A natural resource survey results analysis method and system based on image recognition

Abstract

The present invention discloses a method and system for analyzing natural resource survey results based on image recognition, which relates to the field of natural resource survey and monitoring technology, including obtaining historical remote sensing information and geographic information of a target area, and determining at least one divided plot of the target area; analyzing each divided plot based on the historical remote sensing information of the target area, and respectively determining the gradient characteristic information of each divided plot; respectively collecting remote sensing data information of the target area in different time series segments, and obtaining the real-time gradient characteristics of each divided plot. The present invention uses remote sensing technology to divide the target area into plot outlines in advance, and then collects the historical remote sensing characteristic distribution of each divided plot in different periods, providing an effective reference for realizing the real-time remote sensing characteristic distribution performance of crops in each divided plot, so as to effectively judge whether there is abandonment. That is, the purpose of accurately monitoring the abandonment of agricultural arable land is effectively achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of natural resource survey and monitoring, and in particular to a natural resource survey results analysis method and system based on image recognition. Background Art

[0002] With the acceleration of urbanization, agricultural land, a natural resource, is becoming abandoned in some areas. This not only impacts food security but also leads to a waste of land resources. Accurately monitoring the distribution, area, and changes in abandoned land is crucial for the rational utilization of land resources and the formulation and evaluation of agricultural subsidy policies. Currently, monitoring of abandoned agricultural land is typically done through field visits and sampling, which is difficult to adapt to large-scale monitoring needs and relies on large survey teams. The acquisition of information is costly, time-sensitive, and subject to subjective influence.

[0003] The goal is to monitor agricultural land using remote sensing technology. Various satellite sensors and ground sensor networks are being formed to enable integrated space-ground stereoscopic observation, real-time perception, and spatiotemporal agricultural remote sensing monitoring. That is, high-resolution satellites are used to collect remote sensing images of cultivated land, and then the type of cultivated land is determined based on the different remote sensing image information. However, when processing the image data, the accuracy of determining whether the agricultural land is wasteland may be affected by the different types of crops planted in different cultivated lands. Summary of the Invention

[0004] The purpose of the present invention is to realize accurate monitoring of the phenomenon of abandoned agricultural land, and to propose a natural resource survey results analysis method and system based on image recognition.

[0005] In order to achieve the above object, the present invention adopts the following technical solutions:

[0006] In a first aspect, the present invention provides a natural resource survey results analysis method based on image recognition, comprising:

[0007] Acquire historical remote sensing information and geographic information of the target area, and determine at least one subdivision of the target area;

[0008] According to the historical remote sensing information of the target area, each divided plot is analyzed to determine the gradient characteristic information of each divided plot;

[0009] Collect remote sensing data information of target areas in different time segments in real time, and obtain real-time gradient characteristics of each divided area;

[0010] According to the gradient characteristic information of each divided land parcel, the real-time gradient characteristic of each divided land parcel is analyzed to determine whether there is a divided land parcel of wasteland in the target area.

[0011] In a feasible solution, the method of determining the gradient feature information of each divided land parcel includes:

[0012] According to the historical remote sensing information and geographic information of the target area, the contour information of the current divided land and the distribution of historical remote sensing characteristics are obtained;

[0013] According to the contour information of the current divided plot, two unit comparison areas are determined in the current divided plot;

[0014] According to the historical remote sensing characteristic distribution of the target area, the historical remote sensing characteristic distribution information of each unit comparison area is determined respectively;

[0015] According to the historical remote sensing feature distribution information of each unit comparison area, the features of the two unit comparison areas in the current divided plot are compared to determine the difference interval information of the current divided plot;

[0016] The difference interval information of the current divided land parcel in different time segments is obtained to determine the gradual change feature information of the current divided land parcel.

