Method for extracting structure features of waterfront space based on remote sensing image analysis

Abstract

The application discloses a waterline hydrophilic space structure feature extraction method based on remote sensing image analysis, relates to the technical field of remote sensing image processing and geographic space information analysis, and comprises the following steps: collecting continuous time sequence remote sensing images, and extracting water body boundary positions frame by frame in the time advancing process; identifying the boundary contour successively for the flow rate mutation period; and obtaining a boundary coordinate set arranged in time sequence. The application realizes the structured expression of waterline change through change rhythm expression and time section division, combines the continuous change trajectory to constrain the boundary change path, and makes the boundary keep coherent in the time advancing process; meanwhile, through the trajectory guiding alignment and matching update mechanism, the newly extracted boundary is continued along the existing change path, position jumping and repeated adjustment are avoided, and therefore the continuity of the waterline extraction result and the reliability of the spatial analysis are improved.

Description

Technical Field

[0001] This invention relates to the field of remote sensing image processing and geospatial information analysis technology, specifically to a method for extracting shoreline hydrophilic spatial structure features based on remote sensing image analysis. Background Technology

[0002] The extraction of shoreline waterfront spatial structure features based on remote sensing image analysis refers to the use of surface image data acquired by satellites or drones to automatically identify and quantify the spatial morphology near the water-land boundary (shoreline) through image recognition and spatial analysis, thereby extracting structural information reflecting the accessibility and utilization of the water area. Specifically, this process first interprets and segments the water body extent and shoreline location in the remote sensing image. Based on this, it further identifies the distribution of spatial elements around the shoreline, such as gently sloping beaches, hard revetments, green open spaces, walkways, and platforms—all waterfront-related areas. Subsequently, combining spatial continuity, accessibility, and boundary morphology, the shoreline is structurally divided and feature-coded to form a set of structural features characterizing the waterfront's waterfront attributes. This result can be used in scenarios such as waterfront space planning assessment, ecological restoration analysis, and urban landscape design, realizing the transformation from image data to spatial cognition.

[0003] The existing technology has the following shortcomings: In existing technologies, shoreline extraction based on remote sensing imagery often relies on the continuity of changes between adjacent timeframes. When water flow suddenly accelerates within a short period, significant dynamic erosion can occur near the shoreline, causing frequent shifts in the position of local boundaries over a continuous timeframe. These changes are characterized by their suddenness, short duration, and unstable amplitude, easily disrupting the original rhythm of change and making it difficult for the system to maintain stable tracking of boundary changes during processing. In such cases, existing methods often repeatedly correct the current identification results, leading to frequent fluctuations or even multiple resets in the extraction results. This makes it difficult to form a continuous and consistent representation of shoreline changes, affecting the reliability of subsequent spatial analysis results.

[0004] The information disclosed in the background section is only intended to enhance the understanding of the background of this disclosure, and therefore may include information that does not constitute prior art known to those skilled in the art. Summary of the Invention

[0005] The purpose of this invention is to provide a method for extracting shoreline hydrophilic spatial structure features based on remote sensing image analysis, so as to solve the problems mentioned in the background art.

[0006] To achieve the above objectives, the present invention provides the following technical solution: a method for extracting shoreline hydrophilic spatial structure features based on remote sensing image analysis, comprising the following steps: The system acquires continuous time-series remote sensing images and extracts the water body boundary positions frame by frame as time progresses. It identifies the boundary contours one by one during periods of abrupt changes in flow velocity, and obtains a set of boundary coordinates arranged in chronological order. The set of boundary coordinates is used to characterize the spatial distribution of the shoreline at each time location. Based on the boundary coordinate set, the difference between the boundary coordinates of adjacent time positions is calculated to obtain the boundary offset. The rate of change of the boundary offset is analyzed to extract the fluctuation range of the accelerated change stage and construct an expression of the change rhythm corresponding to the time position. Based on the rhythm of change, the boundary change process is divided into time segments. By segmenting the trend of change rate, the continuous time change is divided into multiple time segments with consistent change trends, and the boundary change direction is kept consistent within each time segment. By combining time segments, the boundary coordinates within each time segment are subjected to continuous constraint processing. By gradually adjusting the boundary offset, the continuous change trajectory within the corresponding time segment is obtained. The continuous change trajectory is used to characterize the stable change path of the boundary within the corresponding time segment. By utilizing the continuously changing trajectory, the water body boundary positions in the newly acquired remote sensing images are aligned during subsequent time progression. By matching and updating the newly extracted boundary coordinates to the continuously changing trajectory, a continuous and consistent boundary extraction result is obtained.

