106 results about "Mangrove" patented technology

The invention relates to the technical field of mangrove forest protection, in particular to a forest protection fence based on biophysical coordination and a prevention and control method thereof.The forest protection fence comprises a plurality of supporting components and an annular protection screen body, the multiple supporting components are arranged around target plants and form an annular supporting system, and each supporting component comprises a supporting rod and an expansion supporting assembly; the supporting rods are vertically arranged, the lower ends of the supporting rods can be inserted into a soil layer, the extension supporting assemblies are arranged on the supporting rods and can partially enter the position below the soil layer along with the supporting rods, and the extension supporting assemblies between every two adjacent supporting components can be connected in a matched mode. The annular protective screen body is connected with the annular supporting system and at least partially extends below the soil layer; through cooperation of the supporting component and the annular protective screen body, benthonic organisms around the target plant can be limited to move in the preset area, and growth of the target plant is assisted through movement of the benthonic organisms. According to the technical scheme, the growth of the target plant is protected by virtue of the cooperation of benthic organism activity, the supporting component and the annular protective screen body.

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 relates to the technical field of seedling transplanting, and discloses mangrove forest seedling transplanting equipment which mainly comprises a high-pressure water gun integrated with a high-pressure water pump, a bearing mechanism mounted on a gun barrel and a water inlet head. The bearing mechanism is provided with a clamping assembly for clamping stems of seedlings and a bearing table for bearing roots of the seedlings, and is provided with an ejection assembly in a matched mode. Through mechanical linkage of a sliding sleeve, a driving plate, a movable connecting rod and a bearing disc, when a lifting rod is operated, the ejection assembly can automatically complete the actions of firstly opening a clamping assembly to release a stem and then ejecting the bearing disc to support the root of a seedling in sequence. During working, a high-pressure water gun is used for spraying water flow to impact on the mud flat to form a planting pit, and seedlings are placed at the bottom of the pit without damage in a water-rich environment. The problem that traditional manual transplanting easily causes mechanical damage to seedling rhizomes is solved.

A mangrove forest extraction method based on a multi-source data time sequence comprises the steps that 1, a remote sensing image of a research area is acquired and preprocessed; 2, after the image is preprocessed, index features of the image are obtained through wave band calculation; 3, mangrove forest and non-mangrove forest pixel points are manually selected to serve as time sequence sample point positions, and meanwhile an index time sequence curve of the sample points is extracted; 4, inputting the sample point time sequence curve into a convolutional long short-term memory network, and training a mangrove forest extraction model; and 5, extracting an index time sequence of all pixels in the mangrove forest extraction region, inputting the index time sequence into the mangrove forest extraction model, and extracting a mangrove forest distribution range. According to the method, the advantages of various data sources are combined, the mangrove forest growth background and the time sequence dynamic characteristics are considered, the mangrove forest planting range is extracted through the multi-remote-sensing-index time sequence, the robustness of the model in a complex environment is improved, and the problems that the mangrove forest range boundary is unstable and is easily interfered by the environment are solved.

The invention provides a mangrove forest degradation type and reason identification method and system based on remote sensing and a multi-factor index system. The method comprises the following steps: firstly, integrating a multi-temporal remote sensing image, ecological monitoring data and ground survey data, and constructing a systematic degradation factor index system covering natural, climate, biological and human factors; secondly, extracting typical degradation characteristics such as vegetation coverage decline and species composition change by using a remote sensing change detection technology and a principal component analysis method; then, through K-means clustering, an ecological classification algorithm based on rules and an ecological threshold standard, mangrove forest degradation types are identified and classified, and the types comprise a man-made interference type, a biological erosion type, a natural succession type and a multi-factor coupling type; then, adopting a supervised machine learning model and combining a feature importance evaluation method such as a Shapley value to identify a degradation cause and a weight thereof; and finally, verifying the precision of the model through an on-site monitoring quadrat and an expert interpretation result, and outputting visual results such as a degradation type distribution diagram, a factor contribution distribution diagram and the like.

