Urban and rural space use evaluation method using mobile phone signaling data

Abstract

The invention discloses an urban and rural space use evaluation method using mobile phone signaling data, and the method comprises the following steps: 1, carrying out the evaluation of the urban and rural space use by using the mobile phone signaling data; the method comprises the following steps: selecting data to evaluate urban and rural areas, selecting urban and rural areas needing space evaluation, performing integrated planning on geographic attributes of the areas, and acquiring mobile phone signaling data of residents in the selected urban and rural areas, in the using process, cross comparison is carried out through online data, special crowds in special occupations and office areas are registered, and meanwhile, offline data registration and online and offline data comparison are carried out on residents who are subjected to long-term cultivation and treatment outside due to diseases; the influence of comparison of residents who work at home or free employees stay at home for a long time or residents who recuperate and treat for a long time outside due to diseases on data can be eliminated, and the accuracy of spatial evaluation data is ensured.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of urban and rural space evaluation, in particular to a method for evaluating urban and rural space use by using mobile signaling data. BACKGROUND

[0002] Reasonable use of urban and rural space can effectively save land, realize reasonable allocation of different regional needs, reduce regional span resource waste, maintain sustainable development of urban and rural areas, properly use urban and rural space, realize intensive development, in addition, reasonable use of urban and rural space can effectively improve the living conditions of residents, introduce facilities and services needed by local residents, provide high-quality and suitable living environment for local residents, and also can more effectively use space and improve the living standards of residents.

[0003] In the prior art, a method for constructing an urban-rural integration ecological security pattern is disclosed in the publication "CN114004416A", which comprises the following steps: determining the research target and collecting data, classifying urban and rural landscape types, establishing a model and constructing a spatial distribution map, ecological security risk assessment, ecological security pattern construction, application of ecological security pattern resistance model and comprehensive ecological security pattern optimization; the present application adopts a unified systematic pattern construction method, which is convenient for use by staff, the constructed framework is clear, the relationship model between environmental variables and ecological security pattern is directly established, and the problem of generating a large amount of transition data in the prior art is avoided, compared with the prior art, the present application can more objectively and scientifically construct the ecological security pattern of each region, and has good reference value in actual use.

[0004] However, the prior art still has great deficiencies, such as:

[0005] In the above device and the prior art, during the evaluation of regional space, the resident data is divided into different types, including children, middle-aged and old people, these three groups of people have different resource needs in the region in daily life, which are respectively represented as medical resources, educational resources, recreational place resources and factory resources, if the mobile signaling data can identify the age group and working area of residents in a specific region, but for residents who take home office or are long-term freelancers, or for residents who are long-term recuperation and treatment outside due to illness, the mobile signaling data cannot provide the actual needs of these residents, so that the urban and rural space utilization and construction process cannot be reasonably adjusted according to the regional differences. SUMMARY

[0006] The present application aims to provide a method for evaluating urban and rural space use by using mobile signaling data to solve the problems raised in the background art.

[0007] In order to achieve the above object, the present application provides the following technical scheme: a kind of urban and rural space use evaluation method using mobile phone signaling data, comprising the following steps:

[0008] Selected data evaluates urban and rural areas, selected urban and rural areas that need to be evaluated using space, so that the geographical properties of the region are integrated planning, planning area is not more than three, to adapt to the evaluation data sample comparison needs;

[0009] The mobile phone signaling data of the residents in the selected urban and rural areas is collected, and the signaling data is classified according to different data types during data collection, and the age level of the residents in the area is distinguished.

[0010] Sample area resident living space interval distance data collection, the proximity of different areas of the sample urban and rural areas is classified;

[0011] Offline data collection, through the above classification area resident data collection by street office or area residents committee, through the comparison of online and offline data, the residents of older age or younger age are distinguished, and the medical condition, education condition, recreational place and number of workshops of different residents in the divided area are collected.

[0012] Preferably, the mobile phone signaling data includes location exchange data, mobile internet data and short message call data, and the geographical attribute is the residence distribution of the residents in the urban and rural areas.