[0007] The preferred method for resolving the location and constructing the temporal correspondence of water body boundaries in continuous time-series remote sensing images involves continuously describing the spatial distribution of shorelines by unifying boundary contour representation and spatial coordinate recording, thus forming a set of boundary coordinates. The steps are as follows: The continuous time-series remote sensing images are organized in chronological order and read frame by frame. By distinguishing the differences between water areas and land areas, the boundary positions are located and processed to form the boundary outline, which is then expressed using a unified spatial reference. By combining the boundary contours and comparing images of adjacent time locations, the time intervals of flow velocity changes are identified, the boundary contours are tracked one by one, and the correspondence between time locations is established by point-by-point correspondence. Connect the boundary contours, convert the boundary contours at each time position into spatial coordinates and record them, unify the coordinate order and spatial orientation, and form a set of boundary coordinates arranged by time; By linking the boundary coordinate set with time information, we can express the relationship between each time location and form the boundary coordinate set corresponding to the shoreline change path by continuously describing the spatial distribution.

[0008] Preferably, the boundary contours are matched according to the spatial distribution order, and the spatial arrangement of corresponding points at each time position is kept consistent; a unified coordinate order and spatial pointing rules are adopted in the process of recording boundary coordinates to standardize the expression of boundary coordinates at each time position, and the continuous correspondence of boundary coordinates in the process of time progression is maintained through the association of time information.

[0009] The preferred method for analyzing the temporal positional changes in the boundary coordinate set involves obtaining boundary coordinate differences and extracting change features to express the rhythm of shoreline changes, thus forming a rhythmic expression of change. The steps are as follows: For the corresponding set of boundary coordinates, the boundary coordinates of adjacent time positions are processed point by point. The movement of the position points is obtained by comparing the spatial positions, forming the spatial displacement relationship between the time positions, and thus obtaining the boundary offset. Connecting boundary offsets involves sequentially organizing the boundary offsets of consecutive time positions and comparing the changes in the degree of offset between adjacent time positions to form a continuous change relationship of the boundary offsets in the time direction. By combining the continuous change relationship of boundary offset, the offset change between adjacent time positions is compared and analyzed. By identifying the trend of increase or decrease in change, the rate of change is extracted and the time range of continuous increase in the rate of change is determined, forming the fluctuation range. By linking fluctuation ranges with time location information, the corresponding change states at each time location are uniformly organized. By associating boundary offsets with changes in the rate of change, an expression of the change rhythm corresponding to the time location is constructed.

[0010] Preferably, in the process of constructing the rhythm of change expression, by continuously comparing the boundary offsets corresponding to each time position within the fluctuation range and combining the consistency of the change rate and change direction, the change state within the fluctuation range is uniformly constrained. By sequentially associating the time position change characteristics, the change trend within the same fluctuation range is kept consistent, thereby further enhancing the ability of the rhythm of change expression to represent the change pattern of time position.

[0011] The preferred method for analyzing the temporal positional change features in the rhythm of change involves extracting the continuous relationship of the rate of change and merging the trend of change to structurally divide the boundary change process into time segments. The specific steps are as follows: Organize the rate of change corresponding to each time position in the expression of the rhythm of change, arrange them in chronological order, and obtain the continuous change relationship by connecting the rate of change of adjacent time positions to form a continuous change trajectory of the rate of change. It inherits the trajectory of continuous change rate, compares the change rate of adjacent time positions, identifies the direction of change, and forms a description of the change trend. By connecting the results of the trend description, time positions with consistent change directions within a continuous time range are merged to divide the continuous trend intervals and form multiple time segments. By combining time segments, the boundary offset direction within each time segment is uniformly defined. By adjusting the boundary offset direction point by point, time segments with consistent trends of change are formed.

[0012] Preferably, the description results of the change trend within the time interval are refined by checking the change direction of each time position in the continuous change trajectory of the change rate segment by segment, ensuring that the change direction within the same time interval remains consistent, and uniformly adjusting the time positions with differences, thereby forming a time interval structure with consistent boundary change direction.

[0013] Preferably, the process of constructing the continuous change relationship of boundary coordinates within a time segment involves adjusting the boundary offset and processing spatial connections to constrain the shoreline change path, forming a continuous change trajectory. The steps are as follows: Extract the set of boundary coordinates corresponding to each time segment and arrange them in chronological order. By organizing the boundary coordinates point by point, a continuous spatial relationship within the time segment is formed. Connect the boundary coordinate set, read the boundary offset of adjacent time positions, and form a continuous change relationship of boundary offset by arranging them in sequence; By combining the continuous change relationship of the boundary offset, the boundary coordinates at each time position are adjusted point by point. By continuously connecting the boundary offsets, a continuous change relationship of the boundary coordinates is formed. The adjusted boundary coordinates are connected and organized within the time interval to form a continuous change trajectory, which is used to characterize the stable change path of the boundary.

