CN113516387B - Regional ecological security pattern construction method and system based on geographic space big data - Google Patents
Regional ecological security pattern construction method and system based on geographic space big data Download PDFInfo
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Abstract
The invention discloses a regional ecological security pattern construction method and a system based on geographic space big data, wherein the method comprises the following steps: determining the relationship between a plurality of environment variables in a research area and a preset safety pattern, obtaining ecological environment space big data of the research area, calculating the weight value of each environment variable in the ecological environment space big data based on the relationship between the plurality of environment variables in the research area and the preset safety pattern, constructing a safety pattern prediction model according to the weight value of each environment variable, obtaining a plurality of ecological indexes in the research area, constructing a plurality of target safety pattern models of the research area according to the plurality of ecological indexes and the safety pattern prediction model, and outputting corresponding safety pattern distribution diagrams by using each target safety pattern model. The safety pattern distribution maps corresponding to different ecological indexes can be obtained by researchers according to different safety pattern models, and experience of the researchers is felt.
Description
Technical Field
The invention relates to the technical field of construction of regional ecological security patterns, in particular to a regional ecological security pattern construction method and system based on geographic space big data.
Background
The human activities are changing the evolution process of the nature continuously since the 20 th century, the resource environment is broken and the ecological safety problem is aggravated continuously, and the political, social and economic safety of the country or the region is threatened, so that the proportion of the conflict and the friction between the country or the region is increased day by day, and the human activities become a great hidden danger influencing the global safety. The emergence of global and regional ecological safety problems has become a turning point for the evolution of the whole human being towards ecological civilization. Ecological safety is the most basic safety requirement for human survival and development, not only provides a priority task for ecological civilization construction, but also is an important basis for ecological civilization construction and sustainable development.
In recent years, relevant research at home and abroad mainly takes landscape pattern optimization, land utilization structure optimization, ecological sensitivity, ecological system service value, ecological system bearing capacity/ecological footprint evaluation, sustainable land resource utilization and the like as entry points, and attaches importance to qualitative explanation of regional ecological processes and internal relationship characteristics. In the aspect of the ecological safety pattern simulation technology, researchers with different knowledge backgrounds propose a plurality of model construction methods from respective understanding of ecological safety patterns, but a single model often lacks the explaining capability of complex ecological processes, and is not beneficial to comprehensively and objectively constructing the ecological safety patterns. From the development trend, the construction of the regional ecological security pattern is developed from digital, static and planar to a space, multidimensional and dynamic model, and the simulation and construction of the ecological security pattern based on geographic space-time big data are the development trend in the future from the pure consideration of the focus problem requirements to the comprehensive consideration of various correlation relations and requirements. The existing construction method of the ecological safety pattern is to use ecological safety indexes in a research area as quantification and simply use environment variables in the research area as variables to construct the ecological safety pattern, but the ecological safety pattern constructed by the method is a unified ecological safety pattern in the research area, cannot visually determine the ecological safety pattern corresponding to each ecological index, increases the difficulty for research workers in the research area, and seriously affects the experience of the researches.
Disclosure of Invention
Aiming at the displayed problems, the invention provides a regional ecological safety pattern construction method and a regional ecological safety pattern construction system based on geographic space big data, which are used for solving the problems that an ecological safety pattern corresponding to each ecological index cannot be visually determined in the background technology, the difficulty is increased for research workers in a research region, and the experience of the researchers is seriously influenced.
A regional ecological security pattern construction method based on geographic space big data comprises the following steps:
determining a relationship between a plurality of environmental variables in a research area and a preset safety pattern;
acquiring ecological environment space big data of the research area, and calculating the weight value of each environment variable in the ecological environment space big data based on the relationship between a plurality of environment variables in the research area and a preset safety pattern;
constructing a safety pattern prediction model according to the weight value of each environment variable;
acquiring a plurality of ecological indexes in the research area, and constructing a plurality of target safety pattern models of the research area by utilizing the safety pattern prediction model according to the plurality of ecological indexes;
and outputting the corresponding safety pattern distribution diagram by utilizing each target safety pattern model.
Preferably, the plurality of target security pattern models includes: the system comprises a land resource safety pattern model, a water resource safety pattern model, a biological resource safety pattern model, an ecological landscape structure safety model, a flood safety pattern model, a water and soil loss and geological disaster safety pattern model.
