CN112581464B - Crop growth condition analysis method, device and storage medium - Google Patents
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Abstract
The invention relates to a crop growth condition analysis method, which comprises the following steps: setting an analysis area according to the field range to be detected, and dividing a target area corresponding to the field to be detected and a comparison area corresponding to the comparison field in the analysis area; acquiring satellite remote sensing images of analysis areas when crops in a field to be detected are in different growth stages; calculating a normalized vegetation index map corresponding to each growth stage according to each satellite remote sensing image; cutting the normalized vegetation index map according to the target area and the comparison area respectively to obtain a target vegetation index map corresponding to the field to be detected and a comparison vegetation index map corresponding to the comparison field; and obtaining crop growth condition analysis results according to the target vegetation index diagrams of different growth stages and the comparison vegetation index diagrams of different growth stages. The invention can objectively, accurately and rapidly analyze the crop growth vigor.
Description
Technical Field
The invention relates to the technical field of crop growth situation analysis, in particular to a crop growth situation analysis method, a crop growth situation analysis device and a storage medium.
Background
The growth vigor of crops, namely the growth condition and trend of the crops, can provide efficient and comprehensive information for field management and crop yield improvement, and has very important significance. The growth condition and trend of the crops can be evaluated by adopting growth parameters such as normalized vegetation index, crop moisture and the like, and the parameters directly affect the growth development and quality of the crops, are important indexes for monitoring the growth condition of the crops, are important data sources for evaluating the growth condition of the crops, and are also important basis for accurately managing and regulating the production of the crops. The crop growth parameters are obtained in real time, so that farmers can know the growth conditions of crops, and make corresponding fertilization, pesticide spraying and irrigation plans, thereby ensuring healthy growth of the crops.
Under the influence of the traditional fertilization mode, the fertilizer formula applied by the same village and town is always the same, the additional fertilizer and the frequency are the same, and different farmer fields seed the same crop, and the harvest has certain difference. Through the comparative analysis of the peasant household field and the peripheral growth potential data, the area with long potential difference and the degree of the growth potential difference can be seen, and the area with long potential difference can be topdressed and the fertilizer consumption can be mastered in a targeted manner, so that the crop yield is improved. However, for analysis of crop growth conditions, a manual mode is still adopted at present, so that the analysis efficiency is low, the analysis accuracy is low, and the objectivity is poor.
Disclosure of Invention
In view of the foregoing, it is necessary to provide a method, an apparatus and a recording medium for analyzing the growth situation of crops, which are used for solving the problems of low efficiency, low precision and poor objectivity of the analysis of the growth situation of crops.
The invention provides a crop growth condition analysis method, which comprises the following steps:
setting an analysis area according to the field range to be detected, and dividing a target area corresponding to the field to be detected and a comparison area corresponding to the comparison field in the analysis area;
acquiring satellite remote sensing images of analysis areas when crops in a field to be detected are in different growth stages;
calculating a normalized vegetation index map corresponding to each growth stage according to each satellite remote sensing image;
cutting the normalized vegetation index map according to the target area and the comparison area respectively to obtain a target vegetation index map corresponding to the field to be detected and a comparison vegetation index map corresponding to the comparison field;
and obtaining crop growth condition analysis results according to the target vegetation index diagrams of different growth stages and the comparison vegetation index diagrams of different growth stages.
Further, an analysis area is set according to the field range to be measured, specifically:
and drawing a field block graph according to the field block to be tested, generating an outsourcing rectangle of the field block graph, and expanding the outsourcing rectangle to obtain the analysis area.
Further, dividing a target area corresponding to the field to be detected and a comparison area corresponding to the comparison field in the analysis area;
setting a range corresponding to the Tian Kuaitu shape in the analysis region as a target region;
and translating the field image to different directions to obtain a plurality of contrast areas corresponding to the contrast fields.
Further, calculating a normalized vegetation index map according to the satellite remote sensing image, specifically:
calculating normalized vegetation indexes corresponding to each pixel of the satellite remote sensing image;
and combining the normalized vegetation indexes corresponding to the pixels of the satellite remote sensing image to generate the normalized vegetation index map.
Further, calculating a normalized vegetation index corresponding to each pixel of the satellite remote sensing image, specifically:
NDVI＝(NIR-RED)/(NIR+RED)；
wherein, NDVI represents normalized vegetation index, NIR is near infrared band emissivity, RED is RED band emissivity.
