CN112509134A - Tidal flat digital elevation model construction method and system - Google Patents
Tidal flat digital elevation model construction method and system Download PDFInfo
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Abstract
The invention relates to a tidal flat digital elevation model construction method and a tidal flat digital elevation model construction system, wherein the method comprises the following steps: acquiring remote sensing images and tide data of a tidal flat area; determining a water line of the tidal flat area according to the tidal data and the remote sensing image; the water side line is a single beach surface weak edge water side line, a complex beach surface weak edge water side line, a single beach surface strong edge water side line or a complex beach surface strong edge water side line; extracting the strong edge water line of the single beach face according to an edge detection algorithm to obtain the water line characteristics; extracting the weak edge water line of the single beach face according to a threshold segmentation algorithm to obtain the water line characteristics; extracting the strong edge water line of the complex beach face according to an object-oriented method to obtain the water line characteristics; extracting the weak edge waterside line of the complex beach surface according to the watershed algorithm to obtain the waterside line characteristics; and constructing a tidal flat digital elevation model according to the characteristics of the water line. The method can improve the extraction precision of the water line, thereby improving the accuracy of model construction.
Description
Technical Field
The invention relates to the field of digital model construction, in particular to a tidal flat digital elevation model construction method and system.
Background
Silty tidal flats generally refer to the zone between the average high tide line and the average high tide line, also known as the intertidal zone. About one fourth of the coast in China belongs to the muddy coast, and the acquisition of the muddy tidal flat terrain has important significance for researching shoreline transition, ecological change of coastal zones and coastal engineering construction. The silt tidal flat is influenced by a plurality of factors such as waves, silt, coastal currents, geology and the like, has the characteristics of wide area, flat water tidal flat and frequent change, and ensures that the ground survey and the topographic mapping in the area have higher difficulty and higher cost and have certain risks. The remote sensing technology has the characteristics of high timeliness, large range and high frequency, and a tidal flat Digital Elevation Model (DEM) is constructed by utilizing the compound tidal level data of the multi-period remote sensing water line, so that an effective way for acquiring the topographic information of the large-range muddy tidal flat is formed.
The remote sensing water sideline is the instantaneous water sideline that the satellite was acquireed when crossing, and the key that the accurate water sideline of drawing is the tidal flat DEM and is constructed. The existing method for extracting the water sideline mainly comprises the following steps: edge detection, thresholding, region growing, active contour modeling, object-oriented classification, etc. Mason and the like extract a multi-phase water line through texture segmentation based on ERSSAR images, and assign the water line elevation by applying a hydrodynamic model to construct a British east Bank Humber/Wash regional tidal flat DEM; the Shenfang and the like are based on Landsat images, the extraction accuracy of the water boundary lines of different wave bands is compared, the water boundary lines are extracted by using a threshold segmentation method, and the water boundary lines are assigned by using tide prediction data interpolation values, so that a DEM (digital elevation model) of nine-section sand at the Yangtze estuary is constructed; based on the BJ-1 image, Mujing and the like extract a water line by using an object-oriented classification method, and the water line is assigned by tide grid data to construct a tidal flat DEM of the Huang-Ye city. At present, most scholars at home and abroad pay attention to accurately simulating the instantaneous tide level of a water line and improving the water line extraction precision of a single method in the research of building the DEM of the tidal flat. However, the instantaneous water line is influenced by factors such as the tide situation, the weather and the beach surface when the satellite passes through the border, the spectrum and the texture difference in the image are large, the water line is extracted based on a single method, the extraction precision of the water line is difficult to guarantee, and the inversion result of the tidal flat DEM is influenced. Wudi et al propose a multi-source multi-algorithm-based water line extraction model, but do not perform systematic division on water lines, have low water line extraction precision, and do not apply the water line extraction model to tidal flat DEM construction research.
Disclosure of Invention
Aiming at the defects in the prior art, the invention aims to provide a tidal flat digital elevation model construction method and a tidal flat digital elevation model construction system, which can classify water sidelines based on tidal data and extract different types of water sidelines based on a multi-algorithm according to classification results, so that the extraction precision of the water sidelines is improved, and the precision of constructing a tidal flat DEM is improved.
In order to achieve the purpose, the invention provides the following scheme:
a tidal flat digital elevation model construction method comprises the following steps:
acquiring remote sensing images and tide data of a tidal flat area at each moment;
for the tidal flat area at any moment, determining a water line of the tidal flat area according to the tidal data and the remote sensing image; the water side line is a single beach surface weak edge water side line, a complex beach surface weak edge water side line, a single beach surface strong edge water side line or a complex beach surface strong edge water side line;
when the water line is a single beach face strong edge water line, extracting the single beach face strong edge water line according to an edge detection algorithm to obtain water line characteristics;
when the water side line is a single beach surface weak edge water side line, extracting the single beach surface weak edge water side line according to a threshold segmentation algorithm to obtain water side line characteristics;
when the water line is a complex beach face strong edge water line, extracting the complex beach face strong edge water line according to an object-oriented method to obtain water line characteristics;
when the waterside line is a complex beach surface weak edge waterside line, extracting the complex beach surface weak edge waterside line according to a waterside algorithm to obtain the characteristics of the waterside line;
and constructing a tidal flat digital elevation model according to the water line characteristics at all the moments.
