CN114862292A - Method and system for measuring and calculating town-level spatial condition data based on geographic information - Google Patents
Method and system for measuring and calculating town-level spatial condition data based on geographic information Download PDFInfo
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Abstract
The utility model provides a village and town level spatial condition data measurement and calculation method and system based on geographic information, which relates to the technical field of spatial condition data measurement and calculation, and the method comprises the following steps: determining a target area to be subjected to spatial condition data measurement and calculation, wherein the target area is a village-level administrative area or a township administrative area; determining indexes for carrying out space condition data measurement and calculation in a target area; acquiring original data of the index; calculating the original data of the index to obtain the data of the index; and calculating the spatial condition data of the target area based on the data of the indexes. The method and the device abandon the complicated acquisition process of economic index data, realize the data statistics of multiple dimensions and multiple indexes, form a comprehensive and standard data processing process, can be suitable for a smaller-scale geographic space, and can be applied to village and town-level administrative areas.
Description
Technical Field
The disclosure relates to the technical field of spatial condition data measurement and calculation, and in particular relates to a method and a system for measuring and calculating town-level spatial condition data based on geographic information.
Background
The spatial condition is used for expressing the quality of data information such as the position and distribution of a spatial entity in the natural world, and has the characteristics of positioning, qualitative, time and spatial relation and the like. Geospatial data is spatial data related to geographical location and is a very important information resource. At present, the adopted geospatial data has the defects of non-specification, non-comprehensiveness, large data volume, single data source, insufficient data fineness and the like, and is not beneficial to the application of the spatial data and the measurement and calculation of the spatial condition data.
In summary, there is still a certain limitation in the measurement and application of spatial condition data.
Disclosure of Invention
In order to solve the above problems in the prior art, the present disclosure aims to provide a method and a system for measuring and calculating spatial condition data of a village and small town, which can solve the problems of single data source, incomprehensiveness, insufficient data fineness, lack of standardized uniform format and calculation mode, and the like, based on geographic information.
In order to achieve the above purpose, the present disclosure adopts the following technical solutions:
the disclosure provides a method for measuring and calculating town-level spatial condition data based on geographic information, which is characterized by comprising the following steps:
s1, determining a target area to be subjected to spatial condition data measurement, wherein the target area is a village-level administrative area or a township administrative area;
s2, determining indexes of the target area for carrying out space condition data measurement;
s3, acquiring original data of the index;
s4, calculating the original data of the index to obtain the data of the index;
and S5, calculating the space condition data of the target area based on the data of the indexes.
Further, the above-mentioned index includes: average elevation, slope proportion above a preset degree, average terrain relief degree and/or Shannon diversity index.
Further, obtaining raw data of the index includes:
acquiring elevation data and geographical national condition monitoring data of the target area;
determining the elevation data as the original data of the average elevation, the original data of the slope proportion above the preset degree and the original data of the average topographic relief;
and determining the geographical national condition monitoring data as the original data of the shannon diversity index.
Further, the calculating the raw data of the index to obtain the data of the index includes:
calculating to obtain an elevation average value of the target area based on the elevation data;
determining the average elevation value as the data of the average elevation;
performing projection coordinate system conversion on the elevation data to obtain elevation data expressed by a projection coordinate system;
acquiring gradient distribution data of the target area by using a gradient percentage method;
extracting data with the gradient greater than a preset degree as target gradient data based on the gradient distribution data;
calculating the area ratio of the area corresponding to the target gradient data relative to the target area as the data of the gradient ratio above the preset degree;
performing neighborhood analysis on the elevation data to obtain pixel-level topographic relief of the target area;
and calculating to obtain the data of the average topographic relief degree of the target area based on the pixel-level topographic relief degree.
Further, the calculating the raw data of the index to obtain the data of the index includes:
counting the number of first-level land types in the geographical national condition monitoring data;
summing the occupied areas corresponding to at least one surface coverage pattern spot of each primary land type to obtain the occupied area corresponding to each primary land type;
and (3) calculating the data of the shannon diversity index by using the following formula:
wherein SHDI is data of Shannon diversity index of target region, P i The occupied area of the ith primary land type in the target area is shown, and a is the number of the primary land types in the target area.
