CN113962923B - Method and device for determining sampling object - Google Patents
Method and device for determining sampling object Download PDFInfo
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- CN113962923B CN113962923B CN202110815627.2A CN202110815627A CN113962923B CN 113962923 B CN113962923 B CN 113962923B CN 202110815627 A CN202110815627 A CN 202110815627A CN 113962923 B CN113962923 B CN 113962923B
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Abstract
The invention discloses a method and a device for determining a sampling object. The method comprises the following steps: acquiring position information of each sampling object; determining a road closest to the sampling object according to the position information; and determining the sampling object with the space access degree between the sampling objects and the nearest road larger than the preset access degree as an important sampling object. By adopting the method provided by the invention, the spatial accessibility of the sampling object is judged by combining the position information of the sampling object, so that the problems of selection missing or insufficient sample quantity of the sampling object in the region with lower accessibility in the traditional sampling survey are avoided.
Description
Technical Field
The invention relates to the technical field of data processing, in particular to a method and a device for determining a sampling object.
Background
At present, survey sampling is mainly carried out based on traditional hierarchical sampling. However, in reality, the sampling unit is often a position in an actual geographic space, and usually, attribute information corresponding to a sampling object has different degrees of relevance in space, for example, sample points close to each other have a certain degree of relevance, and it is difficult to satisfy a precondition of a classical sampling method, namely an independence assumption. Therefore, when a classical sampling method is adopted for sampling and statistics in a geospatial object, due to the random arrangement of the sample points in space, on one hand, the sample points are gathered in space to cause the overlapping of sample information, and on the other hand, the loss of the sample points in a part of areas causes the reduction of sampling estimation efficiency, and finally, the problems of the overlapping of the sample information, the omission of important samples, the loss of effective sample information caused by the non-uniform spatial distribution of the samples, the weak representativeness and the like are caused. Especially, the area of the corner angle of the side with low accessibility is often the area of key investigation. Therefore, the conventional sampling easily causes problems such as sample selection omission or insufficient sample amount, and further influences the judgment on the actual investigation work effect.
Therefore, how to select the key sampling object by using the spatial attribute characteristics of the sample points becomes a technical problem to be solved urgently.
Disclosure of Invention
The invention provides a sampling object determining method and device, which are used for selecting a key sampling object by combining with the spatial attribute characteristics of sample points.
In order to solve the technical problem, the embodiment of the application adopts the following technical scheme: the invention provides a sampling object determining method, which comprises the following steps:
acquiring position information of each sampling object;
determining a road closest to the sampling object according to the position information;
and determining the sampling object with the space access degree between the sampling objects and the nearest road larger than the preset access degree as an important sampling object.
The beneficial effect of this application lies in: in this embodiment, the key sampling object is determined by using the spatial attribute characteristics of the sample points. According to the position information of the sampling object, the space access degree of the sampling object is determined, and the area with the low space access degree is used as the key sampling object, so that the problems of selection omission or insufficient sample size of the sampling object in the traditional sampling survey are avoided.
In one embodiment, further comprising:
acquiring a remote sensing image containing a target area;
the acquiring the position information of each sampling object includes:
and acquiring the position information of each sampling object in the target area in the remote sensing image.
In one embodiment, the determining a road closest to the sampling object according to the location information includes:
acquiring a road in the remote sensing image;
analyzing a road grading buffer area of the road, and determining the road with the distance less than a first distance from the sampling object by combining the position information of the sampling object;
when there are a plurality of roads having a distance less than a first distance from the sampling object, a road closest to the sampling object is determined from among the plurality of roads.
In one embodiment, the determining a road closest to the sampling object from the plurality of roads includes:
determining a road closest to a spatial distance of the sampling object from the plurality of roads;
or
Calculating the arrival time between the sampling object and the plurality of roads;
and determining the road corresponding to the minimum reaching time as the road closest to the sampling object.
