1038 results about "Wetland" patented technology

The invention relates to a coastal wetland ecological restoration effect evaluation method and system, and belongs to the technical field of ecological monitoring and restoration. Aiming at the problems of static evaluation index lag, insufficient data fragmentation integration and lack of causal diagnosis mechanism in the prior art, multi-source time sequence ecological data are acquired by constructing a three-dimensional monitoring network consisting of satellite remote sensing, an unmanned aerial vehicle, an Internet of Things sensor and an underwater robot; a fusion data set is generated based on space-time alignment and tidal phase marking, dynamic evolution characteristics are extracted by using an LSTM network, and a spatial distribution difference chart of ecological parameters before and after restoration is generated in combination with a GAN; and furthermore, through hot area clustering and historical data association mining, a degradation driving factor is positioned, and an optimization suggestion is generated. The method breaks through the space-time limitation of a traditional evaluation method, remarkably improves the degradation diagnosis precision and the regulation and control efficiency of restoration engineering, and is suitable for various ecological restoration scenes such as estuary delta and coral reefs.

The invention relates to the technical field of wetland carbon evaluation, and discloses a wetland carbon flux evaluation and management system based on three-dimensional digital twinning. The system comprises a three-dimensional modeling module, a flux monitoring module, a model optimization module and a twin updating module. The three-dimensional modeling module integrates wetland geographic space coordinates, an ecological parameter set and elevation, vegetation coverage density and soil type layering information, constructs a three-dimensional terrain grid model, and generates a three-dimensional digital twinborn body with a geographic mark; the flux monitoring module is used for collecting data such as atmospheric temperature gradient based on real-time environmental parameters, extracting carbon flux change characteristics through time sequence analysis and outputting a dynamic distribution state value; the model optimization module uses an adaptive evolutionary algorithm to adjust the parameter matching degree, iteratively updates constraint conditions, and generates an optimization parameter set; and the twin updating module recognizes abnormal grid units according to the abnormal grid units, corrects attributes by combining measured data, calibrates a topological relation, and outputs an updated evaluation model.

The invention discloses a wetland ecological restoration dynamic monitoring method based on deep learning, and relates to the technical field of ecological restoration, and the method comprises the following steps: obtaining multi-source wetland ecological sensor data and remote sensing image flow in real time, constructing a space-time fusion data cube, and extracting an ecological feature tensor; performing degradation mode analysis on the ecological characteristic tensor, generating an ecological state dynamic topological graph, and calculating an ecological connectivity index; carrying out restoration demand identification based on the ecological connectivity index, positioning a degradation hot spot region through a multi-modal graph convolutional network, and generating a restoration priority region coordinate set; through multi-source data space-time fusion and deep crossing of deep learning and landscape ecology, a whole-process technical system from ecological state dynamic perception to restoration scheme intelligent optimization is constructed. The problems that in traditional wetland restoration, data scales are not matched, degradation area positioning is fuzzy, restoration path ecological adaptability is poor, and multi-target cooperation is difficult are effectively solved.

The invention relates to the technical field of ecological environment monitoring, and discloses a coastal wetland intelligent monitoring method and system based on artificial intelligence, and the method comprises the steps: collecting unmanned plane data, satellite remote sensing data, Internet of Things sensor data and water quality monitoring buoy data of a coastal wetland; the method comprises the following steps: processing satellite remote sensing data by adopting a wavelet threshold denoising algorithm based on an attention mechanism, calibrating Internet of Things sensor data by adopting an LSTM network, and carrying out data space-time alignment based on a space-time attention fusion model to obtain preprocessed data; inputting the preprocessed data into a Transform-ResNet hybrid model to carry out environmental change evaluation, and outputting an ecological health index; when the predicted ecological health index is lower than a threshold value, a PPO algorithm is adopted to dynamically adjust a monitoring strategy according to the early warning level, and an early warning report is pushed; the whole process is intelligent, manual intervention is greatly reduced, and support is provided for coastal wetland ecological protection.

