9 results about "Ecological study" patented technology

The invention discloses an NEP estimation method based on feature selection and machine learning, and belongs to the technical field of ecological environment monitoring and carbon cycle research, and the method comprises the steps: obtaining remote sensing image data and environment factors of a target region, and carrying out the preprocessing of the obtained remote sensing image data, and obtaining remote sensing factors; based on the remote sensing factor and the environmental factor, obtaining a net ecosystem productivity NEP feature influencing multi-source data fusion of the target area, performing screening, obtaining a preset number of key factors, and performing training through an extreme gradient lifting regression algorithm; analyzing the training result of the extreme gradient lifting regression algorithm by adopting a Shapril addition interpretation method; the extreme gradient lifting regression algorithm is verified through the evaluation indexes, and target area NEP estimation is completed; according to the method, high-precision estimation and driving mechanism analysis of the NEP of the complex mountain ecosystem are realized by fusing multi-source data and a machine learning technology, and clear mechanism explanation is provided for ecological research.

The invention discloses a configuration method suitable for plateau wetland landscape ecological water demand, and the method is characterized in that the method comprises the following steps: S1, obtaining a remote sensing image, carrying out the image classification through a random forest algorithm based on a particle swarm optimization algorithm, and generating a landscape type classification graph; s2, calculating a landscape ecological risk index, identifying a sudden change point of the flow to the landscape ecological risk index by using non-parametric change point analysis, and determining an initial flow and a peak flow of each vegetation growth period; s3, selecting hydrological elements with ecological significance, and quantitatively analyzing wetland hydrological situation changes by adopting ecological hydrological indexes; and S4, coupling an ecological hydrological process, determining a landscape ecological water demand scheme of each time node in the vegetation growth season, and drawing a landscape ecological water demand process. According to the method, the influence of ecological hydrological index changes on the landscape pattern and the ecological risk can be analyzed, and the landscape ecological water demand of the plateau river wetland is quantitatively calculated.

The invention provides a species intrusion detection method and system based on an association relationship, and relates to the crossing field of ecology and information technology, and the method comprises the steps: carrying out the rule matching analysis of multi-source data obtained in real time based on a species intrusion association rule, and obtaining a matching degree result; calculating a species invasion risk score according to a matching degree result; based on a comparison result of the species invasion risk score and a preset early warning threshold value, executing early warning judgment to obtain an early warning judgment result; and when the early warning judgment result is that early warning needs to be triggered, obtaining early warning information containing an early warning position and key data. According to the method, real-time risk assessment is carried out from multi-source data acquisition, fusion and feature extraction to self-adaptive association rule construction, and a complete flow of accurate early warning is finally realized.

The present invention belongs to the field of global change ecology research. Disclosed are a system and method for assessing the resistance and resilience of vegetation under drought stress. The method comprises: using a data collection module to collect data related to vegetation resistance and resilience; inputting the data related to vegetation resistance and resilience into a data storage module for storage; invoking a vegetation physiological index processing sub-module, a vegetation structural index processing sub-module and a vegetation functional index processing sub-module in a data processing module to process the collected and stored data; then, on the basis of data output by the data processing module, invoking a lagged cumulative correlation coefficient calculation sub-module, a vegetation resistance index and resilience index assessment model sub-module and a vegetation resistance and resilience level classification sub-module in an analysis and assessment module; and finally, outputting vegetation resistance and resilience assessment levels. By means of the present invention, comprehensive, systematic and precise assessment and level classification can be performed on the resistance and resilience of vegetation under drought stress, vegetation that has difficulty in resisting drought or recovering from drought stress can be effectively identified from an assessment area, and the operation is simple and easily implemented.

The invention discloses an ecological system health assessment method and system integrating current situation characteristics, stability and historical optimal state comparison, and the method comprises the steps: obtaining an ecological system data set of a research region in an assessment period, and constructing three feature levels: current situation characteristics, stability characteristics and historical optimal state comparison characteristics; setting three ecological attribute dimensions of states, patterns and functions to form a 3 * 3 evaluation framework; and calculating a feature sub-value under each ecological attribute index and a total feature value of each feature level to obtain an ecological system health assessment value. The ecological system health and restoration potential are comprehensively represented through the 3 * 3 framework, compared with the prior art, the ecological significance of the evaluation result is clearer, the restoration direction is clearer, the method is suitable for multiple regional-scale ecological systems, and a scientific basis is provided for setting of subsequent ecological restoration targets and implementation of measures.