[0017] In a feasible solution, the method for obtaining the real-time gradient characteristics of each divided land parcel includes:

[0018] Obtain real-time remote sensing feature distribution information of each unit comparison area in each divided plot;

[0019] According to the real-time remote sensing feature distribution information of each unit comparison area in each divided plot, the difference interval information of the unit comparison area in each divided plot is obtained;

[0020] According to the difference interval information of the unit comparison area in each divided plot, the real-time gradient characteristics of each divided plot are determined respectively.

[0021] In a feasible solution, the method for obtaining the difference interval information of the unit comparison area in the divided plot includes:

[0022] Assume that there is a first unit comparison area in the divided plot Comparison area with Unit 2 , then the remote sensing feature data C of any unit comparison area in the divided plot is:

[0023] Formula 1;

[0024] Formula 2;

[0025] In Equation 1 and Equation 2, is the gray level of the first pixel in the current unit comparison area, is the gray level of the second pixel in the current unit comparison area; is the number of gray levels existing in the current unit contrast area; Grayscale combination The number of occurrences, is the total number of occurrences of all gray-level combinations; are adjacent pixels, for and The relative direction angle between them;

[0026] At this time, according to formula 1 and formula 2, we can know:

[0027] Formula 3;

[0028] In formula 3, is the normalized difference data ratio between the two unit comparison areas in the divided plot, Comparison area for the first unit Remote sensing feature data, For the second unit comparison area Remote sensing feature data, For the comparison area in the first unit The remote sensing feature data in area b is compared with the first unit and takes the maximum value.

[0029] In a feasible solution, the method for determining whether there is wasteland in the target area includes:

[0030] Determine the time series characteristic change information of each divided land parcel respectively according to the gradual change characteristic information of each divided land parcel and the real-time gradual change characteristic of each divided land parcel;

[0031] According to the historical remote sensing information of the target area and the real-time gradient characteristics of each divided land parcel, the trend change of each divided land parcel is determined respectively;

[0032] Based on the historical remote sensing information of the target area and the trend change of each divided land parcel, set the abandonment warning information;

[0033] Based on the abandonment warning information, the abandonment judgment is made on the time series characteristic change information of each divided plot, and the wasteland probability of each divided plot is determined separately.

[0034] In one feasible solution, the method for determining the trend change of each divided land parcel includes:

[0035] set up The normalized difference data ratio of two unit comparison areas in a certain divided plot within the time series is , then the trend transformation value for:

[0036] Formula 4.

[0037] In a feasible solution, the method for setting the early warning information of abandoned land includes:

[0038] Formula 5;

[0039] In formula 5, is the real-time difference ratio in a certain divided plot, is the mean value of the historical difference ratio in a certain divided plot, is the difference ratio threshold, The actual value of the trend transformation in a certain time series segment of a certain divided plot, The threshold for the trend to fall within a parcel.

[0040] In a second aspect, the present invention provides a natural resource survey results analysis system based on image recognition, which adopts any one of the natural resource survey results analysis methods based on image recognition described in the first aspect, and the analysis system further includes:

[0041] A data processing module, wherein the data processing module is used to perform data preprocessing on the remote sensing information of the target area;

[0042] A data integration module, wherein the data integration module is used to integrate the pre-processed data;

[0043] A data analysis module is used to perform land abandonment analysis on the integrated data.

[0044] The beneficial effects of the present invention are:

[0045] This method uses remote sensing technology to pre-delineate the target area. It then aggregates the historical remote sensing characteristic distribution of each divided plot over different time periods. This provides an effective reference for the real-time remote sensing characteristic distribution of crops in each divided plot, effectively determining whether there is abandonment. This effectively achieves the goal of accurately monitoring the phenomenon of abandoned agricultural land. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Figure 1 A schematic diagram of the overall process of a natural resource survey results analysis method based on image recognition provided in an embodiment of the present invention;

[0047] Figure 2 A schematic diagram of a land parcel division model structure of a natural resource survey results analysis method based on image recognition provided in an embodiment of the present invention;

[0048] Figure 3 This is a schematic diagram of unit comparison areas for dividing plots in a natural resource survey results analysis method based on image recognition provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0049] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0050] It should be noted that all directional indications (such as up, down, left, right, front, back, etc.) in the embodiments of the present invention are only used to explain the relative position relationship, movement status, etc. between the various components under a certain specific posture (as shown in the accompanying drawings). If the specific posture changes, the directional indication will also change accordingly.