In one embodiment, the calculating the time of arrival between the sampling object and the plurality of roads includes:
acquiring the landform types between the sampling object and the plurality of roads;
determining the speed of the sampling object reaching each road by combining with the landform types, wherein the landform types comprise plains, hills, basins, mountains and plateaus, and the road information comprises expressways, national roads, provincial roads, county roads and country roads;
and calculating the reaching time of the sampling object to each road according to the speed of the sampling object to each road.
The beneficial effect of this embodiment lies in: when the access time is used for judging the spatial access of the sampling object, the geographic information technology is combined, the multiple spatial attribute characteristics (geographic position, landform type and road information) of the sampling object are utilized, the influence of different geographic characteristics on the vehicle speed is fully considered, the basis for objectively judging the spatial access is provided for the execution of a computer, the artificial subjective interference is avoided, and the accuracy of selecting the sample point is improved.
In one embodiment, the spatial access degree includes a spatial distance, and the determining that a sampling object with a spatial access degree between the closest roads in the sampling objects is greater than a preset access degree is an emphasized sampling object includes:
judging whether the space distance between each sampling object and the nearest road is greater than a second distance or not;
and determining the sampling object with the spatial distance between the sampling object and the nearest road larger than the second distance as an emphasis sampling object.
In one embodiment, the spatial access degree includes an access time, and the determining that a sampling object with a spatial access degree between the closest road and the corresponding sampling object is a key sampling object includes:
judging whether the reaching time between each sampling object and the nearest road is greater than preset time or not;
and determining the sampling object with the reaching time between the nearest road in each sampling object to be an important sampling object, wherein the reaching time is more than the preset time.
In one embodiment, the method further comprises:
acquiring the number of all selected sampling objects;
judging whether the quantity proportion of the selected key sampling objects to all the selected sampling objects reaches a preset proportion or not;
and when the quantity ratio of the selected key sampling objects to all the selected sampling objects reaches a preset ratio, determining that the key sampling objects are selected completely.
In one embodiment, further comprising:
when the quantity ratio of the selected key sampling objects to all the selected sampling objects does not reach a preset ratio, adjusting the accessibility of the preset space;
and reselecting the key sampling object according to the adjusted preset space accessibility threshold until the number proportion of the key sampling object to all the selected sampling objects reaches a preset proportion.
The beneficial effect of this embodiment lies in: by setting a preset proportion and adjusting the range of the space accessibility, the survey village can be ensured to reach a specific proportion in all sampling objects, so that the sampling samples can be objectively and truly used for reflecting the overall information.
The present invention also provides a sample object determining apparatus, comprising:
the acquisition module is used for acquiring the position information of each sampling object;
the first determining module is used for determining a road closest to the sampling object according to the position information;
and the second determining module is used for determining the sampling object of which the space access degree between the sampling object and the nearest road is greater than the preset access degree as the key sampling object.
In one embodiment, further comprising:
the image acquisition module is used for acquiring a remote sensing image containing a target area;
the acquisition module comprises:
and the first acquisition submodule is used for acquiring the position information of the sampling object in the target area in the remote sensing image.
In one embodiment, the first determining module includes:
the second sub-acquisition module is used for acquiring a road in the remote sensing image;
the analysis submodule is used for carrying out road grading buffer area analysis on the road and determining the road with the distance less than a first distance from the sampling object by combining the position information of the sampling object;
a first determining sub-module for determining a road closest to the sampling object from among a plurality of roads when there are a plurality of roads having a distance less than a first distance from the sampling object.
In one embodiment, the first determining submodule is specifically configured to:
determining a road closest to a spatial distance of the sampling object from the plurality of roads;
or, the first determining submodule is specifically configured to:
calculating the time of arrival between the sampling object and the plurality of roads;
and determining the road corresponding to the minimum reaching time as the road closest to the sampling object from the reaching times.
