CN112861766A - Satellite remote sensing extraction method and device for farmland corn straw - Google Patents
Satellite remote sensing extraction method and device for farmland corn straw Download PDFInfo
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Abstract
The invention provides a farmland corn straw satellite remote sensing extraction method and a device, and the method comprises the following steps: determining a normalized short-wave infrared straw index NDSSI, a superimposed infrared straw index AIRSI and a superimposed near-red straw index PNISI according to the reflectivity of each wave band of the target remote sensing image; and determining the corn straw region according to the value range of any one or more of NDSSI, AIRSI and PNISI. According to the method, the farmland corn straw autumn and winter remote sensing monitoring result is determined by three novel straw indexes including the normalized short wave infrared straw index, the superimposed infrared straw index and the superimposed near red straw index, so that the extraction precision and efficiency of the farmland corn straw can be improved, manual investigation is reduced, and data support is provided for straw burning supervision.
Description
Technical Field
The invention relates to the technical field of agricultural remote sensing, in particular to a farmland corn straw satellite remote sensing extraction method and device.
Background
Most of the corn stalks of the farmland are harvested when the corns are harvested, but part of the corn stalks are prepared for planting spring corn areas and scattered planting areas in the next year, and the stalks are not harvested after the harvesting season of the corns and are distributed in the field in an upright or lodging manner. The straws are extremely easy to be burnt in autumn and winter or spring of the next year, and are high-risk key areas for straw burning supervision of agricultural or environmental protection departments. The farmland straw distribution survey is the basis of straw burning prevention and control work.
At present, straw burning prevention and control mainly depends on field ground investigation of a supervisor, and then statistics and reporting are carried out, so that time and labor are wasted, and efficiency is low. At present, the research on remote sensing monitoring of straw plants is less, the relevant research is remote sensing monitoring of straw coverage degree after soil and straw stubbles are mixed after straw returning, the key point is remote sensing monitoring of a field which is crushed and returned after corn harvesting and is covered with the straw stubbles, a monitoring object is a mixture of the crushed straw stubbles and the soil, an object for monitoring the vertical corn straws in the field is a complete corn straw plant on the field, the two monitoring objects are completely different and have different shapes, and therefore, the method for monitoring and extracting the corn straws in the field is completely different from the straw coverage degree. In order to meet the requirements of high-precision and rapid positioning of farmland corn straws and scientific scheduling of straw harvesting in practical work of supervision departments, a novel high-efficiency straw index suitable for satellite remote sensing images is found according to the typical characteristics of the farmland corn straws, and rapid and high-efficiency extraction of the farmland corn straws in autumn and winter becomes a technical problem to be solved urgently.
Disclosure of Invention
Aiming at the problems in the prior art, the invention provides a satellite remote sensing extraction method and device for farmland corn straw.
The invention provides a farmland corn straw satellite remote sensing extraction method, which comprises the following steps: determining a normalized short-wave infrared straw index NDSSI, a superimposed infrared straw index AIRSI and a superimposed near-red straw index PNISI according to the reflectivity of each wave band of the target remote sensing image;
determining the corn straw region according to the value range of any one or more of NDSSI, AIRSI and PNISI, and if various indexes are adopted, the advantages can be complemented to improve the monitoring precision;
wherein the AIRSI is determined according to the reflectivity weighted values of B4, B5 and B12 wave bands; PNISI is determined from B4 and B8 band reflectivities; NDSSI is determined from B9 and B12 band reflectivities.
According to the farmland corn stalk satellite remote sensing extraction method provided by the embodiment of the invention, before the corn stalk region is determined according to the value range of any one or more of NDSSI, AIRSI and PNISI, the method further comprises the following steps:
acquiring satellite remote sensing images of three time phases in a research area;
determining an artificial ground object area according to the remote sensing image of the first time phase, and determining a forest land area according to the remote sensing image of the second time phase;
removing artificial ground object areas and forest land areas from the remote sensing image of the third time phase to obtain the target remote sensing image;
wherein the first time phase is a flowering period with the highest chlorophyll content of the corn straws; the second time phase is the period of the forest land and the corn straw with the largest chlorophyll content difference; and the third phase is a harvesting period with the lowest chlorophyll content after the maize straws are dried.