Further, the spatial condition data is calculated by the following formula:
wherein e is s The entropy value of the data for the s-th index,
specific numerical value, W, of data of the s-th index for the t-th village-level administration or the township administration s Is the coefficient of variation corresponding to the s-th index,
is the standard deviation of the data for the s-th index,
is the average of the data for the s-th index,
is the weight of the s-th index, Z ts A weighted comprehensive evaluation matrix corresponding to the s index of the t village-level administrative unit or the township administrative unit, Y ts A normalized matrix, maxZ, corresponding to the s index of the t village-level administrative unit or the township administrative unit ts The maximum value of the row of the weighted comprehensive evaluation matrix corresponding to the s index of the t village level administrative unit or the township administrative unit, minZ ts The method comprises the steps that the weighted comprehensive evaluation matrix is the minimum column value of a weighted comprehensive evaluation matrix corresponding to the s-th index of the t-th village-level administrative unit or the township administrative unit, n is the quantity of the village-level administrative units or the township administrative units in an experimental area, the experimental area is the area of the previous-level administrative units of a target area, m is the quantity of the indexes, and SDI is space condition data of the target area.
The present disclosure also provides a system for measuring and calculating town-level spatial condition data based on geographic information, including:
the region determining module is used for determining a target region to be subjected to spatial condition measurement and calculation, wherein the target region is a village-level administrative region or a township administrative region;
the index determining module is used for determining indexes of the target area for carrying out space condition data measurement and calculation;
the acquisition module is used for acquiring the original data of the index;
the index calculation module is used for calculating the original data of the index to obtain the data of the index;
and the data calculation module is used for calculating the space condition data of the target area based on the data of the indexes.
Further, the above-mentioned index includes: average elevation, slope proportion above a preset degree, average terrain relief degree and/or Shannon diversity index.
Further, obtaining raw data of the index includes:
acquiring elevation data and geographical national condition monitoring data of the target area;
determining the elevation data as the original data of the average elevation, the original data of the slope proportion above the preset degree and the original data of the average topographic relief;
and determining the geographical national condition monitoring data as the original data of the shannon diversity index.
Further, the calculating the raw data of the index to obtain the data of the index includes:
calculating to obtain an elevation average value of the target area based on the elevation data;
determining the average elevation value as the data of the average elevation;
performing projection coordinate system conversion on the elevation data to obtain elevation data expressed by a projection coordinate system;
acquiring gradient distribution data of the target area by using a gradient percentage method;
extracting data with the gradient greater than a preset degree as target gradient data based on the gradient distribution data;
calculating the area ratio of the area corresponding to the target gradient data relative to the target area as the data of the gradient ratio above the preset degree;
performing neighborhood analysis on the elevation data to obtain pixel-level topographic relief of the target area;
and calculating to obtain the data of the average topographic relief degree of the target area based on the pixel-level topographic relief degree.
Further, the calculating the raw data of the index to obtain the data of the index includes:
counting the number of first-level land types in the geographical national condition monitoring data;
summing the occupied areas corresponding to at least one ground surface coverage pattern spot of each primary land type to obtain the occupied area corresponding to each primary land type;
and (3) calculating the data of the shannon diversity index by using the following formula:
wherein SHDI is data of Shannon diversity index of target region, P i The occupied area of the ith primary land type in the target area is shown, and a is the number of the primary land types in the target area.
Further, the spatial condition data is calculated by the following formula:
wherein e is s The entropy value of the data for the s-th index,
specific numerical value, W, of data of the s-th index for the t-th village-level administration or the township administration s Is the coefficient of variation corresponding to the s-th index,
is the s-th fingerThe standard deviation of the subject data is,
is the average of the data of the s-th index,
is the weight of the s-th index, Z ts A weighted comprehensive evaluation matrix corresponding to the s index of the t village-level administrative unit or the township administrative unit, Y ts A normalized matrix, maxZ, corresponding to the s index of the t village-level administrative unit or the township administrative unit ts The maximum value of the row of the weighted comprehensive evaluation matrix corresponding to the s index of the t village level administrative unit or the township administrative unit, minZ ts The evaluation matrix is a weighted comprehensive evaluation matrix column minimum value corresponding to the s index of the t-th village-level administrative unit or the township administrative unit, n is the village-level administrative unit number or the township administrative unit number in an experimental area, the experimental area is an area of the previous village-level administrative unit of the target area, m is the index number, and SDI is space condition data of the target area.
