CN108345992A - A kind of multiple crop index extracting method and device - Google Patents
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Abstract
A kind of multiple crop index extracting method of present invention offer and device, the method includes：S1 obtains the normalized differential vegetation index time-serial position of the target area in preset duration since the initial time according to the initial time of crop cultivation in target area；S2 obtains the wave crest in the normalized differential vegetation index time-serial position using second differnce method, if each wave crest is single Interference Peaks, it is smooth to carry out condition to single Interference Peaks；S3, reuse the second differnce method obtain condition it is smooth after the normalized differential vegetation index time-serial position in peak value, and statistical condition it is smooth after the normalized differential vegetation index time-serial position in peak value sum, using the peak value sum as the multiple crop index of the target area.The present invention improves the precision of multiple crop index extraction.
Description
Technical Field
The invention belongs to the field of agricultural production evaluation, and particularly relates to a multiple cropping index extraction method and device.
Background
The Multiple Cropping Index (MCI) is a commonly used quantitative Index for agricultural production evaluation and farmland utilization evaluation, and is an average number of times of planting crops on the same farmland in a certain period (generally 1 year), and the numerical value is equal to the ratio of the total seeding area to the tillage area of the crops in the whole year on the farmland. The multiple cropping index reflects the utilization degree of cultivated land and is expressed by percentage. The calculation formula is that the multiple cropping index is the total area of the crop sowed (or transplanted) all year round divided by the total area of the cultivated land multiplied by 100 percent. The multiple cropping index can be used for comparing the utilization conditions of cultivated lands among different years, different regions and different generating units.
At present, the multiple cropping index extraction of cultivated land is mostly obtained through land survey and agricultural statistics. Although the method for obtaining the multiple cropping index through investigation and statistics is simple and easy to implement, the interference of the statistical caliber and human factors is large, and the requirement for obtaining the multiple cropping index in a large range and high timeliness is difficult to meet. Therefore, the farmland multiple cropping index extraction method based on the remote sensing technology becomes a hot problem for research.
The farmland multiple cropping index extraction method based on the remote sensing technology is mostly based on normalized vegetation index time sequence data, and firstly, a smooth annual normalized vegetation index change curve is obtained through various filtering and denoising methods. And then performing different cooking judgments according to a peak value method and a related method thereof. Due to the influence of data noise, management measures in different regions and short-term climate change, the peak value number and the cooking system are not in one-to-one correspondence, and the extraction error of the multiple cropping index is large and inaccurate.
Disclosure of Invention
In order to overcome the problems of large error and inaccuracy of extraction of the multiple cropping indexes or at least partially solve the problems, the invention provides a method and a device for extracting the multiple cropping indexes.
According to a first aspect of the present invention, there is provided a multiple cropping index extraction method, comprising:
s1, acquiring a normalized vegetation index time series curve of the target area within a preset time length from the initial time according to the initial time of crop cultivation in the target area;
s2, obtaining wave crests in the normalized vegetation index time sequence curve by using a second-order difference method, and if each wave crest is a single interference peak, performing conditional smoothing on the single interference peak;
and S3, obtaining the peak value in the normalized vegetation index time series curve after condition smoothing by using the second-order difference method again, counting the total number of the peak values in the normalized vegetation index time series curve after condition smoothing, and taking the total number of the peak values as the multiple seeding index of the target area.
Specifically, the step S1 is preceded by:
according to the coordinates of the target area, acquiring a preset coordinate range to which the coordinates belong and the crop cultivation starting time and the crop growth period corresponding to the preset coordinate range; and the preset coordinate range is pre-associated with the starting time for storage, and the preset coordinate range is pre-associated with the growth cycle for storage.
Specifically, the step S1 is preceded by:
acquiring a normalized vegetation index time series curve of a target area for at least two years; wherein the normalized vegetation index time series curve has a band of less than or equal to half a month;
smoothing the normalized vegetation index time series curve by using an SG filtering algorithm; wherein, the half wave width of the SG filtering algorithm is less than or equal to one half of the total number of wave bands in the normalized vegetation index time series curve;
correspondingly, the step S1 specifically includes:
and according to the starting time of crop cultivation in the target area, selecting a normalized vegetation index time series curve within a preset time length from the starting time from the smoothed normalized vegetation index time series curve.
Specifically, the calculation formula for obtaining the peak in the normalized vegetation index time series curve by using the second order difference method in step S2 is as follows:
di 1＝NDVIi-NDVIi-1；
if d isi 1>0，di 2＝1；
If d isi 1<0，di 2＝-1；
di 3＝di 2-di-1 2；
Wherein NDVIiIs the normalized vegetation index, NDVI, at the ith moment in any normalized vegetation index time series curvei-1Is the normalized vegetation index at a time immediately preceding the i-th time, di 1Is the first order difference at time i, di 2Is an intermediate attribute at time i, di-1 2Intermediate attribute of the time immediately preceding the i-th time, di 3Is the second order difference at the ith moment;
if d isi 3If the normalized vegetation index at the ith moment is a peak, the normalized vegetation index is obtained as-2;
if d isi 3And 2, the normalized vegetation index at the ith moment is known as the trough.
