CN114722353A - Multilayer natural resource geographic entity statistical method - Google Patents
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Abstract
The invention discloses a multilayer natural resource geographic entity statistical method, which belongs to the technical field of survey, monitoring, statistics and analysis of natural resources, wherein geographic entities are divided into edge-connected entities and non-edge-connected entities for respective statistics by judging the spatial position relationship between a statistical unit and the geographic entities to be counted, and the problem of repeated statistics of the number of the geographic entities caused by the cutting of the statistical unit is solved by aggregating the same geographic entities into multiple parts in statistical units of different layers and then extracting unique centroid points; the problem of incomplete counting of the central line length of the boundary river boundary road is compensated by hooking the counting length of the same geographic entity complementary part of the adjacent counting unit, so that the problem of inaccurate counting result caused by the fact that the continuity and the integrity of the geographic entities are not considered in the traditional method is solved, and the problem of repeated counting in the summary counting is also solved.
Description
Technical Field
The invention belongs to the technical field of natural resource investigation, monitoring, statistics and analysis, and particularly relates to a multilayer natural resource element entity statistical method.
Background
The natural resource geographic entity refers to natural or artificial ground objects which are closely related to natural resource development and protection, have a relatively stable spatial range or boundary, have or can be identified clearly, and have independent monitoring and statistical analysis significance, such as rivers, roads, town comprehensive function units, development areas, natural protection areas and the like. The natural resource geographic entity is obtained by natural resource survey and monitoring, and the statistical analysis result is an important component of the base number of the natural resource elements and is an important basis for objective evaluation, homeland space planning and ecological restoration of the natural resources, so that the accuracy, objectivity and reliability of the statistical result of the natural resource geographic entity must be ensured.
And the natural resource geographic entities are stored and expressed in the forms of points, lines and surfaces according to respective acquisition requirements. The natural resource geographic entities are continuous and complete in the objective world, but need to be expressed and organized by depending on a certain statistical unit in the data acquisition and statistical process, so that a large number of geographic entities are cut by the statistical unit, and the problem is easy to exist in the statistical process. The existing natural resource geographic entity statistical method is based on GIS statistical software, takes basic statistical units (such as county-level management boundaries) as statistical ranges, directly calculates quantity indexes such as the number, the length, the area and the like of natural resource survey monitoring geographic entities according to respective statistical models, and then collects the quantity indexes step by step to form statistical results of different levels. In the statistical process, the statistical units are used as the physical storage range of the data source to be counted, and the situation that continuous natural resource geographic entities are segmented commonly exists at the boundary, for example, a natural protection area is segmented into two statistical units across two counties. The same geographic entity is divided into a plurality of elements, which can cause in the statistical process: (1) the statistical result may be greater or less than the geographic entity reality. In example 1, a boundary river of A, B two counties is cut, the center line of the boundary river is not repeatedly collected according to the natural resource survey monitoring data collection principle, the center line of the boundary river respectively falls into A, B two counties according to the actual situation, and when statistics is carried out in GIS software, the direct calculation result is only the center line length in a statistical unit and is smaller than the actual length of the boundary river; example 2, the development area is constructed at the boundary between two municipalities C and D, and is cut into 5 elements due to the irregularity of the boundary between the municipalities, and the municipality C is divided into 3 elements, and if the statistics is directly performed on the C statistical unit, the calculation number 3 is greater than the actual case 1. (2) The summary statistics are different from the objective reality. In example 2, when local-city level summarization is performed, the number of development areas in the city jurisdiction C and the city jurisdiction D is simply added to obtain a summary result, and the statistical result is greater than the actual situation because no deduplication processing is performed. Due to the objective condition, the statistical result of the natural resource geographic entity partially cut by the statistical unit has deviation from the actual condition, and the accuracy of the multi-level statistical result of the natural resource geographic entity is difficult to ensure.
Disclosure of Invention
In order to solve the problems, the invention provides a multilayer natural resource geographic entity statistical method, which can automatically identify and extract the natural resource geographic entities cut at the statistical boundary, divide the natural resource geographic entities into different types, determine the identification rules in the statistical significance of the geographic entities according to attribute consistency, geographic spatial relationship, threshold judgment and the like, and finally solve the problem of statistical accuracy caused by cutting the geographic entities by a statistical unit through a calculation and summary method of each geographic entity at the attribute item marked boundary so as to achieve the aim of multilayer objective statistics and summary.