According to the farmland corn straw satellite remote sensing extraction method provided by the embodiment of the invention, the artificial ground object region is determined according to the remote sensing image of the first time phase, and the forest land region is determined according to the remote sensing image of the second time phase, and the method comprises the following steps: according to the remote sensing image of the first time phase, determining an artificial ground object region in the region where the normalized vegetation index NDVI is less than 0.5 or the reflectivity of the blue light wave band is greater than 0.08; and determining the forest land area according to the remote sensing image of the second time phase and the image area with the NDVI being more than or equal to 0.5.
According to the farmland corn stalk satellite remote sensing extraction method provided by the embodiment of the invention, the method for determining the PNISI or NDSSI correspondingly comprises the following steps:
wherein, B4, B8, B9 and B12 are respectively the reflectivity of the corresponding wave band.
According to the farmland corn straw satellite remote sensing extraction method provided by the embodiment of the invention, the value ranges of PNISI, NDSSI and AIRSI are respectively as follows: PNISI < 0.05, NDSSI < 0.065, NDSSI < 0.07, AIRSI < 0.6, and AIRSI < 0.75.
According to the farmland corn stalk satellite remote sensing extraction method provided by the embodiment of the invention, after the corn stalk region is determined, the method further comprises the following steps: and converting the grid image of the corn straw region extraction result into a vector file.
According to the farmland corn stalk satellite remote sensing extraction method provided by the embodiment of the invention, the corn stalk region is determined according to the value range of any one or more of NDSSI, AIRSI and PNISI, and the method comprises the following steps: and determining the corn straw region according to the region which simultaneously meets the value ranges of NDSSI, AIRSI and PNISI.
The invention also provides a farmland corn straw satellite remote sensing extraction device, which comprises: the acquisition module is used for determining a normalized short wave infrared straw index NDSSI, a superimposed infrared straw index AIRSI and a superimposed near red straw index PNISI according to the reflectivity of each wave band of the target remote sensing image; the processing module is used for determining a corn straw region according to the value range of any one or more of NDSSI, AIRSI and PNISI; wherein the AIRSI is determined according to the reflectivity weighted values of B4, B5 and B12 wave bands; PNISI is determined from B4 and B8 band reflectivities; NDSSI is determined from B9 and B12 band reflectivities.
The invention also provides electronic equipment which comprises a memory, a processor and a computer program which is stored on the memory and can run on the processor, wherein the processor executes the program to realize the steps of any one of the farmland corn straw satellite remote sensing extraction methods.
The invention also provides a non-transitory computer readable storage medium, on which a computer program is stored, which when executed by a processor, implements the steps of the farmland corn stalk satellite remote sensing extraction method as described in any one of the above.
According to the farmland corn straw satellite remote sensing extraction method and device, the farmland corn straw autumn and winter remote sensing result is determined by three novel straw indexes including the normalized short wave infrared straw index, the superimposed infrared straw index and the superimposed near red straw index, so that the extraction precision and efficiency of the farmland corn straw can be improved, manual investigation is reduced, and data support is provided for straw burning supervision.
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In order to more clearly illustrate the technical solutions of the present invention or the prior art, the drawings needed for the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and those skilled in the art can also obtain other drawings according to the drawings without creative efforts.
FIG. 1 is a schematic flow diagram of a farmland corn stalk satellite remote sensing extraction method provided by the invention;
FIG. 2 is a second schematic flow chart of the farmland corn stalk satellite remote sensing extraction method provided by the invention;
FIG. 3 is a novel straw index AIRSI-NDSSI scatter diagram of main ground feature sampling points of a farmland provided by the invention;
FIG. 4 is a schematic structural diagram of a farmland corn stalk satellite remote sensing extraction device provided by the invention;
fig. 5 is a schematic structural diagram of an electronic device provided in the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention clearer, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings, and it is obvious that the described embodiments are some, but not all embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The farmland corn stalk satellite remote sensing extraction method and the device thereof are described below with reference to fig. 1-5. Fig. 1 is a schematic flow diagram of a farmland corn stalk satellite remote sensing extraction method provided by the invention, and as shown in fig. 1, the farmland corn stalk satellite remote sensing extraction method provided by the invention comprises the following steps:
101. determining a normalized short-wave infrared straw index NDSSI, a superimposed infrared straw index AIRSI and a superimposed near-red straw index PNISI according to the reflectivity of each wave band of the target remote sensing image;
102. determining a corn straw region according to the value range of any one or more of NDSSI, AIRSI and PNISI;
wherein the AIRSI is determined according to the reflectivity weighted values of B4, B5 and B12 wave bands; PNISI is determined from B4 and B8 band reflectivities e; NDSSI is determined from B9 and B12 band reflectivities.