The invention provides a mangrove forest dense time sequence detection method and device, and relates to the technical field of target recognition, and the method comprises the steps: obtaining a radar image and an optical remote sensing image of a to-be-detected region; calling a pre-constructed double-branch feature extraction network to independently perform feature extraction on the radar image and the optical remote sensing image to obtain radar features and optical remote sensing features; performing feature fusion on the radar feature and the optical remote sensing feature to obtain a first fusion feature; sSMI features are calculated based on the radar and optical remote sensing image reflectivity data; performing feature fusion on the first fusion feature and the SSMI feature to obtain a second fusion feature; a pre-constructed target network is called to process the second fusion feature, a candidate detection result is obtained, and the target network is used for recognizing the change position and the change type of the target object at the same time; and performing space-time consistency correction on the candidate detection result to obtain a detection result for output.

The invention discloses Moraxella roselle MT01 and application thereof in CO2 fixation and / or sediment carbon emission reduction, and belongs to the technical field of microorganisms. According to the invention, a strain of Moraxella roselle MT01 is obtained through screening and identification, and the preservation number is CCTCC (China Center For Type Culture Collection) NO: M 20252028. Through verification, the strain MT01 contains two key carbon sequestration genes, namely fhs and cbbM; whether the strain MT01 has the carbon sequestration capability or not is detected by using isotope, and the result shows that delta 13C exceeds 60 per thousand; the carbon sequestration capability of the strain MT01 is detected by adopting sediment carbon emission reduction, the result shows that the strain MT01 can obviously reduce the emission of CO2 in mangrove forest sediment, and the emission reduction efficiency is about 16.9%. The invention provides new strain selection and technical basis for microbial carbon sequestration.

The invention discloses a mangrove forest protection effect intelligent evaluation and scene prediction system, and relates to the field of ecological environment information intelligence, and the system comprises a key driving factor recognition module which is used for determining a core variable influencing the protection effect and a dynamic response interval of the core variable based on a statistical analysis and nonlinear fitting method; the protection effect quantitative evaluation module is used for calculating a net improvement effect of protection intervention by comparing ecological index differences inside and outside the protection area; the causal effect analysis module is used for separating independent contributions of natural factors and artificial protection by adopting a dual machine learning framework; the space-time dynamic modeling module is used for performing uncertainty modeling on the space-time evolution of the ecological indexes by using a Bayesian hierarchical structure; and the multi-scene prediction module is used for realizing ecological response prediction under multi-factor driving and supporting input and simulation of user-defined scenes. According to the scheme, multi-dimensional and high-precision evaluation and future trend reliable prediction of mangrove forest protection effects can be realized.

The invention discloses an artificial mangrove forest pest monitoring and early warning method and system, and belongs to the technical field of ecological environment monitoring, and the method comprises the steps: collecting multi-frequency pest acoustic signals and low-altitude thermal infrared image data, constructing a pest energy density field, and forming a multi-dimensional propagation feature matrix; establishing a pest risk node map based on the matrix, simulating a propagation path and calculating a pest energy coupling strength coefficient; carrying out energy refraction remapping and abnormal superposition region identification, extracting an energy convergence core region, and generating a propagation trend trajectory diagram; constructing a combined prediction model of the microscopic infection characteristics and the macroscopic diffusion situation of the insect pests, outputting an evolution stage risk curve, and identifying secondary outbreak latent points; the method has high adaptability, high accuracy and response preposition, and the intelligent level of mangrove forest pest monitoring and early warning is remarkably improved.

The invention discloses a mangrove forest recognition method and system based on ensemble learning, and relates to the technical field of remote sensing data processing.A mangrove forest integrated recognition model driven by feature indexes is constructed, and the model takes various heterogeneous random forest models, gradient elevator models, support vector machine models and K neighbor models as base classifiers; the mangrove forest identification method effectively utilizes respective learning capabilities for different data models, reduces single model deviation, and then couples with the meta-classifier comprising the logistic regression model, so that the classification performance of the model can be further improved, the mangrove forest identification efficiency and accuracy are remarkably improved, and the mangrove forest identification efficiency and accuracy are improved. And meanwhile, the adaptability and the recognition capability of the model under a complex background condition 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.

