741 results about "Wetland" patented technology

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 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 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 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 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 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 present application relates to the technical field of resource assessment, and particularly relates to a system and method for accurately assessing water resource quantity in an inland river basin, comprising the following steps: arranging a multi-modal sensor network in the inland river basin, collecting hydrological characteristic data of the inland river and surrounding wetlands, extracting implicit water exchange characteristic indexes between the inland river and the wetlands, including wetland groundwater recharge, inland river boundary seepage rate and seasonal water exchange amplitude; based on the implicit water exchange characteristic indexes between the inland river and the wetlands, establishing an inland river-wetland implicit water exchange dynamic model; embedding the inland river-wetland implicit water exchange dynamic model into the water cycle system of the inland river basin, and comprehensively calculating the surface water resource quantity and the groundwater resource quantity in the basin. Through the implicit water exchange between the wetlands and the inland river, the present application eliminates the wetland consumption part, so that the water resource quantity calculation is more accurate.

The utility model discloses a coastal wetland shallow underground environment monitoring device, which belongs to the field of coastal wetland environment research and comprises an outer shell, a sealing cover A is arranged at the upper end of the outer shell, a sealing flange is arranged at the lower end of the outer shell, and a sensor mounting seat is arranged on the sealing flange. A plurality of water quality sensors for collecting water quality data are mounted on the sensor mounting seat, a battery and a control circuit board are arranged in the outer shell, and the battery and the plurality of water quality sensors are electrically connected with the control circuit board. According to the utility model, the sensor is buried underground by using the monitoring vertical pipe structure, and the influence of tidal water on a monitored target water source can be effectively isolated by means of the floating ventilation structure, so that the monitoring result is more accurate.

The invention discloses a soil-vegetation collaborative ecological restoration method aiming at a shrub invaded wetland, which comprises the following steps of: performing targeted restoration on key factors of soil by designing a fish-scale pit and a composite water-retaining matrix and a layered pH regulation method, controlling the water content and the pH of the soil at a certain level, and performing vegetation reconstruction. High-leaf-area (LA) type plants, high-specific-leaf-area (SLA) type plants and deep-root-system plants are planted in a matched mode, leaf dry matter accumulation is reduced through the canopy complementary effect, and the soil nitrogen conversion efficiency is improved through rhizosphere collaborative design; and finally, the intelligent control system performs long-term monitoring and feedback regulation on the soil condition, so that the maintenance energy consumption is reduced. According to the method, long-acting recovery of the degraded wetland is realized through a closed-loop system of soil matrix improvement, vegetation function configuration and feedback maintenance.

The invention provides a rural sewage treatment simulation optimization method based on a cellular automaton, which comprises the following steps of: establishing a cellular grid, and defining basic attributes of cells according to space coordinates, terrain types, population density and sewage treatment capacity; according to the sewage treatment scene, respectively establishing a cellular state evolution rule base; the sewage treatment scene comprises a pipe network collection type, an ecological wetland type and a decentralized recycling type; acquiring environmental parameters and pollutant parameters of a target area to be subjected to sewage treatment; selecting a cellular state evolution rule base according to input environmental parameters and pollutant parameters of a target area to be subjected to sewage treatment; and performing sewage treatment simulation, optimizing the sewage treatment simulation process by the cellular state evolution rule base, and outputting a sewage treatment facility layout scheme and a dynamic control strategy. The sewage treatment scheme can be quickly generated, the optimal sewage treatment scene model is automatically selected according to actual conditions, and accurate customization of the sewage treatment scheme is realized.

The invention discloses a hydro-junction ecological flow regulation and control system based on digital twinning, and relates to the technical field of intelligent ecological regulation and control. The system obtains digital elevation data DEM, geometric contour images and coupling power data of a riverbed and a wetland through multi-beam sonar, unmanned aerial vehicle remote sensing and a sensor group; and synchronization and preprocessing are realized in the twinborn simulation model to form a flow evolution data set and a water-sediment power data set. And constructing a dynamic connectivity driving force index Dcl based on the flow evolution data set to carry out flow driving force evaluation, constructing a comprehensive connectivity judgment index Eco to carry out ecological connectivity evaluation under the condition of sufficient driving force, and executing a corresponding regulation and control instruction according to an evaluation result. And dynamic adjustment of hub ex-warehouse flow and long-term maintenance of wetland ecological connectivity are realized. According to the system, real-time monitoring, evaluation and regulation of digital twin driving can be realized under a complex water and sediment power condition, and the guarantee capability of a hydro-junction to a wetland ecosystem is improved.

