42 results about "Variance (land use)" patented technology

The invention relates to a dynamic prediction method of landuse change. The basic idea of GeoCA-Landuse model simulating landuse change can introduce the life character of the land element and simulate the dynamic evolvement of the type of the landuse. Beginning with the superimposition analysis and the transfer analysis of the two phase landuse thematic map, combining with the measurement model of landuse change, analyzing the the landuse change character. According to the model controlling factors of river system and road map analysis, constructing the layer of the controlling factors, determining the reasonable neighbors and transfer rules in light of the historical land-use change process, with the combination of adjusting the model parameters of the social economic data. Setting a powerful spatial data processing of GIS, the land use trend is simulated and predicted. The invention can simulate the dynamic trend of the landuse change and provide a scientific basis for decision-making.

The invention relates to an automatic updating method of a land-use map based on historical data and remote sensed data. Firstly historical data is pre-processed to obtain a land-use patch number map and a land-use mode code map which are overlapped with a remote sensed image first main component map, and various land-use mode patch feature structure arrays are obtained through calculation; changed patches are detected by adopting a cycle average value significance statistical test method; land-use unchanged regions are used as the samples of land-use interest regions; and minimum distance supervised classification is performed to land-use changed regions to obtain the land-use maps of the changed regions, and the land-use maps of the changed regions are united with the images of and-use unchanged regions to obtain new land-use maps. The automatic updating method adopts two data sources, improves the variation test precision, realizes the updating automation of the land-use maps, can be applied to the departments of land and resources to update a great amount of land-use map data, quickly test the land-use variation, and has wide market prospect and application value.

A method for simulating urban land use change merges an idea of dynamic neighborhood into a cellular automation and a Monte-Carlo model and regulates a range of local neighborhood according to different cell state distribution and by a Monte-Carlo method, so that the problems of spatial-dimension uncertainty and time-dimension randomness of urban land use change are solved, and simulation of the urban land use change is implemented. The method includes: acquiring and preprocessing data; determining cell size, cell state and iteration time according to a classification chart, and using the Monte-Carlo model to determine the range of dynamic neighborhood; establishing a land use change simulation system based on the Monte-Carlo model and the cellular automation model; using the land use change simulation system to simulate and predict by the Monte-Carlo method and the cellular automaton method; and analyzing a land use structure based on simulation results. By the method, the problem of uncertainty occurring in simulation of urban land use change is solved, and simulation effect and precision are improved.

The invention discloses a method for automatically extracting a newly added construction land change image spot of a high-resolution remote sensing image. The method comprises the following steps: inputting two high-resolution remote sensing images of a same area at different periods and performing geometrical fine calibration and relative radiation calibration; respectively calculating textural features of all wave bands of the images at two periods; performing difference value operation on the textural features and the spectral signature of the images by waveband, thereby obtaining a difference value image and cutting thresholds; logically combining two-value result images of all wave bands; performing morphological closed operation, hole filling and small-area image spot removing treatment on the two-value result images after being logically combined in turn, thereby obtaining a change image spot of land utilization; making zone marks on the change image spot of land utilization so as to generate an image spot object; calculating the textural features of each image spot object in a remote sensing image at a new period; and extracting the newly added construction land change image spot. According to the method provided by the invention, the problem of extracting the newly added construction land is mainly solved, and meanwhile, the capacity of detecting the interior change of the construction land is achieved.

The invention discloses a method for regulating and controlling a pattern of a protective forest system. The method comprises the following steps of: 1, acquiring land utilization landscape characteristics of a river basin in each period, and analyzing the evolution characteristics of the land utilization pattern of the river basin; 2, analyzing the driving factors of the change of the landscape type of the river basin and the main driving power of the change of the land utilization of the river basin by a principal component analysis method; 3, analyzing and comparing the condition of the ecological service function of the river basin in each period in the aspects of water source conservation, soil conservation, carbon fixation and oxygen release, nutrient substance accumulation, atmospheric environment purification and biodiversity protection; and 4, performing dynamic simulation by using a gray linear planning method and a Clue-s model to acquire the landscape optimized configuration scheme of the river basin. By processing satellite images in different time sequences, the relation between the change of a landscape pattern and natural, social and economic activities is uncovered, a driving mechanism which influences the evolution of the landscape pattern is analyzed, and the method for regulating and controlling the pattern of the protective forest system on the basis of landscape ecology is constructed.