This invention relates to a method for constructing a biodegradable mangrove ecological island based on dynamic tidal energy regulation, and an artificial island siltation device. The artificial island siltation device includes a bamboo gate system, a hemp rope net system, a fixed pile system, and a limiting system. A dynamic filtration structure is formed by the liftable bamboo gate and the hemp rope net. Utilizing the buoyancy difference and water flow velocity changes generated by tidal rise and fall, a synergistic effect is achieved: accelerating the passage of sediment-laden water during high tide and promoting siltation during low tide. A fully biodegradable material is used to construct a growing silt body. The buoyancy balance is regulated by the bamboo joint holes, ensuring the device remains suspended on the surface layer of the silt body. This allows for continuous siltation and elevation of the tidal flat, forming an artificial island that provides a site for mangrove seedling planting and meets the required daily sunrise duration for mangrove growth. The method and device of this invention have technical advantages such as low construction cost, dynamic adaptation to tidal changes, and avoidance of secondary pollution.

The present application relates to the technical field of climate change warning, and discloses a mangrove blue carbon ecological risk identification and warning method and system for climate change, comprising the following steps: acquiring time series of global land surface characteristic satellite leaf area index data and environmental factors, performing detrending, deseasonalization and standardization processing to extract abnormal sequences; determining climate oscillation windows and neutral periods according to multivariate El Nino-Southern Oscillation index and dipole mode index, and calculating the mean value of the environmental factors in the neutral period as a reference; inputting the environmental factors into a long short-term memory network to extract attention weights, calculating the factor difference between the mean value of the climate oscillation window and the reference, mapping the factor difference by using a nonlinear saturation kernel function, combining the weights to obtain contribution amplitude, and selecting a dominant risk factor by comparing the direction; processing the absolute value of the leaf area index anomaly by using an S function to output risk intensity, and predicting future leaf area index anomaly based on the dominant risk factor to generate a warning evaluation.

This invention provides a method and apparatus for detecting dense mangrove forests over time, relating to the field of target recognition technology. The method includes: obtaining radar images and optical remote sensing images of the area to be tested; using a pre-constructed dual-branch feature extraction network to independently extract features from the radar images and optical remote sensing images, obtaining radar features and optical remote sensing features; fusing the radar features and optical remote sensing features to obtain a first fused feature; calculating SSMI features based on the reflectivity data of the radar and optical remote sensing images; fusing the first fused feature and the SSMI feature to obtain a second fused feature; using a pre-constructed target network to process the second fused feature to obtain candidate detection results, wherein the target network is used to simultaneously identify the changing location and type of change of the target object; and performing spatiotemporal consistency correction on the candidate detection results to obtain the detection results for output.

The application provides a mangrove damage early warning method and system based on remote sensing, comprising the following steps: determining a research area and constructing a spatial index database; determining a baseline period and a mangrove distribution area; extracting a vector boundary layer from the mangrove distribution area according to the baseline period, thereby constructing a baseline database; downloading the latest remote sensing image of the research area every month from the baseline period, and calculating NDVI of each latest remote sensing image, thereby forming a time series NDVI dataset; comparing the difference between the monthly NDVI and the NDVI of the same period of the previous year based on each grid unit in the spatial index database; determining the mangrove damage risk according to the difference result; the early warning response is more timely and accurate; and the method is simple and easy to implement automatically.

The invention relates to the technical field of tree height statistics, in particular to a mangrove forest tree height estimation method and device, equipment and a medium. According to the method, the spectral band, the topographic feature and the radar backscattering feature of the boundary area where the mangrove forest is located are collected, and the tree height mean value of the mangrove forest in the boundary area is estimated through the spectral band, the topographic feature and the radar backscattering feature. As the topographic features and radar back scattering are satellite remote sensing data acquired by the radar, the spectral band is data acquired by the spectral imager sensor, and the radar can acquire the satellite remote sensing data of any boundary area where the mangrove forest is located, even if the boundary area is located in a shallow sea area, the data can be accurately acquired. Therefore, the method for estimating the height of the mangrove forest is not limited by the growing environment of the mangrove forest. And the tree height is estimated by adopting the multi-source satellite remote sensing data, so that the accuracy of the tree height estimation value can be improved.