The invention discloses a multi-source remote sensing reflectivity fusion method based on orthogonal matching pursuit and physical constraint, and the method comprises the steps: taking a multi-source remote sensing image as a data basis, and constructing a multiband sparse dictionary through time sequence alignment and overlapping sampling; then, an orthogonal matching pursuit algorithm introducing physical constraints is utilized to gradually select an image atom which is most matched with a target date in a sparse reconstruction process, and physical consistency of a reconstruction result in the aspects of hydrological conditions, phenological characteristics, spectral reflectivity and the like is ensured; and finally, through residual error return correction, day-by-day seamless 30-meter six-waveband reflectivity reconstruction is realized. According to the method, the stability and the physical interpretability of a reconstruction result are remarkably improved while efficient calculation is kept, continuous, multi-band and high-resolution time sequence data generation can be achieved in complex ecological environments such as lake wetlands, and high-precision remote sensing data support is provided for hydrological process simulation, ecological environment evaluation and carbon cycle research.

The invention provides a wetland ecological restoration effect comprehensive evaluation method and system, and belongs to the technical field of big data analysis. According to the method, real-time data of multi-dimensional ecological elements such as water turbidity, vegetation coverage density and soil acidity and alkalinity are collected, a multi-dimensional element correlation matrix based on time sequence correlation is constructed, and the dynamic change frequency of each element is captured. Core influence factors are screened by quantifying the contribution degree of each element to ecological restoration, weight distribution corresponding to clustered element clusters is determined, and then an accurate quantitative score is generated and mapped into a clear restoration condition level through multiplication and summation of inter-cluster correlation coefficients and weights item by item. Meanwhile, an evolution track is compared and analyzed by combining historical time sequence data, and the weight is dynamically adjusted to ensure that evaluation adapts to an actual repair process. The comprehensive, dynamic and accurate evaluation of the wetland ecological restoration effect is realized, scientific support is provided for the accurate adjustment of the restoration strategy, and the fine management of the wetland and the sustainable development of the natural environment are guaranteed.

The invention relates to the technical field of remote sensing image processing, in particular to a wetland information extraction method and system based on multi-source remote sensing data fusion, and the method comprises the following steps: obtaining and fusing a wetland optical radar image and water level time sequence data, extracting near-infrared and back-scattering multi-source characteristic parameters to discriminate water body pixels, and extracting a water body image; and carrying out statistics on spatial connectivity aggregation to generate a water body plaque boundary, calculating an area perimeter and shape index comprehensive model to classify wetland types, and adjusting mismatching labels in combination with vegetation coverage and soil moisture to form a wetland information extraction result map. According to the method, the water body differential expression is enhanced through combined reflection and scattering characteristics, the water body and peripheral differential expression is enhanced through combined reflection and scattering characterization, boundary transition aliasing is restrained through bidirectional threshold constraint, plaque space integrity is restored and maintained through connectivity analysis, and type classification sensitivity is enhanced through morphological parameter combination. And the wetland expression accuracy and the type stability are improved through ecological attribute consistency correction.

The invention relates to the technical field of environmental science, discloses a wetland carbon cycle model construction and optimization method and system, and aims to solve the problems of complex wetland carbon cycle process, insufficient model precision generalization, difficulty in coordination of multi-carbon component management decisions and the like. The method comprises the following steps: acquiring preprocessed multi-source wetland data, and constructing multi-scale spatial-temporal characteristic representation; synergistically simulating the dynamic state of the carbon components of the wetland through a mechanism fusion network; and based on a simulation result, a management strategy is generated through multi-objective optimization, scene prediction is performed, and a response is evaluated. The system comprises a data acquisition and preprocessing module, a multi-scale spatial-temporal feature coding module, a mechanism fusion network module, a multi-target optimization decision module and a scene prediction visualization module. According to the technical scheme, a high-precision and high-generalization model can be constructed, deep learning and a physical mechanism are fused, multi-target optimization decision and scene prediction capabilities are provided, multi-carbon components are effectively simulated and optimized, and the wetland carbon management precision and efficiency are improved.

