84 results about "Ecoregion" patented technology

The invention discloses a water conservancy and hydropower project ecological scheduling optimization method, and relates to the technical field of water conservancy and hydropower ecological scheduling, and the method comprises the steps: carrying out the fine ecological region division of a river channel, and dividing the river channel into a plurality of regions with definite ecological functions through combining a plurality of factors. By monitoring the ecological water demand of different ecological regions in the river channel in real time, the actual demand condition of each ecological region is accurately mastered, so that the ecological scheduling scheme is individually formulated according to the characteristics of different ecological regions, the scheduling accuracy is improved, the ecological model comprehensively considers multiple factors such as hydrology, water quality, ecology and meteorology, and the ecological scheduling efficiency is improved. According to the method, the change trend of the ecological water demand of different ecological areas can be predicted, a suitable living environment is provided for various aquatic organisms by accurately meeting the ecological water demand of different ecological areas, protection of rare and endangered species is facilitated, stable development of biocenosis is promoted, and the biodiversity level of a whole river ecosystem is improved.

The invention provides an ecological restoration area sea grass bed health state monitoring method, and relates to the technical field of sea grass bed ecological restoration, and the method comprises the steps: obtaining a sea grass bed ecological region, carrying out the region division, and determining a plurality of sea grass bed monitoring regions; according to the image sensor, combined with the image feature detection channel, sea grass state feature analysis is carried out, and a plurality of sea grass state feature analysis results are generated; performing illumination detection feature analysis according to the illumination sensor in combination with the illumination feature analysis channel, and generating a plurality of illumination detection feature analysis results; and carrying out abnormity management on the corresponding sea grass bed monitoring area, carrying out abnormity linkage analysis and carrying out abnormity management. The technical problems that the prior art is limited by resolution and environmental factors, the microscopic state change of the sea grass bed cannot be accurately captured, the health state of the sea grass bed is difficult to comprehensively analyze by integrating multiple monitoring dimensions, and the accuracy and comprehensiveness of state monitoring of the sea grass bed are insufficient are solved.

The invention provides an ecological environment remote sensing image classification and feature extraction method based on deep learning, and the method comprises the steps: obtaining the remote sensing image data of a target ecological region, and obtaining the region index data of five ecological indexes; ecological sensitivity evaluation and fusion of the five ecological indexes are carried out, and a plurality of ecological sensitivity sub-regions are divided; and according to the ecological sensitivity data of each ecological sensitivity sub-region, selecting an optimal feature extraction algorithm in combination with the importance weight coefficient to perform feature extraction so as to finally obtain a feature data set. The remote sensing image data can be analyzed and processed purposefully and emphatically, and the processing efficiency is improved on the premise that the quality requirement is met.

The invention discloses a fishery ecological environment restoration method and system based on a symbiotic competition mechanism, and the method comprises the steps: collecting all environment monitoring parameters of each fishery ecological region, carrying out the statistics of the vegetation coverage area of various types of plants and the biological population density of various types of organisms, obtaining an environment time-varying sequence and a community time-varying sequence, and carrying out the calculation of the environment time-varying sequence and the community time-varying sequence. Constructing a symbiotic competition specification matrix and an ecological environment strong dependency matrix, calculating an ecological diverse degeneration index, dividing an ecological degeneration sign area and an ecological diverse area, calculating a balance proportion of each species and a competition superior and disadvantage imbalance factor of each species in each ecological degeneration sign area, and calculating a symbiotic competition standard matrix; and obtaining ecological restoration key species of each ecological degradation sign area, and performing fishery ecological environment restoration on each ecological degradation sign area. According to the fishery ecological environment restoration method and system based on the symbiotic competition mechanism provided by the embodiment of the invention, the fishery ecological environment restoration efficiency is improved.

The invention relates to the technical field of artificial intelligence, and discloses a natural resource ecological protection and restoration engineering monitoring method, which comprises the following steps: acquiring image data of an ecological region, and generating an environment change index of the ecological region according to the image data and a preset environment change index generation algorithm; generating an environment change type of the ecological region according to the environment change index; generating a species community and an ecological niche of the ecological region according to pre-acquired species data; generating a biological change index of the ecological region according to the species community and the ecological niche; and generating a monitoring report of the ecological region according to the environmental change type and the biological change index, and performing ecological protection and ecological restoration on the ecological region according to the monitoring report. According to the invention, the efficiency of natural resource ecological protection and restoration engineering monitoring can be improved.

