230 results about "Coastal zone" patented technology

The invention relates to the technical field of environment assessment, in particular to a coastal zone culture area multi-dimensional environment assessment method and a cloud platform. The method comprises the following steps: continuously recording dissolved oxygen concentration, pH value, centigrade temperature, salinity unit, turbidity scattering unit, chlorophyll fluorescence intensity, ammonia nitrogen milligram per liter and nitrite milligram per liter, synchronously calling multi-source remote sensing images covering a culture area and an adjacent water area, extracting remote sensing reflectivity data through image correction and atmospheric correction, and calculating to obtain water color parameters. According to the method, the water quality sensor array is deployed at the key point of the culture area, continuous multi-parameter environmental data acquisition is carried out, multi-source remote sensing images are synchronously integrated, water color information is extracted in real time, and the timeliness and data accuracy of culture water area environmental monitoring are improved; trend decomposition and dynamic baseline construction are carried out based on the data sequence, so that the environmental fluctuation evaluation of the breeding area is more objective and accurate.

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 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 provides a turbid water area mud flat shoreline fine extraction method based on a hyperspectral satellite, and relates to the technical field of image processing, and the method comprises the following steps: S1, obtaining a plurality of Landsat series satellite original hyperspectral satellite remote sensing images according to a research target area and research time; s2, obtaining a preprocessed image; s3, performing multi-scale segmentation on the preprocessed image and calculating a normalized differential water body index of image data; and S4, performing threshold classification on the image after multi-scale segmentation in combination with a normalized differential water body index, adjusting and setting a proper normalized differential water body index, distinguishing a water body from a non-water body, and extracting a shoreline. According to the method, the long-time change rule of the coastline can be better researched and analyzed, the change trend of the coastline can be predicted, a basis is provided for development of coastal areas, and the method has a good application prospect in the fields of coastline research, coastline engineering construction and the like.

The invention discloses an ocean disaster comprehensive decision-making system based on reinforcement learning, and relates to the technical field of ocean disaster analysis, the ocean disaster comprehensive decision-making system comprises an ocean disaster decision-making platform, the ocean disaster decision-making platform is in communication connection with an ocean environment sensing module, a disaster decision-making analysis module, a disaster risk early warning response module and a feedback optimization module, the modules are in electric signal connection; the marine environment sensing module is used for collecting and integrating marine environment data of a target sea area in real time. According to the method, the historical marine environment data and the real-time marine environment data are learned and analyzed through the reinforcement learning model, the early-stage features and evolution trends of marine disasters can be accurately recognized, the occurrence time, intensity and influence range of the disasters can be accurately predicted in advance, and then high-precision early warning information is quickly generated in combination with historical similar scenes, so that the early warning efficiency is improved. And more time is won for precaution preparation for coastal areas, and disaster loss is effectively reduced.

The invention relates to the technical field of seaweed farm restoration management, in particular to an effect evaluation method for ecological restoration of a seaweed farm. Comprising the following steps: analysis diagnosis and early-stage preparation: diagnosing the degradation degree of a seaweed field, carrying out ecological restoration suitability evaluation on the seaweed field, and carrying out monitoring preparation work before restoration; formulating and implementing a scheme, determining a restoration target, formulating a restoration scheme, and selecting a seaweed field restoration mode and a restoration measure; monitoring a repair project; effect evaluation: comprehensively evaluating the restoration effect from the aspects of engineering index completion degree, seaweed field ecological function and social benefit; and feeding back and adjusting. According to the invention, a whole set of work flow for ecological restoration and effect evaluation of the seaweed farm is provided, and effective technical support can be provided for development of ecological restoration and effect evaluation of the seaweed farm nationwide; the requirement for comprehensively and accurately evaluating the restoration effect can be met, benign interaction between ecological protection and economic development is achieved, and sustainable development of coastal areas is promoted.

