362 results about "Spatial analysis" patented technology

The invention relates to a sponge city design optimization method and system based on rainfall calculation, and the method comprises the following steps: predicting the occurrence probability of a rainfall event in a target sponge city based on rainfall analysis data and climate data, and obtaining the probability distribution of future rainfall and the future calculated rainfall; performing spatial analysis on the target sponge city through a preset geographic information system to obtain an easy water accumulation point distribution map; adopting a Bayesian network algorithm to evaluate the waterlogging risk level of each region in the target sponge city based on the distribution map of the points prone to water accumulation, the future measured rainfall and the probability distribution of the future rainfall, and obtaining a waterlogging risk map; and performing layout optimization design on the target sponge city based on the waterlogging risk map by using a preset multi-target optimization algorithm to obtain an optimal configuration scheme, thereby solving the problem of how to scientifically and reasonably predict a rainfall mode and influence, and effectively relieving the urban waterlogging problem.

The invention provides a multi-mode large model-based precision metal part defect detection method and system. The method comprises the following steps of: acquiring laser scattering image data of a precision metal part in an electromagnetic shielding environment; performing multi-scale spatial analysis on the laser scattering image data to extract a multi-modal image feature set containing a crystal boundary topological structure of the surface of the precision metal part and scattering spot distribution gradient features of the subsurface; converting process parameters, corresponding to the precision metal part, in an existing metal heat treatment process database into heat historical feature vectors, wherein the heat historical feature vectors comprise temperature gradient distribution features and time sequence phase change features; performing fusion processing on the thermal historical feature vector and the multi-modal image feature set through a multi-modal large model to obtain a fusion processing result so as to generate defect detection data; according to the invention, the detection rate and the detection efficiency of micron-sized defects in a complex electromagnetic environment are improved.

The invention provides a remote sensing coastline automatic extraction method and system based on residual space pyramid segmentation and two-dimensional attention, and relates to the technical field of space analysis. The method comprises the steps of high-resolution remote sensing image acquisition and preprocessing, sea-land segmentation network reasoning, probability graph thresholding and edge extraction and vectorization processing. According to the method, the segmentation precision is improved through multi-scale feature aggregation and attention enhancement, coastline vector data with geographic coordinates are generated in combination with edge detection and topological repair, and the method is suitable for spatial analysis and coastline monitoring.

The invention discloses a soil micro-plastic pollution monitoring analysis method based on big data analysis, and relates to the technical field of monitoring analysis. Comprising the following steps: arranging a sensor and sampling equipment, and collecting micro-plastic data; the method comprises the following steps: researching migration and diffusion laws of micro-plastic data in soil in different time periods by utilizing a time sequence analysis method, and constructing a dynamic migration model of micro-plastic in combination with meteorological conditions and geographical conditions; the method comprises the following steps: performing spatial analysis on micro-plastic concentration data of a monitoring area, identifying a high-risk area of micro-plastic pollution, and preliminarily determining a gathering area and a pollution source of pollutants; and comparing the position of the pollution source with a historical pollution source record, verifying the accuracy of the pollution source, and generating early warning information of a potential pollution source. According to the invention, meteorological and topographic factors are combined to identify the trend and path of pollutant diffusion, so that the positioning of the pollution risk area is more accurate, and comprehensive monitoring and deep analysis of micro-plastic pollution are realized.

The invention relates to the technical field of power grid planning, in particular to a charging pile planning method based on dynamic analysis. The method comprises the following steps: obtaining electric vehicle use data in a target area, and carrying out charging demand prediction analysis according to the electric vehicle use data to obtain a charging demand prediction model; based on the charging demand prediction model, performing multi-scene simulation to obtain charging demand distribution map data, multiple scenes including different traffic flows, different driving modes and different charging demand scenes; obtaining geographic information data of the target area; and constructing a spatial analysis model according to the geographic information data, and evaluating the candidate position of the charging pile according to the charging demand distribution map data, thereby obtaining position suitability score data. According to the method, different scenes are simulated, so that the adaptability and robustness of planning are enhanced.

