Rural function characteristic evaluation-based village classification method and system, and medium

Abstract

The invention provides a village classification method based on village function feature evaluation. The method comprises the following steps: S1, acquiring a village image; the step S1 comprises the following steps: S11, counting the total number of acquired village image data to be imported, and recording the total number as Q; the two to-be-imported village images are respectively a first to-be-imported village image, a second to-be-imported village image, a third to-be-imported village image,..., and a Qth to-be-imported village image, and Q is a positive integer greater than or equal to 1; q = 1; s12, the image import code of the qth village image to be imported is calculated, and the calculation method of the image import code of the qth village image to be imported is # imgabs0 #, and # imgabs1 # represents the image import code of the qth village image to be imported; a Classification Number Algorithm [] is used for representing an image import code function, and the image import code function is used for representing an image import code function; iq represents the qth village image to be imported; and S2, classifying the village images obtained in the step S1.

Description

Technical Field

[0001] The present invention relates to the field of data processing technology, and in particular to a village classification method, system and medium based on village function characteristic evaluation. Background Art

[0002] As the "last mile" of national land space planning, village planning plays a fundamental, practical and practical role in the entire national land space planning system. In particular, it is necessary to respect the laws of village development and evolution trends to classify and implement policies, and the understanding of village types should be shifted from a single dimension to a comprehensive dimension. Classification into different types is the basic work for formulating differentiated planning schemes, but there is little research on village classification methods at present. The requirements for obtaining data on the current status of various social and economic types and land use types are high, and there are data inconsistencies. In addition, traditional classification research methods have high labor requirements, low efficiency and low accuracy. There is still a lack of objectivity, universality and scientific promotion of village type evaluation classification methods and conclusions. There is an urgent need for a practical and effective classification method to identify village types and promote them. The present invention intends to start from the classification of rural images, measure their congestion, and combine the time dimension to achieve the classification of villages, enhance judgment accuracy and improve efficiency, in order to provide a practical reference for village classification. Summary of the invention

[0003] The present invention aims to at least solve the technical problems existing in the prior art, and in particular innovatively proposes a village classification method, system and medium based on the evaluation of rural functional characteristics.

[0004] In order to achieve the above-mentioned object of the present invention, the present invention provides a village classification method based on rural functional characteristics evaluation, comprising the following steps:

[0005] S0, log in to the village classification platform;

[0006] S1, obtain village pictures;

[0007] S2, classifying the village pictures obtained in step S1.

[0008] In a preferred embodiment of the present invention, step S1 includes the following steps:

[0009] S11, counting the number of images of the village to be imported, recorded as Q; the first image of the village to be imported, the second image of the village to be imported, the third image of the village to be imported, ..., the Qth image of the village to be imported, Q is a positive integer greater than or equal to 1; let q = 1;

[0010] S12, calculating the image import code of the qth village image to be imported, wherein the calculation method of the image import code of the qth village image to be imported is:

[0011]

[0012] Among them, I q represents the qth village image to be imported;

[0013] Image code Algorithm[] represents the image import code function; preferably, the MD5 function is used;

[0014] The image import code representing the qth village image to be imported;

[0015] S13, determine the size relationship between q and Q:

[0016] If q≥Q, execute step S14;

[0017] If q<Q, then q=q+1, and return to step S12;

[0018] S14, determine the image import code set Does the same image import code exist in:

[0019] If the image import code set The same image import code does not exist in The image import code representing the first village image to be imported, represents the image import code of the second village image to be imported, The image import code representing the third village image to be imported, represents the image import code of the Qth village image to be imported, then the image import code set The image import code in is used as the image name of the corresponding village image to be imported; and the image import code set The image import code in is used as the remaining image import code;

[0020] If the image import code set The same image import code exists in The image import code representing the first village image to be imported, represents the image import code of the second village image to be imported, The image import code representing the third village image to be imported, represents the image import code of the Qth village image to be imported, then delete the redundant image import codes and the village images to be imported corresponding to the redundant image import codes; The remaining image import code is used as the image name of the corresponding village image to be imported;

[0021] S15, import the remaining image import codes into the platform. After the remaining image import codes are imported into the platform, the platform determines whether there is an identical image import code in the platform image import code set:

[0022] If the same image import code does not exist in the platform image import code set, the remaining image import codes are stored in the platform image import code set; and the images corresponding to the remaining image import codes are uploaded to the platform;

[0023] If the same image import code exists in the platform image import code set, delete the image import code in the remaining image import codes that is the same as that in the platform image import code set; after deleting the image import code in the remaining image import codes that is the same as that in the platform image import code set, obtain the remaining platform image import codes; store the remaining platform image import codes in the platform image import code set; upload the image corresponding to the remaining platform image import code to the platform.

[0024] In a preferred embodiment of the present invention, the terrain index is further calculated. The calculation method of the terrain index is:

[0025]

[0026] Where, T is the topographic index;

[0027] E is the elevation value of any grid in the study area;

[0028] is the average elevation value of all grids in the study area;

[0029] S is the slope value of any grid in the study area;

[0030] is the average slope value of all grids in the study area;

[0031] The larger the value of T, the higher the elevation and the greater the slope of the rural settlement.

[0032] In a preferred embodiment of the present invention, step S0 includes the following steps:

[0033] S0-1, determine whether the login virtual button is clicked:

[0034] If the login virtual button is clicked, proceed to the next step;

[0035] If the login virtual button is not clicked, execute step S0-1;

[0036] S0-2, obtain the 11-digit mobile phone number entered in the mobile phone number input box and the 6-digit verification code entered in the verification code input box;

[0037] S0-3, after obtaining the 11-digit mobile phone number entered in the mobile phone number input box and the 6-digit verification code entered in the verification code input box, the 11-digit mobile phone number and the 6-digit verification code are shifted respectively to obtain a mobile phone shift number and a verification shift code;

[0038] S0-4, shift the 11-digit mobile phone number and the 6-digit verification code respectively to obtain the mobile phone shift number and the verification shift code, then combine the mobile phone shift number and the verification shift code to obtain the mobile phone verification number; send the mobile phone verification number to the village classification platform;

[0039] S0-5, after receiving the mobile phone verification number, the village classification platform separates the mobile phone verification number to obtain a mobile phone separation number and a verification separation number respectively;

[0040] S0-6, determine whether the separation number exists in the village classification platform:

[0041] If the verification separation number exists in the village classification platform, extract the mobile phone storage number corresponding to the verification separation number and proceed to the next step;

[0042] If the verification separation number does not exist in the village classification platform, the login fails; it prompts that the verification code entered is wrong;

[0043] S0-7, process the mobile phone separation number to obtain the mobile phone processing number, and determine whether the mobile phone processing number is the same as the mobile phone storage number corresponding to the extracted verification separation number:

[0044] If the mobile phone processing number is the same as the mobile phone storage number corresponding to the extracted verification separation number, the login is successful;

[0045] If the mobile phone processing number is not the same as the mobile phone storage number corresponding to the extracted verification separation number, the login fails.

