47 results about "Ecological indicator" patented technology

The invention relates to the technical field of intelligent mine and environmental protection crossing, and discloses a mine development ecological data fusion and causal mining method based on a double-lineage knowledge graph. The method comprises the steps of constructing a double-pedigree domain ontology model comprising a production activity pedigree and an ecological response pedigree, carrying out multi-modal data space-time alignment and standardization, constructing a dynamic map reflecting the real-time state of a mine, predicting future ecological indexes by using a time sequence diagram neural network introduced with physical constraints, and carrying out real-time monitoring on the real-time state of the mine. And calculating the contribution degree of each production link to abnormity by utilizing anti-fact reasoning so as to lock a disaster-causing source, and generating a production regulation and control instruction according to a causal analysis result, and feeding back and executing the production regulation and control instruction. According to the method and the system, full-process traceability and accurate regulation and control of mine environment problems such as surface deformation and water and soil pollution are realized, so that the problems that data multi-source heterogeneous is difficult to fuse and the causal relationship is difficult to confirm in mine ecological environment monitoring are solved.

The invention relates to the technical field of environment monitoring, in particular to a seawall ecologicalization real-time monitoring method based on multi-source data fusion. The method comprises the following steps: acquiring structure monitoring data, ecological monitoring data and water quality monitoring data of a seawall through an Internet of Things sensor, and acquiring remote sensing data of a seawall area in combination with satellite remote sensing and an unmanned aerial vehicle image; performing space-time registration and fusion on different data sources to generate a unified multi-source fusion data set; identifying a red tide abnormal event based on the fused data set, and constructing a red tide influence conduction model for predicting the damage degree of the red tide to the ecological system and the influence of the red tide to the stability of the embankment body; establishing a coupling evaluation model of ecological indexes and structural indexes, calculating a coupling coefficient by using a fuzzy comprehensive evaluation method, dynamically adjusting ecological and structural weights according to a model output result, and calculating a seawall comprehensive health index; graded early warning information is automatically generated according to a preset threshold value, and collaborative monitoring and intelligent early warning of seawall ecology and structure safety are achieved.

The invention discloses a water quality probability forecasting method based on Bayesian multi-time-sequence deep learning. The method comprises the following steps: S1, determining a forecasted water environment water ecological index, a driving index and a forecasting day number; s2, collecting time sequence data monitored by the forecasting indexes and the driving indexes, and after data preprocessing, constructing a data set required by model construction; s3, carrying out data division on the time sequence data, constructing a driving index forecasting model by adopting a multi-time sequence deep learning method, and carrying out parameter learning by selecting a Bayesian random discarding method; s4, performing effect evaluation on the accuracy and precision of the model, and adopting a hyper-parameter optimization method to improve the simulation forecast effect; s5, carrying out model training by adopting all data without segmenting the training set and the test set, carrying out water quality probability forecasting by utilizing the trained model, and outputting a forecasting mean value and a confidence interval; according to the method, the confidence interval is output while high-precision prediction is provided, and the scientificity and stability of prediction are improved.

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

The invention relates to the technical field of intelligent environmental protection monitoring, in particular to a method for intelligently monitoring and analyzing land utilization change in an ecological protection red line, which comprises the following steps of: acquiring a historical remote sensing image, extracting pixel-level vegetation and artificial indexes, constructing an ecological index time sequence data set, and constructing an ecological index time sequence data set based on the data set; a dynamic baseline prediction model fusing a long-term trend term, a seasonal periodic term and a standard deviation is established for each pixel, personalized prediction of a theoretical state of the pixel is realized, abnormality diagnosis is performed through comparison with a confidence interval output by the model, and an abnormal pixel is marked as a collaborative abnormal pixel, so that comprehensive risk assessment is carried out, and the risk assessment efficiency is improved. The method comprises the steps of calculating risk scores of all indexes and carrying out weighted fusion to obtain a comprehensive risk index, then dividing risk levels, outputting an anomaly diagnosis report, finally, carrying out reverse calibration on model parameters based on confirmed anomaly cases, and mining risk modes from case characteristics through unsupervised clustering.