The present invention proposes and discloses a method for dynamically simulating a land future use scenario. The method integrates a capability that a cellular automaton (CA) simulates a complex systematic space-time evolution process and an advantage that a CLUE-S model simulates multiple types of land use type competitions; and the method overcomes certain inherent defects of a traditional CA or a pure CLUE-S model through advantage integration; in addition, intelligent computation of a distributional probability is realized by adopting an artificial neural network (ANN) algorithm; synchronous simulation of multiple land use changes is realized by introducing a competition mechanism of a roulette, so that the new method is more suitable for multiple types of land use data; and moreover, compared with a traditional model, the method has the practical advantages of higher precision, suitability for multiple scales, low data demand, few parameters, simple and convenient operation, high speed and the like. According to the method for dynamically simulating the land future use scenario, the intelligent algorithm (ANN) and the uncertainty model (the roulette) are effectively combined; and the method is applied to the prediction of the land future use scenario.

The invention discloses a city group ecological space damage identification and evaluation method. The method includes: analyzing and identifying important landscape space patterns such as city groupecological source land and ecological galleries; on the basis, overlapping an urban group landscape pattern comprehensive index and an ecological service function conversion equivalent evaluation result brought by land utilization change to obtain urban group ecosystem damage space distribution; furthermore, combining on-site investigation and classification combing to summarize the typical ecological damage space type of the urban group, and carrying out cause analysis and damage state evaluation.

The invention discloses a remote-sensing-based method for estimating influences of area vegetation cover on the earth surface air temperature, and relates to a method for simulating the influences of area vegetation cover on the earth surface air temperature. The method aims at solving the problem that existing research related to the feedback of vegetation to climate can not be combined with changes of vegetation cover along with time, and includes the steps of 1, obtaining data of a cover research area, and carrying out preprocessing; 2, extracting the distribution of a certain vegetation type without land use changes within a research time period; 3, achieving anomaly processing of data of earth-surface air temperature observing lattice points; 4, obtaining OMR air temperature values of the lattice points; 5, rasterizing OMR air temperature data; 6, calculating pixel NDVI change trend values and pixel OMR air temperature change trend values; 7, extracting NDVI annual average values, the NDVI change trend values and the OMR air temperature change trend values of all pixels within the whole research time period; 8, building an OMR air temperature forecasting model. The remote-sensing-based method is applied to the field of eco-climate researching.

The invention discloses a method for discriminating a changeable graphic spot in dynamic monitoring of a present situation of land use. The method comprises the following steps of: obtaining data of a selected changeable graphic spot; and comparing the data of the changeable graphic spot with a predefined condition of change types of the land use, and determining which change type of the land use the changeable spot belongs based on a comparison result. According to the method and system for discriminating the changeable graphic spot in the dynamic monitoring of the present situation of the land use, the selected change graphic spot is compared with the predefined condition of the change types of the land use to identify which change type of the land use the change graphic spot belongs, and manual work is unnecessary during the whole identification process, so that labor force is saved, and discriminating efficiency is improved; and the data of the changeable graphic data are compared with the preset condition, so that the discrimination accuracy is increased in comparison with that of the artificial judgment.

The invention relates to a land resource utilization change dynamic prediction model based on a GIS (Geographic Information System) and a processing method. The basic idea of the GeoCA (cellular automaton)-Landuse model on simulating land utilization change is as follows: vital signs of a land unit are introduced, and the dynamic evolution of land utilization type is simulated; starting with the overlay analysis and transition analysis of two time phase land utilization thematic maps, and combining with the metering model of land utilization change, the land utilization dynamic change feature is analyzed; the model control factors are analyzed according to a river system and traffic map in a researched area, and a control factor layer is constructed; combining with social economic data, the model parameters are adjusted, and reasonable neighbors and transformation rules are determined; and with the powerful spatial data processing and analyzing functions of the GIS, the land utilization change trend is simulated and predicted according to the change process of history land utilization. According to the model and the method disclosed by the invention, the simulation on dynamic trend and evolution rule of land utilization change is realized, and scientific basis is provided for scientific decision-making.

The invention discloses a remote-sensing satellite image-based highly-automated land utilization updating method. The method includes the steps of: 1) carrying out change detection for image data on which ortho-rectification, image registration and cloud shadow detection preprocessing are already carried out, and extracting a front-back-time-phase land utilization change special-product; 2) obtaining highly homogeneous image segmentation areas, utilizing vectorization technology to generate image object map spots, and using the same as processing units; 3) calculating various map features of the object map spots; 4) collecting training samples to use the same for training of a land utilization classifier; 5) identifying various land utilization land-classes on the basis of land covering classification results to realize extraction of land utilization ground-object information; and 6) combining a change detection product, a base-period land utilization special-map and a land utilizationclassifications special-map, updating special information of change map spots in the base-period land utilization special-map through overlay analysis, and obtaining a present-situation land utilization updating product.