Preferably, the determining the relationship between the plurality of environment variables in the research area and the preset safety pattern comprises:
acquiring an ecosystem structure in the research area;
determining an ecological safety index system in the research area according to the ecological system structure;
acquiring a plurality of environment variables with the influence degree on the ecological safety index system more than or equal to a preset threshold value;
and determining the attribute value of each environment variable, and training a preset model corresponding to the preset safety pattern by using the attribute value corresponding to each environment variable to obtain the relationship between each environment variable and the preset safety pattern.
Preferably, the step of acquiring the ecological environment space big data of the research area comprises:
calling target data related to the ecological environment of the research area from a preset database;
cleaning and sorting the target data to obtain processed target data, and constructing an index of the processed target data;
extracting the geographical position information of the research area, and generating an index factor according to the geographical position information;
and acquiring ecological environment space big data of the research area from the processed target data by using the matching factor.
Preferably, the constructing a safety pattern prediction model according to the weight values of the environmental variables includes:
inputting the weight values of the environmental variables into a preset GIS to obtain a target grid;
training a preset regression model by using the target grid as training data to obtain a trained regression model;
performing performance detection on the trained regression model to obtain a detection result;
and confirming whether the detection result is qualified, if so, confirming the trained regression model as the safety pattern prediction model, otherwise, performing secondary training on the trained regression model again until the performance detection result is qualified.
Preferably, the method further comprises:
analyzing the ecological damage condition in the research area according to the safety pattern distribution diagram corresponding to the plurality of ecological indexes;
generating a corresponding first suggested ecological restoration scheme according to the ecological damage condition;
evaluating a utility index of the first proposed ecological remediation plan for a study area;
and confirming whether the practicability index is larger than or equal to a preset index, if so, uploading the first suggested ecological restoration scheme to a terminal where a worker is located, otherwise, regenerating a second suggested ecological restoration scheme for evaluation until the evaluation is passed, and uploading the second suggested ecological restoration scheme which is passed through the evaluation to the terminal.
Preferably, the step of cleansing the target data includes:
acquiring respective proportions of water resources, biological resources and land resources in a research area and respective corresponding parameters of each landscape;
generating characteristic marks of the research area according to respective proportions of water resources, biological resources and land resources in the research area and respective corresponding parameters of each landscape;
generating a dynamic label according to the feature identifier, and acquiring a data association rule and a data characteristic factor of the dynamic label in a research area;
taking the data association rule and the data characteristic factor as a first cleaning strategy;
performing primary cleaning on the target data by using the first cleaning strategy to obtain cleaned first data;
establishing joint probability distribution related to the pollution degree and the utilization rate of a research area;
dividing a value range in the joint probability into a plurality of probability intervals, and acquiring a target value range of each probability interval;
taking a plurality of target value ranges as a second cleaning strategy;
performing secondary cleaning on the first data by using the second cleaning strategy to obtain second data in the multiple probability intervals in the first data;
and confirming the second data as the cleaned target data.
A regional ecological security pattern construction system based on geospatial big data comprises:
the system comprises a determining module, a judging module and a judging module, wherein the determining module is used for determining the relation between a plurality of environment variables in a research area and a preset safety pattern;
the calculation module is used for acquiring the ecological environment space big data of the research area, and calculating the weight value of each environment variable in the ecological environment space big data based on the relationship between a plurality of environment variables in the research area and a preset safety pattern;
the first construction module is used for constructing a safety pattern prediction model according to the weight values of the environment variables;
the second construction module is used for acquiring a plurality of ecological indexes in the research area and constructing a plurality of target safety pattern models of the research area by utilizing the safety pattern prediction model according to the plurality of ecological indexes;
and the output module is used for outputting the corresponding safety pattern distribution diagram by utilizing each target safety pattern model.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and drawings.
The technical solution of the present invention is further described in detail by the accompanying drawings and embodiments.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention and not to limit the invention.
FIG. 1 is a flowchart of a method for constructing a regional ecological security pattern based on geospatial big data according to the present invention;
FIG. 2 is another work flow diagram of a regional ecological security pattern construction method based on geospatial big data according to the present invention;
FIG. 3 is a flowchart of another operation of a method for constructing a regional ecological security pattern based on geospatial big data according to the present invention;
fig. 4 is a schematic structural diagram of a regional ecological security pattern construction system based on geospatial big data provided by the present invention.