The invention discloses an ecological product value analysis method and system based on multi-source data fusion, and relates to the technical field of ecological product value analysis. Original ecological data are divided into two-dimensional space grid units according to a fixed scale through a space grid construction and index unit; according to the method, automatic mapping from an actual geographic coordinate system to an analysis grid unit is realized, so that multi-source data has a unified projection basis in space, the problems that multiple data source space references are inconsistent and results are difficult to transversely compare in original ecological evaluation are solved, and a strict space organization structure is provided for subsequent ecological supply modeling. In the process of mapping the ecological indexes to the grid units, the system designs a neighborhood interpolation-based mechanism for averaging and filling multiple observation points and invalid units, so that the problem of local deficiency caused by non-uniform distribution of the observation points or influence of shielding on remote sensing data in field sampling is effectively relieved, and the integrity and analysis reliability of a spatial expression matrix are improved.

This invention discloses a comprehensive assessment method and system for wetland ecological quality based on multi-indicator fusion, belonging to the field of wetland ecological protection technology. The method includes acquiring water environment index data, biodiversity index data, carbon storage index data, and remote sensing images of wetland edges; establishing a multi-indicator fusion model based on the water environment index data, biodiversity index data, and carbon storage index data to generate a basic wetland ecological quality index; generating a predicted value of the basic wetland ecological quality index based on the basic wetland ecological quality index; and generating a comprehensive wetland ecological quality index based on the remote sensing images of wetland edges and the predicted value of the basic wetland ecological quality index, and assessing the wetland ecological quality. This invention can integrate multi-dimensional ecological indicators such as water environment, biodiversity, and carbon sink function, achieving dynamic prediction of wetland ecological quality and quantitative assessment of the impact of external pressures, thus improving the comprehensiveness and foresight of the assessment results.

The present application relates to the technical field of marine ecological environment monitoring, and particularly relates to a marine ecological environment assessment and early warning system based on big data and AI, comprising a multi-source data fusion module, a dynamic feature extraction module, a meteorological disturbance coefficient calculation module, an ecological index generation module and a coupling early warning generation module; wherein: the multi-source data fusion module is used for real-time collection of multi-source data; the dynamic feature extraction module is used for extraction of 72-hour change gradients of three types of core parameters; the meteorological disturbance coefficient calculation module is used for calculation and output of meteorological disturbance coefficients; the ecological index generation module is used for generation of water quality deterioration indexes and biological stress indexes; and the coupling early warning generation module is used for output of ecological risk grade signals. Through real-time reduction of meteorological interference and weighted fusion of water quality deterioration and biological stress indexes, the present application can accurately assess marine ecological environment risks and provide scientific support for ecological protection and pollution early warning.

This invention discloses a method for assessing the impact of photovoltaic (PV) installations on grassland ecosystems based on multi-source remote sensing data. The method includes the following steps: constructing a multi-source remote sensing dataset of the PV installation area and surrounding grasslands; acquiring time series data of multi-dimensional ecological indicators such as vegetation, water, and energy; establishing multi-ring buffer zones based on the PV boundary, and extracting the variation characteristics of each ecological indicator within and outside the PV area and at different distances; and quantitatively assessing the intensity and spatial decay characteristics of the impact of PV installations on the grassland ecosystem through spatial difference analysis and comprehensive ecological impact indicators. This method enables long-term dynamic monitoring of the ecological effects of PV construction without ground-based observation, and has the advantages of high automation, strong scalability, and wide application range, providing scientific support for the ecological assessment and management of grassland renewable energy development.

The application relates to the technical field of ecological safety optimization, and discloses an ecological safety pattern intelligent simulation optimization system based on reinforcement learning. An experience pool forming module of the system divides historical optimization strategies into multiple experience layers to form a multilayer experience pool based on the gap between ecological indexes and strategy confidence of the historical optimization strategies. A strategy determining module determines intelligent optimization strategies at each stage based on a set ecological safety target state, and screens the multilayer experience pool to obtain experience optimization strategies in combination with strategy confidence and target matching degree. A strategy adjusting module adjusts the two strategies by using a dynamic mechanism to cope with real-time ecological changes, and determines a target optimization strategy. A simulation optimization module simulates and optimizes the ecological safety pattern based on the target optimization strategy. A state acquisition module acquires an actual state. An experience pool updating module updates the content of the experience layers based on the difference factors between the actual state and the target state, and perfects the multilayer experience pool data. The system can improve the dynamics and adaptability of ecological safety pattern optimization.

