133 results about "Shore zone" patented technology

The invention provides a digital twin model correction method and system based on machine vision. The method comprises the steps that a comprehensive data set is constructed by collecting sounding data, tidal flow velocity data and unmanned aerial vehicle images, wave disturbance deviation and water surface reflection distortion are eliminated based on geometric feature matching, and a dynamic compensation coefficient is generated in combination with tidal parameters; after time deviation of sounding data is corrected, a dynamic incidence relation between terrain elevation and sediment migration rate is calculated, a digital twinborn model fusing sedimentary layer thickness distribution and tidal flow velocity driven erosion boundary prediction is established, and a visual terrain curved surface is generated; through reverse verification of real-time sediment accumulation characteristics and terrain curved surfaces, migration rate weight parameters are adjusted in a self-adaptive mode, and dynamic optimization of the model is achieved. High-precision dynamic coupling simulation of sea area terrain evolution and sediment migration is achieved, the real-time performance and reliability of island surface change prediction are improved, and coastal zone safety and economic collaborative decision making is supported.

The invention discloses a coastal zone carbon sink data acquisition management system and method, and particularly relates to the technical field of carbon sink evaluation, and the method comprises the following steps: dividing carbon flux parameter partitions based on vegetation types, sediment characteristics and historical carbon storage levels, and establishing initial reference values; plant biomass, soil organic carbon content and non-carbon dioxide greenhouse gas flux are regularly collected according to fixed sampling points, and a carbon sink observation data sequence is formed; when data exception triggers an evaluation process, generating a carbon sink credibility index and an ecological interference response index; inputting the two indexes into a prediction model to output an adjustment vector, generating an adjustment strategy in combination with a weight, and dynamically updating an initial carbon flux reference value of each partition; according to the method, regionalized management is realized by constructing carbon flux parameter partitions, a carbon sink observation data sequence is established, an evaluation index is dynamically generated, intelligent updating of a carbon flux reference value is completed in combination with a prediction model, and the precision, responsiveness and adaptive adjustment capability of carbon sink monitoring are improved.

The invention discloses a vegetation-submerged embankment coupled tough coast protection method and system and a storage medium, and the method comprises the steps: firstly, determining a research region, and systematically collecting the near-shore terrain, water and sand power conditions, vegetation parameters and other data; secondly, constructing a water-sand-vegetation coupling numerical simulation model based on the collected data, and performing precision verification on the model; then selecting a suitable vegetation type in combination with environmental characteristics of the research area, carrying out artificial seeding and planting work in a vegetation potential habitat of the tidal flat, and determining a design elevation and an offshore distance of the submerged dike; and finally, evaluating the coast protection effect under the synergistic effect of the submerged embankment and the vegetation, and quantitatively analyzing the improvement degree of the coast protection effect on wave attenuation and beach stability. A sustainable tough coast protection system can be formed under the climate change background through a collaborative protection mechanism integrating natural vegetation and an artificial submerged embankment. The method has the advantages of low cost, remarkable wave reduction effect and the like, and the capability of coping with climate change challenges and comprehensive protection of coastal zones can be effectively improved.

The invention provides a tidal flat evolution prediction method and system based on a hybrid model, and relates to the field of dynamic geomorphology and artificial intelligence cross technology, and the method comprises the steps: constructing a tidal flat erosion and deposition evolution database under different scenes of a target coastal zone; constructing a landform prediction model through an artificial intelligence algorithm based on the database, and taking hydrodynamic characteristic data as input and seabed erosion and deposition variation as output; hybrid simulation is executed based on the physical mechanism model and the landform prediction model, and long-duration evolution prediction is realized by updating terrain boundary conditions through loop iteration; and the configuration service application module is used for receiving user input parameters through the interactive interface and outputting a visual result. According to the method, traditional hydrodynamic force-sediment-landform coupling calculation is decoupled into a physical mechanism and AI coordinated chain process, the calculation complexity is remarkably reduced, offline rapid calculation business of tidal flat evolution is achieved, and real-time technical support is provided for coastal zone planning and disaster prevention decision making.