Further, according to the target vegetation index diagrams of different growth stages and the comparison vegetation index diagrams of different growth stages, the crop growth condition analysis result is obtained, including:
setting a mapping relation table of vegetation indexes and growth levels;
dividing the growth vigor level of the field to be measured according to the mapping relation table and the target vegetation index graph to obtain a growth vigor grading result of the field to be measured;
dividing the growth vigor level of each comparison field according to the mapping relation table and the comparison vegetation index graph to obtain a growth vigor grading result of each comparison field;
and comparing the growth classification result of the field to be tested with the growth classification result of each comparison field to obtain a crop growth analysis result.
Further, based on the comparison of the growth classification result of the field to be measured and the growth classification result of each comparison field, a crop growth analysis result is obtained, which comprises:
comparing the growth classification results of the field to be tested in different growth stages to obtain crop growth analysis results in the time dimension;
and comparing the growth classification results of different fields in the same growth stage to obtain a crop growth analysis result in the space dimension.
Further, the method further comprises the following steps:
and generating a fertilization and irrigation scheme of the field to be tested according to the crop growth analysis result.
The invention also provides a crop growth situation analysis device, which comprises a processor and a memory, wherein the memory is stored with a computer program, and the crop growth situation analysis method is realized when the computer program is executed by the processor.
The present invention also provides a computer storage medium having stored thereon a computer program which, when executed by a processor, implements the crop growth situation analysis method.
The beneficial effects are that: the embodiment firstly sets an analysis area, and sets a target area and a comparison area in the analysis area, so that crop growth conditions in the space dimension are conveniently analyzed and compared; then, satellite remote sensing images of the analysis areas when the crops are in different growth stages are acquired, so that crop growth vigor analysis and comparison in a time dimension are facilitated; calculating a normalized vegetation index diagram according to the satellite remote sensing image, and describing crop growth analysis conditions through the normalized vegetation index; and finally, obtaining crop growth analysis results for target vegetation index diagrams in different growth stages and comparison vegetation index diagrams in different growth stages, and realizing crop growth analysis in space dimension and time dimension. The crop growth situation analysis method provided by the invention can rapidly, accurately and objectively evaluate the crop growth situation, and simultaneously compare the crop growth situation from different dimensions to obtain a multi-dimensional comparison analysis result.
Drawings
FIG. 1 is a flow chart of a method of a first embodiment of a crop growth condition analysis method provided by the invention;
FIG. 2 is a graph showing the comparison of crop growth situation grading duty ratios according to a first embodiment of the crop growth situation analysis method provided by the invention;
fig. 3 is a plot of crop growth curves according to a first embodiment of the method for analyzing crop growth conditions provided by the present invention.
Detailed Description
Preferred embodiments of the present invention will now be described in detail with reference to the accompanying drawings, which form a part hereof, and together with the description serve to explain the principles of the invention, and are not intended to limit the scope of the invention.
Example 1
As shown in fig. 1, embodiment 1 of the present invention provides a crop growth condition analysis method, comprising the steps of:
s1, setting an analysis area according to the field range to be detected, and dividing a target area corresponding to the field to be detected and a comparison area corresponding to the comparison field in the analysis area;
s2, acquiring satellite remote sensing images of analysis areas when crops in the field to be detected are in different growth stages;
s3, calculating a normalized vegetation index map corresponding to each growth stage according to each satellite remote sensing image;
s4, cutting the normalized vegetation index map according to the target area and the comparison area respectively to obtain a target vegetation index map corresponding to the field to be detected and a comparison vegetation index map corresponding to the comparison field;
s5, obtaining crop growth condition analysis results according to the target vegetation index diagrams of different growth stages and the comparison vegetation index diagrams of different growth stages.