[0014] Preferably, the boundary offset within the time segment is continuously constrained. By keeping the direction of change of the boundary offset of adjacent time positions consistent, the boundary coordinates are uniformly adjusted. Combined with the spatial distribution order of the boundary coordinates, the adjustment results are connected point by point to form a continuous change trajectory and maintain the consistency of the change path.

[0015] Preferably, the boundary coordinate update process guided by the continuously changing trajectory continuously expresses the water body boundary position at the new time location through spatial alignment and matching adjustment, forming a consistent boundary extraction result. The steps are as follows: Acquire new time-location remote sensing images and analyze them frame by frame. Identify the location of water body boundaries to form boundary coordinates, and express them using a spatial reference consistent with the continuously changing trajectory. Receive the boundary coordinates, and perform point-by-point correspondence between the boundary coordinates and the end boundary coordinates in the continuously changing trajectory. Form a correspondence relationship through spatial arrangement to complete the alignment process. The alignment process involves adjusting the boundary coordinates point by point along the continuously changing trajectory, and then updating the matching results to form a continuously changing relationship. The linkage matching update results incorporate the boundary coordinates into the continuously changing trajectory, and form a continuous and consistent boundary extraction result by connecting them in time sequence.

[0016] The technical effects and advantages provided by the present invention in the above technical solution are as follows: This invention constructs a rhythmic expression of change and combines it with the trend of change rate for time segmentation, transforming the original continuous expression of shoreline change into multiple time segments with consistent change trends. Within each time segment, the direction of boundary change is defined, thus enabling the boundary to form a structured expression of change over time. Furthermore, by uniformly constraining the boundary position through continuous change trajectories, the boundary changes can unfold continuously along a stable path, thereby improving the coherence of the shoreline change expression and ensuring that the extracted results remain consistent across different time locations, providing a stable data foundation for subsequent spatial analysis.

[0017] This invention aligns the water body boundary positions in newly acquired remote sensing images using continuously changing trajectories and updates the newly extracted boundary coordinates, ensuring that the boundary extraction results continue to extend along the existing change path. This avoids abrupt changes or repeated adjustments in the boundary positions during the time-lapse process, thus guaranteeing the continuity and consistency of the boundary extraction results. By guiding the update of the boundary change process, shoreline changes can be expressed with a unified trajectory, thereby improving the reliability of the spatial feature extraction results and providing stable support for subsequent hydrophilic spatial structure analysis. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this invention. For those skilled in the art, other drawings can be obtained based on these drawings.

[0019] Figure 1 This is a flowchart of the method for extracting shoreline hydrophilic spatial structure features based on remote sensing image analysis according to the present invention. Detailed Implementation

[0020] Exemplary embodiments will now be described more fully with reference to the accompanying drawings. However, these exemplary embodiments can be implemented in many forms and should not be construed as limited to the examples set forth herein; rather, they are provided so that the description of this disclosure will be more complete and fully convey the concept of the exemplary embodiments to those skilled in the art.

[0021] This invention provides, for example Figure 1 The method for extracting shoreline hydrophilic spatial structure features based on remote sensing image analysis, as shown, includes the following steps: The system acquires continuous time-series remote sensing images and extracts the water body boundary positions frame by frame as time progresses. It identifies the boundary contours one by one during periods of abrupt changes in flow velocity, and obtains a set of boundary coordinates arranged in chronological order. The set of boundary coordinates is used to characterize the spatial distribution of the shoreline at each time location. By performing time-series position analysis on the water body boundaries in continuous time-series remote sensing images and combining this with targeted processing of boundary contours based on flow velocity changes, the spatial distribution of the shoreline over time is continuously expressed, thus forming a set of boundary coordinates with temporal correspondence. This provides a stable data foundation for subsequent change analysis. The specific implementation steps are as follows: The acquired continuous temporal remote sensing images are organized in chronological order, and the image content is read frame by frame according to the time progression. In each frame, the boundary between water and land areas is located by distinguishing the differences in color distribution, texture, and spatial connectivity between water and land areas, so that the boundary forms a closed or semi-closed boundary contour. When extracting the boundary contour, the water area in the image is completely covered so that the boundary contour can be continuously distributed around the outer edge of the water body. At the same time, a unified spatial reference benchmark is used to express the boundary contour at different time locations, so that the boundary contour corresponding to each time location has a consistent positioning method in the spatial coordinate system, thereby ensuring that the boundary contours at different time locations can be analyzed in the same spatial range.

[0022] During continuous time progression, the image content of adjacent time positions is continuously compared, and the time intervals in which the water flow velocity changes are identified around the boundary contours formed at each time position. Within these time intervals, the boundary contours of each time position are tracked successively. During this tracking process, the boundary contour of the previous time position is used as a reference, and the movement of each point in the boundary contour in space is matched point by point. This ensures that the boundary contour of the next time position can form a one-to-one correspondence with the previous time position, and this correspondence is maintained throughout the continuous time progression. This ensures that the boundary contours of each time position are continuously associated within the time intervals in which the flow velocity changes, avoiding contour interruptions or spatial misalignments caused by rapid changes in boundary positions.

