54 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 land space optimization configuration method under terrain gradient constraint. The method comprises the following steps: S1, collecting multi-source geographic data to construct a spatial database; s2, factors such as gradient and elevation are extracted, and terrain gradient partitions are divided; s3, constructing a three-dimensional conflict matrix based on suitability evaluation and landscape pattern analysis; s4, constructing a driving index system, and analyzing a driving path of the spatial conflict; s5, setting a multi-objective optimization function, and constructing game rules and spatial conversion constraint conditions of the three types of subjects; s6, integrating the C-FLUS model, the MAOOAM model and the R2D3 model, and constructing a coupling system to execute dynamic optimization; and S7, when the convergence condition is met, outputting an optimal configuration scheme and generating a compensation and control strategy. According to the method, efficient optimization and intelligent decision support of multi-target land configuration under the terrain differentiation condition are realized.

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 discloses an ecological vulnerability evaluation method based on road domain landscape pattern optimization, and the method comprises the steps: obtaining expressway road domain environment data as training data, and obtaining ecological environment data; calculating an ecological environment quality index of the ecological environment data, and obtaining landscape structure features in the target area; integrating the landscape pattern index into an ecological sensitive factor, and constructing an ecological vulnerability evaluation model by adopting an SRP structure; performing spatial autocorrelation analysis on space-time evolution of the ecological vulnerability of the road domain according to the ecological vulnerability evaluation index, establishing an ecological vulnerability multi-scene simulation model, performing overlay analysis on an ecological vulnerability evaluation result and a land utilization type, obtaining a specific restoration strategy, tracking space-time evolution characteristics of the ecological vulnerability, and performing road region ecological vulnerability evaluation. Ecological vulnerability influence factors are adjusted based on different scenes, future possible ecological vulnerability risks are simulated, specific restoration strategies are made according to different partition standards, and effective configuration and use efficiency of resources are ensured.

The present invention discloses a dynamic evaluation method for landscape ecological security based on a multi-attribute decision-making model, including: adopting the gap degree landscape scale analysis method to obtain the spatial characteristic scales of each land use type, and using them as the characteristic grid scales for landscape pattern analysis; calculating the landscape pattern characteristic indices at each characteristic grid scale in different periods to construct a regional landscape ecological security evaluation model; using the Lagrange interpolation method to obtain the landscape ecological security indices within the continuous time range of each characteristic grid scale, and predicting the landscape ecological security index values of each characteristic grid scale in the future period; adopting the multi-attribute decision-making CoCoSo model to calculate the weighted sum and the sum of the exponential weighted products of landscape ecological security, and using different aggregation functions to obtain the dynamic index of landscape ecological security. Finally, the natural breakpoint method is used to conduct hierarchical and zonal management on the dynamic index of landscape ecological security in the research area. The present invention can provide technical support for the protection and restoration of regional landscape ecosystems.

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 invention discloses a watershed landscape pattern change and water quality effect analysis method, which belongs to the technical field of landscape ecology, and comprises the following steps: step 1, data collection and preprocessing; step 2, landscape pattern analysis; 3, water quality analysis; 4, analyzing the correlation between the landscape pattern and the water quality; and 5, formulating a targeted drainage basin management strategy according to an analysis result. According to the method, a plurality of technical means such as a geographic information system (GIS), a remote sensing technology and statistical analysis are combined, the landscape pattern change and the water quality effect of the watershed can be comprehensively and systematically analyzed, and the comprehensive analysis method is beneficial to deeply understanding the complexity and the dynamic nature of the watershed ecosystem; and powerful support is provided for formulating a scientific and reasonable drainage basin management strategy.

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.

The invention relates to an optimal configuration method and system for a blue-green space. The optimal configuration method of the blue-green space comprises the following steps: acquiring acquisition data of a to-be-evaluated area; performing landscape pattern quantitative analysis on the to-be-evaluated area based on the collected data; carrying out fusion degree analysis on the to-be-evaluated area based on a landscape pattern quantitative analysis result; performing landscape optimization evaluation on the to-be-evaluated area based on a landscape pattern quantitative analysis result and a fusion degree analysis result to obtain an optimal fusion degree; and optimizing the to-be-evaluated region based on the optimal fusion degree. According to the method, accurate evaluation of the blue-green space can be realized, and space optimization configuration can be effectively carried out, so that the space distribution of the blue-green space is reasonable, and the problems of fragmentation, poor connectivity and the like do not exist.

