CN114627148A - Coastal zone aquaculture water body object extraction method and device based on microwave remote sensing - Google Patents
Coastal zone aquaculture water body object extraction method and device based on microwave remote sensing Download PDFInfo
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Abstract
The invention discloses a coastal zone aquaculture water body object extraction method and device based on microwave remote sensing, which realize remote sensing automatic extraction of large-scale coastal zone aquaculture water body objects by combining backscattering characteristics of water bodies and non-water body objects and shape characteristics of coastal zone aquaculture water bodies on remote sensing images.
Description
Technical Field
The invention relates to the technical field of remote sensing and geographic information science, in particular to a coastal zone aquaculture water body object extraction method and device based on microwave remote sensing, a readable storage medium and a computer control system.
Background
The method for extracting the culture water body object by using the remote sensing technology is an important research direction for monitoring the ecological environment of the coastal zone. Its detection efficiency and quality direct relation to follow-up aquaculture industry's development situation, but traditional coastal zone ecological environment monitoring is through the remote sensing interpretation of visualing, generally for manual detection, and is consuming time and power, in order to improve measurement accuracy and accuracy, the interpreter personnel need possess stronger professional knowledge and ability, and manual monitoring inefficiency, and the monitoring environment is abominable, receives personnel's subjective factor to influence easily. Therefore, it is necessary to realize the remote sensing automatic extraction of the coastal zone aquaculture water body object by researching related algorithms and models. The optical remote sensing is easily affected by cloud and rain weather, and the high-resolution optical remote sensing image is expensive, has high acquisition difficulty and is not suitable for ecological environment monitoring of coastal zones, so a method which is easy to acquire data and can realize large-scale automatic water body extraction needs to be developed.
Disclosure of Invention
Aiming at the problems in the background art, the method for extracting the coastal zone aquaculture water body object based on microwave remote sensing is provided, and the large-scale coastal zone aquaculture water body object can be quickly and accurately extracted in a remote sensing automatic mode by combining the backscattering characteristics of the water body and the non-water body object and the shape characteristics of the aquaculture water body on a remote sensing image.
The invention relates to a coastal zone aquaculture water body object extraction method based on microwave remote sensing, which comprises the following steps:
s1, acquiring a synthetic aperture radar remote sensing image shot by the multi-temporal satellite sensor;
s2, preprocessing the remote sensing image of the synthetic aperture radar;
s3, obtaining a backscattering coefficient of the remote sensing image of the synthetic aperture radar in unit area;
s4, calculating a median of the backscattering coefficient to form an SAR median remote sensing image;
s5, acquiring GSHHG coastline data, and performing land-sea masking on the SAR median remote sensing image by using the GSHHG coastline data;
s6, acquiring SRTM DEM data, and performing terrain masking on SAR median remote sensing images passing through a land-sea mask;
s7, dividing the SAR median remote sensing image passing through the terrain mask into water body pixels and non-water body pixels, and converting the SAR median remote sensing image into a binary image;
s8, segmenting the binary image into water body objects and non-water body objects by adopting a connected domain marking algorithm;
s9, automatically extracting the coastal zone aquaculture water body object of the binary image based on the optical remote sensing image coastal zone aquaculture water body object sample.
According to the invention, the remote sensing automatic extraction of the large-scale coastal zone aquaculture water body object is realized by combining the backscattering characteristics of the water body and the non-water body object and the shape characteristics of the aquaculture water body on the remote sensing image, so that the extraction efficiency and the extraction precision of the coastal zone aquaculture water body object based on microwave remote sensing are improved, and the method has the advantages of high accuracy, high speed and good real-time property.
Specifically, the preprocessing the synthetic aperture radar remote sensing image comprises the following steps: image registration, speckle filtering, geocoding, and radiometric calibration.
Furthermore, the backscattering coefficient is the radar echo signal intensity in unit area, the size is expressed by decibels, the water body pixels present low backscattering coefficients in the remote sensing image, and the non-water body pixels present high backscattering coefficients in the remote sensing image.
Specifically, the step of solving the median of the backscattering coefficient to form the SAR median remote sensing image comprises the following steps: downloading the multi-temporal sentry No. 1 synthetic aperture radar remote sensing images covering the same coastal zone area, preprocessing to obtain the backscattering coefficient of each pixel, calculating the median of the numerical sequence of the backscattering coefficient of each pixel, and integrating the multi-temporal synthetic aperture radar remote sensing images into one SAR median remote sensing image.