B4 is red band (650nm-680nm), B5 is red side band (698nm-713nm), B8 is near infrared band (785nm-900nm), B9 is water vapor band (1360nm-1390nm), and B12 is short wave infrared band (2100nm-2280 nm).
As an alternative embodiment, the target remote sensing image is a sentry second satellite remote sensing image, which is taken as an example for description below. The sentinel II image has 12 wave bands of B1(433nm-453nm), B2(458nm-523nm), B3(543nm-578nm), B4(650nm-680nm), B5(698nm-713nm), B6(733nm-748nm), B7(773nm-793nm), B8(785nm-900nm), B8B (935nm-955nm), B9(1360nm-1390nm), B11(1565nm-1655nm) and B12(2100nm-2280nm), and the image needs to be preprocessed, and comprises data decompression, data derivation, wave band combination, radiation correction, geometric correction and image cutting. The image data decompression and data derivation can be completed in SNAP software specified by the European Bureau, the wave band combination, radiation correction, geometric correction and image clipping of the image can be completed in ENVI software, the spatial resolution of the image is 10m, and the coordinate system is WGS84_ UTM _ Zone 50N.
And obtaining the reflectivity of each wave band of the target remote sensing image after acquiring the data of the satellite remote sensing image in autumn and winter in the research area. According to a spectral graph of farmland land features, by comprehensively analyzing spectral differences of upright field corn straws, tiled broken stubble straws, bare land, dense wheat, sparse wheat and deciduous forest lands, 3 novel straw indexes are provided and constructed, and specifically three novel straw indexes including a normalized short-wave infrared straw index NDSSI, a superimposed infrared straw index AIRSI and a superimposed near-red straw index PNISI are provided and constructed according to the reflectivity of each wave band.
1. Constructing a novel stacked near-red straw index PNISI.
Through detailed analysis of the spectral curves, the spectral values of the stubble-breaking straws, the sparse wheat and the dense wheat are obviously greater than those of bare land and corn straws at the B8 waveband, and the spectral differences of the stubble-breaking straws, the sparse wheat and the dense wheat at the B4 waveband and the B8 waveband are also obviously greater than those of other ground objects, so that the near-red straw overlapping index is constructed according to the characteristics:
in one embodiment, the PNISI is:
in the above formula, B4 is the reflectance value of B4 band (red band) in the sentinel second satellite image, and B8 is the reflectance value of B8 band (near infrared band) in the sentinel second satellite image.
In order to embody the details, the straw index calculation is carried out after the reflectivity is enlarged by 10000 times. The PNISI is utilized to realize the obvious distinction between dense wheat, sparse wheat, stubble smashing straw, corn straw and bare land, the PNISI is more than 1250 for dense wheat, the PNISI is less than or equal to 1250 for corn straw, sparse wheat, stubble smashing straw and bare land, wherein the corn straw is mainly distributed in (500, 650). Therefore, the triticale can be effectively removed by using PNISI.
2. Construction of novel normalized short-wave infrared straw index NDSSI
Through detailed analysis of the spectral curves, the difference between the spectral values of the corn stalks and the bare land in the B9 waveband is not large, and the spectral value of the bare land in the B12 waveband is obviously larger than that of the corn stalks. Constructing a normalized short-wave infrared straw index NDSSI according to the characteristics:
in one embodiment, the NDSSI is:
in the above formula, B9 is the reflectance value of B9 band in the sentinel second satellite image, and B12 is the reflectance value of B12 band in the sentinel second satellite image.
NDSSI is used for realizing the obvious distinction of dense wheat, stubble-breaking straw and corn straw, bare land and sparse wheat, NDSSI is less than-0.09 for stubble-breaking straw and dense wheat, wherein the corn straw is mainly distributed at (-0.07, 0.07). Therefore, the NDSSI can be used for effectively removing the broken straws and the dense wheat.