In order to achieve the purpose, the invention provides the following technical scheme:
a multilayer natural resource geographic entity statistical method comprises the following steps:
s1, establishing statistical unit space index including spatial position relation among statistical units and hierarchical relation among different statistical units;
s2, according to the spatial index between the statistical units, preparing the natural resource geographic entity data to be counted in the relevant range of the statistical units, including the data in the statistical units and in all spatial adjacent areas;
s3, dividing the geographic entity statistical hierarchy into two types of basic statistics and summary statistics, wherein n statistical hierarchies are provided; the basic statistics developed by the minimum statistical unit is L1 level, and the L2 level is summarized on the basis of L1 level statistics, and the Ln level statistical results are summarized step by step in the same way;
s4, extracting edge-connected and edge-unconnected geographic entities, marking the statistical units and the statistical levels according to the spatial relationship between the statistical units and the geographic entities of the natural resources to be counted;
the border geographical entity means that the same natural resource geographical entity is positioned in the range of 2 or more statistical units; the entity of the inner boundary of the unit to be counted is represented by U, and the entity of the outer boundary of the unit to be counted is represented by R;
the non-edge-contact geographic entity means that the same natural resource geographic entity is all positioned in the range of 1 statistical unit and is represented by a data set Q;
extracting and marking the statistical level of each edge-connected geographic entity and the statistical unit in which the edge-connected geographic entity is located by carrying out spatial analysis on the statistical unit and the geographic entity to be counted;
in L1-Ln level statistics, the data in the L1 edge-connected geographic entity data set U1 is the most, and the edge-connected entities of L2-Ln are all subsets of U1; correspondingly, the edge-connecting entity of Li (i > 1) grade is necessarily the L (i-1) grade edge-connecting entity; however, in the L (i-1) level edge-connecting geographic entities, the edge-connecting boundary of Li is only simultaneously formed when the geographic entities simultaneously pass through the L (i-1) and Li level statistical boundaries, and the rest L (i-1) level edge-connecting entities are not Li level edge-connecting entities;
the Li-level geographic entity data set Di to be counted comprises the following components: di = { Ui, U (i-1) andgateQi, Q (i-1) },
wherein Ui is a boundary data set of the Li-level geographic entity, U (i-1) andgateQi is a data set of which the L (i-1) level is the boundary entity but the Li level is not the boundary entity, and Q (i-1) is a data set of which the L (i-1) level is not the boundary entity; qi = (U (i-1) andgateQi) ueQ (i-1), which is a Li-level non-bordering geographic entity data set;
s5, carrying out edge-connecting natural resource geographic entity statistics in L1 level basic statistics; dividing the edge-connected geographic entity statistical type into two types of repeated statistics and incomplete statistics, physically combining the edge-connected geographic entities according to a spatial adjacency relation to form a complete geographic entity, calculating the proportion ki of the edge-connected geographic entities in the complete geographic entity, judging the relation between the edge-connected geographic entities and a threshold k, setting attribute values according to conditions, carrying out feature calculation, carrying out statistics according to attribute items and outputting results;
s6, carrying out non-bordering natural resource geographic entity statistics in L1-level basic statistics; calculating the indexes of the area, the length and the number of the non-edge-connected geographic entities in GIS software, carrying out classified addition and statistics, outputting the statistical result in a table form, naming the statistical result as INCODDE _ NOJB.XLSX according to different statistical unit codes, and putting the INCODE folder into a corresponding INCODE folder;
s7, combining the edge-connected geographic entity statistical results and non-edge-connected geographic entity statistical results of L1-level basic statistics according to statistical units to form L1-level statistical results; the method comprises the following specific steps: based on the outputted statistical form, extracting the statistical form named by the statistical unit code according to the statistical unit index, classifying and combining the statistical values to obtain a complete statistical result of the region, named as INCODDE.XLSX, and completing L1-level basic statistics;
s8, carrying out L2-Ln level summary statistics; in developing Li (i > 1) level summary statistics:
extracting L (i-1) level edge-connecting geographic entities, and dividing the L (i-1) level edge-connecting geographic entities into two types of Li level edge-connecting entities Li _11 (Li _11= Ui), wherein L (i-1) level edge-connecting entities are Li _12 (Li _12= U (i-1) # Qi) and Li _11 carries out calculation according to a step S5, and Li _12 carries out calculation according to a step S6;
aiming at the L (i-1) level non-bordering geographic entity, no longer performing spatial calculation, and searching a statistical table Li _ (i-1) related to Li according to a hierarchical relationship from the L (i-1) level non-bordering geographic entity statistical result table which is subjected to calculation;
summarizing the calculation results of the Li _11 and Li _12 geographic entities and the searched multiple related tables Li _ (i-1) according to the statistical units, the names and the types of the geographic entities to obtain Li-level summarizing statistical results;
and S9, judging whether the statistics is the last level of summary statistics, if not, repeating the step S8 until the statistics is completed.
Further, in step S1, the step of establishing the statistical unit spatial index includes:
s101, establishing a spatial connection chart among the statistical units, wherein the spatial connection chart is used for representing the range, distribution, spatial incidence relation and the like of the statistical units;
s102, coding the statistical units, defining statistical levels among the statistical units and including hierarchical relations, wherein the minimum statistical unit is L1 level, and the minimum statistical unit is up to Ln level by level; the statistic unit code is recorded in the attribute item encode, and the statistic level is recorded in STATGRADE.
Further, in step S5, the step of bordering the geographic entity includes:
s501, statistical type division
The repeated statistics type means that the natural resource geographic entity is divided into a plurality of elements by a statistics unit, and the direct calculation and summary statistics result in that the number of statistics is more than that of objective reality; for example, in the geographic national condition monitoring data, a linear or planar geographic entity crossing a statistical boundary is divided into a plurality of elements, and the direct calculation and the summary of the number of the elements belong to a repeated statistical type;
the incomplete statistics type is a situation that a natural resource geographic entity is divided into a plurality of elements by a statistics unit, only part of the elements fall into the range of the statistics unit, only partial statistics is directly calculated, and actually complete statistics is required; if the length statistics of the boundary rivers and the boundary roads belong to the condition;
s502, determining the type of the geographic entity to be counted according to the statistical characteristics of the geographic entity and the relation between the statistical unit and the geographic entity.