[0013] Preferably, the processing step of collecting the mobile phone signaling data of the personnel in the selected urban and rural areas comprises:

[0014] S1: standard classification of mobile phone signaling data;

[0015] S2: based on the location exchange data, mobile internet data and short message call data in the mobile phone signaling data, determine the age of the user residents in the area, and classify the user resident age level data;

[0016] S3: based on the location exchange data and short message call data in the mobile phone signaling data, and the user resident age level data is classified twice.

[0017] Preferably, if the location exchange data and the mobile internet data are greater than the short message call data respectively, it indicates that the number of young people in the area mobile phone users is more.

[0018] Preferably, the offline data includes resident data, the number of medical and educational places, the number of recreational places and the number of workshops, and the offline data is integrated and compared with the mobile phone signaling data after collection.

[0019] Preferably, the local resident data includes age range data and occupation data, the occupation data reflects the work type distribution of the local residents, and the age range data indicates the child, middle-aged and elderly resident user distribution of the local users.

[0020] Preferably, the occupation data includes the number of workers and the number of non-workers, and the number of non-workers and the number of workers indicate the proportion of worker residents and non-worker residents in the region.

[0021] Preferably, the elderly resident data is less than the middle-aged resident data, and the middle-aged resident data is greater than the child data, if the number of workers is greater than the number of non-workers, if the number of workers is less than the number of medical and educational institutions, if the number of leisure places is less than the number of medical and educational institutions, and if all the above conditions are met, it indicates that the number of leisure places, workers and educational institutions in the space of the region is unreasonable.

[0022] Preferably, if the child data is greater than the middle-aged resident data, and the middle-aged resident data is less than the elderly resident data, if the number of non-workers is greater than the number of workers, if the number of medical and educational institutions is less than the number of workers which is greater than the number of leisure places, and if all the above conditions are met, it indicates that the medical and educational institutions in the space of the region are unreasonable.

[0023] Preferably, if the child data is greater than the elderly resident data, if the number of medical and educational institutions is greater than the number of leisure places which is greater than the number of workers, and if all the above conditions are met, it indicates that the number of medical and educational institutions in the space of the region is reasonable.

[0024] Compared with the prior art, the present application has the following beneficial effects:

[0025] 1. The space evaluation divides the urban and rural areas reasonably, so that a control group is formed in the space evaluation process of different regions, which facilitates the judgment of the space evaluation result according to the actual distribution of local resources.

[0026] 2. The mobile phone signaling data is collected online, the age range of the users is divided, and the number of residents of different age ranges in each part of the region is understood under the premise of regional division, which provides online data support for the space evaluation process.

[0027] 3. The individual data of the local residents in each divided region is collected offline, and cross comparison is made through online data to reduce data duplication, and the age, occupation and work area of the residents are registered, and special occupations and special groups in office areas are registered, and residents who are long-term recuperation and treatment due to illness are registered offline, which provides offline data support for the space evaluation process and ensures the accuracy of the data in the subsequent space evaluation process.

[0028] 4. In the process of space evaluation, the information accuracy is improved according to online and offline data support, and whether the setting of various resources in the current area is reasonable is judged according to the arrangement of the existing space resources and the comparison of online and offline data. Meanwhile, the comparison of online and offline data can exclude the influence of residents who work from home or are long-term residents due to illness, and ensure the accuracy of space evaluation data.

[0029] In the use process of the present application, first, the urban and rural areas are reasonably divided, then the distance data of each part of the urban and rural planning area is collected, and the resident online mobile phone signaling data is used as the basis, and the data is interacted with reference to offline data;

[0030] If there are more factories in the young adult worker residential area, it will make the young adults in the residential area more convenient to find a job, reduce the employment pressure, and reduce the commuting time. Compared with the long commuting distance, the more convenient and cost-saving transportation tools (such as bicycles or electric vehicles) can be replaced, the commuting cost is reduced, and the life pressure is reduced;

[0031] The setting of leisure places can reduce the work pressure of young adults, and based on the economic level of young adults, the consumption level of the region can be ensured, the resources are reasonably used, children and the elderly are usually prone to illness, so the medical resources in the area where children and the elderly live can provide corresponding protection for the life of children and the elderly. BRIEF DESCRIPTION OF DRAWINGS

[0032] Figure 1 The present application is a flow chart of the urban and rural space use evaluation method;

[0033] Figure 2 The present application is a flow chart of the urban and rural space use evaluation method in the first state;

[0034] Figure 3 The present application is a flow chart of the urban and rural space use evaluation method in the second state;

[0035] Figure 4 The present application is a flow chart of the regional information integration planning. DETAILED DESCRIPTION

[0036] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the present application.