The invention discloses a tidal flat automatic extraction method fused with an irregular hexagonal grid. The method comprises the following steps: step 1, constructing a time sequence remote sensing data set; step 2, establishing a precision verification sample library; step 3, screening spectral indexes; 4, synthesizing an extreme tide level image; 5, generating an irregular hexagonal grid; step 6, carrying out adaptive threshold segmentation; step 7, secondary elimination of confused ground features; step 8, tidal flat range extraction and precision verification; according to the method, based on a time sequence remote sensing image set, pixels at all positions are screened through a specific spectral index maximum value, a new extreme tide level image is formed through combination, spatial heterogeneity of a complex coastal zone is adapted through an irregular hexagonal grid and a bottom-to-top hierarchical merging strategy, local self-adaptive threshold segmentation is achieved in cooperation with a local Otsu algorithm, and a new extreme tide level image is obtained. The optimal grid scale is automatically determined by means of an elbow method, and the confused ground features are secondarily eliminated through the time sequence standard deviation, so that the problem of miscarriage of the confused ground features is effectively solved, and high-precision full-automatic extraction of the tidal flat is realized.

The invention relates to the technical field of coastal zone renovation and repair, in particular to a siltation promotion device for coastal zone renovation and repair, which comprises a siltation promotion assembly and a caisson which are sequentially arranged from top to bottom, the siltation promotion assembly comprises a plurality of siltation promotion modules which are connected through side edges, and the top side of the siltation promotion assembly is used for being fixedly connected with a coast; each siltation promotion module comprises a frame and a plurality of anti-flow plates, the multiple anti-flow plates are sequentially arranged in the frame from top to bottom, the two ends of each anti-flow plate are rotationally connected with the two opposite sides of the frame correspondingly, and every two adjacent siltation promotion modules are rotationally connected through one side edge of the frame; a sedimentation cavity is formed in the top of the caisson, a permeable material is arranged in the sedimentation cavity, flow guide holes penetrating through the two sides are formed in the upstream face and the downstream face of the caisson correspondingly, and the bottom side of the siltation promotion module is connected with the caisson and located above the sedimentation cavity; the siltation promotion device is formed in a splicing mode, the siltation promotion device can be well suitable for complex terrains, and the anti-flow plate is arranged to effectively resist water flow impact.

The invention provides a submarine topography and land elevation matching method based on multi-source data fusion, and belongs to the technical field of geographic information technology and ocean engineering cross fusion. Seamless splicing of sea and land topographies is realized through multi-source data preprocessing, topographic feature correlation extraction, dynamic compensation matching and adaptive weight fusion; according to the method, the problems of data heterogeneity, dynamic environment adaptability and insufficient feature association can be solved, the matching precision can reach + / -3cm, the processing efficiency is also improved, and the method is suitable for coastal zone modeling, ocean engineering and other scenes.

The invention relates to a coastal zone mangrove forest biomass prediction method and device, a storage medium and equipment, and the method comprises the steps: obtaining the image data of a target region and the text description information of the image data, extracting a visual feature vector of the image data based on a pre-trained image feature extraction model, and carrying out the prediction of the biomass of a mangrove forest based on a normalized vegetation coefficient and the image data; the method comprises the following steps: acquiring a visual feature vector, acquiring a spectral feature vector, fusing based on text description information and knowledge graph information to obtain a text feature vector, splicing the visual feature vector, the spectral feature vector and the text feature vector to obtain a fusion feature vector fusing multiple modes of vision, spectrum, text and knowledge graph, and then based on the fusion feature vector, obtaining a fusion feature vector based on the fusion feature vector. And the predicted biomass is obtained by using the trained biomass prediction model, so that the accuracy of predicting the biomass of the mangrove forest in the coastal zone is improved.