The invention discloses a high-beach difficult land mangrove plant restoration method, and relates to the technical field of wetland ecological restoration. Through the design of the concave planting pits and the improvement technology of the compound matrix, the problems of insufficient tide immersion and soil hardening in existing high beach remediation are solved. According to the method, planting pits with specific sizes are dug, 2 / 3 of original soil is removed, and a composite matrix of a coco coir layer, a humus layer and a crushed soil layer is backfilled, so that the concave microhabitat with the surface layer 10-20 cm lower than the native mud flat is formed. The coco coir layer improves the air permeability of the soil, the humus layer provides organic nutrients, and the crushed soil layer enhances the stability of the root system. The concave structure prolongs the residence time of tidal water, promotes benthic organisms such as crabs to move and improves the soil quality. By means of the method, the survival rate of mangrove plants in the kaolin mud flat at the tail of the pond under the xiamen reaches 85% or above, and the forestation problem caused by high-beach soil hardening and insufficient tide flooding is solved.

The invention provides a wetland ecological protection area biodiversity evaluation system, and relates to the technical field of ecological system diversity evaluation. The evaluation system comprises a data acquisition and management module, a species diversity analysis module, an ecological system function evaluation module, a threat factor identification and analysis module, a decision support and suggestion module and a data visualization and report module. According to the invention, the system is a platform integrating data collection, analysis, assessment and decision support, aims to comprehensively assess the biological diversity condition in the wetland ecological system and provide a scientific basis for sustainable management and protection of the wetland, not only can realize scientific and systematic management of wetland ecological protection, but also can provide a scientific basis for the sustainable management and protection of the wetland. The sustainable development of biological diversity protection can be promoted, the relationship between the biological diversity and ecological processes such as material circulation and energy flow in the wetland ecological system can be better understood through the evaluation system, and the ecological process of the wetland ecological system can be deeply understood.

The invention relates to an ecological system carbon sink evaluation method, which comprises the steps of generating a continuous climate distribution grid based on a global ecological system type and climate element data, extracting multi-dimensional characteristic parameters of temperature, rainfall and a carbon sink value through an improved weighted K-means clustering algorithm, quantifying climate transition zone boundary fuzziness in combination with a covariance matrix, and evaluating the ecological system carbon sink evaluation result. Dynamically adjusting the weight of the spatial variation coefficient; a simulated annealing algorithm is utilized to optimize correlation between the division scale and the carbon sink response, and a multi-scale regression model is constructed to generate a high-precision carbon sink distribution diagram; further fusing the remote sensing vegetation index and the ground actual measurement data, and eliminating the evaluation error caused by the conflict between the boundary fuzziness and heterogeneity of the transition zone; according to the method, the problems of insufficient climate-ecology interaction dynamic response modeling and low boundary division precision in the prior art can be solved, the reliability of carbon sink evaluation in complex areas such as forest-grassland interlaced areas and coastal wetlands is remarkably improved, and scientific data support is provided for ecological restoration project site selection and carbon trading markets.

The invention discloses an acoustic automatic recognition system and method for birds in a wetland environment, relates to the technical field of ecological monitoring and acoustic signal recognition, and provides a four-step flow of multi-source noise modeling, blind source separation and noise reduction, multi-label recognition and multi-modal fusion feedback for a wetland complex acoustic environment. The method comprises the following steps: 1, constructing an acoustic dictionary and mixing noise and twitter by using a contribution coefficient; 2, performing multi-sound-source unmixing by using a self-supervision method, and outputting a quasi-pure orbit; step three, identifying and labeling overlapped twitter by combining multi-label classification and dynamic spectrum enhancement time enhancement factors and frequency enhancement factors; and 4, judging the noise type through the microphone array and external environment parameter fusion, updating the noise template and the birdsong template to form closed-loop iteration, maintaining high recognition precision in a noisy and multi-species chorus scene, and providing efficient support for wetland ecological monitoring and protection decision.