In one embodiment, the calculating the time of arrival between the sampling object and the plurality of roads includes:
acquiring landform types between the sampling object and the plurality of roads;
determining the speed of the sampling object reaching each road by combining with the landform types, wherein the landform types comprise plains, hills, basins, mountains and plateaus, and the road information comprises expressways, national roads, provincial roads, county roads and country roads;
and calculating the reaching time of the sampling object to each road according to the speed of the sampling object to each road.
In one embodiment, the spatial access comprises a spatial distance, and the second determining module comprises:
the first judgment sub-module is used for judging whether the space distance between each sampling object and the nearest road is greater than a second distance or not;
and the first selection submodule is used for determining the sampling object with the spatial distance between the sampling object and the nearest road larger than the second distance as the key sampling object.
In one embodiment, the spatial accessibility includes an access time, and the second determining module includes:
the second judgment submodule is used for judging whether the access time between each sampling object and the nearest road is greater than the preset time or not;
and the second selection submodule is used for determining the sampling object with the arrival time between the sampling object and the nearest road being greater than the preset time as the key sampling object.
In one embodiment, the apparatus further comprises:
the quantity acquisition module is used for acquiring the quantity of all the selected sampling objects;
the proportion judging module is used for judging whether the quantity proportion of the selected key sampling objects to all the selected sampling objects reaches a preset proportion or not;
and the third determining module is used for determining that the selection of the key sampling objects is finished when the number proportion of the selected key sampling objects to all the selected sampling objects reaches a preset proportion.
In one embodiment, the apparatus further comprises:
the adjusting module is used for adjusting the accessibility of the preset space when the quantity ratio of the selected key sampling objects to all the selected sampling objects does not reach a preset ratio;
and the selecting module is used for reselecting the key sampling object according to the adjusted preset space accessibility threshold until the number proportion of the key sampling object to all the selected sampling objects reaches a preset proportion.
The technical solution of the present invention is further described in detail by the accompanying drawings and embodiments.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention and not to limit the invention. In the drawings:
FIG. 1 is a flow chart of a method of sample object determination in accordance with an embodiment of the present invention;
FIG. 2 is a flow chart of a method for sample object determination in another embodiment of the present invention;
fig. 3 is a block diagram of a sample object determining apparatus according to an embodiment of the present invention;
fig. 4 is a block diagram of a sample object determining apparatus according to another embodiment of the present invention;
FIG. 5 is a chart illustrating the number of surveys in accordance with an embodiment of the present invention.
Detailed Description
The preferred embodiments of the present invention will be described in conjunction with the accompanying drawings, and it will be understood that they are described herein for the purpose of illustration and explanation and not limitation.
Fig. 1 shows a method for determining a sample object according to an embodiment of the present invention, as shown in fig. 1, the method includes the following steps S11 to S13:
in step S11, position information of each sampling object is acquired;
in step S12, a road closest to the sampling target is determined based on the position information;
in step S13, a sampling object whose spatial access degree with respect to the nearest road is greater than a preset access degree among the respective sampling objects is determined as an emphasized sampling object.
In this embodiment, the position information of each sampling object is obtained, the total range of the sampling object can be obtained through an information system, the position information of the sampling object can be obtained from the system, and when the system does not have the position information, the position information can also be obtained through data such as a map or a remote sensing image; determining a road closest to the sampling object according to the position information, and determining the road closest to the sampling object by combining a geographic information technology; and determining a sampling object with a space access degree between each sampling object and the nearest road being greater than a preset access degree as a key sampling object, wherein the space access degree can comprise distance or time, and the space access degree can also be determined comprehensively by considering the development degree of a local traffic network, namely the factors such as landform environment, road gradient and road connectivity.
Since the area with low spatial accessibility is the key area of the survey, the area with low accessibility is selected as the key sampling object to reflect the real situation of the survey more objectively. However, since these areas are often scattered in areas with non-concentrated population distributions, the sampling sample selection is not objective through traditional sampling. Therefore, the embodiment determines the key sampling object by using the spatial attribute feature of the sample point. According to the position information of the sampling object, the space accessibility of the sampling object is determined, and the area with low space accessibility is used as a key sampling object, so that the problems of selection missing or insufficient sample size of the sampling object in the traditional sampling survey are solved.
