Search

CN-121998300-A - Comprehensive measurement method, device and storage medium for rural area development state

CN121998300ACN 121998300 ACN121998300 ACN 121998300ACN-121998300-A

Abstract

The invention relates to a comprehensive measure method, a device and a storage medium for a village region development state, wherein the method is applied to the technical field of computer technology and village development, and comprises the steps of constructing a six-dimensional characteristic index system for measuring the village region development state by adopting a multi-level fuzzy comprehensive evaluation model, wherein the six-dimensional characteristic index system comprises natural climate characteristic dimension, regional environment characteristic dimension, traffic facility characteristic dimension, urban and rural associated characteristic dimension, resource endowment characteristic dimension and economic development characteristic dimension, establishing a six-dimensional comprehensive measure model for the village region development state by integrating a drive contribution judgment sub-model of the six characteristic dimensions, realizing space-time simulation of multi-source heterogeneous characteristic data corresponding to each characteristic dimension by adopting a high-precision curved surface modeling method and a GIS space-time analysis method, and generating a system measure result of the village region development state by adopting the six-dimensional comprehensive measure model based on the six-dimensional characteristic space-time simulation data. The method can avoid the limitation of the measurement result of a single dimension or a single region.

Inventors

  • FAN ZEMENG
  • SONG CAIYU
  • LIU YANSUI

Assignees

  • 中国科学院地理科学与资源研究所

Dates

Publication Date
20260508
Application Date
20251225

Claims (12)