[0023] The boundary contours of each time location, after successive identification and processing, are uniformly organized and arranged in chronological order. During the organization process, the boundary contour of each time location is converted into spatial coordinates. By recording the coordinates of each point on the boundary contour, the boundary contour can be expressed by multiple coordinate points with spatial location attributes. After the coordinate recording is completed, the boundary coordinates of different time locations are uniformly organized to ensure that the boundary coordinates of each time location are consistent in terms of recording format, coordinate order, and spatial orientation. This forms a set of boundary coordinates arranged in chronological order, and each set of boundary coordinates in the set corresponds to a unique time location, realizing the synchronous expression of time information and spatial location information.

[0024] Around the established set of boundary coordinates, the boundary coordinates at each time point are associated with the corresponding time information, so that each set of boundary coordinates can reflect the spatial distribution of the shoreline at the corresponding time point. In this process, by continuously expressing the spatial distribution of different time points in the boundary coordinate set, the change path of the shoreline in the process of time can be described in coordinate form. At the same time, it is ensured that the boundary coordinates between each time point have a continuous connection relationship in space. Thus, the boundary coordinate set can not only reflect the shoreline distribution at a single time point, but also reflect the overall change process of the shoreline in continuous time, providing a complete data foundation for subsequent expression of the change rhythm based on boundary offset.

[0025] Based on the boundary coordinate set, the difference between the boundary coordinates of adjacent time positions is calculated to obtain the boundary offset. The rate of change of the boundary offset is analyzed to extract the fluctuation range of the accelerated change stage and construct an expression of the change rhythm corresponding to the time position. Based on the spatial variation relationship between different time positions in the boundary coordinate set, by comparing the boundary coordinates time-by-time and combining the velocity characteristics during the change process, the shoreline change state is expressed in layers, thus forming a rhythmic expression that reflects the rhythmic characteristics of the change process. The specific process is as follows: Based on the existing set of boundary coordinates arranged in chronological order, the boundary coordinates of adjacent time positions are matched one by one. By comparing the spatial position of the boundary coordinates at the same time position with the boundary coordinates of the next adjacent time position, the movement of corresponding points on the boundary contour is calculated, so that each point forms a spatial displacement relationship between the two time positions. When obtaining the spatial displacement relationship, the coordinate points on the boundary contour are matched point by point according to the spatial continuous distribution of the coordinates of each time position in the boundary coordinate set, so that the boundary coordinates between the two time positions can form a one-to-one correspondence in space. This ensures that the boundary coordinates have a continuous and traceable change basis in the process of time progression, and on this basis, the boundary offset between each time position is obtained.

[0026] After obtaining the boundary offsets between various time points, the changes in the boundary offsets during continuous time progression are organized so that the offsets between different time points can form a continuous change relationship in chronological order. Based on the trend of the boundary offsets in the time direction, the degree of offset between each time point is compared and analyzed. By comparing the boundary offsets between multiple consecutive time points segment by segment, the increase or decrease of the boundary offsets during the time progression is identified, so that the trend of the boundary offsets between different time points can be continuously expressed, thus providing a complete basis for obtaining the subsequent rate of change.

[0027] Based on the completion of the continuous change relationship of boundary offset, the rate of change of boundary offset over time is analyzed and processed. By comparing the degree of change of boundary offset between adjacent time positions, the rate of change of boundary offset in the time direction is reflected. In this process, the speed change in the process is observed in segments around the change amplitude of boundary offset between multiple consecutive time positions, so that the rate of change in different time intervals can form a continuous comparison relationship. On this basis, the time range of continuous increase in the rate of change is identified, so that the time range can reflect the stage of the shoreline change process from a stable state to a rapid change state, thus obtaining the fluctuation range corresponding to the accelerated change stage.

[0028] After determining the fluctuation range of the accelerated change phase, this fluctuation range is associated with its corresponding time position information. Combined with the characteristics of boundary offset and rate of change within this time range, the change state of the shoreline within this time range is uniformly expressed, allowing the fluctuation range of the accelerated change phase to be described in the form of a continuous time interval. Based on this, the change states corresponding to different time positions are organized chronologically, so that each time position corresponds to a set of expressions reflecting the characteristics of boundary changes. This constructs a change rhythm expression that corresponds one-to-one with each time position. This change rhythm expression not only reflects the changes in boundary offset but also the changing pattern of the rate of change during the time progression, providing a direct basis for subsequent time division processing based on the change rhythm expression.

