42 results about "Landscape pattern" patented technology

The invention discloses a method for evaluating evolution characteristics and evolution driving factors of a space-time pattern of a park green land, and particularly relates to the technical field of crossing of smart cities and landscape ecology, and the method comprises the steps: obtaining multi-period remote sensing image data and planning maps, and constructing a multi-source database; interpreting the image based on a random forest supervised classification algorithm to generate a park green space distribution map, and optimizing the precision; adopting a landscape ecology theory to select a landscape pattern index to quantify space-time evolution characteristics; constructing a driving evaluation index system, and analyzing a driving mechanism by means of a multiple regression model and a space measurement model; and generating a three-level spatial pattern optimization strategy based on the result and outputting a visual decision map. According to the method, the spatial-temporal pattern evolution characteristics and driving factors of the urban park green land can be comprehensively analyzed, and a scientific basis and decision support are provided for planning, management and protection of the urban park green land.

The invention discloses a method and a system for evaluating the nonlinear influence of a greenbelt landscape pattern on a rainfall flood regulation service. The method comprises the following steps: step 1, constructing a basic database; 2, processing data variables; 3, constructing a nonlinear model: taking a green land landscape pattern factor as a core explanation variable, taking a rainfall flood regulation service index as a response variable, introducing a natural environment factor and a social economic factor as control variables, training the random forest model, and constructing a rainfall flood regulation service prediction model; 4, key factors are identified, wherein the top-ranked factors are regarded as key factors playing a role in rainfall flood adjustment service; step 5, analyzing a key threshold: performing visual analysis on a nonlinear relationship between the key factor and the rainfall flood adjustment service by adopting a partial dependency graph algorithm; and by observing positive and negative influence trends and change rates of the key factors on the rainfall flood regulation service indexes in different value intervals, identifying potential key thresholds.

The invention provides a method and system for determining appropriate granularity for landscape pattern analysis, and the method comprises the steps: enabling high-resolution land cover or land utilization vector data of a target region to generate a first multi-granularity sequence with a coarse step length according to a maximum area value rule (Rule of Maximum Area, RMA), and determining a granularity upper threshold value and a scale domain according to three conservation criteria of landscape composition, area and pattern form; a second multi-granularity sequence in the scale domain is generated with a fine step length according to the RMA rule, and a landscape pattern index, sensitive to the scale effect, of the second multi-granularity sequence is calculated; the method comprises the following steps: performing mutation analysis by adopting a non-parametric rank test (Mann-Kendall and Pettitt test), and taking an effective mutation point with the highest frequency as an appropriate granularity; according to the method, information loss and nonparametric mutation inspection are quantified through three conservation criteria, the problems that a traditional method neglects landscape pattern form loss, granularity judgment is high in subjectivity, data distribution depends and the like are solved, and the objectivity of granularity decision and ecological application precision are improved.

The invention provides an ecological risk evaluation and prediction evaluation method based on a multi-source evaluation framework, and relates to the technical field of ecological risk evaluation, and the method specifically comprises the steps: dividing a target region into grid units, and collecting landscape pattern and environmental social economic data; analyzing landscape data through a sliding window method, and calculating a landscape ecological risk value of each unit; constructing a regional ecological risk assessment index system based on social economic data, determining an index weight by adopting Bayesian BWM and CRITIC methods, and performing weighted calculation to obtain a regional ecological risk value; integrating the two types of risk values to form a spatial distribution diagram, and superposing to obtain a unit comprehensive ecological risk value; and performing risk grading by adopting a natural breakpoint method, generating a grading graph, predicting risk early warning time of each unit based on a historical trend, and realizing ecological risk dynamic evaluation and early warning.

The application discloses a method for establishing a non-material cultural heritage space-time database, characterized in that, a basic space-time database is first established to arrange time events of the non-material cultural heritage, then a transmission space-time database is established to analyze space information such as a spatial distribution dispersion degree of the non-material cultural heritage at a transmission destination, a spatial transmission distribution feature of the transmission destination and a spatial action feature of the transmission destination, and then a chronicle space-time database is jointly constructed through the space information and the time events. Thus, the relevant chronicle theme information is associated with basic geographic elements, the non-material cultural heritage landscape pattern described in the chronicle can be presented, and the space-time process of cultural transmission and diffusion can be excavated.