[0037] Please refer toFigures 1-4 The present invention provides a technical solution:

[0038] Example 1: A method for assessing urban and rural spatial use using mobile phone signaling data, comprising the following steps;

[0039] Select urban and rural areas for data assessment, and select the urban and rural areas that need to be used for spatial assessment. Then, integrate and plan the geographical attributes of the area. The planned area shall not exceed three to adapt to the needs of comparison of assessment data samples. In this embodiment, the urban and rural areas to be assessed are divided into limited areas, with no more than three. This ensures that the samples have multiple control groups, while avoiding the situation where the area division is too small, resulting in too much information in the samples that does not have assessment characteristics. If the area is too small, it may lead to the distribution of a certain resource in a single area being too dense or too scattered. The planned samples can be compared with each other in an internal regional manner, and the assessment process is more in line with the distribution of resources in the current area.

[0040] Mobile phone signaling data of residents in selected urban and rural areas was collected. During the data collection process, the signaling data was sampled and classified according to different data types to distinguish the age groups of residents in the area. In this embodiment, the data was classified according to the category of signaling data, which includes location exchange data, mobile internet data, and SMS / call data. If the location exchange data is around 6:00 AM and the distance generated by the location exchange data is short and located near the origin, it indicates that this part of the signal mostly comes from the elderly. The elderly have the habit of getting up early to exercise and buy groceries for their families. When exercising, the elderly will exercise in nearby parks. If the location exchange data is at 8:00 AM and 6:00 PM and the location exchange data is regular, it indicates that this part of the data comes from young and middle-aged people. This is because young and middle-aged people bear the economic pressure of their families and need to work to earn money. At the same time, due to the high level of education, the main occupations of young and middle-aged people are divided into workers or non-workers. The number of factories in the area directly related to the occupations of young and middle-aged workers is crucial. A higher number of factories in the residential areas of young and middle-aged workers makes employment more convenient, reducing employment pressure and commuting time. Longer commutes can be replaced with more convenient and economical transportation (such as bicycles or electric bikes), lowering commuting costs and reducing life pressure. The availability of recreational facilities is also directly related to young and middle-aged workers. A large number of recreational facilities can reduce their work pressure and, based on their economic level, ensure the area's consumption level and the rational use of resources. While guardians of children are not allowed to provide mobile phones due to age restrictions, children and the elderly require appropriate educational and medical resources due to their special needs. Therefore, areas with a large number of children and the elderly should be equipped with abundant educational and medical resources.

[0041] Mobile signaling data includes location exchange data, mobile internet data, and SMS call data, with geographic attributes representing the distribution of residents' locations in urban and rural areas;

[0042] Processing steps for collecting mobile phone signaling data from individuals in selected urban and rural areas:

[0043] S1: Standardize and classify mobile signaling data;

[0044] S2: Based on location exchange data, mobile internet data, and SMS call data in mobile phone signaling data, determine the age range of users in the area and classify the age level data of users.

[0045] S3: Based on location exchange data and SMS call data in mobile phone signaling data, and performing secondary classification of user resident age level data, in this embodiment, the IMSI number obtained through location exchange data and mobile Internet access data in mobile phone signaling data can be repeatedly compared to distinguish between smartphones and non-smartphones. The user's age can be determined online, confirmed based on the registration information of the IMSI number, and the user's age level can be classified to understand the user's data flow.

[0046] If location-swapping data and mobile internet data are both greater than SMS and call data, it indicates that there are a large number of young and middle-aged mobile phone users in that area. In this embodiment, because young and middle-aged people bear the economic pressure of their families and need to work to earn money, although their work areas are different, the location-swapping data generated by each person in their specific work area is regular. Usually, only location-swapping data from home and workplace will appear on weekdays (these two areas generate the longest location-swapping data time. Although location-swapping data is also generated during commuting, the location changes constantly during commuting, so it is not identified as home or workplace). Therefore, this part of the location-swapping data is relatively regular and... The mobile internet usage of young and middle-aged people is frequent. When commuting by public transportation, they often use mobile data to browse information of interest to pass the time. This group of young and middle-aged people uses mobile data frequently. After get off work, young and middle-aged people also use mobile data to relax after a long day. This group of young and middle-aged people also uses mobile data frequently. In current life, some residents who work from home or are freelancers will have their location data set in one place for a long time. Residents who are recuperating or receiving treatment for illness may also have their location data set in one place for a long time. The actual needs of these residents cannot be reflected by location data alone.

