JP4546802B2 - Land price calculation system - Google Patents

Description

  The present invention relates to a technique for calculating land prices.

  Conventionally, as a technique using electronic map data, there is a technique for appraising land prices (hereinafter also referred to as “land prices”). For example, a technique has been proposed for calculating the price of an appraisal target point by referring to data stored in association with the position coordinates on the map and specifying the nearest published price of the appraisal point (for example, , See Patent Document 1).

JP-A-7-73239 Japanese Patent Laid-Open No. 2001-249989 JP 2000-76349 A

  By the way, high reliability is required for appraisal of land prices. Therefore, land prices are appraised based on publicly determined prices such as published prices and prices that serve as standards such as prices actually traded. However, the value of land may vary greatly depending on the condition of the land. As a result, it has not always been easy to improve the reliability of the appraisal results.

  The present invention has been made to solve the above-described conventional problems, and an object thereof is to provide a technique capable of improving the reliability of a land price calculation result.

  In order to solve at least a part of the above-described problems, a land price calculation apparatus according to the present invention is a land price calculation apparatus that calculates land prices, and specifies a target position that is a position of a land on a map according to a user instruction Price map data associating a target position specifying unit, price point information representing a price point that is a point on the map, and price information representing a price of land at the price point, and the geographical location of the household on the map A reference price that can be used to calculate the price of the land at the target position from among a plurality of prices determined by the price map data By referring to the reference price specifying unit and the household map data, the number of target households that are the number of households in a predetermined surrounding area close to the target position and the reference price are associated with each other. A reference number of households that is the number of households in a predetermined surrounding area close to a reference point that is a point, a household number calculation unit that calculates the reference price, the number of target households, and the number of reference households A price calculation unit that calculates the price of the land at the target location, and the price calculation unit decreases the price of the land at the target location as the ratio of the number of target households to the number of reference households decreases. To be determined.

  According to this land price calculation device, the land price at the target position is calculated based on the land price at the reference point, and the predetermined value close to the target position with respect to the number of reference households, which is the number of households in a predetermined peripheral area close to the reference point. Since the calculation is such that the smaller the ratio of the number of target households that are the number of households in the surrounding area, the reliability of the land price calculation result can be improved.

  In the land price calculation device, the data storage unit further stores route valence map data associating route segment information representing a route segment on the map with route fare information representing a route valence of the route segment. The land price calculation device further includes a route price acquisition unit that acquires a route price for each of the target position and the reference point by referring to the route price map data, and the price calculation unit includes: The price of the land at the target position may be determined so as to be lower as the ratio of the road price at the target position to the road price at the reference point is smaller.

  According to this configuration, the land price at the target position is calculated so as to be lower as the ratio of the road price at the target position to the road price at the reference point is smaller. Therefore, the reliability of the land price calculation result can be improved. .

  The present invention can be realized in various forms. For example, a land price calculation method and a land price calculation device, a computer program for realizing the function of the method or device, and a recording medium on which the computer program is recorded Or the like.

Next, embodiments of the present invention will be described in the following order based on examples.
A. Example:
B. Variations:

A. Example:
FIG. 1 is an explanatory diagram showing a configuration of a land price calculation system 300 as an embodiment of the present invention. This land price calculation system 300 includes a client computer 100 and a Web server 200 connected via the Internet INET.

  In the client computer 100, a Web browser (hereinafter also simply referred to as “browser”) is operating. The Web browser acquires a Web page from the Web server 200 and displays the Web page on the monitor M. The user can give various instructions for calculating land prices to the Web server 200 by operating the Web browser. The client computer 100 includes a CPU and a memory, and realizes a function as a Web browser by executing a computer program.

  The Web server 200 includes a data processing unit 210, a communication unit 250, and a data storage unit 270. The data processing unit 210 calculates land prices in response to a request from the client computer 100, and transmits a Web page that displays the calculation results. The communication unit 250 mediates exchange of data between the Internet INET and the data processing unit 210. The data storage unit 270 stores Web page data representing a Web page and various data used for calculating land prices. In the example of FIG. 1, map data 400, a type table 500, a unique price table 510, and a standardized correction coefficient table 530 are stored. The map data 400 includes a map layer 410, a usage layer 420, a public price layer 430, and a route price layer 440. Details of each data will be described later. As the data storage unit 270, various memories such as an HDD and a RAM can be used. In this embodiment, the Web page data is described in HTML (Hyper Text Markup Language). However, any other format (for example, Java (trademark of Sun Microsystems)) may be employed as the format of the Web page data.

  FIG. 1 shows the internal configuration of the data processing unit 210. The data processing unit 210 of this embodiment includes a Web data processing unit 212, a target position specifying unit 214, a type specifying unit 216, a reference price specifying unit 218, a household number calculating unit 220, and a route price acquiring unit 222. , And a land price calculation unit 224. The data processing unit 210 includes a CPU and a memory, and realizes the functions of each component by executing a computer program. Details of the function of each component will be described later.

  The computer program executed by the data processing unit 210 can be supplied in a form recorded on a computer-readable recording medium. Such recording media include flexible disks, CD-ROMs, magneto-optical disks, IC cards, ROM cartridges, punch cards, printed matter on which codes such as bar codes are printed, computer internal storage devices (such as RAM and ROM). A variety of computer-readable media such as a memory) and an external storage device can be used. Note that some or all of the functions of the data processing unit 210 may be realized by hardware.

  FIG. 2 is a flowchart showing a procedure of processing in which the land price calculation system 300 calculates land prices. In step S <b> 100, the client computer 100 transmits a web page browsing request for calculating land prices to the web server 200. Such a browsing request is, for example, when a user inputs a predetermined URL (Uniform Resource Locator) in a browser or when a user operates a link to a Web page (also called “hyperlink” in HTML). Sent.

  In the next step S <b> 110, in the Web server 200, the Web data processing unit 212 receives the browsing request and transmits Web page data specified by the browsing request to the client computer 100. Specifically, the Web data processing unit 212 transmits Web page data representing an input screen for inputting information related to a property for which land price is calculated (hereinafter referred to as “target property”). Then, in the client computer 100, the browser receives the web page data and displays the content (step S120).

