Land abnormal change monitoring method based on multi-modal geographic features

Abstract

The invention provides a multi-modal geographic feature-based land abnormal change monitoring method. The method comprises the following steps of S1, acquiring a land monitoring image by using one or any combination of satellite images, unmanned aerial vehicle cruising and field patrol; s2, storing the land monitoring image obtained in the step S1 in a natural resource information system according to one or any combination of satellite images, unmanned aerial vehicle cruising and field patrol; s3, determining a land abnormal change condition according to the land monitoring image stored in the natural resource information system; and S4, giving a land abnormal change report for the land with the land abnormal change, wherein the land abnormal change report at least comprises one or any combination of the geographic position where the land abnormal change occurs, the occupied area of land, and the contrast images before and after the land abnormal change.

Description

Technical Field

[0001] The present invention relates to the technical field of land monitoring, and particularly to a method for monitoring abnormal land changes based on multimodal geographic features. Background Art

[0002] In the field of monitoring abnormal land changes, traditional methods mainly rely on manual on-site shooting and collection, which have problems such as low monitoring efficiency, high false alarm rate, and poor dynamic adaptability. With the integrated application of geographic information system (GIS), remote sensing (RS), and global positioning system (GPS) technologies (i.e., 3S technology), it is bound to change the traditional way and improve aspects such as monitoring efficiency, accuracy, and dynamic adaptability. Summary of the Invention

[0003] The present invention aims to at least solve the technical problems existing in the prior art, and particularly innovatively proposes a method for monitoring abnormal land changes based on multimodal geographic features.

[0004] To achieve the above object of the present invention, the present invention provides a method for monitoring abnormal land changes based on multimodal geographic features, including the following steps:

[0005] S1, obtaining land monitoring images by one or any combination of satellite images, drone cruising, and on-site inspections;

[0006] S2, storing the land monitoring images obtained by one or any combination of satellite images, drone cruising, and on-site inspections in step S1 in the natural resources information system;

[0007] S3, determining the abnormal land change situation according to the land monitoring images stored in the natural resources information system;

[0008] S4, issuing a land abnormal change report for the land where abnormal land changes have occurred, and the land abnormal change report includes at least one or any combination of the geographical location where the abnormal land changes occur, the occupied acreage, and the comparison images before and after the abnormal land changes.

[0009] The present invention also discloses a computer system, including:

[0010] A processor;

[0011] A memory for storing instructions executable by the processor;

[0012] Wherein, the processor is configured to implement the method for monitoring abnormal land changes based on multimodal geographic features when executing the executable instructions.

[0013] The present invention also discloses a computer-readable storage medium, including:

[0014] A memory on which a computer program is stored;

[0015] A processor for executing the program in the memory to implement the method for monitoring abnormal land changes based on multi-modal geographical features.

[0016] In summary, due to the adoption of the above technical solutions, the present invention can improve the monitoring efficiency, accuracy, dynamic adaptability, etc., and realize the rapid monitoring of abnormal land changes by using satellite images, drone patrols, and on-site inspections.

[0017] Additional aspects and advantages of the present invention will be given in part in the following description, become apparent in part from the following description, or be understood through the practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The above and / or additional aspects and advantages of the present invention will become apparent and be readily understood from the description of the embodiments in conjunction with the following drawings, where:

[0019] Figure 1 is a flowchart schematic diagram of the present invention.

[0020] Figure 2 is a display schematic diagram of the present invention.

[0021] Figure 3 is a display schematic diagram of the present invention.

[0022] Figure 4 is a display schematic diagram of the present invention.

[0023] Figure 5 is a display schematic diagram of the present invention.

[0024] Figure 6 is a display schematic diagram of the present invention.

[0025] Figure 7 is a display schematic diagram of the present invention.

[0026] Figure 8 is a display schematic diagram of the present invention.

[0027] Figure 9 is a display schematic diagram of the present invention.

[0028] Figure 10 is a display schematic diagram of the present invention.

[0029] Figure 11 is a display schematic diagram of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0030] Embodiments of the present invention will be described in detail below. Examples of the embodiments are shown in the accompanying drawings, where like or similar reference numerals denote like or similar elements or elements having like or similar functions throughout. The embodiments described below by referring to the drawings are exemplary only for explaining the present invention and should not be construed as limiting the present invention.

[0031] The present invention discloses a method for monitoring land abnormal changes based on multi-modal geographical features, as Figures 1 to 11 shown, which includes the following steps:

[0032] S1. Obtain land monitoring images by using one or any combination of satellite images, drone cruises, and on-site inspections;

[0033] S2. Store the land monitoring images obtained in step S1 by using one or any combination of satellite images, drone cruises, and on-site inspections in the natural resources information system;

[0034] S3. Determine the land abnormal change situation according to the land monitoring images stored in the natural resources information system;

[0035] S4. Issue a land abnormal change report for the land with land abnormal changes. The land abnormal change report includes at least one or any combination of the geographical location where the land abnormal changes occur, the occupied acreage, and the comparison images before and after the land abnormal changes.

[0036] In a preferred embodiment of the present invention, the method for storing the land monitoring images obtained in step S1 by using one or any combination of satellite images, drone cruises, and on-site inspections in the natural resources information system in step S2 includes the following steps:

[0037] S21. Obtain the pixel values of each channel in the land monitoring images:

[0038]

[0039] C j represents the pixel value of the j-th channel, where j = r, g, b;

[0040] (x p ,y q ) j represents the pixel value of the j-th channel at the position (x p ,y q ),

[0041] p = 1, 2, 3,..., P, where P is the number of horizontal pixel points;

[0042] q = 1, 2, 3,..., Q, where Q is the number of vertical pixel points;

[0043] When j = r, the pixel value of the red channel is:

[0044]

[0045] When j = g, the pixel value of the blue channel is:

[0046]

[0047] When j = b, the pixel value of the blue channel is:

[0048]

[0049] C r represents the pixel value of the r-th channel (red channel), (x p , y q ) r represents the pixel value of the r-th channel (red channel) at the position (x p , y q );

[0050] C g represents the pixel value of the g-th channel (green channel), (x p , y q ) g represents the pixel value of the g-th channel (green channel) at the position (x p , y q );

[0051] C b represents the pixel value of the b-th channel (blue channel), (x p , y q ) b represents the pixel value of the b-th channel (blue channel) at the position (x p , y q );

[0052] S22. Determine whether the pixel values of each channel in the land monitoring image are binary pixel values containing only 0 and 1:

[0053] If the pixel values of each channel in the land monitoring image are binary pixel values containing only 0 and 1, then proceed to the next step;

[0054] If the pixel values of each channel in the land monitoring image are not binary pixel values containing only 0 and 1, then change the pixel values of each channel in the land monitoring image to binary pixel values containing only 0 and 1, and proceed to the next step;

[0055] S23. Determine whether the number of bits of each pixel value in each channel of the land monitoring image is consistent with the preset bit number threshold:

[0056] If the number of bits of each pixel value in each channel of the land monitoring image is consistent with the preset bit number threshold, then proceed to the next step;

[0057] If the number of bits of the pixel values in each channel of the land monitoring image is inconsistent with the preset bit number threshold, then add 0 at the front of the pixel values in each channel of the land monitoring image to make the number of bits of the pixel values in each channel of the land monitoring image consistent with the preset bit number threshold, and proceed to the next step;

[0058]

[0059] C′ j Denotes the pixel value whose number of bits of the pixel value in the j-th channel is consistent with the preset bit number threshold, where j = r, g, b;

[0060] (x p ,y q )′ j Denotes the pixel value whose number of bits of the pixel value in the j-th channel at the position (x p ,y q ) is consistent with the preset bit number threshold,

[0061] p = 1, 2, 3,..., P, where P is the number of horizontal pixel points;