In one embodiment, the method comprises the steps of:
acquiring a remote sensing image containing a target area;
the above step S11 may be implemented as the following steps:
and acquiring the position information of each sampling object in the target area in the remote sensing image.
In the embodiment, a remote sensing image containing a target area is obtained; and acquiring the position information of each sampling object in the target area in the remote sensing image through the remote sensing image.
By applying the modern remote sensing and geographic information technology to sampling investigation, the position information in the sampling sample can be extracted in batches, the manual workload is reduced, and the determination efficiency of the key sampling object is improved.
In one embodiment, the above step S12 can be implemented as the following steps A1-A3:
in the step A1, acquiring a road in a remote sensing image;
in the step A2, the road is subjected to road grading buffer area analysis, and the road with the distance less than the first distance from the sampling object is determined by combining the position information of the sampling object;
in step A3, when the road having a distance less than the first distance from the sampling object is plural, a road closest to the sampling object is determined from the plural roads.
In the embodiment, a road in a remote sensing image is obtained; analyzing a road grading buffer area of the road, setting buffer areas with different ranges according to roads with different grades, and determining the road with the distance less than a first distance from the sampling object by combining the position information of the sampling object; when the road having a distance to the sampling object smaller than the first distance is plural, a road closest to the sampling object is determined from the plural roads.
In the present embodiment, the road grade may be set to a provincial road, a prefecture road, an expressway, or the like. After the remote sensing image is obtained, a first distance is set for a sampling object by combining a geographic information technology, roads within a certain range from the sampling object are selected, and then the roads closest to the sampling object are selected from the range.
The beneficial effect of this embodiment lies in: the remote sensing and geographic information technology is combined, the data processing speed is improved, and the selection of the nearest road is determined based on the spatial data analysis, so that the objectivity of the selection of the sampling object is ensured.
In one embodiment, the step A3 can be implemented as the following step B1 or steps B2-B3:
in step B1, a road closest to the spatial distance of the sampling object is determined from the plurality of roads;
in step B2, the arrival time between the sampling object and the plurality of roads is calculated;
in step B3, the road corresponding to the minimum arrival time is determined as the road closest to the sampling target.
In reality, different region types have different judgment on the accessibility. For example, in plain areas, the spatial distance reference is strong, the judgment is objective, and the computer is fast to execute; however, for mountainous regions, the spatial distance reference meaning is not great, and the real access time needs to be determined by combining the speeds of different road sections.
In this embodiment, one of the two ways of spatial distance and arrival time may be selected as the basis for determining the closest road to the sampling object. And when the space distance is selected as a judgment basis, determining the road closest to the space distance of the sampling object from the plurality of roads. The access time is selected as a judgment basis, the direct access time of the sampling object and the plurality of roads is calculated, and the road corresponding to the minimum access time is determined to be the road closest to the sampling object.
The beneficial effect of this embodiment lies in: two selection modes of the nearest road are set, alternatives are provided for different practical situations, and the nearest road to the sampling object is objectively determined.
In one embodiment, as shown in FIG. 2, the above step B2 may be implemented as the following steps S21-S23:
in step S21, a landform type between the sampling object and the plurality of roads is acquired;
in step S22, determining the speed of the sampling object reaching each road in combination with the types of landforms, wherein the types of landforms include plains, hills, basins, mountains and plateaus, and the road information includes highways, national roads, provincial roads, counties and country roads;
in step S23, the arrival time of the sampling object to each road is calculated based on the speed at which the sampling object arrives at each road.
