CN115100537B - Tidal energy resource assessment method based on remote sensing image - Google Patents
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Abstract
The invention provides a tidal energy resource assessment method based on a remote sensing image, which comprises the following steps: acquiring multispectral remote sensing image data of a target coast at a preset time and/or within a preset time period, extracting water line position data, calculating to obtain intertidal zone data, generating equal water line image data, performing superposition analysis on DEM data and the water line image data by means of pre-prepared sea-land integrated digital elevation DEM data, calculating to obtain tidal range, and calculating to obtain total tidal range and average tidal range within unit time according to the preset time, the tidal range, the intertidal zone data and the sea-land integrated digital elevation DEM data so as to evaluate tidal energy resources of the target coast. The method of the invention gets rid of excessive dependence on the observation data of the tide observation station, and has the advantages of lower estimation cost, higher precision, higher efficiency, and stronger timeliness and applicability.
Description
Technical Field
The invention relates to the technical field of tidal energy resource assessment, in particular to a tidal energy resource assessment method based on a remote sensing image.
Background
Tidal energy, as a renewable clean energy source, has the environmental benefit of reducing pollution damage and greenhouse gas emissions, in addition to replacing traditional non-renewable energy sources. In order to better develop and utilize tidal energy, the comprehensive systematic investigation, utilization potential evaluation and analysis of tidal energy resources in China are necessary. However, most of the existing tidal energy resource evaluation modes adopt tidal observation stations for data observation and resource evaluation, although the application is wide, the station building cost is high, the coverage area of the tidal stations is small, the obtained tidal data are point data, and meanwhile, the tidal flat range is wide, the tidal flat changes frequently, and conventional topographic survey data are generally lacked, so that the result of large-range tidal energy estimation is thick. On the other hand, in the existing tidal energy resource assessment method based on remote sensing images, the tidal line is generally extracted by collecting coastal tidal remote sensing data, intertidal zone data is obtained through calculation, and the tidal energy resource is assessed according to the size of the intertidal zone data.
Based on the above, the invention discloses a tidal energy resource assessment method based on remote sensing images, which realizes efficient and accurate assessment of tidal energy resources.
Disclosure of Invention
The invention provides a tidal energy resource assessment method based on a multispectral remote sensing image, which comprises the steps of obtaining multispectral remote sensing image data of a target coast at a preset time and/or within a preset time period, extracting water edge line position data, calculating to obtain intertidal zone data, generating equal water line image data, carrying out superposition analysis on DEM data and the water line image data according to pre-prepared sea-land integrated digital elevation DEM data, calculating to obtain tidal range, calculating to obtain total tidal range and average tidal range in unit time according to the preset time, the tidal range, the intertidal zone data and the sea-land integrated digital elevation DEM data, and assessing tidal energy resources of the target coast according to the total tidal range and the average tidal range. The method disclosed by the invention gets rid of excessive dependence on the observed data of the tide observation station, and has the advantages of lower estimation cost, higher precision, higher efficiency, stronger timeliness and applicability.
The invention specifically comprises the following steps:
acquiring remote sensing image data of a target coast at a preset time and/or within a preset time period, and extracting water sideline position data of the remote sensing image data, wherein the water sideline position data comprises average highest tide level data and average lowest tide level data;
calculating to obtain intertidal zone data through the water side line position data, and generating equal water side line image data;
acquiring land terrain data and seabed terrain data of the target coast, and performing data fusion calculation on the land terrain data and the seabed terrain data to obtain sea-land integrated digital elevation DEM data of the target coast;
performing superposition analysis on the DEM data and the water line image data, and calculating to obtain average highest tide level, average lowest tide level and tide difference;
and calculating total tidal volume and average tidal volume in unit time according to the preset time, the tidal difference, the intertidal zone data and the sea-land integrated digital elevation DEM data, and evaluating the tidal energy resources of the target coast according to the total tidal volume and the average tidal volume.
Further, the obtaining of the remote sensing image data of the target coast at the predetermined time and/or within the predetermined time period comprises: and preprocessing the remote sensing image data, wherein the preprocessing mode comprises pixel quality identification code mask processing, radiometric calibration, atmospheric correction, orthometric correction and geometric correction.