The invention belongs to the technical field of big data analysis and processing, and particularly relates to a geothermal development full-life-cycle carbon emission reduction and ecological cooperative gain accounting method. The method comprises the following steps of: 1, constructing a graph containing life cycle stage unit process nodes, space grid or plot nodes and ecological index nodes, and setting a process influence edge, a space adjacent edge and a space observation edge in the graph; 2, constructing a graph neural network model adopting a combination of a graph attention network layer and a graph convolutional network layer on the graph; and step 3, writing operation information of the target geothermal development scheme into attribute fields of process nodes of the life cycle stage unit and space grids or plot nodes to obtain a geothermal development full life cycle carbon emission reduction and ecological cooperative gain accounting result. According to the method, the phased influence of engineering activities, the spatial propagation characteristics and the dynamic response of an ecological system can be considered at the same time, so that the carbon emission reduction effect and the ecological cooperative benefit are presented in a spatialization mode on the full life cycle scale.

The invention relates to the technical field of tourism industry data analysis, and discloses a tourism resource development suitability analysis method and device based on resource partition. The method comprises the following steps: firstly, obtaining initial partitions, and calculating a tourism evaluation index of each initial partition; and then according to the tourism evaluation indexes corresponding to all the initial sub-regions, the to-be-analyzed region is divided into a plurality of tourism large regions, and tourism development levels corresponding to all the sub-regions in each tourism large region are basically equivalent. According to the method, the to-be-analyzed area is not regarded as a whole to directly analyze the tourism resource development suitability of the to-be-analyzed area, but places close to the tourism industry development level are clustered into a large tourism area by designing a corresponding partition scheme, so that the analysis of suitability indexes is more reasonable; and finally, the ecological index data and the cultural index data are used as analysis indexes, so that the tourism resource development suitability analysis of each tourism region is more reliable and accurate.

The invention belongs to the field of ecological environment protection and treatment, and discloses a water ecological environment deep learning prediction method based on space-time heterogeneity nesting. The method comprises the following steps: S1, preprocessing water ecology simulation prediction data; s2, fitting a water ecology basic model; s3, watershed spatial element information embedding and serialized interpolation are carried out; and S4, constructing a sampling point water ecological index prediction model. On the basis of a deep neural network algorithm coupling gradient lifting method, a nonlinear response relationship between environmental elements and water ecology evaluation indexes is fitted, and the problem of simulation difficulty caused by a complex physical, chemical and biological multi-process interaction mechanism is solved; the spatial distribution data and the time sequence data are nested and coupled, the spatial correlation data are serialized and converted, and the time sequence data are embedded, so that the time resolution of the sampling data is improved, and the accuracy and applicability of model simulation are improved.

The present application provides a kind of coal mining three-dimensional ecological environment protection method. It relates to coal mining and ecological environment protection technical field, including, S1. the ore body occurrence condition investigation is implemented to the mining area to be mined, according to the ore body occurrence condition investigation result, mining area, dumping area and buffer protection zone are divided, and three-dimensional ecological environment database containing space coordinates and ecological index is established;S2. in the mining process, the soil is stripped in the order of humus layer, plough layer and parent material layer, and each layer of soil is transported to the closed functional soil storage for storage. The coal mining three-dimensional ecological environment protection method significantly shortens the ecological restoration period and improves the agricultural and landscape value of the reclaimed land in the mining area, realizing the long-term stability and sustainable development of green mine.

The application discloses a method for monitoring the effect of marine ecological restoration in an estuary and sea area based on multi-period remote sensing, and relates to the technical field of marine ecological restoration, which comprises the following steps: obtaining multi-period satellite and unmanned aerial vehicle remote sensing images before and after the implementation of a restoration project, and constructing a long-time sequence standardized remote sensing data set; interpreting the multi-period remote sensing images to generate multi-period ecological element data; inputting the multi-period ecological element data into an intelligent simulation model for water and sediment transport and topographic evolution, simulating the water and sediment transport and topographic evolution law in different restoration stages, and evaluating the implementation efficiency of the project; constructing an ecological network topology graph with each ecological patch in the restoration area as a node, using a graph neural network to learn the spatio-temporal characteristics and predict the state evolution of the multi-period ecological indicators, and generating a dynamic change curve of a comprehensive index of the restoration effect; and triggering a graded early warning when the comprehensive index deviates from a preset restoration target track. The application realizes quantitative monitoring and dynamic early warning of the effect of marine ecological restoration in an estuary and sea area.