The invention relates to the field of environmental noise monitoring, and discloses a noise monitoring point position automatic determination method fused with a noise map. The method comprises the following steps: acquiring a base map and sound source data of a target area, layering the base map according to a preset interval in a vertical direction, and carrying out gridding processing to obtain a three-dimensional grid; performing spatial analysis on the sound source data to obtain a sound source intensity matrix, and mapping the sound source intensity matrix to a three-dimensional grid to obtain a three-dimensional noise map; the base map comprises building structure data; performing three-dimensional path exploration on the three-dimensional noise map based on an ant colony algorithm to obtain a noise hotspot path and a pheromone concentration distribution diagram; and carrying out site selection analysis based on a genetic algorithm on the noise hotspot path and the pheromone concentration distribution diagram to obtain a Pareto optimal monitoring site set, the Pareto optimal monitoring site set being used for indicating site selection of the noise automatic monitoring site. By adopting the method, accurate and efficient automatic noise monitoring site selection in a complex urban environment can be realized, and the urban noise monitoring and treatment level is improved.

The invention discloses a real-time geographic information monitoring system and a real-time geographic information monitoring method, and relates to the technical field of geographic information. The geographic information monitoring platform is in communication connection with an image data acquisition module, a weather monitoring and correction module, an image matching and positioning module, a three-dimensional reconstruction and model generation module, a real-time dynamic monitoring module and an intelligent sensing early warning module, and all the modules are in electric signal connection. According to the invention, through integration of various data sources and a preprocessing technology, geographic space data is rapidly collected and processed, the geographic space data comprises various aspects of terrains, vegetation, buildings, meteorology and the like, spatial analysis and feature extraction are carried out through a GIS technology, the real-time state of a geographic environment can be accurately reflected, and compared with a traditional environment monitoring means, the method has the advantages of high efficiency and high reliability. The real-time monitoring system greatly shortens the data updating period and provides more timely and accurate environment information.

The invention relates to the technical field of wetland ecosystem soil carbon sequestration capability, in particular to a seasonal waterlogged wetland soil carbon estimation and dynamic monitoring method, which comprises the following steps of: selecting a sampling zone and a quadrat according to an equal-elevation water level gradient and a vegetation type; an optimal remote sensing estimation carbon model is determined through remote sensing image interpretation and screening of characteristic factors such as image waveband reflectivity, vegetation indexes, principal component characteristics and single-waveband textures, and soil organic carbon spatial distribution characteristics are analyzed through remote sensing inversion and GIS interpolation; constructing a Wetland-DNDC wetland carbon dynamic simulation model based on a DNDC model to predict wetland long-term carbon dynamic change and greenhouse gas emission; the invention provides a method for simulating carbon reserves and carbon dynamic monitoring based on field investigation and coupling a 3S technology with a Wetland-DNDC model. Compared with a traditional field observation method, the method has obvious technical and cost advantages, and can realize the technical advantages of spatial analysis and long-time sequence monitoring. The research method is suitable for a wetland ecosystem with seasonal hydrological characteristic changes.

The invention discloses an implementation method of an unmanned aerial vehicle remote sensing image enhancement system based on multi-source data fusion. The method comprises the following steps: S1, carrying optical and thermal imaging sensors through an unmanned aerial vehicle, performing autonomous flight and collecting data; s2, denoising, geometric correction and radiation correction are carried out on the preprocessed data; s3, performing contrast stretching, histogram equalization and edge detection by using an image enhancement algorithm; s4, extracting topographic features from the enhanced image, and generating a three-dimensional digital elevation model and a digital topographic map; and S5, performing multi-source data fusion, integrating high-precision topographic data into a geographic information system, and supporting map making and spatial analysis. Through the multi-sensor fusion and image processing technology, the image resolution and surveying and mapping precision of the complex terrain area are improved, detailed and accurate terrain information is provided, various applications such as environment monitoring, urban planning and disaster assessment are supported, and the practical value is achieved.