Further, the step of extracting the waterside line position data of the remote sensing image data comprises the following steps:
extracting water body information from the preprocessed image data by adopting a normalized water body index (NDWI) method;
detecting the water body edge by adopting a Canny edge detection algorithm to the water body information to obtain a plurality of instantaneous water edge line position data;
and dividing the instantaneous water sideline position data into a plurality of highest tide position data and a plurality of lowest tide position data, and calculating to obtain average highest tide position data and average lowest tide position data.
Further, the step of extracting the water body information from the preprocessed image data by using a normalized water body index method NDWI comprises the following steps: and carrying out image binarization processing on the water body information.
Further, the intertidal zone data includes an intertidal zone width and an intertidal zone dynamic water surface area.
Further, acquiring land terrain data and seafloor terrain data of the target coast comprises: re-sampling the land terrain data and the seafloor terrain data of the target coast, respectively.
Further, acquiring land terrain data and seafloor terrain data for the target coast comprises: preprocessing the land terrain data and the seafloor terrain data, wherein the preprocessing mode comprises the following steps: unifying data format and reference coordinate system, and obtaining the same projection coordinate and elevation reference.
Further, performing data fusion calculation on the land terrain data and the sea bottom terrain data comprises: and judging whether the land terrain data and the submarine terrain data contain an overlapping area, and if so, integrating the overlapping area.
Further, the method also comprises the following steps: acquiring remote sensing image data of a plurality of different time periods, respectively calculating the average tidal volume of each time period, generating an average tidal volume time sequence, and evaluating tidal energy resources of the target coast according to the average tidal volume time sequence.
The technical scheme provided by the embodiment of the invention at least brings the following beneficial technical effects:
compared with the prior art, the tidal energy resource assessment method based on the remote sensing image gets rid of excessive dependence on observation data of a tidal observation station, realizes rapid reflection of the change situation of tidal energy with time, reduces the cost, shortens the time and improves the efficiency for the estimation of tidal energy in a region; aiming at the target coast with the problems of complex terrain, wide tidal flat range, frequent change and the like, the method has stronger timeliness and applicability and more accurate tidal energy estimation.
Drawings
Fig. 1 is a flowchart of a tidal energy resource assessment method based on remote sensing images according to an embodiment of the present invention;
FIG. 2 is a schematic view of a shoreline and intertidal zone cross-section provided in accordance with an embodiment of the present invention;
FIG. 3 is a schematic illustration of a remote sensing image of a target coast according to an embodiment of the present invention;
FIG. 4 is a schematic diagram of a normalized water body index method NDWI for extracting a water body information image according to an embodiment of the present invention;
fig. 5 is a schematic diagram of detecting an edge image of a water body by using a Canny edge detection algorithm according to an embodiment of the present invention;
FIG. 6 is a schematic diagram of a method for calculating a dynamic water surface area image using remote sensing images according to an embodiment of the invention;
fig. 7 is a schematic diagram of a result of superposition analysis of sea-land integrated digital elevation DEM data and water level line image data according to an embodiment of the present invention.
Detailed Description
It should be noted that the embodiments and features of the embodiments in the present application may be combined with each other without conflict. The terms first, second and the like in the description and in the claims and the drawings of the present invention are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It should be understood that the data so used may be interchanged as appropriate in order to facilitate the embodiments of the invention described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps S or elements is not necessarily limited to those steps S or elements expressly listed, but may include other steps S and elements not expressly listed or inherent to such process, method, article, or apparatus.
In order to make the technical field of the present invention better understand the scheme of the present invention, the scheme of the embodiment of the present invention is clearly and completely described below with reference to the drawings in the embodiment of the present invention, and it is obvious that the described embodiment is only a part of the embodiment of the present invention, and not all the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Examples
The technical solutions provided by the embodiments of the present application are described in detail below with reference to the accompanying drawings.