[0051] In the present invention, unless otherwise specified or limited, the terms "connection" and "fixation" should be understood in a broad sense. For example, "fixation" can mean fixed connection, detachable connection, or integration; mechanical connection or electrical connection; direct connection or indirect connection through an intermediate medium; internal communication between two elements or interaction between two elements, unless otherwise specified. Those skilled in the art will be able to understand the specific meanings of the above terms in the present invention based on specific circumstances.

[0052] In addition, if there are descriptions involving "first", "second", etc. in the embodiments of the present invention, the descriptions of "first", "second", etc. are only for descriptive purposes and cannot be understood as indicating or suggesting their relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one of such features. In addition, the meaning of "and / or" appearing throughout the text includes three parallel schemes. Taking "A and / or B" as an example, it includes scheme A, or scheme B, or a scheme in which A and B are satisfied at the same time. In addition, the technical solutions between the various embodiments can be combined with each other, but it must be based on the ability of ordinary technicians in this field to implement. When the combination of technical solutions is mutually contradictory or cannot be implemented, it should be deemed that such a combination of technical solutions does not exist and is not within the scope of protection required by the present invention.

[0053] Reference Figures 1 to 3In this embodiment, the present invention provides a natural resource survey results analysis method based on image recognition to accurately monitor the phenomenon of abandoned agricultural land. The analysis method pre-divides the land into plots, then analyzes and compares the real-time remote sensing conditions and historical remote sensing conditions of each divided plot, and then determines whether each divided plot is abandoned. That is, the analysis method uses remote sensing technology to pre-divide the plot outlines of the target area, and then collects the historical remote sensing feature distribution of each divided plot at different time periods, providing an effective reference for the real-time remote sensing feature distribution of crops in each divided plot, so as to effectively determine whether the phenomenon of abandonment exists. That is, the purpose of accurately monitoring the phenomenon of abandoned agricultural land is effectively achieved.

[0054] Reference Figure 1 、 Figure 2 and Figure 3 Specifically, in this embodiment, the present invention provides a natural resource survey results analysis method based on image recognition in a first aspect, comprising:

[0055] The historical remote sensing information and geographic information of the target area can be obtained in advance, and then the target area can be divided into plots to obtain at least one divided plot in the target area. It should be noted that in order to facilitate intuitive and clear observation and analysis of the regional conditions of the target area, the regional outline of each divided plot can be determined in advance based on the historical remote sensing information and geographic information of the target area through modeling software, so as to facilitate subsequent accurate monitoring and management of the abandonment of each divided plot. Figure 2 and Figure 3 As shown, the actual situation of the target area can be divided into a first divided plot 1, a second divided plot 2, a third divided plot 3, a fourth divided plot 4, a fifth divided plot 5, a sixth divided plot 6, and a seventh divided plot 7. In addition, when acquiring remote sensing information of the target area, it is necessary to pre-process the acquired remote sensing image and correct and enhance the remote sensing image. That is, after acquiring the remote sensing data, it is necessary to first perform radiation correction and geometric correction on the remote sensing data to reduce interference from factors such as the atmosphere and the sensor. By adopting image enhancement techniques such as histogram equalization and filtering, the internal features and edge information of the plot can be highlighted, and the image quality can be improved to make the image clearer and easier to use.