Detailed Description
Reference will now be made in detail to the exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, like numbers in different drawings represent the same or similar elements unless otherwise indicated. The implementations described in the exemplary embodiments below are not intended to represent all implementations consistent with the present disclosure. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present disclosure, as detailed in the appended claims.
The human activities are changing the evolution process of the nature continuously since the 20 th century, the resource environment is broken and the ecological safety problem is aggravated continuously, and the political, social and economic safety of the country or the region is threatened, so that the proportion of the conflict and the friction between the country or the region is increased day by day, and the human activities become a great hidden danger influencing the global safety. The emergence of global and regional ecological safety problems has become a turning point for the evolution of the whole human being towards ecological civilization. Ecological safety is the most basic safety requirement for human survival and development, not only provides a priority task for ecological civilization construction, but also is an important basis for ecological civilization construction and sustainable development.
In recent years, relevant research at home and abroad mainly takes landscape pattern optimization, land utilization structure optimization, ecological sensitivity, ecological system service value, ecological system bearing capacity/ecological footprint evaluation, sustainable land resource utilization and the like as entry points, and attaches importance to qualitative explanation of regional ecological processes and internal relationship characteristics. In the aspect of the ecological safety pattern simulation technology, researchers with different knowledge backgrounds propose a plurality of model construction methods from respective understanding of ecological safety patterns, but a single model often lacks the explaining capability of complex ecological processes, and is not beneficial to comprehensively and objectively constructing the ecological safety patterns. From the development trend, the construction of the regional ecological security pattern is developed from digital, static and planar to a space, multidimensional and dynamic model, and the simulation and construction of the ecological security pattern based on geographic space-time big data are the development trend in the future from the pure consideration of the focus problem requirements to the comprehensive consideration of various correlation relations and requirements. The existing construction method of the ecological safety pattern is to use ecological safety indexes in a research area as quantification and simply use environment variables in the research area as variables to construct the ecological safety pattern, but the ecological safety pattern constructed by the method is a unified ecological safety pattern in the research area, cannot visually determine the ecological safety pattern corresponding to each ecological index, increases the difficulty for research workers in the research area, and seriously affects the experience of the researches. In order to solve the above problems, the embodiment discloses a regional ecological security pattern construction method based on geospatial big data.
A regional ecological security pattern construction method based on geographic space big data is disclosed, as shown in FIG. 1, and comprises the following steps:
s101, determining the relationship between a plurality of environment variables in a research area and a preset safety pattern;
step S102, acquiring ecological environment space big data of the research area, and calculating the weight value of each environment variable in the ecological environment space big data based on the relationship between a plurality of environment variables in the research area and a preset safety pattern;
s103, constructing a safety pattern prediction model according to the weight values of the environmental variables;
step S104, acquiring a plurality of ecological indexes in the research area, and constructing a plurality of target safety pattern models of the research area according to the plurality of ecological indexes by using the safety pattern prediction model;
and S105, outputting the corresponding safety pattern distribution diagram by using each target safety pattern model.
The working principle of the technical scheme is as follows: determining the relationship between a plurality of environment variables in a research area and a preset safety pattern, obtaining ecological environment space big data of the research area, calculating the weight value of each environment variable in the ecological environment space big data based on the relationship between the plurality of environment variables in the research area and the preset safety pattern, constructing a safety pattern prediction model according to the weight value of each environment variable, obtaining a plurality of ecological indexes in the research area, constructing a plurality of target safety pattern models of the research area according to the plurality of ecological indexes and the safety pattern prediction model, and outputting corresponding safety pattern distribution diagrams by using each target safety pattern model.
The beneficial effects of the above technical scheme are: the weighted values of all environment variables in the research area are used as the quantification, and meanwhile, a plurality of safety pattern models based on different ecological indexes in the research area are constructed by taking a plurality of ecological indexes in the research area as variables, so that researchers can obtain safety pattern distribution diagrams corresponding to different ecological indexes according to different safety pattern models, further more detailed and complete research work can be carried out on the research area, the experience feeling of the researchers and the practicability of the constructed safety pattern distribution diagrams are improved, the problems that the ecological safety pattern diagrams corresponding to all the ecological indexes cannot be visually determined in the prior art, and the difficulty of the researchers for the research work in the research area is increased are solved.