Further, in step S5, the step of calculating the ratio ki of the edge-connecting geographic entity to the complete geographic entity includes:
s503, calculating quantity characteristics including length and area of each entity in the border geographic entity data set U1 to be counted;
s504, performing data fusion of the geographic entities U1 and R1 inside and outside the statistical unit according to the entity codes and names to form a physically combined edge-connected geographic entity data set UR1, and calculating the length and the area of each geographic entity in the UR 1;
s505, carrying out aggregation operation on edge-connected geographic entities in a data set U1 according to entity codes and names, aggregating a plurality of spatially unconnected geographic entities cut by boundary lines in the same statistical unit into a multi-component geographic entity, wherein the aggregated data set is U1_ A, and extracting a centroid point P1_ A of the aggregated geographic entities;
and S506, calculating the proportion ki of the geographic entities in the linear and planar edge-connected geographic entity data set U1_ A in the statistical unit to the corresponding complete entities in the edge-connected entity data set UR1 through spatial superposition analysis.
Further, in step S5, the step of setting the attribute values and performing the feature calculation for each case includes:
s507, adding attribute items
The INCODE attribute item in the bordering geographic entity is used for recording the statistical unit where the geographic entity is located, and has uniqueness; adding a STATCOMODE attribute item, and recording a statistical unit required to be included in the geographic entity statistics, wherein the value of the statistical unit may be the same as or different from the INCODE;
s508, setting of threshold k
Setting a reasonable threshold k, and when the area and the quantity of the geographic entities in the statistical unit account for the whole proportion and are more than or equal to the value, considering that the geographic entities have statistical significance in the statistical unit; if the geographic entity is smaller than the threshold value, the geographic entity is considered to be included in the statistical unit because the boundary of the statistical unit and the entity is not completely combined, and the statistical significance is not achieved;
s509, repeated statistical type calculation of geographic entities
If ki is larger than or equal to the threshold k, directly calculating the length and the area of the geographic entity; counting the number according to the number of the centroid points P1_ A of the geographical entities after the statistics aggregation, and achieving the purpose of removing the duplication in the statistical unit by only collecting one centroid point for the geographical entities with the same name and entity code; the STATCOMODE attribute value of each element statistical unit code in the line, surface element and post-transition P1_ A is consistent with INCODE, and the code of the statistical unit where the element statistical unit code is located is recorded;
if ki is less than the threshold k, the area, length and number of the geographic entity in the statistical unit are not calculated, the INCODE records the code of the statistical unit, but the STATCOMODE attribute item of the planar and linear geographic entity needs to fill the code of the statistical unit which is adjacent to the statistical unit and in which the complete entity mainly falls; the STATCODE value of the statistical unit code of the centroid point P1_ a is null, and no statistical unit is filled, i.e. no counting is involved;
s510, incomplete statistical type geographic entity calculation
If ki is larger than or equal to the threshold k, calculating the area and the number of the geographic entities in the statistical unit by referring to the operation development of the repeated statistical type geographic entities; when length calculation is carried out aiming at the linear geographic entity, the STATCOMODE simultaneously fills and writes the statistical unit codes, the neighborhood statistical unit codes where the border entity is located, and different statistical unit codes are used and separated; the incomplete statistical type geographic entity carries out statistical compensation on the geographic entities which correspondingly fall into but do not fall into the adjacent statistical units in a way of carrying out statistics in the statistical unit and the adjacent statistical units, and similarly, the geographic entities which correspondingly fall into but do not fall into the area are subjected to statistical compensation by the adjacent statistical units, so that the effect of mutual compensation is achieved;
if ki is less than the threshold k, the calculation method is the same as the repeated statistic type.
Further, in step S5, the step of counting and outputting the result according to the attribute items includes:
s511, classifying and summarizing indexes such as area, length and number calculated by the natural resource geographic entity according to STATCOMODE attribute items;
and S512, naming the statistical result according to the situation and outputting the statistical result according to the statistical unit code filled in the STATCOMODE attribute item.
The invention has the beneficial effects that:
(1) according to the statistical method provided by the invention, the geographic entities are divided into the edge-connected entities and the non-edge-connected entities for respective statistics by judging the spatial position relationship between the statistical unit and the geographic entities to be counted, and the problem of repeated statistics of the number of the geographic entities caused by the cutting of the statistical unit is solved by aggregating the same geographic entities into multiple parts in the statistical units of different levels and then extracting a unique center of mass point; the problem of incomplete counting of the central line length of the boundary river boundary road is compensated by hooking the counting length of the same geographic entity complementary part of the adjacent counting unit, so that the problem of inaccurate counting result caused by the fact that the continuity and the integrity of the geographic entities are not considered in the traditional method is solved, and the problem of repeated counting in the summary counting is also solved.
(2) The statistical method provided by the invention is suitable for multi-level statistical units, when the summary statistics is developed, only the spatial calculation needs to be carried out on the edge-connected geographic entities of different levels, the statistical results of the non-edge-connected geographic entities are obtained by classifying and summarizing on the basis of the previous-level statistical table, and the statistical accuracy and the statistical efficiency are considered.