Specifically, the step of determining whether each peak is a single interference peak in step S2 specifically includes:
for each peak in the normalized vegetation index time series curve, if the peak does not meet a first preset condition or a second preset condition, the peak is a single interference peak;
wherein the first preset condition is that the interval duration between the next trough of the peak and the previous trough of the peak is longer than the growth cycle;
the second preset condition is that the ratio of the front independent growth vigor corresponding to the peak to the annual variation of the normalized vegetation index corresponding to the peak is greater than or equal to a first preset threshold, and the ratio of the rear independent growth vigor corresponding to the peak to the annual variation of the normalized vegetation index corresponding to the peak is greater than or equal to the first preset threshold;
the front independent growth corresponding to the peak is the difference between the peak and the front trough of the peak;
the back independent growth corresponding to the peak is the difference between the peak and the next trough of the peak;
the annual variation of the normalized vegetation index corresponding to the peak is the difference between the maximum normalized vegetation index and the minimum normalized vegetation index in the year in which the peak is located.
Specifically, the step of performing conditional smoothing on the single interference peak in step S2 specifically includes:
and changing a curve between the trough before the single interference peak and the trough after the single interference peak into a straight line connecting the trough before the single interference peak and the trough after the single interference peak.
Specifically, the step S2 further includes:
and if the peak is a single interference peak, continuously judging whether the peak and the next peak of the peak form a double interference peak, performing conditional smoothing on the double interference peak twice, and combining the double interference peak into one peak.
Specifically, the step of determining whether the peak and a next peak of the peak form a dual interference peak specifically includes:
if the ratio between the front independent growth vigor corresponding to the peak and the annual change of the normalized vegetation index corresponding to the peak is smaller than the first preset threshold, the ratio between the rear independent growth vigor corresponding to the rear peak of the peak and the annual change of the normalized vegetation index corresponding to the rear peak of the peak is smaller than the first preset threshold, the ratio between the rear independent growth vigor corresponding to the peak and the annual change of the normalized vegetation index corresponding to the rear peak of the peak is larger than or equal to the second preset threshold, and the ratio between the front independent growth vigor corresponding to the rear peak of the peak and the annual change of the normalized vegetation index corresponding to the rear peak of the peak is larger than or equal to the second preset threshold, the rear peak of the peak and the peak of the peak are known to form a double interference peak.
Specifically, the step of performing conditional smoothing twice on the dual interference peaks and combining the dual interference peaks into one peak specifically includes:
performing conditional smoothing on a trough before the double interference peak and a trough between the double interference peaks;
and performing conditional smoothing on the trough between the last trough of the double interference peak and the trough between the double interference peaks.
According to a second aspect of the present invention, there is provided a multiple cropping index extraction device comprising:
the acquiring unit is used for acquiring a normalized vegetation index time series curve of the target area within a preset time length from the initial time according to the initial time of crop cultivation in the target area;
the optimization unit is used for acquiring wave crests in the normalized vegetation index time sequence curve by using a second-order difference method, and performing conditional smoothing on the single interference peak if each wave crest is a single interference peak;
and the extraction unit is used for obtaining the peak value in the normalized vegetation index time series curve after the condition smoothing by using the second-order difference method again, counting the total number of the peak values in the normalized vegetation index time series curve after the condition smoothing, and taking the total number of the peak values as the multiple seeding index of the target area.
The invention provides a multiple cropping index extraction method and a device, the method comprises the steps of obtaining a normalized vegetation index time sequence curve of a target area within a preset time period from the starting time according to the starting time of crop cultivation in the target area, obtaining peaks in the normalized vegetation index time sequence curve by using a second-order difference method, judging whether each peak is a single interference peak, performing conditional smoothing on the single interference peak, and extracting the total number of the peaks extracted from the smoothed normalized vegetation index time sequence curve to obtain the multiple cropping index of the target area, thereby improving the extraction accuracy of the multiple cropping index.
Drawings
Fig. 1 is a schematic overall flow chart of a multiple cropping index extraction method provided by an embodiment of the present invention;
fig. 2 is a schematic view of an overall structure of the multiple cropping index extraction device according to the embodiment of the present invention;
fig. 3 is a schematic view of an overall structure of the multiple cropping index extraction device according to the embodiment of the present invention.
Detailed Description
The following detailed description of embodiments of the present invention is provided in connection with the accompanying drawings and examples. The following examples are intended to illustrate the invention but are not intended to limit the scope of the invention.
In an embodiment of the present invention, a multiple cropping index extraction method is provided, and fig. 1 is a schematic overall flow chart of the multiple cropping index extraction method provided in the embodiment of the present invention, where the method includes: s1, acquiring a normalized vegetation index time series curve of the target area within a preset time length from the initial time according to the initial time of crop cultivation in the target area; s2, obtaining wave crests in the normalized vegetation index time sequence curve by using a second-order difference method, and if each wave crest is a single interference peak, performing conditional smoothing on the single interference peak; and S3, obtaining the peak value in the normalized vegetation index time series curve after condition smoothing by using the second-order difference method again, counting the total number of the peak values in the normalized vegetation index time series curve after condition smoothing, and taking the total number of the peak values as the multiple seeding index of the target area.