[0046] In a preferred embodiment of the present invention, step S2 includes arranging the images, and the method for arranging the images includes the following steps:

[0047] S21, obtaining rotation information of the village image, the rotation information includes rotation radian α, α∈[-π,π], |α| represents rotation by |α| along a plane perpendicular to the rotation point on the image plane, || represents taking an absolute value, α<0 represents counterclockwise rotation by |α| along a plane perpendicular to the rotation point, α≥0 represents clockwise rotation by |α| along a plane perpendicular to the rotation point;

[0048] S22, take any position (x 0 ,y 0 ) as the reference position,

[0049]

[0050] represents the set of all positions in the image plane,

[0051] (x m ,y n ) represents the position of the mth row and nth column in the village image, m = 1, 2, 3, ..., M, n = 1, 2, 3, ..., N, N represents the number of vertical pixels in the village image, M represents the number of horizontal pixels in the village image, (x 1 ,y 1 ) represents the position of the first row and first column in the village image, (x 2 ,y 1 ) represents the position of the 2nd row and nth column in the village image, (x 3 ,y 1 ) represents the position of the 3rd row and 1st column in the village image, (x M ,y 1 ) represents the position of the Mth row and the first column in the village image; (x 1 ,y 2 ) represents the position of the first row and second column in the village image, (x 2 ,y 2 ) represents the position of the 2nd row and 2nd column in the village image, (x 3 ,y 2 ) represents the position of the 3rd row and 2nd column in the village image, (x M ,y 2 ) represents the position of the Mth row and the second column in the village image; (x 1 ,y 3 ) represents the position of the 1st row and 3rd column in the village image, (x 2 ,y 3 ) represents the position of the 2nd row and 3rd column in the village image, (x 3 ,y 3 ) represents the position of the 3rd row and 3rd column in the village image, (x M ,y 3 ) represents the position of the Mth row and the third column in the village image; (x 1 ,y N ) represents the position of the 1st row and Nth column in the village image, (x 2 ,y N ) represents the position of the 2nd row and Nth column in the village image, (x 3 ,y N ) represents the position of the 3rd row and Nth column in the village image, (x M ,y N ) represents the position of the Mth row and Nth column in the village image;

[0052] S23, determine the relationship between N and M:

[0053] If N>M, then an N×N square pixel frame is constructed; N represents the number of vertical pixels in the village image, and M represents the number of horizontal pixels in the village image;

[0054] If N≤M, then construct an M×M square pixel frame; N represents the number of vertical pixels in the village image, and M represents the number of horizontal pixels in the village image;

[0055] The pixel coordinate system is constructed with the center of the square pixel frame as the origin, the left as the positive direction of the X axis, and the upward as the positive direction of the Y axis;

[0056] S24, the position (x m ,y n ) The position (x) of the corresponding red, green and blue pixel values ​​in the pixel coordinate system m ′,y n ′) at;

[0057] Or / and also includes generating an image sequence of rural remote sensing image data according to the time when the rural remote sensing image data is captured.

[0058] In a preferred embodiment of the present invention, in step S24, the position (x m ′,y n The calculation method of ′) comprises the following steps:

[0059] S241, according to the position (x 0 ,y 0 )Get the position (x m ,y n ), the calculation method of the position arc value is:

[0060]

[0061] If y n -y 0 ≥0,x m -x 0 >0, then

[0062] If y n -y 0 >0,x m -x 0 ≤0, then

[0063] If y n -y 0 <0,x m -x 0 ≥0, then

[0064] If yn -y 0 ≤0,x m -x 0 <0, then

[0065] S242, determine the relationship between α and 0:

[0066] If α<0, then

[0067] If α ≥ 0, then

[0068] In a preferred embodiment of the present invention, the calculation of the village congestion degree is also included, and the calculation method of the village congestion degree is:

[0069]

[0070] Among them, U s′ (t′) represents the time taken by car s′ to move from one car position to another;

[0071] K s,s′ (t′) is the village road congestion degree of car s′ and pedestrian s at time t′;

[0072] Υ t′ (s′) represents the number of cars s′ at time t′;

[0073] U s (t′) represents the time taken by pedestrian s to move from one pedestrian position to another pedestrian position;

[0074] Υ t′ (s) represents the number of pedestrians s at time t′;

[0075] s n represents the sum of the number of cars s′ and the number of pedestrians s;

[0076] η represents the distance moved by the car s′ and the pedestrian.

[0077] In a preferred embodiment of the present invention, the congestion classification value is obtained by using the congestion degree. The calculation method of obtaining the congestion classification value by using the congestion degree is:

[0078]

[0079] Among them, s n ″ represents the total number of pedestrians;

[0080] η s′ represents the distance moved by car s′;

[0081] K s,s′(t′) represents the village road congestion degree of car s′ and pedestrian s at time t′;

[0082] η represents the distance moved by the car s′ and the pedestrian;

[0083] s n represents the sum of the number of cars s′ and the number of pedestrians s;

[0084] K s,s′ (t′+1) represents the village road congestion degree of car s′ and pedestrian s at time t′+1;

[0085] s n ′ represents the total number of cars s′;

[0086] K(t′) represents the classification value;

[0087] η s represents the distance moved by pedestrian s;

[0088] If K(t′) is greater than the first preset congestion classification value, it is a large village;

[0089] If K(t′) is less than the second preset congestion classification value, it is a small village; the second preset congestion classification value is less than the first preset congestion classification value;

[0090] If K(t′) is between the first preset congestion classification value and the second preset congestion classification value, it is a medium-sized village.