Fig. 1 is a flow chart of a tidal energy resource assessment method based on remote sensing images, and fig. 2 is a structural schematic diagram of a coastline and an intertidal zone cross section. The method for estimating tidal energy by using remote sensing images provided by the embodiment of the invention comprises the following steps as shown in fig. 1 and fig. 2:
s10, obtaining remote sensing image data of a target coast at a preset time and/or within a preset time period, and extracting water sideline position data of the remote sensing image data, wherein the water sideline position data comprises average highest tide position data and average lowest tide position data.
Fig. 3 is a schematic diagram of a remote sensing image of the object coast, as shown in fig. 3. The preset time is preferably high tide level and low tide level near time of the target area, the time period is preferably one day or more, and the acquired remote sensing image data is preferably acquired by a remote sensing satellite.
Preferably, the remote sensing image data is multispectral remote sensing image data, and the multispectral telemetering is a telemetering technology which uses a multispectral photographing system or a multispectral scanning system to carry out synchronous photographing telemetering on different spectral bands of an electromagnetic spectrum and respectively obtain images of vegetation and other ground features on different spectral bands. The multispectral photography for aerial photography and multispectral scanning for terrestrial satellite can obtain telemetering data of different spectral bands, and the images or data of the spectral bands can be processed by photography color synthesis or computer images to obtain richer images than the conventional method, and the possibility is provided for computer identification and classification of ground feature images. The multispectral telemetering can not only judge the ground object according to the difference of the form and the structure of the image, but also judge the ground object according to the difference of the spectral characteristics, and the telemetering information quantity is enlarged.
It should be noted that the waterside line position data of the remote sensing image data is extracted by adopting an automatic identification algorithm, preferably, the extraction mode adopts a normalized water body index method NDWI to extract water body information and adopts a Canny edge detection algorithm to detect the edge of the water body, so as to obtain a plurality of instantaneous waterside line position data. Further, the instantaneous water sideline position data are divided into a plurality of highest tide position data and a plurality of lowest tide position data, and average highest tide position data and average lowest tide position data are obtained through calculation. Fig. 4 is a schematic diagram of extracting a water body information image by a normalized water body index method NDWI, fig. 5 is a schematic diagram of detecting a water body edge image by a Canny edge detection algorithm, please refer to fig. 4 and fig. 5.
The normalized water body index method NDWI is to perform normalized difference processing by using a specific wave band of the remote sensing image to highlight the water body information in the image, and preferably adopts the following expression: NDWI = (p (Green) -p (NIR))/(p (Green) + p (NIR)), the expression is based on the normalized ratio index of the Green band and the near infrared band, and the expression is generally used for extracting the water body information in the image and has a good effect.
The edge detection algorithm can identify actual edges in the image as much as possible, the probability of missing detection of the actual edges and the probability of false detection of the non-edges are both as small as possible, or the position of the detected edge point is closest to the position of the actual edge point, or the degree of deviation of the detected edge from the actual edge of the object caused by noise influence is minimum. The Canny edge detection algorithm is a relatively excellent algorithm for extracting edge information of a picture, and comprises the following five steps: gaussian filtering, intensity gradient searching, non-maximum suppression technology for eliminating edge false detection, double-threshold method for determining possible boundary and hysteresis technology for tracking the boundary. The gaussian filtering is simply to multiply each pixel and its neighborhood by a gaussian matrix, and take the weighted average value as the final gray value. The main purpose of filtering is noise reduction, general image processing algorithms need noise reduction, and gaussian filtering mainly smoothes an image and possibly increases the width of an edge. The method comprises the steps of determining possible boundaries by adopting double thresholds, searching in a low threshold image by using a non-zero point of a high threshold image, determining the position of a real edge, and using two thresholds is more flexible than using one threshold.
It should be noted that the average highest tide level data and the average lowest tide level data are respectively obtained by performing weighted average calculation on all the acquired highest tide level data or lowest tide level data according to specific gravity at a predetermined time and/or within a predetermined time period, excluding data that tides have a lower probability of reaching the highest tide level or the lowest tide level, and simultaneously reserving data of higher probability tide levels. The average highest tide level data and the average lowest tide level data described in the embodiments of the present invention mean weighted averages.
And S20, calculating the position data of the water side line to obtain intertidal zone data, and generating equal water side line image data.
