Forestry remote sensing tree species identification system based on image identification

Abstract

The invention discloses a forestry remote sensing tree species identification system based on image identification, and belongs to the technical field of remote sensing identification. Comprising a region division unit, a data acquisition unit, a reference data acquisition unit, a network transmission unit, a data processing unit, a storage management unit and a display reminding unit, the region division unit is used for dividing a region needing forestry remote sensing tree species identification into a plurality of regions; and the data acquisition unit is used for acquiring various data required by the forestry remote sensing tree species identification system. When the analysis processing module carries out analysis processing, the analysis processing module can comprehensively analyze the number of each type of trees in each area, the number of each type of trees in each area in the last year, the number of types of trees in each area and the number of types of trees in each area in the last year to obtain a tree change index of each area. Therefore, the change condition of the trees in each area can be obtained according to the tree change index of each area.

Description

Technical Field

[0001] The present invention relates to the technical field of remote sensing identification, and in particular to a forestry remote sensing tree species identification system based on image recognition. Background Art

[0002] The identification and distribution of forest tree species are crucial components of forest resource surveys, providing valuable insights into forest resource management, biodiversity assessment, soil and water conservation, and forest carbon stock estimation. They are also crucial for further research on regional forest carbon storage, carbon sinks, and ecohydrological conservation. Traditional forest type identification methods are relatively backward, relying on extensive manual fieldwork. This is not only labor-intensive and time-consuming, but also leads to inaccurate monitoring results, errors, and timeliness issues. Furthermore, these methods consume significant human, material, and financial resources and often fail to meet anticipated requirements. Summary of the Invention

[0003] Purpose of the invention: The purpose of the present invention is to provide a forestry remote sensing tree species identification system based on image recognition; it can solve the problems of traditional forest type identification methods such as high workload, poor timeliness, inaccurate monitoring results, and errors.

[0004] Technical solution: To solve the above technical problems, according to one aspect of the present invention, more specifically, a forestry remote sensing tree species identification system based on image recognition includes: a region division unit, a data acquisition unit, a reference data acquisition unit, a network transmission unit, a data processing unit, a storage management unit, and a display reminder unit;

[0005] Regional division unit: used to divide the area where forestry remote sensing tree species identification is required into multiple areas;

[0006] Data acquisition unit: used to collect various data required by the forestry remote sensing tree species identification system;

[0007] Reference data acquisition unit: used to obtain various reference data required by the forestry remote sensing tree species identification system;

[0008] Network transmission unit: used for transmitting various data required for the forestry remote sensing tree species identification system collected by the data collection unit and various reference data required for the forestry remote sensing tree species identification system collected by the reference data acquisition unit to the data processing unit, transmitting the data collected by the data collection unit to the storage management unit, transmitting the data stored in the storage management unit to the data processing unit, and transmitting the report on the forestry remote sensing tree species identification area and the report on the forestry remote sensing tree species identification system generated by the data processing unit to the display reminder unit;

[0009] Data processing unit: used to receive various data required by the forestry remote sensing tree species identification system collected by the data collection unit, and the data stored in the reference data storage management unit required by the forestry remote sensing tree species identification system obtained by the reference data acquisition unit, and analyze and process the above data and generate a report on the forestry remote sensing tree species identification area and a report on the forestry remote sensing tree species identification system based on the results of the analysis and processing;

[0010] Storage management unit: used to store various data required by the forestry remote sensing tree species identification system collected by the data collection unit, and to manage the stored data;

[0011] Display reminder unit: used to receive the reports on forestry remote sensing tree species identification areas and reports on forestry remote sensing tree species identification systems generated by the data processing unit, and at the same time receive the reports on forestry remote sensing tree species identification areas and reports on forestry remote sensing tree species identification systems, and issue warning reminders when the received report results are abnormal.

[0012] Furthermore, the data collection unit includes: a tree species number collection module, a tree quantity collection module and a tree area collection module;

[0013] Tree species number collection module: used to collect the number of tree species in each area by identifying remote sensing images;

[0014] Tree quantity collection module: used to collect the number of each type of tree in each area by identifying remote sensing images;

[0015] Tree area collection module: used to collect the area occupied by each tree in each area by identifying remote sensing images.