The utility model relates to the technical field of ocean engineering discloses a kind of ecological breakwater of submerged dike, artificial reef and mangrove composite, including artificial reef, the inside of artificial reef is provided with submerged dike, the outside of submerged dike is fixedly connected with node column, the node column is fixedly connected in the inside of artificial reef, the side of artificial reef is fixedly connected with mangrove bottom protection, the top of mangrove bottom protection is provided with multiple mangrove, artificial reef is hollow triangular structure, the top angle of artificial reef is 60 degrees, submerged dike is triangular structure, the top angle of submerged dike is 60 degrees.In the utility model, under the combination of submerged dike, mangrove and artificial reef, through double wave dissipation effect, effectively reduce the erosion of wave to structure, enhance the dissipation ability of hydrodynamic force, promote ecological restoration, reduce scour, enhance overall stability, prolong service life.

The present application relates to a kind of improved radiation transmission model mangrove chlorophyll estimation method, comprising: the measured data of the tree height, crown width and leaf area index of mangrove are collected;Mathematical relationship between leaf area index and tree height, crown width is constructed;Simulated spectral data is generated as training set using improved radiation transmission model;The sensitive feature screening of mangrove functional traits is carried out;Random forest inversion model based on physical constraint is constructed;The present application estimates the chlorophyll content of mangrove using the random forest inversion model based on physical constraint.The beneficial effects of the present application are: the present application can effectively improve the precision of chlorophyll inversion, provide scientific basis for the fine inversion of mangrove chlorophyll, provide data support and decision-making reference for the protection and scientific management of mangrove.

The invention relates to the technical field of mangrove forest planting, in particular to a mangrove forest seedling field planting assisting method.The mangrove forest seedling field planting assisting method comprises a base rod and a buckle assembly, a telescopic rod is fixedly installed at the top end of the base rod, and the telescopic rod is composed of a head end, a tail end and a plurality of telescopic joints; a buckle assembly is fixedly installed on the outer wall of the telescopic joint close to the tail end and the outer wall of the head end, and two clamping plates capable of linearly moving and two rotatable arc-shaped plates are arranged in the buckle assembly. Through cooperation of the double-face threaded pipe, the second ventilation pipe, the telescopic pipe, the threaded piece and the two-way drill bit piece, the threaded piece is driven by air pressure in the second ventilation pipe to linearly move, meanwhile, the threaded piece can rotate through a threaded groove in the double-face threaded pipe, then the two-way drill bit piece is driven to rotate and linearly move, and the soil drilling capacity of the two-way drill bit piece is improved; and meanwhile, the soil grabbing capacity of the base rod is improved, the insufficient stability of the base rod is avoided, and the practicability of the device is improved.

The utility model discloses a mangrove forest monitoring camera, which comprises a casing, a camera, a sensor module, an infrared lamp, a signal transmission module, a control module and a power supply. When the sensor module senses darkening of ambient light, the control module controls the infrared lamp to be started to emit infrared light, and when people or animals within a certain range are sensed, the control module controls the camera to be started to shoot; when the sensor module senses that ambient light is sufficient, the infrared lamp is kept in an off state, and when people or animals cannot be sensed, the camera is kept in an off state. According to the mangrove forest monitoring camera, work of the camera and the infrared lamp is intelligently controlled through the sensor module and the control module, the mangrove forest monitoring camera is turned on to work only when needed, the camera is kept in a power-off state in other time, power consumption can be effectively reduced, electricity is saved, meanwhile, the frequency of manual battery replacement is reduced, and therefore the labor cost is reduced.

The present application relates to a kind of China and Vietnam mangrove ecological collaborative repair space configuration method, for the heterogeneity of cross-border ecological data and the difficult problem of function connection.Through the collection and space-time alignment hydrology, topography, soil, biological response and other multi-source data, using intelligent denoising and normalization method generates standardized environmental gradient data set, constructs structured semantic ontology library including bilingual semantic mapping and ecological function label, realizes the semantic interoperability of border mangrove habitat characteristics.Combined with real-time sensing node and semantic analysis, dynamically identify ecological module function intent, calculate the compatibility of module function of two countries, automatically generate and optimize coupling strategy instruction, guide physical space reconstruction, form ecological coupling interface entity with hydrological connectivity and nutrient exchange capacity.Continuous monitoring ecological response, realize function achievement degree evaluation and closed-loop optimization, effectively improve the collaborative intelligent level of cross-border ecological restoration.