Drawings
The above and other features, properties and advantages of the present invention will become more apparent from the following description of the embodiments with reference to the accompanying drawings, in which:
FIG. 1 is a basic flowchart of a method for statistics of a multi-level natural resource geographic entity according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of a statistical hierarchy of a method for statistics of a multi-level natural resource geographic entity according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of the relationship between the upper and lower statistical levels of the indirect edge and non-indirect edge geographic entities in the method for calculating a multilayer natural resource geographic entity according to the embodiment of the present invention;
FIG. 4 is a diagram of a repeated statistical geographic entity of the method for multi-level natural resource geographic entity statistics according to the embodiment of the present invention;
FIG. 5 is a schematic diagram of an incomplete statistical geographic entity of the method for calculating a geographic entity of multi-level natural resources according to the embodiment of the present invention;
fig. 6 shows a Li-level summary statistical flowchart of a multilevel natural resource geographic entity statistical method according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Embodiment 1 as shown in fig. 1, a method for counting a multi-level natural resource geographic entity according to an embodiment of the present invention includes the following steps:
s1, establishing a spatial index by taking the administrative division management unit as a statistical unit (figure 2), wherein the spatial index comprises spatial position relations among the statistical units and hierarchical relations among different statistical units;
in step S1, the step of establishing the statistical unit spatial index is:
s101, establishing a spatial connection chart among statistical units, and taking the range surface of each level of administrative division as a spatial graph and each level of administrative division codes as statistical unit codes according to the hierarchical relationship of county level, city level, province level and country level;
s102, coding statistical units, recording the statistical units in the INCODE attribute items, wherein the county-level statistical units are L1-level statistical units, and the coding rule is '2-bit provincial-level codes + 2-bit city-level codes + 2-bit county-level codes'; the local-city level statistical unit is an L2 level statistical unit, and the coding rule of the local-city level statistical unit is 2-bit provincial level code + 2-bit local-city level code + 00; the provincial level statistical unit is an L3 level statistical unit, and the encoding rule is '2-bit provincial level code + 0000'; the state-level statistical unit is an L4-level statistical unit, encoding is not performed any more, and summary is developed based on all provincial statistical results. The statistical hierarchy is recorded in the STATGRADE attribute entry.
For example, the statistical unit INCODE of the undergraduate of Jinan City in Shandong is "370102", and the statistical level STATGRADE is "L1". The spatially adjacent statistic units are statistic codes of "370105", "370104", "370103" and "370112".
S2, according to the spatial index between the statistical units, preparing the natural resource geographic entity data to be counted in the relevant range of the statistical units, including the data in the statistical units and in all spatial adjacent areas;
the geographic entity to be counted comprises three types of elements, namely a point, a line, a surface and the like, wherein each type of element comprises a plurality of natural resource element types. The planar elements comprise the range surfaces of entities such as rivers, reservoirs, lakes, mountains, main functional areas, natural cultural protection areas, forest parks, geological parks, development areas, bonded areas and the like; the line elements comprise the center lines of the entities such as rivers, roads, dams, large-scale water gates, bridges and the like; the point elements are positioning points of residential districts, industrial and mining enterprises, overpasses, administrative villages and the like.
The natural resource geographic entity data in the neighborhood range of the statistical unit only needs to establish a logical adjacency relation according to the spatial connection chart of the statistical unit, and the data does not need to be copied to the same layer.
And S3, dividing the geographic entity statistical hierarchy into two types of basic statistics and summary statistics, wherein n statistical hierarchies are provided. The basic statistics developed by the minimum statistical unit is L1 level, and the statistics are summarized to L2 level on the basis of L1 level statistics, and the statistics are summarized to Ln level statistics results step by step.
In this embodiment, the statistics at level L1, i.e., the statistics at the county administrative district level, and the statistics at level local and city level is the statistics at level L2, which are obtained by summarizing on the basis of the statistics at level L1, and similarly, the statistics at level province L3 are obtained by summarizing at level local and city level L2, and the statistics at level national L4 are obtained by summarizing at level L3.
And S4, extracting edge-connected and edge-unconnected geographic entities and marking the statistical units, statistical levels and the like according to the spatial relationship between the statistical units and the geographic entities of the natural resources to be counted.
The border entity means that the same natural resource geographic entity is located in the range of 2 or more statistical units. The entity of the inner boundary of the unit to be counted is represented by U, and the entity of the outer boundary of the unit to be counted is represented by R. If an economic development area simultaneously spans the undergrowth area and the historic district of Jinan city, the economic development area belongs to the edge-connected geographic entity. For the statistical unit 'under-calendar area', the part of the development area positioned under the calendar area belongs to an internal edge-connected entity and is stored in a data set U, and the development area positioned in the calendar area belongs to a geographical entity externally connected with the statistical unit and is stored in a data set R.
By performing spatial superposition analysis on the statistical unit and the geographic entity to be counted, the geographic entity completely consistent with the range of the statistical unit is cut, and the statistical level STATGRADE of the statistical unit and the attribute of the statistical unit INCODE where the statistical unit is located are hooked. And extracting boundary lines of the statistical units, and carrying out 5-meter buffer area analysis, wherein the geographic entities inside and outside the statistical units, which are intersected with the buffer area, are used as edge-connected geographic entities, and the geographic entities, which are not intersected with the buffer area, in the statistical units are non-edge-connected geographic entities.
As the statistical units at different levels have the characteristics of continuity and seamless in space, for example, the prefecture-level statistical unit consists of the prefecture-level statistical units. Thus, a high level statistical bounding range line must be a low level statistical bounding range, e.g., a prefecture level boundary must be a county level boundary at the same time. Therefore, the data in the boundary geographic entity data set U1 of the county-level statistical unit is the most, and all other level summary statistical boundary geographic entities are subsets of the county-level boundary geographic entities; as the aggregation level increases, the number of edge geographic entities serving as aggregation statistical units is continuously decreasing. When developing the summary of the local level, the data set D2 of the geographic entity to be counted of the local level is constituted by: d2= { U1, U1 & 'Q2, Q1}, wherein U2 is the geographical entity data of local and city level connection, U1 &' Q2 refers to the geographical entity data set of county level connection and local and city level non-connection, and Q1 is the non-connection geographical entity data set of each county under jurisdiction. As shown in fig. 3.