[0016] Furthermore, the reference data acquisition unit includes: a data acquisition module and a data processing module;

[0017] Data acquisition module: used to acquire various reference data required by the forestry remote sensing tree species identification system;

[0018] Data processing module: used to process the various reference data required by the forestry remote sensing tree species identification system obtained by the data acquisition module to adapt to the use of forestry remote sensing tree species identification.

[0019] Furthermore, the data processing unit includes: a data receiving module, an analysis and processing module, and a report generating module;

[0020] Data receiving module: used for receiving various data required by the forestry remote sensing tree species identification system collected by the data collection unit and various data stored in the reference data storage management unit required by the forestry remote sensing tree species identification system collected by the reference data acquisition unit;

[0021] Analysis and processing module: used for analyzing and processing the data on forestry remote sensing tree species identification areas received by the data receiving unit;

[0022] Report generation module: used to generate reports on forestry remote sensing tree species identification areas and reports on forestry remote sensing tree species identification systems based on the analysis and processing results of the analysis and processing module.

[0023] Furthermore, the storage management unit includes: a data acquisition module, a data storage module and a data management module;

[0024] Data acquisition module: used to obtain various data required by the forestry remote sensing tree species identification system collected by the data acquisition unit;

[0025] Data storage module: used to store various data required by the forestry remote sensing tree species identification system collected by the data acquisition unit acquired by the data acquisition module;

[0026] Data management unit: used to manage the various data required by the forestry remote sensing tree species identification system collected by the data acquisition unit stored in the data storage module.

[0027] Furthermore, the display and reminder unit includes: a report receiving module, a report display module and a warning reminder module;

[0028] Report receiving module: used for receiving the report on the forestry remote sensing tree species identification area and the report on the forestry remote sensing tree species identification system generated by the data processing unit;

[0029] Report display module: used to display the reports on forestry remote sensing tree species identification areas and reports on forestry remote sensing tree species identification systems received by the report receiving module;

[0030] Warning reminder module: used to issue a warning reminder when the report result received by the report receiving module is abnormal.

[0031] Furthermore, when performing analysis and processing, the analysis and processing module can obtain a tree change index for each area by comprehensively analyzing the number of each type of tree in each area, the number of each type of tree in each area in the previous year, the number of tree species in each area, and the number of tree species in each area in the previous year:

[0032]

[0033] Therefore, the change of trees in each area can be obtained according to the tree change index of each area. CI>0 means that the number of trees in the area is growing, CI=0 means that the number of trees in the area is unchanged, and CI<0 means that the number of trees in the area is decreasing. Then, the warning module is used to warn and remind people to pay attention to the forestry situation in the area. At the same time, when CI>0, the larger the CI value, the faster the number of trees in the area grows, and when CI<0, the smaller the CI value, the faster the number of trees in the area decreases; where N i is the number of each type of tree in each area, SN i is the number of each type of tree in each area in the previous year, n1 is the number of tree species in each area, and n2 is the number of tree species in each area in the previous year.

[0034] Furthermore, when performing analysis and processing, the analysis and processing module can obtain a reference number of each type of tree in a certain area and the number of each type of tree identified in the corresponding area, obtain a reference area occupied by each type of tree in a certain area and the area occupied by each type of tree identified in the corresponding area, obtain the number of tree species in a certain area and the reference number of tree species identified in the corresponding area, and comprehensively analyze the above data to obtain a deviation index of the forestry remote sensing tree species identification system:

[0035]

[0036] Therefore, the performance of the forestry remote sensing tree species identification system can be obtained based on the deviation index of the forestry remote sensing tree species identification system. The larger the deviation index, the better the performance of the forestry remote sensing tree species identification system. Conversely, the smaller the deviation index, the better the performance of the forestry remote sensing tree species identification system. i and i N i The reference number of each tree type in a certain area and the number of each tree type identified in the corresponding area are obtained, ZS i With S i is the reference area occupied by each tree in a certain area and the area occupied by each tree identified in the corresponding area, m and n1 are the number of tree species obtained in a certain area and the reference number of tree species identified in the corresponding area.