The invention discloses an urban small and micro wetland digital evaluation and parameterization combination construction method and system. The method comprises the steps that an unmanned aerial vehicle collects site multi-source remote sensing data and preprocesses the site multi-source remote sensing data; performing digital evaluation on the ecological factors of the site to obtain site characteristics; constructing a standard ecological factor code label set according to a preset evaluation standard, and allocating corresponding codes to the site based on site features; splitting the ecological functions of the ecological factors into different functional components capable of being spliced and forming a component library, wherein each functional component has an adaptive rule and a functional component code associated with a standard ecological factor code; a site scene type and a construction target are judged, and adaptive conditions are determined; and calling the parameterized functional component library based on the standard ecological factor codes, matching the corresponding functional components according to the adaptation conditions and the adaptation rules, and outputting a functional component code combination configuration scheme through parameterized configuration so as to generate an urban small and micro wetland design scheme. According to the method, the design efficiency of the urban small and micro wetland design scheme can be improved.

The invention relates to the technical field of intelligent data identification, in particular to a wetland ecological drought condition identification method based on multi-source data. According to the technical scheme, the method comprises the following steps: data acquisition: acquiring a multi-source data set of a target wetland region in a preset time sequence; the multi-source data set at least comprises a remote sensing reflectivity data set, a surface temperature data set, a meteorological reanalysis data set and an on-site monitoring hydrological data set; and data processing: sequentially carrying out space-time registration, denoising and missing value interpolation processing on the multi-source data set to generate a standardized space-time data cube. According to the method, multi-source data can be integrated to generate a standardized spatio-temporal data cube, each ecological drought index threshold value is dynamically determined based on the background of the historical wet season of the wetland, the comprehensive drought intensity is calculated in a weighted mode according to the wetland type, and accurate wetland ecological drought spatio-temporal distribution, grade sequence and early warning information are output after multi-scale verification. And a basis is provided for wetland ecological protection and water resource regulation and control.

The invention relates to the technical field of computer vision and image processing, in particular to a forest wetland environment transition zone identification method and system for an unmanned aerial vehicle. The method comprises the steps of obtaining various prior data layers of a detection area and fluctuation scales corresponding to the prior data layers, taking the fluctuation scales as weights, obtaining similarity degrees between area boundaries of different prior data layers, and identifying similar boundary groups based on the similarity degrees; obtaining the environment fusion degree of the similar boundary groups; and based on the environment fusion degree, identifying an environment transition zone and an unmanned aerial vehicle flight focus region. By fusing prior data layers of DEM, hydrology, vegetation and the like, analyzing boundary similarity according to a fluctuation scale and identifying an environment fusion area, an environment transition zone and an unmanned aerial vehicle key monitoring area are further determined, targeted monitoring and identification of a key interface of a complex ecological crisscross zone are realized, the precision and efficiency of complex environment monitoring are effectively improved, and the method is suitable for popularization and application. And meanwhile, terrain and water area flight risks are avoided.

The invention belongs to ecological environment engineering, and particularly relates to a river and lake wetland zoning and classifying ecological water demand fine accounting method, which comprises the following steps of S1, performing zoning and classifying on a river and lake wetland of a research area; s2, establishing a space-time coupling hydrodynamic model based on a partition classification relationship; s3, constructing a multi-factor ecological response model, and calculating an ecological suitability index of each partition; s4, establishing a multi-objective optimization model, and performing optimization solution on the ecological water demand of the partition by combining ecological benefits, water balance and process smoothness objectives; and S5, performing robust correction on an optimization result by adopting an uncertainty analysis method to obtain a final ecological water demand distribution result. By establishing a river and lake wetland partition classification spatial database based on digital elevation, river network distribution, land utilization and ecological attribute information, fine description and dynamic association of different ecological functional areas are realized, and the effects of ecological process differentiation characterization and remarkable improvement of water demand accounting precision are obtained.

The invention provides a coastal wetland ecological restoration system construction method based on a native function, and the method comprises the steps: carrying out the comprehensive evaluation W of an ecological condition and the dynamic prediction of a stress factor f through employing an analytic hierarchy process and a machine learning model in combination with the historical data, the ecological current situation and the real-time monitoring data of an ecological system in a restoration region; determining a degradation degree and a restoration target according to the ecological condition comprehensive evaluation W and the stress factor f; performing repair layout on the repair target, wherein the repair layout comprises corresponding engineering measures and management measures; and an ecological monitoring system and an evaluation index system are established. The method has the following advantages that comprehensive evaluation of the ecological condition of the coastal wetland is achieved through the analytic hierarchy process, restoration measures and management measures are effectively taken, and ecological restoration of wetland native function remodeling is ensured; a perfect system construction method is provided for ecological restoration of the coastal wetland, and important social, economic and environmental benefits are achieved.