The invention relates to the technical field of geological analysis, and discloses a method for fusing a three-dimensional geological model and a WebGIS (Web Geographic Information System), aiming at solving the problems of poor data intercommunity, limited spatial analysis capability, difficulty in real-time updating and low model loading efficiency of the existing method, and the scheme mainly comprises the following steps: extracting geological model data, and carrying out standardized format processing; lightweight processing is carried out, and geological attributes and model nodes are bound one by one; the format is converted into a binary format embedded with a metadata label, and data integrity verification and automatic error correction are carried out in the conversion process; constructing a non-uniform adaptive octree spatial index, a multi-level attribute data architecture and a real-time updating mechanism of attribute data; after the geological model and the terrain are precisely registered and fused, a dynamic loading mechanism, a high-performance rendering mechanism and a geological model real-time updating mechanism are constructed, and a three-dimensional geological analysis tool is integrated. According to the method, efficient loading, real-time rendering, dynamic updating and spatial analysis of the three-dimensional geologic model in the WebGIS are realized.

The invention discloses an alpine grassland no-tillage restoration suitability evaluation method based on a 3S technology, and particularly relates to the technical field of data processing. Through the combination of multi-temporal satellite images and global positioning system data, the spatial dynamic change of the frozen soil layer of the alpine grassland and the long-term influence of the spatial dynamic change on vegetation growth are accurately obtained, and a frozen soil layer depth and distribution dynamic monitoring model is constructed based on multi-source remote sensing data and historical weather and soil temperature and humidity data. Analyzing the influence of freezing and thawing alternation on plant root growth; establishing a vegetation recovery potential index and a soil moisture supply index by combining the vegetation coverage and the dynamic change of the frozen soil layer, and generating a suitability partition map through a GIS spatial analysis and analytic hierarchy process; through field sampling and long-term vegetation growth monitoring data verification and model optimization, the accuracy of no-tillage restoration suitability evaluation is remarkably improved, and scientific and accurate decision support is provided for ecological restoration of alpine grassland.

The invention discloses a refined fourth-century three-dimensional geological modeling integration method which comprises the steps that basic geological data and drilling data of a research area are acquired, and the basic geological data comprise bedrock geological data and fourth-century geological data; the drilling data is modeled by a triangulated irregular network, and the basic unit of the triangulated irregular network is GTP; performing standardization processing on the drilling data; carrying out fourth stratigraphic division on the research area according to the basic geological data; dEMs of stratum interfaces are sequentially established from the earth surface to the underground according to the drilling data, sewing processing is conducted on the adjacent DEMs belonging to the same stratum, and a three-dimensional stratum model based on the multiple layers of DEMs is formed; dividing the GTP into TEN, and according to the three-dimensional stratum model based on the multilayer DEM, taking the TEN as a basic voxel, and constructing a fourth-century three-dimensional geologic model based on MD-GTP-TEN; the model constructed by the invention can express the geologic body more accurately and perform spatial analysis more efficiently.

The invention discloses a reservoir identification method fusing seismic attribute inversion and ancient karst form modeling, and relates to the technical field of reservoir identification and modeling, and the method comprises the steps: carrying out the multi-modal fusion processing of a standardized image data set through an image sensor, obtaining the multi-modal fusion image data, executing the high-precision texture sampling and space alignment processing, and obtaining a multi-modal image data set; generating a cross-modal image fusion matrix; inputting the cross-modal image fusion matrix into an image topological graph structure construction process, establishing an image block node relationship and a spatial connection edge weight, and generating an ancient karst topological graph; and coupling the karst earthquake joint matching graph with the comprehensive reservoir attribute data, establishing an effective reservoir evaluation model, and generating a multi-stage reservoir prediction layer set through weighted fusion and multi-parameter spatial analysis. By constructing an ancient karst topological graph and a karst earthquake joint matching graph, spatial modeling of a complex karst structure and cross-modal correlation analysis of earthquake abnormal attributes are realized.