[0091] The present invention also discloses a computer system, comprising:

[0092] processor;

[0093] a memory for storing processor-executable instructions;

[0094] Wherein, the processor is configured to implement the village classification method based on rural functional characteristics evaluation when executing the executable instructions.

[0095] The present invention also discloses a computer-readable storage medium, comprising:

[0096] a memory having a computer program stored thereon;

[0097] A processor is used to execute the program in the memory to implement the village classification method based on the evaluation of rural functional characteristics.

[0098] In summary, due to the adoption of the above technical solution, the present invention can classify village categories according to the captured images.

[0099] Additional aspects and advantages of the present invention will be given in part in the following description and in part will be obvious from the following description, or will be learned through practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0100] The above and / or additional aspects and advantages of the present invention will become apparent and easily understood from the description of the embodiments in conjunction with the following drawings, in which:

[0101] Figure 1 It is a schematic block diagram of the process of the present invention.

[0102] Figure 2 It is a schematic diagram showing the location of Banan District in the central urban area of ​​Chongqing according to the present invention.

[0103] Figure 3 It is a schematic diagram showing the rural area of ​​Banan District of the present invention.

[0104] Figure 4 It is a schematic diagram showing the comprehensive evaluation results of the present invention.

[0105] Figure 5 It is a schematic diagram showing the evaluation results of the production function of the present invention.

[0106] Figure 6 It is a schematic diagram showing the life function evaluation results of the present invention.

[0107] Figure 7 It is a schematic diagram showing the ecological function evaluation results of the present invention.

[0108] Figure 8 It is a schematic diagram showing the results of the cultural function evaluation of the present invention. DETAILED DESCRIPTION

[0109] Embodiments of the present invention are described in detail below, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, and cannot be understood as limiting the present invention.

[0110] The present invention provides a village classification method based on the evaluation of rural functional characteristics, such as Figure 1 As shown, the following steps are included:

[0111] S0, log in to the village classification platform;

[0112] S1, obtain village pictures;

[0113] S2, classifying the village pictures obtained in step S1.

[0114] In a preferred embodiment of the present invention, step S1 includes the following steps:

[0115] S11, counting the number of images of the village to be imported, recorded as Q; the first image of the village to be imported, the second image of the village to be imported, the third image of the village to be imported, ..., the Qth image of the village to be imported, Q is a positive integer greater than or equal to 1; let q = 1;

[0116] S12, calculating the image import code of the qth village image to be imported, wherein the calculation method of the image import code of the qth village image to be imported is:

[0117]

[0118] Among them, I q represents the qth village image to be imported;

[0119] Image code Algorithm[ ] represents the image import code function; preferably, the MD5 function is used;

[0120] The image import code representing the qth village image to be imported;

[0121] S13, determine the size relationship between q and Q:

[0122] If q≥Q, execute step S14;

[0123] If q<Q, then q=q+1, and return to step S12;

[0124] S14, determine the image import code set Does the same image import code exist in:

[0125] If the image import code set The same image import code does not exist in The image import code representing the first village image to be imported, represents the image import code of the second village image to be imported, The image import code representing the third village image to be imported, represents the image import code of the Qth village image to be imported, then the image import code set The image import code in is used as the image name of the corresponding village image to be imported; and the image import code set The image import code in is used as the remaining image import code;

[0126] If the image import code set The same image import code exists in The image import code representing the first village image to be imported, represents the image import code of the second village image to be imported, The image import code representing the third village image to be imported, represents the image import code of the Qth village image to be imported, then delete the redundant image import codes and the village images to be imported corresponding to the redundant image import codes; The remaining image import code is used as the image name of the corresponding village image to be imported;

[0127] S15, import the remaining image import codes into the platform. After the remaining image import codes are imported into the platform, the platform determines whether there is an identical image import code in the platform image import code set:

[0128] If the same image import code does not exist in the platform image import code set, the remaining image import codes are stored in the platform image import code set; and the images corresponding to the remaining image import codes are uploaded to the platform;

[0129] If the same image import code exists in the platform image import code set, delete the image import code in the remaining image import codes that is the same as that in the platform image import code set; after deleting the image import code in the remaining image import codes that is the same as that in the platform image import code set, obtain the remaining platform image import codes; store the remaining platform image import codes in the platform image import code set; upload the image corresponding to the remaining platform image import code to the platform.

[0130] like Figures 2 to 8 As shown, different line colors are used to divide the district and county streets into functional categories, which is intuitive and clear at a glance.

[0131] In a preferred embodiment of the present invention, the terrain index is further calculated. The calculation method of the terrain index is:

[0132]

[0133] Where, T is the topographic index;

[0134] E is the elevation value of any grid in the study area;

[0135] is the average elevation value of all grids in the study area;

[0136] S is the slope value of any grid in the study area;

[0137] is the average slope value of all grids in the study area;

[0138] The larger the value of T, the higher the elevation and the greater the slope of the rural settlement.

[0139] In a preferred embodiment of the present invention, the method for logging into the village classification platform in step S0 includes the following steps:

[0140] S0-1, determine whether the login virtual button is clicked:

[0141] If the login virtual button is clicked, proceed to the next step;

[0142] If the login virtual button is not clicked, execute step S0-1;

[0143] S0-2, obtain the 11-digit mobile phone number entered in the mobile phone number input box and the 6-digit verification code entered in the verification code input box, where the 11-digit mobile phone number is one of 0 to 9 or any combination of 11 digits, and the first digit cannot be 0, and the 6-digit verification code is one of 0 to 9, A to Z, a to z, or any combination of 6 digits;

[0144] S0-3, after obtaining the 11-digit mobile phone number entered in the mobile phone number input box and the 6-digit verification code entered in the verification code input box, the 11-digit mobile phone number and the 6-digit verification code are shifted respectively to obtain a mobile phone shift number and a verification shift code;