[0056] After preprocessing the target area's remote sensing information, historical remote sensing data can be obtained for each subdivided plot based on the number of plots within the target area. Each subdivided plot is then analyzed based on this historical remote sensing information to determine its gradient characteristic information (e.g., the historical distribution of remote sensing characteristics within different plots, or the historical distribution of remote sensing characteristics across different crop regions within the same plot). This means that the crops cultivated within each subdivided plot and their remote sensing performance can be determined based on historical remote sensing data. This involves extracting the target area's historical remote sensing characteristics using its historical data. When identifying and judging the abandonment of target land, it is necessary to collect remote sensing data information for the target land in different time series segments in real time. After performing the aforementioned data graphics preprocessing on the remote sensing data, the real-time gradient characteristics of each divided land parcel (such as the actual distribution of remote sensing characteristics in different land parcels, and the actual distribution of remote sensing characteristics of different crop areas in the same land parcel) are obtained. Then, it is only necessary to analyze the real-time gradient characteristics of each divided land parcel based on the gradient characteristic information of each divided land parcel to determine whether there are any wasteland divided land parcels in the target area. In other words, the real-time remote sensing characteristic distribution of each divided land parcel in different time periods can be compared with the previous remote sensing characteristic distribution of each divided land parcel in the same period to effectively determine whether there is abandonment. This effectively achieves the purpose of accurately monitoring the abandonment of agricultural arable land.

[0057] Reference Figure 2 and Figure 3In this embodiment, in order to facilitate understanding of how to determine the gradient feature information of each divided plot based on the past historical remote sensing information of the target area, the following explanation is given here. Specifically, the method of separately determining the gradient feature information of each divided plot includes: the contour information and historical remote sensing feature distribution of the current divided plot can be obtained based on the historical remote sensing information and geographic information of the target area; here, in order to facilitate the refined extraction of remote sensing features in the same plot, two unit comparison areas can be determined in the current divided plot based on the contour information of the current divided plot, that is, the distribution situation in the remote sensing image data (such as gray value distribution contour, plot area distribution contour, etc.) can be divided into unit contours in the current divided plot, so as to realize the remote sensing feature extraction of different crops planted in the same plot, and also reduce the impact of partial abandonment of the current plot on the judgment of the final abandonment situation. Then, based on the historical remote sensing feature distribution of the target area, the historical remote sensing feature distribution information of each unit comparison area can be determined respectively; then, based on the historical remote sensing feature distribution information of each unit comparison area, the features of the two unit comparison areas in the current divided plot can be compared to determine the difference interval information of the current divided plot. In this embodiment, in order to reduce the impact of misjudgment of the difference interval information caused by special periods, the difference interval information of the current divided plot in multiple different time segments can be obtained, and then the gradual feature information of the current divided plot can be determined. Similarly, it can be seen that, accordingly, the method for obtaining the real-time gradual feature of each divided plot includes:

[0058] The real-time remote sensing feature distribution information of each unit comparison area in each divided plot is obtained respectively; then, based on the real-time remote sensing feature distribution information of each unit comparison area in each divided plot, the difference interval information of the unit comparison area in each divided plot is obtained; and then, based on the difference interval information of the unit comparison area in each divided plot, the real-time gradient feature of each divided plot is determined respectively.

[0059] In this embodiment, in order to facilitate understanding of how to extract and determine the difference interval information of different unit comparison areas in the divided plot, the following description is provided. Specifically, the method for obtaining the difference interval information of the unit comparison areas in the divided plot includes:

[0060] Suppose there is a first unit comparison area in a certain divided plot Comparison area with Unit 2 , then the remote sensing feature data C of any unit comparison area in the divided plot is:

[0061] Formula 1;

[0062] Formula 2;

[0063] In Equation 1 and Equation 2, is the gray level of the first pixel in the current unit comparison area, is the gray level of the second pixel in the current unit comparison area; is the number of gray levels existing in the current unit contrast area; Grayscale combination The number of occurrences, is the total number of occurrences of all gray-level combinations; are adjacent pixels, for and The relative directions between

[0064] At this time, according to formula 1 and formula 2, we can know:

[0065] Formula 3;