Preferably, after obtaining the remote sensing images and the tide data of each period of the tidal flat area, the method further comprises the following steps:
carrying out data preprocessing on the remote sensing image;
the preprocessing comprises absolute radiometric calibration, geometric fine correction and region clipping.
Preferably, the determining a water line of the tidal flat area from the tidal data and the remote sensing image comprises:
judging the remote sensing image through manual visual observation;
if the remote sensing image has thin clouds or fog, the remote sensing image is a cloud fog image, and a water line of the tidal flat area is determined as a weak edge water line;
if the thin cloud or fog does not exist, the remote sensing image is a clear image, and the tide situation of the remote sensing image is determined through the tide data; if the current moment of the remote sensing image is a tide, determining a water sideline of the tidal flat area as a weak edge water sideline; if the current moment of the remote sensing image is flood tide, judging whether residual water exists on the surface of a tidal flat in the remote sensing image or not, and if the residual water exists, determining a water sideline of the tidal flat area as a weak edge water sideline; if no residual water exists, determining a water line of the tidal flat area as a strong edge water line;
judging whether the area where the water side line of the tidal flat area is located is a near shore area or an offshore area;
if the water side line of the tidal flat area is the weak edge water side line and is in a near shore area, determining the beach surface characteristic of the tidal flat area as a complex beach surface, and determining the weak edge water side line as a complex weak edge water side line;
if the water line of the tidal flat area is the weak edge water line and is in the offshore area, determining the beach surface characteristic of the tidal flat area as a single beach surface, and determining the weak edge water line as a single weak edge water line;
if the water line of the tidal flat area is the strong edge water line and is in a near shore area, determining that the beach surface characteristic of the tidal flat area is a complex beach surface, and determining the strong edge water line as the complex strong edge water line;
and if the water line of the tidal flat area is the strong edge water line and is positioned in the offshore area, determining that the beach surface characteristic of the tidal flat area is a single beach surface, and determining the strong edge water line as the single strong edge water line.
Preferably, the determining whether the area where the water side line of the tidal flat area is located is a near shore area or an offshore area specifically includes:
if the tidal level average value of the remote sensing image corresponding to the tidal flat area at the current moment is larger than the historical total tidal level average value, determining that the area where the water side line of the tidal flat area is located is a near shore area; if the tidal level average value of the remote sensing image corresponding to the tidal flat area at the current moment is smaller than or equal to the historical total tidal level average value, determining that the area where the water edge of the tidal flat area is located is the offshore area; the tide level average value is the tide level average value of the remote sensing image at the last time and the next time of the current time; the historical total tidal level average value is the total tidal level average value of the historical tidal level data at the previous time and the next time of the current time.
Preferably, extracting the weak edge waterside line of the complex beach surface according to the watershed algorithm to obtain the waterside line characteristics, and the method comprises the following steps:
sequentially carrying out normalization water body index and low-pass filtering processing on the remote sensing image;
sequentially carrying out binarization processing and mathematical morphology processing on the low-pass filtered image;
performing buffer area processing on the boundary of the tidal flat and the water body in the image after the mathematical morphology processing to generate marking information of a region to be segmented;
carrying out image transformation on the remote sensing image to obtain 432 false color images;
and performing watershed segmentation by combining the 432 false color images with the marking information, and extracting the waterside line characteristics of the complex beach surface weak edge waterside line.
Preferably, the tidal flat digital elevation model is constructed according to the water line characteristics at all the time, and comprises the following steps:
calculating the instantaneous tide level of the water line characteristic by adopting a polynomial interpolation method according to tide prediction data; the tide prediction data is a predicted tide level value obtained by calculating the tide data through a harmonic analysis method;
sequentially screening the characteristics of the water side line according to the sequence of the single beach face strong edge water side line, the complex beach face strong edge water side line, the single beach face weak edge water side line and the complex beach face weak edge water side line;
resampling the screened features of the waterside line as waterside points, and performing spatial interpolation on the waterside points by adopting an irregular triangular net to obtain an interpolation result;
converting the interpolated results and the instantaneous tide level from a tidal height reference level to elevation data referenced to WGS 84;
and constructing a tidal flat digital elevation model according to the elevation data.
A tidal flat digital elevation model construction system, comprising:
the acquisition module is used for acquiring remote sensing images and tide data of the tidal flat area at each moment;
the water side line determining module is used for determining the water side line of the tidal flat area according to the tidal data and the remote sensing image in the tidal flat area at any moment; the water side line is a single beach surface weak edge water side line, a complex beach surface weak edge water side line, a single beach surface strong edge water side line or a complex beach surface strong edge water side line;
the first extraction module is used for extracting the single beach face strong edge water line according to an edge detection algorithm to obtain water line characteristics when the water line is the single beach face strong edge water line;
the second extraction module is used for extracting the single beach surface weak edge water line according to a threshold segmentation algorithm to obtain water line characteristics when the water line is the single beach surface weak edge water line;
the third extraction module is used for extracting the complex beach face strong edge water line according to an object-oriented method to obtain water line characteristics when the water line is the complex beach face strong edge water line;
the fourth extraction module is used for extracting the complex beach surface weak edge water line according to a watershed algorithm to obtain water line characteristics when the water line is the complex beach surface weak edge water line;
and the model building module is used for building a tidal flat digital elevation model according to the water line characteristics at all the moments.
