Method and system for realizing comprehensive evaluation of ecological resources based on big data model, and application medium

Abstract

The invention provides an ecological resource comprehensive evaluation method and system based on a big data model, and an application medium. The evaluation method comprises the following steps: S1, obtaining massive ecological resource image data shot by a remote sensing satellite; s2, filtering the mass ecological resource image data in the step S1 to obtain filtered mass ecological resource image data; s3, screening the filtered mass ecological resource image data to obtain screened mass ecological resource image data; and S4, evaluating the ecological environment degree of the screened massive ecological resource image data. According to the method, the environmental degree evaluation of the image shooting area can be obtained by analyzing the shot massive ecological resource image data.

Description

Technical Field

[0001] The present invention relates to the field of ecological environment technology, and in particular to a method, system and application medium for realizing comprehensive evaluation of ecological resources based on a big data model. Background Art

[0002] my country attaches great importance to ecological environmental protection and insists on taking a new path of synergistic coexistence between protecting the ecological environment and developing productivity. Patent application number 202210851439X, named "An Environmental Credit Evaluation System and Method", discloses a data acquisition module, an evaluation module and a display module. The data acquisition module is used to obtain the environmental data of the participating units, and the environmental data includes the environmental data uploaded by the participating units; the evaluation module is used to analyze the environmental data and obtain the evaluation results, and the evaluation results include the environmental health level and the environmental credit level. The environmental health level is used to reflect the illegal risk of the current environmental behavior of the participating units, and the environmental credit level is used to reflect the credit of the long-term environmental behavior of the participating units; the display module is used to display the evaluation results through the display platform. 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 method, system and application medium for realizing comprehensive evaluation of ecological resources based on a big data model.

[0004] In order to achieve the above-mentioned object of the present invention, the present invention provides a method for realizing comprehensive evaluation of ecological resources based on a big data model, comprising the following steps:

[0005] S1, obtain massive ecological resource image data taken by remote sensing satellites;

[0006] S2, filtering the massive ecological resource image data in step S1 to obtain the filtered massive ecological resource image data;

[0007] S3, screening the filtered massive ecological resource image data to obtain screened massive ecological resource image data;

[0008] S4, evaluate the ecological environment degree of the screened massive ecological resource image data.

[0009] In a preferred embodiment of the present invention, in step S1, the format of the massive ecological resource image data photographed by the remote sensing satellite is one of TIFF, JPEG2000, IMG, ECW, MrSID or any combination thereof.

[0010] In a preferred embodiment of the present invention, in step S2, the massive ecological resource image data in step S1 is filtered out, and the method for obtaining the filtered massive ecological resource image data includes the following steps:

[0011] S21, counting the number of the massive ecological resource image data obtained in step S1, recorded as M; respectively, the first ecological resource image, the second ecological resource image, the third ecological resource image, ..., the Mth ecological resource image; let the image sequence number j = 1;

[0012] S22, calculating the jth reserved code for the jth ecological resource image, and determining whether the jth reserved code exists in the reserved code determination set:

[0013] If the jth reserved code exists in the reserved code judgment set, the jth reserved code and the jth ecological resource image corresponding to the jth reserved code are screened out, j=j+1; and the next step is executed;

[0014] If the jth reserved code does not exist in the reserved code judgment set, then the jth reserved code is saved in the reserved code judgment set, and the mth ecological resource image corresponding to the jth reserved code is retained in the image retention set, j=j+1; execute the next step;

[0015] S23, determine the size relationship between j and M:

[0016] If j≤M, j represents the image sequence number, and M represents the number of the massive ecological resource image data in step S1, then step S22 is executed;

[0017] If j>M, j represents the image sequence number, and M represents the number of the massive ecological resource image data in step S1, then all ecological resource images in the image retention set are the massive ecological resource image data after filtering.

[0018] In a preferred embodiment of the present invention, the method for calculating the jth reserved code for the jth ecological resource image in step S22 is:

[0019] Retentioncode j =Retentioncodecalculateway(Ecologicalresourcesimage j ),

[0020] Among them, Retentioncode j represents the jth reserved code;

[0021] Retentioncodecalculateway() represents the j-th retention code calculation method, preferably using the digest algorithm MD5;

[0022] Ecological resources image j Represents the j-th ecological resources image;

[0023] Ecological resources image = {Ecological resources image1,

[0024] Ecological resources image2, Ecological resources image3, ……, Ecological resources image M}, where Ecological resources image represents the set of ecological resources images composed of the massive ecological resources image data captured by the remote sensing satellite in step S1, Ecological resources image1 represents the 1st ecological resources image, Ecological resources image2 represents the 2nd ecological resources image, Ecological resources image3 represents the 3rd ecological resources image, Ecological resources image M represents the M-th ecological resources image, Ecological resources image j ∈ Ecological resources image.

[0025] In a preferred embodiment of the present invention, in step S3, the filtered massive ecological resources image data is screened, and the steps for obtaining the screened massive ecological resources image data are as follows:

[0026] S31, count the number of the filtered massive ecological resources image data in step S2, denoted as N; they are the 1st ecological image, the 2nd ecological image, the 3rd ecological image, ……, the -th ecological image respectively; let the image serial number v = 1;

[0027] S32, convert the v-th ecological image into the v-th converted image, and calculate the difference value of the v-th converted image by using the v-th converted image;

[0028] S33, judge the size relationship between v and N:

[0029] If v < N, where v represents the image serial number and N represents the number of the filtered massive ecological resources image data, then v = v + 1, and execute step S32;

[0030] If v ≥ N, where v represents the image serial number and N represents the number of the filtered massive ecological resources image data, then execute the next step;

[0031] S34, arranging all the difference values ​​in descending order, taking the filtered massive ecological resource image data corresponding to the first q difference values ​​as the screened massive ecological resource image data, where q is a positive integer less than N.