In the embodiment, the landform types between the sampling object and the plurality of roads are obtained; as shown in table 1, the speed of the sampling object reaching each road is determined in order to combine the landform types including plains, hills, basins, mountains and plateaus, and the road information includes expressways, national roads, provincial roads, counties and country roads; and calculating the reaching time of the sampling object to each road according to the speed of the sampling object to each road, wherein when the set road grade comprises other road sections with different grades, the reaching time is the sum of the time of each road section.
TABLE 1 road speed per hour for different grades
It should be noted that, information such as the slope and the direction of slope of different roads can be obtained according to the remote sensing information, the speed of each road segment is further refined, and the speed per hour of different roads is determined. In addition, the developed degree of the traffic network in the investigation region can be obtained from the remote sensing information or the traffic network, and different weights can be given to the spatial access degree of the sampling object according to the perfect degree of the traffic network.
The beneficial effect of this embodiment lies in: when the access time is used for judging the spatial access of the sampling object, the geographic information technology is combined, multiple spatial attribute characteristics (geographic position, landform type and road information) of the sampling object are utilized, the influence of different geographic characteristics on the vehicle speed is fully considered, an objective basis for judging the spatial access is provided for computer execution, artificial subjective interference is avoided, and the accuracy of selecting sample points is improved.
In one embodiment, the spatial accessibility includes spatial distance, and the step S13 can be implemented as the following steps C1-C2:
in step C1, it is determined whether the spatial distance between each sampling object and the nearest road is greater than a second distance;
in step C2, a sampling object whose spatial distance from the nearest road is greater than the second distance among the respective sampling objects is determined as an emphasized sampling object.
In this embodiment, a method for selecting an oversampled object by spatial distance is provided. Judging whether the space distance between each sampling object and the nearest road is greater than a second distance or not; and determining the sampling object with the space distance between the sampling object and the nearest road larger than the second distance as the key sampling object.
It should be noted that the method can also use a natural breakpoint method to divide the spatial accessibility levels of different sample villages, and take the sampling object with a low spatial accessibility level as the key sampling object.
The beneficial effect of this embodiment lies in: and taking the space distance as a judgment basis of the space accessibility, and carrying out quantitative calculation and classification on the space accessibility to accurately identify key sampling objects in the sampling objects.
In one embodiment, where the spatial accessibility includes an access time, the above step S13 may be implemented as the following steps D1-D2:
in step D1, judging whether the reaching time between each sampling object and the nearest road is more than the preset time or not;
in step D2, a sampling object whose arrival time with the nearest road is greater than a preset time among the sampling objects is determined as an emphasized sampling object.
In this embodiment, a method for selecting an oversampled object by access time is provided. Judging whether the reaching time between each sampling object and the nearest road is greater than preset time or not; and determining the sampling object with the reaching time between the nearest road in each sampling object to be an important sampling object, wherein the reaching time is more than the preset time.
It should be noted that, for areas with different landform types such as plains, mountains, plateaus and the like, the method can also utilize a natural breakpoint method to divide the spatial accessibility levels of different sample villages, and a sampling object with a low spatial accessibility level is taken as a key sampling object.
After the spatial accessibility is determined, factors such as a geomorphic environment and a productivity level can be combined, and a survey index of each sampling object can be determined through the following formula:
wherein, the survey index of the Y sampling object;
alpha is road perfection, when the number of the road of the sampling object reaching the local business center/government center is 1, the value is 0.2, when 2, the value is 0.6, when 3, the value is 1, when more than 3, the value is 1.2:
g is the productivity level of the sampling object within a preset period;
d is the local landform level, the plain value is 1.2, the hilly basin value is 1, and the mountain plateau value is 0.8;
T 1 is the time of arrival between the sampling object and the nearest road;
T 2 the minimum time for the sampled object to reach the local business/government center;
S 1 the shortest vehicle distance between the sampling object and the nearest road;
S 2 the shortest distance for the sampled object to reach the local business/government center.
According to the formula, after the survey index of each sampling object is obtained, the higher the survey index is, the lower the reaching degree of the sampling object is, and the sampling object is taken as a key survey area.