The invention discloses a coastal wetland grass seed classification method based on sentinel No.2 time sequence analysis and a random forest, and the method comprises the steps: extracting spectrum, texture and polarization parameters as classification variables through combining a sentinel No.2 multi-temporal optical image and sentinel No.1 radar data; and the monthly NDVI maximum time sequence of the sentinel No.2 image is utilized to analyze and capture the difference characteristics of the grass seeds in the growth peak period, the aging period and the change rate, a time difference vegetation index is constructed, and the distinguishability of reed and spartina alterniflora with similar spectral characteristics is enhanced. A random forest algorithm is adopted to carry out classification modeling in combination with a suaeda salsa index, an SHAP method is introduced to carry out visual analysis on the model, contribution of characteristic variables in grass seed identification is quantified, and interaction between characteristics and an influence mechanism of the characteristics on a classification result are disclosed. And finally, the classification precision is evaluated through ten-fold cross validation, and the robustness and reliability of the model are ensured.

The invention discloses a wetland carbon sink benefit evaluation method and system based on remote sensing data, and relates to the technical field of carbon emission evaluation. A wetland carbon sink benefit evaluation system based on remote sensing data comprises a carbon sink evaluation zoning module and a carbon sink benefit evaluation module. According to the invention, through multi-modal remote sensing data fusion and fine grid division, high-resolution analysis of spatial heterogeneity of a wetland region is realized, different types of carbon sink regions and distribution boundaries thereof can be accurately identified, and scientificity and particles of carbon sink partitioning are improved; a dynamic index characteristic graph layer is constructed through a remote sensing time sequence, a hydrological pulse response factor graph layer is constructed in combination with hydrological data, and clustering division is performed on the hydrological pulse response factor graph layer, so that dynamic identification and pixel level benefit calculation of a dynamic carbon sink area are realized.

The invention discloses a wetland ecological risk regulation and control method, system and equipment based on multi-modal early warning, and relates to the related field of water quality parameter abnormity alarm, the method comprises the following steps: collecting physical and chemical parameters of a wetland water body in real time, and generating a dynamic water quality data set; performing detection optimization on the dynamic water quality data set according to the historical abnormal data frequency, and determining a water quality detection sequence; and performing multi-level risk assessment on the target wetland area according to the water quality detection sequence to obtain a plurality of risk scores, triggering a multi-modal early warning mechanism based on the plurality of risk scores, generating a self-adaptive purification scheme, and pushing the self-adaptive purification scheme to a management terminal. The technical problems of insufficient early warning timeliness, monitoring comprehensiveness and data accuracy of the existing wetland water quality monitoring are solved, and the technical effects of improving the early warning timeliness, the monitoring comprehensiveness and the data accuracy of the wetland water quality monitoring are achieved.

The invention discloses an evaluation method for dynamically monitoring carbon sink of a grassland and wetland ecosystem, which relates to the field of ecological environment monitoring and comprises the following steps: acquiring historical carbon flux observation data of a target area; dividing the target area into a plurality of space grid units, taking each grid unit as a node in the graph structure, and establishing graph edge connection between adjacent nodes; extracting ecological features for each node; calculating the edge weight of each edge in the graph structure according to the ecological characteristic difference between the adjacent nodes; inputting the graph structure containing the node features and the edge weights into a graph neural network model, and training the graph neural network model by using historical carbon flux observation data as labels; and predicting the carbon flux of an unobserved node or a future time period node by using the trained graph neural network model. The method solves the problem that a traditional model is large in estimation error of the carbon flux in the ecological boundary region, and can remarkably improve the carbon exchange prediction precision of the boundary region.

The invention relates to the technical field of forest wetland carbon sink monitoring and evaluation, and particularly discloses a forest wetland carbon sink intelligent monitoring and evaluation system and method. According to the method, a vegetation carbon sequestration potential evaluation result is obtained by analyzing vegetation structure feature data of forest, water and soil composite ecology of the forest wetland, a water-soil-carbon cooperative evaluation result is obtained by analyzing specific hydrological-soil carbon cycle key elements of the forest wetland, and environmental disturbance response factors are obtained by combining various environmental disturbance factors. Through multi-source data fusion and intelligent modeling, a carbon sink quantitative evaluation value is output, and abnormal feedback is triggered; the problems that in the prior art, adaptability to a forest wetland compound ecological system is insufficient, evaluation refinement is insufficient, and dynamic response is lacked are solved. According to the method, accurate and dynamic monitoring and evaluation of forest wetland carbon sink are realized, carbon sink short plates can be accurately positioned, optimization support is provided, and technical support is provided for protection, restoration and optimization management of forest wetland carbon sink resources.