The invention belongs to the technical field of remote sensing image data processing, and relates to a multi-feature fusion coastal zone culture pond extraction method, which comprises the following steps: obtaining spectral features and polarization features based on an obtained Sentinel-1 image and an obtained Sentinel-2 image; calculating and evaluating an NDWI time sequence based on the NDWI to generate a time sequence synthesis NDWI image; a water body main body is obtained through the hierarchical feature fusion decision tree; obtaining morphological characteristics based on the water body object; obtaining the chlorophyll a concentration and the dynamic characteristic factor of the chlorophyll a concentration based on the Sentinel-2 image; and extracting a culture pond through a random forest classifier, and generating a culture pond spatial distribution diagram. According to the method, the spectral features, the polarization features, the morphological features, the chlorophyll a concentration and the chlorophyll a concentration dynamic feature factors are fused, and the decision tree and the random forest classifier are fused through the hierarchical features, so that the problems of low accuracy and poor stability of existing culture pond extraction are solved.

The invention discloses a coastal zone planning method and system based on MaXent and hotspot analysis, and relates to the technical field of coastal zone planning. Comprising the following steps: S1, collecting environment variable data, species distribution data and development intensity data, constructing a unified space-time grid system, and realizing time sequence expression of the data through data preprocessing; s2, constructing a quarterly time sequence maximum entropy model, and performing time sequence evaluation on each grid habitat state to form a habitat evolution type; s3, identifying time sequence significant hot spots and hot spot persistence and intensity features, constructing ecological development relationship comprehensive representation, and identifying ecological development conflict types; and S4, spatially superposing the habitat evolution type and the ecological development conflict type to form a self-adaptive access rule, and generating differentiated planning suggestions according to regions. The problem that planning lacks dynamic adaptability due to the fact that coastal zone habitat suitability and development intensity depend on static time point data for a long time and a time sequence evolution rule cannot be recognized is solved.

The invention relates to the technical field of land planning analysis, in particular to a coastal zone land utilization space planning method based on big data analysis, which comprises the following steps: acquiring a multi-time-sequence remote sensing image and environment monitoring data of a planning area, and calculating an ecological safety index of each space unit in the planning area; obtaining economic activity big data and infrastructure data of a planning area, and calculating a land development suitability index of each space unit in the planning area; and establishing a multi-target collaborative game model taking the land utilization demand and the occupancy identifier as constraint conditions, and finally generating and outputting an optimal coastal zone land utilization space planning scheme. According to the method, the real interpretability of the model is improved, rapid adaptation can be conveniently realized through parameter configuration in different regions and different policy tendencies, and the method has high transportability and engineering deployment value.

The invention discloses a water depth inversion and coastal zone topographic surveying and mapping method based on a laser radar, and the method is applied to a surveying and mapping instrument mounted on a small unmanned helicopter, and achieves the quick and accurate measurement of the coastal zone topography. The surveying instrument comprises the following instruments: a laser radar, a camera, an inertial measurement unit and a global positioning unit. The method comprises the following steps: completing internal and external parameter calibration of each sensor on a surveying instrument; using the unmanned aerial vehicle to mount the surveying instrument to the to-be-measured area, and moving to obtain topographic data of the to-be-measured area; preliminarily constructing an odometer by using Kalman filtering, and constructing a land topographic map; the method comprises the following steps: recording motion characteristics of sea waves by using a laser radar point cloud elevation, obtaining a laser radar point cloud elevation program sequence, obtaining the water depth of an offshore sea area through a cBathy water depth estimation algorithm, and converting the water depth into a sea area topographic map; and combining the two topographic maps into a complete coastal zone topographic map based on the geographic coordinates.

The invention discloses an element quantitative fusion-based urban coastal zone landscape evaluation and prediction method, which comprises the following steps of delimiting a vector boundary of a target urban coastal zone based on land change data, and dividing an area covered by the vector boundary into a plurality of grid units; associating the preprocessed spatial element data to the corresponding grid units, and constructing a structured spatial database; establishing a multi-element quantitative index system, calculating a combined weight, and outputting a comprehensive evaluation score of each grid unit through weighted summation; calculating global and local Moran's I indexes based on the comprehensive evaluation score, and identifying a spatial aggregation region and an abnormal region with statistical significance; obtaining dynamic monitoring data in a coastal zone range of a target urban area, and updating the structured spatial database; and based on the updated structured spatial database, comprehensively evaluating the score and the recognition results of the spatial accumulation area and the abnormal area, and generating an evaluation and prediction result.