[0037] Beneficial effect: When the analysis and processing module is performing analysis and processing, it can obtain the tree change index of each area by comprehensively analyzing the number of each type of trees in each area, the number of each type of trees in each area in the previous year, the number of tree species in each area, and the number of tree species in each area in the previous year, so as to obtain the change of trees in each area according to the tree change index of each area. At the same time, when performing analysis and processing, the analysis and processing module can obtain the reference number of each type of trees in a certain area and the number of each type of trees identified in the corresponding area, the reference area occupied by each type of trees in a certain area and the area occupied by each type of trees identified in the corresponding area, the number of tree species in a certain area and the reference number of tree species identified in the corresponding area, and obtain the deviation index of the forestry remote sensing tree species identification system by analyzing the above data, and obtain the performance of the forestry remote sensing tree species identification system according to the deviation index of the forestry remote sensing tree species identification system. The larger the deviation index, the better the performance of the forestry remote sensing tree species identification system. On the contrary, the smaller the deviation index, the better the performance of the forestry remote sensing tree species identification system. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1 It is a schematic diagram of the system principle. DETAILED DESCRIPTION

[0039] In order to make the technical solution of the present invention clearer, the present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0040] Example 1

[0041] The area where forestry remote sensing tree species identification is required is divided into multiple areas through the area division unit, and then the remote sensing images are identified through the tree species number acquisition module, tree quantity acquisition module and tree area acquisition module of the data acquisition unit. The number of tree species in each area and the remote sensing images are identified. The number of each tree in each area and the remote sensing images are identified. The area occupied by each tree in each area is collected. The data acquisition module of the reference data acquisition unit is used to acquire various reference data required for the forestry remote sensing tree species identification system, and the data processing module processes the various reference data required for the forestry remote sensing tree species identification system acquired by the data acquisition module to adapt to the use of forestry remote sensing tree species identification.

[0042] The data collected by the data acquisition unit is then transmitted to the storage management unit through the network transmission unit, and the various data required for the forestry remote sensing tree species identification system collected by the data acquisition unit and the various data stored in the reference data storage management unit required for the forestry remote sensing tree species identification system obtained by the reference data acquisition unit are transmitted to the analysis and processing unit for analysis and processing, and a report on the forestry remote sensing tree species identification area and a report on the forestry remote sensing tree species identification system are generated according to the analysis and processing results of the analysis and processing module through the report generation module.

[0043] When performing analysis and processing, the analysis and processing module can obtain the tree change index of each area by comprehensively analyzing the number of each type of tree in each area, the number of each type of tree in each area in the previous year, the number of tree species in each area, and the number of tree species in each area in the previous year:

[0044]

[0045] Therefore, the change of trees in each area can be obtained according to the tree change index of each area. CI>0 means that the number of trees in the area is growing, CI=0 means that the number of trees in the area is unchanged, and CI<0 means that the number of trees in the area is decreasing. Then, the warning module is used to warn and remind people to pay attention to the forestry situation in the area. At the same time, when CI>0, the larger the CI value, the faster the number of trees in the area grows, and when CI<0, the smaller the CI value, the faster the number of trees in the area decreases; where N i is the number of each type of tree in each area, SN i is the number of each type of tree in each area in the previous year, n1 is the number of tree species in each area, and n2 is the number of tree species in each area in the previous year.

[0046] When performing analysis and processing, the analysis and processing module can obtain the reference number of each tree type in a certain area and the number of each tree type identified in the corresponding area, the reference area occupied by each tree type in a certain area and the area occupied by each tree type identified in the corresponding area, the number of tree species in a certain area and the reference number of tree species identified in the corresponding area, and comprehensively analyze the above data to obtain the deviation index of the forestry remote sensing tree species identification system:

[0047]

[0048] Therefore, the performance of the forestry remote sensing tree species identification system can be obtained based on the deviation index of the forestry remote sensing tree species identification system. The larger the deviation index, the better the performance of the forestry remote sensing tree species identification system. Conversely, the smaller the deviation index, the better the performance of the forestry remote sensing tree species identification system. i andi N i The reference number of each tree type in a certain area and the number of each tree type identified in the corresponding area are obtained, ZS i With S i is the reference area occupied by each tree in a certain area and the area occupied by each tree identified in the corresponding area, m and n1 are the number of tree species obtained in a certain area and the reference number of tree species identified in the corresponding area.