Specifically, the intertidal zone refers to the coast between the average highest tide level and the average lowest tide level. In the embodiment of the invention, the intertidal zone data comprises intertidal zone width and intertidal zone dynamic water surface area. And generating equal water level line image data according to the average highest tide level and the average lowest tide level. Fig. 6 is a schematic diagram of calculating a dynamic water surface area image by using a remote sensing image according to an embodiment of the present invention, as shown in fig. 6.
And S30, acquiring land terrain data and seabed terrain data of the target coast, and performing data fusion calculation on the land terrain data and the seabed terrain data to obtain sea-land integrated digital elevation DEM data of the target coast, wherein the sea-land integrated digital elevation DEM data comprises the gradient, the slope direction and the gradient change rate of the intertidal zone.
Specifically, there are various methods for establishing the DEM, and the data source and the acquisition mode generally include the following three types: the method and the device have the advantages that the method and the device can be used for directly measuring from the ground, obtaining by satellite remote sensing and collecting from the existing topographic map, in the embodiment of the invention, the method of satellite remote sensing obtaining is preferably adopted, and the obtaining efficiency and the measuring precision are higher.
Since the land terrain data and the sea floor terrain data are usually acquired in different manners, for example, the land terrain data is usually acquired by using a visible light channel of a remote sensing satellite, and the sea floor terrain data is usually acquired by using an infrared channel, the land terrain data and the sea floor terrain data need to be acquired and an image needs to be generated respectively. And further, judging whether the image has an overlapping area, if so, acquiring pixels in the overlapping area, otherwise, directly outputting the pixels in the area. And modifying the elevation values of the pixels in the overlapping area by an averaging method to ensure that the pixels of the data in the same area have the same elevation value. And taking the average value of the corresponding pixels of each data source in the overlapping area as a new height value after integration, and assigning the new height value to newly generated integrated data to form high-precision sea-land integrated digital elevation seamless terrain data. And then carrying out data fusion on the land terrain data and the submarine terrain data, automatically identifying an overlapped part in the image, and integrating the land terrain data and the submarine terrain data into integral sea-land integrated digital elevation DEM data after integrating the overlapped part. In a preferred embodiment, contour line image data is generated according to the sea-land integrated digital elevation DEM data. And the sea-land integrated digital elevation DEM data comprises the gradient, the slope direction and the gradient change rate of the intertidal zone.
And S40, performing superposition analysis on the DEM image data and the water level line image data, and calculating to obtain average highest tide level height, average lowest tide level height and tide difference. Fig. 7 is a schematic diagram of a result of analyzing a superposition of sea-land integrated digital elevation DEM data and water level image data according to an embodiment of the present invention, as shown in fig. 7.
Specifically, the sea-land integrated digital elevation DEM data and the water line image data in the embodiment of the present invention are subjected to superposition analysis, a DEM elevation at a position where an average highest tide level is located in the water line image data is a tide height of the average highest tide level, a DEM elevation at a position where an average lowest tide level is located in the water line image data is a tide height of the average lowest tide level, and a tide difference is calculated according to the average highest tide height and the average lowest tide height.
And S50, calculating total tidal volume and average tidal volume in unit time according to the preset time, the tidal range, the intertidal zone data and the sea-land integrated digital elevation DEM data, and evaluating tidal energy resources of the target coast according to the total tidal volume and the average tidal volume.
Specifically, as shown in fig. 2, the average tidal volume per unit time is the average tidal volume contained in the predetermined time, unit time and unit area. And calculating the tidal water volume according to the tidal range, intertidal zone data, and the gradient, slope direction, gradient change rate and other data of the intertidal zone. In a cross section perpendicular to a coastline, a coast where an intertidal zone is located, an intertidal zone width and a tidal range enclose an approximate triangle, the area of the approximate triangle can be calculated through the tidal range, the intertidal zone width, a gradient of the intertidal zone and a gradient change rate, in a selected exemplary embodiment, the coastline is a straight line, the gradient of the intertidal zone and the gradient change rate of the gradient change rate are kept the same in a coastline direction, the area of the approximate triangle is multiplied by the length of the coastline to obtain a total tidal water volume, a single tide rise dwell time specific gravity is obtained through a remote sensing image, for example, in a preferred embodiment, the single tide rise dwell time specific gravity is 30%, the total tidal water volume is multiplied by 30% to obtain a total tidal volume, an average tidal volume is obtained through calculation of unit time and a unit area, and tidal energy resources of the target coast are evaluated according to the total tidal volume and the average tidal volume.