  1. 1. A method for comprehensively measuring the development state of a rural area, which is characterized by comprising the following steps: A multi-level fuzzy comprehensive evaluation model is adopted to construct a six-dimensional characteristic index system for measuring the development state of a rural area, wherein characteristic dimensions in the six-dimensional characteristic index system comprise natural climate characteristic dimensions, regional environment characteristic dimensions, traffic facility characteristic dimensions, urban and rural associated characteristic dimensions, resource endowment characteristic dimensions and economic development characteristic dimensions; establishing a driving contribution judgment sub-model and a model system of influence of each characteristic dimension on the development state of the rural area under the six-dimensional characteristic index system; Integrating the six driving contribution judgment sub-models of the characteristic dimensions, and establishing a six-dimensional comprehensive measure model of the development state of the rural area region; The high-precision curved surface modeling method and the GIS space-time analysis method are used for realizing space-time simulation of multi-source heterogeneous characteristic data corresponding to each characteristic dimension in a target research period of a target research region, so as to obtain six-dimensional characteristic space-time simulation data; And generating a system measurement result of the development state of the rural area in the target research period by adopting a six-dimensional comprehensive measurement model based on the six-dimensional characteristic space-time simulation data, wherein the system measurement result comprises six-dimensional characteristic contribution measurement, development process and state identification calculation.
  2. 2. The method of claim 1, wherein generating a system measure of the state of development of the rural area of the target study area within the target study period based on the six-dimensional feature spatiotemporal simulation data using a six-dimensional comprehensive measure model comprises: acquiring state change parameter values of each characteristic dimension in the target research area based on the six-dimensional characteristic space-time simulation data by adopting a driving contribution judgment sub-model corresponding to each characteristic dimension; And generating a systematic measurement result of the rural regional development state of the target research area in the target research period based on the driving contribution coefficient of each characteristic dimension and the state change parameter value corresponding to each characteristic dimension.
  3. 3. The method according to claim 2, wherein the driving contribution determination sub-model comprises a parameter calculation model corresponding to each measure index in the feature dimension; The driving contribution judgment sub-model corresponding to each characteristic dimension is adopted, the state change parameter value of each characteristic dimension in the target research area is obtained based on the six-dimensional characteristic space-time simulation data, and the driving contribution judgment sub-model comprises the following components: determining a plurality of target measure indexes under the target feature dimension; adopting a parameter calculation model corresponding to each target measure index, and acquiring a parameter value corresponding to each target measure index based on the six-dimensional characteristic space-time simulation data; And obtaining the target state change parameter value of the target feature dimension in the target research area based on the parameter value of each target measure index and the weight decomposition coefficient corresponding to each target measure index.
  4. 4. A method according to claim 3, wherein the driving contribution determination sub-model corresponding to the natural climate characteristic dimension is composed of a system based on weight coefficient decomposition by three first parameter calculation models of an average air temperature calculation model, an average precipitation calculation model and a dry and wet index calculation model; the obtaining the parameter value corresponding to each target measure index based on the six-dimensional characteristic space-time simulation data by adopting the parameter calculation model corresponding to each target measure index comprises the following steps: acquiring daily air temperature data, daily precipitation data and total days in the six-dimensional characteristic space-time simulation data; obtaining an average air temperature parameter value based on the daily air temperature data and the total number of days; Obtaining an average precipitation parameter value based on the daily precipitation data and the total number of days; obtaining a dry-wet index parameter value based on the daily air temperature data, the daily precipitation data, and the total days; The obtaining, based on the parameter values of the target measure indexes and the weight decomposition coefficients corresponding to the target measure indexes, the target state change parameter values of the target feature dimension in the target research area within the target research period includes: And obtaining the target state change parameter value of the natural climate characteristic dimension in a target research period based on the calculation results of the parameter values corresponding to the three first parameter calculation models and the weight decomposition coefficients corresponding to the three first parameter calculation models in the natural climate characteristic dimension.
  5. 5. The method according to claim 3, wherein the driving contribution determination sub-model corresponding to the regional environmental feature dimension is composed of a system based on weight coefficient decomposition by using three second parameter calculation models of a coverage change dynamic attitude calculation model, an ecological vulnerability calculation model and a topography fluctuation calculation model; the obtaining the parameter value corresponding to each target measure index based on the six-dimensional characteristic space-time simulation data by adopting the parameter calculation model corresponding to each target measure index comprises the following steps: determining a first land area of each land utilization coverage type in a first research period at the beginning of the target research period, a second land area of each land utilization coverage type in a second research period at the end of the target research period and the period length of the target research period in the six-dimensional characteristic space-time simulation data; Obtaining a land utilization coverage variation dynamics parameter value based on the first land area, the second land area, and the period length; Based on the coefficient of each parameter variable corresponding to the ecological vulnerability and the grade of each parameter variable in the six-dimensional characteristic space-time simulation data, obtaining an ecological vulnerability parameter value; Obtaining a terrain fluctuation parameter value based on the maximum altitude value, the minimum altitude value and the flat land area of the target research area in the six-dimensional characteristic space-time simulation data; The obtaining, based on the parameter values of the target measure indexes and the weight decomposition coefficients corresponding to the target measure indexes, the target state change parameter values of the target feature dimension in the target research area within the target research period includes: And obtaining a target state change parameter value of the regional environment feature dimension in a target research period based on the calculation results of the parameter values corresponding to the three second parameter calculation models and the weight decomposition coefficients corresponding to the three second parameter calculation models in the regional environment feature dimension.
  6. 6. The method according to claim 3, wherein the driving contribution determination sub-model corresponding to the characteristic dimension of the traffic facility is composed of a traffic density calculation model, a traffic capacity calculation model and a logistics capacity calculation model, which are based on weight coefficient decomposition by three third parameter calculation models; the obtaining the parameter value corresponding to each target measure index based on the six-dimensional characteristic space-time simulation data by adopting the parameter calculation model corresponding to each target measure index comprises the following steps: determining the total length of a road, the total area of the area, the number of vehicles and the total logistics in the target research area in the six-dimensional characteristic space-time simulation data; Obtaining a traffic density parameter value based on the total road length and the total area of the area; Obtaining a traffic capacity parameter value based on the number of vehicles and the total road length; Obtaining a logistics transportation capacity parameter value based on the logistics total amount and the road total length; The obtaining, based on the parameter values of the target measure indexes and the weight decomposition coefficients corresponding to the target measure indexes, the target state change parameter values of the target feature dimension in the target research area within the target research period includes: And obtaining a target state change parameter value of the traffic feature dimension in a target research period based on the calculation results of the parameter values corresponding to the three third parameter calculation models and the weight decomposition coefficients corresponding to the three third parameter calculation models in the traffic feature dimension.