The invention provides a key species population spatial distribution quantification method and system in a complex ecological system, and the method comprises the steps: carrying out the feature extraction of biological and environmental data collected in a target ecological region, and carrying out the fusion of the extracted multi-modal features, and generating a comprehensive feature vector; based on the target large model, analyzing the comprehensive feature vector, identifying species in the target ecological region, and obtaining species identification information of each species; based on the species identification information and the comprehensive feature vector corresponding to the target ecological region, quantifying a species population space distribution condition, and generating species population quantification information at least comprising a population distribution diagram, a population density diagram and a population dynamic change diagram; and based on the species population quantitative information and the collected original data, generating and displaying a quantitative report. According to the method, the species can be intelligently, efficiently and accurately identified based on the large model, the distribution condition and dynamic change of the species can be visually displayed, a quantitative report is provided, and a powerful basis is provided for ecological protection and management.

The invention discloses an ecological environment dynamic monitoring system based on machine learning, and relates to the technical field of artificial intelligence. The system comprises a sensor monitoring part, a feature extraction and mapping part, a support vector analysis and decision part and a prediction risk assessment part. The sensor monitoring part comprises a sample ecological region sensor group and a target ecological region sensor group; the sample ecological region sensor group comprises a plurality of same sample sensor groups; the target ecological region sensor group only comprises one target sensor group which is the same as the sample sensor group; the feature extraction and mapping part is used for obtaining mapping features; constructing a dynamic system state reconstruction equation; the support vector analysis and decision part is used for constructing an optimal support vector prediction controller; and the prediction risk assessment part is used for judging whether ecological environment early warning needs to be carried out or not according to the prediction judgment value. According to the invention, comprehensive monitoring, precise modeling and intelligent early warning of the ecological environment are realized.

The invention discloses a water conservancy project ecological construction method and system based on artificial intelligence, and relates to the technical field of ecological system simulation, and the method comprises the steps: collecting historical ecological event data of each region of a water conservancy project, analyzing the causal association between events based on an artificial intelligence model, and calculating and dynamically updating the association degree index between any two regions; constructing a regional association network based on the association degree indexes, calculating core scores of nodes in the network to identify a core region, and dynamically improving the monitoring sampling frequency of ecological data for the core region; and when an abnormal state is monitored in a single region, predicting the abnormal risk probability of other regions, and generating and recommending an optimal coping plan. Compared with the prior art, the method has the advantages that by constructing a dynamic regional correlation analysis system, the mutual influence between ecological regions is quantified, the monitoring resources are distributed uniformly to be intelligently and optimally configured based on the network core degree, and the monitoring efficiency and the capturing capacity of key information are remarkably improved.

The invention provides a method for quantifying the influence of a black land cultivated land ecological barrier function on the grain yield, and relates to the technical field of grain yield influence assessment, and the method comprises the steps: obtaining the climate, soil, hydrology and land utilization geospatial data of a target ecological region; determining a black land cultivated land ecological barrier range, and calculating service function values of five types of ecological systems including habitat quality, water source conservation, soil conservation, water quality purification and carbon sequestration storage; generating an ecological barrier function comprehensive value ESI through normalization and equal weight superposition; calculating and normalizing the black land cultivated land grain yield in combination with remote sensing data and a harvest index method; and based on multi-scale window random sampling, fitting a non-linear relationship between ESI and grain yield, and determining an optimal proportion of an ecological barrier grid proportion, a minimum threshold value of an ecological function and a saturation threshold value of a cultivated land ecological function through derivative analysis. The problem of landscape or regional scale quantification is solved, and an accurate basis is provided for black land ecological restoration and grain safety decision making.

The invention relates to the technical field of ecological system health assessment, in particular to a regional ecological system health assessment method based on remote sensing data. The method comprises the following steps: acquiring a multi-temporal remote sensing image of a target ecological region; performing wave band reflectivity processing on the multi-temporal remote sensing image, and extracting lake attribute parameters; recognizing a hub lake set based on lake attribute parameters, evaluating lake area and vegetation coverage change to quantify regional ecological degradation, and comprehensively evaluating a regional ecological health index of a current state; the ecological water level of the hub lake is regulated and controlled according to the regional ecological health index, and an ecological water supplementing scheme of the atrophic lake is formulated, so that water resource management of the ecological system of the lake group region is achieved. Through coupling lake group network topology analysis and water volume space redistribution, systematic evaluation of lake group ecological health is realized so as to accurately identify key hub lakes and support differentiated water resource management.