And S5, developing edge-connecting geographic entity statistics in the L1-level basic statistics. Dividing the edge-connected geographic entity statistic types into two types of repeated statistics and incomplete statistics, physically combining the edge-connected geographic entities according to a spatial adjacency relation to form a complete geographic entity, calculating the proportion ki of the edge-connected geographic entities in the complete geographic entity, judging the relation between the edge-connected geographic entities and a threshold k, setting attribute values according to conditions, carrying out feature calculation, carrying out statistics according to attribute items and outputting results.
In S5, the step of dividing the bordering geographic entities is:
s501, statistical type division
The repeated statistics type means that the natural resource geographic entity is divided into a plurality of elements by a statistics unit, and the direct calculation and summary statistics result in that the number of statistics is more than that of objective reality. For example, in the geographic national condition monitoring data, linear or planar geographic entities such as scenic spots, tourist areas, development areas, bridges, dams and the like crossing statistical boundaries are divided into a plurality of elements, and direct calculation and summary belong to repeated statistical types. FIG. 4 shows a forest park which is cut into 5 parts by a county boundary, wherein 4 forest parks are located in B county, the number of B county is counted as 4 when direct statistics is performed, and the number of forest parks is counted as 5 when direct statistics is performed.
The incomplete statistics type is a situation that the natural resource geographic entity is divided into a plurality of elements by a statistics unit, only part of the elements fall into the range of the statistics unit, and only part of the elements are directly calculated, but complete statistics is actually required. The length statistics of the boundary rivers and the boundary roads belong to the situation. As shown in fig. 5, although the county-level boundary is located within the river surface, the river center line is divided into a plurality of segments by the boundary, and if only the length of the center line within each county-level is directly counted within the 3 county-level statistical units shown in the figure, the statistics are incomplete.
S502, determining the type of the geographic entity to be counted according to the statistical characteristics of the geographic entity, the relation between the geographic entity and the statistical unit and the like, wherein in general, the repeated statistical type is preferentially considered except for obvious incomplete statistical types such as a boundary river road and the like.
In S5, the step of calculating the ratio ki of the bordering geographic entity to the complete geographic entity is:
s503, calculating quantity characteristics including length and area of each entity in the border geographic entity data set U1 to be counted; in fig. 4, the area of each part in the forest park area index when statistics are performed in prefecture B is 8.2, 7.5, 1.6, and 0.4 square kilometers, respectively.
S504, performing data fusion of the geographic entities U1 and R1 inside and outside the statistical unit according to key attributes such as entity codes and names to form a physically-combined edge-connected geographic entity data set UR1, and calculating indexes such as the length and the area of each physically-fused geographic entity in UR 1; the combined physical area of the forest park in figure 4 is 43.2 square kilometers.
S505, carrying out aggregation operation on edge-connected geographic entities in a data set U1 according to key attributes such as entity codes and names, aggregating a plurality of spatially unconnected geographic entities cut by boundary lines in the same statistical unit into a multi-component geographic entity, wherein the aggregated data set is U1_ A, and extracting a centroid point P1_ A of the aggregated geographic entity; after aggregation, the aggregated geographic entities in fig. 4 each have a centroid point in prefecture a and prefecture B.
And S506, calculating the proportion ki of the geographic entities in the linear and planar edge-connected geographic entity data set U1_ A in the statistical unit to the corresponding complete entities in the edge-connected entity data set UR1 through spatial superposition analysis. The B-county area ratio ki in fig. 4 is 0.41.
In S5, the step of setting attribute values and performing feature calculation for each case includes:
s507, adding attribute items
The INCODE attribute item in the bordering geographic entity is used for recording the statistical unit where the geographic entity is located, and has uniqueness. And adding a STATCOMODE attribute item, and recording a statistical unit which needs to be included in the geographic entity statistics, wherein the value of the statistical unit may be the same as or different from the INCODE.
S508, setting of threshold k
Setting a reasonable threshold k, and when the integral proportion of the characteristics such as the area, the quantity and the like of the geographic entity in the statistical unit is more than or equal to the value, considering that the geographic entity has statistical significance in the statistical unit; if the value is smaller than the threshold value, the geographic entity is considered to be not statistically significant because the statistical unit and the entity boundary are not completely set and fall into the statistical unit. In fig. 4, the threshold k is set to 0.95, and in different application scenarios, the value of k can be adjusted as needed.
S509, repeated statistical type calculation of geographic entities
If ki is larger than or equal to the threshold k, directly calculating the characteristics of the geographic entity, such as length, area and the like; the number is counted according to the number of the centroid points P1_ A of the geographical entities after the statistics and aggregation, and the purpose of removing the duplication in the statistical unit is achieved by only collecting one centroid point for the geographical entities with the same name and entity code. And (4) enabling the STATCOMODE attribute value of each element statistical unit code of the line element, the surface element and the post-transition P1_ A element to be consistent with the INCODE, and recording the code of the statistical unit where the element statistical unit code is located. In the example of fig. 4, the area of the geographic entity is directly calculated, the area of the forest park in the statistical unit B is 17.7 square kilometers, and the geographic entity is a planar element, so the length characteristic is not counted, and the number is the number of centroid points of the aggregated element 1; and the administrative division code of B county is '370323', and the STATCOMODE and INCODE take values of '370323'.
If ki is less than the threshold k, the characteristics of the area, the length, the number and the like of the entity in the statistical unit are not calculated, the INCODE records the code of the statistical unit where the entity is located, but the STATCOMODE attribute item of the planar and linear geographic entity needs to be filled in the code of the statistical unit which is adjacent to the statistical unit and in which the complete entity mainly falls; the statistic unit code statmode value of the centroid point P1_ a is null and no statistic unit is filled, i.e. no counting is involved.