The beneficial effects of the above technical scheme that this disclosure provided include at least:
according to the method and the system for measuring and calculating the spatial condition data of the village and town based on the geographic information, multi-dimensional and multi-index data statistics is realized through multi-source data such as geographic national condition monitoring data and elevation data, and the method and the system can be suitable for geographic spaces with smaller dimensions and can be applied to administrative areas of the village and town. According to the measurement and calculation of the spatial condition data, the complicated acquisition process of economic index data is abandoned, the acquisition and processing process of huge data volume is not needed, a comprehensive and standard data processing process is formed, and the visualization and digitization of the spatial condition are realized.
Drawings
In order to more clearly explain the technical solutions in the embodiments of the present disclosure, the drawings that are needed to be used in the description of the embodiments will be briefly introduced below. Other features, objects, and advantages of the present disclosure will become more apparent upon reading of the following detailed description of non-limiting embodiments thereof, with reference to the accompanying drawings.
Fig. 1 is a flowchart of a method for measuring and calculating town-level spatial condition data based on geographic information according to an embodiment of the present disclosure;
fig. 2 is a diagram of an example of a structure of a system for measuring and calculating spatial condition data at a village and town level based on geographic information according to an embodiment of the present disclosure.
Detailed Description
For a better understanding of the present disclosure, various aspects of the present disclosure will be described in more detail with reference to the accompanying drawings. It should be understood that the detailed description is merely illustrative of exemplary embodiments of the disclosure and is not intended to limit the scope of the disclosure in any way. Like reference numerals refer to like elements throughout the specification. The expression "and/or" includes any and all combinations of one or more of the associated listed items.
In the drawings, the size, dimension, and shape of elements have been slightly adjusted for convenience of explanation. The figures are purely diagrammatic and not drawn to scale. As used herein, the terms "approximately", "about" and the like are used as table-approximating terms and not as table-degree terms, and are intended to account for inherent deviations in measured or calculated values that would be recognized by one of ordinary skill in the art. In addition, in the present disclosure, the order in which the processes of the respective steps are described does not necessarily indicate an order in which the processes occur in actual operation, unless explicitly defined otherwise or can be inferred from the context.
It will be further understood that terms such as "comprising," "including," "having," "including," and/or "containing," when used in this specification, are open-ended and not closed-ended, and specify the presence of stated features, elements, and/or components, but do not preclude the presence or addition of one or more other features, elements, components, and/or groups thereof. Furthermore, when a statement such as "at least one of" appears after a list of listed features, it modifies that entire list of features rather than just individual elements in the list. Furthermore, when describing embodiments of the present disclosure, the use of "may" mean "one or more embodiments of the present disclosure. Also, the term "exemplary" is intended to refer to an example or illustration.
Unless otherwise defined, all terms (including engineering and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure belongs. It will be further understood that terms, such as those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of the relevant art and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein.
It should be noted that the embodiments and features of the embodiments in the present disclosure may be combined with each other without conflict. The present disclosure will be described in detail below with reference to the accompanying drawings in conjunction with embodiments.
Fig. 1 is a flowchart of a method for calculating spatial condition data of a village and town based on geographic information according to an embodiment of the present disclosure, and as shown in fig. 1, the present disclosure provides a method for calculating spatial condition data of a village and town based on geographic information, including the following steps:
s1, determining a target area to be subjected to spatial condition data measurement, wherein the target area is a village-level administrative area or a township administrative area;
s2, determining indexes of the target area for space condition data measurement, wherein the indexes include but are not limited to average elevation, slope proportion above a preset degree, average topographic relief and/or Shannon diversity index;
the average elevation, the gradient proportion above a preset degree, the average terrain relief degree and the aromatic diversity index are indexes representing the terrain complexity of the target area, and specifically, the terrain complexity represents the actual terrain and landform state and distribution of the target area;
s3, acquiring original data of the index;
s4, calculating the original data of the index to obtain the data of the index;
and S4, calculating the space condition data of the target area based on the data of the indexes.
Further, the method for acquiring the original data of the index specifically comprises the following steps:
s31, acquiring elevation (DEM) data, geographical national condition monitoring data and point of interest (POI) data of a target area;
in some embodiments, elevation (DEM) data may be 30m elevation data, obtained over a geospatial data cloud official network; the geographical national condition monitoring data is obtained through a geographical national condition monitoring project of the Natural resources department; point of interest (POI) data is obtained from public map data such as a gold map.