In one embodiment, the plurality of target security pattern models comprises: the system comprises a land resource safety pattern model, a water resource safety pattern model, a biological resource safety pattern model, an ecological landscape structure safety model, a flood safety pattern model, a water and soil loss and geological disaster safety pattern model.
The beneficial effects of the above technical scheme are: the method can lead researchers to select the safety pattern model required by the researchers according to the actual research needs, and can also determine the damage condition and the functionality of a plurality of resources and landscapes in the research area through the plurality of models, thereby further improving the practicability.
In one embodiment, as shown in FIG. 2, the determining a relationship between a plurality of environmental variables within the area of interest and the preset safety profile comprises:
step S201, acquiring an ecosystem structure in the research area;
step S202, determining an ecological safety index system in the research area according to the ecological system structure;
step S203, acquiring a plurality of environment variables with the influence degree on the ecological safety index system being greater than or equal to a preset threshold value;
and S204, determining the attribute value of each environment variable, training a preset model corresponding to a preset safety pattern by using the attribute value corresponding to each environment variable, and obtaining the relation between each environment variable and the preset safety pattern.
The beneficial effects of the above technical scheme are: the environment variables which can be selected for use according to the ecological safety situation of the research area can be determined according to the ecological safety index system in the research area, a data basis is provided for the subsequent construction of the safety pattern model, the accuracy of the model is guaranteed, furthermore, the preset model corresponding to the preset safety pattern is trained by utilizing the attribute value corresponding to each environment variable, and the relationship between each environment variable and the preset safety pattern is obtained, so that the final relationship between each environment variable and the preset safety pattern is more objective and practical.
In one embodiment, as shown in fig. 3, the step of acquiring the ecological environment space big data of the research area comprises:
s301, calling target data related to the ecological environment of the research area from a preset database;
step S302, cleaning and sorting the target data to obtain processed target data, and constructing an index of the processed target data;
step S303, extracting the geographical position information of the research area, and generating an index factor according to the geographical position information;
and S304, acquiring ecological environment space big data of the research area from the processed target data by using the matching factors.
The beneficial effects of the above technical scheme are: therefore, the finally obtained ecological environment space big data conforms to the research area from the position information or the content information, the accuracy of the data is guaranteed, the data corresponding to the research area is not required to be called by a researcher in large-scale target data, the experience of the researcher is further improved, and the working efficiency is improved.
In one embodiment, the building a safety pattern prediction model according to the weight values of the environment variables includes:
inputting the weight values of the environmental variables into a preset GIS to obtain a target grid;
training a preset regression model by using the target grid as training data to obtain a trained regression model;
performing performance detection on the trained regression model to obtain a detection result;
and confirming whether the detection result is qualified, if so, confirming the trained regression model as the safety pattern prediction model, otherwise, performing secondary training on the trained regression model again until the performance detection result is qualified.
The beneficial effects of the above technical scheme are: the environment variables can be used as quantification to construct a safety pattern detection model more accurately by inputting the weighted values of all the environment variables into a preset GIS to obtain a target grid, and further, the output result of the constructed safety pattern detection model is ensured to be in line with expectation by detecting the performance of the trained regression model, so that the accuracy of model output is improved.
In one embodiment, the method further comprises:
analyzing the ecological damage condition in the research area according to the safety pattern distribution diagram corresponding to the plurality of ecological indexes;
generating a corresponding first suggested ecological restoration scheme according to the ecological damage condition;
evaluating a utility index of the first proposed ecological remediation plan for a study area;
and confirming whether the practicability index is larger than or equal to a preset index, if so, uploading the first suggested ecological restoration scheme to a terminal where a worker is located, otherwise, regenerating a second suggested ecological restoration scheme for evaluation until the evaluation is passed, and uploading the second suggested ecological restoration scheme which is passed through the evaluation to the terminal.
The beneficial effects of the above technical scheme are: the corresponding solution can be intelligently generated according to the ecological damage condition in the research area by generating the first suggested ecological restoration scheme, the analysis of big data is combined to ensure that the generated first suggested ecological restoration scheme meets the requirement of the research area, and further, whether the first suggested ecological restoration scheme meets the actual condition of the research area or not can be effectively determined by carrying out the practicability evaluation on the first suggested ecological restoration scheme, so that the waste of restoration cost is avoided, and the practicability is further improved.