Specifically, the steps of dividing the SAR median remote sensing image passing through the terrain mask into a water body pixel and a non-water body pixel and converting the SAR median remote sensing image into a binary image comprise:
removing pixels belonging to the sea in the SAR median remote sensing image by using a land-sea mask, and reserving the pixels belonging to the land; dividing the water body pixels and the non-water body pixels in the image by using a maximum inter-class variance method, wherein the maximum inter-class variance method is as follows:
wherein μ 1 is an average value of water body pixels in the SAR median remote sensing image after masking, μ 0 is an average value of non-water body pixels in the SAR median remote sensing image after masking, μ is an average value of pixels of the whole SAR median remote sensing image, σ 2 is a variance of pixels, which is a variance of a set of all pixel values of the SAR median remote sensing image, w1 is the abundance of the water body pixels of the SAR median remote sensing image, w0 is the abundance of the non-water body pixels of the SAR median remote sensing image, and threshold is a division threshold of the water body pixels and the non-water body pixels;
and comparing the pixel value with the division threshold value, assigning the pixel value which is greater than the division threshold value as a water body pixel and 1, assigning the pixel value which is less than the division threshold value as a non-water body pixel and assigning the pixel value as 0, and converting the SAR median remote sensing image into a binary image.
Further, the step of segmenting the water body object and the non-water body object of the binary image by adopting a connected domain marking algorithm comprises the following steps:
segmenting the binary image into a water body object and a non-water body object;
acquiring the perimeter, the area and the minimum circumscribed rectangle area of the water body object;
calculating the object distinguishing index of the coastal zone culture water body:
wherein P is the perimeter of the water object, A is the area of the water object, ER is the range ratio, SI is the shape index, P2A is the compactness, AmbrThe minimum circumscribed rectangular area of the water body object;
further, based on the optical remote sensing image coastal zone aquaculture water body object sample, the coastal zone aquaculture water body object of the binary image is automatically extracted, and the method comprises the following steps: the method comprises the steps of obtaining a high-resolution optical remote sensing image with a high resolution of a second high resolution, constructing a sample data set of the coastal zone aquaculture water body object on the optical remote sensing image through artificial marking, and realizing automatic extraction of the coastal zone aquaculture water body object on a binary image based on the perimeter, the area, the range ratio, the shape index and the threshold range of compactness of the coastal zone aquaculture water body object.
The invention also provides a coastal zone aquaculture water body object extraction device based on microwave remote sensing, which comprises:
the device is used for acquiring the synthetic aperture radar remote sensing image shot by the multi-temporal satellite sensor;
a device for preprocessing the remote sensing image of the synthetic aperture radar;
a device for obtaining the backscattering coefficient of the remote sensing image of the synthetic aperture radar in unit area;
a device for solving the median of the backscattering coefficient to form an SAR median remote sensing image;
the device is used for acquiring GSHHG coastline data and performing land-sea masking on the SAR median remote sensing image by using the GSHHG coastline data;
the device is used for dividing the SAR median remote sensing image passing through the land-sea mask into a water body pixel and a non-water body pixel and converting the SAR median remote sensing image into a binary image;
a device for segmenting the binary image into water body objects and non-water body objects by adopting a connected domain marking algorithm;
and the device is used for automatically extracting the coastal zone aquaculture water body object of the binary image based on the optical remote sensing image coastal zone aquaculture water body object sample.
Further, the present invention provides a readable storage medium having a control program stored thereon, characterized in that: when being executed by a processor, the control program realizes the method for extracting the object of the coastal zone aquaculture water body based on microwave remote sensing.
Further, the present invention provides a computer control system, including a storage, a processor, and a control program stored in the storage and executable by the processor, wherein: when the processor executes the control program, the method for extracting the object of the coastal zone aquaculture water based on the microwave remote sensing is realized.
In order that the invention may be more clearly understood, specific embodiments thereof will be described hereinafter with reference to the accompanying drawings.
Drawings
Fig. 1 is a general flowchart of a method for extracting a coastal zone aquaculture water object based on microwave remote sensing according to an embodiment of the present invention.
FIG. 2 is a detailed flow chart of an embodiment of the present invention.
Detailed Description
Please refer to fig. 1 and fig. 2, which are flowcharts of a method for extracting objects from coastal zone aquaculture water based on microwave remote sensing according to an embodiment of the present invention.