The invention relates to the technical field of wetland ecological restoration. The invention discloses a wetland carbon sink capacity improving method and system based on intelligent regulation and ecological restoration, and the method comprises the steps: laying a multi-parameter sensing network, and monitoring the water level, vegetation growth and soil wetland carbon reserve parameters in real time; obtaining a vegetation NDVI index and surface temperature data, and analyzing the vegetation NDVI index and the surface temperature data to obtain an ecological restoration strategy; according to an ecological restoration strategy, carbon sink dominant plants are combined, and emergent aquatic plants, submerged plants and floating-leaved plants are matched; strengthening the microorganisms, and inoculating a carbon sequestration fungicide; establishing a carbon sink-environmental parameter response model according to the historical intelligent regulation and control data; and inputting the ecological restoration strategy into the carbon sink-environmental parameter response model for analysis, and adjusting ecological restoration data according to an analysis result of the carbon sink-environmental parameter response model. According to the invention, intelligent response to environment change is realized, and the carbon sink efficiency is dynamically optimized.

The invention provides a wetland ecosystem health evaluation method based on multi-source remote sensing data, and belongs to the technical field of wetland ecosystems, and the method comprises the steps: carrying out the dense dark pixel and Kalman filtering cooperative atmospheric correction of a multi-spectral remote sensing image to obtain a surface reflectance image, and achieving the precise segmentation of a wetland landscape through a graph cut theory, a spectral unmixing model based on an improved Gaussian kernel is utilized to embed physical constraints to invert water quality parameters, a laser radar canopy height priori constraint three-dimensional radiation transmission model is combined to invert vegetation parameters, and a mixed pixel decomposition result is optimized through a Markov random field. A water quality, vegetation and landscape three-dimensional comprehensive health evaluation system is constructed, degradation dominant factors are identified, and the technical problem that it is difficult for multi-source remote sensing data to cooperatively invert wetland ecosystem multi-dimensional health state parameters is solved.

The invention relates to the technical field of inversion systems, in particular to a coastal wetland forest ecosystem biomass and carbon sink rapid inversion system. According to the technical scheme, the system comprises a data acquisition and preprocessing module, an inversion module based on machine learning, a spatial heterogeneity adaptive module, a dynamic monitoring and updating module and a result visualization and output module. According to the method, a data basis is provided for accurate inversion through multi-source data fusion, and meanwhile, an inversion model combining the generative adversarial network and the long-short-term memory network realizes combination of a physical model and deep learning, so that the interpretability of the physical model is reserved, and the model performance is improved by utilizing the strong fitting capability of the deep learning; according to the invention, the adaptability of the system in a complex coastal wetland environment is improved through the spatial heterogeneity adaptive module, and the reliability of an inversion result is improved; according to the invention, real-time dynamic monitoring of biomass and carbon sink is realized through the dynamic monitoring and updating module, and rapid response of ecological system change is supported.

The invention provides a coastal wetland ecological corridor identification and optimization method and system, and relates to the technical field of ecological environment monitoring. The method comprises the following steps: integrating optical, radar, terrain, night light and road data on an earth engine cloud platform, and unifying time and space references to form an initial data set; extracting a normalized vegetation index and a vegetation coverage degree, and combining with a water body frequency to identify an ecological source land; generating a comprehensive resistance surface according to the land utilization and coverage type and the road distance; and performing minimum cost path and circuit connectivity analysis in a geographic information system to obtain potential galleries, key nodes and barrier regions, and outputting gallery grades and optimization suggestions in a grading manner according to a cost threshold, thereby realizing high-precision identification and optimization of the coastal wetland ecological network.