The method comprises the steps that firstly, an analysis area is set, the analysis area comprises a target area corresponding to a field to be detected and a comparison area corresponding to a comparison field, and meanwhile, the target area and the comparison area are set, so that crop growth conditions in space dimension are conveniently analyzed and compared; then, satellite remote sensing images of the analysis areas when the crops are in different growth stages are acquired, so that crop growth vigor analysis and comparison in a time dimension are facilitated; calculating a normalized vegetation index diagram according to the satellite remote sensing image, and describing crop growth analysis conditions through the normalized vegetation index; and finally, obtaining crop growth analysis results for target vegetation index diagrams in different growth stages and comparison vegetation index diagrams in different growth stages, and realizing crop growth analysis in space dimension and time dimension. The crop growth situation analysis method provided by the invention can rapidly, accurately and objectively evaluate the crop growth situation, and simultaneously compare the crop growth situation from different dimensions to obtain a multi-dimensional comparison analysis result. Based on the crop growth analysis result, reasonable fertilization and irrigation schemes can be calculated, so that crop yield is improved, crop abnormality or health problems are found early, and monitoring and insight level of a farm are enhanced; meanwhile, the change of plant growth vigor and the distribution situation of different growth vigors are identified and monitored, and differentiated management is carried out; the effect of measures such as fertilization, irrigation, pesticide spraying and the like on the health of crops is monitored for specific tasks.
Preferably, the analysis area is set according to the field range to be measured, specifically:
and drawing a field block graph according to the field block to be tested, generating an outsourcing rectangle of the field block graph, and expanding the outsourcing rectangle to obtain the analysis area.
According to the field range to be measured, a field graph F1 is drawn, an outsourcing rectangle R corresponding to the F1 is generated, the height H and the width W of the rectangle R are calculated, in the embodiment, the height direction is defined as the north-south direction, and the width direction is defined as the east-west direction, so that the distance H is outwards expanded in the south direction and the north direction, the distance W is outwards expanded in the east direction and the west direction, and a new rectangle region R1, namely an analysis region, is formed. The purpose of expanding the outsourcing rectangle is to analyze the area, namely the field to be detected and the contrast field around the field to be detected, so that the field to be detected and the contrast field can be conveniently compared. The length and width of the outer rectangle are respectively enlarged to three times in the embodiment, and it should be understood that the expansion multiple can be other multiple, and the embodiment is described by taking three times as an example.
Preferably, a target area corresponding to the field to be detected and a comparison area corresponding to the comparison field are divided in the analysis area;
setting a range corresponding to the Tian Kuaitu shape in the analysis region as a target region;
and translating the field image to different directions to obtain a plurality of contrast areas corresponding to the contrast fields.
The field pattern F1 is a target area. Four comparison fields are arranged in the embodiment, and the embodiment is specific: moving the Tian Kuaitu-shaped F1 upwards by a distance H to form a contrast area N1 corresponding to the northwise contrast field; moving the Tian Kuaitu F1 downwards by H distance to form a contrast area S1 corresponding to the south contrast field; moving Tian Kuaitu F1 leftwards by a distance W to form a comparison area W1 corresponding to the western comparison field; and (5) moving the Tian Kuaitu shape F1 rightward by a distance H to form a contrast area E1 corresponding to the east contrast field.
After the analysis area, the target area and the comparison area are divided, respectively selecting one Sentinel-2 satellite remote sensing image of a plurality of growth stages from the seedling stage to the development and maturation process according to the growth period of crops, and respectively adopting T1, T2 and T3 … Tn to represent the 1 st, 2 nd and 3 … n growth stages. The satellite remote sensing image of each growth stage is required to completely cover the target region R1, and the cloud cover is lower than 5% so as to avoid errors caused by the influence of cloud cover.
Preferably, the normalized vegetation index map is calculated according to the satellite remote sensing image, specifically:
calculating normalized vegetation indexes corresponding to each pixel of the satellite remote sensing image;
and combining the normalized vegetation indexes corresponding to the pixels of the satellite remote sensing image to generate the normalized vegetation index map.
NDVI (Normalized Difference Vegetation Index), i.e. normalized vegetation index, also known as normalized vegetation index, is the best indicator of vegetation growth status and vegetation spatial density, and is linearly related to vegetation distribution density. Therefore, the present example selects a normalized vegetation index to analyze crop vigor.
Preferably, the normalized vegetation index corresponding to each pixel of the satellite remote sensing image is calculated, which specifically includes:
NDVI＝(NIR-RED)/(NIR+RED)；
wherein, NDVI represents normalized vegetation index, NIR is near infrared band emissivity, RED is RED band emissivity.
The normalized vegetation index (NDVI) calculation formula is the ratio of the difference between the near infrared band and red band emissivity to the sum of the near infrared band and red band reflectivities.