The invention relates to the technical field of regional rare earth prediction, in particular to a landscape pattern and spatial statistics coupled ion adsorption type rare earth enrichment region prediction method, and the method comprises the steps: obtaining an ion adsorption type rare earth ore control index parameter set, rare earth abundance data and rare earth content actual measurement data of a target region; constructing an effect coefficient set according to the geological-hydrological index parameter set and the rare earth content measured data; constructing a landscape resistance field according to the landscape index parameter set to obtain the landscape resistance field; obtaining a spatial weight matrix; performing spatial autocorrelation analysis according to the rare earth abundance data and the spatial weight matrix to obtain spatial autocorrelation analysis indexes; performing rare earth enrichment probability index prediction according to the geological-hydrological index parameter set, the effect coefficient set, the landscape resistance field and the spatial autocorrelation analysis index to obtain rare earth enrichment probability index data; and performing rare earth enrichment area prediction on the target area according to the rare earth enrichment probability index data to obtain a rare earth enrichment area prediction result of the target area.

This invention relates to the field of ecological protection zone identification technology, and particularly to a method for improving the accuracy of the Human Footprint Index. The method comprises the following steps: S1, Population Grid Redistribution: A construction land mask is extracted from land cover data. Population statistics data from the construction land mask and population grid data are input into the iURBAN algorithm to redistribute the population grid data. Population statistics data are then used to verify the accuracy of the population grid data before and after redistribution. S2, Fragmentation Index Scoring: A movement speed grid is calculated. City tiers are classified based on land cover data. Based on the city tier classification and movement speed grid, different levels of urban patches representing urban edges are obtained. Landscape pattern indicators representing fragmentation are calculated, and fragmentation index scores are assigned based on the landscape pattern indicator calculation results. S3, Human Footprint Index Calculation. This invention redistributes population data from the population grid to optimize the population distribution and improve the accuracy of the population grid data.

This invention relates to a method and system for optimizing the configuration of blue-green spaces. The method includes: acquiring collected data of the area to be evaluated; performing quantitative landscape pattern analysis of the area based on the collected data; performing integration analysis of the area based on the results of the quantitative landscape pattern analysis; conducting landscape optimization evaluation of the area based on the results of the quantitative landscape pattern analysis and the integration analysis to obtain the optimal integration degree; and optimizing the area based on the optimal integration degree. This invention enables accurate evaluation of blue-green spaces and effectively optimizes their configuration, resulting in a rational spatial distribution that avoids fragmentation and poor connectivity issues.

This application discloses a method and system for paddy field landscape planning and processing based on big data. The method includes: collecting raw paddy field datasets to construct a landscape baseline model; extracting basic field attributes and spatial relationship data to construct candidate and constraint sets, and determining the optimal landscape pattern configuration scheme; extracting unit spatial relationships and ecological adaptability indicators to synthesize spatial weight information; calculating the connectivity distance from the centroid of each unit to the nearest water system node, marking breakpoints to reconstruct the water system path; scheduling the entry sequence and operation time of construction machinery, periodically monitoring water quality parameters, and adjusting planting density. The system includes a data acquisition and modeling module, a field selection module, a weight configuration module, a water system correction module, and a scheduling and execution module. This application achieves collaborative management of paddy field landscape planning and construction operation and maintenance through multi-source data fusion and dynamic optimization mechanisms, providing scientific decision-making support for agricultural modernization.

The invention discloses an ecological protection red line optimization range determination method and system, and the method comprises the steps: obtaining dominant ecological system service evaluation results of each spatial scale unit in a target region under different spatial scales; respectively acquiring landscape pattern index data of each spatial scale unit in the target area under each different spatial scale; analyzing the driving degree of the landscape pattern index to the dominant ecosystem service under different spatial scales, and determining an optimized spatial scale; according to the change trend of the dominant ecosystem service along with the landscape pattern index under the optimized spatial scale, identifying a landscape pattern index abrupt change point and determining a landscape pattern index threshold value; and obtaining a spatial scale unit which does not meet the landscape pattern index threshold requirement in the target area, wherein the ecological protection red line area is the optimization range. According to the method, the ecological protection red line optimization range is determined based on the dynamic coupling relationship between the landscape pattern and the ecological system service, and the scientificity and rationality of ecological protection red line optimization can be ensured.