The invention relates to the technical field of water ecology protection and restoration, in particular to an early warning scheduling optimization decision-making method for water ecology protection and restoration. By fusing the data of the fixed water quality monitoring equipment group and the mobile water quality monitoring equipment group, the coverage limitation of a single fixed monitoring point is broken through, and the comprehensive perception of a water ecological area is realized; meanwhile, the total water quality anomaly value is calculated based on analysis anomaly from three dimensions of biological activity, substance exchange and pollution form, so that the accuracy and comprehensiveness of pollution level judgment are greatly improved, and misjudgment of a single index is avoided; the traceability priority is accurately determined by quantifying the pollution migration probability of each monitoring direction; and a dynamic monitoring unit is combined to control verification of a mobile monitoring point, a preferable pollution deduction direction and an early warning area are quickly locked, the hysteresis of manual troubleshooting is reduced, an efficient closed loop from pollution identification to traceability early warning is realized, and accurate decision support is provided for timely pollution blocking and restoration.

The invention relates to the technical field of remote sensing monitoring, and discloses a remote sensing dynamic monitoring method for a sensitive ecological region and an embankment along a river, which comprises the following steps: dividing the sensitive ecological region and the embankment along the river, and collecting long-time-sequence multi-source remote sensing data and ground actual measurement data; preprocessing the Landsat series satellite image data, calculating an ecological index, performing regression analysis, and constructing a comprehensive ecological index monitoring model; the Landsat series satellite image data and the actually measured water level data are fused through a spatial interpolation method, and a water level safety threshold model is constructed; the method comprises the following steps: preprocessing Sentinel-1 / 3 satellite data, screening image pairs subjected to interference processing, and calculating a differential interference phase to solve terrain deformation rates of a sensitive ecological region and an embankment along a river; performing weight assignment and scoring grade setting on the ecological state, the water level state and the terrain state according to an importance principle, and performing summation through a weighted average method to obtain an overall ecological environment safety condition; the method improves the monitoring precision of the ecological environment.

The invention relates to an ecological source identification method and system based on ecological system service and ecological sensitivity evaluation. The method comprises the following steps: acquiring original data for evaluation and analysis of a research area in a preset time range, and performing ecological system service function importance evaluation and analysis and ecological sensitivity evaluation and analysis to obtain an ecological system service function importance level and an ecological sensitivity level; extracting plaques with high ecological system service function importance level, high ecological sensitivity level and area not smaller than a set area threshold as preliminary ecological plaques, selecting an ecological source from the preliminary ecological plaques according to a landscape connectivity analysis result, and determining the stability level of the ecological source; the system comprises a preprocessing module, a calculation module, an extraction module, a screening module and a determination module. The method is simple and efficient in calculation process, has high flexibility, and can assist a decision maker to quickly and accurately lock a key ecological region in dynamic environment transition.

The invention relates to the technical field of ecological environment monitoring, in particular to an ecological environment monitoring system based on the Internet of Things, which comprises a monitoring module for acquiring environmental data of an ecological area and analyzing to obtain an unqualified water quality parameter deviation ratio and an unqualified soil parameter deviation ratio; the risk analysis module is used for calculating and analyzing an environment evaluation value of each ecological region based on the disqualified water quality parameter deviation ratio and the disqualified soil parameter deviation ratio; the risk assessment module is used for comparing the total environment assessment value with a total environment assessment threshold value and generating an ecological environment risk signal; the influence analysis module is used for analyzing the risk diffusion capability of the ecological environment and outputting to obtain an environmental influence assessment total value; the influence evaluation module is used for comparing the total environment influence evaluation value with a total environment influence evaluation threshold value and generating an ecological environment influence signal; according to the invention, real-time monitoring of the current environmental risk degree of the ecological environment is realized, and monitoring of the environmental influence degree of the ecological environment is also realized.

The invention relates to the field of forest fire alarm, in particular to an ecological environment monitoring method, device and equipment based on a GIS technology. The method comprises the following steps: firstly, obtaining each frame of infrared image of an ecological region to be detected, and obtaining high-temperature characteristic values of pixel points in the infrared images and a plurality of high-temperature regions according to the distribution of gray values of the pixel points in each frame of infrared image; obtaining a high-temperature coefficient of the high-temperature region according to the high-temperature characteristic value of the pixel point in each high-temperature region in the infrared image and the gradient value of the edge pixel point of the high-temperature region; and analyzing the high-temperature coefficients of the same high-temperature area in different frames of infrared images, extracting fire areas, analyzing the hazard degree of each fire area, and sending different levels of alarm information to each fire area in the ecological area to be detected based on the hazard degrees. According to the invention, alarms of different levels can be accurately made for different fire areas, and the forest fire monitoring effect is improved.

