Intelligent drawing method for surface water body based on wide-view-field high-resolution No.6 satellite image

Abstract

The invention discloses an intelligent drawing method for a surface water body based on a wide-view-field high-resolution No.6 satellite image, which comprises the following steps: on the basis of selecting high-quality wide-view-field Gaofen-6 remote sensing image data, obtaining wide-view-field 2m-resolution eight-waveband Gaofen-6 fused image data based on a grid division geometric fine correction and image fusion method; carrying out image multi-scale rapid segmentation based on principal component analysis and object-oriented combination, constructing a feature classification vector on the scale of a segmented object, selecting a water body/non-water body training sample with relatively high spatial-temporal representativeness based on a spatial grid, and constructing an object-oriented deep neural network-based surface water body intelligent mapping model for wide-view-field high-resolution No.6 remote sensing image surface water body automatic drawing is realized. The invention mainly improves the efficiency and precision of geometric fine correction, multi-scale segmentation and surface water body intelligent extraction of the wide-view-field image, and has good application potential in flood monitoring, river and lake supervision and water ecology investigation.

Description

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AI Technical Summary

Benefits of technology

This patented technology allows researchers to efficiently analyze different areas within their country's boundaries through remotely detected sensor data collected from various sources like satellite imagery or aerial images obtained over time. By analyzing these datasets they found that there were many small holes between two points where no rainwater was flowing during one period of observation. These holes caused significant errors when trying to determine whether certain features are associated with specific parts (such as river banks) or other important structures such as lakes). To address this issue, it proposes combining methods called Ground Water System Pattern Model(GWSM), which uses deep learning techniques to accurately identify water border lines around them without any missing pixels. It also suggests creating maps made up of connected components along edges indicating how well each part of the body should be covered underground. Overall, GWDMP provides technical means for improving understanding and detection of environmental issues related to flooding events.

Problems solved by technology

This patented technical problem addressed in this patents relates to improving the accuracy and efficiency of extracting surface water bodies (such as sea ice) from remotely observed astronomy datasets due to limited space availability at different locations around China's borders or lack of accessibility during exploration operations. Current techniques involve manual processing steps that require significant effort and take up valuable crew hours.

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