Of course, in other embodiments, the data of the coastline and the intertidal zone may be irregular, but the total tidal volume and the average tidal volume may be obtained according to the total tidal volume and the average tidal volume by performing automatic calculation through sea-land integrated digital elevation DEM data, tidal range and intertidal zone data.
In the embodiment of the invention, the water borderline position data is extracted through the remote sensing image, the land terrain data and the seabed terrain data of the target coast are obtained, sea-land integrated digital elevation DEM data is obtained through fusion calculation, the tidal range is calculated, the total tidal volume and the average tidal volume are finally calculated, and the tidal energy resource of the target coast is evaluated according to the total tidal volume and the average tidal volume. The method of the embodiment of the invention gets rid of the excessive dependence on the observation data of the tidal observation site, realizes the rapid reflection of the tidal energy change state with time, reduces the cost for the estimation of tidal energy in the area, shortens the time and improves the efficiency; aiming at the target coast with the problems of complex terrain, wide tidal flat range, frequent change and the like, the method has stronger timeliness and applicability and more accurate tidal energy estimation.
In a preferred embodiment, the obtaining of the remote sensing image data of the object coast at the predetermined time and/or time period comprises: and preprocessing the remote sensing image data, wherein the preprocessing mode comprises pixel quality identification code mask processing, radiometric calibration, atmospheric correction, orthometric correction and geometric correction, and the method ensures that the acquired remote sensing data is more accurate.
Specifically, the pixel quality identification code masking process is to screen out pixels without quality problems (generally, identification code value 0 represents no quality problem) according to the quality identification codes of the corresponding pixels, and then enter the subsequent process analysis. Wherein the mask is a identifying digital image consisting of 0 and a number of positive integers greater than 0 (representing different classes of quality problems). When a mask is applied in a certain function, it needs to be deconstructed into product-specific unique interpretation bytes, thereby deciding whether the interpretation quality of each pixel is sufficient for use. Where the 0 value region is processed and masked greater than 0 value regions are not included in the calculation.
When a user needs to calculate the spectral reflectivity or the spectral radiance of a ground object, or needs to compare images acquired by different sensors at different times, the luminance gray value of the image must be converted into absolute radiance, the process is radiometric calibration, and the accuracy of the remote sensing data acquired by the sensors is ensured.
The obtained image is stored in a pixel for atmospheric correction, and is a DN value without practical significance, and because the atmospheric scattering and absorption to solar radiation and ground reflection cause distortion of an original image, the definition and contrast of the image are reduced, and related physical quantities such as reflectivity, radiation brightness and the like are deviated, so that the atmospheric correction is needed to restore the real reflectivity of a target object.
The geometric correction is to add geographical coordinates to the image, and the image geometric deformation can be caused by the change of the height and attitude angle of the remote sensor, atmospheric refraction, curvature of the earth, topographic relief, earth rotation, structural performance of the remote sensor and the like in the acquisition process of the remote sensing image. Geometric distortion causes the geometry in the image to differ from the geometry of the object in the selected map projection, causing distortion of the image geometry or position, primarily in terms of displacement, rotation, zoom, affine, curvature and higher order curvature, or in terms of squeezing, stretching, twisting or shifting of the pixel relative to the actual position of the ground. In order to eliminate the above-mentioned error influence, the remote sensing image needs to be geometrically corrected.
The orthorectification is generally to select some ground control points on the photo, and perform tilt correction and projective aberration correction on the image simultaneously by using the originally acquired DEM data in the range of the photo, so as to resample the image into an orthorectified image. Splicing and inlaying a plurality of orthographic images together, carrying out color balance treatment, and cutting out the images within a certain range to obtain the orthographic images. The orthographic images have both topographic map characteristics and image characteristics, are rich in information and can be used as a data source of a GIS (geographic information system), so that the representation form of the geographic information system is enriched, and the purpose is to eliminate parallax caused by ground elevation.