[0047] Data on the distance between residents' residences in the sample area was collected, and the distance between residents' residences in different areas of the urban and rural areas was classified. In this embodiment, the classification of the distance between residents' residences is to adapt to the regional division, so that the specifications of the samples within the urban and rural areas are more reasonable, and to avoid violating the actual living conditions of local residents. Data on the distance between each residential area and educational and medical resources is also collected. If educational and medical resources are mostly distributed in areas far from residential areas and with underdeveloped transportation, this will lead to special groups not being able to obtain medical resources when needed, and will also cause inconvenience to children's commuting to school. It may also lead to the inefficient use of educational resources in the area. Due to the distance of schools and inconvenient commuting, schools may not be able to enroll all students, resulting in a waste of educational resources within the schools.

[0048] Example 2:

[0049] Based on Embodiment 1, this embodiment considers that if the actual living conditions of residents are analyzed solely through mobile phone signaling data, information about special groups may be missed. Children and elderly people may not be able to use mobile phones, and these groups cannot directly provide feedback on their living conditions through mobile phone signaling data. However, these groups are the ones who need medical and educational resources the most. Therefore, this embodiment sets up offline data collection, allowing assessors to understand the living conditions of these special groups offline. At the same time, the data of these individuals can be interacted with online to reduce information duplication and summarize information, thereby ensuring that the assessment process does not produce data omissions and that accurate assessments are made for various regions.

[0050] Offline data collection involves gathering resident data from the aforementioned categorized areas through street offices or neighborhood committees. By comparing online and offline data, older and younger residents are identified. Simultaneously, data on the medical conditions, educational resources, recreational facilities, and number of factories in different resident areas are collected. In this embodiment, the elderly have a habit of morning exercise and grocery shopping. They often exercise in nearby parks, and the provision of recreational facilities allows them to relax during their morning exercises. These facilities also reduce the work pressure on younger adults and, based on their economic level, ensure a reasonable level of consumption in the area, promoting the rational use of resources. Children and the elderly are typically more likely to... Illness is a concern, so providing appropriate medical resources in areas where children and the elderly reside can ensure their well-being. If factories are located in areas where young and middle-aged people live, it will make it easier for them to find employment, reducing employment pressure and commuting time. Compared to long commutes, they can use more convenient and economical means of transportation (such as bicycles or electric vehicles), reducing commuting costs and life pressure. At the same time, factories in residential areas should be classified, and the locations of heavy factories and chemical plants should be marked. Heavy factories and chemical plants produce substances and gases that are harmful to the human body during the production process. If heavy factories and chemical plants are located in densely populated areas, they will cause long-term health problems for the residents of the area.

[0051] Offline data includes local resident data, the number of medical and educational facilities, the number of leisure facilities, and the number of factories. After collection, offline data is integrated and compared with mobile phone signaling data. In this embodiment, the number of leisure facilities in a certain area determines the range of leisure and relaxation that residents in that area can enjoy. However, if there are too many leisure facilities in a certain area and too few residents, especially children, it will lead to a waste of leisure facility resources in that area, business conflicts between various leisure facilities, and affect industry development.

[0052] Local resident data includes age group data and occupation data. Occupation data reflects the distribution of different types of work among residents in the area, while age group data indicates the distribution of children, young and middle-aged, and elderly users in the area.

[0053] Occupational data includes the number of workers and non-workers. The number of non-workers and workers indicates the ratio of workers and non-workers among residents in the region. In this embodiment, if there are a large number of non-workers among the residents of the region, and there are also a large number of factories in the region, these residents will have to go to places further away from their residences to find work. This will cause these residents to compete with residents of other regions for jobs, resulting in increased employment pressure. At the same time, the long commuting distance and time will lead to greater living pressure and high commuting time costs for residents.