[0062] q = 1, 2, 3,..., Q, where Q is the number of vertical pixel points;

[0063] When j = r, the pixel value whose number of bits of the pixel value in the red channel is consistent with the preset bit number threshold is:

[0064]

[0065] When j = g, the pixel value whose number of bits of the pixel value in the green channel is consistent with the preset bit number threshold is:

[0066]

[0067] When j = b, the pixel value whose number of bits of the pixel value in the blue channel is consistent with the preset bit number threshold is:

[0068]

[0069] C′ r Denotes the pixel value whose number of bits of the pixel value in the r-th channel (red channel) is consistent with the preset bit number threshold, (x p ,y q )′ r Denotes the pixel value whose number of bits of the pixel value in the r-th channel (red channel) at the position (x p ,y q ) is consistent with the preset bit number threshold;

[0070] C′g Pixels whose number of bits of pixel values representing the g-th channel (green channel) is consistent with a preset bit number threshold, (x p ,y q )′ g Represents the pixel value whose number of bits of the pixel value at position (x p ,y q ) of the g-th channel (green channel) is consistent with the preset bit number threshold;

[0071] C′ b Represents the pixel value whose number of bits of the pixel value of the b-th channel (blue channel) is consistent with the preset bit number threshold, (x p ,y q )′ b Represents the pixel value whose number of bits of the pixel value at position (x p ,y q ) of the b-th channel (blue channel) is consistent with the preset bit number threshold;

[0072] S24, perform channel connection on the pixel values of each channel:

[0073]

[0074] Is the channel connection pixel value of the j-th channel;

[0075] (x p ,y q )′ j Represents the pixel value whose number of bits of the pixel value at position (x p ,y q ) of the j-th channel is consistent with the preset bit number threshold;

[0076] p = 1, 2, 3,..., P, where P is the number of horizontal pixel points;

[0077] q = 1, 2, 3,..., Q, where Q is the number of vertical pixel points;

[0078] When j = r, the channel connection pixel value of the red channel is:

[0079]

[0080] Is the channel connection pixel value of the red channel;

[0081] (x p ,y q )′ r Represents the pixel value whose number of bits of the pixel value at position (x p ,y q ) of the red channel is consistent with the preset bit number threshold;

[0082] p = 1, 2, 3, ……, P, where P is the number of horizontal pixel points;

[0083] q = 1, 2, 3, ……, Q, where Q is the number of vertical pixel points;

[0084] When j = g, the channel connection pixel value of the green channel is:

[0085]

[0086] is the channel connection pixel value of the green channel;

[0087] (x p , y q )′ g represents the pixel value whose number of bits of the pixel value at position (x p , y q ) of the green channel is the same as the preset bit number threshold;

[0088] p = 1, 2, 3, ……, P, where P is the number of horizontal pixel points;

[0089] q = 1, 2, 3, ……, Q, where Q is the number of vertical pixel points;

[0090] When j = b, the channel connection pixel value of the blue channel is:

[0091]

[0092] is the channel connection pixel value of the blue channel;

[0093] (x p , y q )′ b represents the pixel value whose number of bits of the pixel value at position (x p , y q ) of the blue channel is the same as the preset bit number threshold;

[0094] p = 1, 2, 3, ……, P, where P is the number of horizontal pixel points;

[0095] q = 1, 2, 3, ……, Q, where Q is the number of vertical pixel points;

[0096] S25. Fully connect the channel connection pixel values of each channel to obtain the fully connected pixel value:

[0097]

[0098] where F cen is the fully connected pixel value;

[0099] The pixel value of the channel connection for the red channel;

[0100] The pixel value of the channel connection for the green channel;

[0101] The pixel value of the channel connection for the blue channel;

[0102] S26. Generate the fully connected merged pixel value based on the fully connected pixel value:

[0103] F mes = coalesceway(F cen ),

[0104] where F mes represents the merged pixel value;

[0105] F cen is the fully connected pixel value;

[0106] coalesceway() represents the merged pixel value calculation function, preferably the SHA-3(384) function, and the merged pixel value is a 384-bit value containing only 0 and 1;

[0107]

[0108] where F neu represents the fully connected merged pixel value;

[0109] F mes represents the merged pixel value;

[0110] K represents the number of merged pixel values;

[0111]

[0112] where K represents the number of merged pixel values;

[0113] floor() represents the rounding function;

[0114] P is the number of horizontal pixel points;

[0115] Q is the number of vertical pixel points;

[0116] represents the number of bits of the merged pixel value;

[0117] S27. Compare the pixel values of each channel in step S23 with the fully connected merged pixel value to obtain the exchange pixel value of each channel:

[0118]

[0119] where, represents Exchange value;

[0120] Indicates the value of the p -th bit in the pixel value (x q , y j )′ ;

[0121] F neu (τ) indicates the value of the τ-th bit in the fully-connected merged pixel value F neu ;

[0122] ◇ represents the exchange value operator;

[0123] p, q, P, τ, η satisfy:

[0124]

[0125] where τ is the τ in F neu (τ);

[0126] η is the preset bit threshold, equal to the depth of the land monitoring image;

[0127] P is the number of horizontal pixel points;

[0128] p is The p in is the subscript value of the abscissa;

[0129] q is The q in is the subscript value of the ordinate;

[0130] is in

[0131] When j = r, the exchange value of is:

[0132]

[0133] Indicates the value of the p -th bit in the pixel value (x q , y r )′ ;

[0134] (x p , y q )′ r represents the pixel value whose number of bits in the red channel at the position (x p , y q ) is consistent with the preset bit threshold;

[0135] When j = g, the exchange value is:

[0136]

[0137] represents the value of the p -th bit in the pixel value (x q , y g )′ ;

[0138] (x p , y q )′ g represents the pixel value whose number of bits of the pixel value at position (x p , y q ) in the green channel is consistent with the preset bit number threshold;

[0139] When j = b, the exchange value is:

[0140]

[0141] represents the value of the p -th bit in the pixel value (x q , y b )′ ;

[0142] (x p , y q )′ b represents the pixel value whose number of bits of the pixel value at position (x p , y q ) in the blue channel is consistent with the preset bit number threshold;

[0143] S28, the exchange pixel value of each channel is:

[0144]

[0145] C″ j represents the exchange pixel value of the j-th channel, j = r, g, b;

[0146] (x p , y q )″ j represents the exchange pixel value of the j-th channel at position (x p , y q );

[0147] p = 1, 2, 3,..., P, where P is the number of horizontal pixel points;

[0148] q = 1, 2, 3,..., Q, where Q is the number of vertical pixel points;

[0149] When j = r, the swapped pixel value of the red channel is:

[0150]

[0151] C″ r represents the swapped pixel value of the red channel;

[0152] (x p ,y q )″ r represents the swapped pixel value of the red channel at the position (x p ,y q );

[0153] When j = g, the swapped pixel value of the green channel is:

[0154]

[0155] C″ g represents the swapped pixel value of the green channel;

[0156] (x p ,y q )″ g represents the swapped pixel value of the green channel at the position (x p ,y q );

[0157] When j = b, the swapped pixel value of the blue channel is:

[0158]

[0159] C″ b represents the swapped pixel value of the blue channel;

[0160] (x p ,y q )″ b represents the swapped pixel value of the blue channel at the position (x p ,y q );

[0161] S29. Generate an image based on the pixel values of each channel and store it in the natural resource information system. It also includes, after generating the image, the combined pixel value F mesAs the search string for storing the image, the stored image can be searched using the search string, and the search string is stored in a date storage set named after the date corresponding to the image shooting date corresponding to the search string. That is, if the shooting date is March 9, 2025, the search string is stored in the file named 20250309; if the shooting date is April 9, 2024, the search string is stored in the file named 20240409; if the shooting date is February 2, 2025, the search string is stored in the file named 20250202.