And generating NDVI growth vigor data, namely a normalized vegetation index graph, according to the acquired Sentinel-2 satellite remote sensing image data and respectively aiming at n satellite remote sensing images in the stages T1, T2 and T3 … Tn.
Cutting each normalized vegetation index map according to the corresponding range of each area of F1, E1, S1, W1 and N1 to obtain target vegetation index maps of the target area in different growth stages: ndvi_f1, ndvi_f2, ndvi_f3 … ndvi_fn, and comparative vegetation index plots of four comparative regions at different growth stages: ndvi_e1, ndvi_e2, ndvi_e3 … ndvi_en; ndvi_s1, ndvi_s2, ndvi_s3 … ndvi_sn; ndvi_w1, ndvi_w2, ndvi_w3 … ndvi_wn; ndvi_n1, ndvi_n2, ndvi_n3 … ndvi_nn.
Preferably, the crop growth condition analysis result is obtained according to the target vegetation index diagrams of different growth stages and the comparison vegetation index diagrams of different growth stages, which comprises the following steps:
setting a mapping relation table of vegetation indexes and growth levels;
dividing the growth vigor level of the field to be measured according to the mapping relation table and the target vegetation index graph to obtain a growth vigor grading result of the field to be measured;
dividing the growth vigor level of each comparison field according to the mapping relation table and the comparison vegetation index graph to obtain a growth vigor grading result of each comparison field;
and comparing the growth classification result of the field to be tested with the growth classification result of each comparison field to obtain a crop growth analysis result.
NDVI can reflect the background influence of plant canopy, such as soil, moist ground, snow, dead leaves, coarse and excessive degree, and is related to vegetation coverage, and NDVI is less than or equal to-1 and less than or equal to 1.NDVI is negative indicating that the ground cover is clouds, water, snow, etc., highly reflective to visible light; NDVI is 0, with rock or bare earth etc., NIR and R are approximately equal; the positive value of NDVI indicates vegetation coverage, and vegetation increases as coverage increases, and the NDVI values are ranked according to this rule to obtain a mapping relationship table shown in the following table.
Table 1: growth potential hierarchical mapping relation table
Dividing the target vegetation index map into a plurality of areas corresponding to a plurality of levels according to the mapping relation table to obtain a growth classification result map of the field to be detected.
Dividing the comparison vegetation index map into a plurality of areas corresponding to a plurality of levels according to the mapping relation table to obtain a growth classification result map of the comparison field.
And comparing and analyzing the growth classification result graphs of the field to be tested in different growth stages and comparing the growth classification result graphs of the field to be tested in different growth stages, so as to realize crop growth analysis.
Preferably, the crop growth condition analysis result is obtained based on the comparison of the growth condition classification result of the field to be measured and the growth condition classification result of each comparison field, and the method comprises the following steps:
comparing the growth classification results of the field to be tested in different growth stages to obtain crop growth analysis results in the time dimension;
and comparing the growth classification results of different fields in the same growth stage to obtain a crop growth analysis result in the space dimension.
The embodiment obtains the crop growth condition analysis results of the field to be detected in different growth stages, and obtains the crop growth condition analysis results of the contrast field in different growth stages, so that the contrast analysis in two dimensions of time dimension (different growth stages) and space dimension (field to be detected and contrast field) can be realized.
Specifically, in this embodiment, the growth classification results of each growth stage of the five research areas F1, E1, S1, W1, and N1 are analyzed, and the growth classification duty ratios of different areas of each growth stage are calculated, so as to obtain a comparison chart of the growth classification duty ratios. Fig. 2 shows a ratio diagram of different growth vigor levels of five different areas (F1, E1, S1, W1, N1) in the jointing period, the diagram visually shows the growth vigor grading conditions of different areas (different field blocks) in the jointing period, and the top dressing irrigation in the jointing period of the field blocks to be tested can be better guided according to the diagram. Specifically, as can be seen from fig. 2, the sector area ratio (22%) of the growth vigor difference of the F1 region is larger than that of the E1, S1 and W1 regions, so that the amount of nitrogen dressing fertilizer should be increased during the jointing period to promote the growth of crops, and the comparison is the comparison in the space dimension.
