1314 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 small watershed hydrological runoff and pollution load short-term prediction refinement method, which comprises the following steps of: constructing a modeling data set, constructing a small watershed foundation base model, segmenting hydrological response units according to land utilization types, crop planting structures and reservoir pond / wetland distribution data in a refinement manner respectively, and calculating the hydrological runoff and pollution load short-term prediction of the small watershed foundation base model. A small watershed foundation base model corresponding to the optimal segmentation scheme is screened out, and a small watershed depth base model is generated; constructing a reservoir pond / wetland simulation module; coupling the small-watershed depth base model and the reservoir pond / wetland simulation module to form a small-watershed hydrology and water quality early warning model, and optimizing the small-watershed hydrology and water quality early warning model; rolling to generate a hot start file for short-term prediction; constructing a future short-term weather enhancement forecasting model; the small watershed hydrology and water quality early warning model is driven to operate, the future water volume and load output are calculated in a rolling mode, and hydrology and water quality results are output; and calibrating and updating the small watershed hydrology and water quality early warning model. The precision and timeliness of hydrology and water quality prediction of the small watershed are remarkably improved.

The invention relates to a restoration method of a wetland ecosystem, and aims to improve the biodiversity of a wetland and restore and enhance the ecological function of the wetland through systematic measures. The method comprises the following steps: firstly, evaluating the current condition of the wetland, and identifying specific or endangered species and alien invasive species; secondly, by introducing or protecting specific animal and plant species, the natural habitat is recovered, and the biodiversity of the wetland is improved; thirdly, the water quality and soil conditions of the wetland are improved by adopting technologies such as hydrological regulation and control and vegetation restoration; fourthly, the connectivity of the interiors of the wetlands and surrounding habitats is enhanced, and species migration and gene exchange are promoted. By means of the measures, a damaged wetland ecosystem can be effectively restored, key functions such as water quality purification, flood regulation and carbon storage of the wetland ecosystem can be restored, meanwhile, endangered species are protected, and the ecological value and landscape aesthetics of the wetland are improved.

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 relates to the technical field of wetland ecosystem soil carbon sequestration capability, in particular to a seasonal waterlogged wetland soil carbon estimation and dynamic monitoring method, which comprises the following steps of: selecting a sampling zone and a quadrat according to an equal-elevation water level gradient and a vegetation type; an optimal remote sensing estimation carbon model is determined through remote sensing image interpretation and screening of characteristic factors such as image waveband reflectivity, vegetation indexes, principal component characteristics and single-waveband textures, and soil organic carbon spatial distribution characteristics are analyzed through remote sensing inversion and GIS interpolation; constructing a Wetland-DNDC wetland carbon dynamic simulation model based on a DNDC model to predict wetland long-term carbon dynamic change and greenhouse gas emission; the invention provides a method for simulating carbon reserves and carbon dynamic monitoring based on field investigation and coupling a 3S technology with a Wetland-DNDC model. Compared with a traditional field observation method, the method has obvious technical and cost advantages, and can realize the technical advantages of spatial analysis and long-time sequence monitoring. The research method is suitable for a wetland ecosystem with seasonal hydrological characteristic changes.

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 discloses a degraded wetland near-natural restoration method based on provenance production improvement, belongs to the technical field of wetland ecological engineering, and solves the restrictive problems of plant provenance deficiency caused by exogenous interference and low sustainable efficiency after wetland restoration. The method comprises the following steps: 1, defining provenance deletion and recovering wetland site selection; 2, creating a grid habitat of the target wetland; 3, collecting and cultivating a breeding matrix; 4, performing segmented management and control on hydrological conditions; and 5, seed source production monitoring and propagation mediation. The method is suitable for a degraded wetland near-natural recovery scene with provenance production obstacles.

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 the technical field of water environment restoration and ecological management, and particularly discloses a sink increasing method based on whole-process water environment restoration and green land water ecological system management, and the method comprises the following steps: identifying and controlling a pollution source through remote sensing and machine learning technologies; a biological floating island, an artificial wetland and physical and chemical means are utilized to carry out water body remediation; the carbon sink function is optimized through the synergistic effect of aquatic plants, greenbelt vegetation and microorganisms; and dynamic monitoring and a feedback control model are combined to regulate and control repair measures in real time. According to the carbon sink increasing method, the carbon sink optimization mathematical model is adopted, the carbon absorption stock of the water body, the green land and the microorganisms is comprehensively calculated, the service function of the water body ecological system is improved, non-point source and point source pollution can be effectively controlled, the water quality is improved, the water ecological system is restored, meanwhile, the regional carbon fixing amount is remarkably increased, and collaborative promotion of ecological restoration and the carbon sink target is achieved.

The present invention relates to the field of carbon storage monitoring technology, which is a sampling device for monitoring wetland carbon storage. The sampling device includes a square frame, a supporting frame, etc. The supporting frame is securely mounted on the square frame, with a U-shaped frame fixed at its top. The U-shaped frame houses a mounting plate, and a lifting plate is also slidingly mounted on the supporting frame. The sampling outer cylinder is fixedly mounted on the lifting plate, with an inner sampling cylinder inserted inside. Additionally, the sampling device comprises a lifting drive component, a depth control component, and a sampling component. The sampling device can both improve the accuracy of sampling work at different soil depths and eliminate detection errors with high degree of automations. At the same sampling position, multiple sets of samples can be collected simultaneously to ensure the accuracy of sampling results.