[0162] In a preferred embodiment of the present invention, the method for determining the abnormal land change situation according to the land monitoring images stored in the natural resource information system in step S3 includes the following steps:

[0163] S31, obtain the selected date, and the selected date includes the selection of the reference date and the comparison date; the reference date includes year, month, and day, the comparison date includes year, month, and day, and if the reference date and the comparison date are not the same day, they are different dates;

[0164] S32, obtain the search string stored on the date according to the selected date;

[0165] S33, search for the stored image corresponding to the search string according to the search string, and use the search string and the stored image corresponding to the search string to obtain the land monitoring images of different dates;

[0166] S34, determine the abnormal land change situation according to the land monitoring images of different dates.

[0167] In a preferred embodiment of the present invention, the method for obtaining the land monitoring images of different dates by using the search string and the image corresponding to the search string in step S33 includes the following steps:

[0168] S331, obtain the pixel values of each channel in the stored image:

[0169]

[0170] D j represents the pixel value of the j-th channel in the stored image, where j = r, g, b;

[0171] (x′ p ,y′ q ) j represents the pixel value of the j-th channel in the stored image at the position (x′ p ,y′ q ),

[0172] p = 1, 2, 3, ……, P, where P is the number of horizontal pixels;

[0173] q = 1, 2, 3, ……, Q, where Q is the number of vertical pixels;

[0174] When j = r, the pixel value of the red channel in the stored image is:

[0175]

[0176] When j = g, the pixel value of the green channel in the stored image is:

[0177]

[0178] When j = b, the pixel value of the blue channel in the stored image is:

[0179]

[0180] D r represents the pixel value of the r - channel (red channel) in the stored image, (x′ p ,y′ q ) r represents the pixel value of the r - channel (red channel) in the stored image at the position (x p ,y q ) of the stored image;

[0181] D g represents the pixel value of the g - channel (green channel) in the stored image, (x′ p ,y′ q ) g represents the pixel value of the g - channel (green channel) in the stored image at the position (x p ,y q ) of the stored image;

[0182] D b represents the pixel value of the b - channel (blue channel) in the stored image, (x′ p ,y′ q ) b represents the pixel value of the b - channel (blue channel) in the stored image at the position (x p ,y q ) of the stored image;

[0183] S332. Determine whether the pixel values of each channel in the stored image are binary pixel values containing only 0 and 1:

[0184] If the pixel values of each channel in the stored image are binary pixel values containing only 0 and 1, then proceed to the next step;

[0185] If the pixel values of each channel in the stored image are not binary pixel values containing only 0 and 1, then change the pixel values of each channel in the stored image to binary pixel values containing only 0 and 1, and proceed to the next step;

[0186] S333. Determine whether the number of bits of each pixel value in each channel of the stored image is consistent with a preset bit number threshold:

[0187] If the number of bits of each pixel value in each channel of the stored image is consistent with the preset bit number threshold, then proceed to the next step;

[0188] If the number of bits of the pixel values in each channel of the stored image is not consistent with the preset bit number threshold, then fill 0 at the front of the pixel values in each channel of the stored image to make the number of bits of the pixel values in each channel of the stored image consistent with the preset bit number threshold, and proceed to the next step;

[0189]

[0190] D′ j Denotes the pixel value whose number of bits of the pixel value of the j-th channel in the stored image is consistent with the preset bit number threshold, where j = r, g, b;

[0191] (x′ p ,y′ q )′ j Denotes the pixel value whose number of bits of the pixel value at position (x′ p ,y′ q ) of the j-th channel in the stored image is consistent with the preset bit number threshold,

[0192] p = 1, 2, 3, ……, P, where P is the number of horizontal pixel points;

[0193] q = 1, 2, 3, ……, Q, where Q is the number of vertical pixel points;

[0194] When j = r, the pixel value whose number of bits of the pixel value of the red channel in the stored image is consistent with the preset bit number threshold is:

[0195]

[0196] When j = g, the pixel value whose number of bits of the pixel value of the green channel in the stored image is consistent with the preset bit number threshold is:

[0197]

[0198] When j = b, the pixel value whose number of bits of the pixel value of the blue channel in the stored image is consistent with the preset bit number threshold is:

[0199]

[0200] D′ rDenotes the pixel value whose number of bits representing the pixel value of the r - channel (red channel) in the stored image is consistent with the preset bit - number threshold, (x′ p ,y′ q )′ r Denotes the pixel value whose number of bits representing the pixel value of the r - channel (red channel) at the position (x′ p ,y′ q ) in the stored image is consistent with the preset bit - number threshold;

[0201] D′ g Denotes the pixel value whose number of bits representing the pixel value of the g - channel (green channel) in the stored image is consistent with the preset bit - number threshold, (x′ p ,y′ q )′ g Denotes the pixel value whose number of bits representing the pixel value of the g - channel (green channel) at the position (x′ p ,y′ q ) in the stored image is consistent with the preset bit - number threshold;

[0202] D′ b Denotes the pixel value whose number of bits representing the pixel value of the b - channel (blue channel) in the stored image is consistent with the preset bit - number threshold, (x′ p ,y′ q )′ b Denotes the pixel value whose number of bits representing the pixel value of the b - channel (blue channel) at the position (x′ p ,y′ q ) in the stored image is consistent with the preset bit - number threshold;

[0203] S334, concatenates all K′ search strings to obtain a fully - connected search string:

[0204]

[0205] where, F str Denotes the fully - connected search string;

[0206] F sea Denotes the search string;

[0207] K′ denotes the number of search strings;

[0208]

[0209] where, K′ denotes the number of search strings;

[0210] floor() denotes the rounding - down function;

[0211] P is the number of horizontal pixel points;

[0212] Q is the number of vertical pixel points;

[0213] Indicates the number of digits of the search string;

[0214] S335. Compare the pixel values of each channel in step S333 with the fully connected search string to obtain the swapped pixel values of each channel:

[0215]

[0216] Among them, Indicates The swapped value of;

[0217] Indicates the value of the p ,y′ q )′ j In the th digit value;

[0218] F str (τ) indicates the value of the τth digit in the fully connected search string F str ; F str Indicates the fully connected search string;

[0219] ◇ represents the swap value operator;

[0220] p, q, P, τ, η satisfy:

[0221]

[0222] Among them, τ is the τ in F str (τ);

[0223] η is the preset digit threshold, equal to the depth of the stored image;

[0224] P is the number of horizontal pixel points;

[0225] p is The p in is the subscript value of the abscissa;

[0226] q is The q in is the subscript value of the ordinate;

[0227] Is In the

[0228] When j = r, The swapped value of is:

[0229]

[0230] Indicates the pixel value (x′p , y' q )' r the value of the th digit;

[0231] (x', p , y' q )' r represents the pixel value whose number of digits of the pixel value at position (x', p , y' q ) is consistent with the preset digit threshold;

[0232] When j = g, the swap value of

[0233]

[0234] represents the value of the p th digit in the pixel value (x', q , y' g )'; th digit;

[0235] (x', p , y' q )' g represents the pixel value whose number of digits of the pixel value at position (x', p , y' q ) is consistent with the preset digit threshold;

[0236] When j = b, the swap value of

[0237]

[0238] represents the value of the p , y' q )' b th digit in the pixel value (x', th digit;

[0239] (x', p , y' q )' b represents the pixel value whose number of digits of the pixel value at position (x', p , y' q ) is consistent with the preset digit threshold;

[0240] S336, store the swapped pixel values of each channel in the image as:

[0241]

[0242] D″ jDenotes the swapped pixel value of the j-th channel in the stored image, where j = r, g, b;

[0243] (x′ p ,y′ q )″ j Denotes the swapped pixel value of the j-th channel in the stored image at the position (x′ p ,y′ q );