The invention discloses a rural landscape pattern collaborative optimization method, device, equipment and medium based on dynamic pollution assessment and multi-target constraint, and the method comprises the steps: carrying out the multi-scale space assessment of the non-point source pollution risk of a target region through obtaining the source-sink landscape space data and dynamic pollution source strong parameters of the target region; pollution risk distribution information is generated; establishing a constraint rule base including an ecological environment target, a policy planning target and a landscape pattern target; and based on a historical landscape evolution rule, introducing the constraint rule base as a decision-making layer, carrying out multi-target comprehensive scoring and screening on state conversion of landscape cells, and simulating to generate a future landscape pattern scheme meeting the multi-target constraint. According to the method, dynamic and fine environmental impact assessment and active and multi-target spatial layout optimization can be deeply coupled, and transformation from assessment and planning separation to assessment and optimization integration is realized.

This invention discloses a wetland landscape pattern classification method based on optimized feature parameters. First, multispectral and topographic data of the target wetland are preprocessed to extract feature parameters from the preprocessed data. Wetland landscape categories are defined, identifying 13 land cover types. Training samples are determined by referencing field survey data, original multispectral image data, principal component analysis (PCA1) of original remote sensing data, and the tasseled cap transformation brightness component of original remote sensing data. For the preprocessed multispectral data, wetland information extraction is performed using both maximum likelihood classification and decision tree classification. The classification results from the two extractions are combined with the extracted feature parameters to form fused data. Information extraction based on maximum likelihood classification is then performed on the fused data to obtain dynamic change analysis results of wetland landscape classification. Combined with optimized feature parameters, multiple feature parameters are fused to achieve information extraction from remote sensing images and refined classification of wetland landscapes.

The invention discloses a Yellow River downstream city landscape ecological risk analysis method based on high-score data, and relates to the technical field of resource analysis, and the method comprises the steps: obtaining land utilization classification data, dividing an ecological risk evaluation price network based on the land utilization classification data, carrying out the statistics of landscape pattern indexes in each grid, and carrying out the calculation of the ecological risk evaluation price network. Generating landscape interference degree space distribution data; obtaining multi-dimensional geographical environment factor data of the research area, performing spatial correlation analysis on the multi-dimensional geographical environment factor data and the land utilization classification data, and screening out dominant environment factors; generating landscape vulnerability spatial distribution data based on a spatial association relationship between the dominant environmental factors and the land utilization classification data; according to the method, all technical links are connected in series by taking a uniform grid space as an analysis reference, so that refined space representation and scientific coupling fusion of the landscape interference degree and the landscape vulnerability are realized, and the space accuracy of a landscape ecological risk analysis result is greatly improved.

The present application belongs to the technical field of hydrodynamics and environmental engineering, and provides a kind of simulation method for water quantity and quality of piedmont plain type town area considering rainwater grate diversion, and the main steps include: basic database construction, catchment unit division, rainwater grate determination, drainage channel generalization and key process numerical calculation.The present application considers the influence of surface runoff velocity and terrain slope on rainwater grate diversion, corrects and establishes the diversion calculation formula of different types of rainwater grates, improves the accuracy of rainwater grate diversion calculation, and overcomes the subjective definition of hydraulic connection between surface runoff and drainage network in traditional method;At the same time, the present application considers the function of piedmont plain city land distribution, establishes a surface catchment unit division method based on landscape pattern, can accurately represent the influence of hydraulic connection between land use types, microtopography and other factors on surface runoff and pollution output, and overcomes the subjectivity and singleness of traditional methods such as thiesen polygon and road cutting method.

The invention discloses a forest and grass landscape pattern identification method based on unmanned aerial vehicle images, and the method comprises the steps: carrying out the definition and cloud shielding screening of images collected by an unmanned aerial vehicle through a random forest algorithm, and obtaining a high-quality first image data set; then, in combination with vegetation types and spatial distribution characteristics, landscape elements are classified by using a support vector machine, acquisition parameters are optimized, and a second image data set is generated. Further considering the influence of seasonal variation on spectral characteristics, selecting representative time phase images, and constructing a third image data set; and plaque information is calculated and fine plaques are fused to obtain fused plaque distribution data, and then multi-scale pattern indexes such as a shape index, an aggregation degree, a separation degree and a spreading degree are analyzed. And finally, indexes related to image definition are extracted, and a landscape pattern report is generated. According to the method, full-process automation from data screening, element classification, time phase selection to pattern analysis is realized, and the recognition precision and adaptability of the forest and grass landscape pattern are remarkably improved.