Preferably, after the acquiring module, the method further comprises:
the preprocessing module is used for preprocessing the data of the remote sensing image; the preprocessing comprises absolute radiometric calibration, geometric fine correction and region clipping.
Preferably, the water line determining module specifically includes:
the first judgment unit is used for judging the remote sensing image through manual visual observation; if the remote sensing image has thin clouds or fog, the remote sensing image is a cloud fog image, and a water line of the tidal flat area is determined as a weak edge water line; if the thin cloud or fog does not exist, the remote sensing image is a clear image, and the tide situation of the remote sensing image is determined through the tide data; if the current moment of the remote sensing image is a tide, determining a water sideline of the tidal flat area as a weak edge water sideline; if the current moment of the remote sensing image is flood tide, judging whether residual water exists on the surface of a tidal flat in the remote sensing image or not, and if the residual water exists, determining a water sideline of the tidal flat area as a weak edge water sideline; if no residual water exists, determining a water line of the tidal flat area as a strong edge water line;
the second judgment unit is used for judging whether the area where the water side line of the tidal flat area is located is a near shore area or an offshore area; if the water side line of the tidal flat area is the weak edge water side line and is in a near shore area, determining the beach surface characteristic of the tidal flat area as a complex beach surface, and determining the weak edge water side line as a complex weak edge water side line; if the water line of the tidal flat area is the weak edge water line and is in the offshore area, determining the beach surface characteristic of the tidal flat area as a single beach surface, and determining the weak edge water line as a single weak edge water line; if the water line of the tidal flat area is the strong edge water line and is in a near shore area, determining that the beach surface characteristic of the tidal flat area is a complex beach surface, and determining the strong edge water line as the complex strong edge water line; and if the water line of the tidal flat area is the strong edge water line and is positioned in the offshore area, determining that the beach surface characteristic of the tidal flat area is a single beach surface, and determining the strong edge water line as the single strong edge water line.
Preferably, the second judging unit specifically includes:
the near bank area determining subunit is used for determining that an area where a water edge of the tidal bank area is located is a near bank area if the tidal level average value of the remote sensing image corresponding to the tidal bank area at the current moment is larger than the historical total tidal level average value;
the offshore area determining subunit is used for determining that an area where a water edge of the tidal flat area is located is an offshore area if the tidal level average value of the remote sensing image corresponding to the tidal flat area at the current moment is smaller than or equal to the historical total tidal level average value; the tide level average value is the tide level average value of the remote sensing image at the last time and the next time of the current time; the historical total tidal level average value is the total tidal level average value of the historical tidal level data at the previous time and the next time of the current time.
According to the specific embodiment provided by the invention, the invention discloses the following technical effects:
the invention provides a tidal flat digital elevation model construction method and a tidal flat digital elevation model construction system, which analyze the edge types of water sidelines in different tidal conditions, classify the water sidelines based on tidal data, and divide the water sidelines in research data into: the tidal flat digital elevation model is constructed according to the instantaneous tidal flat and the water boundary characteristics. The inversion result of the tidal flat digital elevation model of the research area has higher precision, and can accurately reflect the approximate terrain of the tidal flat.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings needed to be used in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings without inventive exercise.
FIG. 1 is a flow chart of a method of constructing a tidal flat digital elevation model according to the present invention;
FIG. 2 is a diagram illustrating specific classification rules in an embodiment of the present invention;
FIG. 3 is a flow chart of an improved watershed algorithm in an embodiment provided by the present invention;
FIG. 4 is a graph of verification point distribution in an embodiment provided by the present invention;
FIG. 5 is a graph of correlation analysis in an embodiment provided by the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of 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.
The invention aims to provide a tidal flat digital elevation model construction method and a tidal flat digital elevation model construction system, which can classify water sidelines based on tidal data and extract different types of water sidelines based on a multi-algorithm according to classification results, so that the extraction precision of the water sidelines is improved, and the precision of construction of a tidal flat DEM is improved.
In order to make the aforementioned objects, features and advantages of the present invention comprehensible, embodiments accompanied with figures are described in further detail below.
Fig. 1 is a flowchart of a method for constructing a tidal flat digital elevation model according to the present invention, as shown in fig. 1, the method includes:
step 100: and acquiring remote sensing images and tide data of the tidal flat area at each moment.
Step 200: for the tidal flat area at any moment, determining a water line of the tidal flat area according to the tidal data and the remote sensing image; the water line is a single beach surface weak edge water line, a complex beach surface weak edge water line, a single beach surface strong edge water line or a complex beach surface strong edge water line.
Step 300: and when the water line is a single beach face strong edge water line, extracting the single beach face strong edge water line according to an edge detection algorithm to obtain the water line characteristics.
Step 301: and when the water side line is a single beach surface weak edge water side line, extracting the single beach surface weak edge water side line according to a threshold segmentation algorithm to obtain the water side line characteristics.
Step 302: and when the water line is a complex beach face strong edge water line, extracting the complex beach face strong edge water line according to an object-oriented method to obtain water line characteristics.
Step 303: and when the waterside line is the complex beach surface weak edge waterside line, extracting the complex beach surface weak edge waterside line according to a waterside algorithm to obtain the characteristics of the waterside line.
Step 400: and constructing a tidal flat digital elevation model according to the water line characteristics at all the moments.
Preferably, after obtaining the remote sensing images and the tide data of each period of the tidal flat area, the method further comprises the following steps:
and carrying out data preprocessing on the remote sensing image.