[0066] In formula 3, is the normalized difference data ratio between the two unit comparison areas in the divided plot, For the first unit comparison area Remote sensing feature data, For the second unit comparison area Remote sensing feature data, For the comparison area in the first unit The maximum value of the remote sensing feature data in the first unit comparison area b is taken. That is, in this embodiment, by pre-extracting the remote sensing image features in the first unit comparison area and the second unit comparison area in the divided land parcel, and then using the remote sensing image features in the first unit comparison area and the second unit comparison area, the real-time remote sensing feature distribution information and the historical remote sensing feature distribution information of the divided land parcel can be determined respectively, and then the remote sensing feature distribution of each divided land parcel can be obtained.

[0067] In this embodiment, in order to facilitate understanding of how to determine the possibility of abandonment of each divided plot in the target area based on the real-time remote sensing feature distribution information and historical remote sensing feature distribution information of the divided plots, the following explanation is given here. Specifically, the method for determining whether there is wasteland in the target area includes: by collecting the real-time remote sensing feature distribution information and historical remote sensing feature distribution information of the divided plots in multiple different time periods, the gradual feature information of each divided plot and the real-time gradual feature of each divided plot can be determined, and then the time series feature change information of each divided plot can be determined according to the gradual feature information of each divided plot and the real-time gradual feature of each divided plot. At the same time, the trend change of each divided plot can be determined based on the historical remote sensing information of the target area and the real-time gradual change characteristics of each divided plot. That is, the remote sensing change trend in the divided plot can be determined based on the gradual change characteristic information of each divided plot and the real-time gradual change characteristics of each divided plot (such as a decrease due to a gradual decrease in planting density or abandonment, an increase due to a gradual increase in planting density or the replacement of crops with different remote sensing characteristics, etc.), so as to more accurately determine the trend change of the divided plot, and then determine whether the divided plot is partially or completely abandoned. Here, in order to facilitate a more intelligent judgment of the abandonment possibility of each divided plot in the target area, abandonment warning information can also be set based on the historical remote sensing information of the target area and the trend change situation of each divided plot; then, based on the abandonment warning information, the time series characteristic change information of each divided plot is used to make an abandonment judgment, and the probability of wasteland of each divided plot is determined. It should be noted that the historical remote sensing characteristic data of the target land may include remote sensing characteristic data of different seasons under normal cultivation. Of course, it can also include remote sensing characteristic data under the condition of abandonment. Different solutions can be selected according to actual conditions.

[0068] Specifically, the method for determining the trend change of each divided land parcel includes:

[0069] Can be set The normalized difference data ratio of two unit comparison areas in a certain divided plot within the time series is , then the trend transformation value for:

[0070] Formula 4.

[0071] In this embodiment, to facilitate understanding of how to pre-set the abandonment warning information, the following description is provided. The method for setting the abandonment warning information includes:

[0072] Formula 5;

[0073] In formula 5, is the real-time difference ratio in a certain divided plot, is the mean value of the historical difference ratio in a certain divided plot, is the difference ratio threshold, The actual value of the trend transformation in a certain time series segment of a certain divided plot, is the trend-down threshold in a certain partitioned plot. It should be noted that the trend-down threshold It can often be a negative value, indicating that the downward trend in the target area is irreversible. In this embodiment, a threshold comparison is performed between the real-time difference ratio of the divided plots and the average historical difference ratio of the divided plots over the same period. This also takes into account the overall trend changes in the divided plots, reducing the impact of partial abandonment in special circumstances and eliminating short-term interference such as climate.

[0074] In addition, in actual use, abandonment judgment can be made only when the trend change of remote sensing characteristics in the divided plots is in a long-term downward trend, thereby reducing the misjudgment rate of abandonment of the target area.