In a preferred embodiment, the step of extracting the water edge line position data of the remote sensing image data comprises the following steps:
extracting water body information from the preprocessed image data by adopting a normalized water body index (NDWI) method;
detecting the water body edge by adopting a Canny edge detection algorithm to the water body information to obtain a plurality of instantaneous water edge line position data;
and dividing the instantaneous water boundary position data into a plurality of highest tide level data and a plurality of lowest tide level data, and calculating to obtain average highest tide level data and average lowest tide level data.
Specifically, the normalized water body index method NDWI is to perform normalized difference processing by using a specific waveband of the remote sensing image to highlight the water body information in the image, and preferably adopts the following expression: NDWI = (p (Green) -p (NIR))/(p (Green) + p (NIR)), and the expression is based on a normalized ratio index of a Green band and a near-infrared band, and is generally used for extracting water body information in an image with a good effect. Fig. 4 is a schematic diagram of extracting a water body information image by a normalized water body index method NDWI, as shown in fig. 4.
The edge detection algorithm can identify actual edges in the image as much as possible, the probability of missing detection of the actual edges and the probability of false detection of the non-edges are both as small as possible, or the position of the detected edge point is closest to the position of the actual edge point, or the degree of deviation of the detected edge from the actual edge of the object caused by noise influence is minimum. The Canny edge detection algorithm is an excellent algorithm for extracting edge information of pictures, and comprises the following five steps: gaussian filtering, searching for intensity gradient, applying non-maximum suppression technology to eliminate edge false detection, applying a double-threshold method to determine a possible boundary, and tracking the boundary by using a hysteresis technology. The gaussian filtering is simply to multiply each pixel and its neighborhood by a gaussian matrix, and take the weighted average value as the final gray value. The main purpose of filtering is noise reduction, general image processing algorithms need noise reduction firstly, and gaussian filtering mainly smoothes an image and also possibly increases the width of an edge. The method comprises the steps of determining possible boundaries by adopting double thresholds, searching in a low threshold image by using a non-zero point of a high threshold image, determining the position of a real edge, and using two thresholds is more flexible than using one threshold. Fig. 5 is a schematic diagram of detecting an edge image of a water body by a Canny edge detection algorithm, as shown in fig. 5.
The average highest tide level data and the average lowest tide level data described in the embodiment of the present invention mean the highest tide level data and the lowest tide level data after weighted averaging. The method of the embodiment of the invention enables the water sideline position data to be more accurately calculated, and improves the precision of tidal energy estimation.
In a preferred embodiment, the extracting water body information from the preprocessed image data by using a normalized water body index method NDWI includes: and carrying out image binarization processing on the water body information.
Specifically, the image binarization is to adjust a proper threshold value according to the image characteristics after the NDWI calculation, and perform binarization processing on the normalized water body index image, so as to enhance the edge characteristics, improve the edge detection precision, and further improve the accuracy of tidal energy estimation.
In a preferred embodiment, the intertidal data includes an intertidal width and an intertidal dynamic water surface area.
The intertidal zone width is the width from the average highest tide level data to the average lowest tide level data in the direction perpendicular to the coastline. Since most shorelines or most areas of shorelines are generally of the same slope and slope, the dynamic water surface area of the intertidal zone can be directly estimated from the width of the intertidal zone and the length of the shoreline. However, there are some irregular coasts, and intelligent operation needs to be performed through the equal water level line image data of the intertidal zone to obtain the dynamic water surface area of the intertidal zone, so that the accuracy of tidal energy estimation is further improved.
In a preferred embodiment, acquiring land terrain data and seafloor terrain data for the target coast comprises: re-sampling the land terrain data and the seafloor terrain data of the target coast, respectively.