[0049] Finally, the report receiving module of the display reminder unit receives the report on the forestry remote sensing tree species identification area and the report on the forestry remote sensing tree species identification system generated by the data processing unit, and the report display module displays the report on the forestry remote sensing tree species identification area and the report on the forestry remote sensing tree species identification system received by the report receiving module. At the same time, when the report result received by the report receiving module is abnormal, the warning reminder module will issue a warning reminder.

[0050] Example 2

[0051] The analysis and processing module can obtain the tree change index of each area by comprehensively analyzing the number of each type of trees in each area, the number of each type of trees in each area in the previous year, the number of tree species in each area and the number of tree species in each area in the previous year. n1=5,n2=5,then we can calculate At this time, CI>0, indicating that the number of trees in the area is growing.

[0052] Example 3

[0053] When the analysis and processing module performs analysis and processing to obtain the deviation index of the forestry remote sensing tree species identification system,

[0054] m=7,n1=7,then we can calculate At this time, the bias index BI of the forestry remote sensing tree species identification system can be used to judge the quality of remote sensing identification in this area. When the BI value reaches the expected threshold, the system needs to be checked to find the reasons for the high BI value.

[0055] The above-described embodiments merely illustrate several implementations of the present invention, and while their descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present invention. It should be noted that a person skilled in the art would be able to make numerous variations and improvements without departing from the spirit of the present invention, all of which fall within the scope of protection of the present invention. Therefore, the scope of protection of the present invention shall be determined by the appended claims.

Claims

1. A forestry remote sensing tree species identification system based on image recognition, characterized in that: include: Area division unit, data collection unit, reference data collection unit, network transmission unit, data processing unit, storage management unit and display reminder unit; Regional division unit: used to divide the area where forestry remote sensing tree species identification is required into multiple areas; Data acquisition unit: used to collect various data required by the forestry remote sensing tree species identification system; Reference data acquisition unit: used to obtain various reference data required by the forestry remote sensing tree species identification system; Network transmission unit: used for transmitting various data required for the forestry remote sensing tree species identification system collected by the data collection unit and various reference data required for the forestry remote sensing tree species identification system collected by the reference data acquisition unit to the data processing unit, transmitting the data collected by the data collection unit to the storage management unit, transmitting the data stored in the storage management unit to the data processing unit, and transmitting the report on the forestry remote sensing tree species identification area and the report on the forestry remote sensing tree species identification system generated by the data processing unit to the display reminder unit; Data processing unit: used to receive various data required by the forestry remote sensing tree species identification system collected by the data collection unit, and the data stored in the reference data storage management unit required by the forestry remote sensing tree species identification system obtained by the reference data acquisition unit, and analyze and process the above data and generate a report on the forestry remote sensing tree species identification area and a report on the forestry remote sensing tree species identification system based on the results of the analysis and processing; Storage management unit: used to store various data required by the forestry remote sensing tree species identification system collected by the data collection unit, and to manage the stored data; Display reminder unit: used to receive the reports on forestry remote sensing tree species identification areas and reports on forestry remote sensing tree species identification systems generated by the data processing unit, and at the same time receive the reports on forestry remote sensing tree species identification areas and reports on forestry remote sensing tree species identification systems, and issue warning reminders when the received report results are abnormal.

2. The forestry remote sensing tree species identification system based on image recognition according to claim 1, characterized in that: The data collection unit includes: a tree species number collection module, a tree quantity collection module and a tree area collection module; Tree species number collection module: used to collect the number of tree species in each area by identifying remote sensing images; Tree quantity collection module: used to collect the number of each type of tree in each area by identifying remote sensing images; Tree area collection module: used to collect the area occupied by each tree in each area by identifying remote sensing images.