[0032] In a preferred embodiment of the present invention, the method of converting the vth ecological image into the vth conversion image in step S32 is:

[0033] f(x v ,y v )=λ r RED(x v ,y v )+λ g GREEN(x v ,y v )+λ b BLUE(x v ,y v ),

[0034] Among them, f(x v ,y v ) represents the vth transformed image at pixel (x v ,y v ) at the conversion value;

[0035] RED(x v ,y v ) represents the vth ecological image at pixel (x v ,y v ) is the pixel value of the red channel at ;

[0036] GREEN(x v ,y v ) represents the vth ecological image at pixel (x v ,y v ) is the pixel value of the green channel at ;

[0037] BLUE(x v ,y v ) represents the vth ecological image at pixel (x v ,y v ) is the pixel value of the blue channel at ;

[0038] Constraints:

[0039] λ r , g , b ∈[0,1];

[0040] λ r +λ g +λ b =1;

[0041] x v =1, 2, 3, ..., X v ;X v Indicates the number of pixels in the x-axis direction of the vth ecological image;

[0042] y v =1, 2, 3, ..., Y v ; Y v Indicates the number of pixels in the Y-axis direction of the vth ecological image;

[0043] The method for calculating the difference value of the vth conversion image using the vth conversion image in step S32 is:

[0044]

[0045] Among them, Q v represents the difference value of the vth transformed image;

[0046] f(x+1,y) represents the conversion value of the vth conversion image at the pixel point (x+1,y);

[0047] f(x,y) represents the conversion value of the vth conversion image at the pixel point (x,y);

[0048] f(x,y+1) represents the conversion value of the vth conversion image at the pixel point (x,y+1);

[0049] X v Indicates the number of pixels in the x-axis direction of the vth ecological image;

[0050] Y v Indicates the number of pixels in the Y-axis direction of the vth ecological image.

[0051] In a preferred embodiment of the present invention, the method for evaluating the ecological environment degree of the filtered massive ecological resource image data in step S4 includes the following steps:

[0052] S41, set k=1;

[0053] S42, obtain the pixel values ​​of the three channels of the k-th image, which are RED(x k′ ,y k′ )、GREEN(x k′ ,y k′ )、BLUE(x k′ ,y k′ );

[0054] RED(x k′ ,y k′ ) indicates that the kth image is at pixel (x k′ ,yk′ ) is the pixel value of the red channel at ;

[0055] GREEN(x k′ ,y k′ ) indicates that the kth image is at pixel (x k′ ,y k′ ) is the pixel value of the green channel at ;

[0056] BLUE(x k′ ,y k′ ) indicates that the kth image is at pixel (x k′ ,y k′ ) is the pixel value of the blue channel at ;

[0057] x k′ =1, 2, 3, ..., X k′ ;X k′ Indicates the number of pixels in the k-th image in the X-axis direction;

[0058] y k′ =1, 2, 3, ..., Y k′ ; Y k′ Indicates the number of pixels in the Y-axis direction of the k-th image;

[0059] S43, That is, if GREEN(x k′ ,y k′ )≥GREEN0&RED(x k′ ,y k′ )≤RED0&BLUE(x k′ ,y k′ )≤BLUE0, GREEN0 represents the preset green channel pixel value, RED0 represents the preset red channel pixel value, BLUE0 represents the preset blue channel pixel value, & represents the logical relationship and, if represents if; then W(x k′ ,y k′ )=1; otherwise W(x k′ ,y k′ )=0;

[0060] W k =∑W(x k′ ,y k′ ) is to accumulate and sum the k-th image to obtain the k-th image judgment value;

[0061] S44, judge W k The relationship between W0 and the

[0062] If W k ≥W0,W krepresents the judgment value of the kth image, W0 represents the preset judgment threshold, then the image is retained; the image is evaluated and the next step is executed;

[0063] If W k <W0,W k represents the judgment value of the kth image, W0 represents the preset judgment threshold, then delete the image; proceed to the next step;

[0064] S45, determine the size relationship between k and K:

[0065] If k<K, K represents the number of filtered massive ecological resource image data, and k represents the image sequence number, then k=k+1, and step S42 is executed;

[0066] If k ≥ K, K represents the number of filtered massive ecological resource image data, and k represents the image sequence number, then the process ends.