  FIG. 3 is an explanatory diagram illustrating an example of the input screen. This input screen IS has an address area AA, a land area field SF, and an OK button OB. The address area AA has a plurality of input fields for the user to specify the address of the target property. Specifically, it has a prefecture field F1, a municipality field F2, a large character field F3, a character string field F4, a city block field F5, and an address field F6. Thus, in the example of FIG. 3, the user can specify the address of the target property by dividing it into a plurality of hierarchies based on administrative divisions (hereinafter, each hierarchy is referred to as “address classification”). ).

  In step S130, the user inputs the address of the target property. FIG. 4 is an explanatory diagram illustrating a state in which the user inputs an address. The user can designate the address division of each hierarchy in order from the top by operating the fields F1 to F6 of the address area AA.

  First, the user can operate the prefecture field F1, which is the highest level. When the prefecture field F1 is operated, a list of selectable prefecture names is displayed (FIG. 4A). The user can specify one of these options. In FIG. 4A, the designated option ("A prefecture" in this example) is displayed surrounded by a double line frame.

  Next, the user can operate the subordinate city field F2. When the city field F2 is operated, a list of selectable city names is displayed (FIG. 4B). These options are included in “A prefecture” designated in the prefecture field F1. The user can designate one of these options as in “prefecture”. In FIG. 4B, “B5 city” is designated.

  Thereafter, the user can designate the address of the target property by operating the remaining fields F3 to F6 in order from the top. At this time, if each of the fields F3 to F6 is operated, a list of options included in the address category represented by the next higher option is displayed as in the city field F2. Such a list of options may be incorporated in the Web page data in advance, or may be appropriately transmitted from the Web server 200 (FIG. 1) to the client computer 100. In the present embodiment, every time the user designates an address category of one hierarchy, the browser transmits designated option information representing the designated option to the Web server 200. Furthermore, the target position specifying unit 214 of the Web server 200 transmits option list information representing an option list of the address classification of the next lower hierarchy (FIG. 2: step S140). As information representing options, for example, a predetermined code number representing options, text data representing options, or the like can be used.

  The target position specifying unit 214 refers to the map layer 410 of the map data 400 to acquire a list of address classification options. An example of the map layer 410 is shown in FIG. The map layer 410 is data representing map information (positions and shapes of features such as roads and houses) in a predetermined geographical coordinate system (for example, latitude b and longitude a). In addition, the map layer 410 stores names and areas (positions and shapes) of various administrative divisions on the map in association with each other. FIG. 4C shows a plurality of prefecture regions stored in the map layer 410. The target position specifying unit 214 can obtain a list of selectable prefectures by referring to the map layer 410. In the Web page data representing the input screen IS, data representing a list of prefectures acquired by the target position specifying unit 214 is incorporated. In the map layer 410, the area is defined using a polygon (also referred to as “polygon”). However, the area may be defined in other formats.

  FIG. 4D shows an enlarged view of prefecture A in the map layer 410. In this A prefecture, the area of the municipality in A prefecture is shown. The map layer 410 stores the name and area of each city in association with each other. By referring to the map layer 410, the target position specifying unit 214 can acquire a list of city names in the prefecture designated by the user.

  The map layer 410 stores the names and areas of all address sections in all layers in association with each other. Therefore, the target position specifying unit 214 can acquire an appropriate option according to the specified option by referring to the map layer 410.

  Note that data that associates address classifications with areas (hereinafter also referred to as “address map data”) may be stored in the data storage unit 270 as a separate sublayer for each address classification hierarchy. For example, it is good also as using the prefecture layer which stores the data regarding a prefecture. The same applies to address classifications at other levels. In any case, it is preferable that the area of each layer is defined by a common coordinate system.

  When all field options in the address area AA are designated, in the next step S150 (FIG. 2), the user inputs the area of the target property in the land area field SF.

  When the user inputs the address of the target property (hereinafter referred to as “target address”) and the area, and further operates the OK button OB, the address data representing the target address and the area data representing the area are converted to the Web server. 200 (step S160). As the address data, for example, a combination of predetermined code numbers representing designation options for each layer can be used.

  In the Web server 200 (FIG. 1), land price calculation processing based on address data and area data is executed (step S170). FIG. 5 is a flowchart showing the procedure of land price calculation processing. In this processing procedure, first, the land type of the target property is specified, then the reference price is specified according to the land type, and finally the land price is calculated based on the reference price.

  In step S300, the target position specifying unit 214 (FIG. 1) specifies a target point related to the geographical position of the target property. The target point is a point on the map used for specifying the land type and the reference price for the target property (details will be described later). In this embodiment, the map layer 410 has one representative point representing the geographical position for each address (for each “address” as the lowest address category). Therefore, the target position specifying unit 214 employs a representative point associated with the address as the target point. Each representative point is set in the area of each address.

  Next, the type specifying unit 216 (FIG. 1) specifies the type related to the use of the land of the target property. FIG. 6 is a table showing land types. In this embodiment, the land type is classified according to the land classification determined based on the City Planning Act. As shown in FIG. 6, all the land on the map is divided into “inside city planning area” and “outside city planning area”. There are two types of “city planning areas”: “drawing area” and “undrawn area”. There are two types of “drawing area”: “urbanization area” and “urbanization adjustment area”. The urbanized area is divided into a plurality of areas according to the use of the land, and any one of 12 types of uses is set in each area. On the other hand, there are two types of “undrawn area”: “use area” and “no use area”. The “use area” is divided into a plurality of areas according to the use of the land, as in the “urbanization area” described above, and any one of 12 kinds of uses is set in each area. The 12 types of applications are roughly classified into three types: “residential”, “commercial” and “industrial”.

  The rightmost column in the table of FIG. 6 represents the land type identified by the type specifying unit 216 (FIG. 1) in this embodiment. In this example, there are three types of use areas ("residential", "commercial", and "industrial"), "urbanization adjustment area", "no use area of undrawn area", and "outside city planning area" ”Are identified. Other types of land can be defined as the type of land, but in general, it is preferable to use a land type grouped into a smaller number of types determined by the City Planning Act.