[0054] If the number of elderly residents is less than that of young and middle-aged residents, and the number of young and middle-aged residents is greater than that of children; if the number of workers is greater than the number of non-workers; if the number of factories is less than the number of medical and educational facilities; and if the number of leisure venues is less than the number of medical and educational facilities, then all of the above conditions are met simultaneously. This indicates that the number of leisure venues, factories, and educational venues in the area is not properly configured. In this embodiment, if there are many young and middle-aged residents and a large number of workers among them in the sample area, and if there are many factories in the residential areas of young and middle-aged workers, it will make it easier for them to find employment, reducing employment pressure and commuting time. Compared to long commutes, they can use more convenient and economical means of transportation (such as bicycles or electric vehicles), reducing commuting costs and life pressure. If there are few factories in the residential areas of young and middle-aged workers, it will lead to these residents being unable to find employment. The reluctance of young and middle-aged residents to seek employment further from their homes leads to increased competition for jobs with residents from other areas, resulting in greater employment pressure. Longer commutes also contribute to increased living costs and financial burdens. The availability of recreational facilities is also directly relevant to this demographic. A large number of young and middle-aged residents in an area can alleviate their work pressure and, given their economic status, ensure a healthy consumption level and efficient use of resources. However, an excessive number of medical and educational facilities in areas with a large young and middle-aged workforce can lead to a waste of these resources. Educational resources may be underutilized, as schools may be unable to fill their enrollment quotas due to distance and inconvenient commutes, resulting in wasted educational resources. Furthermore, students from other areas may be constrained by commuting time when applying to these schools.

[0055] If the number of children is greater than the number of young and middle-aged residents, and the number of young and middle-aged residents is less than the number of elderly residents; if the number of non-workers is greater than the number of workers; if the number of medical and educational facilities is less than the number of factories but greater than the number of leisure facilities, then if all of the above conditions are met, it indicates that the location of medical and educational facilities in the area is unreasonable. In this embodiment, if there are few young and middle-aged residents and a small number of non-workers among the residents, then the area should not have a large number of factories. If there are a large number of factories in the area, these residents will have to go to places further away from their residences to find work, which will lead to them having to compete with residents in other areas for jobs, resulting in increased employment pressure. At the same time, the long commuting distance will lead to greater living pressure and high commuting time costs for residents. If there are many children and elderly residents in the area, then the area should have a large number of medical, educational and leisure facilities. Medical and educational facilities can provide medical and living security for children and elderly residents. At the same time, the location of educational resources can allow children to receive a better education, and nearby schools can reduce the commuting pressure for children and reduce the dangers to children from long commuting distances.

[0056] If the number of children is greater than the number of elderly residents, if the number of medical and educational facilities is greater than the number of leisure facilities, which is greater than the number of factories, and if all of the above are true, it indicates that the number of educational and medical facilities in the area is reasonably set.

[0057] Working Principle: First, urban and rural areas are rationally divided. Then, distance data for each urban and rural planning area is collected. Spatial assessment results are judged based on the actual distribution of local resources, creating a control group for different areas during spatial assessment. Through the above technical solution, this invention uses residents' online mobile phone signaling data as a foundation and interacts with offline data. Data is classified according to the type of signaling data, including location exchange data, mobile internet data, and SMS / call data. The age groups of users are classified based on the patterns and characteristics of the signaling data. Special samples in the offline data are marked to reduce the impact of residents who cannot generate mobile phone signaling data. Simultaneously, the spatial usage within the area is assessed based on this resident data in conjunction with online data. If there are many factories in the residential areas of young and middle-aged workers, this will make employment more convenient for them, potentially reducing unemployment. To reduce commuting pressure and shorten travel time, more convenient and economical transportation options (such as bicycles or electric bikes) can be used to replace longer commutes, thus lowering commuting costs and reducing life stress. If there are many children and elderly residents in the area, there should be a greater number of medical, educational, and recreational facilities. Medical and educational facilities can provide medical and health care for children and the elderly, while educational resources can allow children to receive a better education. Closer schools can also reduce the commuting pressure on children and reduce the dangers of long commutes. If there are few factories in the residential area for young and middle-aged workers, these residents will have to go to places further away from their homes to find work, leading to increased employment pressure as they have to compete with residents from other areas for jobs. At the same time, long commutes will lead to greater life stress and high commuting time costs, indicating inefficient use of space in the area.