The invention belongs to the technical field of hydraulic environment intelligent management, and discloses a hydraulic environment intelligent management system and method based on multi-parameter monitoring. Comprising the following steps: identifying pollution source types in the mixed pollution source based on multi-dimensional environmental parameters, obtaining contribution strength and treatment priority of various pollution sources, analyzing the contribution strength, obtaining pollution concentration gradients and pollution diffusion fluxes of various pollution sources, and determining the pollution source types in the mixed pollution source based on the analysis of the pollution concentration gradients and the pollution diffusion fluxes. The method comprises the following steps: determining migration and diffusion paths and emission sources of various pollution sources, analyzing each divided region of the coastal wetland, obtaining an ecological sensitivity index of each region, determining a risk level of each region of the coastal wetland based on the ecological sensitivity index and a pollution concentration gradient, establishing a constraint system, and formulating a management scheme for each region of the coastal wetland. The management strategy is formulated and dynamically updated for the coastal wetland, the contribution intensity of each pollution source is precisely split, and the management effect of the mixed pollution source is improved.

The invention provides a wetland ecological safety early warning method and system based on remote sensing analysis, and the method comprises the steps: firstly obtaining a multi-dimensional remote sensing data set containing multi-temporal imaging, spectral radiation and microwave scattering data in a target wetland region, and carrying out the interpretation to obtain an ecological process signal set; establishing a mapping relation model of the ecological process signal and the wetland ecological safety state, and obtaining a current ecological safety state description; performing cross-process correlation analysis on the ecological process signal to form an ecological process abnormal conduction chain; constructing an early warning trigger node system and generating an early warning rule; and acquiring real-time multi-dimensional remote sensing data, interpreting the real-time multi-dimensional remote sensing data, matching the interpreted real-time multi-dimensional remote sensing data with an early warning rule, and generating wetland ecological safety early warning information containing an abnormal ecological process link, an abnormal conduction path and an early warning response node. The wetland ecological safety risk can be comprehensively and accurately pre-warned, and the stability of the wetland ecological system is guaranteed.

The invention discloses a flooding wetland carbon flux upscaling method and system fusing a hydrodynamic model and integrated machine learning. The invention relates to the technical field of water conservancy and ecological environment monitoring management, and discloses a method for carrying out multi-scale segmentation on an underlying surface of a flooding wetland by collecting flooding wetland vortex covariance measurement, a digital elevation model, hydro meteorology and remote sensing image data to obtain a carbon flux upscaling calculation unit; a flooding wetland hydrodynamic model is established, and related hydrological situation index factors influencing the flooding wetland NEE are calculated; constructing a plurality of machine learning models, and optimizing the prediction weight of each model to obtain an optimal model integration prediction scheme; nEE spatial upscaling is carried out, multi-model prediction difference is utilized to quantitatively characterize prediction uncertainty, and a NEE space-time distribution diagram and an uncertainty diagram are obtained; according to the method, the wetland NEE upscaling high-precision prediction is realized, and a new technical method and reliable data support are provided for flooding wetland carbon flux research and ecological management.

The invention relates to the technical field of ecological environment monitoring and intelligent information processing, and discloses an intelligent monitoring method and system for ecological restoration of a small and micro wetland. The method comprises the following steps: synchronously collecting multi-dimensional parameters of water, soil, gas and growth through a multi-source sensor array, and constructing ecological state vectors with time-space alignment; carrying out cross-medium nonlinear coupling modeling by utilizing a graph attention space-time fusion network; predicting key water quality and biological indexes by adopting an LSTM (Long Short Term Memory) and GRU mixed framework; and generating graded early warning and self-adaptive repair suggestions in combination with the three-level health threshold and the rule base. The system comprises a multi-source sensing module, a data preprocessing module, a graph structure construction module, a feature fusion module, a time sequence prediction module and an intelligent decision module. According to the system, global sensing, early warning and intervention of the ecological state of the small and micro wetlands are realized, and the restoration timeliness and scientificity are improved.