Specifically, the resampling of the terrain data is to take into account the difference of data sources, which have a certain difference in spatial resolution, and resample the original land terrain data and the submarine terrain data to generate data with the same spatial resolution. The purpose of data resampling is to ensure that data needing to be integrated has the same spatial resolution, ensure compatibility when the land topographic data and the submarine topographic data are fused and calculated, and improve the precision of sea-land integrated digital elevation DEM data of a target coast so as to further improve the precision of tidal energy estimation.
In a preferred embodiment, acquiring land terrain data and seafloor terrain data for the target coast comprises: preprocessing the land terrain data and the seafloor terrain data, wherein the preprocessing mode comprises the following steps: unifying the data format and the reference coordinate system, and acquiring the same projection coordinate and elevation reference.
Specifically, the data to be integrated is ensured to have the same basic information such as data format, reference coordinate system, projection coordinate system, elevation reference and the like. Therefore, compatibility of the land topographic data and the submarine topographic data during fusion calculation is guaranteed, and the precision of sea-land integrated digital elevation DEM data of the target coast is improved, so that the precision of tidal energy estimation is further improved.
In a preferred embodiment, the data fusion calculation of the land terrain data and the sea floor terrain data comprises: and judging whether the land terrain data and the submarine terrain data contain an overlapping area, and if so, integrating the overlapping area.
Specifically, whether the image has an overlapping area is judged, if so, pixels in the overlapping area are obtained, otherwise, the pixels in the area are directly output. And modifying the elevation values of the pixels in the overlapping area by an averaging method to ensure that the pixels of the data in the same area have the same elevation value. And (3) taking the average value of the corresponding pixels of each data source in the overlapping area as a new integrated height value, and assigning the new integrated height value to newly generated integrated data to form high-precision sea-land integrated digital elevation seamless terrain data. And then carrying out data fusion on the land terrain data and the submarine terrain data, automatically identifying an overlapping part in the image, and integrating the overlapping part to integrate the land terrain data and the submarine terrain data into integral sea-land integrated digital elevation DEM data. In a preferred embodiment, contour line image data is generated according to the sea-land integrated digital elevation DEM data, and the method improves the precision of the sea-land integrated digital elevation DEM data of the target coast, so that the precision of tidal energy estimation is further improved.
In a preferred embodiment, the method further comprises the following steps: acquiring remote sensing image data of a plurality of different time periods, respectively calculating the average tidal volume of each time period, generating an average tidal volume time sequence, and evaluating tidal energy resources of the target coast according to the average tidal volume time sequence.
In the specific implementation process, by setting a plurality of different time periods, in a preferred exemplary embodiment, 12 months are set in a year, three days are set in each month, the three days are respectively located in the upper, middle and lower three ten days of each month, and are used as preset time periods, the time of each day is calculated through the steps S10 to S50 of the embodiment of the present invention to obtain the average tidal volume of each day, an average tidal volume time series is generated, and the tidal energy resources of the target coast are evaluated according to the average tidal volume time series. The rapid reflection and monitoring of the change condition of the tidal energy along with time are realized, the assessment efficiency of the tidal energy resource is improved, and the user experience is improved.
Therefore, in the embodiment of the invention, compared with the prior art, the tidal energy resource assessment method based on the remote sensing image at least has the following technical effects: the method gets rid of the over dependence on the observation data of the tidal observation site, realizes the rapid reflection of the tidal energy change along with time, reduces the cost, shortens the time and improves the efficiency for the estimation of tidal energy in the area; aiming at the target coast with the problems of complex terrain, wide tidal flat range, frequent change and the like, the method has stronger timeliness and applicability and more accurate tidal energy estimation.
The above description is only a preferred embodiment of the present invention, and not intended to limit the scope of the present invention, and all modifications of equivalent structures and equivalent processes, which are made by using the contents of the present specification and the accompanying drawings, or directly or indirectly applied to other related technical fields, are included in the scope of the present invention.