Specifically, as shown in fig. 3, in this embodiment, a plot of growth trend curves of the 5 regions F1, E1, S1, W1, and N1 in five growth stages of a seeding stage, a seedling stage, a jointing stage, a flowering stage, and a maturation stage is also drawn, and the growth values of each region in each growth stage are average values of NDVI. Analysis of fig. 3, if a certain growth stage of the broken line of the F1 area is below the comparison area, it is indicated that the growth state of this growth stage is not good, it is necessary to check the leaves of the crop, determine chlorophyll of the crop, calculate the amount of nitrogen fertilizer applied by topdressing, and ensure nutrition required for healthy growth of the crop, where the comparison is also in the spatial dimension. If the average value of NDVI of a certain growth stage of the F1 target area is lower than that of other growth stages, the leaves turn yellow, and the crops are possibly lack of water, the irrigation schemes of the F1 and E1, S1, W1 and N1 are further compared, and if the irrigation amount of the F1 target area is found to be less, proper water supplementing is needed, and the comparison is performed in the time dimension.
The field management decision is assisted through comparative analysis, the topdressing and irrigation strategies in the growth period are calculated, and an analysis report based on remote sensing growth vigor data is obtained, so that the purpose of more scientific planting is achieved, and the crop yield is improved.
Preferably, the method further comprises:
and generating a fertilization and irrigation scheme of the field to be tested according to the crop growth analysis result.
According to the crop growth analysis result, finding out a subarea with poor growth in the target area, pertinently increasing the frequency and the dosage of topdressing to the subarea with long potential difference, improving the nutrient condition of the subarea and promoting the growth of crops; for the subareas with better growth conditions in the target area, the conditions of seedling burning and overnutrition caused by excessive additional fertilizer consumption should be avoided.
According to the crop growth analysis result, finding out a subarea with poor growth in the target area, and pertinently increasing the irrigation times and water quantity for the subarea with long potential difference, so as to ensure the generation of water needed by crops and promote the growth of the crops; and (3) cutting excessive irrigation is carried out on the subareas with better growth conditions in the target area according to a normal irrigation strategy, so that the defect that the air content is insufficient due to excessive water content in soil is avoided, and the growth and development of crops are affected.
According to the crop growth condition analysis method provided by the invention, the selected Sentinel-2 satellite 10-meter multispectral remote sensing image data has the advantages of high spatial resolution and high time resolution, and the advantages of multidimensional space contrast time sequence analysis are combined on the basis, so that fertilization and irrigation schemes are guided. Crop abnormality or health problems can be found early, and monitoring and insight level of farms are enhanced; identifying and monitoring crop growth condition changes and distribution conditions of different growth conditions, and carrying out differential management; the influence of measures such as fertilization, irrigation, pesticide spraying and the like on the health of crops can be monitored; and (3) through growth analysis results, a reasonable fertilization and irrigation scheme is calculated, so that the crop yield is improved.
Example 2
Embodiment 2 of the present invention provides a crop growth situation analysis device, including a processor and a memory, where the memory stores a computer program, and when the computer program is executed by the processor, the crop growth situation analysis method provided in embodiment 1 is implemented.
The crop growth situation analysis device provided by the embodiment of the invention is used for realizing the crop growth situation analysis method, so that the crop growth situation analysis method has the technical effects that the crop growth situation analysis device also has, and the description thereof is omitted.
Example 3
Embodiment 3 of the present invention provides a computer storage medium having stored thereon a computer program which, when executed by a processor, implements the crop growth situation analysis method provided in embodiment 1.
The computer storage medium provided by the embodiment of the invention is used for realizing the crop growth situation analysis method, so that the technical effects of the crop growth situation analysis method are achieved, and the computer storage medium is also achieved and is not described herein.
The present invention is not limited to the above-mentioned embodiments, and any changes or substitutions that can be easily understood by those skilled in the art within the technical scope of the present invention are intended to be included in the scope of the present invention.