The preprocessing comprises absolute radiometric calibration, geometric fine correction and region clipping.
Specifically, the geometric fine correction error is controlled within 0.5 pixel.
As an optional implementation mode, the remote sensing data is GF1-WFV data, the spatial resolution is 16m, the revisiting period is 2d, and the breadth is 800 km.
Preferably, the determining a water line of the tidal flat area from the tidal data and the remote sensing image comprises:
and judging the remote sensing image through manual visual observation.
And if the remote sensing image has thin clouds or fog, the remote sensing image is a cloud fog image, and the water line of the tidal flat area is determined as a weak edge water line.
If the thin cloud or fog does not exist, the remote sensing image is a clear image, and the tide situation of the remote sensing image is determined through the tide data; if the current moment of the remote sensing image is a tide, determining a water sideline of the tidal flat area as a weak edge water sideline; if the current moment of the remote sensing image is flood tide, judging whether residual water exists on the surface of a tidal flat in the remote sensing image or not, and if the residual water exists, determining a water sideline of the tidal flat area as a weak edge water sideline; if no residual water is present, determining a water line of the tidal flat area as a strong edge water line.
And judging whether the area where the water side line of the tidal flat area is located is a near shore area or an offshore area.
And if the water side line of the tidal flat area is the weak edge water side line and is in a near shore area, determining that the beach surface characteristic of the tidal flat area is a complex beach surface, and determining the weak edge water side line as the complex weak edge water side line.
And if the water line of the tidal flat area is the weak edge water line and is in the offshore area, determining that the beach surface characteristic of the tidal flat area is a single beach surface, and determining the weak edge water line as the single weak edge water line.
And if the water line of the tidal flat area is the strong edge water line and is in the near shore area, determining that the beach surface characteristic of the tidal flat area is a complex beach surface, and determining the strong edge water line as the complex strong edge water line.
And if the water line of the tidal flat area is the strong edge water line and is positioned in the offshore area, determining that the beach surface characteristic of the tidal flat area is a single beach surface, and determining the strong edge water line as the single strong edge water line.
Fig. 2 is a schematic diagram of a specific classification rule in an embodiment of the present invention, as shown in fig. 2, in the embodiment of the present invention, the thin clouds or fog in the images significantly weaken the gradient of the gray scale variation, so that the image quality is determined by manual visual observation, and the water line including the thin clouds or fog images is divided into weak edge water lines; and dividing the water line of the clear image by analyzing the tide data. If the tide levels at the three moments of H (10), H (11) and H (12) rise in sequence, the instantaneous tide situation (between 11 and 12 hours) is rising tide, the tidal flat surface does not have the influence of residual water, the water line is divided into a strong edge water line, and if the tide levels at the three moments fall (falling tide) in sequence or the tide level at the moment of 10 hours is higher than the tide level at the moment of 11 hours, the influence of residual water or sediment in water on the tidal flat surface exists, and the tide line is divided into a weak edge water line.
After strong and weak edge water lines are obtained, classifying the beach surface characteristics of the water lines according to the height of the tide level: if the average tide level of the water sideline at 11 and 12 times of the day is higher than the average value H in multiple periods, the water sideline at the period is close to the shore and corresponds to a complex beach surface; and if the average value is lower than or equal to the average value H in multiple periods, the water edge at the period is offshore, and the single beach surface is corresponding. Finally, the obtained 4 types of water lines are respectively as follows: a single weak edge water line, a complex weak edge water line, a single strong edge water line, and a complex strong edge water line. The water lines of the GF1 images used herein were classified in units of images, and the classification results are shown in table 1, where table 1 is the water line classification result.
TABLE 1
Specifically, the gray scale variation gradient of the land and water areas on the two sides of the water line is mainly influenced by the fluctuation tide: when tide rises, the beach surface is clear in dryness and wetness, and the gray level difference of the areas on the two sides of the water line is obvious; the influence of residual water on the beach surface and sediment in water during the tide falling process is small, and the gray level difference of the two sides of the water line is small. Thus, edge types can be classified into strong edges and weak edges by gray scale gradient. The neighborhood noise level of the water line is mainly determined by the height of the tide level: because the types of the land objects on the beach surface are gradually increased from offshore to inland, the water line is in the near shore area with more distribution of tidal ditches, vegetations and buildings at high tide level, the beach surface is broken complicated, and the noise in the neighborhood is higher; at low tide level, the water line is offshore, and the beach surface is relatively homogeneous and single.
Preferably, the determining whether the area where the water side line of the tidal flat area is located is a near shore area or an offshore area specifically includes:
if the current tidal level average value of the remote sensing image corresponding to the tidal flat area is larger than the historical total tidal level average value, determining that the area where the water side line of the tidal flat area is located is a near shore area; if the current tidal level average value of the remote sensing image corresponding to the tidal flat area is smaller than or equal to the historical total tidal level average value, determining that the area where the water edge of the tidal flat area is located is the offshore area; the tide level average value is the tide level average value of the last time and the tide level average value of the next time of the remote sensing image; the historical total tide level average value is the total tide level average value of the previous time and the next time of the current time in the historical tide level data.
Specifically, the total tidal level average value is the tidal level average value of the previous time and the next time of the time when the remote sensing image is located in the multiple groups of historical tidal level data.