The beneficial effect of this embodiment lies in: the access time is used as a judgment basis of the spatial access degree, and the spatial access degree is quantitatively calculated and graded, so that the key sampling object in the sampling objects is accurately identified.
In one embodiment, the method may also be implemented as the following steps E1-E3:
in the step E1, the number of all selected sampling objects is obtained;
in step E2, judging whether the number ratio of the selected key sampling objects to all selected sampling objects reaches a preset ratio;
in step E3, when the number ratio of the selected key sampling objects to all selected key sampling objects reaches a preset ratio, it is determined that the key sampling objects are selected completely.
In this embodiment, the number of all selected sampling objects is obtained; judging whether the quantity proportion of the selected key sampling objects to all the selected sampling objects reaches a preset proportion or not; and when the quantity ratio of the selected key sampling object to all the selected sampling objects reaches a preset ratio, determining that the key sampling object is selected completely.
The beneficial effect of this embodiment lies in: by setting the preset proportion, the sampling object is ensured to reach the specific proportion in the whole body, and the inaccurate result caused by insufficient sample amount is avoided.
In one embodiment, the method may also be implemented as the following steps F1-F2:
in step F1, when the number ratio of the selected key sampling objects to all the selected sampling objects does not reach a preset ratio, adjusting the accessibility of a preset space;
in step F2, the key sampling object is reselected according to the adjusted preset spatial reach threshold until the number ratio of the key sampling object to all the selected sampling objects reaches a preset ratio.
In this embodiment, when the quantity ratio of the selected key sampling object to all the selected sampling objects does not reach the preset ratio, the accessibility of the preset space is adjusted; and reselecting the key sampling objects according to the adjusted preset space accessibility threshold until the number proportion of the key sampling objects to all the selected sampling objects reaches a preset proportion.
Specifically, in this embodiment, the key sampling object is selected by the following method:
first, the total amount of each province sample survey is determined by the following formula:
wherein n represents the total amount of the sample survey of each province; n represents a total sample, and the data is extracted according to the filing card data of each province; z =1.96, representing a statistic with 95% confidence; e represents an acceptable sampling error range of ± 1%;
indicating the degree of sample variation.
Next, a survey county is selected from the provinces. According to different regional types of counties and counties in each province and according to the scale of various population in the counties and counties, the selection proportion and the number of the counties and the counties in different types are determined. Fig. 5 is a chart of the number of surveys in this embodiment.
Then, a key sampling object, namely, a survey village is selected from the survey county. Acquiring position information of each sampling object in a survey county; determining the vehicle speeds of roads of different grades by combining the landform types; calculating the time from the administrative village to the determination of each county road from the county road within 40km from each administrative village, and selecting the road with the minimum arrival time as the nearest road; and when the time for the sampling object to reach the nearest road exceeds 2 hours, determining the sampling object as an important sampling object. Setting the proportion of the key sampling objects in the survey county to be 30%, and adjusting the reaching time until the preset proportion is reached when the proportion of the survey county selected by the method is insufficient.
Finally, the surveyor is selected from the survey village. After the investigation village is obtained, the investigation households are extracted according to the specific investigation monitoring conditions of each household. Random sampling investigation is adopted for investigators which are continuously monitored by combining local practice; for the surveyors who do not continuously monitor, the missing assessment population is identified through a census mode.
Similarly, the embodiment can also divide the edge corner area sampling object by combining the proportion of the target object and the productivity level, and ensure that the proportion of the number of the sampling villages in the area to the total number of the sampling villages reaches a specific proportion.
The beneficial effect of this embodiment lies in: by setting the preset proportion, when the proportion of the sampling sample is less than the preset proportion, the preset value of the space accessibility is adjusted, so that the sampling object is ensured to reach the specific proportion in the whole, and the inaccurate result caused by insufficient sample volume is avoided.