S32, determining the elevation data as the raw data of average elevation, the raw data of gradient proportion more than a preset degree and the raw data of average topographic relief;
the three indexes of average elevation, gradient proportion above a preset degree and average terrain relief are used for representing distribution characteristics of terrain complexity of the target area.
And S33, determining the geographical national condition monitoring data as the original data of the Shannon diversity index.
Further, the method for obtaining the data of the index by calculating the original data of the index specifically comprises the following steps:
s41, calculating the elevation data to obtain average elevation data, including:
s411, calculating to obtain an elevation average value of the target area based on the elevation data;
s412, determining the elevation average value as data of average elevation;
s42, calculating and processing the elevation data to obtain data of gradient proportion more than a preset degree, including:
s421, performing projection coordinate system conversion on the elevation data to obtain elevation data expressed by a projection coordinate system;
in some embodiments, the ArcGIS software may be utilized to convert elevation data of the target area from a geographic coordinate system to a projection coordinate system.
S422, gradient distribution data of the target area are obtained by a gradient percentage method;
specifically, the slope percentage method is calculated using the following formula,
wherein B is gradient distribution data indicating a percentage of an elevation between two points and a horizontal distance between the two points, D is an elevation difference between the two points in the projection coordinate system, and G is a horizontal distance between the two points in the projection coordinate system.
S423, extracting data with the gradient greater than a preset degree as target gradient data based on the gradient distribution data;
s424, calculating the area ratio of the area corresponding to the target gradient data relative to the target area, and taking the area ratio as the gradient ratio data above a preset degree;
in some embodiments, the preset degree may be 16 degrees, and further, the gradient ratio above 16 degrees may be used as an index.
S43, calculating the elevation data to obtain average topographic relief degree data, including:
s431, performing neighborhood analysis on the elevation data to obtain pixel-level topographic relief of the target area;
in some embodiments, the artgis software may be adopted to perform neighborhood analysis on the elevation data, obtain the maximum value and the minimum value in a neighborhood (3 × 3) pixel of the elevation data, calculate a difference value between two grid layers obtained by the neighborhood analysis by using a grid calculator, and obtain a pixel-level topographic relief degree of the target area by subtracting the minimum value of the 3 × 3 neighborhood pixel from the maximum value of the 3 × 3 neighborhood pixel.
And S432, calculating to obtain data of the average topographic relief degree of the target area based on the pixel-level topographic relief degree.
Further, the calculating the original data of the index to obtain the data of the index specifically includes: the method for obtaining the shannon diversity index by calculating and processing the geographic national condition monitoring data comprises the following steps:
step one, counting the number of first-level land types in the geographical national condition monitoring data; wherein, the first-level land types comprise agricultural land, construction land and unused land;
secondly, summing the occupied areas corresponding to at least one ground surface coverage pattern spot of each primary land type to obtain the occupied area corresponding to each primary land type;
in some embodiments, the floor space of each primary land type may be obtained by an ArcGIS field calculator using a Python statement.
Thirdly, calculating to obtain the data of the shannon diversity index by using the following formula:
wherein SHDI is data of Shannon diversity index of target region, P i The occupied area of the ith primary land type in the target area is shown, and a is the number of the primary land types in the target area.
Further, the shannon diversity index is used to characterize the feature distribution of the topographic disruption of the target area.
Further, when the spatial condition data of the target area is calculated, in order to integrate the conditions of the target area, the distribution characteristics of the target area may include, in addition to the terrain complexity, traffic convenience and equipment completeness, wherein the traffic convenience may include, but is not limited to, indexes such as a road density index, an average closest distance to a hospital, an average closest distance to a middle school, and an average closest distance to a sports entertainment facility; the equipment completeness may include, but is not limited to, 3km primary school coverage, 5km station coverage, and 5km highway crossing coverage.
Firstly, determining geographical national condition monitoring data as original data of a road density index; and determining the geographic national condition monitoring data and the interest point data as the original data of the average closest distance to a hospital, the original data of the average closest distance to a middle school, the original data of the average closest distance to a sports entertainment facility, the original data of 3km primary school coverage, the original data of 5km station coverage and the original data of 5km high-speed intersection coverage.