Optionally, the edge detection algorithm in step 300 is to extract the region boundary with the sharply changed gray level in the image based on the first or second derivative of the image gray level, and has the advantages of few model parameters and high running speed, but is sensitive to noise, and serious burrs or discontinuities exist on the water line extracted from the complex beach surface. The Canny edge detection algorithm with high positioning accuracy and good unilateral response is selected.
Specifically, the threshold segmentation algorithm in step 301 may rapidly and effectively distinguish land and water areas by setting a threshold, such as normalized water body index (NDWI), but for a complex beach face at a high tide level, affected by a tidal trench or other water accumulation areas, the water boundary extraction is inaccurate, and therefore, the present invention extracts a single weak edge water boundary of the beach face by threshold segmentation. Specifically, firstly, the NDWI is calculated, and the water body information in the image is enhanced, wherein the calculation formula is as follows:
in the formula, Green and NIR respectively represent the reflectivity of a Green wave band and a near infrared wave band in a GF1-WFV image, and the value range of NDWI is [ -1,1 ]; then, calculating a threshold value through an OTSU algorithm, and binarizing the NDWI gray image; and finally, performing opening operation processing on the binary image, and smoothing the boundary to obtain the water line characteristics.
Alternatively, the object-oriented method in step 302 is a method of segmenting an image by using spectral information, spatial information, and texture information in the image, and then classifying the segmented object as a basic unit, thereby extracting a water line. The object-oriented method has stronger noise resistance, effectively inhibits the influence of other ground objects on the complex beach surface, and can accurately keep the detail information of the strong edge water line, but the method is too sensitive to texture change, and the extracted weak edge water line is not smooth, so the method extracts the strong edge water line of the complex beach surface by the object-oriented method. Firstly, an image is divided into a plurality of objects through multi-scale division, then merging is carried out according to the spectral similarity of each object, and the water line characteristics are finally obtained after multiple iterations.
Preferably, extracting the weak edge waterside line of the complex beach surface according to the watershed algorithm to obtain the waterside line characteristics, and the method comprises the following steps:
and sequentially carrying out normalization water body index and low-pass filtering processing on the remote sensing image.
And sequentially carrying out binarization processing and mathematical morphology processing on the low-pass filtered image.
And performing buffer area processing on the boundary of the tidal flat and the water body in the image after the mathematical morphology processing to generate marking information of the region to be segmented.
And carrying out image transformation on the remote sensing image to obtain 432 false color images.
And performing watershed segmentation by combining the 432 false color images with the marking information, and extracting the waterside line characteristics of the complex beach surface weak edge waterside line.
Fig. 3 is a flow chart of an improved watershed algorithm in the embodiment, as shown in fig. 3, the watershed algorithm is a commonly used image segmentation algorithm, and has the characteristics of high computation speed, continuous closing of extraction boundaries, and good response to weak edges, but is sensitive to noise, and has severe over-segmentation and under-segmentation phenomena. By marking the regions to be segmented, the phenomena of over-segmentation and under-segmentation can be effectively avoided. According to the method, firstly, the land and water boundary area is extracted as the marking information through operations such as low-pass filtering, mathematical morphology processing and the like, the effect of restraining the complex beach face noise is achieved, and then the waterside line in the marking area is extracted based on watershed segmentation. The improved watershed algorithm is relatively complex, but the extraction precision of the weak edge waterside line of the complex beach surface is higher. After the high-frequency noise is removed by NDWI low-pass filtering, removing the tidal creeks on the tidal beaches, the sandbars at the river mouths and smaller artificial buildings; after binarization processing, completely removing inland water bodies such as salt pan, river and the like through mathematical morphology processing, and performing buffer area processing at the boundary to generate marking information of a region to be segmented; and (4) performing watershed segmentation by using the false color image of the original image 432 and combining the marking information to obtain the water line characteristics.
Preferably, the tidal flat digital elevation model is constructed according to the water line characteristics at all the time, and comprises the following steps:
calculating the instantaneous tide level of the water line characteristic by adopting a polynomial interpolation method according to tide prediction data; the tide prediction data is a predicted tide level value obtained by calculating the tide data through a harmonic analysis method.
And screening characteristics of the water side lines in sequence according to the single beach face strong edge water side line, the complex beach face strong edge water side line, the single beach face weak edge water side line and the complex beach face weak edge water side line.
Resampling the screened features of the waterside line as waterside points, and performing spatial interpolation on the waterside points by adopting an irregular triangular net to obtain an interpolation result.
The interpolated results and the instantaneous tide level are converted from a tidal height reference surface to elevation data referenced to WGS 84.
And constructing a tidal flat digital elevation model according to the elevation data.
The GF1-WFV data used in the invention are acquired between 11 am and 12 am every day, a cubic polynomial is constructed by using 4 full-time tide values from 10 am to 13 am, if a tide level extreme value exists between 10 am and 13 am, the full-time tide value far away from the image acquisition time is replaced by the tide level extreme value, and the instantaneous tide level of the water line is calculated by polynomial interpolation. When the research data is limited, the method is effective, and the water line corresponds to the instantaneous tide level as shown in table 2, and table 2 shows the instantaneous tide level of the water line.
