmental data) and auxiliary data, which expands the scope of application of the method and provides an important method for hydrological analysis of lakes and their watersheds and environmental change research. support.

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

Images