[0145] S0-4, shift the 11-digit mobile phone number and the 6-digit verification code respectively to obtain the mobile phone shift number and the verification shift code, then combine the mobile phone shift number and the verification shift code to obtain the mobile phone verification number; send the mobile phone verification number to the village classification platform;

[0146] S0-5, after receiving the mobile phone verification number, the village classification platform separates the mobile phone verification number to obtain a mobile phone separation number and a verification separation number respectively;

[0147] S0-6, determine whether the separation number exists in the village classification platform:

[0148] If the verification separation number exists in the village classification platform, extract the mobile phone storage number corresponding to the verification separation number and proceed to the next step;

[0149] If the verification separation number does not exist in the village classification platform, the login fails; it prompts that the verification code entered is wrong;

[0150] S0-7, process the mobile phone separation number to obtain the mobile phone processing number, and determine whether the mobile phone processing number is the same as the mobile phone storage number corresponding to the extracted verification separation number:

[0151] If the mobile phone processing number is the same as the mobile phone storage number corresponding to the extracted verification separation number, the login is successful;

[0152] If the mobile phone processing number is not the same as the mobile phone storage number corresponding to the extracted verification separation number, the login fails.

[0153] In a preferred embodiment of the present invention, in step S0-3, the 11-digit mobile phone number is shifted to obtain the mobile phone shift number as follows:

[0154] Determine whether the last digit of the mobile phone number is equal to 0:

[0155] If the last digit of the mobile phone number is equal to 0, then shift the mobile phone number by 10 digits from the back to the front; the mobile phone shift number can be obtained;

[0156] If the last digit of the mobile phone number is not equal to 0, the mobile phone number is shifted Q places from back to front to get the mobile phone shift number; Q is the last digit of the mobile phone number;

[0157] In step S0-3, the 6-bit verification code is shifted to obtain the verification shift code as follows:

[0158] Determine whether the first digit of the verification number is equal to 0, A to Z, or a to z:

[0159] If the first digit of the verification number is equal to one of 0, A-Z, a-z, then the verification number is shifted 10 digits from the back to the front; the verification shift number can be obtained;

[0160] If the first digit of the verification number is not equal to one of 0, A-Z, a-z, then the verification number is shifted by W digits from back to front to obtain the verification shift number; W is the first digit value of the verification number;

[0161] In a preferred embodiment of the present invention, in step S0-4, the mobile phone shift number and the verification shift code are combined to obtain the mobile phone verification number by:

[0162] Phonecom=Phonecode&Yzhengcode,

[0163] Among them, Phonecom represents the mobile phone verification number;

[0164] Phonecode indicates the mobile phone shift number;

[0165] & represents a combining character;

[0166] Yzhengcode means verification shift code;

[0167] In a preferred embodiment of the present invention, the method of separating the mobile phone verification number in step S0-5 to obtain the mobile phone separation number and the verification separation number is as follows:

[0168] Phonesepcode=Phonecom 11 ,

[0169] Among them, Phonesepcode represents the mobile phone separation number;

[0170] Phonecom 11 Indicates the first 11 digits of the mobile phone verification number;

[0171] Ysepcode=Phonecom 6

[0172] Ysepcode indicates the verification separation number

[0173] Phonecom 6 Indicates the last 6 digits of the mobile phone verification number.

[0174] In a preferred embodiment of the present invention, the method for processing the mobile phone separation number in step S0-7 to obtain the mobile phone processing number is:

[0175] Pcode=Phoneprocessway(Phonesepcode),

[0176] Among them, Pcode represents the mobile phone processing number;

[0177] Phoneprocessway() represents the method of generating the mobile phone processing number, preferably using the MD algorithm;

[0178] Phonesepcode indicates the phone sepcode number.

[0179] In a preferred embodiment of the present invention, the method for obtaining the 6-digit verification code in step S0-3 comprises the following steps:

[0180] S0-3-1, determine whether the verification code is clicked to obtain the virtual button:

[0181] If you click the verification code to get the virtual button, proceed to the next step;

[0182] If the verification code is not clicked to obtain the virtual button, execute step S0-3-1;

[0183] S0-3-2, obtain the 11-digit mobile phone number entered in the mobile phone number input box, where the 11-digit mobile phone number is one of 0 to 9 or any combination of 11 digits, and the first digit cannot be 0; send the mobile phone shift number to the village classification platform;

[0184] S0-3-3, after receiving the mobile phone number, the village classification platform performs shift processing on the mobile phone number to obtain the mobile phone shift number; processes the mobile phone shift number to obtain the mobile phone storage number; the method for processing the mobile phone shift number to obtain the mobile phone storage number is:

[0185] Pstocode=Phonestoway(Phonemovcode),

[0186] Among them, Pstocode represents the mobile phone storage number;

[0187] Phonestoway() represents the method for generating the mobile phone storage number, preferably using the MD algorithm;

[0188] Phonemovcode represents the mobile phone shift code.

[0189] S0-3-4, determine whether the mobile phone processing number exists in the village classification platform:

[0190] If the mobile phone processing number exists in the village classification platform, a 6-digit verification code is randomly generated and sent to the received mobile phone number, and the next step is executed;

[0191] If the mobile phone number does not exist in the village classification platform, it will prompt that it is not registered. Please register first;

[0192] S0-3-5, determine whether the first digit of the verification number is equal to one of 0, A to Z, or a to z:

[0193] If the first digit of the verification number is equal to one of 0, A-Z, a-z, then the verification number is shifted 10 digits from the back to the front; the verification shift number can be obtained;

[0194] If the first digit of the verification number is not equal to one of 0, A-Z, a-z, then the verification number is shifted by W digits from back to front to obtain the verification shift number; W is the first digit value of the verification number;

[0195] The verification shift number and the mobile phone processing number form a storage pair and are stored in the village classification platform; at this time, the mobile phone processing number in the storage pair is the mobile phone storage number.