TABLE 2
Under the influence of silt at the tidal canal or river entrance on the beach surface, the extracted multi-stage water lines are partially crossed or overlapped. Aiming at the problems, the tidal flat DEM inversion method selects the water side lines according to the priority sequence of the single tidal flat strong edge, the complex tidal flat strong edge, the single tidal flat weak edge and the complex tidal flat weak edge, resamples the screened water side lines into 16m multiplied by 16m water side points, performs spatial interpolation by using an irregular triangular network, and converts an interpolation result and an instant tide level from a tidal height datum plane into elevation data with WGS84 as a datum so as to obtain a tidal flat DEM inversion result.
Specifically, the beach face is single, the edge information of the water line is obvious, the used algorithm is simple and stable, the extraction precision is highest, the selection is preferred, the algorithm with the complex beach face and the unobvious edge information of the water line has the worst extraction precision, and finally, the simplicity of the extraction algorithm of the strong edge relative to the weak edge is considered, the algorithm robustness is good, so the extraction results of 2 strong edges are preferably considered.
Fig. 4 is a verification point distribution diagram in the embodiment provided by the present invention, and as shown in fig. 4, in order to verify the effectiveness of the method, the present invention performs precision evaluation on the inversion result of the tidal flat DEM by using the measured elevation data in the field. The actual measurement elevation data acquisition time is 12 months in 2017, the TrimbleR5GPS receiver is adopted for measurement, and the static observation time is not less than 20 minutes. The measured elevation data is resolved into WGS84 coordinate data through precise ephemeris, and the total number of verification points is 18.
FIG. 5 is a correlation analysis diagram in an embodiment of the present invention, and as shown in FIG. 5, correlation analysis is performed on the measured elevation and the inversion result, where the correlation between the measured elevation and the inversion result corresponding to the DEM is high, and R is20.8649, the error distribution is between 0.31m and 0.78m, and the median error is 0.1734 m.
The invention also provides a tidal flat digital elevation model construction system, which comprises:
and the acquisition module is used for acquiring remote sensing images and tide data of the tidal flat area at each moment.
The water side line determining module is used for determining the water side line of the tidal flat area according to the tidal data and the remote sensing image in the tidal flat area at any moment; the water line is a single beach surface weak edge water line, a complex beach surface weak edge water line, a single beach surface strong edge water line or a complex beach surface strong edge water line.
And the first extraction module is used for extracting the single beach face strong edge water line according to an edge detection algorithm to obtain the water line characteristics when the water line is the single beach face strong edge water line.
And the second extraction module is used for extracting the single beach surface weak edge water line according to a threshold segmentation algorithm to obtain the water line characteristics when the water line is the single beach surface weak edge water line.
And the third extraction module is used for extracting the complex beach face strong edge water line according to an object-oriented method to obtain the water line characteristics when the water line is the complex beach face strong edge water line.
And the fourth extraction module is used for extracting the complicated beach surface weak edge water line according to the improved watershed algorithm to obtain the water line characteristics when the water line is the complicated beach surface weak edge water line.
The model construction module is used for constructing a tidal flat digital elevation model according to the water line characteristics at all the moments
Preferably, the method further comprises the following steps:
the preprocessing module is used for preprocessing the data of the remote sensing image; the preprocessing comprises absolute radiometric calibration, geometric fine correction and region clipping.
Preferably, the water line determining module specifically includes:
the first judgment unit is used for judging the remote sensing image through manual visual observation; if the remote sensing image has thin clouds or fog, the remote sensing image is a cloud fog image, and a water line of the tidal flat area is determined as a weak edge water line; if the thin cloud or fog does not exist, the remote sensing image is a clear image, and the tide situation of the remote sensing image is determined through the tide data; if the current moment of the remote sensing image is a tide, determining a water sideline of the tidal flat area as a weak edge water sideline; if the current moment of the remote sensing image is flood tide, judging whether residual water exists on the surface of a tidal flat in the remote sensing image or not, and if the residual water exists, determining a water sideline of the tidal flat area as a weak edge water sideline; if no residual water is present, determining a water line of the tidal flat area as a strong edge water line.
The second judgment unit is used for judging whether the area where the water side line of the tidal flat area is located is a near shore area or an offshore area; if the water side line of the tidal flat area is the weak edge water side line and is in a near shore area, and the beach surface characteristic of the tidal flat area is a complex beach surface, determining the weak edge water side line as the complex weak edge water side line; if the water line of the tidal flat area is the weak edge water line and is in the offshore area, and the beach surface characteristic of the tidal flat area is a single beach surface, determining the weak edge water line as the single weak edge water line; if the water line of the tidal flat area is the strong edge water line and is in the near shore area, and the beach surface characteristic of the tidal flat area is a complex beach surface, determining the strong edge water line as the complex strong edge water line; and if the water edge line of the tidal flat area is the strong edge water edge line and is positioned in the offshore area, and the beach surface characteristic of the tidal flat area is a single beach surface, determining the strong edge water edge line as the single strong edge water edge line.
Preferably, the second judging unit specifically includes:
and the near bank area determining subunit is used for determining that the area where the water edge of the tidal flat area is located is the near bank area if the current tidal level average value of the remote sensing image corresponding to the tidal flat area is greater than the historical total tidal level average value.
The offshore area determining subunit is used for determining that an area where a water edge of the tidal flat area is located is an offshore area if the tidal level average value of the remote sensing image corresponding to the tidal flat area at the current moment is smaller than or equal to the historical total tidal level average value; the tide level average value is the tide level average value of the last time and the tide level average value of the next time of the remote sensing image; the historical total tide level average value is the total tide level average value of the previous time and the next time of the current time in the historical tide level data.