[0244] p = 1, 2, 3, ……, P, where P is the number of horizontal pixel points;

[0245] q = 1, 2, 3, ……, Q, where Q is the number of vertical pixel points;

[0246] When j = r, the swapped pixel value of the red channel in the stored image is:

[0247]

[0248] D″ r Denotes the swapped pixel value of the red channel in the stored image;

[0249] (x′ p ,y′ q )″ r Denotes the swapped pixel value of the red channel in the stored image at the position (x′ p ,y′ q );

[0250] When j = g, the swapped pixel value of the green channel in the stored image is:

[0251]

[0252] D″ g Denotes the swapped pixel value of the green channel in the stored image;

[0253] (x′ p ,y′ q )″ g Denotes the swapped pixel value of the green channel in the stored image at the position (x′ p ,y′ q );

[0254] When j = b, the swapped pixel value of the blue channel in the stored image is:

[0255]

[0256] D″ b Denotes the swapped pixel value of the blue channel in the stored image;

[0257] (x′ p ,y′ q)″ b Indicates the swapped pixel value at position (x′ p , y′ q ) in the blue channel of the stored image;

[0258] S337. Generate an image based on the swapped pixel values of each channel, thus obtaining an image, which is an image generated from a search string and the image retrieved by the search string. All images for two epochs are obtained by performing the corresponding steps for other search strings in the same way.

[0259] It further includes,

[0260] S3371. In step S337, it further includes connecting the connected swapped pixel values of each channel in the stored image:

[0261]

[0262] is the connected swapped pixel value of the j-th channel;

[0263] (x′ p , y′ q )″ j Indicates the swapped pixel value at position (x′ p , y′ q ) in the j-th channel of the stored image;

[0264] p = 1, 2, 3, ……, P, where P is the number of horizontal pixel points;

[0265] q = 1, 2, 3, ……, Q, where Q is the number of vertical pixel points;

[0266] When j = r, the connected swapped pixel value of the red channel is:

[0267]

[0268] is the connected swapped pixel value of the red channel;

[0269] (x′ p , y′ q )′ r Indicates the swapped pixel value at position (x′ p , y′ q ) in the red channel of the stored image;

[0270] p = 1, 2, 3, ……, P, where P is the number of horizontal pixel points;

[0271] q = 1, 2, 3, ……, Q, where Q is the number of vertical pixel points;

[0272] When j = g, the channel connection pixel value of the green channel is:

[0273]

[0274] is the channel connection exchange pixel value of the green channel;

[0275] (x′ p ,y′ q )′ g represents the exchange pixel value of the green channel at the position (x′ p ,y′ q ) in the stored image;

[0276] p = 1, 2, 3, ……, P, where P is the number of horizontal pixel points;

[0277] q = 1, 2, 3, ……, Q, where Q is the number of vertical pixel points;

[0278] When j = b, the channel connection pixel value of the blue channel is:

[0279]

[0280] is the channel connection exchange pixel value of the blue channel;

[0281] (x′ p ,y′ q )′ b represents the exchange pixel value of the blue channel at the position (x′ p ,y′ q ) in the stored image;

[0282] p = 1, 2, 3, ……, P, where P is the number of horizontal pixel points;

[0283] q = 1, 2, 3, ……, Q, where Q is the number of vertical pixel points;

[0284] S3372, fully connect the channel connection exchange pixel values of each channel in the stored image to obtain the fully connected exchange pixel value:

[0285]

[0286] where F′ cen is the fully connected exchange pixel value;

[0287] is the channel connection exchange pixel value of the red channel;

[0288] is the channel connection exchange pixel value of the green channel;

[0289] The pixel values of the channel connection of the blue channel are exchanged;

[0290] S3373. Generate a fully connected merged exchange pixel value based on the fully connected exchange pixel value:

[0291] F′ mes = coalesceway(F′ cen )

[0292] where F′ mes represents the merged exchange pixel value;

[0293] F′ cen is the fully connected exchange pixel value;

[0294] coalesceway() represents a merged pixel value calculation function, preferably the SHA-3(384) function, and the merged exchange pixel value is a 384-bit value containing only 0s and 1s;

[0295] S3374. Determine whether the merged exchange pixel value F′ mes is consistent with the search string:

[0296] If the merged exchange pixel value F′ mes is consistent with the search string, generate an image based on the exchange pixel values of each channel, and thus obtain a correct image, that is, a correct image generated by a search string and the image searched by the search string. All other search strings are executed according to the corresponding steps to obtain all correct images for two periods;

[0297] If the merged exchange pixel value F′ mes is not consistent with the search string, delete the generated image and calculate the images corresponding to other search strings and the search string.

[0298] In a preferred embodiment of the present invention, the method for determining the abnormal land change situation according to the land monitoring images of different dates in step S34 includes the following steps:

[0299] S341. Obtain the pixel values of each channel in the land monitoring image:

[0300]

[0301] E j represents the pixel value of the j-th channel, where j = r, g, b;

[0302] (x″ p ,y″ q ) j represents the value of the j-th channel at the position (x″ p ,y″ q) pixel value,

[0303] p = 1, 2, 3, ……, P, where P is the number of horizontal pixel points;

[0304] q = 1, 2, 3, ……, Q, where Q is the number of vertical pixel points;

[0305] When j = r, the pixel value of the red channel is:

[0306]

[0307] When j = g, the pixel value of the red channel is:

[0308]

[0309] When j = b, the pixel value of the red channel is:

[0310]

[0311] E r represents the pixel value of the r-th channel (red channel), (x″ p , y″ q ) r represents the pixel value of the r-th channel (red channel) at the position (x″ p , y″ q );

[0312] E g represents the pixel value of the g-th channel (green channel), (x″ p , y″ q ) g represents the pixel value of the g-th channel (green channel) at the position (x″ p , y″″);

[0313] E b represents the pixel value of the b-th channel (blue channel), (x″ p , y″ q ) b represents the pixel value of the b-th channel (blue channel) at the position (x″ p , y″ q );

[0314] S342. Generate the pixel value of the merged channel according to the pixel values of each channel in the obtained land monitoring image:

[0315]

[0316] That is:

[0317]

[0318] Among them, Ergb represents the pixel value of the merged channel; δ r represents the pixel value coefficient of the red channel; δ g represents the pixel value coefficient of the green channel; δ b represents the pixel value coefficient of the blue channel;

[0319] δ r (x″ p ,y″ q ) r +δ g (x″ p ,y″ q ) g +δ r (x″ p ,y″ q ) b represents the pixel value of the merged channel at the position (x″ p ,y″ q );

[0320] p = 1, 2, 3, ……, P, where P is the number of horizontal pixel points;

[0321] q = 1, 2, 3, ……, Q, where Q is the number of vertical pixel points;

[0322] S343. Determine the pixel value for the pixel values on the same date:

[0323] S3431. Arrange all the pixel values with the same pixel coordinates in ascending order, which are Pix1, Pix2, Pix3, ……, Pix H ;

[0324] S3432. Take as the pixel value participating in the calculation to obtain the first determined pixel value:

[0325]

[0326] where Pix1 represents the pixel value ranked 1st after arranging the pixel values with the same pixel coordinates in ascending order;

[0327] Pix2 represents the pixel value ranked 2nd after arranging the pixel values with the same pixel coordinates in ascending order;

[0328] Pix3 represents the pixel value ranked 3rd after arranging the pixel values with the same pixel coordinates in ascending order;

[0329] Pix H represents the pixel value ranked Hth after arranging the pixel values with the same pixel coordinates in ascending order;

[0330] It represents the pixel value located at the h1-th position after arranging the pixel values of the same pixel coordinates in ascending order;

[0331] It represents the pixel value located at the h2-th position after arranging the pixel values of the same pixel coordinates in ascending order;