[0196] In a preferred embodiment of the present invention, step S2 includes arranging the images, and the method for arranging the images includes the following steps:

[0197] S21, obtaining rotation information of the village image, the rotation information includes rotation radian α, α∈[-π,π], |α| represents rotation by |α| along a plane perpendicular to the rotation point on the image plane, || represents taking an absolute value, α<0 represents counterclockwise rotation by |α| along a plane perpendicular to the rotation point, α≥0 represents clockwise rotation by |α| along a plane perpendicular to the rotation point;

[0198] S22, take any position (x 0 ,y 0 ) as the reference position,

[0199]

[0200] represents the set of all positions in the image plane,

[0201] (x m ,y n ) represents the position of the mth row and nth column in the village image, m = 1, 2, 3, ..., M, n = 1, 2, 3, ..., N, N represents the number of vertical pixels in the village image, M represents the number of horizontal pixels in the village image, (x 1 ,y 1 ) represents the position of the first row and first column in the village image, (x 2 ,y 1 ) represents the position of the 2nd row and nth column in the village image, (x 3 ,y 1 ) represents the position of the 3rd row and 1st column in the village image, (x M ,y 1 ) represents the position of the Mth row and the first column in the village image; (x 1 ,y 2 ) represents the position of the first row and second column in the village image, (x 2 ,y 2 ) represents the position of the 2nd row and 2nd column in the village image, (x 3 ,y 2 ) represents the position of the 3rd row and 2nd column in the village image, (x M ,y 2 ) represents the position of the Mth row and the second column in the village image; (x 1 ,y 3 ) represents the position of the 1st row and 3rd column in the village image, (x 2 ,y 3 ) represents the position of the 2nd row and 3rd column in the village image, (x 3 ,y 3 ) represents the position of the 3rd row and 3rd column in the village image, (x M ,y 3 ) represents the position of the Mth row and the third column in the village image; (x 1 ,y N ) represents the position of the 1st row and Nth column in the village image, (x 2 ,y N ) represents the position of the 2nd row and Nth column in the village image, (x 3 ,y N ) represents the position of the 3rd row and Nth column in the village image, (x M ,y N ) represents the position of the Mth row and Nth column in the village image;

[0202] S23, determine the relationship between N and M:

[0203] If N>M, then an N×N square pixel frame is constructed; N represents the number of vertical pixels in the village image, and M represents the number of horizontal pixels in the village image;

[0204] If N≤M, then construct an M×M square pixel frame; N represents the number of vertical pixels in the village image, and M represents the number of horizontal pixels in the village image;

[0205] The pixel coordinate system is constructed with the center of the square pixel frame as the origin, the left as the positive direction of the X axis, and the upward as the positive direction of the Y axis;

[0206] S24, the position (x m ,y n ) The position (x) of the corresponding red, green and blue pixel values ​​in the pixel coordinate system m ′,y n ′) at;

[0207] Or / and also includes generating an image sequence of the rural remote sensing image data according to the time when the rural remote sensing image data is taken, and the method for generating an image sequence of the rural remote sensing image data according to the time when the rural remote sensing image data is taken includes the following steps:

[0208] S31, counting the number of acquired rural remote sensing image data, recorded as K, K represents the number of rural remote sensing image data; let the sequence number k = 1;

[0209] S32, extract the kth rural remote sensing image S k The time of shooting, remove the day, minute and second in the time, and keep the year and month;

[0210] S33, if the kth rural remote sensing image S k The shooting time is y year m month, then the kth rural remote sensing image S k Put in the rural image dataset y,m ;

[0211] That is, if the kth rural remote sensing image S k The shooting time is y 1 In January of the year, the kth rural remote sensing image S k Put in the rural image dataset

[0212] If the kth rural remote sensing image S k The shooting time is y 1 In February of the year, the kth rural remote sensing image S k Put in the rural image dataset

[0213] If the kth rural remote sensing image S k The shooting time is y1 In March of the year, the kth rural remote sensing image S k Put in the rural image dataset

[0214] ……;

[0215] If the kth rural remote sensing image S k The shooting time is y 1 In December of the year, the kth rural remote sensing image S k Put in the rural image dataset

[0216] If the kth rural remote sensing image S k The shooting time is y 2 In January of the year, the kth rural remote sensing image S k Put in the rural image dataset

[0217] If the kth rural remote sensing image S k The shooting time is y 2 In February of the year, the kth rural remote sensing image S k Put in the rural image dataset

[0218] If the kth rural remote sensing image S k The shooting time is y 2 In March of the year, the kth rural remote sensing image S k Put in the rural image dataset

[0219] ……;

[0220] If the kth rural remote sensing image S k The shooting time is y 2 In December of the year, the kth rural remote sensing image S k Put in the rural image dataset

[0221] If the kth rural remote sensing image S k The shooting time is y 3 In January of the year, the kth rural remote sensing image S k Put in the rural image dataset

[0222] If the kth rural remote sensing image S k The shooting time is y 3 In February of the year, the kth rural remote sensing image S k Put in the rural image dataset

[0223] If the kth rural remote sensing image S k The shooting time is y 3 In March of the year, the kth rural remote sensing image S k Put in the rural image dataset

[0224] ……;

[0225] If the kth rural remote sensing image S k The shooting time is y 3 In December of the year, the kth rural remote sensing image S k Put in the rural image dataset

[0226] ……;

[0227] If the kth rural remote sensing image S k The shooting time is y n In January of the year, the kth rural remote sensing image S k Put in the rural image dataset

[0228] If the kth rural remote sensing image S k The shooting time is y n In February of the year, the kth rural remote sensing image S k Put in the rural image dataset

[0229] If the kth rural remote sensing image S k The shooting time is y n In March of the year, the kth rural remote sensing image S k Put in the rural image dataset

[0230] ……;

[0231] If the kth rural remote sensing image S k The shooting time is y n In December of the year, the kth rural remote sensing image S k Put in the rural image dataset

[0232] S34, determine the relationship between k and K:

[0233] If k>K, execute the next step;

[0234] If k≤K, execute step S32;

[0235] S35, generating an image sequence in chronological order; that is:

[0236]

[0237] Where S represents the image sequence of rural remote sensing image data;

[0238] s y,m represents a rural image dataset taken by remote sensing satellites in month m of year y; y = y 1 ,y 2 ,y 3 ,……,y n , m=1, 2, 3,..., 12; ζ=2、3、……、n, That is y 1 <y 2 <y 3 <……<y n ≤2024;