3. Constructing a novel superposed infrared straw index AIRSI.
Detailed analysis on a spectral curve shows that the discrimination of farmland corn stalks and other land features (corn stubbles, bare lands and wheat) is higher in B4 and B5, particularly in B12 wave bands, so that three wave bands of B4 (red light), B5 (red side) and B12 (short-wave infrared) are sensitive wave bands extracted from the farmland corn stalks, the B12 wave band image value is about 3000 (corresponding to the reflectivity of 0.3), the discrimination is maximum, the B4 and B5 wave band image values are about 1500 (corresponding to the reflectivity of 0.15), and the wave band discrimination is inferior. According to the characteristics, the index AIRSI of the superposed infrared straw is constructed as follows:
AIRSI＝(a×B4+b×B5+B12)/c
in the above formula, B4 is the B4 band reflectivity in the sentinel second satellite image, B5 is the B5 band reflectivity in the sentinel second satellite image, and B12 is the B12 band reflectivity in the sentinel second satellite image. The B4 waveband adjusting coefficient is 1.8 in the case of a, the B5 waveband adjusting coefficient is 1.5 in the case of B5, and the B12 waveband adjusting coefficient is 10000 in the case of c.
According to the sampling point statistical result of the superimposed infrared straw index AIRSI, the AIRSI can be used for realizing the obvious distinction of the corn straw, the dense wheat, the broken straw, the sparse wheat and the bare land, wherein the AIRSI is more than 0.6 and less than 0.75, the corn straw is used, the AIRSI is less than or equal to 0.6, the dense wheat is used, and the AIRSI is more than or equal to 0.76, the sparse wheat, the broken straw and the bare land are used.
According to the farmland corn straw satellite remote sensing extraction method, the farmland corn straw autumn and winter remote sensing result is determined by three novel straw indexes including the normalized short wave infrared straw index, the superimposed infrared straw index and the superimposed near red straw index, so that the extraction precision and efficiency of the farmland corn straw can be improved, manual investigation is reduced, and data support is provided for straw burning supervision.
In one embodiment, before determining the corn stalk region according to the value range of any one or more of the NDSSI, the AIRSI and the PNISI, the method further comprises: acquiring satellite remote sensing images of three time phases in a research area; determining an artificial ground object area according to the remote sensing image of the first time phase, and determining a forest land area according to the remote sensing image of the second time phase; removing artificial ground object areas and forest land areas from the remote sensing image of the third time phase to obtain the target remote sensing image; wherein the first time phase is a flowering period with the highest chlorophyll content of the corn straws; the second time phase is the period of the forest land and the corn straw with the largest chlorophyll content difference; and the third phase is a harvesting period with the lowest chlorophyll content after the maize straws are dried.
Considering that the artificial land features and the forest land can influence the regional result, in order to improve the accuracy of straw extraction, the method and the device respectively extract and remove the artificial land features and the forest land according to three different time phase data. That is, the target remote sensing image is a remote sensing image from which the forest land and the artificial land feature are removed.
In the present invention, the time periods corresponding to the three phases may be selected from the corresponding time periods as a relatively large time period, and the time period is not limited to the most significant time period, and may be a time period within a certain range of the most significant time period. For example, in one embodiment, the first, second, and third phases have periods of 9 months, 4 days, 10 months, 16 days, and 11 months, 8 days, respectively, that are close to enabling relatively accurate corn stover extraction. However, the date is not limited to the above.
In one embodiment, the determining the artificial ground object region according to the remote sensing image of the first time phase and the determining the forest land region according to the remote sensing image of the second time phase respectively comprise: according to the remote sensing image of the first time phase, determining an artificial ground object region in the region where the normalized vegetation index NDVI is less than 0.5 or the reflectivity of the blue light wave band is greater than 0.08; and determining the forest land area according to the remote sensing image of the second time phase and the image area with the NDVI being more than or equal to 0.5.
Firstly, in order to better extract the corn straws of the farmland, non-target ground objects need to be removed, and artificial ground objects such as house buildings, roads and the like which belong to the non-target ground objects need to be removed.