The utility model belongs to the ecological recovery technical field, concretely relates to a kind of degraded mangrove forest rapid recovery ecological system, including highway and located coastal slope of highway side, coastal slope is provided with water storage tank and mangrove forest planting area, the upper side of water storage tank is provided with water inlet;Water storage tank includes the box body embedded in the inside of coastal slope, box body is upside open structure, the upper side opening of box body is the water inlet of water storage tank, the inside of box body is fixedly connected with multiple baffle, the space in the inside of box body is separated and presents multiple small water storage room by baffle, mangrove forest planting area is divided into multiple and small water storage room one-one correspondence small planting area, the lower side of box body close to mangrove forest planting area side is opened with multiple water-permeable mouth, the lower part of baffle is opened with water guide hole.The utility model can concentrate medicine to treat the mangrove forest plant of degraded area, reduce the phenomenon of medicine loss to non-degraded mangrove forest plant while recovering the ecology of mangrove forest plant rapidly.

The present application relates to the technical field of planting and repairing of mudflat mangrove, and discloses a method for constructing mangrove mudflat suitable land based on lifting elevation, which comprises the following steps: S1, constructing mudflat suitable land: constructing suitable land according to target elevation; S2, constructing primary protection structure: constructing wooden pile protection structure on the sea side of suitable land; S3, constructing secondary protection structure: constructing oyster reef protection layer between the periphery of suitable land and the wooden pile protection structure; S4, constructing ecological dam: constructing ecological dam between the primary protection structure and the secondary protection structure, forming water storage area between the ecological dam and the secondary protection structure, and the ecological dam is further provided with a plurality of planting areas for filling planting biological nutrients. The present application can reduce the adverse effects of wind, wave and tide on mudflat and mangrove seedlings, improve the effect of mud and dam fixation, improve the survival rate of mangrove, and optimize the marine ecological environment.

The invention relates to the technical field of microbial fermentation and enzyme engineering, and in particular relates to a strain Precottula equi GXAS 17-2 for high yield of chitin deacetylase as well as a fermentation culture medium and application thereof, the preservation number of the strain Precottula equi GXAS 17-2 is GDMCC NO: 67488, and the strain is separated from mangrove forest soil and can efficiently produce enzyme in the culture medium taking N-acetylglucosamine (GlcNAc) as an inducer. The enzyme activity is remarkably improved by optimizing culture medium components (3% of colloidal chitin, 10% of yeast powder and 0.3% of GlcNAc) and culture conditions (30 DEG C, 180 rpm, pH 7 and 48 h). The method has the advantages of high induction efficiency, green process, stable enzyme activity and the like, and is suitable for chitin degradation and chitosan green preparation industry.

The utility model discloses a mangrove forest system plant debris collection device, belongs to the technical field of water area experiment sample collection, and aims to improve the representativeness of plant debris collection so as to improve the accuracy of carbon flux measurement. The mangrove forest system plant debris collecting device comprises a collecting net and at least two stand columns. The stand columns are fixed to the bottom of a water area or on the bank and arranged at intervals in the direction perpendicular to the water area flow direction. The collecting net is used for collecting plant debris, and the collecting net is fixedly connected with the threaded pipe of each stand column. According to the mangrove forest system plant debris collection device, plant debris in a larger area and different depths in a water area can be collected, the representativeness of plant debris collection can be improved, and then the accuracy of carbon flux measurement can be improved; meanwhile, the device has the advantages of simple structure and reliability in use.

The invention relates to the technical field of garbage cleaning devices, in particular to a mangrove forest canopy garbage precise grabbing claw type device which comprises a handle and a grabbing assembly, and the grabbing assembly comprises a mounting shell, an outer rod, an inner rod, a fixing bolt, a control component and a clamping component; a first screw hole and a second screw hole are formed in the side of the inner rod; during use, a worker screws out the fixing bolt from the first screw hole, pulls the inner rod out of the outer rod, enables the clamping part to extend to a higher position, screws the fixing bolt into the second screw hole, fixes the position of the inner rod, and then holds the handle by hand to move the clamping part to a garbage position on a mangrove crown. And the control part is controlled to drive the clamping part to act to clamp the garbage, so that the garbage clamped on the mangrove crown can be conveniently cleaned.