The invention relates to the technical field of forestry management, and discloses a forest stand quality evaluation method for a complex forest region. Comprising the steps of S01, collecting ecological indexes of an ecological evaluation area, S02, collecting growth indexes of a growth evaluation area, S03, collecting environment indexes of an environment evaluation area, S04, recognizing quality indexes corresponding to comprehensive evaluation indexes through a quality learning model, and S05, determining the quality grade of a forest stand to be evaluated. According to the method, the limitation of a single-dimension or specific-dimension data index in forest stand overall quality evaluation is avoided, the multi-dimension evaluation effect of the forest stand quality in a complex forest region is realized, and the divided regions can be kept independent; the interference phenomenon existing when multiple data indexes of different dimensions are collected in the same area is avoided, the comprehensive, accurate and efficient evaluation effect of the forest stand quality of the complex forest area is achieved, and a scientific theoretical basis is provided for specific measures of forestry resource management.

The invention relates to a method for evaluating urban and rural integration ecological efficiency based on resource utilization, environmental influence and social participation. The method comprises the following steps: step 1, data collection: collecting urban and rural integration ecological efficiency evaluation index data; step 2, data preprocessing; 3, constructing an entropy weight method model and an unexpected output super-efficiency SBM model; step 4, ecological efficiency difference analysis; based on the dimensions of resource utilization, environmental influence and social participation, the method enriches the connotation of the urban-rural fusion ecological efficiency, constructs an ecological index system, is expected to be closer to the actual input-output process, and improves the accuracy of the estimation result of the urban-rural fusion ecological efficiency. And on the basis, the regional difference of the city is further analyzed, and reliable evidence is provided for promoting the sustainable development of regional ecology.

The present application relates to the technical field of water environment treatment, solves the technical problems that the existing buffer zone design generally has the problems of width / structure determined by experience, lack of multi-scenario adaptation and quantifiable ecological target constraint, and particularly relates to a method for constructing a composite buffer zone at a lake inlet based on a hydrology-water ecology response model, a multi-scenario fingerprint library is constructed based on multi-source data of a target lake inlet area, a hydrology-water ecology response model is established for quantifying ecological indexes such as transparency, algal risk and submerged plant adaptability probability into an ecological response vector, a functional unit library is constructed and structure gene coding is used to describe the topology and parameters of units such as dissipation allocation, sedimentation dredging, reaction bed fixation, vegetation rhizosphere reaction and bottom protection and motion suppression; multi-objective inversion optimization and robustness evaluation are carried out under multi-scenarios, and a composite buffer zone spatial layout, size parameters and operation and maintenance trigger threshold values that meet flood discharge and stability constraints are output, so that parameterization and deliverable design of the lake inlet buffer zone are realized.

The present application relates to the technical field of plant ecological configuration, and particularly relates to an aquatic plant ecological configuration parameterization design method and system. The design method can provide quantitative basis for the design and optimization of the scheme based on the dual targets of aquatic plant ecological function and landscape benefit by constructing a parameterization standard module including ecological index standards and landscape index standards, realize precise design of the aquatic plant configuration scheme, and reduce the dependence on artificial experience. Meanwhile, by constructing a multi-dimensional database and adopting a multi-database linkage data fusion mechanism, the design recommendation and optimization can be provided with data support, and the quantitative linkage of plant variety-planting amount-purification effect-landscape score-cost can be realized. Meanwhile, by automatically matching plant varieties through an algorithm design process, an optimized combination structure can be obtained, the aquatic plant configuration scheme considering ecological efficiency and landscape value can be quickly obtained, and the precise design of aquatic plant configuration from 'experience-driven' to 'data-driven' is realized.