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 area foundation pit dewatering system and method, and belongs to the technical field of foundation pit dewatering, the coastal area foundation pit dewatering system comprises a foundation pit, a plurality of light well points, a deep tube well and an electroosmosis auxiliary module, and the light well points are annularly arranged in a shallow layer area on the periphery of the foundation pit; the deep tube well extends to a deep area from the ground; and a plurality of electro-osmosis auxiliary modules are arranged in the peripheral clay layer area of the foundation pit. The annularly-arranged light well points evenly intercept shallow underground water around the foundation pit, the deep pipe wells can rapidly reduce the deep underground water level, and the drainage problem of a low-permeability clay layer area is effectively solved through the synergistic effect of the arranged electro-osmosis auxiliary modules and the well points / pipe wells; the synchronous precipitation uniformity of the complex soil layer is improved, layered targeted precipitation design is adopted in a shallow area, a deep area and a clay layer area, and the overall precipitation efficiency is improved. According to the foundation pit dewatering system in the coastal area, the problem that in the prior art, in the environment with complex hydrogeological conditions, the dewatering efficiency of a single dewatering measure is low is solved.

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 invention discloses a wetland ecological restoration method combined with water ecological restoration monitoring, and relates to the technical field of ecological restoration. The method comprises the following steps: acquiring water depths, nitrogen and phosphorus concentrations, dissolved oxygen and biodiversity indexes of a deep water area, a shallow water area and a coastal zone of a wetland through a sensor network, and generating an initial data set; dividing a wetland region by adopting a K-means clustering algorithm, and constructing a classification region feature model; based on the nitrogen and phosphorus concentration and the water depth of each region, configuring plant species, simulating a water flow gallery and optimizing the pollutant removal efficiency; integrating coastal zone data, optimizing the external pollution interception efficiency by using a genetic algorithm, and obtaining an optimal matching parameter; generating a collaborative ecological restoration framework by iteratively adjusting plant parameters, and establishing a comprehensive numerical evaluation model; and a management data set is generated according to an evaluation result, and quantitative optimization of the wetland ecological restoration effect is realized. According to the method, the pollutant removal efficiency can be effectively improved, and collaborative recovery of ecological functions can be ensured.

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 the technical field of pipe fitting welding, and particularly discloses an automobile air conditioner connecting pipeline welding method.The automobile air conditioner connecting pipeline welding device comprises a welding device, the welding device comprises a bottom plate and bearing pipes, the bearing pipes are symmetrically and fixedly connected to the upper surfaces of the two sides of the bottom plate, and sliding rods are symmetrically and fixedly connected to the upper surface of the middle of the bottom plate; the top of the sliding rod is slidably connected with a high-frequency vibration auxiliary welding gun. According to the bronze drum, the rare earth element cerium is added into the welding wire, a local dehumidification device is combined for use, the chloride ion corrosion problem of an automobile air conditioner pipeline in the marine climate environment is effectively solved, the cerium element reacts with invaded chloride ions to generate a stable cerium-chlorine compound protection layer, the corrosion path is blocked, and the corrosion resistance of the automobile air conditioner pipeline is improved. And meanwhile, the welding environment humidity is strictly controlled to be below 30% through the local dehumidification device, the condition that water participates in electrochemical corrosion is eliminated from the source, stress corrosion cracks are completely eliminated, and the durability of the welding structure in the coastal area is remarkably improved.

The invention discloses an anti-corrosion method for a low-pressure steel pipe pole in a coastal area, which comprises the following steps: arranging a spiral grain pavement on the outer wall of the steel pipe pole, and sequentially arranging an outer anti-corrosion layer I, an outer anti-corrosion layer II and an outer anti-corrosion layer III from inside to outside after a micron-sized honeycomb porous structure is formed on the spiral grain pavement; the inner wall of the steel pipe pole is provided with a net-shaped grain surface, and after a micron-sized honeycomb porous structure is formed on the net-shaped grain surface, an inner anti-corrosion layer I, an inner anti-corrosion layer II and an inner anti-corrosion layer III are sequentially arranged from inside to outside; wherein flow guide grooves are formed in the spiral grain surface and the net-shaped grain surface and are used for discharging penetrating fluid; according to the anti-corrosion method provided by the invention, the anti-corrosion performance is synergistically enhanced through multiple mechanisms, and the overall corrosion resistance is remarkably improved by combining the design of the composite coating with layered inner and outer walls with multiple mechanisms such as chemical passivation, sacrificial anodes and physical shielding.