Secondly, the original data of the index is calculated to obtain the data of the index, which specifically comprises the following steps:
the data of the road density index is obtained through calculation and processing of the geographical national condition monitoring data, and the data comprises the following steps:
acquiring three road linear element special image layers based on the geographic national condition monitoring data, acquiring three road data of an urban road (LCTL), a highway (LRDL) and a rural road (LRRL) in a target area, fusing and constructing a road data set of the target area, and acquiring the actual length of a corresponding road or highway;
in some embodiments, the actual length of the corresponding road or highway may be obtained by the ArcGIS field calculator using a Python statement;
the road density index of the target area is calculated according to the following formula,
wherein the content of the first and second substances,
is the coefficient of variation of the road or highway within the target area,
the standard deviation of the length of the road or highway in the target area,
is the average of the length of the roads or highways within the target area,
is the weight of the road or highway in the target area, and RDI is the road density of the target areaDegree index; ard is a normalization coefficient;
is the actual length of the urban road in the target area,
is the actual length of the road in the target area,
is the actual length of the rural road in the target area,
is the administrative area of the target area. Wherein, the length standard deviation of the road or highway and the average of the length of the road or highway are obtained by calculating the actual length of the corresponding road or highway; the numerical value of the normalization coefficient is a calculation result of 100 to the maximum value of the intermediate number, wherein the intermediate number is a calculation result of the sum of the products of the lengths of various roads in the target area and the corresponding weights to the administrative unit area of the target area; here, the road density index is used to represent traffic convenience of the target area;
by way of example, when j is 1,
may be the coefficient of variation of an urban road,
may be the weight of the urban road; when the value of j is 2, the ratio,
it may be the coefficient of variation of the road,
may be the weight of the road; when the value of j is 3, the ratio,
can be the coefficient of variation of rural roads,
may be the weight of the rural road.
The method comprises the following steps of calculating average closest distance data to a hospital, average closest distance data to a middle school and average closest distance data to a sports entertainment facility, 3km primary school coverage data, 5km station coverage data and 5km high-speed intersection coverage data through geographic national condition monitoring data and interest point data, wherein the method comprises the following steps:
acquiring residential community point location data, administrative village point location data and various road linear data in a target area based on geographic national condition monitoring data, fusing the residential community point location data and the administrative village point location data, and eliminating point location data with the same name to obtain residential location bit data in the target area; mutually fusing the road linear data and constructing a road network data set to obtain target area road network data;
calculating the path distances from the residential site positions in the target area to various public service facilities based on the interest point data, the residential site position data and the road network data, thereby screening the shortest path distance from each residential site to the corresponding public service facility, and counting the number of the shortest paths from the residential sites in the target area to the public service facilities, wherein the public service facilities comprise high school, hospital and sports entertainment facilities, the hospital comprises a grade hospital, a special hospital and the like, and the sports entertainment facilities comprise parks, stadiums, swimming pools, gymnasiums, science and technology museums and the like;
in some embodiments, a network analysis tool of the ArcGIS software can be adopted to calculate the path distances from residential site points in a target area to various public service facilities through an OD cost matrix;
calculating an average of shortest paths from the residential property to the public service facility within the target area according to the following formula, wherein the average of the shortest paths from the residential property to the public service facility within the target area is used for representing the acquirability of the public service facility of the target area,
wherein the content of the first and second substances,
is the average of the shortest paths to the public service facilities for the residents in the target area,
the distance of the r shortest path from the residential land to the public service facility, and c is the number of the shortest paths from the residential land to the public service facility in the target area;
establishing a primary school 3km buffer area, a station 5km buffer area and a high-speed intersection 5km buffer area by adopting ArcGIS software based on the data of interest points and the data of residential sites, wherein the stations comprise railway stations and bus stations, the number of residential sites in a target area and the number of residential sites in each buffer area are obtained, the coverage rate of the primary school 3km, the coverage rate of the station 5km and the coverage rate of the high-speed intersection 5km in the target area are calculated according to the following formula, and the coverage rate of the primary school 3km, the coverage rate of the station 5km and the coverage rate of the high-speed intersection 5km in the target area are used for representing the configuration level of infrastructure in the target area,
wherein the content of the first and second substances,
in order to be able to obtain the coverage rate,
k is 1, 2 and 3 for the number of residents in each buffer area,
the number of residents in the target area;
by way of example, when k is 1,
the number of residents in a 3km elementary school buffer in the target area can be calculated,
the coverage rate of the primary school can be 3km in the target area; when the number k is 2, the number k is,
the number of residents in a 5km station buffer area in the target area can be counted,
the coverage rate of a station in a target area can be 5 km; when k is 3, the number of the transition metal atoms is 3,
the number of residents in the 5km cache buffer in the target area can be,
the coverage rate of the high-speed intersection within the target area can be 5 km.
