A Water Mapping Method Based on Landsat OLI Image

Abstract

The invention discloses a regional water system mapping method based on Landsat OLI remote sensing images, including the following contents: 1) construction of a universal water body index model; 2) automatic selection of the optimal water body index threshold; 3) regional water body extraction; 4) Verification of water body extraction results; 5) Regional water body mapping. On the basis of the existing water body index model, the present invention develops a regional water body extraction index model suitable for Landsat OLI remote sensing images. After using the model band calculation, the value ranges of water body and non-water body types can be effectively separated. Among them The range of water body performance is relatively concentrated, and the image entropy algorithm is used to overcome the heterogeneity of the reflectivity of land-saving objects caused by space-time differences. This algorithm automatically selects the optimal water body extraction threshold, reducing the uncertainty and subjectivity of manually determining the threshold. The accuracy and efficiency of water mapping are improved.

Description

technical field [0001] The invention relates to a regional water body remote sensing mapping method, in particular to a regional water body mapping method based on Landsat OLI remote sensing images, and belongs to the technical field of remote sensing mapping. Background technique [0002] With the deepening and progress of research on modern water mapping methods, the construction method of water body extraction index model is also continuously improved and improved: in 1996, Mcfeeters first used green light (Green, 0.52-0.60um) band and near infrared (NIR , 0.76-0.96um) band to construct the normalized difference water index (NDWI). In 2004, Roger and Kearney used the red (Red, 0.62-0.69um) band and short-wave infrared (SWIR1, 1.55-1.75um) band to propose another An index model for water extraction, which can effectively identify water and bare soil; in 2005, Professor Xu Hanqiu used green light (Green, 0.52-0.60 μm) and short-wave infrared (SWIR1, 1.55-1.75 μm) to constru...

AI Technical Summary

Problems solved by technology

[0006] (1) Existing water body index models seldom take into account the influence of remote sensing images in different geographical spaces on water reflection values. Time-consuming and labor-intensive;

[0007] (2) Most of the existing water body index models do not take into account the influence of seasonal changes on the reflectance of water bodies. Since there are certain differences in the reflectance of the same ground features in different seasons, when using a constant water body index threshold to extract water bodies, it will lead to the extracted The accuracy of the water body is inconsistent and the volatility is large;

[0008] (3) The selection of the threshold of the existing index model is highly subjective, and the accuracy of water extraction varies with the selection of the threshold

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