The invention discloses a sea-land collaborative coastal wetland ecological quality remote sensing evaluation method under a spartina alterniflora expansion background, and the method comprises the steps: obtaining multi-source remote sensing data of a research region, and carrying out the preprocessing of the data, and obtaining a preprocessed remote sensing image; according to the preprocessed remote sensing image, obtaining a salt marsh vegetation space-time distribution diagram of the research area; remote sensing evaluation is conducted on coastal wetland land and water body ecological quality, land ecological quality remote sensing evaluation indexes integrate NDVI, WET, NDSI, LST and DHI, and water body ecological quality remote sensing evaluation indexes integrate TSM, WST, CDOM and Chl-a; and finally, quickly obtaining the ecological quality change of the affected area of the spartina alterniflora through a spartina alterniflora change condition mask evaluation result. The ecological quality remote sensing evaluation method provided by the invention is more suitable for the coastal wetland under the background of spartina alterniflora expansion, and a scientific basis is provided for making coastal wetland ecological management and protection strategies.

The invention provides a wetland forest and grass ecosystem restoration strength evaluation method under drought stress. The method comprises the steps of data collection, daily-scale ecosystem service function index ESS construction, ecological drought identification and restoration elasticity curve construction. Wherein the time resolution of the index is accurate to the day, the capture of short-time drought below the monthly scale is enhanced, and the accurate description of the dynamic process of ecological system restoration under the drought stress is realized; combined identification is carried out on the drought events in combination with the standardized ecological water deficit, and the accuracy of identification of the drought events causing significant differences of ecological system service functions is improved; a quantile regression model is utilized to quantify the ecological system recovery capability of different vegetation types, and data characteristics of different recovery time distributions of the ecological system under the same drought intensity are considered, so that the defect that a traditional mean value regression model cannot fully describe drought complex characteristics is overcome; and a theoretical support is provided for sustainable development of an ecological system under an extreme climate condition.

The invention relates to the field of geographic information analysis, in particular to a method and a device for identifying a threshold value of an influence of urbanization on supply and demand of a coastal wetland ecological function, and the method and the device are based on spatial position coordinate data of a plurality of grid units of a coastal area, an urbanization level comprehensive index and a coastal wetland comprehensive ecological function supply and demand ratio. Performing model fitting on a preset initial space weighted threshold identification model to identify a critical point of the urbanization level to the change of the supply and demand relationship of the coastal wetland ecological function, and reflect the staged response characteristics of the supply and demand of the coastal wetland ecological function to urbanization and the spatial heterogeneity characteristics of the urbanization influence mechanism in different geographic units; the spatial difference threshold value characteristics of the coastal wetland ecological function supply and demand relation in the urbanization response process are effectively identified, and a refined and zoned scientific basis is provided for a regional ecological management strategy.

The invention provides assembly type integrated sewage treatment equipment for environmental emergency treatment, which is applied to the field of sewage treatment, and comprises an assembly type stepped assembled wetland system, an in-situ filler regeneration system and an ecological filler regeneration system, the wetland system comprises a wetland box, a purification mechanism is arranged in the wetland box, the wetland box comprises an inner box, and an outer box is arranged in the inner box; a plurality of parallel and inclined filler columns are arranged in the inner box, each filler column comprises a columnar reticulated shell, filler and flexible spiral blades are arranged in the columnar reticulated shell, the purification mechanism further comprises a side plate, the assembly type assembly design is adopted, all the systems can be rapidly connected and installed, the deployment time in an emergency scene is greatly shortened, the design of the filler columns is convenient, and the service life of the system is prolonged. Impurities and pollutants in sewage can be effectively intercepted and filtered, the arrangement of a rotating structure of the filler column and the flexible spiral blades can promote the uniformity of filler biofilm formation, and the treatment efficiency is improved; meanwhile, the grid box, the aeration box, the settling box and the like work cooperatively, so that multi-stage treatment of the sewage is realized.

The invention relates to the technical field of microorganism monitoring, and particularly discloses a wetland microorganism activity monitoring method and system.The method comprises the steps that a plurality of first time sequence data sets of different layers and related to different wetland state parameters are obtained; analyzing and acquiring a parameter change mode of each layer according to the first time sequence data set; similarity matching is carried out based on the parameter change mode and a pre-constructed parameter correlation model library, so that microbial metabolism modes of different layers are determined; determining an activity evaluation mode of the microorganisms in the corresponding layer based on a microorganism metabolism mode; generating an activity evaluation result according to the activity evaluation mode and the first time sequence data set; according to the method, the biological action signal and the non-biological process signal are distinguished, the evaluation accuracy is improved, the activity evaluation mode corresponding to the metabolism mode is determined based on the identified metabolism mode, and the difference of evaluating the activity of microorganisms in different metabolism pathways by adopting one index is avoided.