Claims (5)
1. The crop growth condition analysis method is characterized by comprising the following steps:
setting an analysis area according to the field range to be detected, and dividing a target area corresponding to the field to be detected and a comparison area corresponding to the comparison field in the analysis area;
the analysis area is set according to the field range to be measured, specifically:
drawing a field block graph according to the field block to be tested, generating an outsourcing rectangle of the field block graph, and expanding the outsourcing rectangle to obtain the analysis area;
dividing a target area corresponding to the field to be detected and a comparison area corresponding to the comparison field in the analysis area, wherein the target area and the comparison area are specifically as follows:
setting a range corresponding to the Tian Kuaitu shape in the analysis region as a target region;
translating the field image to different directions to obtain a plurality of contrast areas corresponding to the contrast fields;
acquiring satellite remote sensing images of analysis areas when crops in a field to be detected are in different growth stages;
calculating a normalized vegetation index map corresponding to each growth stage according to each satellite remote sensing image;
cutting the normalized vegetation index map according to the target area and the comparison area respectively to obtain a target vegetation index map corresponding to the field to be detected and a comparison vegetation index map corresponding to the comparison field;
according to the target vegetation index diagrams of different growth stages and the comparison vegetation index diagrams of different growth stages, acquiring crop growth condition analysis results, wherein the crop growth condition analysis results comprise:
setting a mapping relation table of vegetation indexes and growth levels, wherein the growth levels comprise bare soil, long potential difference, general growth and good growth;
dividing the growth vigor level of the field to be measured according to the mapping relation table and the target vegetation index graph to obtain a growth vigor grading result of the field to be measured;
dividing the growth vigor level of each comparison field according to the mapping relation table and the comparison vegetation index graph to obtain a growth vigor grading result of each comparison field;
comparing the growth classification result of the field to be tested with the growth classification result of each comparison field to obtain a crop growth analysis result, comprising:
comparing the growth classification results of the field to be detected in different growth stages to obtain crop growth analysis results in the time dimension, wherein the crop growth analysis results specifically comprise:
drawing a growth trend line graph of the target area and the corresponding comparison area in different growth stages, wherein the growth trend value of each area in each growth stage adopts an average value of NDVI;
comparing the growth classification results of different fields in the same growth stage to obtain crop growth analysis results in space dimension, wherein the crop growth analysis results specifically comprise:
respectively calculating the growth classification duty ratio of the target area and the corresponding comparison area of each growth stage to obtain a growth classification duty ratio diagram;
the field management decision is assisted through comparative analysis, the topdressing and irrigation strategies in the growth period are calculated, and an analysis report based on remote sensing growth condition data is obtained;
according to the crop growth analysis result, a fertilization and irrigation scheme of the field to be tested is generated, specifically:
according to the crop growth analysis result, finding out a sub-area with long potential difference in the target area, pertinently increasing the frequency and the dosage of topdressing to the sub-area with long potential difference, improving the nutrient condition of the sub-area and promoting the growth of crops; for the subareas with good growth vigor in the target area, the conditions of seedling burning and overnutrition caused by excessive additional fertilizer consumption are avoided, and according to the crop growth vigor analysis result, the subareas with long potential difference in the target area are found, the number of times and the water quantity of irrigation are purposefully increased for the subareas with long potential difference, the water content required by crop generation is ensured, and the growth of the crop is promoted; the subareas with good growth vigor in the target area are irrigated in a cutting and overquantity mode according to a normal irrigation strategy, so that the defect that the air content is insufficient due to the excessive water content in soil is avoided, and the growth and development of crops are affected;
the subregion of long potential difference refers to the region with the NDVI value of 0-0.3, and the subregion with good growth potential refers to the region with the NDVI value of 0.6-1.
2. The crop growth situation analysis method according to claim 1, wherein the calculating a normalized vegetation index map according to the satellite remote sensing image specifically comprises:
calculating normalized vegetation indexes corresponding to each pixel of the satellite remote sensing image;
and combining the normalized vegetation indexes corresponding to the pixels of the satellite remote sensing image to generate the normalized vegetation index map.
3. The crop growth situation analysis method according to claim 2, wherein the calculating of the normalized vegetation index corresponding to each pixel of the satellite remote sensing image specifically includes:
NDVI = (NIR - RED) / (NIR + RED)；
wherein, NDVI represents normalized vegetation index, NIR is near infrared band emissivity, RED is RED band emissivity.
4. A crop growth analysis device comprising a processor and a memory, the memory having stored thereon a computer program which, when executed by the processor, implements the crop growth analysis method of any of claims 1-3.
5. A computer storage medium having stored thereon a computer program which, when executed by a processor, implements a method of crop growth situation analysis according to any of claims 1-3.
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