Specifically, in S1, the target region is a region in which a multiple cropping index needs to be obtained. The Normalized Difference Vegetation Index (NDVI) is the most direct remote sensing Index reflecting the growth state of crops, and is generally defined as the ratio of the Difference between the reflectivity of a near infrared band and a visible red band to the sum of the reflectivities of the two bands, i.e., the ratio
NDVI＝(ρNIR-ρRED)/(ρNIR+ρRED)；
Where NDVI represents the normalized vegetation index, ρ NIR is the reflectance of the near infrared band, and ρ RED is the reflectance of the RED band. If the normalized vegetation index of a crop is aligned with time on the abscissa, a normalized vegetation index time series curve for crop growth is formed, which reflects the process of crop from sowing, emergence, heading, maturity to harvesting in the most intuitive form. Considering the planting times of crops in the same region within a preset time length, the multiple cropping index of the target region is equal to the times of occurrence of the peak value in the normalized vegetation index time series curve within the preset time length. The normalized vegetation index time series curve is the normalized vegetation index time series curve of the target area within a preset time length from the initial cultivation time of the crops in the target area. The preset time period is generally one year.
For example, since the cultivation rules of crops in the south and north hemispheres are different, cultivation starting time has south and north difference, and the selection of the starting time is required in the process of extracting the multiple cropping index. Although the growth cycles of crops are greatly different from each other from south to north in the northern hemisphere, the cultivation starting time is approximately the same, the cultivation starting time of the crops is 2 months per year, and if the normalized vegetation index time series curve takes half a month as a wave band, the wave band corresponding to 2 months is a 4 th wave band; and the crop cultivation time of the southern hemisphere is mostly 7 months of each year, and the wave band corresponding to 7 months is the 14 th wave band. Therefore, during the extraction of the multiple cropping indexes, the south-north hemisphere attribute of the target area is judged according to the projection coordinate system of the target area. And if the target area is a northern hemisphere, acquiring a normalized vegetation index time series curve of the target area within 1 year from month 2. At different longitudes and latitudes, the growth cycles of crops are different due to the influence of weather factors such as precipitation, temperature and the like. In high latitude areas, the growth cycle of crops is more than 100 days; in the middle latitude area, the growth cycle of crops is 80-100 days; in low latitude areas, the growth cycle of crops is 60-80 days mostly.
And S2, the first order difference is the difference between two continuous adjacent terms in the discrete function, and the second order difference is the difference between the adjacent first order differences. According to the second-order difference idea, the peaks and the troughs in the normalized vegetation index time series curve are obtained. And judging whether the peak is a single interference peak or not for each acquired peak, namely judging whether the maturity time is a season crop or not. And simultaneously, according to whether the difference between the peak and the adjacent trough of the peak meets the condition. And taking the wave crest which does not meet the condition as a single interference peak, and performing conditional smoothing on the single interference peak, thereby optimizing the normalized vegetation index time sequence curve and enabling the extracted multiple index to be more accurate. In S3, the second order difference method is used again to obtain the peak in the normalized vegetation index time series curve after conditional smoothing, and the total number of peaks in the normalized vegetation index time series curve after conditional smoothing is counted, and the total number of peaks is used as the multiple seeding index of the target area. Each normalized vegetation index time series curve corresponds to a multiple planting index, and each pixel in the remote sensing image of the target area corresponds to a normalized vegetation index time series curve, so that a two-dimensional array is finally output. For convenience of identification, the output result is displayed as three default colors, for example, the multiple index is 1, and blue is displayed; the multiple cropping index is 2, and green is displayed; the multiple cropping index was 3, showing red. If there is a multiple index of 4 or more, yellow is displayed and the background value is black.
In the embodiment, the normalized vegetation index time series curve of the target area within the preset time duration from the starting time is obtained according to the starting time of crop cultivation in the target area, the peaks in the normalized vegetation index time series curve are obtained by using a second-order difference method, whether each peak is a single interference peak is judged, the single interference peak is subjected to conditional smoothing, the total number of the peaks extracted from the smoothed normalized vegetation index time series curve is used as the multiple cropping index of the target area, and therefore the extraction accuracy of the multiple cropping index is improved.
On the basis of the foregoing embodiments, in this embodiment, before the step S1, the method further includes: according to the coordinates of the target area, acquiring a preset coordinate range to which the coordinates belong and the crop cultivation starting time and the crop growth period corresponding to the preset coordinate range; and the preset coordinate range is pre-associated with the starting time for storage, and the preset coordinate range is pre-associated with the growth cycle for storage.
Specifically, the coordinates of the target area are the longitude and latitude of the target area. And acquiring the preset coordinate range of the coordinates. Each preset coordinate range corresponds to the starting time of crop cultivation and the growth period of crops. And the preset coordinate range is pre-associated with the starting time for storage, and the preset coordinate range is pre-associated with the growth cycle for storage.
On the basis of the foregoing embodiments, in this embodiment, before the step S1, the method further includes: acquiring a normalized vegetation index time series curve of a target area for at least two years; wherein the normalized vegetation index time series curve has a band of less than or equal to half a month; smoothing the normalized vegetation index time series curve by using an SG filtering algorithm; wherein, the half wave width of the SG filtering algorithm is less than or equal to one half of the total number of wave bands in the normalized vegetation index time series curve; correspondingly, the step S1 specifically includes: and according to the starting time of crop cultivation in the target area, selecting the normalized vegetation index time series curve of the target area within a preset time length from the starting time from the smoothed normalized vegetation index time series curve.
