51 results about "Ecological assessment" patented technology

The invention discloses a marine ecological protection and restoration project comprehensive evaluation method based on multi-dimensional analysis, and relates to the field of marine ecological analysis, and the method comprises the steps: obtaining multi-dimensional monitoring data through constructing a target region map model and setting a monitoring point, and generating an ecological feature vector; calculating a relative distance and a deviation between the monitoring point and the comparison feature vector to obtain a repair expected goodness of fit; screening monitoring points with low goodness of fit and integrating the ecological data set; training and generating an optimized simulation feature vector based on a GAN model; and analyzing the simulation parameters and evaluating the ecological evolution trend to complete comprehensive evaluation. According to the method, multi-dimensional and high-precision ecological assessment is realized, the accuracy of restoration effect prediction and the scientificity of an assessment result are improved, reliable support is provided for a marine ecological protection restoration decision, and the problems of one-sided monitoring, insufficient prediction and the like of an existing method are solved.

The invention discloses a goaf ecological restoration method and system based on artificial intelligence, and the method comprises the steps: obtaining multi-source remote sensing data and geological survey data of a goaf, and generating a three-dimensional geological damage model of the goaf through a space-time fusion technology; performing multi-scale feature extraction on the three-dimensional geological damage model by using a deep convolutional neural network to obtain a multi-dimensional ecological feature data set, identifying an ecologically fragile region and an instability risk region, and outputting an ecological risk level map; performing parallel processing on the multi-dimensional ecological characteristic data set to generate an ecological assessment report containing health degree scores of each ecological subsystem of the goaf; and based on the ecological risk grade map and the ecological assessment report, a multi-objective optimization algorithm is adopted to generate a vegetation-soil / rock mass-water body collaborative restoration strategy. By means of the goaf ecological restoration method and device, accurate assessment and collaborative strategy generation of goaf ecological restoration can be achieved, and scientificity, efficiency and overall ecological benefits of restoration engineering are improved.

The invention relates to the technical field of grassland ecological evaluation, in particular to a dynamic reference index calculation method and system for grassland ecological quality evaluation. The method comprises the following steps: acquiring historical reference data of a non-degraded sample plot covered with different interference degrees in a target area, and constructing a reference system time sequence prediction model based on the historical reference data; based on pre-acquired historical monitoring data of a to-be-evaluated grassland, utilizing the reference system time sequence prediction model to obtain a dynamic reference index potential value; extracting an interference factor from the historical reference data, and setting an interference weight for the interference factor; and correcting the potential value of the dynamic reference index by using the interference weight based on the historical monitoring data and the historical reference data to obtain the dynamic reference index. The problem that in the prior art, a fixed reference index is difficult to dynamically respond to the change of the environment, so that the evaluation of the ecological condition of the grassland is inaccurate is solved, and the scientificity of reference index calculation is greatly improved.

The invention provides a road network ecological bearing capacity estimation method and system based on multi-source remote sensing data, and relates to the technical field of remote sensing technology and ecological evaluation. The method comprises the following steps: acquiring a multispectral remote sensing image and ecological system basic data for preprocessing; supervising and classifying the remote sensing image to extract linear ground feature pattern spots and construct a topological relation to obtain road network topological structure data; associating the historical traffic flow statistical data with the road network space and performing interpolation to generate day and night noise spatial and temporal distribution data; extracting habitat distribution data based on the habitat type thematic map and the historical field survey point of the species, and obtaining acoustic sensitive threshold data of the species in combination with behavior experiment records; according to the method, noise spatial-temporal distribution data and habitat distribution data are superposed, noise data in a habitat range are screened out, then the noise data are compared with an acoustic sensitive threshold pixel by pixel, the total area of pixels exceeding the threshold is counted to serve as a road network ecological interference index, and accurate estimation of road network ecological interference is achieved.