[0332] Pix con1 It represents the first determined pixel value;

[0333] H represents the number of images taken on the same date;

[0334]

[0335] S3433, take all the pixel values Pix1, Pix2, Pix3,..., Pix of the same pixel coordinates H as the pixel values participating in the calculation, and obtain the second determined pixel value:

[0336]

[0337] where Pix con2 represents the second determined pixel value;

[0338] H represents the number of images taken on the same date;

[0339] Pix j represents the pixel value located at the j-th position after arranging the pixel values of the same pixel coordinates in ascending order;

[0340] S3434, determine the magnitude relationship between the first determined pixel value and the second determined pixel value:

[0341] If |Pix con1 - Pix con2 | ≤ Pix sd , then the second determined pixel value is the determined pixel value;

[0342] If |Pix con1 - Pix con2 | > Pix sd , then the first determined pixel value is the determined pixel value; Pix sd is the preset pixel value exceeding the threshold;

[0343] By steps S3431 to S3434, the pixel value of one pixel coordinate can be determined, and the pixel values of other pixel coordinates are determined in the same way; correspondingly, the pixel values of the image on the reference date and the image on the comparison date can be determined;

[0344] S344, determine the pixel value anomaly for pixel values on different dates:

[0345] If then the land at pixel point (x″′ p , y″′ q ) has not undergone abnormal changes; is the preset first abnormal change threshold,

[0346] If then the land at pixel point (x″′ p , y″′ q ) has undergone abnormal changes;

[0347] Among them, then the land at pixel point (x″′ p , y″′ q ) has undergone a level III abnormal change; is the preset second abnormal change threshold;

[0348] then the land at pixel point (x″′ p , y″′ q ) has undergone a level II abnormal change; is the preset third abnormal change threshold;

[0349] then the land at pixel point (x″′ p , y″′ q ) has undergone a level I abnormal change;

[0350] p = 1, 2, 3,..., P, where P is the number of horizontal pixel points;

[0351] q = 1, 2, 3,..., Q, where Q is the number of vertical pixel points; Pix dat (x″′ p , y″′ q ) is the pixel value of the reference date image at pixel point (x″′ p , y″′ q ); Pix com (x″′ p , y″′ q ) is the pixel value of the comparison date image at pixel point (x″′ p , y″′ q );

[0352] The level III abnormal change is lower than the level II abnormal change, and the level I abnormal change is higher than the level II abnormal change.

[0353] It also includes that if any one or any combination of level-I abnormal changes, level-II abnormal changes, and level-III abnormal changes occurs, the geographical location of the land where the image is located is obtained, and its occupied area in mu is:

[0354] S = nξ / ψ,

[0355] n is the number of abnormal change pixel points; ξ is the proportionality coefficient between the actual area and the image area; ψ is the area conversion unit, and its value is 666.7; S is the abnormal change area in mu;

[0356]

[0357] R is the image resolution; pcs / cm; P is the number of horizontal pixel points; Q is the number of vertical pixel points; s represents the actual area corresponding to the image.

[0358] In a preferred embodiment of the present invention, after step S4, there is also step S5 of entering the natural resources information system by using a mobile phone or an office computer; after entering the natural resources information system by using a mobile phone or an office computer, download and view the land abnormal change report.

[0359] In a preferred embodiment of the present invention, in step S5, the method of entering the natural resources information system by using a mobile phone or an office computer includes the following steps:

[0360] S51, input the account number and password on the natural resources information system login interface; the number of digits of both the account number and the password is not less than 6 digits;

[0361] S52, after inputting the account number and password on the natural resources information system login interface, perform security encryption processing on the input account number and password;

[0362] S53, after performing security encryption processing on the input account number and password, send the securely encrypted account number and password to the natural resources information system verification platform;

[0363] S54, after the natural resources information system verification platform receives the securely encrypted account number and password, decrypt the received securely encrypted account number and password; alternatively, use the public key held by the login end to perform security encryption processing on the input account number and password; correspondingly, the natural resources information system verification platform uses the held private key to decrypt the received securely encrypted account number and password, where the private key is held by the platform and the public key is held by the login end, and the private key and the public key are a pair of asymmetric encryption and decryption keys.

[0364] S55, if both the decrypted account number and password exist in the natural resources information system verification platform, enter the natural resources information system; after entering the natural resources information system verification platform, the following operations can be performed as Figures 3 to 11The interface shown

[0365] Otherwise, if the account number and password entered on the natural resource information system login interface are incorrect, the correct account number and password need to be re-entered.

[0366] In a preferred embodiment of the present invention, the method for performing secure encryption processing on the input account number and password in step S52 includes the following steps:

[0367] S521, Obtain the current time, convert the current time into a ten-digit standard format. The current time includes year, month, day, and hour. For example, if the obtained time is 17:00 on March 26, 2025, the ten-digit standard format is 2025032617; if the obtained time is 21:00 on April 16, 2024, the ten-digit standard format is 2024041621;

[0368] S522, Determine the size relationship between the number of digits of the input account number and password and 10:

[0369] S5221, If the number of digits of the account number is less than 10, remove the first e1 digits from the front of the ten-digit standard format time, and the remaining number of digits is equal to the number of digits of the account number; proceed to the next step; e1 = 10 - e0, where e0 is the number of digits of the account number and e1 is the number of digits removed from the time;

[0370] If the number of digits of the account number is greater than 10, add e2 digits e3 to the front of the ten-digit standard format time, and the resulting number of digits is equal to the number of digits of the account number; proceed to the next step; e2 = e0 - 10, where e0 is the number of digits of the account number, e2 is the number of digits added to the time, and e3 is the last digit value in the ten-digit standard format;

[0371] If the number of digits of the account number is equal to 10, proceed to the next step;

[0372] S5222, If the number of digits of the password is less than 10, remove the first f1 digits from the front of the ten-digit standard format time, and the remaining number of digits is equal to the number of digits of the password; proceed to the next step; f1 = 10 - f0, where f0 is the number of digits of the password and f1 is the number of digits removed from the time;

[0373] If the number of digits of the password is greater than 10, add f2 digits f3 to the front of the ten-digit standard format time, and the resulting number of digits is equal to the number of digits of the password; proceed to the next step; f2 = f0 - 10, where f0 is the number of digits of the password, f2 is the number of digits added to the time, and f3 is the last digit value in the ten-digit standard format;

[0374] If the number of digits of the password is equal to 10, proceed to the next step; for example, if the input account and password are Zhanghao123 and miMa3211 respectively, and the ten - digit standard - format time is 2025050515, then after processing, the times are 52025050515 and 25050515 respectively; if the input account and password are Zhanghao12332 and miMa3211222 respectively, and the ten - digit standard - format time is 2025050515, then after processing, the times are 5552025050515 and 552025050515 respectively;

[0375] At this time, the account and password remain unchanged, but the times corresponding to the account and password may change;

[0376] S523, move the first digits of the account and password backward by f4 bits respectively, where f4 = floor(f3 / 2), and f4 is the number of bits moved backward; for example, if the input account and password are Zhang1hao3 and mi2Ma2 respectively, and the ten - digit standard - format time is 2025060715, then after processing, the account and password are haZng1hao3 and i2mMa2 respectively; if the input account and password are Zhang1hao3 and mi2Ma2 respectively, and the ten - digit standard - format time is 2025060716, then after processing, the account and password are hanZg1hao3 and i2Mma2 respectively;

[0377] S524, convert each character in the account, password, and time into 7 - bit binary ASCII form, calculate the ASCII - form account with the ASCII - form time, and calculate the ASCII - form password with the ASCII - form time to obtain the encrypted account and encrypted password respectively.