S510, incomplete statistical type geographic entity calculation
And if ki is larger than or equal to the threshold k, calculating the area, the number and other characteristics of the geographic entity in the statistical unit by referring to the repeated statistical geographic entity operation development. When length calculation is carried out aiming at linear geographic entities, the STATCOMODE simultaneously fills in the statistical unit codes, the neighborhood statistical unit codes where the bordering entities are located, and different statistical unit codes are used and separated. The incomplete statistical type geographic entity carries out statistical compensation on the geographic entities which fall into the adjacent statistical unit and do not fall into the adjacent statistical unit correspondingly in a mode of carrying out statistics in the statistical unit and the adjacent statistical unit, and similarly, the geographic entities which fall into the adjacent statistical unit and do not fall into the area correspondingly carry out statistical compensation so as to play a mutual compensation effect. In fig. 5, the information of the statistical length of the jungle, A, B, C, the geocode of the jungle center line in three counties are respectively assigned as "370215", "370283", "370285", and the statode of the jungle center line in a county is "370215, 370283"; the STATCOMODE of the B county junctional river center line at A, B county junctional river is "370283, 370215", and the STATCOMODE at the B, C county junctional river is "370283, 370285"; the STATCODE of the junctional river of prefecture C is "370285, 370283".
If ki is less than the threshold k, the calculation method is the same as the repeated statistic type.
In S5, the step of counting and outputting the result by attribute items is:
and S511, classifying and summarizing indexes such as the area, the length, the number and the like calculated by the natural resource geographic entity according to STATCOMDE attribute items. When calculation is carried out, multiple types of geographic entities such as points, lines and planes can be counted together or a certain type of geographic entity can be selected for individual statistics in a targeted manner according to needs; and (4) classifying and summarizing the indexes calculated by each record.
And S512, naming the output statistical result according to the situation according to the statistical unit code filled in the STATCOMODE attribute item.
In order to avoid the condition that renaming exists in output tables among different statistical units, each statistical unit creates a folder and is named by an INCODE attribute value.
If the STATCOMODE only contains 1 statistical unit, the output statistical table is named as: STATCOMODE _ JB.XLSX;
if the STATCOMODE comprises a plurality of statistical units, taking the 'number' as a separator, extracting each value in the STATCOMODE, and respectively outputting statistical tables of STATCOMODE {0} _ JB _0.XLSX, STATCOMODE {1} _ JB _1.XLSX, … … and the like.
And if the STAT _ CODE attribute value is null, the entity does not participate in the number statistics and does not generate a statistical record.
Taking fig. 5 as an example, when statistics is performed on the geographical entities of the junctional river in prefecture a, a folder named "370215" is established, two tables 370215_ JB _0.XLSX, 370283_ JB _1.XLSX are generated, the length of the junctional river center line in prefecture a is recorded, note that at this time, the geographical entity objects, lengths, and the like counted by the two tables are completely consistent, which means that the center line is counted in prefecture a and prefecture B at the same time; correspondingly, when statistics is carried out in B county, a folder named '370283' is established, and three tables 370283_ JB _0.XLSX, 370215_ JB _1.XLSX, 370285_ JB _2.XLSX and the like are contained in the folder.
And S6, developing non-edge-connected element statistics in the L1-level basic statistics. Calculating indexes such as area, length, number and the like of the non-edge-connected geographic entities in GIS software, carrying out classified addition and statistics, outputting statistical results in a table form, naming the statistical results as INCODDE _ NOJB.XLSX according to different statistic unit codes, and putting the INCODDE folders into corresponding INCODE folders.
In fig. 5, the statistical result name for the a-county geographic entity is 370215_ nojb.
And S7, combining the edge-connected geographic entity statistical result and the non-edge-connected geographic entity statistical result of the L1-level basic statistics according to the statistical units to form an L1-level statistical result.
The method specifically comprises the following steps: based on the outputted statistical table, the statistical table named by the statistical unit code is extracted according to the statistical unit index, the statistical values are classified and merged to obtain a complete statistical result of the region, named as INCODDE.XLSX, and the L1-level basic statistics is completed.
In the example of fig. 5, for the merging of statistical results of geographic entities in prefecture a, folders "370215", "370283", and … … of prefecture a and its adjacent statistical units need to be screened, a form containing "370215" in the statistical table is selected from the folders, and each statistical record is read and added and summarized according to the same statistical items. River M in prefecture A, which contained the non-border stretch in the "370215" folder, was stored in 370215_ NOJB.XLSX and was 15.3 km in length; A. the river reach at junction B, 4.6 km in 370215_ JB _0.XLSX and 5.5 km in 370215_ JB _1.XLSX in the "370283" folder, totaled a total of 25.4 km for the M river length in A county. And the method effectively achieves the compensation effect by adopting a direct calculation mode and the length of the river M is 19.9 kilometers.
S8, developing L2-Ln level summary statistics, as shown in FIG. 6. In developing Li (i > 1) level summary statistics:
and (3) extracting L (i-1) level edge-connecting geographic entities, and dividing the L (i-1) level edge-connecting geographic entities into two types of conditions, namely Li _11 level edge-connecting entities and Li _12 level edge-connecting entities, wherein the Li _11 carries out calculation according to S5, and the Li _12 carries out calculation according to S6.
And aiming at the L (i-1) level non-bordering geographic entity, no longer performing spatial calculation, and searching a statistical table Li _ (i-1) related to Li according to a hierarchical relationship from the L (i-1) level non-bordering geographic entity statistical result table after calculation is completed.
And summarizing the calculation results of the Li _11 and Li _12 geographic entities and the searched multiple related tables Li _ (i-1) according to the classification of statistical units, geographic entity names, types and the like to obtain Li-level summarizing statistical results.