The invention relates to the technical field of ecological assessment, and discloses a coastal wetland ecosystem condition assessment method and device, a medium and a product, different smooth regression functions are obtained through double generalized additive model processing, and the influence of an environmental single factor on vegetation and the cooperative influence of the environment and the vegetation on benthic organisms are accurately quantified. Furthermore, the index value is determined by taking historical data as a reference and combining a nonlinear rule of a smooth function, so that subjective weighting deviation is avoided. Furthermore, the weight is calculated based on the association between the real-time index value and the biological index, so that human subjective intervention is avoided, and the weight is ensured to reflect the actual contribution of the index to the ecological system. Meanwhile, the influence of single data deviation is reduced by using the multi-tree integration characteristic of the random forest model, so that the weight result is more stable. Furthermore, the complex ecosystem condition of the coastal wetland can be comprehensively evaluated in combination with the index value and the weight, the biodiversity is protected, and the stability of the ecosystem is maintained.

The invention discloses a WSRS framework-based ecological safety assessment method for a drainage basin in an arid region, relates to the technical field of ecological assessment, and solves the technical problems that the prior art is not adaptive to a coupling process of water, salt, evapotranspiration and underground water and lacks key factors, and an assessment method lacks weight uncertainty description and robustness analysis. The method comprises the steps of S1, acquiring multi-source data of a target drainage basin, and performing data preprocessing; s2, constructing a WSRS evaluation index system, and carrying out standardization processing on indexes; s3, based on the standardized indexes, determining the comprehensive weight of each index by adopting a subjective and objective combination weighting method; s4, performing comprehensive evaluation based on the comprehensive weight, and quantifying uncertainty of an evaluation result by adopting a cloud model to obtain an ecological safety index; s5, constructing a composite stress model and correcting an ecological safety index; and S6, carrying out risk grade division and result visualization. The method has the advantages that the arid region process adaptability is high, the evaluation result is stable and explainable, and the like.

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.

This application discloses a method for determining the threshold of watershed ecological environment quality based on the PSR model, belonging to the field of watershed ecological assessment technology; it includes: determining the evaluation index items of the target watershed; arranging and combining all possible score values ​​of each index to obtain all score combinations; calculating the comprehensive score of each combination to generate a full sample space; performing fuzzy clustering on the full sample space, iteratively determining the membership degree and cluster center value of each sample to multiple preset cluster categories; sorting the cluster center values ​​of each cluster category in ascending order to form multiple health levels; classifying each sample to the cluster category with the largest membership degree based on the principle of maximum membership degree to obtain the sample set corresponding to each health level; fitting continuous distribution density curves to the sample sets of each health level, and determining the intersection of the distribution density curves of adjacent health levels as the critical threshold between adjacent health levels; and determining the health level of the target watershed based on each critical threshold.

The invention relates to the technical field of remote sensing monitoring and ecological evaluation, in particular to a karst rocky desertification evolution identification method fusing an ecological process. The method comprises the following steps: acquiring a suitable detection height of a detection area according to a proportion condition of pure pixels in an image acquired by remote sensing at different heights and an overall pixel purity index; the method comprises the following steps: determining a rocky desertification comprehensive evolution index based on remote sensing data, analyzing a rocky desertification change degree, establishing a prediction model, and judging the influence degree of different driving factors on the current rocky desertification evolution process according to the difference between a prediction result and an actual result and the influence caused by the change of the different driving factors. And finally, generating a stony desertification evolution diagram and a stony desertification risk zoning diagram. According to the method, stony desertification static monitoring in the past is converted into dynamic evolution analysis, and deep understanding of stony desertification evolution trend from representation to mechanism is realized.

The invention relates to a vegetation damage identification and ecological evaluation method for a power transmission and transformation construction area. The method comprises the following steps: data preparation and preprocessing; identifying a vegetation damaged area; optimizing and verifying a result; ecological system service value loss evaluation; and ecological restoration suggestion generation: fusing the vegetation damage degree and the spatial distribution information of the ecological system service value loss, carrying out restoration priority partitioning, providing differentiated ecological restoration measures for different partitions, and outputting a partition ecological restoration planning map and an evaluation report. Through ecological system service value evaluation, quantification of ecological economic loss is realized, and a scientific basis is provided for power transmission and transformation project ecological supervision and restoration.