The invention belongs to a vehicle path planning technology, mainly relates to the field of agricultural vehicle path planning, and particularly relates to a farm operation path planning method and application. Spatial analysis is carried out on the basis of a plot boundary, a target strip-shaped obstacle boundary and a non-target obstacle boundary which are obtained through pre-surveying and mapping, according to strip-shaped geometrical characteristics of a target strip-shaped obstacle, the long edge of the target strip-shaped obstacle is extracted as a boundary to be operated, and the outer side areas of the short edges at the two ends serve as turning areas; and generating a global path for traversing the to-be-operated boundary of the target strip-shaped obstacle in a reciprocating manner and avoiding a non-target obstacle in a specified direction until the last target strip-shaped obstacle in the specified direction is traversed. According to the method, the strip-shaped geometrical characteristics of the target strip-shaped obstacles are fully utilized, the redundancy rate and the omission rate of the operation path are reduced, the quality and the efficiency of farm unmanned operation are improved, meanwhile, the algorithm efficiency is greatly improved by using a pure geometric algorithm, and the global operation path traversing each specified target strip-shaped obstacle can be quickly generated.

The invention provides a prospecting data anomaly detection and early warning system, and relates to the technical field of data processing. Comprising a data acquisition module used for acquiring various kinds of prospecting data in a preset time period to obtain original data; the data fusion module is used for carrying out data fusion on the original data to obtain a multi-dimensional data set corresponding to each moment; the data processing module is used for calculating an anomaly detection index according to the difference of the multi-dimensional data sets at adjacent moments; the first detection module is used for determining real abnormal data and fault data according to the distribution of the abnormal detection indexes; the second detection module is used for determining spatial abnormal characteristics of the real abnormal data according to a spatial analysis algorithm to obtain spatial abnormal data; and the early warning module is used for generating corresponding early warning information according to the spatial abnormal data. According to the invention, the problems of incomplete prospecting data anomaly detection and low accuracy in the prior art are solved.

The invention discloses a method for analyzing the influence of railway tunnel construction on urban underground water, which belongs to the field of railway tunnel construction and comprises the following steps: S1, acquiring and preprocessing multi-source data; s2, constructing a geology-hydrology-construction-remote sensing multi-dimensional feature vector, and extracting an underground water disturbance index; s3, establishing a stress-seepage-heat conduction three-field coupling model; s4, analyzing a three-field coupling effect based on the three-field coupling model, and outputting a comprehensive risk level of the influence of tunnel construction on underground water; s5, fusing a comprehensive risk level by utilizing a GIS spatial analysis function, and combining real-time data to realize spatial visualization and graded early warning of underground water influence; and S6, geological parameters of the three-field coupling model are updated in real time, and an optimal construction parameter combination is searched. By adopting the method for analyzing the influence of the railway tunnel construction on the urban underground water, the scientificity and engineering practicability of analyzing the influence of the railway tunnel construction on the urban underground water are remarkably improved.

The innovation is the Landscape Syntax Algorithm, a new analytical framework to transcend the age-old limitations of space syntax. It integrates the highly versatile idea of landscape. Space syntax is largely objective and deals with the arrangement of space, along with little or no consideration for the more subjective parts of human aspects and experiences. Thus, the Landscape Syntax Algorithm fills that gap by providing a model that marries objective spatial measures with the more subjective cognitive and experiential aspects of landscape. This is carried out by infusing perceptual cognition and history / contextual layers within spatial analysis. Hence, there is a thorough reading of the relation between human experience and the built world. It opens up the opportunity to unify the most objective spatial configuration and subjective perceptual cognition to provide a powerful resource for the architect, urban planner, or researcher interested in analyzing and designing spaces that connect to the human experience in a more profound and mature sense. This invention enables quantification and analysis of landscape as moving and interactive phenomena towards a much more human-oriented contextual design of space.