[0067] In a preferred embodiment of the present invention, the method for evaluating the retained image in step S44 comprises the following steps:

[0068] S441, obtain the pixel values ​​of the three channels of the retained image, which are

[0069] Indicates Keep the image at the pixel level The pixel value of the red channel at ;

[0070] Indicates Keep the image at the pixel level The pixel value of the green channel at ;

[0071] Indicates Keep the image at the pixel level The pixel value of the blue channel at ;

[0072] Indicates Keep the number of pixels of the image in the X-axis direction; Indicates Keep the number of pixels of the image in the Y-axis direction;

[0073] S442, That is, if but if

[0074] but if but GREEN0 represents the preset green channel pixel value, GREEN′ represents the preset green channel first pixel value, GREEN′>GREEN0; RED0 represents the preset red channel pixel value, RED′ represents the preset red channel first pixel value, RED0>RED′; BLUE0 represents the preset blue channel pixel value, BLUE′ represents the preset blue channel first pixel value; & represents the logical relationship and, if represents if; η3>η2>η1>0; η1 represents the preset first environment value, η2 represents the preset second environment value, and η3 represents the preset third environment value;

[0075] That is to Keep the image and add it up to get the Image environment value;

[0076] S443, if Q0 represents the preset first environmental total value, and the area corresponding to the image has an excellent ecological environment;

[0077] like Q0′ represents the preset second environment total value, and the area corresponding to the image is a fresh ecological environment;

[0078] like Q0 represents the preset first environment total value, Q0′ represents the preset second environment total value, and if Q0>Q0′, the area corresponding to the image has a good ecological environment;

[0079] S443, judgment The relationship between ε and ε is:

[0080] like represents the reserved image sequence number, ε represents the number of reserved images; then Execute step S441;

[0081] like Indicates the reserved image sequence number, ε indicates the number of reserved images; then it ends.

[0082] The present invention also discloses a system for realizing comprehensive evaluation of ecological resources based on a big data model, including an ecological resource image data acquisition module, an ecological resource image data filtering module, an ecological resource image data screening module, and an ecological resource image data evaluation module;

[0083] The data output end of the ecological resource image data acquisition module is connected to the data input end of the ecological resource image data filtering module. The data output end of the ecological resource image data filtering module is connected to the data input end of the ecological resource image data screening module. The data output end of the ecological resource image data screening module is connected to the data input end of the ecological resource image data evaluation module;

[0084] The ecological resource image data acquisition module is used to acquire a large amount of ecological resource image data captured by remote sensing satellites;

[0085] The ecological resource image data filtering module is used to filter the large amount of ecological resource image data in the ecological resource image data acquisition module to obtain the filtered large amount of ecological resource image data;

[0086] The ecological resource image data screening module is used to screen the filtered large amount of ecological resource image data to obtain the screened large amount of ecological resource image data;

[0087] The ecological resource image data evaluation module is used to evaluate the ecological environment degree of the screened large amount of ecological resource image data.

[0088] In a preferred embodiment of the present invention, screening the filtered large amount of ecological resource image data in the ecological resource image data screening module to obtain the screened large amount of ecological resource image data includes the following steps:

[0089] S31. Count the quantity of the filtered large amount of ecological resource image data in step S2, denoted as N; they are the 1st ecological image, the 2nd ecological image, the 3rd ecological image,..., the th ecological image respectively; let the image serial number v = 1;

[0090] S32. Convert the vth ecological image into the vth converted image, and calculate the difference value of the vth converted image by using the vth converted image;

[0091] S33. Judge the size relationship between v and N:

[0092] If v < N, where v represents the image serial number and N represents the quantity of the filtered large amount of ecological resource image data, then v = v + 1, and execute step S32;

[0093] If v ≥ N, where v represents the image serial number and N represents the quantity of the filtered large amount of ecological resource image data, then execute the next step;

[0094] S34. Arrange all the difference values in descending order, and take the filtered large amount of ecological resource image data corresponding to the first q difference values as the screened large amount of ecological resource image data, where q is a positive integer less than N.

[0095] In a preferred embodiment of the present invention, the method for evaluating the ecological environment of the filtered massive ecological resource image data in the ecological resource image data evaluation module comprises the following steps:

[0096] S41, set k=1;

[0097] S42, obtain the pixel values ​​of the three channels of the k-th image, which are RED(x k′ ,y k′ )、GREEN(x k′ ,y k′ )、BLUE(x k′ ,y k′ );

[0098] RED(x k′ ,y k′ ) indicates that the kth image is at pixel (x k′ ,y k′ ) is the pixel value of the red channel at ;

[0099] GREEN(x k′ ,y k′ ) indicates that the kth image is at pixel (x k′ ,y k′ ) is the pixel value of the green channel at ;

[0100] BLUE(x k′ ,y k′ ) indicates that the kth image is at pixel (x k′ ,y k′ ) is the pixel value of the blue channel at ;

[0101] x k′ =1, 2, 3, ..., X k′ ;X k′ Indicates the number of pixels in the k-th image in the X-axis direction;

[0102] y k′ =1, 2, 3, ..., Y k′ ; Y k′ Indicates the number of pixels in the Y-axis direction of the k-th image;

[0103] S43, That is, if GREEN(x k′ ,y k′ )≥GREEN0&RED(x k′ ,y k′ )≤RED0&BLUE(x k′ ,y k′)≤BLUE0, GREEN0 represents the preset green channel pixel value, RED0 represents the preset red channel pixel value, BLUE0 represents the preset blue channel pixel value, & represents the logical relationship and, if represents if; then W(x k′ ,y k′ )=1; otherwise W(x k′ ,y k′ )=0;

[0104] W k =∑W(x k′ ,y k′ ) is to accumulate and sum the k-th image to obtain the k-th image judgment value;

[0105] S44, judge W k The relationship between W0 and the

[0106] If W k ≥W0,W k represents the judgment value of the kth image, W0 represents the preset judgment threshold, then the image is retained; the image is evaluated and the next step is executed;

[0107] If W k <W0,W k represents the judgment value of the kth image, W0 represents the preset judgment threshold, then delete the image; proceed to the next step;

[0108] S45, determine the size relationship between k and K:

[0109] If k<K, K represents the number of filtered massive ecological resource image data, and k represents the image sequence number, then k=k+1, and step S42 is executed;

[0110] If k ≥ K, K represents the number of filtered massive ecological resource image data, and k represents the image sequence number, then the process ends.