The invention discloses a vegetation classification method based on space-time multi-modal deep learning, and relates to the technical field of image processing, and the method comprises the steps: obtaining a multi-temporal optical image, a radar image and digital elevation model data of a to-be-classified region, and forming multi-modal data; extracting spectral features, microwave features, topographic features and texture features to form fusion features; calculating graph node features, and updating the graph node features to form graph features; and fusing the fusion features and the graph features to obtain pixel-level coarse classification logs, carrying out feature extraction and fusion on the fusion features to form region-level coarse classification logs, carrying out fusion to obtain a coarse classification probability, and carrying out fine classification on coarse basic features to obtain a final classification result. The method provided by the invention can adapt to a mountainous area environment with multiple clouds, multiple shadows and large topographic relief, improves the stability and classification fineness of vegetation type identification, and is suitable for wide-range vegetation monitoring and ecological assessment scenes.

This application discloses a vegetation classification method based on spatiotemporal multimodal deep learning, relating to the field of image processing technology. The method includes: acquiring multi-temporal optical images, radar images, and digital elevation model data of the region to be classified, forming multimodal data; extracting spectral features, microwave features, topographic features, and texture features to form fused features; calculating graph node features and updating the graph node features to form graph features; fusing the fused features and graph features to obtain pixel-level coarse classification logits; extracting and fusing the fused features to form region-level coarse classification logits; fusing to obtain coarse classification probabilities; and performing fine classification on the coarse class basic features to obtain the final classification result. The method of this application can adapt to mountainous environments with frequent cloud cover, shadows, and large topographic relief, improving the stability and classification precision of vegetation type identification, and is suitable for large-scale vegetation monitoring and ecological assessment scenarios.

The invention discloses an urban ecological evaluation method based on dynamic evolution and spatial correlation, and belongs to the technical field of urban ecological performance. The method comprises the following steps: establishing an urban ecological performance index system through a Markov chain and a kernel density estimation method, and dynamically evaluating the urban ecological performance; weighting the urban ecological performance index system through an entropy method; analyzing spatial correlation of urban ecological performance by adopting a global Moran index and Datonian coefficient decomposition method; and combining convergence and a convergence model to evaluate the long-term development trajectory of urban ecological performance. The space-time evolution rule and the space correlation characteristics of the urban ecological performance are disclosed from time and space dimensions, so that the dynamic change state of the city and different cities are linked, the comprehensive performance of the city in the aspects of ecological resource utilization, environmental protection and carbon emission control is comprehensively reflected, the defects of an existing evaluation system are overcome, and the evaluation system is suitable for the urban ecological environment. And the accuracy, comprehensiveness and scientificity of evaluation are improved.

The application discloses an ecological protection and restoration planning method and system, and the method comprises the following steps: acquiring ecological multi-source data of a target region, performing spatial registration and format standardization processing through a geographic information system; constructing a three-dimensional ecological background model, and generating a gridded geographic unit by fusing the ecological multi-source data; performing dynamic coupling analysis on the ecological multi-source data by using a convolutional neural network, identifying an ecological degradation hotspot region, and outputting a spatial probability distribution map; based on the spatial probability distribution of the ecological degradation hotspot region and the ecological background model, generating a multi-level ecological restoration scheme through a self-organizing feature mapping neural network, and outputting a visual planning atlas. The scheme disclosed by the application improves the accuracy and efficiency of ecological assessment, reduces the economic cost of regional ecological protection and restoration, improves the efficiency, and can achieve good expected effects through tests, and has a good popularization prospect.