[0378]

[0379] g′2(φ) represents the φ - th digit value in the ASCII - form encrypted account;

[0380] g2(φ) represents the φ - th digit value in the ASCII - form account;

[0381] t2(φ) represents the φ - th digit value in the ASCII - form time;

[0382] φ = 1, 2, 3, ……, φ1; φ1 is the number of digits of the ASCII - form account;

[0383] φ1 = 7φ2, where φ2 is the number of digits of the account;

[0384] ◇ represents the swap - value operator;

[0385]

[0386] v′2(θ) represents the θ-th digit value in the encrypted password in ASCII form;

[0387] v2(θ) represents the θ-th digit value in the password in ASCII form;

[0388] t′2(θ) represents the θ-th digit value in the time in ASCII form;

[0389] θ = 1, 2, 3, ……, θ1; θ1 is the number of digits of the password in ASCII form;

[0390] θ1 = 7θ2, where θ2 is the number of digits of the password;

[0391] Convert the encrypted account number in ASCII form and the encrypted password in ASCII form into the encrypted account number and encrypted password in character form.

[0392] For example, the input account number and password are ZHangHao12234 and MIma912 respectively, and the obtained time is 23:00 on January 22, 2025;

[0393] In step S521, the time in the ten-digit standard format is 2025012223;

[0394] In step S522, the account number is ZHangHao12234, and the time corresponding to the account number ZHangHao12234 is 3332025012223;

[0395] The password is MIma912, and the time corresponding to the password MIma912 is 5012223;

[0396] In step S523, the account number is HanZgHao12234, and the time corresponding to the account number HanZgHao12234 is 3332025012223;

[0397] The password is ImaM912, and the time corresponding to the password ImaM912 is 5012223;

[0398] In step S524, the ASCII form of the account number HanZgHao12234 is 1001000110000111011101011010110011110010001100001110111101100010110010011001001100110110100, and the ASCII form of the time 3332025012223 corresponding to the account number HanZgHao12234 is 0110011011001101100110110010011000001100100110101011000001100010110010011001001100100110011; the ASCII form of the encrypted account number is 1111011101001010111011101000101011111110101010100101111100000000000000000000000000010000111, and the corresponding encrypted account number is {R]hWzT_NUT NUT NUTSOH BEL, as shown in Table 1.

[0399] Table 1 ASCII corresponding to each character in the account number, time, and encrypted account number

[0400] Character ASCII Character ASCII Character ASCII H 1001000 3 0110011 { 1111011 a 1100001 3 0110011 R 1010010 n 1101110 3 0110011 ] 1011101 Z 1011010 2 0110010 h 1101000 g 1100111 0 0110000 W 1010111 H 1001000 2 0110010 z 1111010 a 1100001 5 0110101 T 1010100 o 1101111 0 0110000 _ 1011111 1 0110001 1 0110001 NUT 0000000 2 0110010 2 0110010 NUT 0000000 2 0110010 2 0110010 NUT 0000000 3 0110011 2 0110010 SOH 0000001 4 0110100 3 0110011 BEL 0000111

[0401] The ASCII form of the account number of the password ImaM912 is 1001001110110111000011001101011100101100010110010, and the ASCII form of the time 5012223 corresponding to the password ImaM912 is 0110101011000001100010110010011001001100100110011; the ASCII form of the encrypted password is 1111100101110110100001111111000101100000110000001, and the corresponding encrypted password is |]P DEL VT ETX SOH, as shown in Table 2.

[0402] Table 2 ASCII corresponding to each character in the password, time, and encrypted password

[0403] Character ASCII Character ASCII Character ASCII I 1001001 5 0110101 | 1111100 m 1101101 0 0110000 ] 1011101 a 1100001 1 0110001 P 1010000 M 1001101 2 0110010 DEL 1111111 9 0111001 2 0110010 VT 0001011 1 0110001 2 0110010 ETX 0000011 2 0110010 3 0110011 SOH 0000001

[0404] In a preferred embodiment of the present invention, the method for decrypting the received account number and password that have undergone secure encryption processing in step S54 includes the following steps:

[0405] S541. Obtain the current moment and convert it into a ten - digit standard format.

[0406] S542. Determine the magnitude relationship between the number of digits of the received encrypted account and encrypted password and 10:

[0407] S5221. If the number of digits of the encrypted account is less than 10, then remove e′1 digits from the front of the ten - digit standard - formatted moment. After removal, it is equal to the number of digits of the encrypted account; proceed to the next step; e′1 = 10 - e′0, where e′0 is the number of digits of the encrypted account and e1′ is the number of digits removed from the moment.

[0408] If the number of digits of the encrypted account is greater than 10, then add e′2 digits e′3 to the front of the ten - digit standard - formatted moment. After addition, it is equal to the number of digits of the encrypted account; proceed to the next step; e′2 = e′0 - 10, where e′0 is the number of digits of the encrypted account, e′2 is the number of digits added to the moment, and e′3 is the last digit value in the ten - digit standard format.

[0409] If the number of digits of the encrypted account is equal to 10, proceed to the next step;

[0410] S5222. If the number of digits of the encrypted password is less than 10, then remove f1′ digits from the front of the ten - digit standard - formatted moment. After removal, it is equal to the number of digits of the encrypted password; proceed to the next step; f1′ = 10 - f0′, where f0′ is the number of digits of the encrypted password and f1′ is the number of digits removed from the moment.

[0411] If the number of digits of the encrypted password is greater than 10, then add f2′ digits f3′ to the front of the ten - digit standard - formatted moment. After addition, it is equal to the number of digits of the encrypted password; proceed to the next step; f2′ = f0′ - 10, where f0′ is the number of digits of the encrypted password, f2′ is the number of digits added to the moment, and f3′ is the last digit value in the ten - digit standard format.

[0412] If the number of digits of the encrypted password is equal to 10, proceed to the next step;

[0413] At this time, the encrypted account and encrypted password remain unchanged, but the moments corresponding to the encrypted account and encrypted password may change;

[0414] S543. Move each of the first f4′ digits of the encrypted account and encrypted password one position backward as a whole, where f4′ = floor(f3′ / 2), and f4′ is the number of digits as a whole;

[0415] S544. Convert each character in the encrypted account, encrypted password, and moment into a 7 - bit binary ASCII form. Calculate the ASCII - form encrypted account with the ASCII - form moment, and calculate the ASCII - form encrypted password with the ASCII - form moment to obtain the decrypted account and decrypted password respectively.

[0416]

[0417] g″′2(φ′) represents the φ′-th numerical value in the decrypted account in ASCII form;

[0418] g″2(φ′) represents the φ′-th numerical value in the encrypted account in ASCII form;

[0419] t″2(φ′) represents the φ′-th numerical value in the time in ASCII form;

[0420] φ′ = 1, 2, 3, ……, φ′1; φ′1 is the number of digits of the encrypted account in ASCII form;

[0421] φ′1 = 7φ′2, where φ′2 is the number of digits of the encrypted account;

[0422] ◇ represents the swap value operator;

[0423]

[0424] v″′2(θ′) represents the θ′-th numerical value in the decrypted password in ASCII form;

[0425] v″2(θ′) represents the θ′-th numerical value in the encrypted password in ASCII form;

[0426] t″2(θ′) represents the θ′-th numerical value in the time in ASCII form;

[0427] θ′ = 1, 2, 3, ……, θ′1; θ′1 is the number of digits of the encrypted password in ASCII form;

[0428] θ′1 = 7θ′2, where θ′2 is the number of digits of the encrypted password;

[0429] Convert the decrypted account in ASCII form and the decrypted password in ASCII form into the decrypted account and decrypted password in character form.

[0430] The present invention also discloses a computer system, including:

[0431] A processor;

[0432] A memory for storing processor-executable instructions;

[0433] Wherein, when the processor is configured to execute the executable instructions, the land anomaly change monitoring method based on multi-modal geographical features is implemented.