The invention discloses a grain storage sub-ecological region intelligent division method based on a spatial analysis and clustering technology, and the method comprises the following steps: 1, obtaining the geographic position data, meteorological data and grain condition data of each sampling point in a research region, and enabling the data to serve as the sample data of each sampling point; taking the meteorological data and the grain condition data of each sampling point as grain storage variables of the sample; wherein the geographic position information comprises the longitude, the latitude and the altitude of the sampling point, the meteorological data comprises the air temperature, the relative humidity, the precipitation and the sunshine duration of the sampling point, and the grain condition data comprises the grain temperature of the granary corresponding to the sampling point; step 2, calculating a global Moran index of each grain storage variable in each sampling point, and respectively screening out characteristic indexes in the meteorological data and the grain condition data according to the global Moran index; and step 3, determining a clustering target number K, clustering sampling points in the research area by using a K-means clustering algorithm, and dividing the research area into K grain storage sub-ecological areas.

The invention relates to the technical field of water environment and water ecology safety, and discloses a water ecology risk management system, an evaluation method, equipment and a storage medium. According to the invention, risk assessment can be systematically carried out on the to-be-assessed water ecological area through the risk assessment module, and the risk assessment result is converted into different colors through the risk early warning module and displayed on the map, so that a user can rapidly know the risk distribution condition of the water ecological area. Furthermore, the risk color is hidden when the map is not used and is displayed when the user is interested in the specific target area and the map is amplified, so that disordered interference of information is avoided, and the requirement of the user for detailed risk information of the local area is met. And finally, the visual color information is converted into specific text description, which is convenient for the user to observe, so that the user can know the specific condition of the area in time, the life safety of the user is ensured, and the economic loss of the user can be avoided to a certain extent.

The invention relates to the technical field of risk assessment, in particular to a grassland ecosystem comprehensive drought risk assessment system based on multi-source data. The risk feature highlighting characterization value is calculated by determining the feature highlighting factors of the different risk areas of the grassland, so that the feature highlighting sorting sequence of the risk areas of the grassland is rapidly determined, the precision of grassland comprehensive drought risk assessment is improved, and meanwhile, the risk assessment accuracy is improved. According to the grassland actual data uploaded by the user side and the drought risk index information corresponding to the grassland ecological system, the maximum feature highlighting characterization value of each risk area of the grassland can be accurately obtained, and the accuracy of comprehensive drought risk assessment of the grassland ecological area is improved.

This invention provides a method and system for mine ecological restoration, relating to the field of ecological environment restoration technology. The method includes: obtaining soil damage characteristics based on a pre-acquired ecological area to be restored; obtaining a mine geological composition based on the soil damage characteristics and pre-acquired restoration goals, combined with geological soil selection principles; obtaining a plant species composition based on sampling results from pre-acquired sample plots and restoration goals; and performing ecological restoration of the ecological area to be restored based on the mine geological composition and plant species composition. This invention accelerates the process of geological soil formation and vegetation restoration in abandoned open-pit mines, improves the tolerance of restored vegetation communities to climate fluctuations, and truly achieves precise and sustainable ecological restoration of open-pit mines.

The present invention relates to the technical field of environmental assessment, and discloses a multi-dimensional and multi-granularity environmental impact assessment method for ecological sensitive areas. The method includes: constructing an environmental assessment index system for ecological sensitive areas, collecting index data according to the index system and performing preprocessing; improving the data quality of the preprocessed index data; performing multi-level filtering on the enhanced index data to obtain the filtered key index data; and using the environmental assessment model for ecological sensitive areas to receive the key index data and conduct environmental impact assessment. The present invention selects multi-granularity environmental assessment indicators for ecological sensitive areas from multiple dimensions such as pollution control, ecological environment, resource environment, environmental planning, and environmental quality of ecological regions, sequentially performs cleaning of abnormal data and cleaning of redundant or non-critical indicators on the index data, and performs convolution, mapping, and correction processing on the cleaning results to obtain an environmental impact assessment result representing the ecological sensitivity of the region.