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 the technical field of ecological assessment, in particular to an unmanned aerial vehicle cooperative coverage path generation method based on ecological assessment of a photovoltaic power station, which comprises the following steps of: 1, constructing an ecological assessment map, and drawing a plurality of building distribution areas; 2, historical construction high-angle pictures corresponding to the building distribution areas are obtained, construction high-angle pictures shot in the next day are combined, overlapping comparison analysis is carried out, an influence area corresponding to each building distribution area is determined, and recovery areas in the influence areas are divided in combination with the building distribution areas; step 3, marking a recovery area corresponding to each building distribution area in the ecological evaluation map as a probing area, performing path planning based on position distribution of the probing area and in combination with detection data of the plurality of unmanned aerial vehicles, and generating a probing path covering all the probing areas; and 4, obtaining a vegetation image in the recovery area shot by the unmanned aerial vehicle in the exploration process, and analyzing the vegetation coverage rate in the vegetation image.

The invention relates to an intelligent soil sample sampling system based on air-ground cooperation, and belongs to the technical field of agricultural monitoring and environment detection. The system is composed of an unmanned aerial vehicle end and a ground end, and the unmanned aerial vehicle end comprises an image sensor, an edge calculation module, a positioning module and a wireless communication module and is used for completing area image acquisition, boundary detection and position information transmission; and the ground end comprises an edge calculation module, a positioning module, a wireless communication module, a sampling point generation algorithm, a path planning algorithm, a visual interface and a sampling and storage device, and is used for realizing image segmentation, sampling point automatic generation and path dynamic planning and completing sampling task execution and result management in combination with visual interaction. According to the system, air-ground information interconnection is achieved through multi-source cooperative positioning and wireless communication, scientificity and representativeness of sampling point distribution are improved through edge calculation and algorithm optimization, and unmanned efficient sampling under the complex terrain is achieved in combination with automatic path planning. The method significantly reduces the labor cost, improves the sampling efficiency and data reliability, and is suitable for the scenes of agricultural environment monitoring, engineering geological survey, ecological evaluation and the like.

1. The name of the design product: environmental data collection and analysis system display graphical user interface for electronic equipment. 2. The use of the design product: for electronic equipment. 3. The design points of the design product: in the graphical user interface. 4. The picture or photo that best indicates the design points: front view. 5. The use of the graphical user interface: for the collection and analysis of environmental data display. 6. The human-computer interaction mode of the graphical user interface: in the main view, clicking the functional buttons in the interface can realize interaction, for example, clicking "water quality change" on the right side of "ecological assessment and historical comparison" can display the corresponding water quality change curve. 7. Other circumstances that need to be explained: X in the view represents alternative text.

This invention relates to the field of river basin ecological assessment technology, specifically to a method for assessing ecosystem damage in the Yellow River Basin based on multi-feature analysis. By integrating five dimensions of indicators—vegetation cover, land use structure, soil and water conservation function, water source conservation function, and ecological environment quality—a comprehensive diagnosis is achieved, encompassing ecological structure, service functions, and overall quality. Furthermore, it acquires actual spatial patch sets of various threat sources across the entire basin, such as industrial and mining land and transportation networks. Using a distance attenuation algorithm, it quantifies the ecological pressure borne by each raster pixel from all neighboring threat source patches, directly transforming the spatial expansion of human activities into dynamic changes in ecological environment quality. Finally, an area-weighted aggregation algorithm is used to summarize the assessment results at the sub-basin scale to the entire basin scale, overcoming evaluation biases caused by spatial unit heterogeneity.

The invention discloses a hydro-fluctuation belt vegetation community remote sensing space-time evolution driving analysis system and method, and belongs to the technical field of remote sensing monitoring and ecological analysis. The system comprises a data acquisition and preprocessing module, a multi-feature fusion input construction module, a distillation type depth classification module, a space-time evolution analysis module and a driving factor quantification module. The method comprises the following steps: acquiring and preprocessing a multi-source remote sensing image and environment data; constructing multi-channel data fusing the spectral band and the characteristic index; training a Res-U-Net model by using a knowledge distillation strategy to realize high-precision classification of six types of ground features; analyzing vegetation space-time evolution characteristics based on a long time sequence classification result; in combination with multi-source environment data, contribution of each driving factor to vegetation change is quantified by adopting an interpretable machine learning method. According to the method, the problems of fine classification of vegetation in the hydro-fluctuation belt and quantitative analysis of the driving mechanism in a complex environment are solved, and an efficient and reliable technical tool is provided for ecological assessment and management of a reservoir.