[0029] Based on the rhythm of change, the boundary change process is divided into time segments. By segmenting the trend of change rate, the continuous time change is divided into multiple time segments with consistent change trends, and the boundary change direction is kept consistent within each time segment. By continuously analyzing the changing characteristics of each time position in the rhythm of change, and combining the changing trend of the rate of change in the process of time, the boundary change process is segmented, transforming the original continuous change process into multiple time segments with consistent changing trends. At the same time, the direction of boundary change is uniformly defined within each time segment, thus giving the shoreline change a clear structure in the time dimension. The specific steps are as follows: Based on the rate of change information corresponding to each time position in the rhythm of change, all time positions are arranged in chronological order, and the rate of change value corresponding to each time position is read one by one. During the reading process, the rate of change of adjacent time positions is sequentially matched to form a continuous arrangement of the rate of change in the time direction. After the arrangement is completed, the rate of change of the current time position is used as the starting point to compare it with the rate of change of the next time position point by point, and the changes in the values ​​between the two are recorded. This ensures that the difference in the rate of change between each pair of adjacent time positions can be fully expressed, thus forming a continuous trajectory of the rate of change across the entire time range, providing a complete data source for subsequent trend identification.

[0030] Based on the established continuous trajectory of rate of change, the direction of change of the rate of change between adjacent time positions is identified segment by segment. During the identification process, the rate of change at the previous time position is used as a reference to compare the rate of change at the next time position. When the rate of change at the next time position is higher than that at the previous time position, the time period is marked as the direction of increasing rate of change; when the rate of change at the next time position is lower than that at the previous time position, the time period is marked as the direction of decreasing rate of change; when the rates of change at two adjacent time positions are consistent, the time period is marked as the direction of maintaining rate of change. After completing the direction marking between all time positions, the direction marking results are arranged in chronological order to fully express the directional changes of the rate of change throughout the entire time process, thus forming a continuous description of the trend of change.

[0031] After obtaining the trend description results, time positions with consistent change directions within a continuous time range are merged. During the merging process, starting from the initial time position, the change direction of subsequent time positions is checked one by one along the time progression direction. When the change direction of multiple consecutive time positions is consistent, the continuous time range is divided into the same trend interval. When a change in change direction is detected, the current interval division is terminated at the position where the change direction occurs, and this position is used as the starting point of the next trend interval, continuing the same merging process. By merging the entire time range segment by segment, all time positions are divided into multiple continuous time ranges with consistent change directions, and each continuous time range is determined as an independent time segment, making a clear distinction in the change trend between time segments.

[0032] For each time segment that has been divided, the boundary change direction within each time segment is uniformly defined. During the definition process, the boundary offset direction corresponding to each time position in the change rhythm expression is extracted one by one, and the boundary offset directions within the same time segment are arranged in chronological order. The arrangement results are compared point by point to ensure that the boundary offset direction between each time position within the time segment is consistent. When the boundary offset direction of individual time positions within the same time segment is found to differ from the overall direction of the segment, the direction expression of that time position is adjusted to be consistent with the overall direction of the time segment. This ensures that the boundary change direction within each time segment is uniformly expressed and that the boundary changes in the same direction within the time segment, providing stable constraints for the subsequent construction of continuous change trajectories based on time segments.

[0033] By combining time segments, the boundary coordinates within each time segment are subjected to continuous constraint processing. By gradually adjusting the boundary offset, the continuous change trajectory within the corresponding time segment is obtained. The continuous change trajectory is used to characterize the stable change path of the boundary within the corresponding time segment. Around the already divided time segments, the continuous change relationship of the boundary coordinates within each time segment is constrained. Combined with the changes in boundary offset over time, the boundary position is gradually adjusted to create a continuous trajectory for the boundary within each time segment, thus achieving a stable representation of the shoreline change path. The specific steps are as follows: For each of the defined time segments, the boundary coordinate set corresponding to each time segment is extracted. The boundary coordinates within the same time segment are then arranged in chronological order. During the arrangement process, the boundary coordinates corresponding to each time position within the same time segment are read one by one and organized according to the spatial distribution order of the boundary contour, so that the boundary coordinates of each time position within the same time segment can form a point-to-point correspondence in space. After the correspondence is organized, the boundary coordinates between each time position are connected one by one, so that the boundary forms a continuous spatial change relationship within the time segment, thereby providing a unified data foundation for subsequent continuity constraint processing.

[0034] Based on the established continuous correspondence of boundary coordinates within the same time interval, the boundary offsets between adjacent time positions are read segment by segment and arranged in chronological order to ensure a continuous change in boundary offsets within the time interval. When processing the boundary offsets, the boundary coordinates of the current time position are used as a reference to analyze the boundary offsets corresponding to the boundary coordinates of the next time position point by point. By continuously observing the changes in the spatial direction of the boundary offsets, the trend of the boundary offsets within the time interval is fully expressed, providing a basis for subsequent gradual adjustments.