  FIG. 7 is an explanatory diagram illustrating a state in which the type specifying unit 216 specifies the type of land of the target property. FIG. 7A shows a map image. This map image shows map information (features such as roads and houses) stored in the map layer 410. FIG. 7A shows an example of the target point (two target points S1 and S2). Each target point is defined by coordinates in the map layer 410. In the example of FIG. 7A, the coordinates of the target point S1 are (a1, b1), and the coordinates of the target point S2 are (a2, b2). Hereinafter, the target property represented by the target point S1 is also referred to as the target property S1. Similarly, the target property represented by the target point S2 is also referred to as a target property S2.

  FIG. 7B shows a usage layer 420. The use layer 420 is data that stores an area representing a use area defined by the City Planning Law and its use in association with each other. Specifically, the data regarding 12 types of use areas is stored. In the example of FIG. 7B, four application areas U1 to U4 are shown. In the usage layer 420, each area is defined using polygons expressed in the same coordinate system as the map layer 410.

  In step S <b> 310 of FIG. 5, the type identification unit 216 determines whether or not the target point is within the use area determined by the use layer 420. If it is within the use area, the type associated with the use area including the target point is adopted as the land type of the target property (step S320). For example, in FIG. 7, the target point S1 is in the first type residential area U1. Therefore, for this target point (target property) S1, the type is specified as “residential”.

  If the target point is not in the use area, the type specifying unit 216 specifies the type with reference to the type table 500 (step S330). FIG. 7C shows an example of the type table 500. This type table 500 is data that stores “address”, “whether it is in a city planning area”, “whether it is a drawing area”, and “whether use area is designated” in association with each other. The type specifying unit 216 specifies the type of land of the target property using the type table 500 and the target address designated by the user. For example, in the example of FIG. 7, the target point S2 is outside the use area. Further, the address of the target property S2 is “A prefecture B5 city C7 town D3 chome”. Therefore, the type identification unit 216 refers to the type table 500 and identifies the type of the target property as “outside city planning area”. In the example of FIG. 7C, the address “outside city planning area” is classified without using the data of “whether it is a drawing area” and “whether or not a use area is specified”. Is going to be identified.

  In this embodiment, in the type table 500, the type is set in units of “character chome”. Further, the type specifying unit 216 refers to the type table 500 and identifies three types “urbanization adjustment zone”, “no use zone of undrawn zone”, and “outside city planning zone” without designation of a usage zone. . For example, when “within city planning area”, “within drawing area”, and “no use area designation”, it can be identified as “urbanization adjustment area”. In the type table 500, the address and the type may be directly associated with each other.

  Here, tentatively, in the usage layer 420, a portion (region) where the usage area is not specified is further divided using a region (polygon) associated with the type, and the type is specified without using the type table 500. I decided to. Then, in the extended temporary usage layer, the entire range of the land represented by the temporary usage layer is filled with an area (polygon) related to the type, and the amount of data becomes enormous.

  On the other hand, suppose that the type is specified using the type table for the use area without using the use layer 420. However, designation of a use area determined based on the City Planning Act is performed by designating an area on a map. For example, a line that is separated from the center of the road by a certain distance (for example, 200 m) may be defined as the boundary line of the use area. Therefore, considering the reduction of the burden on the operator when modifying or changing the use area, it is preferable to specify the type of the use area by using data (use layer 420) for defining a region on the map. In addition, the boundary line of the application area may not match the boundary line of the address (for example, “address” which is the lowest address category). Therefore, from the viewpoint of ensuring the fidelity of data representing a use area, it is preferable to specify the use area type using the use layer 420.

  Therefore, in the present embodiment, the type specifying unit 216 specifies the type with respect to the use zone with reference to the use layer 420 that stores the type (use) and the area (position and shape) on the map in association with each other. In addition, for an area for which no use area is designated, the type is specified with reference to the type table 500 that stores the address and the type in association with each other. As a result, it is possible to easily expand the geographical range where the type can be specified. Furthermore, it is possible to prevent the amount of data from becoming excessively large, and to greatly reduce the burden on the operator who manages the land price calculation system 300.

When the type of the target property is specified, the reference price specifying unit 218 next specifies a reference price that is a price that can be used for calculating land prices. FIG. 8 is an explanatory diagram showing how the reference price is specified. In FIG. 8A, the public price layer 430 is shown. The public price layer 430 is data that associates and stores a point on the map and a publicly determined land price at the point (hereinafter referred to as “public price”). In this embodiment, a public price determined based on the land price public notice method and a standard price determined based on the national land use planning law are used. The published price is associated with a point on the map that represents a standard location (also referred to as “published location”), and the standard price is associated with a location on the map that represents a reference location. Hereinafter, a point where a price is determined in the public price layer 430 is referred to as a “public price point”. In the public price layer 430, the unit of price is represented by “1000 yen / m ² (price in units of 1000 yen per square meter)”. Note that “publicly defined” means defined by a public institution (national or local public entity).

  In step S340 (FIG. 5), the reference price specifying unit 218 says that the distance to the target point is a predetermined threshold (for example, 3 km) or less and the land type is the same as the target property type. It is determined whether or not there is a public price point that satisfies a condition (hereinafter referred to as “reference price condition”). When there is a public price point that satisfies the reference price condition, the reference price specifying unit 218 uses the price of the point with the smallest distance from the target point among the public price points that satisfy the reference price condition as the reference price. Adopt (step S350). For example, in FIG. 8, there are two public price points O1 and O2 in a region C1 whose distance from the target point S1 is within a threshold value. Furthermore, the types of these public price points O1 and O2 are “residential” as in the target property S1, and both the points O1 and O2 satisfy the reference price condition. Therefore, the reference price specifying unit 218 selects the point O1 closest to the target point S1 among the two public price points O1 and O2. In the following description, the public price point O1 is described as representing a “published price”.