This invention discloses a method and system for simplifying indicators for assessing the resilience of aquatic ecosystems. The method generates a multimodal retrieval strategy and obtains diverse text by parsing the assessment scenario instructions using thought chain analysis. It then extracts indicator relationships from the text, analyzes the coupling relationships between indicators, constructs a knowledge graph of aquatic ecological indicators, and forms a pool of all candidate indicators. Semantic and correlation analyses are used to calculate the correlation between indicators, eliminating highly correlated redundant indicators to form a preliminary simplified indicator set. The preliminary simplified indicator set and selection criteria are output. After verification, the final simplified indicators are output. This invention solves the problems of complex indicator systems, high collinearity and redundancy, and strong subjectivity in traditional aquatic ecological assessments by integrating the logical constraints of knowledge graphs with the semantic understanding capabilities of large-scale models. It achieves scientific dimensionality reduction and dynamic optimization of assessment indicators, possessing simplicity, interpretability, and engineering application value.

The invention provides a contrast analysis-based rain and snow enhancement benefit evaluation method, system and device, and a medium. The method comprises the steps of obtaining a first data set and a second data set of an influence area, obtaining a third data set of a contrast area, and obtaining a meteorological data set; determining an index mean difference based on the first data set and the second data set; determining a standardized effect quantity based on the second data set and the third data set; after a covariable effect value is determined through covariable analysis, the standardized effect quantity is updated to be a target effect quantity, a comprehensive contribution index is determined based on the index mean value difference of all the ecological indexes and the target effect quantity, and an ecological benefit evaluation result is determined. According to the technical scheme of the embodiment of the invention, multi-dimensional analysis is realized through a plurality of ecological indexes, a longitudinal analysis result of rain and snow enhancement is represented through the index mean value difference, a transverse analysis result is represented through the target effect quantity, and covariable analysis is introduced, so that the comprehensive contribution index can eliminate climate fluctuation, and the evaluation accuracy of ecological benefits is improved.

The application relates to a sidewalk tree screening method based on a forest ecological index, a regional environment model is established by using a DEM technology, tree body data of different types of sidewalk trees are measured and recorded, a plurality of tree body data sub-models are established, and simulation calculation is sequentially performed on the tree body data sub-models, a simulation result is analyzed by using a stepwise multiple linear regression, a regional environment model and a sidewalk tree type model are fused, a simulation model is established, the regional environment model is trained by using the tree body data sub-models, simulation model characteristics are obtained, a heat balance coefficient of the simulation model and a tree species growth characteristic value are calculated, a trend curve is estimated, the simulation model trend curve is compared with a reference target model trend curve, and high-quality plants suitable for the target region are determined. When the simulation model is constructed, the heat balance coefficient in the target region range and the growth characteristic value trend of the plants in the target region are considered, so that more stable and longer forest ecological effects can be achieved in the target region.

The invention relates to the technical field of water environment treatment, solves the technical problem that the existing buffer zone design generally has the defects of width determination / structure determination according to experience and lack of multi-scene adaptation and quantifiable ecological target constraint, and particularly relates to a lake inlet composite buffer zone construction method based on a hydrological-water ecological response model. The method comprises the following steps: constructing a multi-scene fingerprint database based on multi-source data of a target lake entrance area, and establishing a hydrological-water ecological response model for quantifying ecological indexes such as transparency, algae risk and submerged plant survival probability into ecological response vectors; constructing a functional unit library, and describing topologies and parameters of units such as dissipation distribution, sedimentation dredging, reaction bed fixation, vegetation rhizosphere reaction and bottom protection movement inhibition by adopting structural gene coding; and carrying out multi-target inversion optimization and robustness evaluation under multiple scenes, and outputting a spatial layout, a size parameter and an operation and maintenance trigger threshold value of the composite buffer zone meeting flood discharge and stability constraints, so that parameterization and deliverable design of the lake entrance buffer zone are realized.

The invention discloses a coal gangue soil formation quadruple factor evaluation method, which belongs to the technical field of coal gangue resource utilization, and comprises the steps of organic matter and nutrient activation evaluation, heavy metal safety threshold evaluation, leachate environment safety evaluation and ecological effect verification. Through four-dimensional factor integration, the one-sidedness problem of traditional single evaluation is solved, and the risk misjudgment rate is reduced from 40% to 10%; the accuracy is improved through three-stage detection of total amount, effective state and leachate, and ecological indexes are introduced to ensure long-term safety.