[0035] Based on the established continuous relationship of boundary offset changes, the boundary offsets within the same time segment are gradually adjusted. During the adjustment process, the boundary coordinates at the beginning of the time segment are used as the initial reference, and the boundary coordinates at subsequent time positions are corrected point by point according to the trend of boundary offset changes. This ensures that the boundary coordinates gradually transition along the direction of continuous change as time progresses. During the gradual adjustment, the boundary offsets between adjacent time positions are continuously connected, so that the change process of the boundary between each time position no longer exhibits abrupt changes, but rather achieves a smooth connection through a point-by-point transition. This ensures that the boundary coordinates at each time position within the time segment form a continuous relationship of change and avoids discontinuous changes in the boundary position as time progresses.

[0036] After gradually adjusting the boundary offset, the boundary coordinates of each time position within the same time interval are integrated as a whole, so that the adjusted boundary coordinates can form a unified expression within the time interval. By organizing the continuous spatial distribution of the boundary coordinates of each time position, a continuous change trajectory within the corresponding time interval is constructed. When constructing the continuous change trajectory, the boundary coordinates of all time positions within the time interval are connected in chronological order, so that the change path of the boundary within the time interval can be expressed in a continuous form. Thus, the continuous change trajectory can reflect the stable change path of the boundary within the time interval and provide a direct basis for subsequent alignment processing based on the continuous change trajectory.

[0037] By utilizing the continuously changing trajectory, the water body boundary positions in the newly acquired remote sensing images are aligned during subsequent time progression. By matching and updating the newly extracted boundary coordinates to the continuously changing trajectory, a continuous and consistent boundary extraction result is obtained. By introducing a continuously changing trajectory to guide the water body boundary position at subsequent time points, the boundary coordinates in newly acquired remote sensing images can continue along the existing change path as time progresses. The boundary coordinates are updated through spatial alignment and point-by-point matching, thus forming a continuous and consistent boundary extraction result. The specific steps are as follows: New remote sensing images are acquired during the time progression, and the image content is analyzed frame by frame. During the analysis, the boundary between water and non-water areas in the image is located. By identifying the spatial distribution range of the water body edge in the image, the water body boundary position at the current time position can be completely extracted, and the water body boundary position is converted into the corresponding boundary coordinates according to the spatial distribution order. When extracting the boundary coordinates, the same spatial reference method as the aforementioned time position is used, so that the boundary coordinates at the current time position maintain the same coordinate reference as the boundary coordinates in the continuously changing trajectory in spatial expression, thereby ensuring that the newly extracted boundary coordinates can directly participate in the subsequent alignment process.

[0038] The boundary coordinates of the current time position are spatially mapped to the existing boundary coordinates in the continuous change trajectory. During the mapping process, the boundary coordinates of the last time position in the continuous change trajectory are used as a reference object, and the boundary coordinates of the current time position are processed point by point. By following the spatial arrangement order of the boundary contour, the boundary coordinates of the current time position are reordered so that they correspond to the reference boundary coordinates in spatial distribution. After completing the point-by-point correspondence, the boundary coordinates of the current time position are compared with the change trend of the continuous change trajectory in the spatial direction, so that the current boundary coordinates can be arranged in space along the extension direction of the continuous change trajectory, thereby completing the initial alignment process.

[0039] After completing the spatial location mapping, the boundary coordinates of the current time location are matched and updated. During the matching and update process, guided by the boundary change path reflected by the continuous change trajectory, the boundary coordinates of the current time location are adjusted point by point along the direction of the change path. By gradually correcting the spatial position of each boundary coordinate point, its spatial distribution is brought closer to the continuous change trajectory, and the consistency of the boundary change direction is maintained during the adjustment process. When adjusting point by point, the boundary coordinates of the current time location are connected with the boundary coordinates of adjacent time locations in the continuous change trajectory, so that the boundary coordinates form a continuous transition relationship in the process of time advancement, thereby avoiding abrupt deviations of the boundary position at the new time location.

[0040] After the matching update is completed, the adjusted boundary coordinates at the current time position are incorporated into the continuous change trajectory, making these boundary coordinates a new component of the continuous change trajectory and participating in the subsequent time progression process. The continuous change trajectory is extended continuously in the time direction. During the extension process, the boundary coordinates at each time position are continuously connected in chronological order, so that the boundary change path forms a unified expression throughout the entire time range. This ensures that the boundary extraction results remain continuous and consistent during the time progression process and can reflect the complete trajectory of the shoreline change process, providing a stable and reliable data foundation for subsequent spatial analysis.