  In addition, as a geographical range for searching for a public price point (hereinafter referred to as “price point search range”), not only a circle centered on the target point but also an arbitrary range close to the target point may be adopted. it can. For example, it is good also as searching in the square range whose center is a target point and whose length of one side is a predetermined length (for example, 4 km). The distance from the target point within the price point search range is preferably 10 km or less, particularly preferably 6 km or less, and most preferably 3 km or less.

  Further, the reference price specifying unit 218 can specify the type of the public price point by referring to the usage layer 420 and the type table 500 in the same manner as the target point. The address of the public price point can be specified by referring to the address classification stored in the map layer 410. That is, the map layer 410, the usage layer 420, and the type table 500 as a whole correspond to “data that associates a public price with a land type (price type data)”. However, data that directly associates the official price with the type may be used.

  When there is no official price point within the range satisfying the reference price condition, the reference price specifying unit 218 specifies the reference price with reference to the unique price table 510 (FIG. 5: Step S360). In the example of FIG. 8, there is no official price point whose type is “outside city planning area” in the region C2 where the distance from the target point S2 is within the threshold value. Therefore, the reference price specifying unit 218 specifies the reference price for the target property S2 with reference to the unique price table 510.

FIG. 8B shows an example of the unique price table 510. The unique price table 510 is data that stores “address”, “price”, “representative point”, and “area” in association with each other. The reference price specifying unit 218 can specify the reference price of the target property using the unique price table 510 and the target address designated by the user. For example, in the example of FIG. 8, since the address of the target property S2 is “A prefecture B5 city C7 town D3 chome”, the reference price is specified to be 78.2,000 yen / m ² .

  Note that the price determined in the unique price table 510 is a price determined based on an independent survey, independently of the publicly determined price. “Public price” and “standard price” are not evenly distributed on the map. Therefore, a price survey is performed in advance for an area where neither “advertised price” nor “standard price” is set. In the unique price table 510, a price based on such a survey result and an address to which the price is applied are stored in association with each other. Since the price is associated with the address in the unique price table 510, the operator managing the Web server 200 can easily update the unique price table 510. In addition, the representative point of the original price table 510 represents a point on the map representing the price, and a point where attributes such as land use status and land shape are standard in the surrounding area. Adopted. As the area, the standard area of land traded in the surrounding area is adopted. A method of using these representative points and areas will be described later. As shown in FIG. 8B, the price, the representative point, and the area may be set to the same value for a plurality of addresses.

  As described above, the reference price specifying unit 218 specifies the reference price with reference to the public price layer 430 that stores the public price and the point on the map in association with each other. In addition, when there is no official price point within the range that satisfies the reference price condition, the reference price is specified with reference to the unique price table 510 that stores the address and the price in association with each other. As a result, the geographical range in which the reference price can be specified can be easily expanded.

  In this embodiment, the reference price is associated with a point on the map. Therefore, the reference price specifying unit 218 specifies a point on the map in addition to the price. Hereinafter, a point on the map associated with the reference price is referred to as a “reference point”.

  Once the reference price is specified, the land price calculation unit 224 calculates the land price of the target property. FIG. 9 is an explanatory diagram showing an outline of land price calculation. FIG. 9A shows a land price calculation formula E1. In addition, FIG. 10 shows an example of a Web page that represents a land price calculation result for the target property S1.

The “level price” in the calculation formula E1 is a price calculated from the official price and the route price. FIG. 9B shows a level price calculation formula E2. The “official price” in the calculation formula E2 means the official price adopted as the reference price. For example, for the target property S1, the price of the reference point (public price point) O1 is “78.2 thousand yen / m ² ” (FIG. 8A).

  Further, the “target point route price” and the “reference point route price” are acquired by the route price acquisition unit 222 (FIG. 1). FIG. 11 is an explanatory diagram showing how the route price acquisition unit 222 acquires these route prices. FIG. 11A shows an example of the route valence layer 440 around the reference point O1, and FIG. 11B shows an example of the route valence layer 440 around the target point S1.

The route price layer 440 is data that stores a route (road) for which a route price on the map is set and the route price in association with each other. “Line price” is a price set by the NTA along a track (road) on a map in order to use it as a standard for calculating inheritance tax. In the route price layer 440 shown in FIG. 11, a route for which a route price is set (hereinafter referred to as “price setting route”) is defined in the same coordinate system as the map layer 410. In FIG. 11, the price setting route includes a number (unit: “1,000 yen / m ² ”) indicating the route price, and an arrow line indicating the applicable section of the route price.

  In addition, as a format for determining the price setting route, any format for determining the route section can be adopted. For example, you may determine using the line showing an area. In this case, the route price is associated with the line on the map. Alternatively, it may be determined using a polygon representing the shape of the route (road). In this case, the route price is associated with the area on the map.

The route price acquisition unit 222 refers to the route price layer 440 and employs the route price of the route facing the reference point as the reference point route price. In the example of FIG. 11A, the line price (“65,000 yen / m ² ”) of the line O1r facing the reference point O1 is adopted as the reference point line price. Similarly, the line price of the route facing the target point is also adopted as the target point line price for the target point. In the example of FIG. 11B, the line price (“115,000 yen / m ² ”) of the line S1r facing the target point S1 is adopted as the target point line price. Whether or not each point and the route face each other is determined by determining whether or not the route is in contact with the area of the address representing each point (lowest address category “address”). .

  By the way, the reference point may not face the pricing route. In such a case, the price of the price setting route closest to the reference point may be adopted as the reference point route price. However, it is preferable to search the price setting route from within a predetermined range close to the reference point. For example, the search may be performed from within a square range with a side length of 50 m centered on the reference point, or may be performed within a circle range with a radius of 25 m centered on the reference point. The shortest distance between the reference point and the reference point line price is preferably 100 m or less, particularly preferably 50 m or less, and most preferably 30 m or less.