The invention belongs to the technical field of image processing, and discloses a coastal zone ground feature coverage information extraction method and system based on a remote sensing cloud platform. Multi-source remote sensing data are integrated, and a standardized image is generated after preprocessing; an improved U-Net model is constructed, an encoder of the improved U-Net model adopts a residual convolution module to enhance feature extraction, a decoder recovers details through bilinear interpolation up-sampling and jump connection, the segmentation precision of an artificial shoreline and a natural shoreline is optimized in combination with a weighted cross entropy loss function, and the recognition robustness of a complex ground feature coverage area is improved; and superposing the coastline segmentation result and the ground feature classification data space, generating a vector result, and verifying the precision through a comprehensive evaluation system fusing multiple indexes. According to the method, high-precision extraction of coastal zone ground feature information is realized, and technical support is provided for ocean space planning and implementation and coastal zone resource management.

The invention relates to the technical field of water environment monitoring and water ecological protection, solves the technical problem that hydrology, water quality, vegetation and bottom mud monitoring are mutually dispersed and are difficult to correspond in the prior art, and particularly relates to a lakeside microenvironment composite monitoring pile and an ecological disturbance evaluation method. The composite monitoring piles sequentially comprise an overwater area, a variable water level zone monitoring area and an underwater area in the vertical direction, the bottoms of the composite monitoring piles are fixed to bottom mud, the multiple composite monitoring piles are arranged according to the water depth gradient of 0-20 cm, 20-50 cm and 50-100 cm, a hydrodynamic force disturbance index and a microenvironment response index are established by comparing base line and disturbance working condition monitoring results, a composite ecological disturbance index is established, and the water level zone monitoring area and the water level zone monitoring area are located in the bottom mud. The method is used for quantitatively evaluating lakeside disturbance intensity and engineering measure effects. According to the method, quantitative and graded evaluation of the ecological disturbance degree of the lakeside zone is realized, and a scientific basis is provided for lakeside zone revetment form optimization, ecological restoration measure arrangement and water function zone management.

The invention relates to a coastal zone sediment erosion pore scale flow field observation system and observation method. The observation system comprises a wave-flow water tank, a sediment accumulation body arranged in the wave-flow water tank and PIV equipment used for observing the internal flow field and the pore size of sediment. A wave making plate and a wave dissipating plate opposite to the wave making plate are arranged in the wave flow water tank, experimental fluid used for simulating waves is arranged between the wave making plate and the wave dissipating plate, and a wave height meter floats on the experimental fluid; the sediment accumulation body is formed by accumulation of transparent solid particles with the same refractive index as the experimental fluid; the PIV equipment comprises a laser light source and a camera, the laser light source is focused on the sediment accumulation body, and the camera directly faces the sediment accumulation body and is used for collecting images. Compared with the prior art, a clearer sediment pore internal flow field image is obtained through the combination of the refractive index matching technology and the image particle velocity measurement method, so that effective observation of the pore scale flow field eroded by the sediment in the coastal zone is realized.

The invention provides a coastal zone land coverage type classification method based on a random forest and a topology rule, and belongs to the technical field of coastal zone land coverage type classification. The method comprises the following steps: based on a GEE cloud platform, integrating a multispectral remote sensing image and elevation data, extracting spectral features and geographic features, and realizing pixel-level classification of random forest machine learning; generating a clustering unit through a simple non-iterative clustering method, and performing object-oriented special classification on the water body and the aquaculture pond in combination with spectral and morphological characteristics of the clustering unit; spatial filtering is introduced to remove salt and pepper noise, a coastal zone ground feature topology rule base is established to carry out spatial logic verification, and coastal zone land coverage classification with high precision and reasonable spatial layout is realized. According to the method, the multi-source remote sensing data and the multi-level classification strategy are fused, the problems of coastal zone ground feature spectrum confusion, boundary fuzziness and space logic inconformity are effectively solved, the classification precision and practicability are remarkably improved, and the method is suitable for land coverage monitoring and management of the complex coastal zone environment.