As shown in fig. 3, the present invention also provides a sample object determining apparatus, including:
an obtaining module 31, configured to obtain position information of each sampling object;
a first determination module 32, configured to determine a road closest to the sampling object according to the location information;
and a second determining module 33, configured to determine, as an emphasized sampling object, a sampling object whose spatial access degree with respect to a nearest road is greater than a preset access degree among the sampling objects.
In one embodiment, the above sampling object determining apparatus further includes:
the image acquisition module is used for acquiring a remote sensing image containing a target area;
an acquisition module 31, comprising:
and the first acquisition sub-module is used for acquiring the position information of the sampling object in the target area in the remote sensing image.
In one embodiment, the first determination module 32 includes:
the second sub-acquisition module is used for acquiring a road in the remote sensing image;
the analysis submodule is used for carrying out road grading buffer area analysis on the road and determining the road with the distance less than the first distance from the sampling object by combining the position information of the sampling object;
and a first determining sub-module for determining a road closest to the sampling object from among the plurality of roads when there are a plurality of roads having a distance to the sampling object smaller than the first distance.
In one embodiment, the first determining submodule is specifically configured to:
determining a road closest to a spatial distance of the sampling object from the plurality of roads;
or, the first determining submodule is specifically configured to:
calculating the time of arrival between the sampling object and a plurality of roads;
and determining the road corresponding to the minimum reaching time as the road closest to the sampling object from the reaching times.
In one embodiment, the calculating, in the first determining sub-module, the time of arrival between the sampling object and the plurality of roads includes:
acquiring the landform types between the sampling object and the plurality of roads;
determining the speed of the sampling object reaching each road by combining with the landform types, wherein the landform types comprise plains, hills, basins, mountains and plateaus, and the road information comprises expressways, national roads, provincial roads, county roads and country roads;
and calculating the reaching time of the sampling object to each road according to the speed of the sampling object reaching each road.
In one embodiment, the spatial access comprises a spatial distance, and the second determining module 33 comprises:
the first judgment submodule is used for judging whether the space distance between each sampling object and the nearest road is greater than the second distance or not;
and the first selection submodule is used for determining the sampling object with the spatial distance between the sampling object and the nearest road larger than the second distance in each sampling object as an emphasis sampling object.
In one embodiment, the spatial accessibility includes an access time, and the second determining module 33 includes:
the second judgment sub-module is used for judging whether the access time between each sampling object and the nearest road is greater than the preset time or not;
and the second selection submodule is used for determining the sampling object with the arrival time between the sampling object and the nearest road being greater than the preset time as the key sampling object.
In one embodiment, as shown in fig. 4, the apparatus further comprises:
a quantity obtaining module 41, configured to obtain the quantity of all selected sampling objects;
a proportion judging module 42, configured to judge whether the quantity proportion between the selected key sampling object and all the selected sampling objects reaches a preset proportion;
and a third determining module 43, configured to determine that the selection of the key sampling object is completed when the number ratio of the selected key sampling object to all the selected sampling objects reaches a preset ratio.
In one embodiment, the apparatus further comprises:
the adjusting module is used for adjusting the accessibility of the preset space when the quantity ratio of the selected key sampling objects to all the selected sampling objects does not reach the preset ratio;
and the selecting module is used for reselecting the key sampling object according to the adjusted preset space accessibility threshold until the number proportion of the key sampling object to all the selected sampling objects reaches a preset proportion.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
It will be apparent to those skilled in the art that various changes and modifications may be made in the present invention without departing from the spirit and scope of the invention. Thus, if such modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include such modifications and variations.