[0041] This invention constructs a rhythmic expression of change and combines it with the trend of change rate for time segmentation, transforming the original continuous expression of shoreline change into multiple time segments with consistent change trends. Within each time segment, the direction of boundary change is defined, thus enabling the boundary to form a structured expression of change over time. Furthermore, by uniformly constraining the boundary position through continuous change trajectories, the boundary changes can unfold continuously along a stable path, thereby improving the coherence of the shoreline change expression and ensuring that the extracted results remain consistent across different time locations, providing a stable data foundation for subsequent spatial analysis.

[0042] This invention aligns the water body boundary positions in newly acquired remote sensing images using continuously changing trajectories and updates the newly extracted boundary coordinates, ensuring that the boundary extraction results continue to extend along the existing change path. This avoids abrupt changes or repeated adjustments in the boundary positions during the time-lapse process, thus guaranteeing the continuity and consistency of the boundary extraction results. By guiding the update of the boundary change process, shoreline changes can be expressed with a unified trajectory, thereby improving the reliability of the spatial feature extraction results and providing stable support for subsequent hydrophilic spatial structure analysis.

[0043] The foregoing has only described certain exemplary embodiments of the present invention by way of illustration. Undoubtedly, those skilled in the art can modify the described embodiments in various ways without departing from the spirit and scope of the present invention. Therefore, the foregoing drawings and descriptions are illustrative in nature and should not be construed as limiting the scope of protection of the claims of the present invention.

Claims

1. A method for extracting shoreline hydrophilic spatial structure features based on remote sensing image analysis, characterized in that, Includes the following steps: The system acquires continuous time-series remote sensing images and extracts the water body boundary positions frame by frame as time progresses. It then identifies the boundary contours sequentially during periods of abrupt changes in flow velocity to obtain a set of boundary coordinates arranged in chronological order. Based on the boundary coordinate set, the difference between the boundary coordinates of adjacent time positions is calculated to obtain the boundary offset. The rate of change of the boundary offset is analyzed to extract the fluctuation range of the accelerated change stage and construct an expression of the change rhythm corresponding to the time position. Based on the rhythm of change, the boundary change process is divided into time segments. By segmenting the trend of change rate, the continuous time change is divided into multiple time segments with consistent change trends, and the boundary change direction is kept consistent within each time segment. By combining time segments, the boundary coordinates within each time segment are subjected to continuity constraints. By gradually adjusting the boundary offset, the continuous change trajectory within the corresponding time segment is obtained. By utilizing the continuously changing trajectory, the water body boundary positions in the newly acquired remote sensing images are aligned during subsequent time progression. By matching and updating the newly extracted boundary coordinates to the continuously changing trajectory, a continuous and consistent boundary extraction result is obtained.

2. The method for extracting shoreline hydrophilic spatial structure features based on remote sensing image analysis according to claim 1, characterized in that, The process of resolving the location of water body boundaries and constructing their temporal correspondence in continuous time-series remote sensing imagery involves continuously describing the spatial distribution of shorelines through a unified boundary contour representation and spatial coordinate recording, forming a set of boundary coordinates. The steps are as follows: The continuous time-series remote sensing images are organized in chronological order and read frame by frame. By distinguishing the differences between water areas and land areas, the boundary positions are located and processed to form the boundary outline, which is then expressed using a unified spatial reference. By combining the boundary contours and comparing images of adjacent time locations, the time intervals of flow velocity changes are identified, the boundary contours are tracked one by one, and the correspondence between time locations is established by point-by-point correspondence. Connect the boundary contours, convert the boundary contours at each time position into spatial coordinates and record them, unify the coordinate order and spatial orientation, and form a set of boundary coordinates arranged by time; By linking the boundary coordinate set with time information, we can express the relationship between each time location and form the boundary coordinate set corresponding to the shoreline change path by continuously describing the spatial distribution.

3. The method for extracting shoreline hydrophilic spatial structure features based on remote sensing image analysis according to claim 2, characterized in that, The boundary contours are matched according to the spatial distribution order, and the spatial arrangement of corresponding points at each time position is kept consistent. In the process of recording boundary coordinates, a unified coordinate order and spatial pointing rules are adopted to standardize the expression of boundary coordinates at each time position, and the continuous correspondence of boundary coordinates in the process of time progression is maintained through the association of time information.

4. The method for extracting shoreline hydrophilic spatial structure features based on remote sensing image analysis according to claim 2, characterized in that, The process of analyzing the temporal positional changes in the boundary coordinate set involves obtaining boundary coordinate differences and extracting change features to express the rhythm of shoreline changes, thus forming a rhythmic expression of change. The steps are as follows: For the corresponding set of boundary coordinates, the boundary coordinates of adjacent time positions are processed point by point. The movement of the position points is obtained by comparing the spatial positions, forming the spatial displacement relationship between the time positions, and thus obtaining the boundary offset. Connecting boundary offsets involves sequentially organizing the boundary offsets of consecutive time positions and comparing the changes in the degree of offset between adjacent time positions to form a continuous change relationship of the boundary offsets in the time direction. By combining the continuous change relationship of boundary offset, the offset change between adjacent time positions is compared and analyzed. By identifying the trend of increase or decrease in change, the rate of change is extracted and the time range of continuous increase in the rate of change is determined, forming the fluctuation range. By linking fluctuation ranges with time location information, the corresponding change states at each time location are uniformly organized. By associating boundary offsets with changes in the rate of change, an expression of the change rhythm corresponding to the time location is constructed.