[0434] The present invention also discloses a computer-readable storage medium, including:

[0435] A memory, on which a computer program is stored;

[0436] A processor for executing the program in the memory to implement the method for monitoring land abnormal changes based on multimodal geographical features.

[0437] Although the embodiments of the present invention have been shown and described, those of ordinary skill in the art can understand that various changes, modifications, substitutions, and variations can be made to these embodiments without departing from the principles and spirit of the present invention. The scope of the present invention is defined by the claims and their equivalents.

Claims

1. A method for monitoring land abnormal changes based on multi-modal geographical features, characterized in that, It includes the following steps: S1. Obtain land monitoring images by one or any combination of satellite images, drone cruising, and on-site inspections; S2. Store the land monitoring images obtained in step S1 by one or any combination of satellite images, drone cruising, and on-site inspections in the natural resources information system; S3. Determine the abnormal land changes based on the land monitoring images stored in the natural resources information system; S4. Issue a land abnormal change report for the land with abnormal land changes. The land abnormal change report shall include at least one or any combination of the geographical location where the land abnormal change occurs, the occupied acreage, and the comparison images before and after the land abnormal change.

2. The method for monitoring abnormal land changes based on multi-modal geographical features according to claim 1, wherein The method of storing the land monitoring images obtained in step S1 by one or any combination of satellite images, drone cruising, and on-site inspections in the natural resources information system in step S2 includes the following steps: S21. Obtain the pixel values of each channel in the land monitoring images: C j represents the pixel value of the j-th channel, where j = r, g, b; (x p ,y q ) j represents the pixel value at the position (x p ,y q ) of the j-th channel. p = 1, 2, 3, ……, P, where P is the number of horizontal pixel points; q = 1, 2, 3, ……, Q, where Q is the number of vertical pixel points; S22. Determine whether the pixel values of each channel in the land monitoring images are binary pixel values containing only 0 and 1: If the pixel values of each channel in the land monitoring images are binary pixel values containing only 0 and 1, proceed to the next step; If the pixel values of each channel in the land monitoring images are not binary pixel values containing only 0 and 1, change the pixel values of each channel in the land monitoring images to binary pixel values containing only 0 and 1, and proceed to the next step; S23. Determine whether the number of digits of each pixel value in each channel of the land monitoring images is consistent with the preset digit threshold: If the number of digits of each pixel value in each channel of the land monitoring images is consistent with the preset digit threshold, proceed to the next step; If the number of digits of the pixel values in each channel of the land monitoring images is inconsistent with the preset digit threshold, fill 0 at the front of the pixel values in each channel of the land monitoring images to make the number of digits of the pixel values in each channel of the land monitoring images consistent with the preset digit threshold, and proceed to the next step; C j ′ represents the pixel value whose number of bits of the pixel value of the j-th channel is consistent with the preset bit threshold, where j = r, g, b; (x p , y q )' j represents the pixel value of the j-th channel at the position (x p , y q ) whose number of bits is consistent with the preset bit threshold, p = 1, 2, 3, ……, P, where P is the number of horizontal pixel points; q = 1, 2, 3, ……, Q, where Q is the number of vertical pixel points; S24. Connect the pixel values of each channel: is the channel connection pixel value for the j-th channel; (x p , y q )' j represents the pixel value whose number of bits of the pixel value at the position (x p , y q ) is consistent with the preset bit number threshold; p = 1, 2, 3, ……, P, where P is the number of horizontal pixel points; q = 1, 2, 3, ……, Q, where Q is the number of vertical pixel points; When j = r, the channel-connected pixel value of the red channel is: The pixel value of the channel connection for the red channel; (x p , y q )' r represents the pixel value whose number of bits of the pixel value at position (x p , y q ) is consistent with the preset bit number threshold; p = 1, 2, 3, ……, P, where P is the number of horizontal pixel points; q = 1, 2, 3, ……, Q, where Q is the number of vertical pixel points; When j = g, the channel-connected pixel value of the green channel is: is the channel connection pixel value of the green channel; (x p , y q )' g represents a pixel value whose number of bits of the pixel value at the position (x p , y q ) in the green channel is consistent with the preset bit number threshold; p = 1, 2, 3, ……, P, where P is the number of horizontal pixel points; q = 1, 2, 3, ……, Q, where Q is the number of vertical pixel points; When j = b, the channel-connected pixel value of the blue channel is: is the channel connection pixel value for the blue channel; (x p , y q )′ b represents the pixel value whose number of bits of the pixel value at position (x p , y q ) in the blue channel is consistent with the preset bit number threshold; p = 1, 2, 3, ……, P, where P is the number of horizontal pixel points; q = 1, 2, 3, ……, Q, where Q is the number of vertical pixel points; S25. Fully connect the channel-connected pixel values of each channel to obtain the fully connected pixel value Among them, F cen is the fully connected pixel value; is the pixel value of the channel connection for the red channel; is the channel connection pixel value of the green channel; is the channel connection pixel value for the blue channel; S26. Generate a fully-connected merged pixel value based on the fully-connected pixel values: F mes = coalesceway(F cen ) Among them, F mes represents the merged pixel value; F cen is the fully connected pixel value; coalesceway() represents the function for calculating the merged pixel value; Among them, F neu represents the fully connected merged pixel value; F mes represents the combined pixel value; K represents the number of merged pixel values; where K represents the number of merged pixel values; floor() represents the rounding function; P is the number of horizontal pixel points; Q is the number of vertical pixel points; Indicates the number of bits for combining pixel values; S27. Compare the pixel values of each channel in step S23 with the fully-connected merged pixel value to obtain the swapped pixel value of each channel: Among them, represents exchange value; Indicates the value of the p -th bit in (x q , y j )′ ; F neu (τ) represents the value of the τ-th bit in the fully connected merged pixel value F neu ; ◇ represents the swap value operator; p, q, P, τ, satisfy the following among η: where τ is the τ in F neu (τ); η is the preset bit threshold, which is equal to the depth of the land monitoring image; P is the number of horizontal pixel points; p is the subscript value of the abscissa in q is the subscript value of the ordinate in For in ; S28. The swapped pixel value of each channel is: C j ″ represents the exchanged pixel value of the j-th channel, where j = r, g, b; (x p , y q )″ j represents the swapped pixel value of the j-th channel at the position (x p , y q ); p = 1, 2, 3, ……, P, where P is the number of horizontal pixel points; q = 1, 2, 3, ……, Q, where Q is the number of vertical pixel points; S29. Generate an image based on the pixel values of each channel and store it in the natural resources information system.

3. The land abnormal change monitoring method based on multimodal geographic features according to claim 1, wherein The method for determining the abnormal land change situation based on the land monitoring image stored in the natural resources information system in step S3 includes the following steps: S31. Obtain the selected date, and the selected date includes the selection of the reference date and the comparison date; the reference date includes year, month, and day, the comparison date includes year, month, and day, and if the reference date and the comparison date are not the same day, they are different dates; S32. Obtain the search string stored under the selected date according to the selected date; S33. Search for the stored image corresponding to the search string according to the search string, and use the search string and the stored image corresponding to the search string to obtain the land monitoring images of different dates; S34. Determine the abnormal land change situation based on the land monitoring images of different dates.