The invention relates to the technical field of synthetic aperture radars, discloses a method for monitoring activity of a high-order loose body based on multi-source SAR data, and aims to solve the problem that an existing high-order loose body activity identification mode is poor in accuracy. Obtaining multi-source SAR data and carrying out adaptive preprocessing; extracting a maximum back scattering feature and quantifying activity; carrying out activity identification and multi-scale feature analysis on the high-position loose body; and comprehensively evaluating the multi-dimensional risk of the movable high-position loose body. Through organic combination of multi-track collaboration, fine feature extraction and multi-dimensional model evaluation, an effective scheme is provided for solving the problems that early recognition of the high-position loose body in the alpine and valley region is difficult and risk evaluation is inaccurate, and the accuracy and timeliness of monitoring and early warning are remarkably improved.

The invention discloses a traffic meteorological data fusion method based on inverse distance weight interpolation, and relates to the technical field of traffic meteorological data fusion. The traffic meteorological data fusion method based on inverse distance weight interpolation comprises the following steps: acquiring longitude values, latitude values and visibility measurement values of a plurality of time points of each traffic meteorological station in a set area; each traffic weather station in the set area is screened and analyzed based on the visibility measurement values of the plurality of time points to obtain a plurality of effective traffic weather stations, and the data from different time points and places are integrated and analyzed, so that the data utilization rate and accuracy are remarkably improved; the time sequence analysis of the visibility helps to understand the behavior pattern of each station changing with time, the spatial analysis ensures the continuity and consistency of data in geography, and the integration method optimizes the data processing flow, so that the visibility prediction is more accurate, and the complex traffic and meteorological condition analysis is effectively supported.

The invention relates to the technical field of underwater robots, in particular to an underwater robot cluster path planning method and system based on a dung beetle algorithm, and the method comprises the steps: obtaining a coordinate division region to construct an environment model, calculating and extracting an obstacle distance to fuse ocean current interference to generate a dynamic obstacle avoidance strategy, and evaluating the path speed similarity to generate a candidate path. And acquiring an offset angle difference, normalizing environmental factors to generate a correction path, and calculating a curvature fusion collision probability to generate a global path control instruction. According to the method, a dynamic model is constructed based on Cartesian coordinate division, the spatial analysis precision is improved, a sonar distance and ocean current interference are fused to generate a dynamic obstacle avoidance strategy, the trajectory smoothness is enhanced, candidate paths are screened by using vector similarity and Monte Carlo simulation, the collaboration is optimized, disturbance is reduced through coordinate offset and ocean current correction, and the accuracy of the dynamic obstacle avoidance strategy is improved. The curvature and collision probability are combined to balance safe energy consumption, and multi-dimensional parameter fusion improves cluster adaptability, precision, efficiency and energy utilization rate.

The invention relates to the technical field of geological early warning, in particular to a dangerous rock mass instability analysis method, system and equipment based on a space-time diagram neural network, by fusing unmanned aerial vehicle LiDAR, multispectral data, meteorological radar data and the space-time diagram neural network (ST-GNN), the system realizes sub-meter spatial resolution and minute-level time response, and the stability of dangerous rock mass instability analysis is improved. The four-dimensional (time and space) analysis result of the instability probability of the dangerous rock mass is obtained through high-precision space-time modeling, the problems that a traditional geological disaster early warning system is low in resolution ratio, slow in response and high in misinformation are solved, the comprehensiveness, accuracy and reliability of instability prediction of the dangerous rock mass are improved, and the early warning effect is good. And full-chain intelligent closed-loop management of real-time data acquisition-dynamic prediction-early warning push-feedback optimization is supported, the emergency decision time is shortened by real-time rainfall superposition risk thermodynamic diagrams, and the attenuation rate of long-term prediction precision is reduced by dynamically fusing newly added geological data and instability events through incremental learning.