5. The method for extracting shoreline hydrophilic spatial structure features based on remote sensing image analysis according to claim 4, characterized in that, In the process of constructing the rhythm of change expression, by continuously comparing the boundary offsets corresponding to each time position within the fluctuation range and combining the consistency of the change rate and direction, the change state within the fluctuation range is uniformly constrained. By sequentially associating the change characteristics of time position, the change trend within the same fluctuation range is kept consistent, further enhancing the ability of the rhythm of change expression to represent the change pattern of time position.

6. The method for extracting shoreline hydrophilic spatial structure features based on remote sensing image analysis according to claim 4, characterized in that, The process of analyzing the temporal and positional change features in the expression of rhythmic change involves extracting the continuous relationship of the rate of change and merging the trend of change, structurally dividing the boundary change process into time segments. The specific steps are as follows: Organize the rate of change corresponding to each time position in the expression of the rhythm of change, arrange them in chronological order, and obtain the continuous change relationship by connecting the rate of change of adjacent time positions to form a continuous change trajectory of the rate of change. It inherits the trajectory of continuous change rate, compares the change rate of adjacent time positions, identifies the direction of change, and forms a description of the change trend. By connecting the results of the trend description, time positions with consistent change directions within a continuous time range are merged to divide the continuous trend intervals and form multiple time segments. By combining time segments, the boundary offset direction within each time segment is uniformly defined. By adjusting the boundary offset direction point by point, time segments with consistent trends of change are formed.

7. The method for extracting shoreline hydrophilic spatial structure features based on remote sensing image analysis according to claim 6, characterized in that, The description results of the changing trend within the time interval are refined by checking the changing direction of each time position in the continuous trajectory of the rate of change segment by segment. The changing direction within the same time interval is kept consistent, and the time positions with differences are uniformly adjusted, thereby forming a time interval structure with consistent boundary changing direction.

8. The method for extracting shoreline hydrophilic spatial structure features based on remote sensing image analysis according to claim 6, characterized in that, The process of constructing the continuous change relationship of boundary coordinates within a time segment involves adjusting boundary offsets and processing spatial connections to constrain the shoreline change path, forming a continuous change trajectory. The steps are as follows: Extract the set of boundary coordinates corresponding to each time segment and arrange them in chronological order. By organizing the boundary coordinates point by point, a continuous spatial relationship within the time segment is formed. Connect the boundary coordinate set, read the boundary offset of adjacent time positions, and form a continuous change relationship of boundary offset by arranging them in sequence; By combining the continuous change relationship of the boundary offset, the boundary coordinates at each time position are adjusted point by point. By continuously connecting the boundary offsets, a continuous change relationship of the boundary coordinates is formed. The adjusted boundary coordinates are then connected and organized within the time segment to form a continuously changing trajectory.

9. The method for extracting shoreline hydrophilic spatial structure features based on remote sensing image analysis according to claim 8, characterized in that, The boundary offset within the time segment is continuously constrained. By keeping the direction of change of the boundary offset of adjacent time positions consistent, the boundary coordinates are uniformly adjusted. Combined with the spatial distribution order of the boundary coordinates, the adjustment results are connected point by point to form a continuous change trajectory and maintain the consistency of the change path.

10. The method for extracting shoreline hydrophilic spatial structure features based on remote sensing image analysis according to claim 8, characterized in that, The boundary coordinate update process guided by a continuously changing trajectory, through spatial alignment and matching adjustments, continuously represents the water body boundary position at the new time location, forming a consistent boundary extraction result. The steps are as follows: Acquire new time-location remote sensing images and analyze them frame by frame. Identify the location of water body boundaries to form boundary coordinates, and express them using a spatial reference consistent with the continuously changing trajectory. Receive the boundary coordinates, and perform point-by-point correspondence between the boundary coordinates and the end boundary coordinates in the continuously changing trajectory. Form a correspondence relationship through spatial arrangement to complete the alignment process. The alignment process involves adjusting the boundary coordinates point by point along the continuously changing trajectory, and then updating the matching results to form a continuously changing relationship. The linkage matching update results incorporate the boundary coordinates into the continuously changing trajectory, and form a continuous and consistent boundary extraction result by connecting them in time sequence.

Images