[0058] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A method for assessing urban and rural spatial use using mobile phone signaling data, characterized in that: Includes the following steps; Select urban and rural areas for data assessment, and select urban and rural areas that need to be assessed for spatial use. In this way, integrate and plan the geographical attributes of the area. The planning area shall not exceed three, so as to meet the needs of comparison of assessment data samples. Mobile phone signaling data of residents in selected urban and rural areas were collected. During the data collection process, the signaling data was classified according to different data types to distinguish the age groups of residents in the region. Data on the distance between residents' residences in the sample area was collected to classify the distance between residents' residences in different areas of the urban and rural sample areas; Offline data collection involves collecting resident data from the above-mentioned categorized areas through street offices or neighborhood committees. By comparing online and offline data, older or younger residents are identified. At the same time, data on the medical conditions, educational resources, recreational facilities, and number of factories in the different resident areas are collected.

2. The method for assessing urban and rural spatial use using mobile phone signaling data according to claim 1, characterized in that: The mobile signaling data includes location exchange data, mobile internet data, and SMS call data, and the geographic attribute is the distribution of residents' locations in the urban and rural areas.

3. The method for assessing urban and rural spatial use using mobile phone signaling data according to claim 2, characterized in that: The following processing steps are used to collect mobile phone signaling data from individuals in selected urban and rural areas: S1: Standardize and classify mobile signaling data; S2: Based on location exchange data, mobile internet data, and SMS call data in mobile phone signaling data, determine the age range of users in the area and classify the age level data of users. S3: Based on location exchange data and SMS call data in mobile phone signaling data, and perform secondary classification of user resident age level data.

4. The method for assessing urban and rural spatial use using mobile phone signaling data according to claim 3, characterized in that: If the location exchange data and the mobile internet data are both greater than the SMS call data, it indicates that there are a large number of young and middle-aged people among the mobile phone users in this area.

5. The method for assessing urban and rural spatial use using mobile phone signaling data according to claim 4, characterized in that: The offline data includes local resident data, the number of medical and educational facilities, the number of leisure venues, and the number of factories. After collection, the offline data is integrated and compared with the mobile phone signaling data.

6. The method for assessing urban and rural spatial use using mobile phone signaling data according to claim 1, characterized in that: The local resident data includes age group data and occupation data. The occupation data reflects the distribution of job types among residents in the area, and the age group data indicates the distribution of children, young and middle-aged adults, and elderly users in the area.

7. The method for assessing urban and rural spatial use using mobile phone signaling data according to claim 5, characterized in that: The occupational data includes the number of workers and the number of non-workers, and the number of non-workers and the number of workers indicate the proportion of worker residents and non-worker residents in the region.

8. A method for assessing urban and rural spatial use using mobile phone signaling data according to claim 6, characterized in that: If the number of elderly residents is less than the number of young and middle-aged residents, and the number of young and middle-aged residents is greater than the number of children, if the number of workers is greater than the number of non-workers, if the number of factories is less than the number of medical and educational facilities, if the number of leisure facilities is less than the number of medical and educational facilities, and if all of the above are true simultaneously, it indicates that the number of leisure facilities, factories, and educational facilities in the area is set unreasonably.

9. A method for assessing urban and rural spatial use using mobile phone signaling data according to claim 7, characterized in that: If the number of children is greater than the number of young and middle-aged residents, and the number of young and middle-aged residents is less than the number of elderly residents, if the number of non-workers is greater than the number of workers, if the number of medical and educational facilities is less than the number of factories but greater than the number of leisure facilities, and if all of the above are true, it indicates that the location of medical and educational facilities in the area is unreasonable.

10. A method for assessing urban and rural spatial use using mobile phone signaling data according to claim 7, characterized in that: If the number of children is greater than the number of elderly residents, if the number of medical and educational facilities is greater than the number of leisure facilities, and if all of the above are true, it indicates that the number of educational and medical facilities in the area is reasonably set.

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