The present invention belongs to the field of cultivated land protection and the application of spatial information technology, and specifically relates to a method for tapping potential and evaluating the effectiveness of supplementary cultivated land resources at the county scale; the method includes: data acquisition, comprehensive investigation of exploitable resources, analysis of the probability of cultivated land growth based on the random forest algorithm, suitability evaluation based on multi-objective correction, steps of simulating supplementary cultivated land and evaluating the implementation effectiveness; a cellular automaton module for generating a land use simulation model based on patches to simulate cultivated land changes, and carrying out quantitative evaluation of the cultivated land simulation results in combination with landscape pattern indices. The purpose of the present invention is to provide a scientific and objective method for evaluating the effectiveness of tapping and renovating the potential of cultivated land reserve resources at the county scale, to solve problems such as data distortion, strong subjectivity, scale mismatch, and insufficient effectiveness evaluation in the prior art, and to provide technical support for the work of achieving dynamic balance between cultivated land occupation and compensation.

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 discloses a simulation analysis method and system for the influence of watershed landscape pattern evolution on water quality, and relates to the technical field of water quality simulation analysis, and the method comprises the following steps: collecting water quality monitoring data including image data, landform data, meteorological data and river data; constructing a water quality output model through the pre-processed river data in combination with a multiple linear regression algorithm, and further obtaining a water quality evaluation index; based on the obtained water quality evaluation index, combining a neural network algorithm to construct a drainage basin water quality simulation analysis model; according to the method, the multispectral analysis technology, the multiple linear regression algorithm, the neural network algorithm and the simulation analysis technology are closely combined with the modern information technology, and therefore the simulation analysis report of the drainage basin water quality is generated. The problem that the traditional method is difficult to analyze the dynamic influence of basin landscape pattern evolution on water quality is solved.

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 analysis and evaluation method suitable for a coral reef area landscape pattern, and belongs to the technical field of coral reef areas, and the method comprises the following steps: (1) laying a short-term monitoring quadrat or a long-term monitoring quadrat according to actual needs, and determining the length of the quadrat according to underwater transparency; (2) shooting a high-definition picture of a substrate landscape in the quadrat along the length direction of the quadrat; (3) correcting and splicing the pictures through gis or CAD software, and interpreting the species of the coral reef according to the spliced quadrat pictures; and (4) calculating a landscape pattern index to judge the condition of the coral reef habitat landscape pattern. The two kinds of quadrats can make up for the problem that a transect method cannot record landscape plaques in detail, the problems that original large quadrats are fuzzy in shooting and inconvenient to move can be solved, small quadrats divided in the two quadrats are shot one by one, the types of substrates such as coral reef plaques can be clearly reflected, seamless splicing between the small quadrats is facilitated, and the method is suitable for large-scale popularization and application. Errors are reduced, and large-area landscape pattern research can be carried out.

The invention provides a high-resolution remote sensing complex scene intelligent classification method and device based on landscape pattern measurement, and belongs to the technical field of image processing or recognition. The problem that in an existing complex scene, landscape pattern measurement with a segmentation object as a space unit is difficult to accurately reflect a fine space relation is solved, and the problem that due to an existing land cover classification system, the accuracy of the landscape pattern measurement is insufficient is solved. According to the high-resolution remote sensing complex scene intelligent classification method based on landscape pattern measurement, segmentation objects are no longer taken as the basis of landscape pattern measurement, and landscape elements of a research area are not classified into an existing land cover classification system in advance; according to the method, pixel-scale unsupervised classification is carried out on the whole region of a research area, mutually communicated similar pixels in the same scene unit are merged to serve as the basis of landscape pattern measurement, and then a machine learning model is utilized to carry out supervised classification on the scene unit, so that the classification accuracy of a complex scene under high resolution is improved.

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.