Specifically, the tie linking the multiple cropping index to the normalized vegetation index time series curve is a cyclic law within a preset time period of the crop. The normalized vegetation index time series curve implies the climate change of the cultivated land crops, the multiple cropping index reflects the cultivated land utilization degree of the time series, and the climate change of the cultivated land crops is influenced by the change of the cultivated land utilization degree. For example, if a quarter crop is planted in a field a year, the normalized vegetation index time series curve exhibits a climatic cycle for the quarter crop, and if a quarter crop is planted in a field a year, the normalized vegetation index time series curve exhibits a climatic cycle for the quarter crop.
Since the multiple cropping index generally refers to the utilization degree of the cultivated land within one year, and the starting time of the cultivated land is generally not early years, the normalized vegetation index time series curve of the target area for at least two years needs to be acquired. The normalized vegetation index time series curve is a normalized vegetation index time series curve of the initially acquired target area. The normalized vegetation index time series curve takes less than or equal to half a month as a waveband, and generally takes half a month as a waveband. The two-year normalized vegetation index time series curve has 48 bands. In order to meet the requirement of SG (Savitzky-Golay) filtering, the total number of wave bands in the normalized vegetation index time series curve can be only odd, the first wave band or the last wave band can be removed, and a null wave band can be added in front of or behind the normalized vegetation index time series curve.
And when the SG filtering algorithm is used for smoothing the normalized vegetation index time series curve, setting the half-wave width and polynomial times of SG filtering. The half-wave width and the polynomial degree can be adjusted as required, for example, the default value of the half-wave width is set to 6, and the default value of the polynomial degree is set to 5. In order to improve the accuracy, the half-wave width and the polynomial degree may be appropriately increased, but the amount of calculation increases and the calculation time is prolonged. The half-wave width is less than or equal to one-half of the total number of wave bands in the normalized vegetation index time series curve. And selecting a normalized vegetation index time series curve within a preset time length from the starting time from the smoothed normalized vegetation index time series curve.
In the embodiment, the normalized vegetation index time series curve of the target area for at least two years is obtained in advance, the SG algorithm is used for smoothing the normalized vegetation index time series curve, and the normalized vegetation index time series curve within the preset time duration from the crop cultivation starting time is selected from the smoothed normalized vegetation index time series curve, so that the multiple planting index extracted from the selected normalized vegetation index time series curve is more accurate.
On the basis of the foregoing embodiments, the calculation formula for obtaining the peak in the normalized vegetation index time series curve in step S2 by using the second-order difference method is as follows:
di 1＝NDVIi-NDVIi-1；
if d isi 1>0，di 2＝1；
If d isi 1<0，di 2＝-1；
di 3＝di 2-di-1 2；
Wherein NDVIiIs the normalized vegetation index, NDVI, at the ith moment in any normalized vegetation index time series curvei-1Is the normalized vegetation index at a time immediately preceding the i-th time, di 1Is the first order difference at time i, di 2Is an intermediate attribute at time i, di-1 2Intermediate attribute of the time immediately preceding the i-th time, di 3Is the second order difference at the ith moment; if d isi 3And (2) obtaining the normalized vegetation index at the ith moment as a peak.
Specifically, before determining whether each peak is a single interference peak, the position of each peak needs to be acquired. In this embodiment, the peak and the trough in the normalized vegetation index time series curve are obtained by a second order difference method. Taking the difference of the normalized vegetation indexes at adjacent moments as a first-order difference di 1. If the first order difference is greater than 0, assigning 1 to the intermediate attribute di 2(ii) a If the first order difference is less than 0, assigning-1 to the intermediate attribute di 2. Neighboring intermediate attribute di 2Is taken as the second order difference di 3。di 3The calculation result of (c) is-2, 2 or 0. If d isi 3If the normalized vegetation index at the ith moment is a peak, the normalized vegetation index is obtained as-2; if d isi 3And 2, the normalized vegetation index at the ith moment is known as the trough.
On the basis of the foregoing embodiments, the step of determining whether each peak is a single interference peak in step S2 in this embodiment specifically includes: for each peak in the normalized vegetation index time series curve, if the peak does not meet a first preset condition or a second preset condition, the peak is a single interference peak; wherein the first preset condition is that the interval duration between the next trough of the peak and the previous trough of the peak is longer than the growth cycle; the second preset condition is that the ratio of the front independent growth vigor corresponding to the peak to the annual variation of the normalized vegetation index corresponding to the peak is greater than or equal to a first preset threshold, and the ratio of the rear independent growth vigor corresponding to the peak to the annual variation of the normalized vegetation index corresponding to the peak is greater than or equal to the first preset threshold; the front independent growth corresponding to the peak is the difference between the peak and the front trough of the peak; the back independent growth corresponding to the peak is the difference between the peak and the next trough of the peak; the annual variation of the normalized vegetation index corresponding to the peak is the difference between the maximum normalized vegetation index and the minimum normalized vegetation index in the year in which the peak is located.
