CN114359703A - Method and system for quickly identifying shrub distribution range of shrub grassland - Google Patents
Method and system for quickly identifying shrub distribution range of shrub grassland Download PDFInfo
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- CN114359703A CN114359703A CN202111443397.8A CN202111443397A CN114359703A CN 114359703 A CN114359703 A CN 114359703A CN 202111443397 A CN202111443397 A CN 202111443397A CN 114359703 A CN114359703 A CN 114359703A
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Abstract
The invention discloses a method and a system for rapidly identifying the shrub and shrub distribution range of shrub grassland, which are used for acquiring a first image of the shrub grassland in a first set time range of a designated area; from the first grassland shrunken area image, regarding an area with a pixel value larger than a set threshold as a grassland area without shrunken; acquiring a second grassland shrunken area image within a second set time range of the designated area; and carrying out image alignment on the second grassland shrunken area image and the first grassland shrunken area image, removing the grassland areas without shrubbering from the aligned second grassland shrubbered area image, and marking the areas with the pixel point values larger than the set threshold value in the remaining areas to obtain the distribution range of the shrubbering.
Description
Technical Field
The invention relates to the technical field of image processing, in particular to a method and a system for quickly identifying the shrub distribution range of shrubbery grassland.
Background
The statements in this section merely provide background information related to the present disclosure and may not constitute prior art.
The ecological system of the grassland has the situation of increasing shrub density, coverage and biomass, and is developed into the shrub grassland. The occurrence of the shrunken formation threatens the sustainable development of the ecosystem and the livestock industry, and once the shrunken formation begins to appear, the shrunken formation is difficult to reverse, and is an ecological problem commonly faced in many arid and semi-arid regions.
The inventor finds that in vegetation index images such as NDVI, EVI and the like obtained from multi-spectrum remote sensing images, grassland and shrubs in shrunken grassland cannot be visually distinguished directly through vegetation index values or images.
Disclosure of Invention
In order to solve the defects of the prior art, the invention provides a method and a system for quickly identifying the shrub distribution range of shrubbery grassland; the method can quickly identify the shrub distribution range, monitor the shrub expansion area, reasonably utilize and protect grassland shrubbery areas, and has certain scientific value and production practice value.
In a first aspect, the invention provides a method for rapidly identifying the shrub distribution range of shrubbery grassland;
a method for rapidly identifying the shrub distribution range of shrubbery grassland comprises the following steps:
acquiring a first grassland shrunken area image in a first set time range of a designated area;
from the first grassland shrunken area image, regarding an area with a pixel value larger than a set threshold as a grassland area without shrunken;
acquiring a second grassland shrunken area image within a second set time range of the designated area;
and carrying out image alignment on the second grassland shrunken area image and the first grassland shrunken area image, removing the grassland areas without shrubbering from the aligned second grassland shrubbered area image, and marking the areas with the pixel point values larger than the set threshold value in the remaining areas to obtain the distribution range of the shrubbering.
In a second aspect, the present invention provides a system for rapidly identifying shrub distribution range of shrubbery grassland;
a system for rapidly identifying shrunken grassland shrub distribution ranges, comprising:
a first acquisition module configured to: acquiring a first grassland shrunken area image in a first set time range of a designated area;
a screening module configured to: from the first grassland shrunken area image, regarding an area with a pixel value larger than a set threshold as a grassland area without shrunken;
a second acquisition module configured to: acquiring a second grassland shrunken area image within a second set time range of the designated area;
an output module configured to: and carrying out image alignment on the second grassland shrunken area image and the first grassland shrunken area image, removing the grassland areas without shrubbering from the aligned second grassland shrubbered area image, and marking the areas with the pixel point values larger than the set threshold value in the remaining areas to obtain the distribution range of the shrubbering.
In a third aspect, the present invention further provides an electronic device, including:
a memory for non-transitory storage of computer readable instructions; and
a processor for executing the computer readable instructions,
wherein the computer readable instructions, when executed by the processor, perform the method of the first aspect.
In a fourth aspect, the present invention also provides a storage medium storing non-transitory computer readable instructions, wherein the non-transitory computer readable instructions, when executed by a computer, perform the instructions of the method of the first aspect.
In a fifth aspect, the invention also provides a computer program product comprising a computer program for implementing the method of the first aspect when run on one or more processors.
Compared with the prior art, the invention has the beneficial effects that:
the method is simple and convenient to operate, results can be automatically fed back after spring growth seasons every year through programming and other technical means, shrub expansion development can be monitored through year-by-year data accumulation, measures are reasonably taken to control shrub development, and sustainable development of ecology and production life in grassland areas is guaranteed.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, are included to provide a further understanding of the invention, and are incorporated in and constitute a part of this specification, illustrate exemplary embodiments of the invention and together with the description serve to explain the invention and not to limit the invention.
FIG. 1 is a flowchart of a method according to a first embodiment.
Detailed Description
It is to be understood that the following detailed description is exemplary and is intended to provide further explanation of the invention as claimed. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.