The present application relates to a kind of railway corridor biodiversity value evaluation method and evaluation device, the method comprises: the habitat quality data of target railway corridor collected in advance and landscape pattern data are input to the model constructed in advance, the ecological value index of the railway corridor is output;Based on the social value type and evaluation rule constructed in advance, the social value index of the target railway corridor is calculated;The ecological value index and the social value index are weighted by the analytic hierarchy process constructed in advance, and the ecological value index and the social value index are superimposed according to the weight calculation, to determine the biodiversity value comprehensive evaluation index of the target railway corridor.This method is obtained by combining geographic information software, landscape pattern model, ecosystem service and the comprehensive evaluation model of trade-off multiple models or tools, and the research evaluation index is comprehensive, improves the accuracy and real of railway corridor biodiversity value, and the practicality is high.

The invention relates to a riverside landscape pattern rapid quantification method based on remote sensing and deep learning, and the method comprises the steps: enabling a river land-water boundary line to extend towards a land side to form a buffer region, and obtaining a riverside space range; segmenting the spatial range of the riverside zone into a plurality of riverside zone objects along the flow direction of a river according to a preset distance, cutting out the corresponding riverside zone objects from the high-resolution optical remote sensing image, and extracting riverside zone scene pattern spots; dividing the river side scene pattern spots into different landscape types by using a convolutional neural network model; diversity quantification is carried out; according to the method, a plurality of landscape segments are extracted from a riverside object along a riverside direction based on continuously distributed natural landscapes, and the landscape pattern connectivity is quantified by using an improved dendritic connectivity index, so that the range, type and connectivity evaluation result of the riverside can be quickly obtained in a large-area scale.

The invention relates to the technical field of ecology, in particular to a watershed water quality space-time dynamic characteristic driving factor identification method. Collecting land utilization type data of the target watershed, and constructing a landscape pattern index system according to a source-sink landscape pattern theory; based on the landscape pattern index system and the hydrological connectivity index of the target drainage basin, in combination with the water quality monitoring data of different years, performing correlation research on the source-flow-sink landscape pattern influencing the water quality change of the target drainage basin by using a space-time geographic weighted regression model; determining the time-space diversity of the water quality of the target watershed in different landscape configuration modes; and comparing source-flow-sink landscape pattern mode configuration and water quality monitoring data of different drainage basins, and determining a landscape mode countermeasure of water conservation and water quality purification function improvement of the target drainage basin. According to the method, the spatial-temporal relevance of the landscape pattern index and the water quality index is combined, so that decision support and scientific guidance are provided for a drainage basin management mechanism to analyze water quality characteristics.

The invention provides an ecological landscape pattern suitability evaluation method and device. The method comprises the following steps: acquiring landscape type data of a plurality of time nodes of a target area; performing trajectory coding on the landscape type data to obtain a landscape type change trajectory code; determining a stable land parcel according to the landscape type change track code; determining an ecological suitability probability according to a preset key factor; determining a change intensity index according to the landscape type change trajectory code; determining a suitability index according to the ecological suitability probability and the change intensity index; and performing ecological landscape pattern suitability evaluation on the target area according to the suitability index and the stable plot to obtain an evaluation result. According to the invention, the dynamicity and accuracy of the evaluation result are improved.

This invention discloses a method and system for determining the optimized scope of ecological protection red lines, comprising: acquiring the assessment results of dominant ecosystem services for each spatial scale unit within a target area at different spatial scales; acquiring landscape pattern index data for each spatial scale unit within the target area at different spatial scales; analyzing the driving force of landscape pattern indices on dominant ecosystem services at different spatial scales to determine the optimized spatial scale; identifying abrupt change points in landscape pattern indices and determining landscape pattern index thresholds based on the changing trends of dominant ecosystem services with landscape pattern indices at the optimized spatial scale; and identifying spatial scale units within the target area that do not meet the landscape pattern index threshold requirements, wherein the ecological protection red line area is the optimized scope. This invention determines the optimized scope of ecological protection red lines based on the dynamic coupling relationship between landscape pattern and ecosystem services, ensuring the scientific and rational nature of ecological protection red line optimization.