[0239] Represents y 1 A dataset of rural images taken by remote sensing satellites in January 2017;

[0240] Represents y 1 A dataset of rural images taken by remote sensing satellites in February 2017;

[0241] Represents y 1 A dataset of rural images taken by remote sensing satellites in March 2017;

[0242] Represents y 1 A dataset of rural images taken by remote sensing satellites in December 2017;

[0243] Represents y 2 A dataset of rural images taken by remote sensing satellites in January 2017;

[0244] Represents y 2 A dataset of rural images taken by remote sensing satellites in February 2017;

[0245] Represents y 2 A dataset of rural images taken by remote sensing satellites in March 2017;

[0246] Represents y 2 A dataset of rural images taken by remote sensing satellites in December 2017;

[0247] Represents y 3 A dataset of rural images taken by remote sensing satellites in January 2017;

[0248] Represents y3 A dataset of rural images taken by remote sensing satellites in February 2017;

[0249] Represents y 3 A dataset of rural images taken by remote sensing satellites in March 2017;

[0250] Represents y 3 A dataset of rural images taken by remote sensing satellites in December 2017;

[0251] Represents y n A dataset of rural images taken by remote sensing satellites in January 2017;

[0252] Represents y n A dataset of rural images taken by remote sensing satellites in February 2017;

[0253] Represents y n A dataset of rural images taken by remote sensing satellites in March 2017;

[0254] Represents y n A dataset of rural images taken by remote sensing satellites in December 2017;

[0255]

[0256] Among them, s y,m It represents a rural image dataset taken by remote sensing satellites in month m of year y;

[0257] s y,m,1 Represents the rural image dataset s y,m The 1st rural image in;

[0258] s y,m,2 Represents the rural image dataset s y,m The 2nd rural image in;

[0259] s y,m,3 Represents the rural image dataset s y,m The 3rd rural image in;

[0260] Represents the rural image dataset s y,m The ψth y,m Rural image; y,m Represents the rural image dataset s y,m The number of images of the middle and rural areas;

[0261] That is

[0262] in, Represents y 1 A dataset of rural images taken by remote sensing satellites in January 2017;

[0263] Represents a rural image dataset The 1st rural image in;

[0264] Represents a rural image dataset The 2nd rural image in;

[0265] Represents a rural image dataset The 3rd rural image in;

[0266] Represents a rural image dataset The rural images; Represents a rural image dataset The number of images of the middle and rural areas;

[0267]

[0268] in, Represents y 1 A dataset of rural images taken by remote sensing satellites in February 2017;

[0269] Represents a rural image dataset The 1st rural image in;

[0270] Represents a rural image dataset The 2nd rural image in;

[0271] Represents a rural image dataset The 3rd rural image in;

[0272] Represents a rural image dataset The rural images; Represents a rural image dataset The number of images of the middle and rural areas;

[0273]

[0274] in, Represents y 1 A dataset of rural images taken by remote sensing satellites in March 2017;

[0275] Represents a rural image dataset The 1st rural image in;

[0276] Represents a rural image dataset The 2nd rural image in;

[0277] Represents a rural image dataset The 3rd rural image in;

[0278] Represents a rural image dataset The rural images; Represents a rural image dataset The number of images of the middle and rural areas;

[0279]

[0280] in, Represents y 1 A dataset of rural images taken by remote sensing satellites in December 2017;

[0281] Represents a rural image dataset The 1st rural image in;

[0282] Represents a rural image dataset The 2nd rural image in;

[0283] Represents a rural image dataset The 3rd rural image in;

[0284] Represents a rural image dataset The rural images; Represents a rural image dataset The number of images of the middle and rural areas;

[0285]

[0286] in, Represents y 2 A dataset of rural images taken by remote sensing satellites in January 2017;

[0287] Represents a rural image dataset The 1st rural image in;

[0288] Represents a rural image dataset The 2nd rural image in;

[0289] Represents a rural image dataset The 3rd rural image in;

[0290] Represents a rural image dataset The rural images; Represents a rural image dataset The number of images of the middle and rural areas;

[0291]

[0292] in, Represents y 2 A dataset of rural images taken by remote sensing satellites in February 2017;

[0293] Represents a rural image dataset The 1st rural image in;

[0294] Represents a rural image dataset The 2nd rural image in;

[0295] Represents a rural image dataset The 3rd rural image in;

[0296] Represents a rural image dataset The rural images; Represents a rural image dataset The number of images of the middle and rural areas;

[0297]

[0298] in, Represents y 2 A dataset of rural images taken by remote sensing satellites in March 2017;

[0299] Represents a rural image dataset The 1st rural image in;

[0300] Represents a rural image dataset The 2nd rural image in;

[0301] Represents a rural image dataset The 3rd rural image in;

[0302] Represents a rural image dataset The rural images; Represents a rural image dataset The number of images of the middle and rural areas;

[0303]

[0304] in, Represents y 2 A dataset of rural images taken by remote sensing satellites in December 2017;

[0305] Represents a rural image dataset The 1st rural image in;

[0306] Represents a rural image dataset The 2nd rural image in;

[0307] Represents a rural image dataset The 3rd rural image in;

[0308] Represents a rural image dataset The rural images; Represents a rural image dataset The number of images of the middle and rural areas;

[0309]

[0310] in, Represents y 3 A dataset of rural images taken by remote sensing satellites in January 2017;

[0311] Represents a rural image dataset The 1st rural image in;

[0312] Represents a rural image dataset The 2nd rural image in;

[0313] Represents a rural image dataset The 3rd rural image in;

[0314] Represents a rural image dataset The rural images; Represents a rural image dataset The number of images of the middle and rural areas;

[0315]

[0316] in, Represents y 3 A dataset of rural images taken by remote sensing satellites in February 2017;

[0317] Represents a rural image dataset The 1st rural image in;

[0318] Represents a rural image dataset The 2nd rural image in;

[0319] Represents a rural image dataset The 3rd rural image in;

[0320] Represents a rural image dataset The rural images; Represents a rural image dataset The number of images of the middle and rural areas;

[0321]

[0322] in, Represents y 3 A dataset of rural images taken by remote sensing satellites in March 2017;

[0323] Represents a rural image dataset The 1st rural image in;