The invention discloses a wave energy array development site selection method, which belongs to the field of wave energy development and utilization, and comprises the following steps of: 1) processing geographical distribution data by utilizing a GIS (Geographic Information System) spatial analysis method to obtain a limited development area graph layer; and 2) constructing an evaluation index system of wave energy array development site selection, and carrying out standardization processing to obtain a comprehensive evaluation result. And 3) calculating an offshore distance, and generating a refined developable range layer. And 4) carrying out wave direction statistical analysis in the developable range to obtain an array development range. And 5) on the basis of determining the array development range of the target sea area, determining a potential development site. 6, quantitative analysis and trend analysis of the array development capability are carried out with the potential development site as the center point, and the key development site is determined.According to the method, multi-dimensional evaluation indexes such as environment compatibility, resource endowment, technical feasibility and economic rationality are integrated, and a scientific basis is provided for array development site selection of the wave power station.

The invention provides a geological disaster monitoring method based on BIM and LiDAR combination. The method specifically comprises the steps that coordinate conversion from a BIM model to LiDAR point cloud data is carried out; bIM + point cloud three-dimensional space analysis is carried out, and the spatial position relation between the surface collapse area and the tunnel is calculated; carrying out multi-time sequence LiDAR point cloud earth surface monitoring, and carrying out filtering classification on the ground point cloud of each time sequence to obtain real ground feature points; through point cloud space distance analysis, the 3D deviation of surface deformation is obtained and is used as a supplement of a foundation SAR monitoring result. Therefore, the spatial position relation between the ground collapse area and the tunnel can be accurately obtained. Belongs to the field of geological disaster monitoring and rescue.

The invention relates to a grassland ecological degradation recovery effect dynamic evaluation method and device, equipment and a medium, and the method comprises the steps: obtaining interannual remote sensing data for a target region, carrying out the vegetation feature extraction of the interannual remote sensing data based on the sliding operation of a predetermined window on the interannual remote sensing data, and obtaining a reference time sequence; calculating the relative change rate of vegetation in the target area based on the reference time sequence; and according to the relative change rate and a preset threshold value, evaluating the degradation or recovery condition of the vegetation in the target area. According to the method, the optimal spatial analysis scale, namely the window, is determined according to spatial heterogeneity characteristics (semi-variable function range), adaptive conversion from the pixel to the landscape scale can be realized, subjective interference can be eliminated, a reference time sequence reflecting vegetation characteristics can be accurately determined on the basis of the window, and the method has the advantages of being simple in structure and convenient to operate. And the degradation or recovery condition of the target area can be accurately evaluated based on the reference time sequence.

The invention discloses an intelligent beam field construction management system based on BIM and GIS, and relates to the technical field of beam field construction management. Main parameters of a beam field construction environment can be fully covered by deploying a temperature and humidity sensor, an air quality sensor, a noise sensor, a wind speed and direction sensor and a rainfall sensor; spatial data association is performed on the BIM model by using a spatial analysis tool in a GIS platform, geographic information and construction in the BIM model are subjected to geographic space matching, and the accuracy of an association result is ensured through verification, so that data integration and sharing are facilitated, the use efficiency of the data is improved, and the method is suitable for popularization and application. A construction supervisor can monitor the construction progress according to the tracking data recorded in real time, a construction plan is adjusted in time, and smooth construction is ensured.

The invention discloses a multi-disaster chain type marine disaster risk assessment method based on regional disaster-bearing body distribution, relates to the technical field of marine disaster prevention and control, and aims to clarify the range of a research region, extract all disaster-bearing bodies in the research region, analyze the interaction relationship of the disaster-bearing bodies and establish an association probability matrix. By integrating a disaster chain theory, a probability statistical model and GIS spatial analysis, systematic identification and quantification of multi-disaster chain type marine disaster risks are realized, a logical relationship among a native event, a secondary event and a derivative event is defined, a disaster chain type structure chart is constructed, the total probability of a disaster-bearing body is calculated through a probability iterative algorithm, and the risk of the multi-disaster chain type marine disaster risk is identified and quantified. According to the method, direct and indirect conduction risks are comprehensively reflected, individual risk values are calculated in combination with disaster-bearing body vulnerability, and disaster chain overall risk values are generated through superposition, so that the limitation of isolated analysis of a single disaster in a traditional method is avoided, and complex interaction and cumulative effects of a disaster chain can be more comprehensively captured.