Further, taking the data of the index obtained by calculation as an independent variable, and calculating by adopting an entropy weight variation ideal value model through the following formula to obtain spatial condition data:
wherein e is s The entropy value of the data for the s-th index,
specific numerical value, W, of data of the s-th index for the t-th village-level administration or the township administration s Is the coefficient of variation corresponding to the s-th index,
is the standard deviation of the data for the s-th index,
is the average of the data of the s-th index,
is the weight of the s-th index, Z ts A weighted comprehensive evaluation matrix corresponding to the s index of the t village-level administrative unit or the township administrative unit, Y ts A normalized matrix, maxZ, corresponding to the s index of the t village-level administrative unit or the township administrative unit ts The maximum value of the row of the weighted comprehensive evaluation matrix corresponding to the s index of the t village level administrative unit or the township administrative unit, minZ ts Specifically, when the selected target area is the village-level administrative area, the experimental area is the area of the upper-level administrative unit of the village-level administrative area, when the selected target area is the village-level administrative area, the experimental area is the area of the upper-level administrative unit of the ballast-level administrative area, when the selected target area is the ballast-level administrative area, the experimental area is the area of the upper-level administrative unit of the ballast-level administrative area, m is the number of the indexes, and SDI is the spatial condition data of the target area.
The beneficial effects of the above technical scheme that this disclosure provided include at least:
according to the method for measuring and calculating the village and town-level spatial condition data based on the geographic information, multi-dimensional and multi-index data statistics is achieved through multi-source data such as geographic national condition monitoring data and elevation data. According to the measurement and calculation of the spatial conditions, the complicated acquisition process of economic index data is abandoned, the acquisition and processing process of huge data amount is not needed, a comprehensive and standard data processing process is formed, and the visualization and digitization of the spatial conditions are realized. The space condition obtained through calculation in the method can also be applied to aspects such as space poverty evaluation of the area, transportation of the area and the like.
Fig. 2 is a diagram illustrating a structure example of a system for measuring and calculating spatial condition data at village and town level based on geographic information according to an embodiment of the present disclosure, and as shown in fig. 2, the present disclosure further provides a system for measuring and calculating spatial condition data at village and town level based on geographic information, including:
the region determining module 100 is configured to determine a target region to be subjected to spatial condition measurement, where the target region is a village-level administrative region or a township administrative region;
the index determining module 200 is configured to determine an index for performing spatial condition data measurement and calculation in the target area;
an obtaining module 300, configured to obtain raw data of an index;
the index calculation module 400 is configured to perform calculation processing on raw data of an index to obtain data of the index;
and a data calculation module 500, configured to calculate spatial condition data of the target area based on the data of the index.
Further, the index includes: average elevation, slope proportion above a preset degree, average terrain relief degree and/or Shannon diversity index.
Further, obtaining raw data of the index includes:
acquiring elevation data and geographical national condition monitoring data of a target area;
determining elevation data as original data of average elevation, original data of gradient proportion more than a preset degree and original data of average topographic relief;
and determining the geographical national condition monitoring data as the original data of the shannon diversity index.
Further, the calculating the original data of the index to obtain the data of the index includes:
calculating to obtain an elevation average value of the target area based on the elevation data;
determining the average elevation value as data of average elevation;
performing projection coordinate system conversion on the elevation data to obtain elevation data expressed by a projection coordinate system;
acquiring gradient distribution data of a target area by using a gradient percentage method;
extracting data with the gradient greater than a preset degree as target gradient data based on the gradient distribution data;
calculating the area ratio of the area corresponding to the target gradient data relative to the target area, and taking the area ratio as the gradient ratio data above a preset degree;
performing neighborhood analysis on the elevation data to obtain pixel grade topographic relief of the target area;
and calculating to obtain the data of the average topographic relief degree of the target area based on the pixel-level topographic relief degree.