Specifically, when judging whether each peak in each normalized vegetation index time series curve is a single interference seal, calculating an interval duration between a next trough of each peak and a previous trough of each peak. The first preset condition is that the interval duration is longer than the growth cycle of the crops in the target area, and the curve between the two troughs is a normalized vegetation index time series curve of the crops in one season. Definition PaIs the normalized vegetation index annual variation of the year a in which each peak is located. GfFor the front independent growth of each peak, GbIs the independent growth of each peak. The second preset condition is Gf/Pa≥0.5，Gb/PaAnd the growth vigor of the crops represented by the wave crest is more obvious. And if each peak does not meet one of the first preset condition and the second preset condition, each peak is known to be a single interference peak. The single interference peak is subjected to conditional smoothing, and the embodiment is not limited to the conditional smoothing method.
On the basis of the foregoing embodiments, in this embodiment, the step of performing conditional smoothing on the single interference peak in step S2 specifically includes: and changing a curve between the trough before the single interference peak and the trough after the single interference peak into a straight line connecting the trough before the single interference peak and the trough after the single interference peak.
Specifically, the formula of conditional smoothing is:
NDVIx＝NDVIm+[(NDVIn-NDVIm)*(x-m)]/(n-m)；
wherein m is the time corresponding to the previous trough of the single interference peak, n is the time corresponding to the next trough of each single interference peak, and x is the range [ m, n [ ]]Time of day, NDVImNDVI as the preceding trough of each single interference peaknFor the next trough of each single interference peak, NDVIxIs the normalized vegetation index at time x. Thereby changing the curve between the trough before the single interference peak and the trough after the single interference peak into a straight line connecting the trough before the single interference peak and the trough after the single interference peak.
On the basis of the foregoing embodiment, step S2 in this embodiment further includes: and if the peak is a single interference peak, continuously judging whether the peak and the next peak of the peak form a double interference peak, performing conditional smoothing on the double interference peak twice, and combining the double interference peak into one peak.
Specifically, for nested farming type crops, the judgment of the double interference peak is performed. Namely, if each peak is judged to be a single interference peak, whether each peak and the next peak of each peak form a double interference peak is continuously judged. And smoothing the double interference peaks through a condition, and combining two peaks in the double interference peaks into one peak.
On the basis of the above embodiment, the step of determining whether the peak and a peak subsequent to the peak form a dual interference peak in this embodiment specifically includes: if the ratio between the front independent growth vigor corresponding to the peak and the annual change of the normalized vegetation index corresponding to the peak is smaller than the first preset threshold, the ratio between the rear independent growth vigor corresponding to the rear peak of the peak and the annual change of the normalized vegetation index corresponding to the rear peak of the peak is smaller than the first preset threshold, the ratio between the rear independent growth vigor corresponding to the peak and the annual change of the normalized vegetation index corresponding to the rear peak of the peak is larger than or equal to the second preset threshold, and the ratio between the front independent growth vigor corresponding to the rear peak of the peak and the annual change of the normalized vegetation index corresponding to the rear peak of the peak is larger than or equal to the second preset threshold, the rear peak of the peak and the peak of the peak are known to form a double interference peak.
Specifically, if the peak satisfies Gf/Pa< 0.5, and Gb/PaNot less than 0.2, and the next peak of the peak satisfies Gb/Pa< 0.5, and Gf/PaAnd if the peak value is more than or equal to 0.2, the peak value and the next peak value of the peak value form a double interference peak.
On the basis of the above embodiment, the step of performing conditional smoothing twice on the dual interference peaks in this embodiment, and combining the dual interference peaks into one peak specifically includes: performing conditional smoothing on a trough before the double interference peak and a trough between the double interference peaks; and performing conditional smoothing on the trough between the last trough of the double interference peak and the trough between the double interference peaks.
Specifically, a curve between a trough before the dual interference peak and a trough between the dual interference peaks is changed into a straight line connecting the trough before the dual interference peak and the trough between the dual interference peaks. And changing a curve between the next trough of the double interference peak and the trough between the double interference peaks into a straight line connecting the next trough of the double interference peak and the trough between the double interference peaks. Thereby combining two peaks of the dual interference peak into one peak.
In another embodiment of the present invention, a multiple cropping index extraction device is provided, and fig. 2 is a schematic diagram of an overall structure of the multiple cropping index extraction device provided in the embodiment of the present invention, and the device includes an obtaining unit 1, an optimizing unit 2, and an extracting unit 3, where:
the acquisition unit 1 is used for acquiring a normalized vegetation index time series curve of a target area within a preset time length from an initial time according to the initial time of crop cultivation in the target area; the optimization unit 2 is configured to obtain peaks in the normalized vegetation index time series curve by using a second order difference method, and perform conditional smoothing on a single interference peak if each peak is the single interference peak; the extraction unit 3 is configured to obtain the peak value in the normalized vegetation index time series curve after conditional smoothing by using the second order difference method again, count the total number of peak values in the normalized vegetation index time series curve after conditional smoothing, and use the total number of peak values as the multiple cropping index of the target area.