The invention relates to a remote sensing image semantic segmentation method based on an encoder-decoder architecture. The method comprises the following steps: acquiring remote sensing image data to be segmented; and inputting the to-be-segmented remote sensing image data into a trained semantic segmentation model to obtain a segmented remote sensing image, and realizing identification and classification of the surface ecological elements in the to-be-segmented remote sensing image data, the semantic segmentation model being an encoder-decoder architecture. According to the method, multi-scale processing and feature fusion are carried out, high-precision surface ecological element recognition is realized, the problems of cross-domain generalization and small target recognition are solved, and environmental monitoring and ecological evaluation are supported.

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 present application relates to the technical field of environmental monitoring and ecological assessment, and specifically discloses a dynamic evaluation system for carbon flux of lakes in cold regions based on in-situ monitoring, which comprises a watershed carbon input flux monitoring module, a high-frequency monitoring module for in-situ carbon process of lakes, a multi-scale process coupling simulation engine, and a carbon flux dynamic evaluation and visualization module. By integrating the watershed input and high-frequency monitoring data in the lake, the model coupling hydrology, ice conditions and biogeochemical processes is driven to dynamically simulate the carbon migration and transformation, and the net carbon flux at multiple time scales is calculated based on mass balance, thereby realizing the systematic, accurate and visual dynamic evaluation of the carbon source and sink function of lakes in cold regions. Through the dynamic evaluation algorithm in the carbon flux dynamic evaluation and visualization module, the present application realizes the sublimation from instantaneous flux monitoring to net carbon flux evaluation at multiple time scales.

This invention discloses a method, system, and storage medium for diagnosing and regulating the degradation of intermittent river ecosystems. This invention relates to the field of environmental monitoring and ecological assessment technology, aiming to address the limitations of existing technologies in accurately diagnosing the degradation mechanisms of intermittent river ecosystems, tracing stress sources, and simulating scenarios. This invention adapts to the monitoring needs of both wet and dry periods by collecting eDNA from water and sediment dual samples, integrates multi-source data to extract specific biological index characteristics of intermittent rivers, and uses a hierarchical Bayesian causal network model incorporating specific ecological knowledge to distinguish between natural hydrological fluctuations and anthropogenic disturbances. Finally, it outputs the dominant degradation factors of intermittent rivers and ecological regulation recommendations. This invention overcomes the bottlenecks of traditional monitoring in intermittent river scenarios, such as the lack of monitoring during dry periods and ambiguous attributions, improving the accuracy and specificity of diagnosis, and providing scientific support for the ecological protection, ecological flow determination, and restoration plan formulation of intermittent rivers.

The application discloses a kind of slope and small watershed surface biomass rapid measurement method and system thereof.The method is based on water and sediment dynamics and similarity theory, constructs the three-dimensional physical model covering rainfall, soil and vegetation characteristics, obtains model biomass by dynamic simulation test, deduces biomass scale λ BH Combining static geometric scale and vegetation bulk density scale Y M BH M M Actual biomass of prototype area is converted to get by conversion formula. Corresponding system includes modeling module, dynamic simulation device, data processing unit and verification module. The method has the characteristics of high measurement accuracy, strong non-destructive and wide applicability, and is suitable for biomass monitoring, ecological assessment and vegetation restoration process analysis in ecologically fragile areas such as the Loess Plateau.

The invention discloses a phytoplankton community stability evaluation method based on cascade reservoir influence. The method comprises the following steps: step 1, river reach division and sample collection; step 2, community structure and diversity analysis; step 3, analyzing a community construction mechanism; step 4, co-occurrence network construction and stability evaluation; step 5, environment driving factor modeling; and step 6, performing multi-group comparative analysis. According to the method, multi-dimensional analysis of a community structure, a construction mechanism, network stability and environment driving factors is integrated, and a complete evaluation chain is formed; a neutral community model and a co-occurrence network analysis method are introduced, and the influence mechanism of the cascade reservoir is revealed from the angles of the ecological process and interaction; the method is suitable for river and reservoir systems of different scales and different types, and is especially suitable for ecological assessment of areas without data or with less data; the method has important theoretical and practical values for scientifically guiding ecological scheduling and biodiversity protection of the drainage basin.