Claims (8)
1. A tidal energy resource assessment method based on remote sensing images is characterized by comprising the following steps:
acquiring remote sensing image data of a target coast at a preset time and/or within a preset time period, and extracting water sideline position data of the remote sensing image data, wherein the water sideline position data comprises average highest tide level data and average lowest tide level data;
calculating to obtain intertidal zone data through the water side line position data, and generating equal water side line image data;
acquiring land terrain data and seabed terrain data of the target coast, and performing data fusion calculation on the land terrain data and the seabed terrain data to obtain sea-land integrated digital elevation DEM data of the target coast, wherein the sea-land integrated digital elevation DEM data comprises the gradient, the slope direction and the gradient change rate of the intertidal zone;
performing superposition analysis on the sea-land integrated digital elevation DEM data and the water line image data, and calculating to obtain average highest tide level tide height, average lowest tide level tide height and tide difference;
calculating a total tidal volume and an average tidal volume in unit time according to the preset time and/or time period, the tidal difference, the intertidal zone data and the sea-land integrated digital elevation DEM data, and evaluating tidal energy resources of the target coast according to the total tidal volume and the average tidal volume;
the sea-land integrated digital elevation DEM data and the water line image data are subjected to superposition analysis, the DEM elevation at the position of the average highest tide level in the water line image data is the tide height of the average highest tide level, the DEM elevation at the position of the average lowest tide level is the tide height of the average lowest tide level, and the tide difference is calculated according to the average highest tide level tide height and the average lowest tide level tide height;
the intertidal zone data comprises intertidal zone width and intertidal zone dynamic water surface area;
in a cross section perpendicular to a coastline, a coast where an intertidal zone is located, the width of the intertidal zone and a tidal range enclose an approximate triangle, the area of the approximate triangle can be calculated through the tidal range, the width of the intertidal zone, the gradient of the intertidal zone and the gradient change rate, the area of the approximate triangle is multiplied by the length of the coastline to obtain the total tidal water volume, the specific gravity of the single tidal rising retention time is obtained through a remote sensing image, and the total tidal volume is calculated.
2. The method for tidal energy resource assessment based on remote sensing images of claim 1, wherein the step of obtaining remote sensing image data of the target coast at a predetermined time and/or within a predetermined period of time comprises:
and preprocessing the remote sensing image data, wherein the preprocessing mode comprises pixel quality identification code mask processing, radiometric calibration, atmospheric correction, orthometric correction and geometric correction.
3. The method for tidal energy resource assessment based on remote sensing images as claimed in claim 2, wherein the step of extracting the water edge line position data of the remote sensing image data comprises the following steps:
extracting water body information from the preprocessed image data by adopting a normalized water body index (NDWI) method;
detecting the water body edge by adopting a Canny edge detection algorithm to the water body information to obtain a plurality of instantaneous water edge line position data;
and dividing the instantaneous water boundary position data into a plurality of highest tide level data and a plurality of lowest tide level data, and calculating to obtain average highest tide level data and average lowest tide level data.
4. The method for evaluating tidal energy resources based on remote sensing images according to claim 3, wherein the step of extracting water body information from the preprocessed image data by using a normalized water body index method NDWI comprises the following steps: and carrying out image binarization processing on the water body information.
5. The method for tidal energy resource assessment based on remote sensing images of claim 1, wherein the obtaining of land terrain data and seafloor terrain data of the target coast comprises: re-sampling the land terrain data and the seafloor terrain data of the target coast, respectively.
6. The method for tidal energy resource assessment based on remote sensing images of claim 1, wherein the obtaining of land terrain data and seafloor terrain data of the target coast comprises: preprocessing the land terrain data and the seafloor terrain data, wherein the preprocessing mode comprises the following steps: unifying the data format and the reference coordinate system, and acquiring the same projection coordinate and elevation reference.
7. The method for tidal energy resource assessment based on remote sensing images as claimed in claim 1, wherein the data fusion calculation of the land terrain data and the sea floor terrain data comprises: and judging whether the land terrain data and the submarine terrain data contain an overlapping area, and if so, integrating the overlapping area.
8. The method for evaluating the tidal energy resource based on the remote sensing image according to claim 1, further comprising the following steps:
acquiring remote sensing image data of a plurality of different time periods, respectively calculating the average tidal volume of each time period, generating an average tidal volume time sequence, and evaluating tidal energy resources of the target coast according to the average tidal volume time sequence.
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