Specifically, the target region is a region in which a multiple cropping index needs to be acquired. Since the starting time of crop cultivation in different areas is different, the obtaining unit 1 needs to obtain the normalized vegetation index time series curve of the target area within a preset time period from the starting time according to the starting time of crop cultivation in the target area. The normalized vegetation index is the most direct remote sensing index reflecting the growth state of crops, and is generally defined as the ratio of the difference between the reflectivity of the near infrared band and the visible red band to the sum of the reflectivities of the two bands. If the normalized vegetation index of a crop is aligned with time on the abscissa, a normalized vegetation index time series curve for crop growth is formed, which reflects the process of crop from sowing, emergence, heading, maturity to harvesting in the most intuitive form. Considering the planting times of crops in the same region within a preset time length, the multiple cropping index of the target region is equal to the times of occurrence of the peak value in the normalized vegetation index time series curve within the preset time length. The normalized vegetation index time series curve is the normalized vegetation index time series curve of the target area within a preset time length from the initial cultivation time of the crops in the target area. The preset time period is generally one year.
The first order difference is the difference between two consecutive adjacent terms in the discrete function, and the second order difference is the difference between two adjacent first order differences. And the optimization unit 2 acquires the wave crest and the wave trough in the normalized vegetation index time series curve according to the idea of second-order difference. And judging whether the peak is a single interference peak or not for each acquired peak, namely judging whether the maturity time is a season crop or not. And simultaneously, according to whether the difference between the peak and the adjacent trough of the peak meets the condition. And taking the wave crest which does not meet the condition as a single interference peak, and performing conditional smoothing on the single interference peak, thereby optimizing the normalized vegetation index time sequence curve and enabling the extracted multiple index to be more accurate.
The extraction unit 3 obtains the peak value in the normalized vegetation index time series curve after the condition smoothing by using the second order difference method again, counts the total number of the peak values in the normalized vegetation index time series curve after the condition smoothing, and takes the total number of the peak values as the multiple seeding index of the target area. Each normalized vegetation index time series curve corresponds to a multiple planting index, and each pixel in the remote sensing image of the target area corresponds to a normalized vegetation index time series curve, so that a two-dimensional array is finally output. For convenience of identification, the output result is displayed as three default colors, for example, the multiple index is 1, and blue is displayed; the multiple cropping index is 2, and green is displayed; the multiple cropping index was 3, showing red. If there is a multiple index of 4 or more, yellow is displayed and the background value is black.
In the embodiment, the normalized vegetation index time series curve of the target area within the preset time duration from the starting time is obtained according to the starting time of crop cultivation in the target area, the peaks in the normalized vegetation index time series curve are obtained by using a second-order difference method, whether each peak is a single interference peak is judged, the single interference peak is subjected to conditional smoothing, the total number of the peaks extracted from the smoothed normalized vegetation index time series curve is used as the multiple cropping index of the target area, and therefore the extraction accuracy of the multiple cropping index is improved.
On the basis of the foregoing embodiment, in this embodiment, the obtaining unit is further configured to: according to the coordinates of the target area, acquiring a preset coordinate range to which the coordinates belong and the crop cultivation starting time and the crop growth period corresponding to the preset coordinate range; and the preset coordinate range is pre-associated with the starting time for storage, and the preset coordinate range is pre-associated with the growth cycle for storage.
On the basis of the foregoing embodiment, in this embodiment, the optimization unit is further configured to: acquiring a normalized vegetation index time series curve of a target area for at least two years; wherein the normalized vegetation index time series curve has a band of less than or equal to half a month; smoothing the normalized vegetation index time series curve by using an SG filtering algorithm; wherein, the half wave width of the SG filtering algorithm is less than or equal to one half of the total number of wave bands in the normalized vegetation index time series curve; correspondingly, the obtaining unit is specifically configured to: and according to the starting time of crop cultivation in the target area, selecting the normalized vegetation index time series curve of the target area within a preset time length from the starting time from the smoothed normalized vegetation index time series curve.
On the basis of the foregoing embodiments, in this embodiment, the calculation formula of the optimization unit using a second order difference method to obtain the peak in the normalized vegetation index time series curve is as follows:
di 1＝NDVIi-NDVIi-1；
if d isi 1>0，di 2＝1；
If d isi 1<0，di 2＝-1；
di 3＝di 2-di-1 2；
Wherein NDVIiIs the normalized vegetation index, NDVI, at the ith moment in any normalized vegetation index time series curvei-1Is the normalized vegetation index at a time immediately preceding the i-th time, di 1Is the first order difference at time i, di 2Is an intermediate attribute at time i, di-1 2Intermediate attribute of the time immediately preceding the i-th time, di 3Is the second order difference at the ith moment; if d isi 3And (2) obtaining the normalized vegetation index at the ith moment as a peak.
On the basis of the foregoing embodiments, in this embodiment, the optimization unit is specifically configured to: for each peak in the normalized vegetation index time series curve, if the peak does not meet a first preset condition or a second preset condition, the peak is a single interference peak; wherein the first preset condition is that the interval duration between the next trough of the peak and the previous trough of the peak is longer than the growth cycle; the second preset condition is that the ratio of the front independent growth vigor corresponding to the peak to the annual variation of the normalized vegetation index corresponding to the peak is greater than or equal to a first preset threshold, and the ratio of the rear independent growth vigor corresponding to the peak to the annual variation of the normalized vegetation index corresponding to the peak is greater than or equal to the first preset threshold; the front independent growth corresponding to the peak is the difference between the peak and the front trough of the peak; the back independent growth corresponding to the peak is the difference between the peak and the next trough of the peak; the annual variation of the normalized vegetation index corresponding to the peak is the difference between the maximum normalized vegetation index and the minimum normalized vegetation index in the year in which the peak is located.