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 relates to a rice growth process three-dimensional scene construction method based on a crop growth model and a rendering engine, and the method comprises the following steps: obtaining plant density, distribution, leaf inclination angle distribution, a leaf spectrum, a canopy spectrum and substrate reflectivity through a field experiment, and constructing a single-plant rice 3D model; coupling a crop growth model, and describing vegetation canopy reflection characteristics through canopy structure parameters and leaf BRDF to simulate canopy reflection factors; respectively calculating a water body scattering phase function and a water surface BRDF according to the water body biological optical model and the wave water surface reflection model; generating a three-dimensional water body volume model through an AVRM model; blender software is combined with a LuxCoreRender rendering engine to couple incident radiation, vegetation canopy reflection factors, water optical attributes and other related input parameters, and a real rice scene is constructed. According to the method, the high-precision three-dimensional rice scene model is established, important technical support is provided for improving the precision and efficiency of rice remote sensing radiation modeling and further for agricultural remote sensing and wetland monitoring, and the method has popularization and application prospects.

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 provides a digital wetland ecological environment monitoring system, which comprises an intelligent sensing terminal deployed in a wetland experiment sample area and used for collecting multi-source heterogeneous wetland monitoring data and transmitting the multi-source heterogeneous wetland monitoring data to information transmission equipment; the information transmission equipment is used for receiving, transmitting, summarizing, storing and analyzing the multi-source heterogeneous wetland monitoring data; and the wetland data center is used for acquiring the summarized multi-source heterogeneous wetland monitoring data through information transmission equipment, providing data analysis service on line by utilizing a distributed calculation and analysis technology and a data mining tool on the basis of the multi-source heterogeneous wetland monitoring data, and providing data service for the application service center and the intelligent decision center. According to the invention, multi-source heterogeneous data is integrated, wetland ecological monitoring related management applications and data services are integrated to a unified monitoring platform, and application of the system in ecological evaluation and simulation prediction is realized, so that informatization, digitization and intelligence of wetland ecological monitoring are further realized.

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 discloses a wetland bird community structure and diversity observation device and method, and the device comprises an installation support column which is used for being installed in a wetland area; the bird luring mechanism is arranged on the mounting supporting column; and the acquisition mechanism is arranged on the bird inducing mechanism, is in wireless connection with an external monitoring terminal, and is used for acquiring bird image data and bird sound data on the wetland area and the bird inducing mechanism, and sending the bird image data and the bird sound data to the external monitoring terminal for processing and analysis. Bird image data and bird sound data in the wetland area can be acquired through the acquisition mechanism, meanwhile, birds in the wetland area can be lured through the bird luring mechanism, the quality of the bird image data and the bird sound data acquired by the acquisition mechanism is improved, and the difficulty of subsequent data analysis is reduced.

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 belongs to the technical field of water resource planning and management, and particularly relates to a method for calculating an effective hydrological connectivity strength index range of a wetland based on an InSAR (Interferometric Synthetic Aperture Radar) technology. The calculation method comprises the following steps: acquiring image data of an area to be calculated; identifying all wetland plaques in the water body area; dividing the wetland plaques into different effective hydrological communication type groups; calculating an elastic force value of each wetland patch; constructing a water level fluctuation-ecological elastic force curve under different effective hydrological communication situations, carrying out segmented fitting on the water level fluctuation to generate a fitting line, calculating the mean value of the elastic force of the wetland plaques under the effective hydrological communication type, generating an elastic force mean value line, and calculating the elastic force mean value line; the two intersection points of the elastic force mean value line and the fitting line are the effective hydrological connection strength index range. According to the method, the wetland plaques of different effective hydrological connection type groups are divided according to the difference of the effective hydrological connection strength, the optimal ecosystem elastic force of the wetland plaques is calculated respectively, and then the effective hydrological connection strength index range is determined.

The invention relates to the technical field of carbon sink data processing, in particular to a tamarix chinensis forest wetland ecosystem carbon sink data analysis and processing system and method. The system comprises a carbon sink data calculation module, a data proofreading information acquisition platform and a data analysis proofreading module. Wherein the carbon sink data calculation module determines carbon sink resource data corresponding to a tamarix chinensis forest in a target area based on tamarix chinensis coverage data and pre-input matched carbon sink resource parameters of tamarix chinensis in different types of land; according to the method, an affected area of a tamarix chinensis forest is identified, the affected area is divided into a plurality of areas, the areas are matched with various environments in a city, an abnormal damage database is constructed by utilizing a portable monitoring environment of the city, and the short plate of which a broken branch is difficult to identify through remote sensing monitoring is supplemented through damage information recorded in the abnormal damage database. Therefore, proofreading of the carbon sink resource data is completed, and accuracy of remote sensing monitoring is improved.

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 relates to a cold region wetland water quality risk factor screening method, and belongs to the technical field of water ecological water quality screening. Establishing a water quality monitoring data file; the water quality screening calculation comprises the steps of data file selection and identification, seasonal screening calculation, data file establishment, principal component scoring, main factor direct calculation score, non-rotation factor sample direct scoring, variance maximum orthogonal rotation, factor post-rotation scoring, Bartlett inspection, risk factor probability screening and conjecturing of over-standard elements in each month of the next year. The method has the advantages that the problem that risk factors cannot be quantitatively analyzed in a factor analysis method can be solved, and identification and analysis can be independently carried out in different seasons. According to a method for performing factor analysis and probability calculation according to seasons, the water quality risk factors are screened by combining factor analysis scores with probable probabilities.

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.