The invention provides a forest grass ecological environment monitoring system and method, and the method comprises the steps: extracting dynamic significance features from a multi-temporal remote sensing image, and generating a spatial-temporal change diagram of forest grass ecological elements according to the dynamic significance features; screening out a plurality of ecological response characteristics reflecting the target forest grass ecological region according to the spatial-temporal change diagram, and further converting all the ecological response characteristics into image quantitative indexes of the forest grass ecological state; determining the dynamic influence quantity of the environmental factors on the forest grass ecological state in the forest grass ecological environment based on the incidence relation between the environmental factors and the vegetation characteristics in the multi-modal environmental data; and carrying out evolution prediction on the forest grass ecological state in the target forest grass ecological region through the image quantitative index and the dynamic influence quantity to obtain an ecological environment evolution monitoring result of the target forest grass ecological region. By adopting the scheme of the invention, the evolution prediction of the forest grass ecological state can be realized in a complex and changeable forest grass ecological environment, so that the monitoring capability of the forest grass ecological state in a large range is improved.

The invention discloses an ecological biomass estimation method based on fusion of a remote sensing image and ground observation data, which relates to the technical field of ecological biomass estimation, and comprises the following steps: obtaining a remote sensing image of an observation area, and carrying out image preprocessing on the remote sensing image to obtain an enhanced image; dividing different ecological regions; extracting ground observation data; dividing the similar ecological areas into an ecological area group; calculating a fluctuation index of the ecological biomass in the similar ecological region; analyzing the ground observation data in the different ecological area groups, and calculating the density relationship of the ecological biomass in the different ecological area groups; the ecological biomass in other areas to be estimated is estimated; the method is used for solving the problem of large deviation of a biomass estimation result caused by insufficient consideration of factors influencing biomass distribution in an existing ecological biomass estimation technology.

The invention relates to the technical field of environment assessment, and discloses a multi-dimensional multi-granularity ecological sensitive area environment influence assessment method, which comprises the following steps: constructing an ecological sensitive area environment assessment index system, and collecting index data according to the index system and preprocessing the index data; performing data quality improvement on the preprocessed index data; performing multi-stage filtering on the enhanced index data to obtain filtered key index data; and using the ecological sensitive area environment evaluation model to receive the key index data and perform environment influence evaluation. According to the method, multi-granularity ecological sensitive area environment evaluation indexes are selected from the multi-dimensional level of pollution control, ecological environment, resource environment, environment planning, environment quality and the like of an ecological area, and abnormal data cleaning and redundant index or non-key index cleaning processing are sequentially carried out on index data; and carrying out convolution, mapping and correction processing on the cleaning result to obtain an environmental influence assessment result representing the regional ecological sensitivity.

The present invention discloses a method, device and storage medium for generating an ecological region temperature field based on GIS, the method comprising: obtaining multiple temperatures of multiple observation points in an ecological region; obtaining GIS data corresponding to the ecological region, the GIS data comprising: multiple GIS grids and geographic information parameters corresponding to each GIS grid; performing data fitting on the geographic information parameters corresponding to the multiple observation points and the temperature, and obtaining a temperature-geographic information parameter conversion formula for the corresponding relationship between the temperature and the geographic information parameter in the ecological region; based on the temperature-geographic information parameter conversion formula and the geographic information parameters corresponding to each GIS grid, calculating the temperature corresponding to each GIS grid, and displaying the temperature on each GIS grid. The method can also achieve equivalent temperature monitoring under limited monitoring conditions, with low monitoring cost, and the monitoring results meet the requirements.

The invention discloses an ecological operation data acquisition AI analysis system, which comprises a distributed multi-source environment collection unit, an edge computing platform and a cloud service platform, and is characterized in that the edge computing platform is in communication connection with the cloud service platform, and the edge computing platform is in communication connection with the distributed multi-source environment collection unit; a fire risk analysis module is integrated in the cloud service platform, the multi-source environment collection unit collects ecological region environment parameters, and the edge calculation unit preprocesses collected data; and the fire risk analysis module obtains the preprocessed data and outputs a fire risk level. Compared with the prior art, the ecological operation data acquisition AI analysis system and the operation method have the advantages that operation and use are convenient, and data acquisition can be carried out to complete ecological safety protection.