Claims (5)
1. A method for determining poor sample objects, comprising:
s11, acquiring position information of each sampling object, and acquiring a remote sensing image containing a target area;
the acquiring the position information of each sampling object comprises:
acquiring position information of each sampling object in the target area in the remote sensing image;
step S12, determining a road closest to the sampling object according to the position information;
the determining a road closest to the sampling object according to the position information includes:
a1, acquiring a road in the remote sensing image;
step A2, carrying out road grading buffer area analysis on the road, and determining the road with the distance less than a first distance from the sampling object by combining the position information of the sampling object;
step A3, when the road with the distance less than the first distance to the sampling object is a plurality of roads, determining the road closest to the sampling object from the plurality of roads;
the determining a road closest to the sampling object from among the plurality of roads includes:
step B1, determining a road closest to the space distance of the sampling object from the plurality of roads;
step B2, calculating the arrival time between the sampling object and the plurality of roads;
the calculating the time of arrival between the sampling object and the plurality of roads includes:
acquiring landform types between the sampling object and the plurality of roads;
determining the speed of the sampling object reaching each road by combining with the landform types, wherein the landform types comprise plains, hills, basins, mountains and plateaus, and the road information comprises expressways, national roads, provincial roads, county roads and country roads;
calculating the reaching time of the sampling object to each road according to the speed of the sampling object reaching each road;
step B3, determining the road corresponding to the minimum reaching time as the road closest to the sampling object;
step S13, determining the sampling object of which the space access degree between each sampling object and the nearest road is greater than a preset access degree as a key sampling object; the spatial degree of access comprises a spatial distance or an access time;
the sampling object is a poverty village, and the key sampling object is a survey village;
after determining the spatial accessibility, the index of investigation for each sample object is determined by the following formula:
wherein, the survey index of the Y sampling object; wherein, the higher the survey index is, the lower the access degree of the sampling object is;
alpha is road perfection, when the number of the road of the sampling object reaching the local business center/government center is 1, the value is 0.2, when 2, the value is 0.6, when 3, the value is 1, when more than 3, the value is 1.2:
g is the productivity level of the sampling object within a preset period;
d is the local landform level, the plain value is 1.2, the hilly basin value is 1, and the mountain plateau value is 0.8;
t1 is the time of arrival between the sampling object and the nearest road;
t2 is the minimum time for the sample object to reach the local business/government center;
s1, the shortest distance between a sampling object and the nearest road is obtained;
s2, the shortest distance from the sampling object to the local business center/government center is obtained;
and after the investigation index of each sampling object is obtained according to the formula, selecting the sampling object of which the investigation index is greater than the preset investigation index as a key sampling object.
2. The method of claim 1, wherein the spatial accessibility includes a spatial distance, and the determining that a sampling object among the sampling objects having a spatial accessibility with respect to a nearest road that is greater than a preset accessibility is an emphasized sampling object comprises:
judging whether the space distance between each sampling object and the nearest road is greater than a second distance or not;
and determining the sampling object with the spatial distance between the sampling object and the nearest road larger than the second distance as an emphasis sampling object.
3. The method of claim 1, wherein the spatial accessibility includes an accessibility time, and the determining that a sampling object among the sampling objects having a spatial accessibility with a nearest road greater than a preset accessibility is an emphasized sampling object comprises:
judging whether the reaching time between each sampling object and the nearest road is greater than preset time or not;
and determining the sampling object with the arrival time between the sampling objects and the nearest road being more than the preset time as the key sampling object.
4. The method of claim 1, wherein the method further comprises:
acquiring the number of all selected poverty-stricken villages;
judging whether the quantity ratio of the selected key sampling objects to all the selected poverty-stricken villages reaches a preset ratio or not;
and when the quantity ratio of the selected key sampling object to all the selected poverty-stricken villages reaches a preset ratio, determining that the key sampling object is selected completely.
5. The method of claim 4, wherein the method further comprises:
when the quantity ratio of the selected key sampling objects to all the selected poverty-stricken villages does not reach a preset ratio, adjusting the accessibility of the preset space;
and re-selecting the key sampling object according to the adjusted preset space accessibility threshold until the number proportion of the key sampling object to all the selected poverty-stricken villages reaches a preset proportion.
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