A northern arid region ecological system key node identification and evaluation method comprises the following steps: calling long-time-sequence remote sensing data, and extracting ecological indexes from the called remote sensing data to construct ecological risk indexes; based on an ecological space network analysis method, degree centrality (DC) is adopted as a node importance evaluation index, quantitative evaluation is carried out on the network node connection capability, and nodes with the DC located at the top 10% are screened out to serve as main key ecological nodes; according to the direct flow matrix and the comprehensive flow matrix between the nodes, risk flow intensity is graded, a main control path, a risk diffusion path and a key connection path in the network are extracted, and a key ecological path is obtained; and constructing an ecological comprehensive evaluation system based on the ecological risks, the key nodes and the key paths, identifying ecological partitions, and realizing dynamic closed-loop evaluation of the ecological system. According to the method, the key ecological path can be obtained while the key nodes of the ecological system in the arid region are quickly and accurately recognized, and the recognition and dynamic closed-loop updating of the restoration region are realized.

The application discloses a kind of forest ecological environment monitoring systems based on data analysis, comprising: data processing module, for collecting environmental parameters, and pre-processing;Heterogeneous modeling module, for building heterogeneous graph structure, and using Gaussian kernel function to calculate edge weight value;Convolution residual module, for performing multilayer graph convolution operation, and residual output is applied in next layer graph convolution;Pooling mapping module, for executing global pooling and multilayer perceptron mapping to node feature representation, generates state feature vector;Ecological clustering module, for performing clustering analysis using DENCLUE clustering algorithm, and calculating the ecological index value of each region;Monitoring analysis module, for comparing and analyzing the clustering result with historical environmental state data, and generating forest ecological risk monitoring result.The application realizes the structured modeling and dynamic risk intelligent identification of forest ecological environment, improves the precision of ecological monitoring and the timeliness of early warning.

The invention relates to the technical field of environmental science and engineering, in particular to an ecological health system evaluation method and device for a travel lake and computer equipment, and aims to introduce tourist perception text subjective information on the basis of objective ecological indexes to construct an evaluation system and objectively fix the weight. And the cloud model is introduced to characterize uncertainty and fuzziness and calculate the comprehensive health index of the lake, and the ecological health system evaluation is performed based on the obtained comprehensive health index of the lake, so that the reliability of the ecological health evaluation result of the Zhongguo lake is improved.

1. The name of the design product: forestry ecological sign. 2. The use of the design product: the design product is used for forestry ecological information sign. 3. The design points of the design product: in shape. 4. The picture or photo that best indicates the design points: perspective view 1.

The invention relates to the technical field of water ecology monitoring and aquatic product proliferation management, in particular to a plankton-based reservoir proliferation capacity evaluation method and system, and the method comprises the steps: obtaining multi-source monitoring data of a reservoir, and executing time alignment, space registration and quality control to form a standardized observation set; determining a residence time profile and a water body layering index, dividing water area partitions and constructing a partition connected graph; constructing an ecological index space field and carrying out persistent coherence analysis to obtain a topological skeleton so as to correct a partition boundary, generating a partition function group evidence sequence and calculating an optimal transmission distance; and adopting conformal prediction to calibrate the upper bound of algal blooms and hypoxia risks, solving and cutting partition quotas on the connected graph in combination with energy flow constraint, and outputting a multiplication capacity evaluation result. According to the invention, the risk controllability and linkage constraint of the partition quota are realized, and the evaluation stability and performability are improved.

The present application relates to the technical field of ecological environment data monitoring, and more particularly to a mine re-greening supervision method based on remote sensing image semantic segmentation.The method comprises the following steps: step 1: based on the original ecological index of a mine, a six-column time sequence matrix is established for each mine landscape patch; step 2: at each monitoring time, the time sequence matrix is iteratively decomposed by constrained non-negative matrix factorization by minimizing the K-L divergence, and the objective is to decompose the time sequence matrix into the product of a latent ecological function module weight matrix and a latent ecological function module index contribution matrix; and step 3: the resource-liability balance degree is weighted and averaged using the area of each mine landscape patch to evaluate the effect of mine ecological restoration.The present application realizes dynamic, fine and structured monitoring and evaluation of the mine ecological restoration process.