The invention discloses a near-coastal zone geological survey data management system and method, and relates to the technical field of coastline monitoring, and the method comprises the following steps: collecting a remote sensing image of a near-coastal zone, and carrying out the preprocessing of the remote sensing image, and obtaining a first coastal remote sensing image; extracting a remote sensing image of the land and water contact area based on the first coastline remote sensing image to obtain a second coastline remote sensing image, and performing first coastline extraction processing to obtain first coastline information; performing second coastline extraction processing based on the second coastline remote sensing image to obtain second coastline information; performing coastline correction processing based on the first coastline information and the second coastline information to obtain real-time coastline information; the method is used for solving the problem that when a water body and land in an image are distinguished based on a remote sensing image and a spectral index in an existing coastline monitoring technology, seawater and a tidal flat cannot be accurately distinguished in the tide rising and falling process, and the coastline cannot be accurately identified.

The invention discloses a coastal zone human activity interference remote sensing quantification and ecological profit and loss evaluation method and device, belongs to the technical field of remote sensing monitoring, and solves the problems of low efficiency due to dependence on field investigation and insufficient reliability caused by separation of ecological evaluation and remote sensing data in the prior art. The method is characterized by comprising the following steps: acquiring two-stage multispectral remote sensing images containing multiple wavebands such as blue light at an interval of 5-10 years and with spatial resolution of 10-30m, and synchronously integrating tide, elevation and geological background data; eliminating environmental errors of image radiometric calibration and atmospheric correction; calculating a normalized building index based on the short-wave and near-infrared band reflectivity, and detecting a quantized interference area in combination with land utilization classification change; and the change area and the corrected intensity change value are extracted and input into an ecological system service value model, and an evaluation result is output by using a unit area value equivalent factor method. According to the method, full-process remote sensing automatic processing is realized, field investigation is avoided, the difference adjustment cost is effectively reduced, and the pertinence of management decision is remarkably improved.

The invention discloses a coastal zone ecological safety early warning method and system based on big data, and relates to the technical field of big data analysis, and the method comprises the steps: determining a coastal type through remote sensing and geological map spots, carrying out the ecological multi-source data collection according to the coastal type, and carrying out the data preprocessing; based on preprocessed data, a sparse attention mechanism is combined with an LSTM network, key ecological factors are dynamically recognized, and ecological index trends are predicted, the time causal relationship between ecological variables is recognized through a Granger causal test method, the root cause traceability of early warning is improved, information granulation modeling is combined, and the early warning efficiency is improved. According to the method, the processing capacity of the system on nonlinear and fuzzy information is enhanced, the stability and adaptability of an early warning model are improved, through conditional transfer entropy analysis, intermediary interference is effectively eliminated, the accuracy of causal identification is ensured, and finally accurate identification, interpretable early warning and scientific intervention on coastal zone ecological safety problems are achieved.

The invention discloses a portable coastal zone shallow layer columnar sampler, and relates to the technical field of samplers, the portable coastal zone shallow layer columnar sampler comprises a sampling barrel, the bottom end of the sampling barrel is fixedly provided with a vertical cone, the inner side of the sampling barrel is movably connected with a sampling barrel, and one end, protruding out of the sampling barrel, of the sampling barrel is fixedly provided with a guide seat; an assembling cylinder is fixedly installed at the end, away from the sampling cylinder, of the guiding base, a drill bit body is detachably installed on the assembling cylinder through an assembling mechanism, a separating mechanism used for solid-liquid separation is further arranged on the sampling cylinder, and the assembling mechanism comprises a balance weight lantern ring movably connected to the outside of the assembling cylinder; during use, through the replaceable adaptive drill bit, counter weight auxiliary pressing and elastic rubber sleeve anti-contact design, the drill bit is adaptive to different hard impurity soil, drilling resistance is reduced, part loss is reduced, the drill bit is detachable and convenient to carry, the service life of the drill bit is prolonged, the service life of the drill bit is prolonged, and the service life of the drill bit is prolonged. And the suitability, the portability and the durability are improved.