In one embodiment, the step of cleansing the target data comprises:
acquiring respective proportions of water resources, biological resources and land resources in a research area and respective corresponding parameters of each landscape;
generating characteristic marks of the research area according to respective proportions of water resources, biological resources and land resources in the research area and respective corresponding parameters of each landscape;
generating a dynamic label according to the feature identifier, and acquiring a data association rule and a data characteristic factor of the dynamic label in a research area;
taking the data association rule and the data characteristic factor as a first cleaning strategy;
performing primary cleaning on the target data by using the first cleaning strategy to obtain cleaned first data;
establishing joint probability distribution related to the pollution degree and the utilization rate of a research area;
dividing a value range in the joint probability into a plurality of probability intervals, and acquiring a target value range of each probability interval;
taking a plurality of target value ranges as a second cleaning strategy;
performing secondary cleaning on the first data by using the second cleaning strategy to obtain second data in the multiple probability intervals in the first data;
and confirming the second data as the cleaned target data.
The beneficial effects of the above technical scheme are: the target data can be preliminarily screened to obtain the matched first data by utilizing the parameters in the research area to generate the first cleaning strategy, useless data can be rapidly eliminated, the working efficiency is improved, further, the first data can be secondarily cleaned by constructing joint probability distribution of the pollution degree and the utilization rate of the research area, more precise screening can be carried out aiming at the real-time pollution degree and the utilization rate in the research area to obtain second data, the final second data is ensured to be in accordance with the actual condition of the research area, and the accuracy of the data is ensured.
In one embodiment, the evaluating the utility index of the first suggested ecological remediation plan for a research area includes:
analyzing the first suggested ecological restoration scheme to obtain a plurality of corresponding operation instructions;
acquiring a target operation index weight of each operation instruction in a preset operation index weight range;
calculating the operability of the first suggested ecological restoration scheme according to the target operation index weight of each operation instruction within a preset operation index weight range:
wherein k is represented as the operability of the first proposed eco-remediation scheme, N is represented as the number of operation instructions, SiTarget operation index weight, M, expressed as ith operation instructioniAn index value expressed as a target operation index weight of the ith operation instruction, q expressed as a desired average operation index weight, BiExpressed as the cost required for the ith operation instruction, B1Expressed as the desired total cost of repair, QiA difficulty factor expressed as the execution of the ith operation instruction;
obtaining a current health degree in a research area;
calculating the comprehensive ecological system health degree index of the research area according to the current health degree in the research area:
wherein F is the comprehensive index of the health degree of the ecological system of the research area, D is the current health degree in the research area, A is the regional environment in the research area, and mu1Expressed as the weight value of the regional environment in the research region, b is expressed as the plant growth in the research region, mu2Expressed as the weight value occupied by the growth of the plants in the research area, C is expressed as the disaster index in the research area, mu3Expressed as the weighted value of the disaster index in the research area, M is the number of ecological indexes in the research area, UjThe deviation degree of the current index value expressed as the jth ecological index and the preset index value;
calculating the practical index of the first suggested ecological restoration scheme to the research area according to the comprehensive index of the ecological system health degree of the research area and the operability of the first suggested ecological restoration scheme:
h represents the practical index of the first suggested ecological restoration scheme to the research area, e represents a natural constant with the value of 2.72 and ViExpressed as the area of utilization of the ith operating instruction, G is expressed as the ecosystem elasticity coefficient in the research area, XiExpressed as the desired ecosystem recovery coefficient, V, for the area under study for the ith operating instruction1Expressed as the floor space of the study area and Z as the self ecosystem restoration factor of the study area.
The beneficial effects of the above technical scheme are: whether the first suggested ecological restoration scheme accords with the research area can be evaluated according to the operability by calculating the operability of the first suggested ecological restoration scheme, whether the first suggested ecological restoration scheme is feasible can be preliminarily evaluated, further, the damage condition in the research area can be effectively determined by calculating the comprehensive index of the ecological system health degree of the research area, further, a basis is provided for the follow-up calculation of the first suggested ecological restoration scheme on the research area, and the accuracy of the calculation result is guaranteed.