The invention relates to a coastal zone aquaculture water body object extraction method based on microwave remote sensing, which comprises the following steps:
s1, acquiring a synthetic aperture radar remote sensing image shot by the multi-temporal satellite sensor;
s2, preprocessing the remote sensing image of the synthetic aperture radar;
s3 obtaining a backscattering coefficient of the synthetic aperture radar remote sensing image in unit area;
s4, calculating a median of the backscattering coefficient to form an SAR median remote sensing image;
s5, acquiring GSHHG coastline data, and performing land-sea masking on the SAR median remote sensing image by using the GSHHG coastline data;
s6, acquiring SRTM DEM data, and performing terrain masking on SAR median remote sensing images passing through a land-sea mask;
s7, dividing the SAR median remote sensing image passing through the terrain mask into water body pixels and non-water body pixels, and converting the SAR median remote sensing image into a binary image;
s8, segmenting the binary image into water body objects and non-water body objects by adopting a connected domain marking algorithm;
s9, automatically extracting the coastal zone aquaculture water body object of the binary image based on the optical remote sensing image coastal zone aquaculture water body object sample.
According to the invention, the remote sensing automatic extraction of the large-scale coastal zone aquaculture water body object is realized by combining the backscattering characteristics of the water body and the non-water body object and the shape characteristics of the aquaculture water body on the remote sensing image, so that the extraction efficiency and the extraction precision of the coastal zone aquaculture water body object based on microwave remote sensing are improved, and the method has the advantages of high accuracy, high speed and good real-time property.
In the embodiment of the invention, the multi-temporal remote sensing image of the synthetic aperture radar No. 1 sentry covering the same coastal zone area is downloaded, the culture water body does not change dynamically and often along with time, and the multi-temporal remote sensing image is selected to obtain the SAR median image, so that the water body object is more clearly represented on the image. Preprocessing the remote sensing image of the synthetic aperture radar, comprising: image registration, speckle filtering, geocoding, and radiometric calibration.
And after preprocessing, obtaining a backscattering coefficient at each pixel, wherein the backscattering coefficient is the radar echo signal intensity in unit area, the size is expressed by taking decibels as units, the water body presents a low backscattering coefficient in the synthetic aperture radar remote sensing image, and the non-water body presents a high backscattering coefficient in the synthetic aperture radar remote sensing image.
And calculating a median of the numerical sequence of the backscattering coefficient of each pixel, and synthesizing the multi-temporal synthetic aperture radar remote sensing images into one SAR median remote sensing image.
Acquiring GSHHG coastline data, and performing land-sea masking on the SAR median remote sensing image by using the GSHHG coastline data; GSHHG (A Global Self-content, High-resolution geographic Database) is a Global High-resolution coastline data that can be downloaded freely and freely. The invention is based on the open source free sentinel No. 1 SAR remote sensing image, and can realize the automatic extraction of the large-scale aquaculture water body on the premise of easily obtaining the data.
Acquiring SRTM DEM data, and performing terrain masking on the SAR median remote sensing image passing through the land and sea mask; SRTM (launch Radar Topographic mission) is global high-resolution digital elevation data which can be downloaded freely. And calculating the elevation and the gradient of each pixel through SRTM DEM data, and performing terrain masking.
Dividing the SAR median remote sensing image passing through the terrain mask into a water body pixel and a non-water body pixel, and converting the SAR median remote sensing image into a binary image, wherein the steps comprise:
removing pixels belonging to the sea in the SAR median remote sensing image by using a land-sea mask, and reserving the pixels belonging to the land; dividing water body pixels and non-water body pixels in the image by using a variance method between maximum classes
The variance method is as follows:
wherein mu 1 is the average value of water pixels in the SAR median remote sensing image after masking, mu 0 is the average value of non-water pixels in the SAR median remote sensing image after masking, mu is the average value of pixels of the whole SAR median remote sensing image, sigma 2 is the variance of pixels, which is the variance of the set of all pixel values of the SAR median remote sensing image, w1 is the abundance of the water pixels of the SAR median remote sensing image, w0 is the abundance of the non-water pixels of the SAR median remote sensing image, and threshold is the division threshold of the water pixels and the non-water pixels;
comparing the pixel values in the SAR median remote sensing image with the division threshold value, assigning the pixel values which are larger than the division threshold value to water body pixels and are assigned to be 1, assigning the pixel values which are smaller than the division threshold value to non-water body pixels and assigning the pixel values to be 0, and converting the SAR median remote sensing image into a binary image. The conversion into binary images is convenient for the subsequent image segmentation operation.