  Moreover, the route price acquisition unit 222 may acquire the route price of the reference point according to the user's instruction. For example, the browser may display a map image indicating the reference point O1 and the surrounding route prices as shown in FIG. 11A, and the user may specify a route on the map image. Specifically, the route price acquisition unit 222 generates a map image indicating the reference point O1 and the route prices in the vicinity thereof, and the Web data processing unit 212 transmits the map image to the client computer 100. Further, the browser may display the received map image and transmit route position information indicating the route position (coordinates on the map) designated by the user to the Web server 200. The route price acquisition unit 222 can acquire the route price of the reference point O1 based on the route position information. In this way, the user can specify an appropriate line price.

  Moreover, the route price acquisition part 222 should just acquire a route price also about a target point similarly to a reference point.

  When the route price acquisition unit 222 acquires the route price between the reference point and the target point, the land price calculation unit 224 calculates the level price. As shown in the calculation formula E2 (FIG. 9B), the level price is obtained by multiplying the public price by the ratio of the line price. Line price means the standard price of land around the line. Therefore, it can be estimated that the price of the surrounding land is high if the route price is high, and the price of the surrounding land is low if the route price is low. Therefore, the reliability of land price evaluation can be improved by calculating the level price according to the calculation formula E2.

  In addition, when the line price cannot be acquired for at least one of the reference point and the target point, the land price calculation unit 224 calculates the price by using the public price as it is instead of the level price. .

  Next, the land price calculation unit 224 calculates a “time correction coefficient” relating to the line price at the reference point (FIG. 9A: calculation formula E1). FIG. 9C shows a calculation formula E3 of “time correction coefficient”. “Current year price” means the latest price when the price is calculated, and “previous year price” means a price set one year before the latest price. The “elapsed months” means the number of months that have elapsed from the price point of the “current year price” to the time point when the price is calculated. This point-in-time correction factor corrects prices on the assumption that price fluctuations in the current year are similar to fluctuations in the previous year. The “price point” means the price at the point of time.

FIG. 10 shows a calculation example of the time correction coefficient (also referred to as “variation rate”). The “current year price” is “65,000 yen / m ² ” which is the latest line price at the reference point O1 (FIG. 11A). The “previous year price” is “68,000 yen / m ² ” which is the line price of the reference point O1 in the previous year. The data storage unit 270 stores a previous-year road price layer that stores the previous-year road price layer, as well as a road price layer 440 that stores the latest road price (not shown). The “current price” and “previous year price” related to the route price are acquired by the route price acquisition unit 222 referring to the route price layer 440 and the previous year price layer. In the example of FIG. 10, the price is calculated at “June”. Therefore, the “elapsed months” is “5 months” (the price point of the route price is January 1). As a result, the time correction coefficient is “98%”.

  When the time correction coefficient regarding the route price of the reference point cannot be calculated (for example, when the previous year's road price is not stored), the land price calculation unit 224 uses the public time correction coefficient regarding the route price instead of the public time correction coefficient. Use the time correction factor for the price. The time correction coefficient for the official price is also calculated according to the calculation formula E3 in the same manner as the time correction coefficient for the route price. In this case, “current year price” is the latest public price of the reference point, and “previous year price” is the public price in the previous year. In the data storage unit 270, in addition to the public price layer 430 that stores the latest public price, a previous year public price layer that stores the previous year's public price is stored (not shown). The “current year price” and “previous year price” related to the public price are acquired by the reference price specifying unit 218 referring to the public price layer 430 and the previous year public price layer.

  Next, the land price calculation unit 224 calculates a “standardized correction coefficient” (FIG. 9A: calculation formula E1). FIG. 9D shows an example of a standardized correction coefficient table 530 that defines “standardized correction coefficient”. The standardized correction coefficient table 530 is a table that defines the relationship between the combination of the standard area and the target property area and the standardized correction coefficient (also referred to as “standardized correction rate”). In the example of FIG. 9D, the range in which the level area can take a value is divided into a plurality of ranges, and a table for defining the correspondence between the target property area and the standardized correction coefficient is provided for each division.

  This standardized correction coefficient is a coefficient for correcting land prices according to the target property area. For example, in a mountainous area, relatively large land is more valuable and easier to buy and sell. On the other hand, in urban areas, the price of wide land is high, so relatively small land is easier to buy and sell. Therefore, even if the land is in the same region, the market price of the unit price of land (land price per unit area) may differ depending on the area of the land. The standardized correction coefficient is a coefficient for correcting the difference in the market price according to the land area.

  First, the land price calculation unit 224 acquires a level area. Here, the “level area” means a standard value of the area of land sold and sold in the surrounding area of the target property. When the official price is used as the reference price, the area of the land where the official price is set is adopted as the standard area. The official price is set for land with a standard area in the neighborhood of the official price point. Therefore, the area of the land where the official price is set can be used as the standard area. Such land area is stored in the public price layer 430 together with the public price (not shown). The land price calculation unit 224 refers to the public price layer 430 and acquires an area associated with the same public price point as the public price. Such land area is announced by public institutions along with public prices.

When the land price calculation unit 224 acquires the standard area, the land price calculation unit 224 acquires the standardization correction coefficient according to the standardization correction coefficient table 530 of FIG. 9D and the target property area (FIG. 3) designated by the user. The standardization correction coefficient of the standardization correction coefficient table 530 is set in advance in consideration of the actual situation of land transactions. Roughly, the standardized correction coefficient tends to decrease as the target property area moves away from the standard area. However, depending on the actual situation of land transactions, the standardization correction coefficient in an area different from the standard area may be set to a value larger than the standardization correction coefficient in the standard area. In the example of FIG. 10, the standard area is “100 m ² ”, the target property area is “150 m ² ”, and the correction factor is “95%” (FIG. 9D).

  In this embodiment, the standardized correction coefficient table 530 has two types of tables: a table for the city planning area and a table for the city planning area (not shown). The land price calculation unit 224 uses these tables properly according to the type of the target property. As a result, the reliability of land price evaluation can be improved. In addition, as a classification of the land for properly using the standardized correction coefficient table 530, a classification other than this may be adopted. For example, tables for “residential use”, “commercial use”, and “industrial use” may be provided and used separately.