The invention provides a method for optimizing land use evolution CA model transformation rules, and the method comprises the following steps: firstly, according to the multitemporal spatiotemporal land use data of a studied area, selecting factors influencing the land use change of the studied area as the spatial characteristic variables of land use evolution CA; establishing a Logistic regression method based land use evolution CA model, selecting sampling point data, and calculating the influence weight of each space variable; and optimizing the parameters of the land use evolution CA model and establishing an evolution programming algorithm based land use evolution CA model by using an evolution programming method, and finally, verifying the simulation accuracy and efficiency of the model. Compared with the existing commonly-used method for obtaining land use evolution CA model transformation rules, the method provided by the invention is simpler in operation, faster in convergence speed and higher in simulation precision; and compared with other methods for obtaining land use evolution CA model transformation rules, the method provided by the invention is more identical with the essential characteristics of spatiotemporal land use evolution.

The invention provides an intelligent understanding method of land use change, based on multi-temporal remote sensing images. The intelligent understanding method of land use change, based on multi-temporal remote sensing images includes the steps: detecting objects which are changed in the two-temporal remote sensing image target area and the content of the changes described by natural language,wherein detection of the objects which are changed in the two-temporal remote sensing image target area includes acquisition of the data of two-temporal, preprocessing of the remote sensing images, blocked cutting of the two-temporal data, construction of a mask layer, model training, model testing, detection of the content which is changed, and highlighting of the changed blocks; and the contentof the changes described by natural language includes determination of statement templates for describing the content of changes, and generation of description statement. The intelligent understandingmethod of land use change, based on multi-temporal remote sensing images respectively segments the two-temporal remote sensing images, uses the natural object class information to determine the change of the same position natural object class, is more accurate in change detection, is deterministic in the described content, describes the content of changes by the natural language, visually displays the content of changes of the two-temporal images, and is convenient for deep understanding of remote sensing images.

The invention relates to a sub-pixel spatial mapping method based on spatial correlation, which comprises the step of calculating the spatial distribution of a basic component in pixels, namely sub-pixels by utilizing area vector or abundance ratio of mixed pixels and components (end members) of neighbor pixels of the mixed pixels so as to simulate a land feature boundary which is more detailed than that by a common remote sensing classification method. The method has the advantages of wide practicability, high analog simulation and the like, and is suitable for topographical information extraction and topographical data mining work such as target extraction by remote sensing data, monitoring of land resource utilization change, evaluation of environmental pollution, analysis of natural disasters and the like.

Embodiments of the invention disclose a land utilization change analysis and prediction method and device. The method comprises the steps of obtaining land remote sensing image data of a plurality ofhistorical years; extracting land types in the land remote sensing image data of the historical years by utilizing a human-computer interaction interpretation method, and drawing a classification vector diagram; according to the classification vector diagram, calculating the land change amplitude, the dynamic attitude and the spatial change, further analyzing the dynamic change of the land in different periods, and concluding the land utilization space-time change characteristics and rules in historical years; selecting a plurality of driving factors to construct a Markov-CA prediction model;and according to the land utilization space-time change characteristics and rules of the historical years, utilizing a Markov-CA prediction model to obtain a land utilization space pattern of a futuretarget year. According to the land utilization change analysis and prediction method and device disclosed by the embodiment of the invention, the Markov-CA prediction model is constructed by introducing the driving factors for different land types, so that the precision of land utilization change analysis and prediction is improved.

The present invention discloses a coupling evaluation method for the simulation precision of the cellular automata of land use change. The method comprises: firstly using a remote sensing image to extract land use information; based on the cellular automata, simulating the land use change and calculating the Kappa coefficient and the Contagion index of the precision evaluation index; and using theentropy weight method to assign weights to the Kappa coefficient and the Contagion index, and constructing a coupling evaluation model for simulation precision based on the weights to more accuratelyevaluate the simulation precision of the land use change, so that comprehensive and objective analysis on the problem of the land use change can be implemented. According to the method disclosed by the present invention, for the problem of selecting the evaluation index of the simulation precision of the land use change, not only the more mainstream Kappa coefficient is used, but also the appropriate landscape index Contagion index is selected, so that a coupling evaluation model for the simulation precision is constructed; and compared with using a certain index alone, the model comprehensively considers the simulation precision of the cellular automata of land use change from two aspects of numerical errors and error spatial distribution.