[0111] The present invention also discloses a computer system, comprising:

[0112] processor;

[0113] a memory for storing processor-executable instructions;

[0114] Among them, the processor is configured to implement the method for comprehensive evaluation of ecological resources based on a big data model when executing the executable instructions.

[0115] The present invention also discloses a computer-readable storage medium, comprising:

[0116] a memory having a computer program stored thereon;

[0117] A processor is used to execute the program in the memory to implement the comprehensive evaluation method of ecological resources based on the big data model.

[0118] In summary, due to the adoption of the above technical solution, the present invention can obtain an environmental evaluation of the image shooting area by analyzing the massive amount of ecological resource image data shot.

[0119] 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

[0120] 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:

[0121] Figure 1 It is a schematic block diagram of the process of the present invention. DETAILED DESCRIPTION

[0122] 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.

[0123] The present invention provides a method for realizing comprehensive evaluation of ecological resources based on big data model. Figure 1 As shown, the following steps are included:

[0124] S1, obtain massive ecological resource image data taken by remote sensing satellites;

[0125] S2, filtering the massive ecological resource image data in step S1 to obtain the filtered massive ecological resource image data;

[0126] S3, screening the filtered massive ecological resource image data to obtain screened massive ecological resource image data;

[0127] S4, evaluate the ecological environment degree of the screened massive ecological resource image data.

[0128] In a preferred embodiment of the present invention, in step S1, the format of the massive ecological resource image data photographed by the remote sensing satellite is one of TIFF, JPEG2000, IMG, ECW, MrSID or any combination thereof.

[0129] In a preferred embodiment of the present invention, in step S2, the massive ecological resource image data in step S1 is filtered out, and the method for obtaining the filtered massive ecological resource image data includes the following steps:

[0130] S21, counting the number of the massive ecological resource image data obtained in step S1, recorded as M; respectively, the first ecological resource image, the second ecological resource image, the third ecological resource image, ..., the Mth ecological resource image; let the image sequence number j = 1;

[0131] S22, calculating the jth reserved code for the jth ecological resource image, and determining whether the jth reserved code exists in the reserved code determination set:

[0132] If the jth reserved code exists in the reserved code judgment set, the jth reserved code and the jth ecological resource image corresponding to the jth reserved code are screened out, j=j+1; and the next step is executed;

[0133] If the jth reserved code does not exist in the reserved code judgment set, then the jth reserved code is saved in the reserved code judgment set, and the mth ecological resource image corresponding to the jth reserved code is retained in the image retention set, j=j+1; execute the next step;

[0134] S23, determine the size relationship between j and M:

[0135] If j≤M, j represents the image sequence number, and M represents the number of the massive ecological resource image data in step S1, then execute step S22;

[0136] If j>M, j represents the image sequence number, and M represents the number of the massive ecological resource image data in step S1, then all ecological resource images in the image retention set are the massive ecological resource image data after filtering.

[0137] In a preferred embodiment of the present invention, the method for calculating the jth reserved code for the jth ecological resource image in step S22 is:

[0138] Retentioncode j =Retentioncodecalculateway(Ecologicalresourcesimage j ),

[0139] Among them, Retentioncode j represents the jth reserved code;

[0140] Retentioncodecalculateway() represents the j-th retention code calculation method, preferably using the digest algorithm MD5;

[0141] Ecological resources image j Represents the j-th ecological resources image;

[0142] Ecological resources image = {Ecological resources image1,

[0143] Ecological resources image2, Ecological resources image3, ……, Ecological resources image M}, where Ecological resources image represents the ecological resources image set composed of the massive ecological resources image data captured by the remote sensing satellite in step S1, Ecological resources image1 represents the first ecological resources image, Ecological resources image2 represents the second ecological resources image, Ecological resources image3 represents the third ecological resources image, Ecological resources image M represents the M-th ecological resources image, Ecological resources image j ∈ Ecological resources image.

[0144] In a preferred embodiment of the present invention, in step S3, the filtered massive ecological resources image data is screened, and the steps for obtaining the screened massive ecological resources image data are as follows:

[0145] S31, count the number of the filtered massive ecological resources image data in step S2, denoted as N; they are the first ecological image, the second ecological image, the third ecological image, ……, the -th ecological image; let the image serial number v = 1;

[0146] S32, convert the v-th ecological image into the v-th converted image, and calculate the difference value of the v-th converted image by using the v-th converted image;

[0147] S33, judge the size relationship between v and N:

[0148] If v < N, where v represents the image serial number and N represents the number of the filtered massive ecological resources image data, then v = v + 1, and execute step S32;

[0149] If v ≥ N, where v represents the image serial number and N represents the number of the filtered massive ecological resources image data, then execute the next step;

[0150] S34, arrange all the difference values ​​in order from large to small or from small to large, take the filtered massive ecological resource image data corresponding to the first q difference values ​​as the screened massive ecological resource image data, q is a positive integer less than N.