[0075] In the second aspect, the present invention provides a natural resource survey results analysis system based on image recognition, which adopts a natural resource survey results analysis method based on image recognition described in any one of the first aspects. The analysis system also includes: a data processing module, a data integration module and a data analysis module. The data processing module is used to preprocess the remote sensing information of the target area; the data integration module is used to integrate the preprocessed data; and the data analysis module is used to perform land abandonment analysis on the integrated data.

[0076] In some embodiments, the analysis system can communicate using any currently known or later developed network protocol, such as HTTP (Hypertext Transfer Protocol), and can interconnect with any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include a local area network ("LAN"), a wide area network ("WAN"), an internet (e.g., the Internet), and a peer-to-peer network (e.g., an ad hoc peer-to-peer network), as well as any currently known or later developed network.

[0077] The functions described above herein may be performed, at least in part, by one or more hardware logic components. For example, and without limitation, exemplary types of hardware logic components that may be used include: field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), complex programmable logic devices (CPLDs), and the like.

[0078] In a third aspect, the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein, when executed by a processor, the program implements a natural resource survey results analysis method based on image recognition as described in any one of the first aspects. The computer-readable medium in this embodiment may contain computer program code for performing the operations of some embodiments of the present disclosure, written in one or more programming languages, or a combination thereof. These programming languages ​​include object-oriented programming languages ​​such as Java, Smalltalk, and C++, as well as conventional procedural programming languages ​​such as C or similar programming languages. The program code may be executed entirely on a user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0079] The flowcharts and block diagrams in the accompanying drawings illustrate the possible implementation architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each box in the flowchart or block diagram can represent a module, program segment, or a part of code, and the module, program segment, or a part of code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order than that marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flowchart, and the combination of the boxes in the block diagram and / or flowchart, can be implemented with a dedicated hardware-based system that performs the specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0080] In particular, according to some embodiments of the present disclosure, the processes described above with reference to the flowcharts may be implemented as computer software programs. For example, some embodiments of the present disclosure include a computer program product comprising a computer program carried on a computer-readable medium, the computer program including program code for executing the methods shown in the flowcharts.

[0081] The fourth aspect of the present invention provides an electronic device, comprising: one or more processors; a storage device having one or more programs stored thereon; when the one or more programs are executed by the one or more processors, the one or more processors implement a natural resource survey results analysis method based on image recognition as described in the first aspect. The computer-readable medium may be included in the electronic device; or it may exist independently, that is, not assembled into the electronic device. The computer-readable medium carries one or more programs, and when the one or more programs are executed by the electronic device, the electronic device can implement a natural resource survey results analysis method based on image recognition as described in the first aspect.

[0082] A fifth aspect of the present invention provides a computer program product, comprising a computer program, which, when executed by a processor, implements a natural resource survey results analysis method based on image recognition as described in the first aspect.

[0083] The above descriptions are merely some preferred embodiments of the present disclosure and illustrate the underlying technical principles. Those skilled in the art should understand that the scope of the invention encompassed by the embodiments of the present disclosure is not limited to technical solutions formed by specific combinations of the aforementioned technical features. It also encompasses other technical solutions formed by any combination of the aforementioned technical features or their equivalents, without departing from the aforementioned inventive concept. For example, a technical solution formed by replacing the aforementioned features with (but not limited to) technical features with similar functions disclosed in the embodiments of the present disclosure.

Claims

1. A natural resource survey results analysis method based on image recognition, characterized in that: include: Acquire historical remote sensing information and geographic information of the target area, and determine at least one subdivision of the target area; According to the historical remote sensing information of the target area, each divided plot is analyzed to determine the gradient characteristic information of each divided plot; Collect remote sensing data information of target areas in different time segments in real time, and obtain real-time gradient characteristics of each divided area; According to the gradient characteristic information of each divided land parcel, the real-time gradient characteristics of each divided land parcel are analyzed to determine whether there is a divided land parcel of wasteland in the target area; The method of determining the gradient feature information of each divided land parcel includes: According to the historical remote sensing information and geographic information of the target area, the contour information of the current divided land and the distribution of historical remote sensing characteristics are obtained; According to the contour information of the current divided plot, two unit comparison areas are determined in the current divided plot; According to the historical remote sensing characteristic distribution of the target area, the historical remote sensing characteristic distribution information of each unit comparison area is determined respectively; According to the historical remote sensing feature distribution information of each unit comparison area, the features of the two unit comparison areas in the current divided plot are compared to determine the difference interval information of the current divided plot; The difference interval information of the current divided land parcel in different time segments is obtained to determine the gradual change feature information of the current divided land parcel.