In one embodiment, the method further comprises:
dividing the plan of the research area into a preset number of grids;
determining the habitat degradation degree of each grid;
calculating the habitat quality of the research area according to the habitat degradation degree of each grid:
wherein P represents the habitat quality of the research area, a represents the preset habitat suitability in the research area, L represents the number of the division grids, EzExpressed as the degree of habitat degradation in the z-th grid, δ is expressed as a half-saturation constant;
determining the surface runoff coefficient of the research area, counting the rainfall of the research area during each rainfall, and calculating the average rainfall during rainfall in the research area according to the counted rainfall;
calculating the average surface runoff of the research area during rainfall according to the average rainfall and the surface runoff coefficient in the research area;
calculating the water and soil loss vulnerability index in the research area according to the average surface runoff of the research area during rainfall and the habitat quality of the research area:
wherein R is expressed as a soil erosion vulnerability index in the research area, g is expressed as an average surface runoff of the research area during rainfall, c is expressed as an average rainfall in the research area during rainfall, alpha is expressed as a rainfall erosion force factor in the research area, beta is expressed as a soil erodibility factor in the research area, phi is expressed as a topographic relief factor in the target area, and omega is expressed as a vegetation coverage factor in the research area;
and generating an environmental quality report in the research area according to the water and soil loss vulnerability index and each safety pattern distribution map in the research area.
The beneficial effects of the above technical scheme are: the environment damage condition in the research area can be effectively evaluated by calculating the habitat quality in the research area, further, an environment quality report under the influence of the water and soil loss vulnerability index can be quickly evaluated by calculating the water and soil loss vulnerability index in the research area in combination with each safety pattern distribution diagram, the environment quality report is automatically generated for researchers, the intellectualization is improved, meanwhile, the researchers can also generate solving measures according to the environment quality report, and the working efficiency is improved.
The embodiment also discloses a regional ecological security pattern construction system based on geographic space big data, as shown in fig. 4, the system includes:
a determining module 401, configured to determine a relationship between a plurality of environment variables in a research area and a preset security pattern;
a calculating module 402, configured to obtain the ecological environment space big data of the research area, and calculate a weight value of each environment variable in the ecological environment space big data based on a relationship between a plurality of environment variables in the research area and a preset safety pattern;
a first constructing module 403, configured to construct a safety pattern prediction model according to the weight values of the environmental variables;
a second constructing module 404, configured to obtain a plurality of ecological indexes in the research area, and construct a plurality of target security pattern models of the research area according to the plurality of ecological indexes by using the security pattern prediction model;
an output module 405, configured to output the security pattern distribution map corresponding to each target security pattern model.
The working principle and the advantageous effects of the above technical solution have been explained in the method claims, and are not described herein again.
It will be understood by those skilled in the art that the first and second terms of the present invention refer to different stages of application.
Other embodiments of the disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the disclosure disclosed herein. This application is intended to cover any variations, uses, or adaptations of the disclosure following, in general, the principles of the disclosure and including such departures from the present disclosure as come within known or customary practice within the art to which the disclosure pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the disclosure being indicated by the following claims.
It will be understood that the present disclosure is not limited to the precise arrangements described above and shown in the drawings and that various modifications and changes may be made without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.