[0151] In a preferred embodiment of the present invention, the method of converting the vth ecological image into the vth conversion image in step S32 is:

[0152] f(x v ,y v )=λ r RED(x v ,y v )+λ g GREEN(x v ,y v )+λ b BLUE(x v ,y v ),

[0153] Among them, f(x v ,y v ) represents the vth transformed image at pixel (x v ,y v ) at the conversion value;

[0154] RED(x v ,y v ) represents the vth ecological image at pixel (x v ,y v ) is the pixel value of the red channel at ;

[0155] GREEN(x v ,y v ) represents the vth ecological image at pixel (x v ,y v ) is the pixel value of the green channel at ;

[0156] BLUE(x v ,y v ) represents the vth ecological image at pixel (x v ,y v ) is the pixel value of the blue channel at ;

[0157] Constraints:

[0158] λ r , g , b ∈[0,1];

[0159] λ r +λ g +λ b =1;

[0160] x v =1, 2, 3, ..., X v ;X v Indicates the number of pixels in the x-axis direction of the vth ecological image;

[0161] y v =1, 2, 3, ..., Y v ; Y v Indicates the number of pixels in the Y-axis direction of the vth ecological image;

[0162] The method for calculating the difference value of the vth conversion image using the vth conversion image in step S32 is:

[0163]

[0164] Among them, Q v represents the difference value of the vth transformed image;

[0165] f(x+1,y) represents the conversion value of the vth conversion image at the pixel point (x+1,y);

[0166] f(x,y) represents the conversion value of the vth conversion image at the pixel point (x,y);

[0167] f(x,y+1) represents the conversion value of the vth conversion image at the pixel point (x,y+1);

[0168] X v Indicates the number of pixels in the x-axis direction of the vth ecological image;

[0169] Y v Indicates the number of pixels in the Y-axis direction of the vth ecological image.

[0170] In a preferred embodiment of the present invention, the method for evaluating the ecological environment degree of the filtered massive ecological resource image data in step S4 includes the following steps:

[0171] S41, set k=1;

[0172] S42, obtain the pixel values ​​of the three channels of the k-th image, which are RED(x k′ ,y k′ )、GREEN(x k′ ,y k′ )、BLUE(x k′ ,y k′ );

[0173] RED(x k′ ,y k′ ) indicates that the kth image is at pixel (x k′,y k′ ) is the pixel value of the red channel at ;

[0174] GREEN(x k′ ,y k′ ) indicates that the kth image is at pixel (x k′ ,y k′ ) is the pixel value of the green channel at ;

[0175] BLUE(x k′ ,y k′ ) indicates that the kth image is at pixel (x k′ ,y k′ ) is the pixel value of the blue channel at ;

[0176] x k′ =1, 2, 3, ..., X k′ ;X k′ Indicates the number of pixels in the k-th image in the X-axis direction;

[0177] y k′ =1, 2, 3, ..., Y k′ ; Y k′ Indicates the number of pixels in the Y-axis direction of the k-th image;

[0178] S43, That is, if GREEN(x k′ ,y k′ )≥GREEN0&RED(x k′ ,y k′ )≤RED0&BLUE(x k′ ,y k′ )≤BLUE0, GREEN0 represents the preset green channel pixel value, RED0 represents the preset red channel pixel value, BLUE0 represents the preset blue channel pixel value, & represents the logical relationship and, if represents if; then W(x k′ ,y k′ )=1; otherwise W(x k′ ,y k′ )=0;

[0179] W k =∑W(x k′ ,y k′ ) is to accumulate and sum the k-th image to obtain the k-th image judgment value;

[0180] S44, judge W k The relationship between W0 and the

[0181] If W k ≥W0,W krepresents the judgment value of the kth image, W0 represents the preset judgment threshold, then the image is retained; the image is evaluated and the next step is executed;

[0182] If W k <W0,W k represents the judgment value of the kth image, W0 represents the preset judgment threshold, then delete the image; proceed to the next step;

[0183] S45, determine the size relationship between k and K:

[0184] If k<K, K represents the number of filtered massive ecological resource image data, and k represents the image sequence number, then k=k+1, and step S42 is executed;

[0185] If k ≥ K, K represents the number of filtered massive ecological resource image data, and k represents the image sequence number, then the process ends.

[0186] In a preferred embodiment of the present invention, the method for evaluating the retained image in step S44 comprises the following steps:

[0187] S441, obtain the pixel values ​​of the three channels of the retained image, which are

[0188] Indicates Keep the image at the pixel level The pixel value of the red channel at ;

[0189] Indicates Keep the image at the pixel level The pixel value of the green channel at ;

[0190] Indicates Keep the image at the pixel level The pixel value of the blue channel at ;

[0191] Indicates Keep the number of pixels of the image in the X-axis direction; Indicates Keep the number of pixels of the image in the Y-axis direction;

[0192] S442, That is, if but if

[0193] but if but GREEN0 represents the preset green channel pixel value, GREEN′ represents the preset green channel first pixel value, GREEN′>GREEN0; RED0 represents the preset red channel pixel value, RED′ represents the preset red channel first pixel value, RED0>RED′; BLUE0 represents the preset blue channel pixel value, BLUE′ represents the preset blue channel first pixel value; & represents the logical relationship and, if represents if; η3>η2>η1>0; η1 represents the preset first environment value, η2 represents the preset second environment value, and η3 represents the preset third environment value;