3. The forestry remote sensing tree species identification system based on image recognition according to claim 2, characterized in that: The reference data acquisition unit includes: a data acquisition module and a data processing module; Data acquisition module: used to acquire various reference data required by the forestry remote sensing tree species identification system; Data processing module: used to process the various reference data required by the forestry remote sensing tree species identification system obtained by the data acquisition module to adapt to the use of forestry remote sensing tree species identification.

4. The forestry remote sensing tree species identification system based on image recognition according to claim 3, characterized in that: The data processing unit includes: a data receiving module, an analysis and processing module and a report generating module; Data receiving module: used for receiving various data required by the forestry remote sensing tree species identification system collected by the data collection unit and various data stored in the reference data storage management unit required by the forestry remote sensing tree species identification system collected by the reference data acquisition unit; Analysis and processing module: used for analyzing and processing the data on forestry remote sensing tree species identification areas received by the data receiving unit; Report generation module: used to generate reports on forestry remote sensing tree species identification areas and reports on forestry remote sensing tree species identification systems based on the analysis and processing results of the analysis and processing module.

5. The forestry remote sensing tree species identification system based on image recognition according to claim 4, characterized in that: The storage management unit includes: a data acquisition module, a data storage module and a data management module; Data acquisition module: used to obtain various data required by the forestry remote sensing tree species identification system collected by the data acquisition unit; Data storage module: used to store various data required by the forestry remote sensing tree species identification system collected by the data acquisition unit acquired by the data acquisition module; Data management unit: used to manage various data required by the forestry remote sensing tree species identification system collected by the data acquisition unit stored in the data storage module.

6. The forestry remote sensing tree species identification system based on image recognition according to claim 5, characterized in that: The display and reminder unit includes: a report receiving module, a report display module and a warning reminder module; Report receiving module: used for receiving the report on the forestry remote sensing tree species identification area and the report on the forestry remote sensing tree species identification system generated by the data processing unit; Report display module: used to display the reports on forestry remote sensing tree species identification areas and reports on forestry remote sensing tree species identification systems received by the report receiving module; Warning reminder module: used to issue a warning reminder when the report result received by the report receiving module is abnormal.

7. The forestry remote sensing tree species identification system based on image recognition according to claim 6, characterized in that: When performing analysis and processing, the analysis and processing module can obtain the tree change index of each area by comprehensively analyzing the number of each type of trees in each area, the number of each type of trees in each area in the previous year, the number of tree species in each area, and the number of tree species in each area in the previous year: Therefore, the change of trees in each area can be obtained according to the tree change index of each area. CI>0 means that the number of trees in the area is growing, CI=0 means that the number of trees in the area is unchanged, and CI<0 means that the number of trees in the area is decreasing. Then, the warning module is used to warn and remind people to pay attention to the forestry situation in the area. At the same time, when CI>0, the larger the CI value, the faster the number of trees in the area grows, and when CI<0, the smaller the CI value, the faster the number of trees in the area decreases; where N i is the number of each type of tree in each area, SN i is the number of each type of tree in each area in the previous year, n1 is the number of tree species in each area, and n2 is the number of tree species in each area in the previous year.

8. The forestry remote sensing tree species identification system based on image recognition according to claim 6, characterized in that: When performing analysis and processing, the analysis and processing module can obtain the reference number of each type of tree in a certain area and the number of each type of tree identified in the corresponding area, the reference area occupied by each type of tree in a certain area and the area occupied by each type of tree identified in the corresponding area, the number of tree species in a certain area and the reference number of tree species identified in the corresponding area, and comprehensively analyze the above data to obtain the deviation index of the forestry remote sensing tree species identification system: Therefore, the performance of the forestry remote sensing tree species identification system can be obtained based on the deviation index of the forestry remote sensing tree species identification system. The larger the deviation index, the better the performance of the forestry remote sensing tree species identification system. Conversely, the smaller the deviation index, the better the performance of the forestry remote sensing tree species identification system. i and i N i The reference number of each tree type in a certain area and the number of each tree type identified in the corresponding area are obtained, ZS i With S i The reference area occupied by each tree in a certain area and the area occupied by each tree identified in the corresponding area are obtained. m and n1 are the number of tree species obtained in a certain area and the reference number of tree species identified in the corresponding area.

Images