Further, the calculating the original data of the index to obtain the data of the index includes:
counting the number of first-level land types in the geographical national condition monitoring data;
summing the occupied areas corresponding to at least one ground surface coverage pattern spot of each primary land type to obtain the occupied area corresponding to each primary land type;
and (3) calculating the data of the shannon diversity index by using the following formula:
wherein SHDI is data of Shannon diversity index of target region, P i Is a target areaAnd (4) the floor area of the ith primary land type in the target area, wherein a is the number of the primary land types in the target area.
Further, the spatial condition data is calculated by the following formula:
wherein e is s The entropy value of the data for the s-th index,
specific numerical value, W, of data of the s-th index for the t-th village-level administration or the township administration s Is the coefficient of variation corresponding to the s-th index,
is the standard deviation of the data for the s-th index,
is the average of the data of the s-th index,
is the weight of the s-th index, Z ts For the t village level administrative unitOr weighting comprehensive evaluation matrix, Y, corresponding to the s-th index of the ballast administrative unit ts A normalized matrix, maxZ, corresponding to the s index of the t village-level administrative unit or the township administrative unit ts The maximum value of the row of the weighted comprehensive evaluation matrix corresponding to the s index of the t village level administrative unit or the township administrative unit, minZ ts The evaluation matrix is a weighted comprehensive evaluation matrix column minimum value corresponding to the s index of the t-th village-level administrative unit or the township administrative unit, n is the village-level administrative unit number or the township administrative unit number in an experimental area, the experimental area is an area of the previous village-level administrative unit of the target area, m is the index number, and SDI is space condition data of the target area.
The beneficial effects of the above technical scheme that this disclosure provided include at least:
according to the geographic information-based village and town-level spatial condition data measuring and calculating system, multi-dimensional and multi-index data statistics is achieved through multi-source data such as geographic national condition monitoring data and elevation data, the geographic information-based village and town-level spatial condition data measuring and calculating system can be suitable for geographic spaces with small dimensions, and can be applied to village and town-level administrative areas. According to the measurement and calculation of the spatial conditions, the complicated acquisition process of economic index data is abandoned, the acquisition and processing process of huge data amount is not needed, a comprehensive and standard data processing process is formed, and the visualization and digitization of the spatial conditions are realized. The space condition obtained through calculation in the method can also be applied to aspects such as space poverty evaluation of the area, transportation of the area and the like.
While particular embodiments of the present disclosure have been described in the foregoing specification, the various illustrations do not limit the spirit of the disclosure, and one of ordinary skill in the art, after reading the description, can make modifications and alterations to the particular embodiments described above without departing from the spirit and scope of the disclosure.
Claims (10)
1. A method for measuring and calculating town-level spatial condition data based on geographic information is characterized by comprising the following steps:
s1, determining a target area to be subjected to spatial condition data measurement, wherein the target area is a village-level administrative area or a township administrative area;
s2, determining indexes of the target area for carrying out space condition data measurement;
s3, acquiring original data of the index;
s4, calculating the original data of the index to obtain the data of the index;
and S5, calculating the space condition data of the target area based on the data of the indexes.
2. The method as claimed in claim 1, wherein the index includes: average elevation, slope proportion above a preset degree, average terrain relief degree and/or Shannon diversity index.
3. The method for measuring and calculating town-level spatial condition data based on geographic information as claimed in claim 2, wherein the obtaining of the raw data of the index includes:
acquiring elevation data and geographical national condition monitoring data of the target area;
determining the elevation data as the raw data of the average elevation, the raw data of the slope proportion more than the preset degree and the raw data of the average topographic relief;
and determining the geographic national condition monitoring data as the original data of the shannon diversity index.
4. The method for measuring and calculating town-level spatial condition data based on geographic information as claimed in claim 3, wherein the step of calculating the raw data of the index to obtain the data of the index comprises:
calculating to obtain an elevation average value of the target area based on the elevation data;
determining the average elevation value as the data of the average elevation;
performing projection coordinate system conversion on the elevation data to obtain elevation data expressed by a projection coordinate system;
acquiring gradient distribution data of the target area by using a gradient percentage method;
extracting data with the gradient greater than a preset degree as target gradient data based on the gradient distribution data;
calculating the area ratio of the area corresponding to the target gradient data relative to the target area, and taking the area ratio as the gradient ratio data above the preset degree;
performing neighborhood analysis on the elevation data to obtain pixel-level topographic relief of the target area;
and calculating to obtain the data of the average topographic relief degree of the target area based on the pixel-level topographic relief degree.