The invention provides a coastal zone mangrove forest ecological evaluation monitoring method and system, and the method comprises the steps: obtaining historical environment parameters of a mangrove forest region, carrying out the standardization processing of the historical environment parameters, and obtaining a standardized data set; wherein the historical environment parameters comprise water body parameters, air parameters and temperature parameters; constructing an XGBoost model, and training the XGBoost model through the standardized data set to obtain a prediction model for outputting mangrove forest health scores; wherein the XGBoost model is trained by minimizing a total loss function obtained by superposing a Huber loss function value, a threshold violation loss function value and an expert knowledge guidance loss function value; and acquiring real-time environment parameters acquired in real time, predicting the real-time environment parameters based on the trained prediction model, outputting a current ecological health score of the mangrove forest region, and generating a corresponding score early warning. According to the invention, the accuracy of health evaluation and environment monitoring can be improved.

The invention relates to the technical field of soil sampling, and discloses a mangrove forest original columnar soil sampler convenient to open and close, which comprises two groups of semi-arc sampling pipes, cleaning parts arranged in inner cavities of the semi-arc sampling pipes, and a plurality of sampling pipes arranged in the inner cavities of the semi-arc sampling pipes, and the ends, close to each other, of the two groups of semi-arc sampling pipes are hinged to each other. The one-way intercepting part is arranged at the bottom of the semi-arc sampling pipe and comprises an intercepting cylinder arranged on the surface of the bottom of the semi-arc sampling pipe. According to the mangrove forest original columnar soil sampler convenient to open and close, two sets of semi-arc sampling pipes are arranged in a half-and-half mode in a hinged mode, the two sets of semi-arc sampling pipes can be freely opened in a half-and-half mode, complete undisturbed soil samples can be directly taken out conveniently, secondary disturbance and pollution caused by bulldozing or cutting and other modes are avoided, meanwhile, intercepting cylinders are arranged at the bottoms of the semi-arc sampling pipes, and the sampling effect is good. Meanwhile, a chamfer notch is polished to be sharp, the influence of tree roots on a soil layer can be cut off, and disturbance of the tree roots to the soil is reduced.

A sea water desalination device and method based on coastal wetland vegetation transpiration belong to the technical field of ecology and water resource treatment crossing, and comprise a fresh water collection system, a fresh water storage system, and an auxiliary regulation and display system. According to the method, sea water desalination is achieved through the natural transpiration effect of coastal wetland vegetation (such as mangrove forests), condensed fresh water is collected through a transparent air chamber / ceiling, and operation is guaranteed by combining solar power supply and environment regulation and control. Compared with a traditional seawater desalination technology, the method is wide in application range, easy to manufacture and extremely low in energy consumption, the efficiency and sustainability of obtaining fresh water in the coastal area are improved, meanwhile, ecological protection is considered, a stable water supply solution is provided for coastal and island areas lacking fresh water resources, and technical support is provided for related resource utilization and ecological restoration research.

The invention discloses a mangrove forest ecological restoration multi-dimensional effect comprehensive evaluation method and system. The method comprises the following steps: acquiring first remote sensing image data, first environment monitoring data, a first biological investigation quadrat image and first ecological background data corresponding to a restored mangrove forest carrying a first geographic coordinate and a first time label; inputting the processed first remote sensing image data into a nested U-shaped model to obtain a first pixel-level semantic segmentation map, and inputting the processed first biological investigation quadrat image into a comparison enhanced YOLOv8 model to obtain a first detection feature vector; obtaining a first ecological network embedding vector through the processed first environment monitoring data, the processed first ecological background data and a GraphSAGE model; obtaining a first ecological parameter index through the first pixel-level semantic segmentation map, the first detection feature vector, the first ecological network embedding vector and a multi-modal Transform model; and after the first ecological parameter indexes are converted into scores and preset thresholds, the restoration effect of the restored mangrove forest is obtained.