On the basis of the foregoing embodiments, in this embodiment, the optimization unit is specifically configured to: and changing a curve between the trough before the single interference peak and the trough after the single interference peak into a straight line connecting the trough before the single interference peak and the trough after the single interference peak.
On the basis of the foregoing embodiment, in this embodiment, the optimization unit is further configured to: and if the peak is a single interference peak, continuously judging whether the peak and the next peak of the peak form a double interference peak, performing conditional smoothing on the double interference peak twice, and combining the double interference peak into one peak.
On the basis of the foregoing embodiment, the optimization unit in this embodiment is further specifically configured to: if the ratio between the front independent growth vigor corresponding to the peak and the annual change of the normalized vegetation index corresponding to the peak is smaller than the first preset threshold, the ratio between the rear independent growth vigor corresponding to the rear peak of the peak and the annual change of the normalized vegetation index corresponding to the rear peak of the peak is smaller than the first preset threshold, the ratio between the rear independent growth vigor corresponding to the peak and the annual change of the normalized vegetation index corresponding to the rear peak of the peak is larger than or equal to the second preset threshold, and the ratio between the front independent growth vigor corresponding to the rear peak of the peak and the annual change of the normalized vegetation index corresponding to the rear peak of the peak is larger than or equal to the second preset threshold, the rear peak of the peak and the peak of the peak are known to form a double interference peak.
On the basis of the foregoing embodiment, the optimization unit in this embodiment is further specifically configured to: performing conditional smoothing on a trough before the double interference peak and a trough between the double interference peaks; and performing conditional smoothing on the trough between the last trough of the double interference peak and the trough between the double interference peaks.
The present embodiment provides a multiple cropping index extraction device, and fig. 3 is a schematic diagram of an overall structure of the multiple cropping index extraction device provided in the embodiment of the present invention, where the device includes: at least one processor 31, at least one memory 32, and a bus 33; wherein,
the processor 31 and the memory 32 complete mutual communication through the bus 33;
the memory 32 stores program instructions executable by the processor 31, and the processor calls the program instructions to execute the methods provided by the method embodiments, for example, the method includes: s1, acquiring a normalized vegetation index time series curve of the target area within a preset time length from the initial time according to the initial time of crop cultivation in the target area; s2, obtaining wave crests in the normalized vegetation index time sequence curve by using a second-order difference method, and if each wave crest is a single interference peak, performing conditional smoothing on the single interference peak; and S3, obtaining the peak value in the normalized vegetation index time series curve after condition smoothing by using the second-order difference method again, counting the total number of the peak values in the normalized vegetation index time series curve after condition smoothing, and taking the total number of the peak values as the multiple seeding index of the target area.
The present embodiments provide a non-transitory computer-readable storage medium storing computer instructions that cause the computer to perform the methods provided by the above method embodiments, for example, including: s1, acquiring a normalized vegetation index time series curve of the target area within a preset time length from the initial time according to the initial time of crop cultivation in the target area; s2, obtaining wave crests in the normalized vegetation index time sequence curve by using a second-order difference method, and if each wave crest is a single interference peak, performing conditional smoothing on the single interference peak; and S3, obtaining the peak value in the normalized vegetation index time series curve after condition smoothing by using the second-order difference method again, counting the total number of the peak values in the normalized vegetation index time series curve after condition smoothing, and taking the total number of the peak values as the multiple seeding index of the target area.
Those of ordinary skill in the art will understand that: all or part of the steps for implementing the method embodiments may be implemented by hardware related to program instructions, and the program may be stored in a computer readable storage medium, and when executed, the program performs the steps including the method embodiments; and the aforementioned storage medium includes: various media that can store program codes, such as ROM, RAM, magnetic or optical disks.
The above-described embodiments of the multiple index extraction device are merely illustrative, where the units illustrated as separate components may or may not be physically separate, and the components displayed as units may or may not be physical units, may be located in one place, or may be distributed on multiple 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, the method of the present application is only a preferred embodiment and is not intended to limit the scope of the present invention. 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 multiple cropping index extraction method is characterized by comprising the following steps:
s1, acquiring a normalized vegetation index time series curve of the target area within a preset time length from the initial time according to the initial time of crop cultivation in the target area;
s2, obtaining wave crests in the normalized vegetation index time sequence curve by using a second-order difference method, and if each wave crest is a single interference peak, performing conditional smoothing on the single interference peak;
and S3, obtaining the peak value in the normalized vegetation index time series curve after condition smoothing by using the second-order difference method again, counting the total number of the peak values in the normalized vegetation index time series curve after condition smoothing, and taking the total number of the peak values as the multiple seeding index of the target area.