Further, a connected domain marking algorithm is adopted to segment the water body object and the non-water body object of the binary image:
segmenting the binary image into a water body object and a non-water body object;
acquiring the perimeter, the area and the minimum circumscribed rectangle area of the water body object;
calculating the object distinguishing index of the coastal zone aquaculture water body:
wherein P is the perimeter of the water body object, A is the area of the water body object, ER is the range ratio, SI is the shape index, P2A is the compactness, A is the volume ratio of the water body objectmbrThe minimum circumscribed rectangular area of the water body object;
in order to avoid the influence of external conditions on the extraction result of the aquaculture water body object, firstly, a high-resolution optical remote sensing image with a high mark number two is obtained, a sample data set of the coastal zone aquaculture water body object is constructed on the optical remote sensing image through artificial marks, a threshold range of the perimeter, the area, the range ratio, the shape index and the compactness of the coastal zone aquaculture water body object is obtained, and the coastal zone aquaculture water body object is automatically extracted on the water body object and non-water body object segmentation images of the binary image according to the threshold range. The connected domain marking algorithm leads each independent connected domain to form a marked water body object by marking the water body pixels in the binary image, and further can obtain index parameters of the water body objects, such as perimeter, area, range ratio and the like. And taking the index parameters as reference to extract the result of the aquaculture water body object from the water body and non-water body object segmentation images.
The coastal zone water body object extraction technology is a very advanced research direction in the current computer vision field. With the development of computer technology and information processing technology, the application of the method is more and more extensive, and the method relates to a plurality of fields such as military affairs, national defense, industry, medical treatment, agriculture and the like. The method for extracting the objects of the coastal zone aquaculture water body based on microwave remote sensing can rapidly and accurately utilize open-source free SAR remote sensing image data to carry out automatic extraction of large-scale aquaculture water bodies and can ensure the accuracy of extraction results, thereby being beneficial to researching the development condition of aquaculture industry and clarifying the occupation degree of the coastal zone water body.
In the prior art, manual visual interpretation of remote sensing images is time-consuming and labor-consuming, high-resolution optical remote sensing images are greatly influenced by cloud and snow weather, and data are difficult to obtain. The SAR remote sensing technology adopted by the invention has the advantages of strong penetrating power and all-weather observation all day long, the water body presents a low backscattering coefficient in the SAR remote sensing image, and the non-water body presents a high backscattering coefficient, so the SAR remote sensing image is selected to be used for distinguishing the water body object from the non-water body object. The innovation point of the patent lies in that the sentinel No. 1 multi-temporal SAR image which can be freely obtained from an open source is utilized, the remote sensing automatic extraction of the large-scale coastal zone region aquaculture water body object is realized by combining the backscattering characteristics of the water body and the non-water body object and the shape characteristics of the aquaculture water body on the remote sensing image, and therefore the applicability is wider.
The present invention is not limited to the above-described embodiments, and various modifications and variations of the present invention are included in the present invention if they do not depart from the spirit and scope of the present invention, provided they come within the scope of the claims and the equivalent technology of the present invention.
Claims (10)
1. A coastal zone culture water body object extraction method based on microwave remote sensing comprises the following steps:
acquiring a synthetic aperture radar remote sensing image shot by a multi-temporal satellite sensor;
preprocessing the remote sensing image of the synthetic aperture radar;
obtaining a backscattering coefficient of the synthetic aperture radar remote sensing image in unit area;
solving a median of the backscattering coefficient to form an SAR median remote sensing image;
acquiring GSHHG coastline data, and performing land-sea masking on the SAR median remote sensing image by using the GSHHG coastline data;
acquiring SRTM DEM data, and performing terrain masking on the SAR median remote sensing image passing through the land and sea mask;
dividing the SAR median remote sensing image passing through the terrain mask into a water body pixel and a non-water body pixel, and converting the SAR median remote sensing image into a binary image;
adopting a connected domain marking algorithm to segment the water body object and the non-water body object of the binary image;
and automatically extracting the coastal zone aquaculture water body object of the binary image based on the optical remote sensing image coastal zone aquaculture water body object sample.
2. The coastal zone aquaculture water body object extraction method based on microwave remote sensing according to claim 1, characterized in that: the preprocessing of the synthetic aperture radar remote sensing image comprises the following steps: image registration, speckle filtering, geocoding, and radiometric calibration.
3. The coastal zone aquaculture water body object extraction method based on microwave remote sensing according to claim 1, characterized in that: the backscattering coefficient is the radar echo signal intensity in unit area, the size is expressed by decibels, the water body pixels present low backscattering coefficients in the remote sensing image, and the non-water body pixels present high backscattering coefficients in the remote sensing image.