Claims (7)
1. A regional ecological security pattern construction method based on geographic space big data is characterized by comprising the following steps:
determining a relationship between a plurality of environmental variables in a research area and a preset safety pattern;
acquiring ecological environment space big data of the research area, and calculating the weight value of each environment variable in the ecological environment space big data based on the relationship between a plurality of environment variables in the research area and a preset safety pattern;
constructing a safety pattern prediction model according to the weight value of each environment variable;
acquiring a plurality of ecological indexes in the research area, and constructing a plurality of target safety pattern models of the research area by utilizing the safety pattern prediction model according to the plurality of ecological indexes;
outputting a corresponding safety pattern distribution diagram by using each target safety pattern model;
the method further comprises the following steps:
analyzing the ecological damage condition in the research area according to the safety pattern distribution diagram corresponding to the plurality of ecological indexes;
generating a corresponding first suggested ecological restoration scheme according to the ecological damage condition;
evaluating a utility index of the first proposed ecological remediation plan for a study area;
confirming whether the practicability index is larger than or equal to a preset index, if so, uploading the first suggested ecological restoration scheme to a terminal where a worker is located, otherwise, regenerating a second suggested ecological restoration scheme for evaluation until the evaluation is passed, and uploading the second suggested ecological restoration scheme which is passed through the evaluation to the terminal;
the evaluating a utility index of the first proposed ecological remediation plan for a research area, comprising:
analyzing the first suggested ecological restoration scheme to obtain a plurality of corresponding operation instructions;
acquiring a target operation index weight of each operation instruction in a preset operation index weight range;
calculating the operability of the first suggested ecological restoration scheme according to the target operation index weight of each operation instruction within a preset operation index weight range:
wherein k represents the operability of the first proposed ecological restoration scheme,
expressed as a number of operational instructions,
target operation expressed as ith operation instructionAs the weight of the index,
an index value expressed as a target operation index weight of the ith operation instruction,
expressed as a desired average operation index weight,
expressed as the cost required for the ith operation instruction,
expressed as a desired total cost of the repair,
a difficulty factor expressed as the execution of the ith operation instruction;
obtaining a current health degree in a research area;
calculating the comprehensive ecological system health degree index of the research area according to the current health degree in the research area:
wherein F is expressed as a comprehensive index of the health degree of the ecological system in the research area, D is expressed as the current health degree in the research area,
represented as the regional environment within the area of interest,
expressed as a weighted value of the area environment within the study area,
expressed as the growth vigour of the plants in the area under investigation,
expressed as the weight value occupied by the growth vigor of plants in the research area, C is expressed as the disaster index in the research area,
expressed as a weighted value of the disaster indicators within the investigation region,
expressed as the number of ecological indicators in the area under study,
the deviation degree of the current index value expressed as the jth ecological index and the preset index value;
calculating the practical index of the first suggested ecological restoration scheme to the research area according to the comprehensive index of the ecological system health degree of the research area and the operability of the first suggested ecological restoration scheme:
wherein H is expressed as the practical index of the first suggested ecological restoration scheme to the research area, e is expressed as a natural constant with the value of 2.72,
expressed as the area utilized by the ith operation instruction,
expressed as the ecosystem elastic coefficient in the area under investigation,
denoted as the ith operation fingerWith the desired ecosystem restoration coefficient for the area under study,
expressed as the footprint of the area under investigation,
expressed as the self ecosystem restoration factor of the study area.
2. The method according to claim 1, wherein the plurality of target security pattern models comprise: the system comprises a land resource safety pattern model, a water resource safety pattern model, a biological resource safety pattern model, an ecological landscape structure safety model, a flood safety pattern model, a water and soil loss and geological disaster safety pattern model.
3. The method for constructing the geospatial big data-based regional ecological security pattern according to claim 1, wherein the determining the relationship between the plurality of environment variables in the research region and the preset security pattern comprises:
acquiring an ecosystem structure in the research area;
determining an ecological safety index system in the research area according to the ecological system structure;
acquiring a plurality of environment variables with the influence degree on the ecological safety index system more than or equal to a preset threshold value;
and determining the attribute value of each environment variable, and training a preset model corresponding to the preset safety pattern by using the attribute value corresponding to each environment variable to obtain the relationship between each environment variable and the preset safety pattern.
4. The method for constructing the regional ecological security pattern based on the geospatial big data according to claim 1, wherein the step of obtaining the ecological environment space big data of the research region comprises:
calling target data related to the ecological environment of the research area from a preset database;
cleaning and sorting the target data to obtain processed target data, and constructing an index of the processed target data;
extracting the geographical position information of the research area, and generating an index factor according to the geographical position information;
and acquiring ecological environment space big data of the research area from the processed target data by using the index factor.
5. The method for constructing the regional ecological security pattern based on the geospatial big data according to claim 1, wherein the constructing a security pattern prediction model according to the weight values of the environment variables comprises:
inputting the weight values of the environmental variables into a preset GIS to obtain a target grid;
training a preset regression model by using the target grid as training data to obtain a trained regression model;
performing performance detection on the trained regression model to obtain a detection result;
and confirming whether the detection result is qualified, if so, confirming the trained regression model as the safety pattern prediction model, otherwise, performing secondary training on the trained regression model again until the performance detection result is qualified.