[0194] That is to Keep the image and add it up to get the Image environment value;

[0195] S443, if Q0 represents the preset first environmental total value, and the area corresponding to the image has an excellent ecological environment;

[0196] like Q0′ represents the preset second environment total value, and the area corresponding to the image is a fresh ecological environment;

[0197] like Q0 represents the preset first environment total value, Q0′ represents the preset second environment total value, and if Q0>Q0′, the area corresponding to the image has a good ecological environment;

[0198] S443, judgment The relationship between ε and ε is:

[0199] like represents the reserved image sequence number, ε represents the number of reserved images; then Execute step S441;

[0200] like Indicates the reserved image sequence number, ε indicates the number of reserved images; then it ends.

[0201] The present invention also discloses a computer system, comprising:

[0202] processor;

[0203] a memory for storing processor-executable instructions;

[0204] Among them, the processor is configured to implement the method for comprehensive evaluation of ecological resources based on a big data model when executing the executable instructions.

[0205] The present invention also discloses an ecological resource comprehensive evaluation system based on a big data model, including an ecological resource image data acquisition module, an ecological resource image data filtering module, an ecological resource image data screening module, and an ecological resource image data evaluation module;

[0206] The data output end of the ecological resource image data acquisition module is connected to the data input end of the ecological resource image data filtering module, the data output end of the ecological resource image data filtering module is connected to the data input end of the ecological resource image data screening module, and the data output end of the ecological resource image data screening module is connected to the data input end of the ecological resource image data evaluation module;

[0207] The ecological resource image data acquisition module is used to acquire a large amount of ecological resource image data taken by remote sensing satellites;

[0208] The ecological resource image data filtering module is used to filter the large amount of ecological resource image data in the ecological resource image data acquisition module to obtain the filtered large amount of ecological resource image data;

[0209] The ecological resource image data screening module is used to screen the filtered large amount of ecological resource image data to obtain the screened large amount of ecological resource image data;

[0210] The ecological resource image data evaluation module is used to evaluate the ecological environment degree of the screened large amount of ecological resource image data.

[0211] In a preferred embodiment of the present invention, screening the filtered large amount of ecological resource image data in the ecological resource image data screening module to obtain the screened large amount of ecological resource image data includes the following steps:

[0212] S31, count the number of the filtered large amount of ecological resource image data in step S2, denoted as N; they are the first ecological image, the second ecological image, the third ecological image,..., the ecological image; let the image serial number v = 1;

[0213] S32, convert the v-th ecological image into the v-th converted image, and calculate the difference value of the v-th converted image by using the v-th converted image;

[0214] S33, judge the size relationship between v and N:

[0215] If v < N, where v represents the image serial number and N represents the number of the filtered large amount of ecological resource image data, then v = v + 1, and execute step S32;

[0216] If v ≥ N, where v represents the image serial number and N represents the number of the filtered large amount of ecological resource image data, then execute the next step;

[0217] S34, arrange all the difference values ​​in order from large to small or from small to large, take the filtered massive ecological resource image data corresponding to the first q difference values ​​as the screened massive ecological resource image data, q is a positive integer less than N.

[0218] In a preferred embodiment of the present invention, the method for evaluating the ecological environment of the filtered massive ecological resource image data in the ecological resource image data evaluation module comprises the following steps:

[0219] S41, set k=1;

[0220] S42, obtain the pixel values ​​of the three channels of the k-th image, which are RED(x k′ ,y k′ )、GREEN(x k′ ,y k′ )、BLUE(x k′ ,y k′ );

[0221] RED(x k′ ,y k′ ) indicates that the kth image is at pixel (x k′ ,y k′ ) is the pixel value of the red channel at ;

[0222] GREEN(x k′ ,y k′ ) indicates that the kth image is at pixel (x k′ ,y k′ ) is the pixel value of the green channel at ;

[0223] BLUE(x k′ ,y k′ ) indicates that the kth image is at pixel (x k′ ,y k′ ) is the pixel value of the blue channel at ;

[0224] x k′ =1, 2, 3, ..., X k′ ;X k′ Indicates the number of pixels in the k-th image in the X-axis direction;

[0225] y k′ =1, 2, 3, ..., Y k′ ; Y k′ Indicates the number of pixels in the Y-axis direction of the k-th image;

[0226] S43, That is, if GREEN(x k′ ,y k′ )≥GREEN0&RED(xk′ ,y k′ )≤RED0&BLUE(x k′ ,y k′ )≤BLUE0, GREEN0 represents the preset green channel pixel value, RED0 represents the preset red channel pixel value, BLUE0 represents the preset blue channel pixel value, & represents the logical relationship and, if represents if; then W(x k′ ,y k′ )=1; otherwise W(x k′ ,y k′ )=0;

[0227] W k =∑W(x k′ ,y k′ ) is to accumulate and sum the k-th image to obtain the k-th image judgment value;

[0228] S44, judge W k The relationship between W0 and the

[0229] If W k ≥W0,W k represents the judgment value of the kth image, W0 represents the preset judgment threshold, then the image is retained; the image is evaluated and the next step is executed;

[0230] If W k <W0,W k represents the judgment value of the kth image, W0 represents the preset judgment threshold, then delete the image; proceed to the next step;

[0231] S45, determine the size relationship between k and K:

[0232] If k<K, K represents the number of filtered massive ecological resource image data, and k represents the image sequence number, then k=k+1, and step S42 is executed;

[0233] If k ≥ K, K represents the number of filtered massive ecological resource image data, and k represents the image sequence number, then the process ends.