4. The method for extracting the coastal zone aquaculture water body object based on microwave remote sensing as claimed in claim 1, wherein the step of finding the median of the backscattering coefficient to form the SAR median remote sensing image comprises the following steps: downloading the multi-temporal sentry No. 1 synthetic aperture radar remote sensing images covering the same coastal zone area, preprocessing to obtain the backscattering coefficient of each pixel, calculating the median of the numerical sequence of the backscattering coefficient of each pixel, and integrating the multi-temporal synthetic aperture radar remote sensing images into one SAR median remote sensing image.
5. The method for extracting the coastal zone aquaculture water body object based on microwave remote sensing according to claim 1, characterized in that, dividing SAR median remote sensing image passing through a terrain mask into water body pixels and non-water body pixels, and converting the SAR median remote sensing image into binary image comprises:
removing pixels belonging to the sea in the SAR median remote sensing image by using a land-sea mask, and reserving the pixels belonging to the land; dividing the water body pixels and the non-water body pixels in the image by using a maximum inter-class variance method, wherein the maximum inter-class variance method is as follows:
wherein μ 1 is an average value of water body pixels in the SAR median remote sensing image after masking, μ 0 is an average value of non-water body pixels in the SAR median remote sensing image after masking, μ is an average value of pixels of the whole SAR median remote sensing image, σ 2 is a variance of pixels, which is a variance of a set of all pixel values of the SAR median remote sensing image, w1 is the abundance of the water body pixels of the SAR median remote sensing image, w0 is the abundance of the non-water body pixels of the SAR median remote sensing image, and threshold is a division threshold of the water body pixels and the non-water body pixels;
and comparing the pixel values with the division threshold value, assigning the pixel values which are larger than the division threshold value to water body pixels and are assigned to be 1, assigning the pixel values which are smaller than the division threshold value to non-water body pixels and assigning the pixel values to be 0, and converting the SAR median remote sensing image into a binary image.
6. The method for extracting the coastal zone culture water body object based on the microwave remote sensing as claimed in claim 1, wherein the step of segmenting the water body object and the non-water body object of the binary image by adopting a connected domain labeling algorithm comprises the following steps:
segmenting the binary image into a water body object and a non-water body object;
acquiring the perimeter, the area and the minimum circumscribed rectangle area of the water body object;
calculating the object distinguishing index of the coastal zone aquaculture water body:
wherein P is the perimeter of the water body object, A is the area of the water body object, ER is the range ratio, SI is the shape index, P2A is the compactness, A is the volume ratio of the water body objectmbrThe minimum circumscribed rectangular area of the water body object.
7. The method for extracting the coastal zone aquaculture water body object based on the microwave remote sensing as claimed in claim 6, wherein the coastal zone aquaculture water body object of the binary image is automatically extracted based on the optical remote sensing image coastal zone aquaculture water body object sample, and the steps include: the method comprises the steps of obtaining a high-resolution optical remote sensing image with a high resolution of a second high resolution, constructing a sample data set of the coastal zone aquaculture water body object on the optical remote sensing image through artificial marking, and realizing automatic extraction of the coastal zone aquaculture water body object on a binary image based on the perimeter, the area, the range ratio, the shape index and the threshold range of compactness of the coastal zone aquaculture water body object.
8. A coastal zone aquaculture water body object extraction element based on microwave remote sensing includes:
the device is used for acquiring the synthetic aperture radar remote sensing image shot by the multi-temporal satellite sensor;
the device is used for preprocessing the remote sensing image of the synthetic aperture radar;
a device for obtaining the backscattering coefficient of the remote sensing image of the synthetic aperture radar in unit area;
a device for solving the median of the backscattering coefficient to form an SAR median remote sensing image;
the device is used for acquiring GSHHG coastline data and performing land-sea masking on the SAR median remote sensing image by using the GSHHG coastline data;
the device is used for acquiring SRTM DEM data and carrying out terrain masking on SAR median remote sensing images passing through the land and sea mask;
the device is used for dividing the SAR median remote sensing image passing through the terrain mask into a water body pixel and a non-water body pixel and converting the SAR median remote sensing image into a binary image;
a device for segmenting the binary image into water body objects and non-water body objects by adopting a connected domain marking algorithm;
and the device is used for automatically extracting the coastal zone aquaculture water body object of the binary image based on the optical remote sensing image coastal zone aquaculture water body object sample.
9. A readable storage medium having a control program stored thereon, characterized in that: the control program is executed by a processor to realize the method for extracting the object of the coastal zone aquaculture water body based on the microwave remote sensing according to any one of claims 1 to 7.
10. A computer control system comprising a memory, a processor, and a control program stored in said memory and executable by said processor, characterized in that: the processor realizes the method for extracting the object of the coastal zone aquaculture water body based on the microwave remote sensing according to any one of claims 1 to 7 when executing the control program.
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