Because the majority of the artificial buildings are grey white, and are mixed with roofs of blue, red and the like, the chlorophyll content of the corn stalks of the farmland is rich in the early stage of 9 months, the green vegetation signals are strong, great contrast is formed between the green vegetation signals and grey white, blue and red of the artificial buildings, and the distinguishability is high. And selecting a 9-month and 4-day image to calculate the normalized vegetation index NDVI, and finding that the NDVI value of the artificial building in the period is generally lower than 0.5 through repeated debugging, so that the NDVI less than 0.5 is set as the extraction threshold of the artificial building. The blue roof included in the artificial building is easy to be subjected to the missing division, and the B2 (blue light band) reflectivity of the blue ground object is more than 0.08 through repeated debugging. Therefore, the image of day 4 and 9 months is subjected to binarization processing, the image area with NDVI < 0.5 or B2 > 0.08 is assigned as 1, and the other image areas are assigned as 0, so as to generate the artificial terrain distribution map. This step may be performed in the ENVI software.
In the above formula, B4 is the reflectance value of B4 band (red band) in the sentinel second satellite image, and B8 is the reflectance value of B8 band (near infrared band) in the sentinel second satellite image.
Besides artificial land features, the same plants as the corn stalks in the forest land are withered and yellow in winter, so that the corn stalks in the forest land need to be removed for better extraction of the corn stalks in the farmland. At the early stage of 10 months, the forest land is dense, the chlorophyll content is rich, the green vegetation signal is strong, and the distinguishing degree is high by contrast with the withered and yellow corn straws at the period. The method comprises the steps of selecting a 10-month 16-day image to calculate the NDVI vegetation index, finding that the NDVI value of the forest land in the period is generally higher than 0.5 through repeated debugging, setting the NDVI to be more than or equal to 0.5 as a forest land extraction threshold, carrying out binarization processing on the 10-month 16-day image, assigning the image area with the NDVI to be more than or equal to 0.5 as 1, assigning the image area with the NDVI to be less than 0.5 as 0, and generating a forest land distribution map. This step is done in the ENVI software.
Setting the artificial ground object distribution map as a mask map layer, performing mask processing on the 11-month and 8-day (third time phase) image, and removing the artificial ground objects in the 11-month and 8-day image; and then setting the forest land distribution map as a mask map layer, carrying out secondary mask processing on the 11-month and 8-day image from which the artificial land objects are removed, and removing the forest land in the 11-month and 8-day image. And generating a new remote sensing image of 11 months and 8 days without artificial ground objects and forest lands. This step may be performed in the ENVI software.
According to the farmland corn straw satellite remote sensing extraction method, the influence of artificial land features and woodland is eliminated through three different time phases, and the accuracy of straw extraction can be improved.
In an embodiment, the method for determining the PNISI or NDSSI correspondingly includes:
wherein, B4, B8, B9 and B12 are respectively the reflectivity of the corresponding wave band. The above embodiments have been described by way of example, and are not described in detail herein.
In an embodiment, the value ranges of PNISI, NDSSI, and AIRSI are: 0.05 < PNISI < 0.065 (500 < PNISI < 650 if the magnification is 10000 times), 0.07 < NDSSI < 0.07, 0.6 < AIRSI < 0.75.
The discrimination of the dense wheat and other four ground objects is maximum, and the extraction is easy; the combination of two indexes of AIRSI-NDSSI can effectively extract the broken stubble straws; the combination of PNISI-NDSSI two indexes is utilized, so that bare land can be effectively extracted; wheat thinning is easily confused with corn stover.
In one embodiment, determining the corn stalk region according to the value range of any one or more of NDSSI, AIRSI and PNISI comprises: and determining the corn straw region according to the region which simultaneously meets the value ranges of NDSSI, AIRSI and PNISI.
The separation and extraction of the sparse wheat and the corn stalks are realized by combining three indexes of AIRSI-PNISI-NDSSI, which shows that the corn stalks have better separability with other fields. Through extraction of multiple indexes, advantage complementation of each index can be realized, and therefore monitoring precision is further improved.
Based on the constructed 3 novel straw indexes PNISI, AIRSI and NDSSI, through comprehensive analysis of a ground feature spectral curve and a statistical analysis chart, and repeated debugging, a reasonable threshold value for distinguishing different ground features is determined, and a comprehensive autumn and winter farmland corn straw classification extraction rule set is formed. This step may be performed in the ENVI software.
In one embodiment, after the determining the corn stalk region, the method further comprises: and converting the grid image of the corn straw region extraction result into a vector file.
The farmland corn straw distribution map generated in the previous step is a grid image, and in order to facilitate later-stage practical application, the farmland corn straw distribution map (grid image) is converted into a farmland corn straw distribution map (vector file) in an shp format by a grid-to-vector tool. This step can be done in ArcGIS software.