  7. 7. The method according to claim 3, wherein the driving contribution determination sub-model corresponding to the urban and rural associated feature dimension is composed of a population density calculation model, a cultural education state calculation model and an urban and rural commute calculation model, which are based on weight coefficient decomposition by three fourth parameter calculation models; the obtaining the parameter value corresponding to each target measure index based on the six-dimensional characteristic space-time simulation data by adopting the parameter calculation model corresponding to each target measure index comprises the following steps: Determining population total number, regional total area, first population meeting preset academic level, second population living in city and working in country, third population living in country and working in city, city resident population and country resident population in the target research region in the six-dimensional characteristic space-time simulation data; Obtaining population density parameter values based on the population total and the area total; obtaining a cultural education level parameter value based on the first population and the population total; Obtaining an urban and rural commute parameter value based on the second number of people, the third number of people, the urban resident population and the rural resident population; The obtaining, based on the parameter values of the target measure indexes and the weight decomposition coefficients corresponding to the target measure indexes, the target state change parameter values of the target feature dimension in the target research area within the target research period includes: And obtaining a target state change parameter value of the urban and rural associated feature dimension in a target research period based on the calculation results of the parameter values corresponding to the three fourth parameter calculation models and the weight decomposition coefficients corresponding to the three fourth parameter calculation models in the urban and rural associated feature dimension.
  8. 8. The method according to claim 3, wherein the driving contribution determination sub-model corresponding to the characteristic dimension of the resource endowment is composed of an ecological bearing capacity calculation model, a water resource bearing capacity calculation model and a population bearing capacity calculation model, which are based on weight coefficient decomposition by three fifth parameter calculation models; the obtaining the parameter value corresponding to each target measure index based on the six-dimensional characteristic space-time simulation data by adopting the parameter calculation model corresponding to each target measure index comprises the following steps: Based on the equalization factors, yield factors and areas corresponding to the land utilization coverage types, obtaining ecological bearing capacity parameter values; Obtaining a water resource bearing capacity parameter value based on a water resource balance factor, a water resource yield factor, the total amount of water resources in the target research area and the water production capacity per unit area; Obtaining a population bearing capacity parameter value based on the agricultural land area, the average agricultural land productivity, the availability coefficient of the agricultural land and the average grain demand in the target research area; The obtaining, based on the parameter values of the target measure indexes and the weight decomposition coefficients corresponding to the target measure indexes, the target state change parameter values of the target feature dimension in the target research area within the target research period includes: And obtaining a target state change parameter value of the resource endowment feature dimension in a target research period based on the calculation results of the parameter values corresponding to the three fifth parameter calculation models and the weight decomposition coefficients corresponding to the three fifth parameter calculation models in the resource endowment feature dimension.
  9. 9. The method according to claim 3, wherein the driving contribution determination sub-model corresponding to the economic development feature dimension is composed of a system based on weight coefficient decomposition by three sixth parameter calculation models of a production value variation calculation model, an industrial structure dynamic state calculation model and a production total value variation dynamic state calculation model; the obtaining the parameter value corresponding to each target measure index based on the six-dimensional characteristic space-time simulation data by adopting the parameter calculation model corresponding to each target measure index comprises the following steps: determining the industrial proportion of each industrial type in each period and the industrial production value of each industrial type in each period in the six-dimensional characteristic space-time simulation data; Obtaining a production value variation degree parameter value, an industrial structure dynamic degree parameter value and a production total value variation dynamic degree parameter value based on the industrial specific gravity and the industrial production value; The obtaining, based on the parameter values of the target measure indexes and the weight decomposition coefficients corresponding to the target measure indexes, the target state change parameter values of the target feature dimension in the target research area within the target research period includes: And obtaining the target state change parameter value of the economic development feature dimension in a target research period based on the calculation results of the parameter values corresponding to the three sixth parameter calculation models and the weight decomposition coefficients corresponding to the three sixth parameter calculation models in the economic development feature dimension.
  10. 10. The method according to claim 3, wherein the six-dimensional comprehensive measure model is a rural regional development state six-dimensional comprehensive measure model established by comprehensively integrating six characteristic dimensions of the natural climate characteristic dimension, the regional environment characteristic dimension, the traffic facility characteristic dimension, the urban and rural associated characteristic dimension, the resource endowment characteristic dimension and the economic development characteristic dimension on the basis of decomposing a weight coefficient of the rural regional development driving influence by each characteristic dimension by using a GIS space-time dynamic weighting method based on a system theory and a comprehensive integration thought; the generating a system measurement result of the rural regional development state of the target research area in the target research period based on the driving contribution coefficient of each characteristic dimension and the state change parameter value corresponding to each characteristic dimension comprises the following steps: and obtaining a systematic measurement result of the development state of the rural area in the target research period of the target research area by adopting state change parameter values corresponding to the six driving contribution judgment sub-models of the characteristic dimensions and driving contribution coefficients of the characteristic dimensions to the development state of the rural area.
  11. 11. A comprehensive measure device for the development status of a rural area, the device comprising: the six-dimensional system construction unit is used for constructing a six-dimensional characteristic index system for measuring the development state of a rural area by adopting a multi-level fuzzy comprehensive evaluation model, wherein characteristic dimensions in the six-dimensional characteristic index system comprise natural climate characteristic dimensions, regional environment characteristic dimensions, traffic facility characteristic dimensions, urban and rural associated characteristic dimensions, resource endowment characteristic dimensions and economic development characteristic dimensions; The sub-model construction unit is used for constructing a driving contribution judgment sub-model and a model system of influence of each characteristic dimension on the development state of the rural area under the six-dimensional characteristic index system; the submodel integration unit is used for integrating the six driving contribution judgment submodels of the characteristic dimensions and establishing a six-dimensional comprehensive measure model of the development state of the rural area region; The space-time simulation unit is used for realizing space-time simulation of the multi-source heterogeneous characteristic data corresponding to each characteristic dimension in a target research period of a target research region by using a high-precision curved surface modeling method and a GIS space-time analysis method to obtain six-dimensional characteristic space-time simulation data; The measurement result acquisition unit is used for generating a system measurement result of the rural area development state of the target research area in the target research period based on the six-dimensional characteristic space-time simulation data by adopting a six-dimensional comprehensive measurement model, wherein the system measurement result comprises six-dimensional characteristic contribution measurement, development process and state identification calculation.
  12. 12. A computer storage medium storing a plurality of instructions adapted to be loaded by a processor and to perform the method steps of any one of claims 1 to 10.