It is noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of exemplary embodiments according to the invention. As used herein, the singular forms "a", "an", and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise, and it should be understood that the terms "comprises" and "comprising", and any variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
The embodiments and features of the embodiments of the present invention may be combined with each other without conflict.
All data are obtained according to the embodiment and are legally applied on the data on the basis of compliance with laws and regulations and user consent.
Example one
The embodiment provides a method for rapidly identifying the shrub distribution range of shrubbery grassland;
as shown in fig. 1, a method for rapidly identifying the shrunken grassland shrub distribution range includes:
s101: acquiring a first grassland shrunken area image in a first set time range of a designated area;
s102: from the first grassland shrunken area image, regarding an area with a pixel value larger than a set threshold as a grassland area without shrunken;
s103: acquiring a second grassland shrunken area image within a second set time range of the designated area;
s104: and carrying out image alignment on the second grassland shrunken area image and the first grassland shrunken area image, removing the grassland areas without shrubbering from the aligned second grassland shrubbered area image, and marking the areas with the pixel point values larger than the set threshold value in the remaining areas to obtain the distribution range of the shrubbering.
Further, the first grassland shrunken area image is a remote sensing image of a grassland shrunken area MODIS (model-resolution Imaging spectroscopy, abbreviated as MODIS, chinese to medium-resolution Imaging spectrometer).
Furthermore, the designated area refers to a part or all of the area selected from the grassland.
Further, the first set time range is from 4 middle ten months to 5 early months. For example, 4 months 15 days to 5 months 1 days.
Preferably, the first set time range is replaced by a first time point; the first time point refers to 4 months and 20 days.
Further, the S102: from the first grassland shrunken area image, regarding an area with a pixel value larger than a set threshold as a grassland area without shrunken; the method specifically comprises the following steps:
extracting an NDVI (Normalized Difference Vegetation Index, abbreviated as NDVI, and explained in Chinese as a Normalized Vegetation Index) map layer, and regarding an area with a pixel value larger than a set threshold as a grassland area without shrunken clustering; wherein, setting the dynamic threshold value to be 0.1 means that the area is identified as the grassland when the pixel NDVI value reaches 10% of the amplitude of the current year.
Further, the step S103: the second predetermined time range is from about 5 months to about 6 months. For example, 5 months 2 days to 6 months 1 days.
Preferably, the second set time range is replaced by a second time point; the second time point is 5 months and 20 days.
Further, the S104: and carrying out image alignment on the second grassland shrunken area image and the first grassland shrunken area image, and carrying out image alignment by adopting an ORB (ordered Brief) -based characteristic.
Further, the removing of the area of the grassland where no shrubbling occurs from the aligned second image of the grassland shrubbed area refers to: and selecting the grassland areas without shrubbery from the aligned second grassland shrubbery area image, and removing the selected areas in a segmentation mode or setting the pixel values of the selected areas to be zero.
Further, the marking an area in which the pixel point value in the remaining area is greater than a set threshold to obtain a distribution range of the brushwood specifically includes: and carrying out area statistics on the marked area to obtain the distribution range of the bush.
The invention is based on the data of the on-site observation of the shrub and grassland green turning period by the author, combines the remote sensing data, and rapidly distinguishes the shrub distribution range, and the specific method is as follows:
and (3) the shrub green-turning period appears at the early stage of 5 months earliest, and all the peripheral grasslands turn green in the middle ten days of 4 months latest (see Fan et al, 2018), so that the remote sensing image of the grassland shrubbery area MODIS is obtained, and the green-turning period of each pixel is extracted according to the NDVI initial threshold of 0.1 by a dynamic threshold method.
The results are divided by the classification function of the Arcgis, the area with the green returning before 5 months can be regarded as the grassland area without shrubbling, and the range with the green returning after 5-6 months can be regarded as the shrub.
Example two
The embodiment provides a system for rapidly identifying the shrub distribution range of shrubbery grassland;
a system for rapidly identifying shrunken grassland shrub distribution ranges, comprising:
a first acquisition module configured to: acquiring a first grassland shrunken area image in a first set time range of a designated area;
a screening module configured to: from the first grassland shrunken area image, regarding an area with a pixel value larger than a set threshold as a grassland area without shrunken;
a second acquisition module configured to: acquiring a second grassland shrunken area image within a second set time range of the designated area;
an output module configured to: and carrying out image alignment on the second grassland shrunken area image and the first grassland shrunken area image, removing the grassland areas without shrubbering from the aligned second grassland shrubbered area image, and marking the areas with the pixel point values larger than the set threshold value in the remaining areas to obtain the distribution range of the shrubbering.
It should be noted here that the first obtaining module, the screening module, the second obtaining module and the output module correspond to steps S101 to S104 in the first embodiment, and the modules are the same as the corresponding steps in the implementation example and the application scenario, but are not limited to the disclosure of the first embodiment. It should be noted that the modules described above as part of a system may be implemented in a computer system such as a set of computer-executable instructions.
In the foregoing embodiments, the descriptions of the embodiments have different emphasis, and for parts that are not described in detail in a certain embodiment, reference may be made to related descriptions of other embodiments.