6. The method for constructing the regional ecological security pattern based on the geospatial big data as claimed in claim 4, wherein the step of cleaning the target data comprises the following steps:
acquiring respective proportions of water resources, biological resources and land resources in a research area and respective corresponding parameters of each landscape;
generating characteristic marks of the research area according to respective proportions of water resources, biological resources and land resources in the research area and respective corresponding parameters of each landscape;
generating a dynamic label according to the feature identifier, and acquiring a data association rule and a data characteristic factor of the dynamic label in a research area;
taking the data association rule and the data characteristic factor as a first cleaning strategy;
performing primary cleaning on the target data by using the first cleaning strategy to obtain cleaned first data;
establishing joint probability distribution related to the pollution degree and the utilization rate of a research area;
dividing a value range in the joint probability into a plurality of probability intervals, and acquiring a target value range of each probability interval;
taking a plurality of target value ranges as a second cleaning strategy;
performing secondary cleaning on the first data by using the second cleaning strategy to obtain second data in the multiple probability intervals in the first data;
and confirming the second data as the cleaned target data.
7. A regional ecological security pattern construction system based on geospatial big data is characterized by comprising:
the system comprises a determining module, a judging module and a judging module, wherein the determining module is used for determining the relation between a plurality of environment variables in a research area and a preset safety pattern;
the calculation module is used for acquiring the ecological environment space big data of the research area, and calculating the weight value of each environment variable in the ecological environment space big data based on the relationship between a plurality of environment variables in the research area and a preset safety pattern;
the first construction module is used for constructing a safety pattern prediction model according to the weight values of the environment variables;
the second construction module is used for acquiring a plurality of ecological indexes in the research area and constructing a plurality of target safety pattern models of the research area by utilizing the safety pattern prediction model according to the plurality of ecological indexes;
the output module is used for outputting the corresponding safety pattern distribution diagram by utilizing each target safety pattern model;
the system is further configured to:
analyzing the ecological damage condition in the research area according to the safety pattern distribution diagram corresponding to the plurality of ecological indexes;
generating a corresponding first suggested ecological restoration scheme according to the ecological damage condition;
evaluating a utility index of the first proposed ecological remediation plan for a study area;
confirming whether the practicability index is larger than or equal to a preset index, if so, uploading the first suggested ecological restoration scheme to a terminal where a worker is located, otherwise, regenerating a second suggested ecological restoration scheme for evaluation until the evaluation is passed, and uploading the second suggested ecological restoration scheme which is passed through the evaluation to the terminal;
the evaluating a utility index of the first proposed ecological remediation plan for a research area, comprising:
analyzing the first suggested ecological restoration scheme to obtain a plurality of corresponding operation instructions;
acquiring a target operation index weight of each operation instruction in a preset operation index weight range;
calculating the operability of the first suggested ecological restoration scheme according to the target operation index weight of each operation instruction within a preset operation index weight range:
wherein k represents the operability of the first proposed ecological restoration scheme,
expressed as a number of operational instructions,
target operation index expressed as ith operation instructionThe weight of the weight is calculated,
an index value expressed as a target operation index weight of the ith operation instruction,
expressed as a desired average operation index weight,
expressed as the cost required for the ith operation instruction,
expressed as a desired total cost of the repair,
a difficulty factor expressed as the execution of the ith operation instruction;
obtaining a current health degree in a research area;
calculating the comprehensive ecological system health degree index of the research area according to the current health degree in the research area:
wherein F is expressed as a comprehensive index of the health degree of the ecological system in the research area, D is expressed as the current health degree in the research area,
represented as the regional environment within the area of interest,
expressed as a weighted value of the area environment within the study area,
expressed as the growth vigour of the plants in the area under investigation,
expressed as the weight value occupied by the growth vigor of plants in the research area, C is expressed as the disaster index in the research area,
expressed as a weighted value of the disaster indicators within the investigation region,
expressed as the number of ecological indicators in the area under study,
the deviation degree of the current index value expressed as the jth ecological index and the preset index value;
calculating the practical index of the first suggested ecological restoration scheme to the research area according to the comprehensive index of the ecological system health degree of the research area and the operability of the first suggested ecological restoration scheme:
wherein H is expressed as the practical index of the first suggested ecological restoration scheme to the research area, e is expressed as a natural constant with the value of 2.72,
expressed as the area utilized by the ith operation instruction,
expressed as the ecosystem elastic coefficient in the area under investigation,
expressed as the desired ecosystem recovery coefficient for the area under study for the ith operating instruction,
expressed as the footprint of the area under investigation,
expressed as the self ecosystem restoration factor of the study area.
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