  In addition, as a format for determining the “standardization correction coefficient”, any format for determining the standardization correction coefficient from the target property area and the level area can be adopted. For example, the “standardized correction coefficient” may change continuously with respect to the change in the target property area.

  Next, the land price calculation unit 224 calculates the “regional disparity correction coefficient” (FIG. 9A: calculation formula E1). FIG. 9E is a graph showing the “regional disparity correction coefficient”. The vertical axis represents the regional disparity correction coefficient (also referred to as “regional disparity correction rate”), and the horizontal axis represents “number of target spot / reference number of houses”. “Number of target point houses” means the number of households around the target point, and “reference number of houses” means the number of households around the reference point. The “number of target spot houses” and the “number of reference spot houses” are calculated by the household number calculation unit 220.

  FIG. 12 is an explanatory diagram illustrating a state in which the household number calculation unit 220 calculates the target point house number and the reference point house number. FIG. 12 shows a map image including the target point S1 and the reference point O1. In this map image, a black mark H representing a house is shown. One black mark H represents one house defined in the map layer 410. FIG. 12 shows a square R1 centered on the target point S1 and a square R2 centered on the reference point O1. These squares R1 and R2 are squares each having a predetermined length (for example, 1 km). The number-of-households calculation unit 220 employs the number of houses in the square R1 as the “target number of houses”. Further, the number of houses in the square R2 is adopted as the “reference point house number”.

  When the “number of target spot houses” and the “number of reference spot houses” are calculated, the land price calculation unit 224 calculates a regional disparity correction coefficient according to the graph of FIG. In the example of FIG. 9E, the “regional disparity correction coefficient” is determined according to the ratio of the number of target point houses to the number of reference point houses. When the “number of target point houses” is smaller than the “number of reference point houses”, the “regional disparity correction coefficient” is set to be smaller as the “number of target point houses” decreases. When the “number of target point houses” is larger than the “number of reference point houses”, it is set to 1.0.

  The “regional disparity correction coefficient” determined in this way can be explained as follows. Areas with a relatively small number of households are less popular, so the market value of land prices tends to be relatively low. Therefore, if the “regional disparity correction coefficient” is determined so as to decrease as the “target number of houses” decreases, the reliability of the calculated land price can be increased. In addition, when the “number of target point houses” is larger than the “reference point number of houses”, the market price of the land price around the target point may be higher than that around the reference point. However, since it is not appropriate to evaluate land prices too high, the “regional disparity correction coefficient” is set to 1.0. However, the “regional disparity correction coefficient” may be determined so as to increase as the “number of target location units” increases.

  Note that the geographical range for calculating the “number of target points” (hereinafter referred to as “target number calculation range”) is not limited to a square range centered on the target point, but an arbitrary range close to the target point. Can be adopted. For example, the number of households within a circle of a predetermined size centered on the target point (for example, a radius of 500 m) may be counted. In addition, the distance from the target point in the target number calculation range is preferably 5 km or less, particularly preferably 2 km or less, and most preferably 1 km or less. In addition, for the “number of reference point houses”, it is preferable to adopt a range having the same shape as the “number of target point houses”. In this embodiment, the map layer 410 corresponds to “household map data representing the geographical distribution of households”.

  In addition, as the format of the “regional disparity correction coefficient”, any format that determines a smaller value as the “number of target location houses” is smaller can be adopted. For example, the “regional disparity correction coefficient” may be a constant value in a partial range of the “number of target spot houses”, or may change discontinuously with respect to the change of the “number of target spot houses”. In addition, the relationship between the ratio of the number of houses and the regional disparity correction coefficient may be different for each land classification. For example, it may be different between the city planning area and outside the city planning area, and may be different between the urbanization area and the urbanization adjustment area. At this time, the type identification unit 216 identifies the land classification of the target property, and the land price calculation unit 224 calculates the regional disparity correction coefficient according to the identified land classification.

After calculating the “regional disparity correction coefficient”, the land price calculation unit 224 calculates the unit price of the land price of the target property according to the calculation formula E1 (FIG. 9A). Furthermore, the price of the target property is calculated by multiplying the land price unit by the target property area. In the example shown in FIG. 10, the land price unit price is “92000 yen / m ² ” (rounded off to the hundreds), and the land price is “1380000 yen”.

  The case where land prices are calculated using official prices has been described above. However, when using original prices instead of official prices, the original prices are used as they are instead of standard prices, and land prices are not corrected. Is calculated. Further, when acquiring the standardized correction coefficient, the area (FIG. 8B) associated with the unique price is adopted as the level area. Furthermore, when calculating the number of reference point units (FIG. 12), the “representative point (FIG. 8B)” associated with the unique price is used as the reference point.

  When the land price calculation ends, the Web data processing unit 212 of the Web server 200 (FIG. 1) generates Web page data representing the land price calculation result and transmits it to the client computer 100 (FIG. 2: step S180). Then, in the client computer 100, the browser receives the web page data and displays the contents (step S190, FIG. 10). In the Web page data representing the calculation result, it is preferable to display a specific value of the parameter used for calculating the land price. For example, when the time correction of the official price is performed instead of the time correction of the route price, it is preferable to display the official price for the current year and the previous year, and when the original price is used instead of the official price. It is preferable to display the original price.

  As described above, in this embodiment, since the type of the target property is specified using the usage layer 420 and the type table 500, the geographical range in which the type can be specified can be easily expanded. Moreover, since the reference price is specified using the public price layer 430 and the unique price table 510, the geographical range in which the reference price can be specified can be easily expanded. As a result, the geographical range where land prices can be calculated can be easily expanded. Moreover, since the public price of the same type of land as the target property is used as the reference price, the reliability of the calculated price can be improved.

  In the present embodiment, since the land price is corrected based on the number of households around the reference point and the number of households around the target point, the reliability of the calculated land price can be improved. Moreover, since the land price is corrected using the ratio between the road price at the reference point and the road price at the target point, the reliability of the calculated land price can be further increased.

B. Variations:
The present invention is not limited to the above-described examples and embodiments, and can be implemented in various modes without departing from the gist thereof. For example, the following modifications are possible.