The invention discloses an integrated removal and treatment method for spartina alterniflora in a mudflat wetland. The integrated removal and treatment method sequentially comprises the steps that a construction operation area is divided; mowing the spartina alterniflora for more than three times in the construction operation area, and airing the crushed straws; performing anaerobic landfill on the straws into the first landfill ditch; carrying out more than two times of root system ploughing on the construction operation area which is already cut; a second landfill ditch with the depth not smaller than two meters is dug, and the ploughed spartina alterniflora root system is placed into the second landfill ditch; and covering soil and compacting the second landfill ditch. According to the method, the formation of mature seeds of the spartina alterniflora can be effectively prevented, the sexual propagation path of the spartina alterniflora can be effectively cut off, the surface of the first landfill ditch after landfill is no longer suitable for growth of the spartina alterniflora, mowing and ploughing are carried out in different areas at the same time, the spartina alterniflora is prevented from sprouting again, the treatment efficiency of the wetland spartina alterniflora is further improved, and the economic benefit is increased. Vegetative propagation of spartina alterniflora is avoided, repeated treatment of spartina alterniflora is avoided, and the treatment cost of spartina alterniflora is reduced.

The invention discloses a high-toughness wetland ecological grid structure and a restoration system thereof. The grid structure comprises a plurality of rows of slope fixing grids which extend longitudinally and are arranged at intervals, and the slope fixing grids in the adjacent rows are arranged in a staggered mode; interval zones between the adjacent slope fixing grids form planting base bands which are communicated with each other. The slope fixing grids and the planting base band are made of artificial substrates of a multi-level pore structure, and a plurality of longitudinally-extending artificial waterways are arranged in the planting base band. The staggered ecological grid structure is matched with the wave-shaped artificial waterway to enhance the overall stability and anti-interference capability of the wetland, and the artificial matrix with the multi-level pore structure improves the water retention, filtration and adsorption effects and enhances the hydraulic connectivity of the matrix. According to the remediation system, a grid structure is divided into four planting belts, the remediation system of an arbor-shrub-grass-hygrophilous four-layer three-dimensional community is formed, a functional microorganism-plant combined remediation mechanism is achieved in cooperation with microbial flora, and the remediation adjusting capacity and stability of the wetland are improved.

The invention relates to a biological and ecological ectopic integrated tail water purification device and method, the device comprises a buffer sedimentation tank at the lower part, an ecological treatment area at the middle part and an aeration tank at the top, tail water at the upper part of the buffer sedimentation tank is conveyed to the aeration tank through a water pump, the bottom is provided with a drain outlet, and the ecological treatment area comprises a benthic organism tank, a microorganism tank and a wetland tank of which the heights are sequentially reduced; the upper part of the wetland pool is not blocked, and tail water flows out from a water outlet of the wetland pool after sequentially passing through the aeration pool, the benthic organism pool, the microorganism pool and the wetland pool. A series of three-dimensional structures such as the vertical flow wetland and the laminated filter tank are adopted, compared with the prior art, the occupied area is greatly reduced, the space utilization rate is increased, and the intensive culture space contradiction is solved.

The invention belongs to the technical field of remote sensing image processing, and particularly relates to a wetland feature extraction system and method based on a multi-source remote sensing image and deep learning, and the system comprises a data acquisition module, a feature fusion module, a CNN model training module and a feedback control module. Dynamically optimizing the feature fusion matrix by adopting a principal component analysis method; constructing a depth feature extraction network, and performing training in combination with a gradient descent algorithm; and feature extraction parameters are fed back and adjusted in real time by using normalized dot product similarity, and feature extraction precision is improved through local consistency optimization. According to the method, the bottlenecks of insufficient precision and limited feature expression ability in wetland feature extraction of a traditional method are broken through, accurate extraction of multi-scale and multi-dimensional wetland features is realized, and high-precision feature data support is provided for applications such as wetland monitoring and ecological evaluation.