The proposed system can be implemented in other ways. For example, the above-described system embodiments are merely illustrative, and for example, the division of the above-described modules is merely a logical division, and in actual implementation, there may be other divisions, for example, multiple modules may be combined or integrated into another system, or some features may be omitted, or not executed.
EXAMPLE III
The present embodiment also provides an electronic device, including: one or more processors, one or more memories, and one or more computer programs; wherein, a processor is connected with the memory, the one or more computer programs are stored in the memory, and when the electronic device runs, the processor executes the one or more computer programs stored in the memory, so as to make the electronic device execute the method according to the first embodiment.
It should be understood that in this embodiment, the processor may be a central processing unit CPU, and the processor may also be other general purpose processors, digital signal processors DSP, application specific integrated circuits ASIC, off-the-shelf programmable gate arrays FPGA or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, and so on. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The memory may include both read-only memory and random access memory, and may provide instructions and data to the processor, and a portion of the memory may also include non-volatile random access memory. For example, the memory may also store device type information.
In implementation, the steps of the above method may be performed by integrated logic circuits of hardware in a processor or instructions in the form of software.
The method in the first embodiment may be directly implemented by a hardware processor, or may be implemented by a combination of hardware and software modules in the processor. The software modules may be located in ram, flash, rom, prom, or eprom, registers, among other storage media as is well known in the art. The storage medium is located in a memory, and a processor reads information in the memory and completes the steps of the method in combination with hardware of the processor. To avoid repetition, it is not described in detail here.
Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
Example four
The present embodiments also provide a computer-readable storage medium for storing computer instructions, which when executed by a processor, perform the method of the first embodiment.
The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (10)
1. A method for rapidly identifying the shrub distribution range of shrubbery grassland is characterized by comprising the following steps:
acquiring a first grassland shrunken area image in a first set time range of a designated area;
from the first grassland shrunken area image, regarding an area with a pixel value larger than a set threshold as a grassland area without shrunken;
acquiring a second grassland shrunken area image within a second set time range of the designated area;
and carrying out image alignment on the second grassland shrunken area image and the first grassland shrunken area image, removing the grassland areas without shrubbering from the aligned second grassland shrubbered area image, and marking the areas with the pixel point values larger than the set threshold value in the remaining areas to obtain the distribution range of the shrubbering.
2. The method as claimed in claim 1, wherein the first grassland shrunken area image is a grassland shrunken area MODIS remote sensing image.
3. The method as claimed in claim 1, wherein the designated area is a part or all of the area selected from the grassland.
4. The method according to claim 1, wherein the first predetermined time range is from 4 middle of month to 5 early months; the second time range, from about 5 months to about 6 months.
5. The method of claim 1, wherein the second grassland shrunken area image is image-aligned with the first grassland shrunken area image, and wherein the image-alignment is performed based on ORB features.
6. The method as claimed in claim 1, wherein the removing of the area of the grassland where no shrubby occurs from the aligned second grassland shrubbed area image is: and selecting the grassland areas without shrubbering from the aligned second grassland shrubbed area image, and segmenting and removing the selected areas or setting the pixel values of the selected areas to be zero.
7. The method as claimed in claim 1, wherein said marking the areas with pixel point values greater than the set threshold in the remaining areas to obtain the shrub distribution range comprises: and carrying out area statistics on the marked area to obtain the distribution range of the bush.
8. A system for rapidly identifying the shrub distribution range of shrubbery grassland is characterized by comprising the following components:
a first acquisition module configured to: acquiring a first grassland shrunken area image in a first set time range of a designated area;
a screening module configured to: from the first grassland shrunken area image, regarding an area with a pixel value larger than a set threshold as a grassland area without shrunken;
a second acquisition module configured to: acquiring a second grassland shrunken area image within a second set time range of the designated area;
an output module configured to: and carrying out image alignment on the second grassland shrunken area image and the first grassland shrunken area image, removing the grassland areas without shrubbering from the aligned second grassland shrubbered area image, and marking the areas with the pixel point values larger than the set threshold value in the remaining areas to obtain the distribution range of the shrubbering.
9. An electronic device, comprising:
a memory for non-transitory storage of computer readable instructions; and
a processor for executing the computer readable instructions,
wherein the computer readable instructions, when executed by the processor, perform the method of any of claims 1-7.
10. A storage medium storing non-transitory computer-readable instructions, wherein the non-transitory computer-readable instructions, when executed by a computer, perform the instructions of the method of any one of claims 1-7.
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116481600A (en) * | 2023-06-26 | 2023-07-25 | 四川省林业勘察设计研究院有限公司 | Plateau forestry ecological monitoring and early warning system and method |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN116481600A (en) * | 2023-06-26 | 2023-07-25 | 四川省林业勘察设计研究院有限公司 | Plateau forestry ecological monitoring and early warning system and method |
| CN116481600B (en) * | 2023-06-26 | 2023-10-20 | 四川省林业勘察设计研究院有限公司 | Plateau forestry ecological monitoring and early warning system and method |
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