2. The method for analyzing natural resource survey results based on image recognition according to claim 1, characterized in that: The method for obtaining the real-time gradient characteristics of each divided land parcel includes: Obtain real-time remote sensing feature distribution information of each unit comparison area in each divided plot; According to the real-time remote sensing feature distribution information of each unit comparison area in each divided plot, the difference interval information of the unit comparison area in each divided plot is obtained; According to the difference interval information of the unit comparison area in each divided plot, the real-time gradient characteristics of each divided plot are determined respectively.

3. The method for analyzing natural resource survey results based on image recognition according to claim 2, characterized in that: Methods for obtaining difference interval information of unit comparison areas in a divided plot include: Assume that there is a first unit comparison area in the divided plot Comparison area with Unit 2 , then the remote sensing feature data C of any unit comparison area in the divided plot is: Formula 1; Formula 2; In Equation 1 and Equation 2, is the gray level of the first pixel in the current unit comparison area, is the gray level of the second pixel in the current unit comparison area; is the number of gray levels existing in the current unit contrast area; Grayscale combination The number of occurrences, is the total number of occurrences of all gray-level combinations; are adjacent pixels, for and The relative direction angle between them; At this time, according to formula 1 and formula 2, we can know: Formula 3; In formula 3, is the normalized difference data ratio between the two unit comparison areas in the divided plot, For the first unit comparison area Remote sensing feature data, For the second unit comparison area Remote sensing feature data, For the comparison area in the first unit The remote sensing feature data in area b is compared with the first unit and takes the maximum value.

4. The method for analyzing natural resource survey results based on image recognition according to claim 3, characterized in that: The method for determining whether there is wasteland in the target area includes: Determine the time series characteristic change information of each divided land parcel respectively according to the gradual change characteristic information of each divided land parcel and the real-time gradual change characteristic of each divided land parcel; According to the historical remote sensing information of the target area and the real-time gradient characteristics of each divided land parcel, the trend change of each divided land parcel is determined respectively; Based on the historical remote sensing information of the target area and the trend change of each divided land parcel, set the abandonment warning information; Based on the abandonment warning information, the abandonment judgment is made on the time series characteristic change information of each divided plot, and the wasteland probability of each divided plot is determined separately.

5. The method for analyzing natural resource survey results based on image recognition according to claim 4, characterized in that: Methods for determining the trend change of each divided plot include: set up The normalized difference data ratio of two unit comparison areas in a certain divided plot within the time series is , then the trend transformation value for: Formula 4.

6. The method for analyzing natural resource survey results based on image recognition according to claim 5, characterized in that: The method for setting the early warning information of wasteland abandonment includes: Formula 5; In formula 5, is the real-time difference ratio in a certain divided plot, is the mean value of the historical difference ratio in a certain divided plot, is the difference ratio threshold, The actual value of the trend transformation in a certain time series segment of a certain divided plot, The threshold for the trend to fall within a parcel.

7. A natural resource survey results analysis system based on image recognition, characterized in that: A natural resource survey results analysis method based on image recognition according to any one of claims 1 to 6 is adopted, wherein the analysis system further comprises: A data processing module, wherein the data processing module is used to perform data preprocessing on the remote sensing information of the target area; A data integration module, wherein the data integration module is used to integrate the pre-processed data; A data analysis module is used to perform land abandonment analysis on the integrated data.

Images