The invention relates to a dynamic monitoring and analysis system for a multi-trophic-level interaction relationship of an ecological system, and relates to the field of ecological monitoring. Multiple types of sensing terminals are integrated to communicate with the Internet of Things, and real-time and multivariate data acquisition of different nutritional level biological populations and environmental parameters is realized. The intelligent data fusion and ecological network modeling technology is adopted, the complex interaction rule between groups is deeply mined, key nodes and ecological effects are dynamically recognized, and the precision and efficiency of ecological system structure and function evaluation are improved. The system has an automatic operation and maintenance capability, and can efficiently support ecological change monitoring, health condition assessment and risk early warning. Compared with a traditional method, multi-scale, multi-dimensional and intelligent dynamic monitoring of the ecological network is realized, and scientific support is provided for ecological protection and environment management.

The invention, which relates to the technical field of marine environment monitoring and information, discloses a big-data-based marine ecological evaluation and analysis system comprising a data sensing and acquisition module, a feature analysis and extraction module, an ecological parameter mapping module, and a self-adaptive multilevel evaluation and ecological diagnosis report module. The system obtains marine environment original data through a sensing network, and the marine environment original data is processed and converted into to-be-evaluated parameters with ecological meanings. The self-adaptive evaluation module can dynamically adjust the execution path and strength of an evaluation strategy according to the data characteristics of input parameters and the environment context, and then composite calculation and fusion analysis are carried out. And the report module longitudinally compares the current quantitative diagnosis conclusion with a historical evaluation record, identifies an ecological state change track and generates a structured report. According to the scheme, dynamic intelligent adaptation of the evaluation strategy and deep mining of the ecological evolution trend are realized, so that the accuracy of the evaluation result is effectively improved, and the decision support capability of long-term ecological monitoring and management is enhanced.

The invention discloses an ecological resistance high-precision modeling method based on an uncertainty superposition model, and relates to the cross technical field of geographic information systems and landscape ecology, and the method comprises the following steps: selecting a plurality of resistance factors influencing an ecological process; performing standardization processing on each resistance factor by adopting an uncertainty reasoning concept, distinguishing positive or negative effects of the resistance factors, and endowing corresponding weights; the standardized factors are synthesized through the superposition operation process of the model, and a preliminary ecological resistance surface is obtained; and finally, performing normalization processing on the result to generate a high-precision ecological resistance surface. By the adoption of the ecological resistance high-precision modeling method based on the uncertainty superposition model, the characteristics of all resistance factors can be effectively reserved, information loss caused by a traditional weighted average method is avoided, the accuracy and reliability of ecological resistance surface modeling are improved, and the method is suitable for popularization and application. And a scientific basis is provided for ecological network construction, biodiversity protection and ecological safety pattern planning.

This application relates to a method and system for assessing the health of island ecosystems. The method collects and standardizes multi-source ecological data from islands to generate an evaluation index matrix and assigns initial static weights. It then constructs a niche network and relationship matrix that characterizes the nonlinear interactions between indicators. Based on this, it calculates a comprehensive niche overlap index among the indicators and constructs an overlap matrix. Subsequently, based on the degree of deviation of each indicator's actual state and utilizing the conflict or synergistic relationships between indicators revealed by the overlap matrix, it dynamically adjusts the initial weights—that is, when an indicator deteriorates, it increases the weight of conflicting indicators and decreases the weight of synergistic indicators. Finally, it uses the dynamic weights to calculate a comprehensive health index and determine the health level. This overcomes the shortcomings of traditional fixed-weight evaluation methods that cannot reflect the dynamic relationships between indicators within the ecosystem, achieving a more accurate, sensitive, and ecologically sound assessment of the health status of island ecosystems.