The invention discloses a digital fishing field ecological chain intelligent scheduling system and method based on digital twinning, and relates to the technical field of digital twinning, and the method comprises the following steps: S1, arranging an Internet of Things sensor, and collecting a preliminary environment data set; s2, in combination with a Kalman filter algorithm, constructing and updating a digital twin virtual model in real time; s3, calculating a resource consumption index, and generating a resource scheduling optimization scheme in combination with a conjugate gradient algorithm; s4, performing dynamic simulation, and generating a resource scheduling implementation scheme in combination with an ecological assessment result; and S5, calculating a resource scheduling adjustment amount according to a feedback control algorithm, and generating a resource scheduling adjustment effect report in combination with an adjustment result. According to the method, the digital twinborn technology, the conjugate gradient algorithm and the feedback control algorithm are combined, intelligent scheduling of fishing field resources is achieved, and the method has the advantages of being high in real-time performance, high in intelligent degree and fast in data processing.

The application discloses a kind of evapotranspiration calculation methods considering soil moisture and carbon dioxide influence, specifically: collection flux station observed meteorological information and vegetation water carbon flux information;Carbon dioxide stress function to leaf stomatal conductance and soil moisture stress function to stomatal conductance are constructed;Based on the stress function constructed, canopy conductance parameterization model is constructed, and canopy resistance is obtained;Through the canopy resistance of parameterization land surface process and aerodynamic resistance, the water and heat flux transport model of soil-vegetation-atmosphere continuum is constructed, and latent heat flux is calculated;Through the latent heat flux observed by flux station, the parameters in water and heat flux transport model are optimized;The optimized parameters are substituted into water and heat flux transport model for calculation, and latent heat flux and canopy conductance value are obtained.The application improves the accuracy of evapotranspiration estimation under the condition of rapid environmental change, and provides a reliable tool for water resource management, ecological assessment and climate research.

This invention discloses an artificial intelligence-based method, system, equipment, and storage medium for rural pollutant assessment, relating to the field of ecological assessment technology. The method includes: dividing the assessment area into multiple units and encoding them, and using a sliding window assessment on a monthly cycle. It involves collecting multi-source data, including remote sensing, meteorological, pollution monitoring, and rural statistics data, processing them uniformly, and constructing pollution pressure characteristics (including monthly and cumulative effects) and ecosystem stability characteristic sequences. An artificial intelligence discrimination model is used to train and infer from the two types of features, outputting pollution risk classifications and a list of high-risk units. A database is established to store the results, supporting incremental model updates, and finally, the regional risk distribution results are output periodically. This invention enables traceable and reusable long-term management ledgers, improving the consistency, automation level, and engineering application value of assessments.

The invention relates to the technical field of environmental monitoring and ecological evaluation, and particularly discloses a cold region lake carbon flux dynamic evaluation system based on in-situ monitoring, which comprises a drainage basin carbon input flux monitoring module, a lake in-situ carbon process high-frequency monitoring module, a multi-scale process coupling simulation engine and a carbon flux dynamic evaluation and visualization module. By integrating basin input and high-frequency monitoring data in the lake, a model coupled with hydrology, ice conditions and biogeochemical processes is driven, carbon migration and transformation are dynamically simulated, and multi-time-scale net carbon flux is calculated based on mass balance, so that systematic, accurate and visual dynamic evaluation of the carbon source sink function of the lake in the cold region is realized. According to the system, sublimation from instantaneous flux monitoring to multi-time scale net carbon flux evaluation is realized through a dynamic evaluation algorithm in a carbon flux dynamic evaluation and visualization module.