The invention discloses a subarea treatment method and device for soil erosion, a storage medium and electronic equipment, and the method comprises the steps: carrying out the preprocessing of collected multi-source data needed by landscape pattern research, and obtaining the preprocessed data; calculating an equation factor of the general soil loss equation by using the preprocessed data, and deducing a soil erosion modulus based on the equation factor inversion; determining a landscape index space layer of the landscape pattern, inputting the landscape index space layer and the soil erosion modulus into a space-time geographically weighted regression model, and outputting a local regression coefficient on each space-time unit; and dividing treatment stages based on the local regression coefficient and generating a partitioning scheme. By means of the method and device, the problem that in the related technology, due to the fact that correlation analysis between the landscape pattern and soil erosion is insufficient, the zoning treatment effect of the soil erosion is poor is solved.

The application discloses a kind of urban waterlogging risk influence factor exploration method based on landscape analysis, first, the soil type data needed to simulate urban waterlogging surface runoff, land use data and rainfall data are collected, and based on the obtained urban drainage planning, further sub-catchment is divided, so as to obtain the water depth and water range of each sub-catchment in combination with elevation DEM data;Then, the landscape of the study area is analyzed, the macro pattern of urban green space is analyzed using the MSPA method, and the micro form of urban green space is analyzed using landscape pattern index, to obtain the macro and micro urban green space landscape analysis results;Finally, using geographic detector software, coupling analysis waterlogging water depth and macro pattern, micro landscape form, to explore the most influential factor on waterlogging water depth under the condition of landscape pattern spatial differentiation.The application establishes a method system for urban landscape analysis, which can provide a landscape influence factor exploration method for urban areas affected by waterlogging.

The invention discloses an intelligent evaluation and prediction system coupling a landscape pattern index and an ecological system service function, and relates to the technical field of ecological environment evaluation and prediction, and the system comprises a data input layer, a landscape index intelligent processing layer, an ecological service evaluation layer, an association prediction layer and a result output layer which are connected in sequence. The method can achieve the precise analysis of the dynamic change of the regional landscape pattern, achieves the comprehensive evaluation of the service functions of four types of ecosystems, namely supply service, adjustment service, support service and culture service, supports the short-term and medium-and-long-term landscape-service association prediction, is suitable for the scenes of ecological protection planning, land space optimization, environmental impact evaluation and the like, and is high in practicability. And scientific decision support is provided for sustainable management of an ecological system.

The invention provides a bird diversity prediction method and device, belongs to the field of bird diversity prediction, is applied to electronic equipment, and comprises the steps that multi-stage land distribution data and regional development trend data of a to-be-predicted region are acquired, and the multi-stage land distribution data comprise current land distribution data and historical land distribution data; according to the multi-stage land distribution data and the regional development trend data, determining future land distribution data of the to-be-predicted region at a future preset moment; determining future landscape pattern data of the to-be-predicted region at a future preset moment based on the future land distribution data; and processing the future landscape pattern data by using the bird diversity prediction model to obtain a bird diversity prediction result of the to-be-predicted area at a future preset moment. The accuracy of bird diversity prediction results can be improved.

The application discloses a kind of basin mountain and water forest lake grass sand stable suitable coordination method, it is related to the technical field of ecological environment protection and management, including the following steps: step 1: collecting basin ecological background data, and constructing ecological hydrology database;Step 2: according to ecological hydrology database, construct landscape pattern-ecosystem coupling model, and carry out ecological function zoning;Step 3: according to ecological function zoning, construct integrated coupling relationship framework in basin, and identify key ecological hydrology problem;Step 4: according to key ecological hydrology problem, construct nonlinear-multi-objective dynamic programming model;Step 5: solving nonlinear-multi-objective dynamic programming model, obtain parameter optimal solution;Step 6: according to parameter optimal solution, construct coordination strategy.Collaborative optimization of basin ecological hydrology function is taken as core target, the model of basin ecosystem collaborative regulation is established, the optimal parameter is determined by optimizing the model, and coordination strategy is formulated.