The invention provides a natural shoreline and mangrove forest supervision method and system based on video recognition, and the method comprises the steps: S1, installing and deploying information collection equipment, and setting a preset position and a cruise plan according to different monitoring targets; s2, accessing original sample data acquired by information acquisition equipment, reinforcing an original sample data set through a three-level data enhancement framework, and constructing a shoreline target sample data set; s3, optimizing by taking the YOLOv8n model as a basic model, and constructing a shoreline target recognition model; s4, constructing a target entity-spatial constraint-ownership state triple verification rule fusion judgment model as a behavior recognition model; and S5, inputting a recognition result of the shoreline target recognition model into a behavior recognition model, judging an illegal behavior through a triple verification rule, and generating early warning information. According to the invention, the working efficiency of natural shoreline supervision can be improved, and a replicable solution is provided for fine management of the coastal zone and the mangrove forest.

The invention discloses a multi-spectrum and SAR cooperative sensing sea reclamation increment remote sensing detection method, and belongs to the technical field of land change remote sensing monitoring. According to the scheme, multi-spectrum and SAR satellite data are fused, the data advantages of optical images and synthetic aperture radar images are effectively combined, and through the wave band operation and threshold segmentation technology, the real-time performance of the sea reclamation increment is improved. According to the method, more detailed and reliable sea reclamation pattern spot information can be obtained, the spatial distribution and dynamic change of suspected sea reclamation pattern spots can be accurately identified, and the limitation that traditional optical remote sensing is interfered by cloudy and rainy weather is effectively overcome. The method is used for a computer program to execute and complete multi-source data fusion, change detection and sea reclamation suspected pattern spot detection and analysis, and can be widely applied to the fields of coastal zone ecological environment protection, coastal city planning management, ocean resource sustainable utilization, relevant policy making and the like. And a core technical support is provided for full-process monitoring and scientific decision making of the reclamation activity.

The embodiment of the invention provides a riverside and lakeside zone remote sensing monitoring method and product. The riverside and lakeside zone remote sensing monitoring method comprises the following steps: acquiring historical medium-resolution remote sensing image data and historical high-resolution remote sensing image data; extracting an end member spectrum of a typical ground feature from the historical medium-resolution remote sensing image data; correcting the end member spectrum according to the high-resolution remote sensing image data and eliminating shadow or cloud interference to obtain a target end member spectrum matrix; performing pixel unmixing on the to-be-decomposed medium-resolution remote sensing image data according to the target end member spectrum matrix to obtain a pixel unmixing result; determining a water level amplitude variation area according to the pixel unmixing result and the flooding frequency; determining a coastal zone monitoring range according to the water level amplitude variation area; inputting image data corresponding to the monitoring range of the coastal zone into a wavelet transform U-Net deep convolutional neural network model to obtain a land utilization classification result of the coastal zone; and quantifying the ecological bank zone ratio result of each river reach according to the land utilization classification result of the coastal zone.

The application discloses a coastal zone planning method and system based on MaXent and hotspot analysis, and relates to the technical field of coastal zone planning. The method comprises the following steps: S1, collecting environmental variable data, species distribution data and development intensity data, constructing a unified space-time grid system, and realizing time series expression of the data through data preprocessing; S2, constructing a quarterly time series maximum entropy model, time series evaluating habitat states of each grid, and forming habitat evolution types; S3, identifying time series significant hotspots and hotspot persistence and intensity characteristics, constructing a comprehensive representation of ecological development relationship, and identifying ecological development conflict types; and S4, spatially superimposing the habitat evolution types and the ecological development conflict types, forming adaptive access rules, and generating differentiated planning suggestions according to regions. The problems that the long-term dependence of coastal zone habitat suitability and development intensity on static time point data and the inability to identify time series evolution rules result in the lack of dynamic adaptability of planning are solved.

The invention relates to an island bedrock shoreline safety monitoring and early warning system and method, and belongs to the technical field of coast engineering safety. The system is based on a multi-source heterogeneous data fusion and intelligent decision technology, a sensing-computing-decision closed-loop system is constructed, and the system comprises a multi-parameter sensing array, an edge computing node, a hybrid transmission module, a cloud platform and an early warning terminal. The stress, displacement and environmental parameters of the rock mass are collected in real time by arranging fiber bragg grating, micro-seismic, visual and other multi-mode sensors; data preprocessing and local early warning are achieved through edge calculation, and an early warning threshold value is dynamically optimized in combination with cloud multi-physics coupling analysis; and yellow, orange and red three-level early warning is realized by adopting a grading trigger mechanism, and emergency response equipment is linked. The method breaks through the singleness and hysteresis of traditional monitoring, remarkably improves the early recognition capability of bedrock instability in a complex marine environment, has the characteristics of high precision, high adaptability and low false alarm rate, and can be widely applied to safety protection fields of coastal zones such as islands and ports.