Modification 1:
In the land price calculation formula (FIG. 9: E1), the correction contents for the reference price (official price or original price) are not limited to those shown in FIG. Can be adopted. For example, the correction may be performed according to the shape of the land of the target property. In this case, as with the target property area, the user may specify the shape of the land. In the above-described embodiment, the time correction coefficient is related to two types of the public price of the reference point and the road price of the reference point. It is good also as using.

  Further, the content of the land price calculation formula (E1) may be changed for each land type. For example, when the land type is either “commercial” or “industrial”, the regional disparity correction may not be performed. In addition, when the regional disparity correction is omitted, the representative point in the unique price table 510 (FIG. 8B) can be omitted.

Modification 2:
The format in which the user specifies the position of the target property is not limited to the format in which the address is specified, and various formats can be adopted. For example, the position of the target property may be specified by the user specifying a point on the map. In this case, the target position specifying unit 214 can specify the address by referring to the map layer 410 and specifying the address classification including the designated point. Moreover, as a target point, the point designated by the user may be employed as it is, or a representative point associated with an address may be employed. In this case, the target position specifying unit 214 may display a map image on the client computer 100, and the user may specify a point on the map image.

  Thus, the target position specifying unit 214 appropriately specifies the address and the geographical position of the target property by using the map layer 410 (address map data) that defines the relationship between the address and the area on the map. be able to. This is the same when the user designates an address. At this time, it is preferable that the target position specifying unit 214 provides the user with a list of selectable options by referring to the address map data as in the above-described embodiment. Moreover, it is preferable to divide one address into a plurality of address sections and specify them in order from the higher address section.

Modification 3:
In the above-described embodiment, when an official price is selected (FIG. 8), the newer one of “advertised price” and “standard price” may be used preferentially. The “advertised price” and “standard price” are updated once a year. However, the “announced price” and the “standard price” are set (announced) at different times. The “advertised price” will be announced on March 1st at the price date. The “standard price” is July 1st and will be announced in September. Therefore, if the newer one is used preferentially, the reliability of land price evaluation can be improved. For example, when the land price is calculated in June, first, a reference price is searched from relatively new “published prices”, and when there is no “published price” that satisfies the reference price condition, The reference price may be searched from “standard price”.

Modification 4:
In the above-described embodiment, the reference price specifying unit 218 can use two kinds of prices, that is, a public price and an original price as a reference price, but may also use other kinds of prices. Good. For example, a price actually traded (hereinafter referred to as “example price”) may be used. If such a case price is associated with a point on the map, it can be used in the same way as a public price.

Modification 5:
In the above-described embodiment, the type specifying unit 216 specifies the type of land using the usage layer 420 (corresponding to “attribute map data”) and the type table 500 (corresponding to “attribute address data”). However, it may be specified according to other methods. For example, an area type for which no use area is specified may be stored in the use layer and specified using the use layer without using the type table 500. Alternatively, the type of use area may be stored in the type table and specified using the type table without using the use layer 420.

  The reference price specifying unit 218 specifies the reference price using the public price layer 430 (corresponding to “attribute map data”) and the unique price table 510 (corresponding to “attribute address table”). However, it may be specified according to other methods. For example, information on the official price may be stored in the unique price table 510 and specified using the unique price table 510 without using the official price layer 430.

  However, it is preferable to specify at least one of the land type and the reference price using “attribute map data” and “attribute address data”. In addition, the attributes to be specified using the “attribute map data” and “attribute address data” are not limited to the land type and reference price, but include various types such as “school district” and “distance to the nearest station”. The attributes can be adopted.

Modification 6:
In the above-described embodiment, when calculating the number of target spot units and the number of reference spot units (FIG. 12), for apartment houses, count each of the multiple rooms included in the apartment house as an independent household. Is preferred. In this case, the map layer 410 may store the apartment house and the number of rooms in association with each other. Moreover, when counting the number of households, it is preferable to count only the house where a resident is. In this case, the map layer 410 may store information regarding the presence or absence of a resident in each house. If it carries out like this, the reliability of the calculated land price can be improved.

  In addition, as a method for calculating the number of houses within a geographical range, a method is used in which representative points representing the position of a house (in this example, representative points associated with addresses) are counted within the range. Can do. Moreover, a house may be defined as an area on the map, and the area whose area is included in the range may be counted.

Modification 7:
In the embodiment described above, the coordinate system on the map layer 410 is used to determine the geographical position and area. However, this coordinate system only needs to have a predetermined relationship with actual map information (positions and shapes of features such as roads and houses) and is determined using the map layer 410 that stores map information. It does not have to be. Thus, “on the map” means that it is a real geographical thing. For example, “location on the map” means an actual geographical location.

  In addition, the format representing the position of the target property is not limited to a format using a point (target point), and various formats can be adopted. For example, a format using an area (hereinafter referred to as “target area”) may be adopted. As such a target area, for example, an area associated with an address (lowest address category (address)) can be used. Here, when specifying the use (type) (FIG. 7B), the type specifying unit 216 may adopt the type of the use area including the target area. When one target area extends over a plurality of use areas, the type may be specified according to the area of the target area included in each use area. For example, the type of the application area having the widest area overlapping with the target region may be adopted. Moreover, when specifying a public price (FIG. 8 (A)), the reference price specific | specification part 218 should just employ | adopt the price of the point with the shortest shortest distance with an object area | region. Moreover, when calculating the number of households (FIG. 12), the household number calculation part 220 should just determine the geographical range which counts a household based on an object area | region. For example, the range may be determined based on the center of gravity of the target area.

Modification 8:
In the above-described embodiment, the Web server 200 calculates the land price, but instead, the attributes of the target property (for example, the land type and the reference price) may be displayed on the client computer 100. In this case, the land price calculation system 300 functions as an attribute identification system.

Modification 9:
In the above-described embodiment, the plurality of functions of the Web server 200 may be realized by being distributed on different computer hardware. The functions of the client computer 100 and the Web server 200 may be realized on a single computer hardware.