[0324] Represents a rural image dataset The 2nd rural image in;

[0325] Represents a rural image dataset The 3rd rural image in;

[0326] Represents a rural image dataset The rural images; Represents a rural image dataset The number of images of the middle and rural areas;

[0327]

[0328] in, Represents y 3A dataset of rural images taken by remote sensing satellites in December 2017;

[0329] Represents a rural image dataset The 1st rural image in;

[0330] Represents a rural image dataset The 2nd rural image in;

[0331] Represents a rural image dataset The 3rd rural image in;

[0332] Represents a rural image dataset The rural images; Represents a rural image dataset The number of images of the middle and rural areas;

[0333]

[0334] in, Represents y n A dataset of rural images taken by remote sensing satellites in January 2017;

[0335] Represents a rural image dataset The 1st rural image in;

[0336] Represents a rural image dataset The 2nd rural image in;

[0337] s yn,1,3 Represents a rural image dataset The 3rd rural image in;

[0338] Represents a rural image dataset The rural images; Represents a rural image dataset The number of images of the middle and rural areas;

[0339]

[0340] in, Represents y n A dataset of rural images taken by remote sensing satellites in February 2017;

[0341] Represents a rural image dataset The 1st rural image in;

[0342] Represents a rural image dataset The 2nd rural image in;

[0343] Represents a rural image dataset The 3rd rural image in;

[0344] Represents a rural image dataset The rural images; Represents a rural image dataset The number of images of the middle and rural areas;

[0345]

[0346] in, Represents y n A dataset of rural images taken by remote sensing satellites in March 2017;

[0347] Represents a rural image dataset The 1st rural image in;

[0348] Represents a rural image dataset The 2nd rural image in;

[0349] Represents a rural image dataset The 3rd rural image in;

[0350] Represents a rural image dataset The rural images; Represents a rural image dataset The number of images of the middle and rural areas;

[0351]

[0352] in, Represents y n A dataset of rural images taken by remote sensing satellites in December 2017;

[0353] Represents a rural image dataset The 1st rural image in;

[0354] Represents a rural image dataset The 2nd rural image in;

[0355] Represents a rural image dataset The 3rd rural image in;

[0356] Represents a rural image dataset The rural images; Represents a rural image dataset The number of images of the middle and rural areas;

[0357]

[0358] Where K represents the number of rural remote sensing image data;

[0359] Represents a rural image dataset The number of images of the middle and rural areas;

[0360] Represents a rural image dataset The number of images of the middle and rural areas;

[0361] Represents a rural image dataset The number of images of the middle and rural areas;

[0362] Represents a rural image dataset The number of images of the middle countryside.

[0363] In a preferred embodiment of the present invention, in step S24, the position (x m ′,y n The calculation method of ′) comprises the following steps:

[0364] S241, according to the position (x 0 ,y 0 )Get the position (x m ,y n ), the calculation method of the position arc value is:

[0365]

[0366] If y n -y 0 ≥0,x m -x 0 >0, then

[0367] If y n -y 0 >0,x m -x 0 ≤0, then

[0368] If y n -y 0 <0,x m -x 0 ≥0, then

[0369] If y n -y 0 ≤0,x m -x 0 <0, then

[0370] S242, determine the relationship between α and 0:

[0371] If α<0, then

[0372] If α ≥ 0, then

[0373] In a preferred embodiment of the present invention, the calculation of the village congestion degree is also included, and the calculation method of the village congestion degree is:

[0374]

[0375] Among them, U s′ (t′) represents the time taken by car s′ to move from one car position to another;

[0376] K s,s′ (t′) is the village road congestion degree of car s′ and pedestrian s at time t′;

[0377] Υ t′ (s′) represents the number of cars s′ at time t′;

[0378] U s (t′) represents the time taken by pedestrian s to move from one pedestrian position to another pedestrian position;

[0379] Υ t′ (s) represents the number of pedestrians s at time t′;

[0380] s n represents the sum of the number of cars s′ and the number of pedestrians s;

[0381] η represents the distance moved by the car s′ and the pedestrian.

[0382] In a preferred embodiment of the present invention, the congestion classification value is obtained by using the congestion degree. The calculation method of obtaining the congestion classification value by using the congestion degree is:

[0383]

[0384] Among them, s n ″ represents the total number of pedestrians;

[0385] η s′ represents the distance moved by car s′;

[0386] K s,s′ (t′) represents the village road congestion degree of car s′ and pedestrian s at time t′;

[0387] η represents the distance moved by the car s′ and the pedestrian;

[0388] s n represents the sum of the number of cars s′ and the number of pedestrians s;

[0389] K s,s′ (t′+1) represents the village road congestion degree of car s′ and pedestrian s at time t′+1;

[0390] s n ′ represents the total number of cars s′;

[0391] K(t′) represents the classification value;

[0392] η s represents the distance moved by pedestrian s;

[0393] If K(t′) is greater than the first preset congestion classification value, it is a large village;

[0394] If K(t′) is less than the second preset congestion classification value, it is a small village; the second preset congestion classification value is less than the first preset congestion classification value;

[0395] If K(t′) is between the first preset congestion classification value and the second preset congestion classification value, it is a medium-sized village.

[0396] The present invention also discloses a computer system, comprising:

[0397] processor;

[0398] a memory for storing processor-executable instructions;

[0399] Wherein, the processor is configured to implement the village classification method based on rural functional characteristics evaluation when executing the executable instructions.

[0400] The present invention also discloses a computer-readable storage medium, comprising:

[0401] a memory having a computer program stored thereon;

[0402] A processor is used to execute the program in the memory to implement the village classification method based on the evaluation of rural functional characteristics.

[0403] While embodiments of the present invention have been shown and described, those skilled in the art will appreciate that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the claims and their equivalents.

Claims

1. A village classification method based on rural functional characteristics evaluation, characterized in that: The following steps are involved: S0, log in to the village classification platform; S1, obtain village pictures; S2, classifying the village pictures obtained in step S1.