After the step, the generated farmland corn straw distribution map (shp format) and the remote sensing image of the sentinel II can be overlaid, displayed and plotted, and a final farmland corn straw thematic map is generated. This step can be done in ArcGIS software.
Fig. 2 is a second schematic flow chart of the farmland corn stalk satellite remote sensing extraction method provided by the invention, which can be seen in the steps of the above embodiment and fig. 2. FIG. 3 is a diagram of a novel straw index AIRSI-NDSSI scatter diagram of main land feature sampling points of a farmland, which can be referred to in the embodiment.
The farmland corn stalk satellite remote sensing extraction device provided by the invention is described below, and the farmland corn stalk satellite remote sensing extraction device described below and the farmland corn stalk satellite remote sensing extraction method described above can be referred to correspondingly.
Fig. 4 is a schematic structural diagram of the farmland corn stalk satellite remote sensing extraction device provided by the invention, and as shown in fig. 4, the farmland corn stalk satellite remote sensing extraction device comprises: an acquisition module 401 and a processing module 402. The acquisition module 401 is configured to determine a normalized short-wave infrared straw index NDSSI, a superimposed infrared straw index AIRSI, and a superimposed near-red straw index PNISI according to the reflectivity of each band of the target remote sensing image; the processing module 402 is configured to determine a corn stalk region according to a value range of any one or more of NDSSI, AIRSI, and PNISI; wherein the AIRSI is determined according to the reflectivity weighted values of B4, B5 and B12 wave bands; PNISI is determined from B4 and B8 band reflectivities; NDSSI is determined from B9 and B12 band reflectivities.
The device embodiment provided in the embodiments of the present invention is for implementing the above method embodiments, and for details of the process and the details, reference is made to the above method embodiments, which are not described herein again.
According to the farmland corn straw satellite remote sensing extraction device provided by the embodiment of the invention, the farmland corn straw autumn and winter remote sensing result is determined by three novel straw indexes including the normalized short wave infrared straw index, the superimposed infrared straw index and the superimposed near red straw index, so that the extraction precision and efficiency of the farmland corn straw can be improved, manual investigation is reduced, and data support is provided for straw burning supervision.
Fig. 5 is a schematic structural diagram of an electronic device provided in the present invention, and as shown in fig. 5, the electronic device may include: a processor (processor)501, a communication Interface (Communications Interface)502, a memory (memory)503, and a communication bus 504, wherein the processor 501, the communication Interface 502, and the memory 503 are configured to communicate with each other via the communication bus 504. Processor 501 may call logic instructions in memory 503 to perform a method for farmland corn stalk satellite remote sensing extraction, the method comprising: determining a normalized short-wave infrared straw index NDSSI, a superimposed infrared straw index AIRSI and a superimposed near-red straw index PNISI according to the reflectivity of each wave band of the target remote sensing image; and determining the corn straw region according to the value range of any one or more of NDSSI, AIRSI and PNISI.
In addition, the logic instructions in the memory 503 may be implemented in the form of software functional units and stored in a computer readable storage medium when the logic instructions are sold or used as independent products. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
In another aspect, the present invention further provides a computer program product, the computer program product includes a computer program stored on a non-transitory computer-readable storage medium, the computer program includes program instructions, when the program instructions are executed by a computer, the computer can execute the farmland corn stalk satellite remote sensing extraction method provided by the above methods, the method includes: determining a normalized short-wave infrared straw index NDSSI, a superimposed infrared straw index AIRSI and a superimposed near-red straw index PNISI according to the reflectivity of each wave band of the target remote sensing image; and determining the corn straw region according to the value range of any one or more of NDSSI, AIRSI and PNISI.
In still another aspect, the present invention further provides a non-transitory computer-readable storage medium, on which a computer program is stored, where the computer program is implemented by a processor to execute the farmland corn stalk satellite remote sensing extraction method provided in the foregoing embodiments, and the method includes: determining a normalized short-wave infrared straw index NDSSI, a superimposed infrared straw index AIRSI and a superimposed near-red straw index PNISI according to the reflectivity of each wave band of the target remote sensing image; and determining the corn straw region according to the value range of any one or more of NDSSI, AIRSI and PNISI.
The above-described embodiments of the apparatus are merely illustrative, and the units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment. One of ordinary skill in the art can understand and implement it without inventive effort.