The invention has the following beneficial effects:
(1) the invention analyzes the difference between the edge type of the water sideline and the beach face noise in different tide situations, classifies the water sideline based on tide data, and divides the multi-stage water sideline in the research data into: and 4 types of single weak edge water line, complex weak edge water line, single strong edge water line and complex strong edge water line are adopted, and the result can be further used for water line extraction and tidal flat DEM construction.
(2) The tidal flat DEM is constructed by extracting the water line based on a multi-algorithm, obtaining the multi-phase water line instantaneous tide level through tide prediction data interpolation, and further screening according to the water line type. The research area DEM inversion result has high precision, can accurately reflect the approximate terrain of the tidal flat, and can be effectively used for acquiring the information of the tidal flat terrain.
The embodiments in the present description are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other. For the system disclosed by the embodiment, the description is relatively simple because the system corresponds to the method disclosed by the embodiment, and the relevant points can be referred to the method part for description.
The principle and the implementation mode of the invention are explained by applying a specific example, and the description of the embodiment is only used for helping to understand the method and the core idea of the invention; meanwhile, for a person skilled in the art, according to the idea of the present invention, the specific embodiments and the application range may be changed. In view of the above, the present disclosure should not be construed as limiting the invention.
Claims (10)
1. A tidal flat digital elevation model construction method is characterized by comprising the following steps:
acquiring remote sensing images and tide data of a tidal flat area at each moment;
for the tidal flat area at any moment, determining a water line of the tidal flat area according to the tidal data and the remote sensing image; the water side line is a single beach surface weak edge water side line, a complex beach surface weak edge water side line, a single beach surface strong edge water side line or a complex beach surface strong edge water side line;
when the water line is a single beach face strong edge water line, extracting the single beach face strong edge water line according to an edge detection algorithm to obtain water line characteristics;
when the water side line is a single beach surface weak edge water side line, extracting the single beach surface weak edge water side line according to a threshold segmentation algorithm to obtain water side line characteristics;
when the water line is a complex beach face strong edge water line, extracting the complex beach face strong edge water line according to an object-oriented method to obtain water line characteristics;
when the waterside line is a complex beach surface weak edge waterside line, extracting the complex beach surface weak edge waterside line according to a waterside algorithm to obtain the characteristics of the waterside line;
and constructing a tidal flat digital elevation model according to the water line characteristics at all the moments.
2. The method of constructing a tidal flat digital elevation model of claim 1, further comprising, after acquiring the remote sensing images and tidal data of each period of the tidal flat area:
carrying out data preprocessing on the remote sensing image;
the preprocessing comprises absolute radiometric calibration, geometric fine correction and region clipping.
3. The method of constructing a tidal flat digital elevation model, according to claim 1, wherein the determining the water line of the tidal flat area from the tidal data and the remote sensing image comprises:
judging the remote sensing image through manual visual observation;
if the remote sensing image has thin clouds or fog, the remote sensing image is a cloud fog image, and a water line of the tidal flat area is determined as a weak edge water line;
if the thin cloud or fog does not exist, the remote sensing image is a clear image, and the tide situation of the remote sensing image is determined through the tide data; if the current moment of the remote sensing image is a tide, determining a water sideline of the tidal flat area as a weak edge water sideline; if the current moment of the remote sensing image is flood tide, judging whether residual water exists on the surface of a tidal flat in the remote sensing image or not, and if the residual water exists, determining a water sideline of the tidal flat area as a weak edge water sideline; if no residual water exists, determining a water line of the tidal flat area as a strong edge water line;
judging whether the area where the water side line of the tidal flat area is located is a near shore area or an offshore area;
if the water side line of the tidal flat area is the weak edge water side line and is in a near shore area, determining the beach surface characteristic of the tidal flat area as a complex beach surface, and determining the weak edge water side line as a complex weak edge water side line;
if the water line of the tidal flat area is the weak edge water line and is in the offshore area, determining the beach surface characteristic of the tidal flat area as a single beach surface, and determining the weak edge water line as a single weak edge water line;
if the water line of the tidal flat area is the strong edge water line and is in a near shore area, determining that the beach surface characteristic of the tidal flat area is a complex beach surface, and determining the strong edge water line as the complex strong edge water line;
and if the water line of the tidal flat area is the strong edge water line and is positioned in the offshore area, determining that the beach surface characteristic of the tidal flat area is a single beach surface, and determining the strong edge water line as the single strong edge water line.
4. The tidal flat digital elevation model construction method of claim 3, wherein the determining whether the area where the water side of the tidal flat area is located is a near shore area or an offshore area specifically comprises:
if the tidal level average value of the remote sensing image corresponding to the tidal flat area at the current moment is larger than the historical total tidal level average value, determining that the area where the water side line of the tidal flat area is located is a near shore area; if the tidal level average value of the remote sensing image corresponding to the tidal flat area at the current moment is smaller than or equal to the historical total tidal level average value, determining that the area where the water edge of the tidal flat area is located is the offshore area; the tide level average value is the tide level average value of the remote sensing image at the last time and the next time of the current time; the historical total tidal level average value is the total tidal level average value of the historical tidal level data at the previous time and the next time of the current time.