The invention discloses a risk zoning method for active fault engineering influence, which relates to the technical field of engineering construction evaluation, and comprises the following steps: I, fusing multi-source data of a detection fault, constructing a three-dimensional geometric model of the fault, and analyzing and correcting a fault distribution rule by utilizing a GIS (Geographic Information System) space; iI, combining fault sliding rate, paleoearthquake recurrence period and deep engineering crustal stress inversion, and evaluating activity characteristics of the hidden fracture in the engineering service period. Through multi-source data fusion, three-dimensional model construction and GIS correction, multi-factor overlay analysis and a dynamic correction mechanism, multivariate characteristics of the active fault and complex geological conditions of an engineering site are comprehensively considered, the problem of limitation of a zoning result is solved, the accuracy of risk assessment is improved, limitation of a single index is broken through, and the risk assessment efficiency is improved. Closed-loop management of data acquisition-risk assessment-engineering response is realized, and scientific and reliable technical support is provided for safe site selection, optimization design and operation and maintenance of major infrastructures.

The invention belongs to the technical field of coastal zone protection and restoration project effect evaluation, and provides a coastal zone protection and restoration project ecological environment effect evaluation method and system, and the method comprises the steps: obtaining coastal zone protection and restoration project ecological environment effect evaluation index data; establishing a coastal zone protection and restoration project ecological environment effect evaluation system and determining an evaluation index weight; a Spline with Barrier method in a GIS (Geographic Information System) is combined to predict the spatial distribution characteristics of each index data of the ecological environment; according to a standard assignment method, obtaining score distribution characteristics of each index of the ecological environment of the coastal zone protection and restoration project region, and evaluating the ecological environment effect of the coastal zone protection and restoration project region in combination with an analytic hierarchy process and a GIS spatial analysis method. According to the method, the ecological environment effect of the protection and restoration project is evaluated, the ecological environment grade result can be reflected spatially, comprehensively and objectively, and suggestions are provided for coastal zone protection and restoration project maintenance.

The invention discloses a wind power plant micro-siting assessment method based on spatial analysis and climate adaptability, relates to the technical field of wind power plant siting, and solves the problems that in the prior art, spatial analysis depends on static topographic data, climate adaptability assessment uses dynamic meteorological data, and the static topographic data and the dynamic meteorological data lack a space-time synchronization mechanism; and a prediction result has a large deviation. The method comprises the following steps: firstly, acquiring multi-source data and fusing to realize time-space synchronization of the data; then, constructing and solving an objective function to obtain a candidate point set, and screening out an optimized point distribution scheme of which the prevailing wind direction coverage is greater than a set threshold value; and finally, inputting prediction data of various extreme climates into the cost-per-kilowatt-hour model, introducing extreme climate toughness parameters into calculation to carry out climate adaptability data correction, and calculating return on investment cycles under different carbon emission scenes. Through the steps, the limitation that only static wind resources are concerned on traditional site selection is broken through, and combined evaluation of the regional climate adaptability and the complex terrain adaptability is achieved.

The invention discloses a map database-based land type map spot storage and analysis method and system. The method comprises the following steps of: acquiring and processing data; storing data; monitoring pattern spot type distribution analysis; performing annual change investigation pattern spot and land type change analysis; and reading and displaying data. According to the method, spatial analysis is carried out on land type change monitoring pattern spots and annual change investigation pattern spots, and a method based on a pattern database is designed to store analysis results; the incidence relation and important attributes of the change monitoring pattern spots and the annual change pattern spots can be expressed on a visual platform, and the monitoring type distribution condition and the annual change survey of the change conditions of different land types in a certain space range are analyzed; according to the storage and analysis method, the internal relation between the change monitoring pattern spots and the annual change pattern spots is visually presented, the effectiveness of change monitoring pattern spot analysis is improved, the data value of the monitoring pattern spots is deeply mined, natural resource data analysis and application are facilitated, and planning and decision making of related departments of the natural resource industry are supported.