2. The village classification method based on rural functional characteristics evaluation according to claim 1 is characterized in that: Step S1 includes the following steps: S11, counting the number of images of the village to be imported, recorded as Q; the first image of the village to be imported, the second image of the village to be imported, the third image of the village to be imported, ..., the Qth image of the village to be imported, Q is a positive integer greater than or equal to 1; let q = 1; S12, calculating the image import code of the qth village image to be imported, wherein the calculation method of the image import code of the qth village image to be imported is: Among them, I q represents the qth village image to be imported; Image code Algorithm[] represents the image import code function; The image import code representing the qth village image to be imported; S13, determine the size relationship between q and Q: If q≥Q, execute step S14; If q<Q, then q=q+1, and return to step S12; S14, determine the image import code set Does the same image import code exist in: If the image import code set The same image import code does not exist in The image import code representing the first village image to be imported, represents the image import code of the second village image to be imported, The image import code representing the third village image to be imported, represents the image import code of the Qth village image to be imported, then the image import code set The image import code in is used as the image name of the corresponding village image to be imported; and the image import code set The image import code in is used as the remaining image import code; If the image import code set The same image import code exists in The image import code representing the first village image to be imported, represents the image import code of the second village image to be imported, The image import code representing the third village image to be imported, represents the image import code of the Qth village image to be imported, then delete the redundant image import codes and the village images to be imported corresponding to the redundant image import codes; The remaining image import code is used as the image name of the corresponding village image to be imported; S15, import the remaining image import codes into the platform. After the remaining image import codes are imported into the platform, the platform determines whether there is an identical image import code in the platform image import code set: If the same image import code does not exist in the platform image import code set, the remaining image import codes are stored in the platform image import code set; and the images corresponding to the remaining image import codes are uploaded to the platform; If the same image import code exists in the platform image import code set, delete the image import code in the remaining image import codes that is the same as that in the platform image import code set; after deleting the image import code in the remaining image import codes that is the same as that in the platform image import code set, obtain the remaining platform image import codes; store the remaining platform image import codes in the platform image import code set; upload the image corresponding to the remaining platform image import code to the platform.

3. The village classification method based on rural functional characteristics evaluation according to claim 1 is characterized in that: It also includes the calculation of terrain potential index, which is calculated as follows: Where, T is the topographic index; E is the elevation value of any grid in the study area; is the average elevation value of all grids in the study area; S is the slope value of any grid in the study area; S is the average slope value of all grids in the study area; The larger the value of T, the higher the elevation and the greater the slope of the rural settlement.

4. The village classification method based on rural functional characteristics evaluation according to claim 1 is characterized in that: Step S0 includes the following steps: S0-1, determine whether the login virtual button is clicked: If the login virtual button is clicked, proceed to the next step; If the login virtual button is not clicked, execute step S0-1; S0-2, obtain the 11-digit mobile phone number entered in the mobile phone number input box and the 6-digit verification code entered in the verification code input box; S0-3, after obtaining the 11-digit mobile phone number entered in the mobile phone number input box and the 6-digit verification code entered in the verification code input box, the 11-digit mobile phone number and the 6-digit verification code are shifted respectively to obtain a mobile phone shift number and a verification shift code; S0-4, shift the 11-digit mobile phone number and the 6-digit verification code respectively to obtain the mobile phone shift number and the verification shift code, then combine the mobile phone shift number and the verification shift code to obtain the mobile phone verification number; send the mobile phone verification number to the village classification platform; S0-5, after receiving the mobile phone verification number, the village classification platform separates the mobile phone verification number to obtain a mobile phone separation number and a verification separation number; S0-6, determine whether the separation number exists in the village classification platform: If the verification separation number exists in the village classification platform, extract the mobile phone storage number corresponding to the verification separation number and proceed to the next step; If the verification separation number does not exist in the village classification platform, the login fails; it prompts that the verification code entered is wrong; S0-7, process the mobile phone separation number to obtain the mobile phone processing number, and determine whether the mobile phone processing number is the same as the mobile phone storage number corresponding to the extracted verification separation number: If the mobile phone processing number is the same as the mobile phone storage number corresponding to the extracted verification separation number, the login is successful; If the mobile phone processing number is not the same as the mobile phone storage number corresponding to the extracted verification separation number, the login fails.

5. The village classification method based on rural functional characteristics evaluation according to claim 1 is characterized in that: Step S2 includes arranging the images. The method for arranging the images includes the following steps: S21, obtaining rotation information of the village image, where the rotation information includes a rotation radian α; S22, taking any position (x0, y0) in the image plane as the reference position; S23, determine the relationship between N and M: If N>M, then an N×N square pixel frame is constructed; N represents the number of vertical pixels in the village image, and M represents the number of horizontal pixels in the village image; If N≤M, then construct an M×M square pixel frame; N represents the number of vertical pixels in the village image, and M represents the number of horizontal pixels in the village image; The pixel coordinate system is constructed with the center of the square pixel frame as the origin, the left as the positive direction of the X axis, and the upward as the positive direction of the Y axis; S24, the position (x m ,y n ) The position (x) of the corresponding red, green and blue pixel values ​​in the pixel coordinate system m ′,y n ′).

6. The village classification method based on rural functional characteristics evaluation according to claim 1 is characterized in that: It also includes generating an image sequence of the rural remote sensing image data according to the time when the rural remote sensing image data was taken.

7. The village classification method based on rural functional characteristics evaluation according to claim 1 is characterized in that: It also includes obtaining a congestion classification value by using the congestion degree. The calculation method for obtaining the congestion classification value by using the congestion degree is: If K(t′) is greater than the first preset congestion classification value, it is a large village; If K(t′) is less than the second preset congestion classification value, it is a small village; the second preset congestion classification value is less than the first preset congestion classification value; If K(t′) is between the first preset congestion classification value and the second preset congestion classification value, it is a medium-sized village.

8. A computer system, characterized in that: include: processor; a memory for storing processor-executable instructions; Wherein, the processor is configured to implement the village classification method based on rural functional characteristics evaluation as described in one of claims 1 to 7 when executing the executable instructions.

9. A computer-readable storage medium, characterized in that: include: a memory having a computer program stored thereon; A processor is used to execute the program in the memory to implement the village classification method based on rural functional characteristics evaluation as described in any one of claims 1 to 7.

Images