Description

Comprehensive measurement method, device and storage medium for rural area development state Technical Field The present application relates to the field of computer technology and rural development technology, and more particularly, to a comprehensive measure method, apparatus and storage medium for a rural regional development status in the field of computer technology. Background The measure of the development state of the rural area is always a hotspot problem of the research of the humane geography and regional economy, is helpful for optimizing land space planning, guiding infrastructure, public service and industrial layout to match with regional characteristics, activates the endophytic development kinetic energy, measures the development state of the regional by single indexes such as economic indexes, ecological indexes and the like in the prior art, but the development process of the rural area is a space-time dynamic complex process which is jointly driven and mutually coupled by natural climate, regional environment, social economic development and the like in the rural area and is presented in the rural area space, and the method for improving the accuracy and convenience of the measure of the development state of the rural area is required to be provided. Disclosure of Invention The embodiment of the application provides a comprehensive measure method, a comprehensive measure device and a comprehensive measure storage medium for a rural area development state, which can comprehensively measure the rural area development state by combining data under multiple characteristic dimensions of a target research area, avoid limitation of a measure result under a single dimension, realize systematic quantitative calculation of the rural area development state and improve accuracy of the measure result. In a first aspect, an embodiment of the present application provides a comprehensive measure method for a development state of a rural area, where the method includes: A multi-level fuzzy comprehensive evaluation model is adopted to construct a six-dimensional characteristic index system for measuring the development state of a rural area, wherein characteristic dimensions in the six-dimensional characteristic index system comprise natural climate characteristic dimensions, regional environment characteristic dimensions, traffic facility characteristic dimensions, urban and rural associated characteristic dimensions, resource endowment characteristic dimensions and economic development characteristic dimensions; establishing a driving contribution judgment sub-model and a model system of influence of each characteristic dimension on the development state of the rural area under the six-dimensional characteristic index system; Integrating the six driving contribution judgment sub-models of the characteristic dimensions, and establishing a six-dimensional comprehensive measure model of the development state of the rural area region; The high-precision curved surface modeling method and the GIS space-time analysis method are used for realizing space-time simulation of multi-source heterogeneous characteristic data corresponding to each characteristic dimension in a target research period of a target research region, so as to obtain six-dimensional characteristic space-time simulation data; And generating a system measurement result of the development state of the rural area in the target research period by adopting a six-dimensional comprehensive measurement model based on the six-dimensional characteristic space-time simulation data, wherein the system measurement result comprises six-dimensional characteristic contribution measurement, development process and state identification calculation. In a second aspect, an embodiment of the present application provides a comprehensive measure device for a development status of a rural area, where the device includes: the six-dimensional system construction unit is used for constructing a six-dimensional characteristic index system for measuring the development state of a rural area by adopting a multi-level fuzzy comprehensive evaluation model, wherein characteristic dimensions in the six-dimensional characteristic index system comprise natural climate characteristic dimensions, regional environment characteristic dimensions, traffic facility characteristic dimensions, urban and rural associated characteristic dimensions, resource endowment characteristic dimensions and economic development characteristic dimensions; The sub-model construction unit is used for constructing a driving contribution judgment sub-model and a model system of influence of each characteristic dimension on the development state of the rural area under the six-dimensional characteristic index system; the submodel integration unit is used for integrating the six driving contribution judgment submodels of the characteristic dimensions and establishing a six-dimensional comprehensive measure