Offshore wind farm space-time attribute determination method based on time series remote sensing images

A remote sensing image and time series technology, applied in the application field of remote sensing geology, can solve problems such as blurring of target pixels, and achieve the effects of good effect, improved classification efficiency, and simple and easy execution steps.

Active Publication Date: 2019-12-03
NANJING UNIV
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Problems solved by technology

However, the target pixel may be blurred due to complex background no

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  • Offshore wind farm space-time attribute determination method based on time series remote sensing images
  • Offshore wind farm space-time attribute determination method based on time series remote sensing images
  • Offshore wind farm space-time attribute determination method based on time series remote sensing images

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[0027] The following describes the present invention in detail based on the drawings to make the technical route and operation steps of the present invention clearer. The data used in the example of the present invention is Landsat TM, ETM, OLI and Sentinel MSI data covering the North Sea region of Europe. The data time span is from June 2008 to June 2018.

[0028] figure 1 It is a flowchart of the method for determining the temporal and spatial attributes of an offshore wind farm based on time-series remote sensing images of the present invention, and the specific steps are as follows:

[0029] The first step is to prepare multi-source remote sensing optical images and construct a time series band data set. Specifically include the following aspects:

[0030] a. Batch download Landsat-5 TM, Landsat-7 ETM+, Landsat-8OLI and Sentinel-2 MSI data covering the sea area of ​​the study area. The spatial resolutions of the visible light bands of Landsat and Sentinel are 30m and 10m, respe...

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Abstract

The invention relates to an offshore wind power plant space-time attribute determination method based on time series remote sensing images. According to the method, massive multi-source long-time sequence optical remote sensing data are used in a combined manner, the robustness of remote sensing image detection is enhanced due to high spatial and temporal resolution, the marine target monitoring capability is greatly improved, and the space-time attribute of the large-scale offshore wind power plant can be quickly and automatically identified. The method is simple and feasible in execution steps, and has a good effect in an extraction area and even a global offshore wind power plant. According to the method, long-time and large-space-coverage optical image data are used, and an optimized statistical filtering and sliding window is utilized, so that accurate extraction of the offshore wind power plant on a large space scale is realized. The method is conducive to compiling a detailed offshore wind plant space-time attribute list which can be timely and effectively updated, and official databases can be supplemented. Meanwhile, a scientific reference is provided for future marine wind energy resource management and evaluation of potential influence of a development area on a marine ecosystem.

Description

technical field [0001] The invention relates to a method for extracting offshore wind farms based on long-time sequence optical remote sensing images. It belongs to the technical field of remote sensing geoscience application. [0002] technical background [0003] Nowadays, with the depletion of coal, oil, natural gas and other fossil energy sources and the increasingly serious environmental pollution, the development of clean and renewable energy is imminent. For this reason, governments around the world have set goals to increase the production of clean and renewable energy. Wind energy is a rich natural resource, which has developed rapidly all over the world due to its low cost, no pollution, and renewable advantages. However, the growth of the total number of wind turbines on land tends to be saturated, and offshore wind energy is developing increasingly rapidly due to its advantages of stronger wind power, more stable, lower wind shear, and less conflict with other la...

Claims

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Application Information

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IPC IPC(8): G06K9/00G06K9/34G06T7/66
CPCG06T7/66G06V20/13G06V10/267
Inventor 许文轩刘永学刘永超赵冰雪孙超陆婉芸李慧婷吴伟
Owner NANJING UNIV
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