4. The method for monitoring land abnormal changes based on multi-modal geographical features according to claim 1, wherein The method for obtaining the land monitoring images of different dates by using the search string and the image corresponding to the search string in step S33 includes the following steps: S331. Obtain the pixel values of each channel in the stored image: D j represents the pixel value of the j-th channel in the stored image, where j = r, g, b; (x′ p ,y′ q ) j represents the pixel value at the position (x′ p ,y′ q ) in the j-th channel of the stored image. p = 1, 2, 3, ……, P, where P is the number of horizontal pixel points; q = 1, 2, 3, ……, Q, where Q is the number of vertical pixel points; S332. Determine whether the pixel values of each channel in the stored image are binary pixel values containing only 0 and 1: If the pixel values of each channel in the stored image are binary pixel values containing only 0 and 1, then proceed to the next step; If the pixel values of each channel in the stored image are not binary pixel values containing only 0 and 1, then change the pixel values of each channel in the stored image to binary pixel values containing only 0 and 1, and proceed to the next step; S333. Determine whether the number of bits of each pixel value in each channel of the stored image is consistent with the preset bit threshold: If the number of bits of each pixel value in each channel of the stored image is consistent with the preset bit threshold, then proceed to the next step; If the number of bits of the pixel values in each channel of the stored image is inconsistent with the preset bit threshold, then add 0 at the front of the pixel values in each channel of the stored image to make the number of bits of the pixel values in each channel of the stored image consistent with the preset bit threshold, and proceed to the next step; D j ′ represents the pixel value whose number of bits of the pixel value of the j-th channel in the stored image is consistent with the preset bit threshold, where j = r, g, b; (x′ p ,y′ q )′ j represents the pixel value whose number of bits of the pixel value at the position (x′ p ,y′ q ) in the j-th channel of the stored image is consistent with the preset bit number threshold, p = 1, 2, 3, ……, P, where P is the number of horizontal pixel points; q = 1, 2, 3, ……, Q, where Q is the number of vertical pixel points; S334. Fully connect K' search strings to obtain a fully-connected search string: Among them, F str represents the fully connected search string; F sea represents a search string; K' represents the number of search strings; where K' represents the number of search strings; floor() represents the rounding function; P is the number of horizontal pixel points; Q is the number of vertical pixel points; Indicates the number of digits of the search string; S335. Compare the pixel values of each channel in step S333 with the fully connected search strings to obtain the swapped pixel values of each channel: Among them, represents exchange value; Indicates the value of the p -th bit in (x′ q , y′ j )′ ; F str (τ) represents the value of the τ-th bit in the fully connected search string F str ; F str represents the fully connected search string; ◇ represents the swap value operator; p, q, P, τ, , and η satisfy: where τ is the τ in F str (τ); η is a preset bit threshold, equal to the depth of the stored image; P is the number of horizontal pixel points; p is the subscript value of the abscissa in q is the subscript value of the vertical coordinate in For in ; S336. The swapped pixel values of each channel in the stored image are: D j ″ represents the swapped pixel value of the j-th channel in the stored image, where j = r, g, b; (x′ p ,y′ q )″ j represents the swapped pixel value at the position (x′ p ,y′ q ) in the j-th channel of the stored image; p = 1, 2, 3,..., P, where P is the number of horizontal pixel points; q = 1, 2, 3,..., Q, where Q is the number of vertical pixel points; S337. Generate an image based on the swapped pixel values of each channel.

5. The land anomaly change monitoring method based on multi-modal geographical features according to claim 1, characterized in that The method for determining the abnormal land changes according to the land monitoring images of different dates in step S34 includes the following steps: S341. Obtain the pixel values of each channel in the land monitoring image: E j represents the pixel value of the j-th channel, where j = r, g, b; (x′ p ′,y′ q ′) j represents the pixel value of the j-th channel at the position (x′ p ′,y′ q ′), p = 1, 2, 3,..., P, where P is the number of horizontal pixel points; q = 1, 2, 3,..., Q, where Q is the number of vertical pixel points; S342. Generate the pixel values of the merged channels according to the pixel values of each channel in the obtained land monitoring image: Among them, E rgb represents the pixel value of the merged channel; δ r represents the pixel value coefficient of the red channel; δ g represents the pixel value coefficient of the green channel; δ b represents the pixel value coefficient of the blue channel; δ r (x′ p ′,y′ q ′) r +δ g (x′ p ′,y′ q ′) g +δ r (x′ p ′,y′ q ′) b represents the pixel value of the merged channel at the position (x′ p ′,y′ q ′); p = 1, 2, 3,..., P, where P is the number of horizontal pixel points; q = 1, 2, 3,..., Q, where Q is the number of vertical pixel points; S343. Determine the pixel values for the pixel values of the same date: S3431, arrange all pixel values at the same pixel coordinate in ascending order, which are Pix1, Pix2, Pix3, ……, Pix H ; S3432, take as the pixel value participating in the calculation to obtain the first determined pixel value: where Pix1 represents the pixel value ranked 1st after arranging the pixel values of the same pixel coordinates in ascending order; Pix2 represents the pixel value ranked 2nd after arranging the pixel values of the same pixel coordinates in ascending order; Pix3 represents the pixel value ranked 3rd after arranging the pixel values of the same pixel coordinates in ascending order; Pix H represents the pixel value at the H-th position after arranging the pixel values of the same pixel coordinates in ascending order; It represents the pixel value that is in the h1-th position after arranging the pixel values of the same pixel coordinates in ascending order. It represents the pixel value at the h2-th position after arranging the pixel values at the same pixel coordinates in ascending order. Pix con1 represents a first determined pixel value; H represents the number of images taken on the same date; S3433, take all pixel values Pix1, Pix2, Pix3, ……, Pix at the same pixel coordinate H as the pixel values participating in the calculation to obtain the second determined pixel value: wherein, Pix con2 represents a second determined pixel value; H represents the number of images taken on the same date; Pix j represents the pixel value at the j-th position after arranging the pixel values at the same pixel coordinates in ascending order; S3434. Determine the magnitude relationship between the first determined pixel value and the second determined pixel value: If |Pix con1 -Pix con2 | ≤ Pix sd , then the second determined pixel value is the determined pixel value; If |Pix con1 -Pix con2 | > Pix sd , then the first determined pixel value is the determined pixel value; Pix sd is the preset pixel value exceeding the threshold; S344. Determine the pixel value anomalies for the pixel values of different dates: If then there is no abnormal change in the land at the pixel point (x′ p ″, y′ q ″); is a preset first abnormal change threshold, If then there is an abnormal change in the land at the pixel point (x′ p ″, y′ q ″); Among them, then a level III abnormal change occurs in the land at the pixel point (x′ p ″, y′ q ″); is a preset second abnormal change threshold; Then there is a level II abnormal change in the land at the pixel point (x′ p ″, y′ q ″); is the preset third abnormal change threshold; Then, there is a Class-I abnormal change in the land at the pixel point (x′″ p , y′″ p ); p = 1, 2, 3,..., P, where P is the number of horizontal pixel points; q = 1, 2, 3, ……, Q, where Q is the number of vertical pixel points; Pix dat (x′ p ″, y′ q ″) is the pixel value of the reference date image at the pixel point (x′ p ″, y′ q ″); Pix com (x′ p ″, y′ q ″) is the pixel value of the comparison date image at the pixel point (x′ p ″, y′ q ″); Level III abnormal changes are lower than Level II abnormal changes, and Level I abnormal changes are higher than Level II abnormal changes.

6. The land anomaly change monitoring method based on multi-modal geographical features according to claim 1, characterized in that, After step S4, there is also step S5, enter the natural resources information system using a mobile phone or an office computer; after entering the natural resources information system using a mobile phone or an office computer, download and view the land abnormal change report.

7. A computer system, characterized in that, Including: a processor; a memory for storing the executable instructions of the processor; wherein, when the processor is configured to execute the executable instructions, it implements the method for monitoring abnormal land changes based on multi-modal geographical features according to one of claims 1 to 6.

8. A computer-readable storage medium, characterized in that, Including: a memory, on which a computer program is stored; a processor, for executing the program in the memory to implement the method for monitoring abnormal land changes based on multi-modal geographical features according to one of claims 1 to 6.

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