Through the above description of the embodiments, those skilled in the art will clearly understand that each embodiment can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware. With this understanding in mind, the above-described technical solutions may be embodied in the form of a software product, which can be stored in a computer-readable storage medium such as ROM/RAM, magnetic disk, optical disk, etc., and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the methods described in the embodiments or some parts of the embodiments.
Finally, it should be noted that: the above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (10)
1. A farmland corn straw satellite remote sensing extraction method is characterized by comprising the following steps:
determining a normalized short-wave infrared straw index NDSSI, a superimposed infrared straw index AIRSI and a superimposed near-red straw index PNISI according to the reflectivity of each wave band of the target remote sensing image;
determining a corn straw region according to the value range of any one or more of NDSSI, AIRSI and PNISI;
wherein the AIRSI is determined according to the reflectivity weighted values of B4, B5 and B12 wave bands; PNISI is determined from B4 and B8 band reflectivities; NDSSI is determined from B9 and B12 band reflectivities.
2. The farmland corn stalk satellite remote sensing extraction method as claimed in claim 1, wherein before determining the corn stalk region according to the value range of any one or more of NDSSI, AIRSI and PNISI, the method further comprises:
acquiring satellite remote sensing images of three time phases in a research area;
determining an artificial ground object area according to the remote sensing image of the first time phase, and determining a forest land area according to the remote sensing image of the second time phase;
removing artificial ground object areas and forest land areas from the remote sensing image of the third time phase to obtain the target remote sensing image;
wherein the first time phase is a flowering period with the highest chlorophyll content of the corn straws; the second time phase is the period of the forest land and the corn straw with the largest chlorophyll content difference; and the third phase is a harvesting period with the lowest chlorophyll content after the maize straws are dried.
3. The farmland corn stalk satellite remote sensing extraction method as claimed in claim 2, wherein the determining of the artificial ground object region according to the remote sensing image of the first time phase and the determining of the forest land region according to the remote sensing image of the second time phase respectively comprise:
according to the remote sensing image of the first time phase, determining an artificial ground object region in the region where the normalized vegetation index NDVI is less than 0.5 or the reflectivity of the blue light wave band is greater than 0.08;
and determining the forest land area according to the remote sensing image of the second time phase and the image area with the NDVI being more than or equal to 0.5.
4. The farmland corn stalk satellite remote sensing extraction method as claimed in claim 1, wherein the PNISI or NDSSI determination method correspondingly comprises:
wherein, B4, B8, B9 and B12 are respectively the reflectivity of the corresponding wave band.
5. The farmland corn stalk satellite remote sensing extraction method as claimed in claim 1, wherein the value ranges of PNISI, NDSSI and AIRSI are respectively:
0.05＜PNISI＜0.065，-0.07＜NDSSI＜0.07，0.6＜AIRSI＜0.75。
6. the farmland corn stalk satellite remote sensing extraction method as claimed in claim 1, wherein after the corn stalk region is determined, the method further comprises:
and converting the grid image of the corn straw region extraction result into a vector file.
7. The farmland corn stalk satellite remote sensing extraction method as claimed in claim 1, wherein the determining of the corn stalk region according to the value range of any one or more of NDSSI, AIRSI and PNISI comprises:
and determining the corn straw region according to the region which simultaneously meets the value ranges of NDSSI, AIRSI and PNISI.
8. The utility model provides a farmland maize straw satellite remote sensing extraction element which characterized in that includes:
the acquisition module is used for determining a normalized short wave infrared straw index NDSSI, a superimposed infrared straw index AIRSI and a superimposed near red straw index PNISI according to the reflectivity of each wave band of the target remote sensing image;
the processing module is used for determining a corn straw region according to the value range of any one or more of NDSSI, AIRSI and PNISI;
wherein the AIRSI is determined according to the reflectivity weighted values of B4, B5 and B12 wave bands; PNISI is determined from B4 and B8 band reflectivities; NDSSI is determined from B9 and B12 band reflectivities.
9. An electronic device comprising a memory, a processor and a computer program stored in the memory and operable on the processor, wherein the processor executes the program to implement the steps of the farmland corn stalk satellite remote sensing extraction method according to any one of claims 1 to 7.
10. A non-transitory computer readable storage medium, having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of the farmland corn stover satellite remote sensing extraction method as claimed in any one of claims 1 to 7.
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