This invention provides a method and system for dynamic assessment of urban green space ecosystem services based on multi-source data fusion, relating to the fields of urban ecology and geographic information systems. The method sequentially integrates green space patch landscape data and multi-source socioeconomic proxy data, relying on local spatial clustering to screen typical green spaces with high and low activity intensities; it conducts multi-period ecosystem service value accounting, and analyzes the spatial response patterns of landscape patterns and ecosystem value using concentric buffer zones. A symbiotic dynamic coupled differential equation is introduced, and parameters are fitted to obtain the cross-influence coefficient of the two systems to quantify the symbiotic relationship; multiple coverage scenarios are set by combining environmental Gini and green contribution coefficients to determine the green space coverage balance threshold under the synergistic achievement of multi-dimensional indicators, and the rate of change and evolution trend of ecosystem service value are calculated over time. This invention relies on multi-source data to compensate for the shortcomings of single data sources, quantitatively characterizes the symbiotic feedback relationship between green space and socioeconomic factors, and provides quantitative support for urban green space planning and management.

The invention discloses a river bank wetland ecosystem stability quantification method based on a high-precision remote sensing image, and relates to the technical field of ecological quantification. The method comprises the following steps: acquiring remote sensing image data and hydrological data; preprocessing the remote sensing image data, and determining landscape classification and features of a target area; the landscape classification comprises a wetland type and a non-wetland type; constructing a landscape space data set according to the landscape classification and features; the landscape space data set comprises landscape pattern indexes and corresponding ecological meanings; the landscape pattern index comprises a plaque type level and a landscape level; and analyzing a response relationship between wetland landscape pattern evolution and water and sand elements based on the landscape space data set, and constructing a regression equation according to the response relationship. According to the method, the wetland landscape database is constructed based on the Landsat satellite image, the stability of the river bank wetland ecosystem can be quantitatively evaluated, and the response relation between the wetland landscape pattern evolution and the water and sand elements is obtained.

The application relates to the technical field of urban renewal planning research, and discloses a city stormwaterlogging influence factor quantitative analysis method based on SHAP. First, DEM data, high-resolution land use data and waterlogging point spatial distribution data in a research area are collected; second, the collected data are preprocessed through format conversion, cutting, projection and the like; third, terrain factors are extracted and landscape pattern indexes are calculated based on the collected data; fourth, all the obtained influence factor data are standardized, and a simple random sampling method is used to divide the data into training samples and verification samples; the application combines feature importance sorting, tolerance and a variance inflation factor, retains the most important influence factors, solves information cross-redundancy between the influence factors, and makes the analysis result of city waterlogging and the influence factors more reasonable and easier to explain.

The invention provides an ecological landscape pattern dynamic prediction method based on multi-source remote sensing data and a CA-Markov model, and the method comprises the steps: obtaining a remote sensing image data set which comprises the image information of a plurality of landscape regions; analyzing the remote sensing image data set, determining preliminary category division and boundary contours of landscape elements, and obtaining an initial boundary information layer; according to the accurate boundary description, a network construction algorithm is adopted to generate a connection relation model between landscape elements, and path connectivity and spatial isolation intervals between different areas are determined; and for the connection relation model, calculating the boundary contact length and the region overlapping area between the landscape elements to obtain a spatial interaction relation index.

This invention discloses a method for analyzing and optimizing the impact of landscape patterns on county-level carbon storage, relating to the field of energy conservation and carbon reduction technology. It addresses the problems of weak quantitative foundations, inaccurate analysis of impact mechanisms, and a lack of differentiated optimization strategies in existing technologies for analyzing the correlation between carbon storage and landscape patterns. This solution includes constructing standardized land use data and a regionally adapted carbon density parameter library to quantify the landscape pattern index and county-level carbon storage; determining the spatial clustering characteristics of both through spatial autocorrelation analysis and hotspot identification; analyzing nonlinear interaction effects and identifying optimal thresholds for key factors using the XGBoost-SHAP model; analyzing spatial heterogeneity using the GWR model; and revealing the impact mechanisms based on the analysis results to formulate differentiated landscape pattern and land space optimization strategies. This invention also proposes a method and analysis system for enhancing carbon sequestration capacity, achieving accurate analysis of the correlation between carbon storage and landscape patterns. The optimization strategies are highly targeted and practical, providing scientific guidance for enhancing county-level carbon sequestration.