Modification 10:
In the above embodiment, a part of the configuration realized by hardware may be replaced with software, and conversely, a part of the configuration realized by software may be replaced by hardware.

Explanatory drawing which shows the structure of the land price calculation system 300. FIG. The flowchart which shows the procedure of the process which calculates a land price. Explanatory drawing which shows an example of an input screen. Explanatory drawing which shows a mode that a user designates an address. The flowchart which shows the procedure of a land price calculation process. A table showing the type of land. Explanatory drawing which shows a mode that the classification specific | specification part 216 specifies the classification of the land of an object property. Explanatory drawing which shows a mode that a reference price is specified. Explanatory drawing which shows the outline | summary of land price calculation. Explanatory drawing which shows an example of the web page showing the calculation result of land prices. Explanatory drawing which shows a mode that the route price acquisition part 222 acquires a route price. Explanatory drawing which shows a mode that the number of object point houses and the number of reference point houses are calculated.

Explanation of symbols

DESCRIPTION OF SYMBOLS 100 ... Client computer 200 ... Web server 210 ... Data processing part 212 ... Web data processing part 214 ... Target position specific | specification part 216 ... Type specific | specification part 218 ... Reference price specific | specification part 220 ... Number of households calculation unit 222 ... Road price acquisition unit 224 ... Land price calculation unit 250 ... Communication unit 270 ... Data storage unit 300 ... Land price calculation system 400 ... Map data 410 ... Map layer 420 ... Use layer 430 ... Public price layer 440 ... Line price layer 500 ... Type table 510 ... Unique price table 530 ... Standardized correction coefficient table INET .. Internet M ... Monitor F1 ... Prefectural field F2 ... City field F3 ... Large field F4 ... Character field F5 ... Block field F6 ... Address field AA .. Address area OB ... OK button SF ... Land area field IS ... input screen

Claims (4)

A land price calculation device for calculating land prices,
According to the user's instructions, and the target position specifying unit for specifying a target point is a point for specifying a land on the map to be land prices calculated,
Price map data associating price point information representing a price point that is a point on the map and price information representing a price of land at the price point, and a household map representing a geographical distribution of households on the map A data storage unit for storing data in advance ;
The price map data is read from the data storage unit, and the price point represented by each price point information included in the price map data is selected as a price point whose distance from the target point is a predetermined threshold value or less. A reference price specifying unit for specifying the price of land at the selected price point as a reference price and storing it in the data storage unit ;
The household map data is read from the data storage unit, and based on the household map data , the number of target households that are the number of households in a predetermined peripheral area close to the target point , and a reference that is a point associated with the reference price Calculating the number of reference households, which is the number of households in a predetermined surrounding area close to the point, and storing it in the data storage unit ;
Wherein the data storage unit, reading out said reference price before Symbol target households before Symbol reference number of households, with respect to the reference price, a predetermined correction associated with the difference between the reference number of households and the target number of households by performing, and a price calculation unit for calculating the price of land is identified by the object point,
The price calculation unit multiplies the reference price by the ratio of the number of target households to the number of reference households as the predetermined correction.
Land price calculation device. The land price calculation apparatus according to claim 1,
The data storage unit further stores in advance route price map data associating route section information representing a section of a route on the map and route price information representing a route price of the route section;
The land price calculation device further acquires a road price for each of the target point and the reference point by reading the road price map data from the data storage unit and referring to the road price map data And a road price acquisition unit for storing in the data storage unit ,
The price calculation unit reads a road price for the target point and a road price for the reference point from the data storage unit, and further, as the predetermined correction, further calculates the road price of the target point with respect to the road price of the reference point. Multiplying the reference price by the ratio,
Land price calculation device. Price map data that associates price point information that represents a price point that is a point on the map with price information that represents the price of land at the price point, and household map data that represents the geographical distribution of households on the map And calculating a land price using a computer having a data storage unit for storing in advance ,
(A) The computer specifies a target point that is a point for specifying a land on the map that is a target of land price calculation according to a user instruction;
(B) The computer reads the price map data from the data storage unit, and among the price points represented by the price point information included in the price map data, a distance from the target point is a predetermined threshold value. Selecting the following price points, specifying the price of the land at the selected price point as a reference price, and storing in the data storage unit ;
(C) The computer reads the household map data from the data storage unit , and based on the household map data , the number of target households that are the number of households in a predetermined peripheral area close to the target point , and the reference price Calculating a reference household number that is the number of households in a predetermined peripheral area close to a reference point that is an associated point, and storing the calculated number in a data storage unit ;
; (D) computer, from the data storage unit, the reference price before SL reads the target number of households and the previous SL reference number of households, with respect to the reference price, and the reference number of households and the target number of households Calculating a price of land identified by the target point by performing a predetermined correction related to the difference ; and
Have
In the step (d), as the predetermined correction, the computer multiplies the reference price by the ratio of the target household number to the reference household number.
Land price calculation method. Price map data that associates price point information that represents a price point that is a point on the map with price information that represents the price of land at the price point, and household map data that represents the geographical distribution of households on the map And a computer program for causing a computer having a data storage unit to store the land price in advance ,
(A) A function for specifying a target point that is a point for specifying the land on the map that is a target of land price calculation according to a user's instruction;
(B) The price map data is read from the data storage unit, and among the price points represented by the price point information included in the price map data, a price point whose distance from the target point is a predetermined threshold value or less Selecting the land price at the selected price point as a reference price, and storing it in the data storage unit ;
(C) Reading the household map data from the data storage unit , and based on the household map data , the number of target households that are the number of households in a predetermined surrounding area close to the target point , and points associated with the reference price A reference household number that is the number of households in a predetermined surrounding area close to a reference point, and a function for storing in the data storage unit ;
(D) from said data storage unit, reading out said reference price before Symbol target households before Symbol reference number of households, with respect to the reference price, related to the difference between the reference number of households and the target number of households A function of calculating a price of land specified by the target point by performing a predetermined correction ;
Is a computer program that causes a computer to realize
The function (d) multiplies the reference price by the ratio of the number of target households to the number of reference households as the predetermined correction.
Computer program.

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