The present invention provides a method for inverting seawater depth that integrates a numerical wave evolution model, comprising the following steps: Step 1: Obtaining the wave number of any sea area using remote sensing imagery; Step 2: Obtaining the characteristic wave period of offshore waves in a specific sea area; Step 3: Calculating the water depth based on the wave number and characteristic wave period using the dispersion relationship corresponding to linear wave theory; Step 4: Calculating the wave height and wave number using a numerical wave model; Step 5: Inverting the wave height and wave number using the nonlinear dispersion relationship to obtain the corrected water depth within the area of ​​interest; Step 6: Calculating the final water depth within the area of ​​interest using the numerical wave model based on the corrected water depth. The bathymetric model developed by the present invention is suitable for sea areas with relatively deeper water depths. In particular, the use of wave number information to obtain water depth significantly improves accuracy compared to methods using remote sensing wave height inversion. Furthermore, this method is fast and applicable to large-scale water depth calculations, making it suitable for rapid surveys of coastal resources.

The application discloses a kind of oyster reef repair methods based on plant material construction attachment matrix, it is related to the technical field of coastal zone ecological restoration.The repair method includes the following steps: S1, selecting plant material, the stem of salt marsh plant is the plant material;S2, the plant material is cut into segments and pretreated, and an attachment matrix assembly is prepared;S3, a plurality of the attachment matrix assemblies are tied and connected to form an attachment matrix unit, the attachment matrix unit is arranged in a matrix, is vertically fixed on the surface of a bearing member, and forms a deployable matrix structure unit;S4, the matrix structure unit is laid in the target repair area, and is fixed to the base by anchoring assembly.The plant material of the application maintains structural durability during the oyster attachment period, and is completely degraded naturally in the later period;It reduces the dependence on hard artificial matrix, has a wide source of materials, is easy to construct, has remarkable repair effect, and is suitable for oyster reef repair in intertidal zone or shallow water area and other areas where natural attachment matrix is lacking.

The invention provides a sea area influence measurement method and device for a coastal zone land area development level, and belongs to the technical field of information suitable for administrative purposes. The method comprises the following steps: generating a plurality of equidistant sampling lines perpendicular to a coastline along the coastline, wherein each sampling line extends a preset distance towards a land area and a sea area; acquiring an intersection point of each sampling line and the coastline as a sampling intersection point SIP; calculating an index average value of all pixels penetrated by each sampling line based on land social economic index data, and assigning the average value to the corresponding SIP to form a land development level point with vertical representativeness; carrying out nearest distance matching operation on a target pixel in the sea area and each SIP (Session Initiation Protocol); and according to the Euclidean distance between the target pixel and the SIP, performing attenuation processing on the land development level represented by the SIP by adopting a Gaussian attenuation function to obtain a sea area social economic influence score of the target pixel, thereby realizing fine description of transmitting the land development level to the sea area.

The invention relates to the technical field of coastal zone ecological restoration, and discloses a tidal creek pattern construction method and a dredged soil ecological utilization method.The tidal creek pattern construction method comprises the following steps that a tidal creek restoration area is selected, and a spacing dam is constructed on the periphery of the restoration area; a drainage water gate is arranged on the water-facing boundary of the spacing dam, the restoration area is filled with dredged soil in a fixed-point hydraulic reclamation mode, and a plurality of mud outlets are formed; a drainage channel is formed in the restoration area through natural drainage or artificial guide drainage; after the dredged soil is solidified, the drainage sluice is dismantled; and lowering or removing a sea-facing boundary structure of the spacing dam to promote formation of a natural tidal creek system. The invention provides an artificial guidance and natural molding coupled tidal creek pattern construction method, and solves the technical contradiction of'manual intervention and natural process collaboration 'in tidal flat habitat restoration.