2. The method according to claim 1, wherein the step S1 is preceded by:
according to the coordinates of the target area, acquiring a preset coordinate range to which the coordinates belong and the crop cultivation starting time and the crop growth period corresponding to the preset coordinate range; and the preset coordinate range is pre-associated with the starting time for storage, and the preset coordinate range is pre-associated with the growth cycle for storage.
3. The method according to claim 1, wherein the step S1 is preceded by:
acquiring a normalized vegetation index time series curve of a target area for at least two years; wherein the normalized vegetation index time series curve has a band of less than or equal to half a month;
smoothing the normalized vegetation index time series curve by using an SG filtering algorithm; wherein, the half wave width of the SG filtering algorithm is less than or equal to one half of the total number of wave bands in the normalized vegetation index time series curve;
correspondingly, the step S1 specifically includes:
and according to the starting time of crop cultivation in the target area, selecting a normalized vegetation index time series curve within a preset time length from the starting time from the smoothed normalized vegetation index time series curve.
4. The method according to any one of claims 1 to 3, wherein the step S2 of obtaining the peak in the normalized vegetation index time series curve by using a second order difference method is represented by the following formula:
di 1＝NDVIi-NDVIi-1；
if d isi 1>0，di 2＝1；
If d isi 1<0，di 2＝-1；
di 3＝di 2-di-1 2；
Wherein NDVIiIs the normalized vegetation index, NDVI, at the ith moment in any normalized vegetation index time series curvei-1Is the normalized vegetation index at a time immediately preceding the i-th time, di 1Is the first order difference at time i, di 2Is an intermediate attribute at time i, di-1 2Intermediate attribute of the time immediately preceding the i-th time, di 3Is the second order difference at the ith moment;
if d isi 3If the normalized vegetation index at the ith moment is a peak, the normalized vegetation index is obtained as-2;
if d isi 3And 2, the normalized vegetation index at the ith moment is known as the trough.
5. The method according to any one of claims 1 to 3, wherein the step of determining whether each peak is a single interference peak in the step S2 specifically includes:
for each peak in the normalized vegetation index time series curve, if the peak does not meet a first preset condition or a second preset condition, the peak is a single interference peak;
wherein the first preset condition is that the interval duration between the next trough of the peak and the previous trough of the peak is longer than the growth cycle;
the second preset condition is that the ratio of the front independent growth vigor corresponding to the peak to the annual variation of the normalized vegetation index corresponding to the peak is greater than or equal to a first preset threshold, and the ratio of the rear independent growth vigor corresponding to the peak to the annual variation of the normalized vegetation index corresponding to the peak is greater than or equal to the first preset threshold;
the front independent growth corresponding to the peak is the difference between the peak and the front trough of the peak;
the back independent growth corresponding to the peak is the difference between the peak and the next trough of the peak;
the annual variation of the normalized vegetation index corresponding to the peak is the difference between the maximum normalized vegetation index and the minimum normalized vegetation index in the year in which the peak is located.
6. The method according to any one of claims 1 to 3, wherein the step of conditionally smoothing the single interference peak in step S2 specifically comprises:
and changing a curve between the trough before the single interference peak and the trough after the single interference peak into a straight line connecting the trough before the single interference peak and the trough after the single interference peak.
7. The method according to claim 5, wherein the step S2 further comprises:
and if the peak is a single interference peak, continuously judging whether the peak and the next peak of the peak form a double interference peak, performing conditional smoothing on the double interference peak twice, and combining the double interference peak into one peak.
8. The method of claim 7, wherein the step of determining whether the peak and a next peak of the peak form a dual interference peak specifically comprises:
if the ratio between the front independent growth vigor corresponding to the peak and the annual change of the normalized vegetation index corresponding to the peak is smaller than the first preset threshold, the ratio between the rear independent growth vigor corresponding to the rear peak of the peak and the annual change of the normalized vegetation index corresponding to the rear peak of the peak is smaller than the first preset threshold, the ratio between the rear independent growth vigor corresponding to the peak and the annual change of the normalized vegetation index corresponding to the rear peak of the peak is larger than or equal to the second preset threshold, and the ratio between the front independent growth vigor corresponding to the rear peak of the peak and the annual change of the normalized vegetation index corresponding to the rear peak of the peak is larger than or equal to the second preset threshold, the rear peak of the peak and the peak of the peak are known to form a double interference peak.
9. The method according to claim 7, wherein the step of performing two conditional smootheings on the dual interference peaks and combining the dual interference peaks into one peak specifically comprises:
performing conditional smoothing on a trough before the double interference peak and a trough between the double interference peaks;
and performing conditional smoothing on the trough between the last trough of the double interference peak and the trough between the double interference peaks.
10. A multiple cropping index extraction device is characterized by comprising:
the acquiring unit is used for acquiring a normalized vegetation index time series curve of the target area within a preset time length from the initial time according to the initial time of crop cultivation in the target area;
the optimization unit is used for acquiring wave crests in the normalized vegetation index time sequence curve by using a second-order difference method, and performing conditional smoothing on the single interference peak if each wave crest is a single interference peak;
and the extraction unit is used for obtaining the peak value in the normalized vegetation index time series curve after the condition smoothing by using the second-order difference method again, counting the total number of the peak values in the normalized vegetation index time series curve after the condition smoothing, and taking the total number of the peak values as the multiple seeding index of the target area.
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