5. The method for measuring and calculating town-level spatial condition data based on geographic information as claimed in claim 3, wherein the step of calculating the raw data of the index to obtain the data of the index comprises:
counting the number of first-level land types in the geographic national condition monitoring data;
summing the occupied areas corresponding to at least one surface coverage pattern spot of each primary land type to obtain the occupied area corresponding to each primary land type;
and (3) calculating the data of the shannon diversity index by using the following formula:
wherein SHDI is data of Shannon diversity index of the target region, P i And a is the occupied area of the ith primary land type in the target area, and a is the number of the primary land types in the target area.
6. The method for estimating spatial condition data in villages and towns based on geographic information according to claim 3, wherein said spatial condition data is calculated by the following formula:
wherein e is s The entropy value of the data for the s-th index,
specific numerical value, W, of data of the s-th index for the t-th village-level administration or the township administration s Is the coefficient of variation corresponding to the s-th index,
is the standard deviation of the data for the s-th index,
is the average of the data of the s-th index,
is the weight of the s-th index, Z ts Weighted comprehensive evaluation corresponding to s index of t village-level administrative unit or township administrative unitMatrix, Y ts A normalization matrix corresponding to the s index of the t village-level administrative unit or the township administrative unit, maxZ ts The maximum value of the row of the weighted comprehensive evaluation matrix corresponding to the s index of the t village level administrative unit or the township administrative unit, minZ ts The method comprises the steps that the weighted comprehensive evaluation matrix is the column minimum value of a weighted comprehensive evaluation matrix corresponding to the s index of the t-th village-level administrative unit or the land-level administrative unit, n is the number of the village-level administrative units or the land-level administrative units in an experimental area, the experimental area is the area of the last-level administrative unit of the target area, m is the number of the indexes, and SDI is the spatial condition data of the target area.
7. A village and town-level spatial condition data measuring and calculating system based on geographic information is characterized by comprising:
the region determining module is used for determining a target region to be subjected to spatial condition measurement and calculation, and the target region is a village-level administrative region or a township administrative region;
the index determining module is used for determining an index of the target area for carrying out space condition data measurement and calculation;
the acquisition module is used for acquiring the original data of the index;
the index calculation module is used for calculating the original data of the index to obtain the data of the index;
and the data calculation module is used for calculating to obtain the spatial condition data of the target area based on the data of the indexes.
8. The geographic information-based village-to-town spatial condition data measurement and calculation system of claim 7, wherein said metrics comprise: average elevation, slope proportion above a preset degree, average terrain relief degree and/or Shannon diversity index.
9. The geographic information-based village-town-level spatial condition data measurement and calculation system according to claim 8, wherein said obtaining raw data of the index comprises:
acquiring elevation data and geographical national condition monitoring data of the target area;
determining the elevation data as the raw data of the average elevation, the raw data of the slope proportion more than the preset degree and the raw data of the average topographic relief;
and determining the geographic national condition monitoring data as the original data of the shannon diversity index.
10. The geographic information-based village-and-town spatial condition data estimation system according to claim 9, wherein said spatial condition data is calculated by the following formula:
wherein e is s The entropy value of the data for the s-th index,
specific numerical value, W, of data of the s-th index for the t-th village-level administration or the township administration s Is the coefficient of variation corresponding to the s-th index,
is the standard deviation of the data for the s-th index,
is the average of the data of the s-th index,
is the weight of the s-th index, Z ts A weighted comprehensive evaluation matrix corresponding to the s index of the t village-level administrative unit or the township administrative unit, Y ts A normalization matrix corresponding to the s index of the t village-level administrative unit or the township administrative unit, maxZ ts The maximum value of the row of the weighted comprehensive evaluation matrix corresponding to the s index of the t village level administrative unit or the township administrative unit, minZ ts The method comprises the steps that the weighted comprehensive evaluation matrix is the column minimum value of a weighted comprehensive evaluation matrix corresponding to the s index of the t-th village-level administrative unit or the land-level administrative unit, n is the number of the village-level administrative units or the land-level administrative units in an experimental area, the experimental area is the area of the last-level administrative unit of the target area, m is the number of the indexes, and SDI is the spatial condition data of the target area.
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