This application provides an online authentication method and apparatus for ecological asset data based on privacy computing. The method includes: acquiring multi-source ecological asset data for a target ecological region and separating it into environmental physical features and ecological asset accounting features; generating spatiotemporal zero-knowledge proofs for the environmental physical features and generating homomorphic ciphertext for the ecological asset accounting features; constructing a dual-track verification task for the spatiotemporal zero-knowledge proofs and homomorphic ciphertext in a trusted execution environment; executing the dual-track verification task for cross-domain verification to obtain multi-dimensional verification results; and generating an online authentication certificate based on the multi-dimensional verification results and the consensus digital signature output by the trusted execution environment when the multi-dimensional verification results meet the composite authenticity conditions. This application, by combining privacy computing with a trusted execution environment, improves the privacy protection level of ecological asset data in the cross-domain verification process and enhances the verification consistency between physical features and economic indicators.

The application provides an Internet of Things intelligent management system for construction machinery, and relates to the technical field of construction machinery management, comprising: a sensing and collecting module for collecting device state parameters and environmental parameters of the construction machinery in real time; a space-time data processing module for processing, storing and analyzing the device state parameters and environmental parameters; an intelligent decision module for generating intermediate decision instructions; a decision execution module for issuing the intermediate decision instructions to a target construction machinery control system; and an ecological coordination module for interacting with an external ecological supervision system and executing an ecological compensation strategy. The application realizes Pareto optimal solution among conflicting targets such as energy consumption, efficiency and failure rate through an intelligent decision module based on a multi-objective genetic algorithm; through an ecological red line dynamic matching algorithm, high-precision identification of the boundary of a work prohibited area is realized, and in combination with the migration cycle data of migratory birds, the interference rate of key ecological areas is reduced, so that the protection effect of biological diversity is improved.

The application discloses a kind of marine ecological space red tide risk area division methods, it is related to marine ecological regional division technical field, including the following steps: through monitoring point collection sea water body's chemical oxygen demand, inorganic nitrogen, active phosphate and dissolved oxygen, obtain the original data of sea water body;And pretreatment is carried out, obtain the reference data of sea water body, and establish water body parameter variation index, obtain water body variation index data;And obtain the reasonable threshold of water body parameter variation index, obtain index reasonable threshold information;Based on the chemical oxygen demand of collected sea water body, inorganic nitrogen, active phosphate and dissolved oxygen, and according to index reasonable range information, divide red tide risk area;The present application is used to solve the problem that the existing marine ecological regional division technology cannot be combined with the eutrophication index of water body according to the index change of regulatory sea water body when dividing red tide high-risk area in specified sea area, and timely and reliably divide out red tide high-risk area.

The invention relates to the technical field of ecological monitoring, and provides a visual ecological intelligent monitoring system and method based on three-dimensional simulation, and the system comprises a data optimization module which is used for calculating an angle abnormal factor between data in an ecological data flow, carrying out the quality optimization of the ecological data flow, and obtaining a target data flow; the image partitioning module is used for performing image partitioning processing on the multi-temporal remote sensing image to obtain a multi-temporal water area map and a multi-temporal landform map; the landform analysis module is used for carrying out semantic segmentation on the landform structure to obtain landform types and calculating the landform transition amplitude between the landform types; the water area analysis module is used for calculating the element deviation amount corresponding to each element in the water area elements and analyzing the water area evolution trend of the ecological area; and the ecological monitoring module is used for constructing a three-dimensional simulation area corresponding to the ecological area and dynamically monitoring the three-dimensional simulation area to obtain an area ecological monitoring result. The invention aims to improve the accuracy of ecological monitoring.

The invention relates to the technical field of hydro-fluctuation belt ecological environment monitoring, and provides a hydro-fluctuation belt ecological environment monitoring method, system and device and a storage medium, and the method comprises the steps: obtaining monitoring information of a falling belt coverage canceling region, ecological vegetation and a character target; decoding the monitoring image of the hydro-fluctuation belt based on the monitoring information, and performing frame extraction according to a preset time interval to obtain a to-be-analyzed image; and calculating and analyzing the proportion of the bare land area of the hydro-fluctuation belt area in the whole hydro-fluctuation belt area, the proportion of the ecological vegetation area in the whole hydro-fluctuation belt area and the appearance duration of the figure target based on the to-be-analyzed image, and outputting early warning information. Therefore, by comparing the bare land area of the hydro-fluctuation belt, the ecological vegetation area and the appearance duration of the person target with the preset threshold value and recording the change of the area of the concerned area according to the time change, the purposes of ecological monitoring and early warning management are achieved, and the behavior of artificially entering the ecological area of the hydro-fluctuation belt is sensed and early warned in real time. Man-made interference on the ecological environment of the hydro-fluctuation belt is avoided.