The invention discloses a land utilization change driving force screening method and device based on LASSO regression. The method comprises the steps that explanatory variable and response variable data in a research region is acquired; a LASSO regression model is constructed, and LASSO regression is executed; a residual sum of squares and multi-colinearity indexes in each step of LASSO regressionare calculated, and driving factors needing to be eliminated are determined according to calculation results; remaining driving factors are used as explanatory variables of the LASSO regression modelto execute LASSO regression again; and the importance of the driving factors is determined according to coefficients of response variables in the LASSO regression executed again. Through the screening method and device, a refined model can be constructed, variable screening and complexity adjustment can be performed during fitting of a generalized linear model, and accurate screening can be performed according to numerous dependent variables in multi-colinearity. The screening method and device can be widely applied to the environment modeling field.

The invention discloses a land use transition economic and social effect evaluation and monitoring information integration system. The system comprises a database, a land use status and transition characteristic analysis module, a comprehensive economic and social development level evaluation module and an economic and social development driving mechanism spatial and temporal differentiation characteristic module; the database is used for storing data; the land use status and transition characteristic analysis module is used for analyzing the quantity and structure of land use statuses and obtaining the spatial distribution and land use transfer matrix of land use transition; the comprehensive economic and social development level evaluation module is used for obtaining economic and socialdevelopment level spatial differentiation characteristics; and the economic and social development driving mechanism spatial and temporal differentiation characteristic module is used for obtaining the spatial differentiation characteristic analysis results of three driving mechanisms, namely, economic development environment, ecological development environment and land use status. According to the system, on the basis of the dynamic monitoring of land use change and land use transition economic and social effect indicators, the automatic evaluation and dynamic tracking of land use transitioneconomic and social effects can be completed, and therefore, the economic and social evaluation efficiency of the land use transition can be improved, and costs can be reduced.

The invention discloses a global land utilization and land cover sequence spatialization method integrating GCAM and CA. The GCAM model and the geographic CA are combined, global 283 subareas are achieved, global land use sequence spatial data products from 2010 years to 2100 years are achieved, the spatial resolution is 1 km, and the time resolution is 5 years. By integrating the initial probability of the neural network, the neighborhood influence, the ground class transformation weight matrix of each sub-region and a planning constraint condition, the comprehensive transformation probability of the ground class of each sub-region is obtained, and the land utilization and the land coverage of each sub-region is spatialized. The method is mainly applied to the global land utilization change and coverage modeling under different development scenes in the future, has the capability of producing high-resolution global LUCC products, and promotes the research on the construction of a high-resolution land utilization model under the global scale.

The invention discloses a land use change simulation method and system based on a partitioned CLUE-S model. The method comprises the following steps: obtaining driving factors of land use change and three-phase land use status data; The driving factors of the land use change are analyzed and processed by hot spots, and after the analysis and processing, the spatial partition is carried out to obtain the spatial partition result; carrying out data classification and processing on the three-phase land use status data, uniformly processing the spatial resolution after the data classification andprocessing, and obtaining the three-phase land use status data with unified spatial resolution; according to the driving factors of the land use change, the land use change simulation is carried out according to the classified land use status data of three periods with unified spatial zoning results and spatial resolution, and the simulation results are obtained. In the implementation of the invention, the regional difference of land use in space can be reflected, the applicability of the research area with obvious regional difference and the precision of the simulation can be realized.

The invention discloses a knowledge representation dynamic frame model for land utilization changes, and the knowledge representation dynamic frame model includes nodes, connecting sides and a probability parameter set, wherein the probability parameter set is located nearby the nodes; the nodes are used for representing the land use patterns, and include the time attributes and the area characteristics of corresponding land use patterns; the connecting sides are connected with the nodes, representing the existence of the conversion relationship between the connected nodes; the arrow directions of the connecting sides represent the conversion direction between the connected nodes; and the probability parameter set represent the conversion intensity between the nodes. The model can efficiently represent various knowledge patterns of the land use changes, uses the nodes and directed edges to represent the qualitative knowledge of the land use changes, uses the probability parameter set to represent the quantitative knowledge, establishes the frame model integrally representing the qualitative knowledge and the quantitative knowledge, and realizes the organic combination of representation of the qualitative knowledge and the quantitative knowledge.