In this embodiment, the county-level statistics are L1-level statistics, and when the county-level summary is performed as a prefecture, the county-level summary is L2-level summary statistics. At this time, as shown in fig. 3, according to the spatial relationship between the L1 level edge-connected geographic entity and the L2 level statistical boundary (city boundary), the L2 level edge-connected geographic entity L2_11 and the L2 level non-edge-connected geographic entity L2_12 are extracted from the county level L1 edge-connected geographic entity. Wherein L2_11 carries out calculation and statistics in a mode of 'S5 edge-connected geographic entity statistics'; l2_12 carries out calculation and statistics in GIS software according to the mode of 'S6 non-edge geographic entity statistics'; and extracting the statistical table of the prefecture from the statistical table of the county-level non-bordering geographic entity according to the index relationship. And (4) classifying and combining the three types of statistical forms to form a L2 city-level summary statistical result.
And S9, judging whether the statistics is the last level of summary statistics, if not, repeating the step S8 until the statistics is completed.
The above embodiments are provided only for illustrating the present invention and not for limiting the present invention, and those skilled in the art can make various changes or modifications without departing from the spirit and scope of the present invention. Those skilled in the art, having the benefit of this disclosure and the benefit of this written description, will appreciate that other embodiments can be devised which do not depart from the specific details disclosed herein.
Claims (6)
1. A multilayer natural resource geographic entity statistical method is characterized by comprising the following steps:
s1, establishing statistical unit space index including spatial position relation among statistical units and hierarchical relation among different statistical units;
s2, according to the spatial index among the statistical units, preparing the natural resource geographic entity data to be counted in the relevant range of the statistical units, including the data in the statistical units and in all spatial adjacent areas;
s3, dividing the geographic entity statistical hierarchy into two types of basic statistics and summary statistics, wherein n statistical hierarchies are provided; the basic statistics developed by the minimum statistical unit is L1 level, and the L2 level is summarized on the basis of L1 level statistics, and the Ln level statistical results are summarized step by step in the same way;
s4, extracting edge-connected and edge-unconnected geographic entities, marking the statistical units and the statistical levels according to the spatial relationship between the statistical units and the geographic entities of the natural resources to be counted;
the border geographic entity means that the same natural resource geographic entity is positioned in the range of 2 or more statistical units; the entity of the inner boundary of the unit to be counted is represented by U, and the entity of the outer boundary of the unit to be counted is represented by R;
the non-bordering geographic entities mean that the same natural resource geographic entity is all located in the range of 1 statistical unit and represented by a data set Q;
extracting and marking the statistical level of each edge-connected geographic entity and the statistical unit in which the edge-connected geographic entity is located by carrying out spatial analysis on the statistical unit and the geographic entity to be counted;
in L1-Ln level statistics, the data in the L1 edge-connected geographic entity data set U1 is the most, and the edge-connected entities of L2-Ln are all subsets of U1; correspondingly, the Li-level edge-connecting entity is necessarily an L (i-1) -level edge-connecting entity; however, in the L (i-1) level edge-connecting geographic entities, the edge-connecting boundary of Li is only simultaneously formed when the geographic entities simultaneously pass through the L (i-1) and Li level statistical boundaries, and the rest L (i-1) level edge-connecting entities are not Li level edge-connecting entities; wherein i is a positive integer greater than 1;
the Li-level geographic entity data set Di to be counted comprises the following components: di = { Ui, U (i-1) andgateQi, Q (i-1) },
wherein Ui is a boundary data set of the Li-level geographic entity, U (i-1) andgateQi is a data set of which the L (i-1) level is the boundary entity but the Li level is not the boundary entity, and Q (i-1) is a data set of which the L (i-1) level is not the boundary entity; qi = (U (i-1) andgateQi) ueQ (i-1), which is a Li-level non-bordering geographic entity data set;
s5, carrying out border natural resource geographic entity statistics in L1-level basic statistics; dividing the edge-connected geographic entity statistical type into two types of repeated statistics and incomplete statistics, physically combining the edge-connected geographic entities according to a spatial adjacency relation to form a complete geographic entity, calculating the proportion ki of the edge-connected geographic entities in the complete geographic entity, judging the relation between the edge-connected geographic entities and a threshold k, setting attribute values according to conditions, carrying out feature calculation, carrying out statistics according to attribute items and outputting results;
s6, carrying out non-bordering natural resource geographic entity statistics in L1-level basic statistics; calculating the indexes of the area, the length and the number of non-edge-connected geographic entities in GIS software, performing classified addition statistics, outputting the statistical results in a table form, naming the statistical results as INCODE _ NOJB.XLSX according to different INCODE codes, and putting the INCODE codes into corresponding INCODE folders;
s7, combining the edge-connected geographic entity statistical results and non-edge-connected geographic entity statistical results of L1-level basic statistics according to statistical units to form L1-level statistical results;
s8, carrying out L2-Ln level summary statistics; in developing Li-level aggregation statistics, where i is a positive integer greater than 1:
extracting L (i-1) level edge-connected geographic entities, and dividing the L (i-1) level edge-connected geographic entities into two types of situations, namely Li _11 of Li level edge-connected entities, and Li _12 of L (i-1) level edge-connected entities, wherein Li _11 carries out calculation according to a step S5, and Li _12 carries out calculation according to a step S6;
aiming at the L (i-1) level non-bordering geographic entity, no longer performing spatial calculation, and searching a statistical table Li _ (i-1) related to Li according to a hierarchical relationship from the L (i-1) level non-bordering geographic entity statistical result table which is subjected to calculation;
summarizing the calculation results of the Li _11 and Li _12 geographic entities and the searched multiple related tables Li _ (i-1) according to the statistical units, the names and the types of the geographic entities to obtain Li-level summarizing statistical results;
and S9, judging whether the statistics is the last level of summary statistics, if not, repeating the step S8 until the statistics is completed.