[0234] The present invention also discloses a computer-readable storage medium, comprising:

[0235] a memory having a computer program stored thereon;

[0236] A processor is used to execute the program in the memory to implement the comprehensive evaluation method of ecological resources based on the big data model.

[0237] Although the embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art 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 method for comprehensive evaluation of ecological resources based on a big data model, characterized in that: It includes the following steps: S1. Obtain a large amount of ecological resource image data captured by a remote sensing satellite; S2. Filter the large amount of ecological resource image data in step S1 to obtain the filtered large amount of ecological resource image data; S3. Screen the filtered large amount of ecological resource image data to obtain the screened large amount of ecological resource image data; S4. Evaluate the ecological environment degree of the screened large amount of ecological resource image data.

2. According to claim 1, the method for realizing comprehensive evaluation of ecological resources based on big data model is characterized in that: In step S1, the format of the large amount of ecological resource image data captured by the remote sensing satellite is one of TIFF, JPEG2000, IMG, ECW, MrSID or any combination.

3. The method for realizing comprehensive evaluation of ecological resources based on big data model according to claim 1 is characterized in that: In step S3, screening the filtered large amount of ecological resource image data to obtain the screened large amount of ecological resource image data includes the following steps: S31. Count the quantity of the filtered large amount of ecological resource image data in step S2, denoted as N; they are the 1st ecological image, the 2nd ecological image, the 3rd ecological image,..., the nth ecological image respectively; let the image serial number v = 1; S32. Convert the vth ecological image into the vth converted image, and calculate the difference value of the vth converted image by using the vth converted image; S33. Judge the size relationship between v and N: If v < N, where v represents the image serial number and N represents the quantity of the filtered large amount of ecological resource image data, then v = v + 1, and execute step S32; If v ≥ N, where v represents the image serial number and N represents the quantity of the filtered large amount of ecological resource image data, then execute the next step; S34. Arrange all the difference values in descending order, and take the filtered large amount of ecological resource image data corresponding to the first q difference values as the screened large amount of ecological resource image data, where q is a positive integer less than N.

4. The method for realizing comprehensive evaluation of ecological resources based on big data model according to claim 1 is characterized in that: In step S32, the method of converting the vth ecological image into the vth converted image is: f(x v ,y v )=λ r RED(x v ,y v )+λ g GREEN(x v ,y v )+λ b BLUE(x v ,y v ), Among them, f(x v ,y v ) represents the vth transformed image at pixel (x v ,y v ) at the conversion value; RED(x v ,y v ) represents the vth ecological image at pixel (x v ,y v ) is the pixel value of the red channel at ; GREEN(x v ,y v ) represents the vth ecological image at pixel (x v ,y v ) is the pixel value of the green channel at ; BLUE(x v ,y v ) represents the vth ecological image at pixel (x v ,y v ) is the pixel value of the blue channel at ; Constraint conditions: l r 、l g 、l b ∈[0,1]; l r +λ g +λ b =1; x v =1, 2, 3, ..., X v ;X v Indicates the number of pixels in the x-axis direction of the vth ecological image; y v =1, 2, 3, ..., Y v ; Y v Indicates the number of pixels in the Y-axis direction of the vth ecological image.

5. The method for realizing comprehensive evaluation of ecological resources based on big data model according to claim 1 is characterized in that: In step S4, the method of evaluating the ecological environment degree of the screened large amount of ecological resource image data includes the following steps: S41. Let k = 1; S42, obtain the pixel values ​​of the three channels of the k-th image, which are RED(x k′ ,y k′ )、GREEN(x k′ ,y k′ )、BLUE(x k′ ,y k′ ); RED(x k′ ,y k′ ) indicates that the kth image is at pixel (x k′ ,y k′ ) is the pixel value of the red channel at ; GREEN(x k′ ,y k′ ) indicates that the kth image is at pixel (x k′ ,y k′ ) is the pixel value of the green channel at ; BLUE(x k′ ,y k′ ) indicates that the kth image is at pixel (x k′ ,y k′ ) is the pixel value of the blue channel at ; x k′ =1, 2, 3, ..., X k′ ;X k′ Indicates the number of pixels in the k-th image in the X-axis direction; y k′ =1, 2, 3, ..., Y k′ ; Y k′ Indicates the number of pixels in the Y-axis direction of the k-th image; S43, That is, if GREEN(x k′ ,y k′ )≥GREEN0&RED(x k′ ,y k′ )≤RED0&BLUE(x k′ ,y k′ )≤BLUE0, GREEN0 represents the preset green channel pixel value, RED0 represents the preset red channel pixel value, BLUE0 represents the preset blue channel pixel value, & represents the logical relationship and, if represents if; then W(x k′ ,y k′ )=1; otherwise W(x k′ ,y k′ )=0; W k =∑W(x k′ ,y k′ ) is to accumulate and sum the k-th image to obtain the k-th image judgment value; S44, judge W k The relationship between W0 and the If W k ≥W0,W k represents the judgment value of the kth image, W0 represents the preset judgment threshold, then the image is retained; the image is evaluated and the next step is executed; If W k <W0,W k represents the judgment value of the kth image, W0 represents the preset judgment threshold, then delete the image; proceed to the next step; S45. Judge the size relationship between k and K: If k < K, where K represents the quantity of the screened large amount of ecological resource image data and k represents the image serial number, then k = k + 1, and execute step S42; If k ≥ K, where K represents the quantity of the screened large amount of ecological resource image data and k represents the image serial number, then end.