5. The tidal flat digital elevation model construction method of claim 1, wherein extracting the weak edge waterside of the complex beach according to a watershed algorithm to obtain the waterside features comprises:
sequentially carrying out normalization water body index and low-pass filtering processing on the remote sensing image;
sequentially carrying out binarization processing and mathematical morphology processing on the low-pass filtered image;
performing buffer area processing on the boundary of the tidal flat and the water body in the image after the mathematical morphology processing to generate marking information of a region to be segmented;
carrying out image transformation on the remote sensing image to obtain 432 false color images;
and performing watershed segmentation by combining the 432 false color images with the marking information, and extracting the waterside line characteristics of the complex beach surface weak edge waterside line.
6. The method of constructing a tidal flat digital elevation model according to claim 1, wherein constructing the tidal flat digital elevation model according to the waterside characteristics at all times comprises:
calculating the instantaneous tide level of the water line characteristic by adopting a polynomial interpolation method according to tide prediction data; the tide prediction data is a predicted tide level value obtained by calculating the tide data through a harmonic analysis method;
sequentially screening the characteristics of the water side line according to the sequence of the single beach face strong edge water side line, the complex beach face strong edge water side line, the single beach face weak edge water side line and the complex beach face weak edge water side line;
resampling the screened features of the waterside line as waterside points, and performing spatial interpolation on the waterside points by adopting an irregular triangular net to obtain an interpolation result;
converting the interpolated results and the instantaneous tide level from a tidal height reference level to elevation data referenced to WGS 84;
and constructing a tidal flat digital elevation model according to the elevation data.
7. A tidal flat digital elevation model construction system, comprising:
the acquisition module is used for acquiring remote sensing images and tide data of the tidal flat area at each moment;
the water side line determining module is used for determining the water side line of the tidal flat area according to the tidal data and the remote sensing image in the tidal flat area at any moment; the water side line is a single beach surface weak edge water side line, a complex beach surface weak edge water side line, a single beach surface strong edge water side line or a complex beach surface strong edge water side line;
the first extraction module is used for extracting the single beach face strong edge water line according to an edge detection algorithm to obtain water line characteristics when the water line is the single beach face strong edge water line;
the second extraction module is used for extracting the single beach surface weak edge water line according to a threshold segmentation algorithm to obtain water line characteristics when the water line is the single beach surface weak edge water line;
the third extraction module is used for extracting the complex beach face strong edge water line according to an object-oriented method to obtain water line characteristics when the water line is the complex beach face strong edge water line;
the fourth extraction module is used for extracting the complex beach surface weak edge water line according to a watershed algorithm to obtain water line characteristics when the water line is the complex beach surface weak edge water line;
and the model building module is used for building a tidal flat digital elevation model according to the water line characteristics at all the moments.
8. The tidal flat digital elevation model building system of claim 7, further comprising:
the preprocessing module is used for preprocessing the data of the remote sensing image; the preprocessing comprises absolute radiometric calibration, geometric fine correction and region clipping.
9. The tidal flat digital elevation model building system of claim 7, wherein the waterside determining module specifically comprises:
the first judgment unit is used for judging the remote sensing image through manual visual observation; if the remote sensing image has thin clouds or fog, the remote sensing image is a cloud fog image, and a water line of the tidal flat area is determined as a weak edge water line; if the thin cloud or fog does not exist, the remote sensing image is a clear image, and the tide situation of the remote sensing image is determined through the tide data; if the current moment of the remote sensing image is a tide, determining a water sideline of the tidal flat area as a weak edge water sideline; if the current moment of the remote sensing image is flood tide, judging whether residual water exists on the surface of a tidal flat in the remote sensing image or not, and if the residual water exists, determining a water sideline of the tidal flat area as a weak edge water sideline; if no residual water exists, determining a water line of the tidal flat area as a strong edge water line;
the second judgment unit is used for judging whether the area where the water side line of the tidal flat area is located is a near shore area or an offshore area; if the water side line of the tidal flat area is the weak edge water side line and is in a near shore area, determining the beach surface characteristic of the tidal flat area as a complex beach surface, and determining the weak edge water side line as a complex weak edge water side line; if the water line of the tidal flat area is the weak edge water line and is in the offshore area, determining the beach surface characteristic of the tidal flat area as a single beach surface, and determining the weak edge water line as a single weak edge water line; if the water line of the tidal flat area is the strong edge water line and is in a near shore area, determining that the beach surface characteristic of the tidal flat area is a complex beach surface, and determining the strong edge water line as the complex strong edge water line; and if the water line of the tidal flat area is the strong edge water line and is positioned in the offshore area, determining that the beach surface characteristic of the tidal flat area is a single beach surface, and determining the strong edge water line as the single strong edge water line.
10. The tidal flat digital elevation model construction method of claim 9, wherein the second determination unit specifically comprises:
the near bank area determining subunit is used for determining that an area where a water edge of the tidal bank area is located is a near bank area if the tidal level average value of the remote sensing image corresponding to the tidal bank area at the current moment is larger than the historical total tidal level average value;
the offshore area determining subunit is used for determining that an area where a water edge of the tidal flat area is located is an offshore area if the tidal level average value of the remote sensing image corresponding to the tidal flat area at the current moment is smaller than or equal to the historical total tidal level average value; the tide level average value is the tide level average value of the remote sensing image at the last time and the next time of the current time; the historical total tidal level average value is the total tidal level average value of the historical tidal level data at the previous time and the next time of the current time.
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