2. The method for statistics of multi-level natural resources geographic entities as claimed in claim 1, wherein in step S1, the step of creating the statistical unit spatial index comprises:
s101, establishing a spatial connection chart among the statistical units, wherein the spatial connection chart is used for representing the range, distribution and spatial association relation of the statistical units;
s102, coding the statistical units, defining statistical levels among the statistical units and including hierarchical relations, wherein the minimum statistical unit is L1 level, and the minimum statistical unit is up to Ln level by level; the statistic unit code is recorded in attribute item encode, and the statistic level is recorded in STATGRADE.
3. The method for statistics of multi-level natural resources geographic entities as claimed in claim 1, wherein in step S5, the step of dividing the statistical type of the bordering geographic entities comprises:
s501, statistical type division
The statistical types are divided into a repeated statistical type and an incomplete statistical type;
s502, determining the statistical type of the geographic entity to be counted according to the statistical characteristics of the geographic entity and the relation between the statistical unit and the geographic entity.
4. The method for counting the multi-level natural resource geographic entities according to claim 1, wherein the step of calculating the ratio ki of the edge-connected geographic entity to the complete geographic entity in step S5 comprises:
s503, calculating quantity characteristics including length and area of each entity in the border geographic entity data set U1 to be counted;
s504, performing data fusion of the geographic entities U1 and R1 inside and outside the statistical unit according to the entity codes and names to form a physically combined edge-connected geographic entity data set UR1, and calculating the length and the area of each geographic entity in the UR 1;
s505, carrying out aggregation operation on edge-connected geographic entities in a data set U1 according to entity codes and names, aggregating a plurality of spatially unconnected geographic entities cut by boundary lines in the same statistical unit into a multi-component geographic entity, wherein the aggregated data set is U1_ A, and extracting a centroid point P1_ A of the aggregated geographic entities;
and S506, calculating the proportion ki of the geographic entities in the linear and planar edge-connected geographic entity data set U1_ A in the statistical unit to the corresponding complete entities in the edge-connected entity data set UR1 through spatial superposition analysis.
5. The method for statistics of multi-level natural resources geographic entities as claimed in claim 1, wherein in step S5, the step of setting attribute values according to situations and performing feature calculation comprises:
s507, adding attribute items
The INCODE attribute item in the bordering geographic entity is used for recording the statistical unit where the geographic entity is located, and has uniqueness; adding a STATCOMODE attribute item, and recording a statistical unit required to be included in the geographic entity statistics, wherein the value of the statistical unit may be the same as or different from the INCODE;
s508, setting of threshold k
Setting a reasonable threshold k, and when the area and the quantity of the geographic entities in the statistical unit account for the whole proportion and are more than or equal to the value, considering that the geographic entities have statistical significance in the statistical unit; if the geographic entity is smaller than the threshold value, the geographic entity is considered to be included in the statistical unit because the boundary of the statistical unit and the entity is not completely combined, and the statistical significance is not achieved;
s509, repeated statistical type geographic entity calculation
If ki is larger than or equal to the threshold k, directly calculating the length and the area of the geographic entity; counting the number according to the number of the centroid points P1_ A of the geographical entities after the statistics aggregation, and achieving the purpose of removing the duplication in the statistical unit by only collecting one centroid point for the geographical entities with the same name and entity code; the STATCOMODE attribute value of each element statistical unit code in the line, surface element and post-transition P1_ A is consistent with INCODE, and the code of the statistical unit where the element statistical unit code is located is recorded;
if ki is less than the threshold k, the area, length and number of the geographic entity in the statistical unit are not calculated, the INCODE records the code of the statistical unit, but the STATCOMODE attribute item of the planar and linear geographic entity needs to fill the code of the statistical unit which is adjacent to the statistical unit and in which the complete entity mainly falls; the STATCODE value of the statistical unit code of the centroid point P1_ a is null, and no statistical unit is filled, i.e. no counting is involved;
s510, incomplete statistical type geographic entity calculation
If ki is larger than or equal to the threshold k, calculating the area and the number of the geographic entities in the statistical unit by referring to the operation development of the repeated statistical geographic entities; when length calculation is carried out aiming at the linear geographic entity, the STATCOMODE simultaneously fills and writes the statistical unit codes, the neighborhood statistical unit codes where the border entity is located, and different statistical unit codes are used and separated; the incomplete statistical type geographic entity carries out statistical compensation on the geographic entities which correspondingly fall into but do not fall into the adjacent statistical units in a way of carrying out statistics in the statistical unit and the adjacent statistical units, and similarly, the geographic entities which correspondingly fall into but do not fall into the area are subjected to statistical compensation by the adjacent statistical units, so that the effect of mutual compensation is achieved;
if ki is less than the threshold k, the calculation method is the same as the repeated statistic type.
6. The method for counting multi-level natural resources geographic entities according to claim 1, wherein the step of counting and outputting the result according to the attribute items in step S5 comprises:
s511, classifying and summarizing the quantity characteristics of the area, the length and the number calculated by the natural resource geographic entity according to STATCOMODE attribute items;
and S512, naming the statistical result according to the situation and outputting the statistical result according to the statistical unit code filled in the STATCOMODE attribute item.
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