6. A comprehensive evaluation system for ecological resources based on a big data model, characterized in that: It includes an ecological resource image data acquisition module, an ecological resource image data filtering module, an ecological resource image data screening module, and an ecological resource image data evaluation module; The data output end of the ecological resource image data acquisition module is connected to the data input end of the ecological resource image data filtering module, the data output end of the ecological resource image data filtering module is connected to the data input end of the ecological resource image data screening module, and the data output end of the ecological resource image data screening module is connected to the data input end of the ecological resource image data evaluation module; The ecological resource image data acquisition module is used to obtain a large amount of ecological resource image data captured by a remote sensing satellite; The ecological resource image data filtering module is used to filter the massive ecological resource image data in the ecological resource image data acquisition module to obtain the filtered massive ecological resource image data; The ecological resource image data screening module is used to screen the filtered massive ecological resource image data to obtain the screened massive ecological resource image data; The ecological resource image data evaluation module is used to evaluate the ecological environment degree of the screened massive ecological resource image data.

7. The ecological resource comprehensive evaluation system based on the big data model according to claim 6 is characterized in that: In the ecological resource image data screening module, screening the filtered massive ecological resource image data to obtain the screened massive ecological resource image data includes the following steps: S31, count the number of the filtered massive ecological resource image data in step S2, denoted as N; they are the 1st ecological image, the 2nd ecological image, the 3rd ecological image,..., the nth ecological image respectively; let the image serial number v = 1; S32, convert the vth ecological image into the vth converted image, and calculate the difference value of the vth converted image by using the vth converted image; S33, judge the size relationship between v and N: If v < N, where v represents the image serial number and N represents the number of the filtered massive ecological resource image data, then v = v + 1, and execute step S32; If v ≥ N, where v represents the image serial number and N represents the number of the filtered massive ecological resource image data, then execute the next step; S34, arrange all the difference values in descending order, and take the filtered massive ecological resource image data corresponding to the first q difference values as the screened massive ecological resource image data, where q is a positive integer less than N.

8. The ecological resource comprehensive evaluation system based on big data model according to claim 7 is characterized in that: In the ecological resource image data evaluation module, the method for evaluating the ecological environment degree of the screened massive ecological resource image data includes the following steps: S41, let k = 1; S42, obtain the pixel values ​​of the three channels of the k-th image, which are RED(x k′ ,y k′ )、GREEN(x k′ ,y k′ )、BLUE(x k′ ,y k′ ); RED(x k′ ,y k′ ) indicates that the kth image is at pixel (x k′ ,y k′ ) is the pixel value of the red channel at ; GREEN(x k′ ,y k′ ) indicates that the kth image is at pixel (x k′ ,y k′ ) is the pixel value of the green channel at ; BLUE(x k′ ,y k′ ) indicates that the kth image is at pixel (x k′ ,y k′ ) is the pixel value of the blue channel at ; x k′ =1, 2, 3, ..., X k′ ;X k′ Indicates the number of pixels in the k-th image in the X-axis direction; y k′ =1, 2, 3, ..., Y k′ ; Y k′ Indicates the number of pixels in the Y-axis direction of the k-th image; S43, That is, if GREEN(x k′ ,y k′ )≥GREEN0&RED(x k′ ,y k′ )≤RED0&BLUE(x k′ ,y k′ )≤BLUE0, GREEN0 represents the preset green channel pixel value, RED0 represents the preset red channel pixel value, BLUE0 represents the preset blue channel pixel value, & represents the logical relationship and, if represents if; then W(x k′ ,y k′ )=1; otherwise W(x k′ ,y k′ )=0; W k =∑W(x k′ ,y k′ ) is to accumulate and sum the k-th image to obtain the k-th image judgment value; S44, judge W k The relationship between W0 and the If W k ≥W0,W k represents the judgment value of the kth image, W0 represents the preset judgment threshold, then the image is retained; the image is evaluated and the next step is executed; If W k <W0,W k represents the judgment value of the kth image, W0 represents the preset judgment threshold, then delete the image; proceed to the next step; S45, judge the size relationship between k and K: If k < K, where K represents the number of the screened massive ecological resource image data and k represents the image serial number, then k = k + 1, and execute step S42; If k ≥ K, where K represents the number of the screened massive ecological resource image data and k represents the image serial number, then end.

9. A computer system, characterized in that: Including: A processor; A memory for storing processor-executable instructions; Wherein, the processor is configured to implement the ecological resource comprehensive evaluation method according to any one of claims 1 to 8 when executing the executable instructions.

10. A computer-readable storage medium, characterized in that: Including: A memory with a computer program stored thereon; A processor for executing the program in the memory to implement the ecological resource comprehensive evaluation method according to any one of claims 1 to 8.

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