CN115271343A - A method and system for monitoring and adjusting decision-making of crop planting structure in water-deficient areas - Google Patents

Abstract

The invention provides a method and a system for monitoring and adjusting decision of crop planting structure in a water-deficient area, belonging to the technical field of agricultural remote sensing and comprising the following steps: acquiring gravity satellite data of an underground water shortage region, and combining underground water bit data space interpolation calculation to obtain an underground water key water shortage region distribution map; acquiring remote sensing image data of an underground water shortage area, carrying out vegetation index selection calculation on the remote sensing image data of the underground water shortage area and carrying out remote sensing classification according to large-area crop planting to obtain a crop dominance degree graph; and integrating the distribution diagram of the key water shortage area of the underground water and the crop dominance degree diagram to obtain a crop planting adjustment guidance result. The invention utilizes multi-source remote sensing data, integrates groundwater level lines such as groundwater and the like, rapid groundwater decline and crop planting dominance remote sensing monitoring aiming at groundwater shortage areas, assists crop planting decision, can improve crop planting dominance remote sensing monitoring and decision efficiency, and provides powerful technical support for reducing and controlling agricultural water consumption and retarding groundwater level decline trend.

Description

Method and system for monitoring and adjusting decision-making of crop planting structure in water-scarce areas

technical field

The invention relates to the technical field of agricultural remote sensing, in particular to a method and system for monitoring and adjusting decision-making of crop planting structures in water-scarce areas.

Background technique

For a long time, people have generally used artificial irrigation to develop land resources, but the existing arable land area is limited, especially in arid or semi-arid areas. Large-scale artificial reclamation and extensive flood irrigation consume a large amount of groundwater resources and cause regional insufficiency. Large areas of water and salt migration, reorganization and accumulation have caused a sharp reduction in the area of agricultural and pastoral land suitable for arable and high-yield farming in these areas. Therefore, it is necessary to implement effective monitoring of cultivated land in water-scarce areas to guide reasonable crop planting structure adjustments.

The current crop planting structure adjustment mainly relies on manual statistics and reported data. On the one hand, there is no spatial location information of specific fields, and on the other hand, there is a lack of spatial coupling and overlay analysis with groundwater shortage changes. Manually counting and reporting data has the obvious problems of low efficiency and low accuracy.

In view of the above defects, it is necessary to propose a new crop planting guidance method in water-scarce areas.

Contents of the invention

The present invention provides a method and system for crop planting structure monitoring and adjustment decision-making in water-deficient areas, which is used to solve the problem that the guidance of crop planting structure adjustment for water-deficient areas in the prior art mainly relies on manual work, resulting in low efficiency and accuracy Defects.

In a first aspect, the present invention provides a method for monitoring and adjusting decision-making of crop planting structures in water-scarce areas, including:

Obtain gravity satellite data of underground water-shortage areas, combine with groundwater level data spatial interpolation calculations, and obtain the distribution map of key water-shortage areas of groundwater;

Obtain the remote sensing image data of the underground water-deficient area, perform vegetation index selection calculation on the remote-sensing image data of the underground water-deficient area, and classify according to the remote sensing of crop planting in a large area to obtain a crop dominance map;

Combining the distribution map of key groundwater water shortage areas and the crop dominance map, a crop planting adjustment guidance result is obtained.

According to a method for crop planting structure monitoring and adjustment decision-making in a water-scarce area provided by the present invention, the acquisition of gravity satellite data in an underground water-short area includes:

Call the gravity satellite dataset through Google map engine GEE;

Extracting the total groundwater storage data in the gravity satellite data set, and screening the relative change data of the groundwater average value in the preset time period in the total groundwater storage data;

Converting the relative change data to a preset scale range by interpolation to obtain the gravity satellite data of the underground water-shortage area;

Obtain groundwater observation record data;

Carrying out spatial interpolation to the groundwater observation record data by Kriging interpolation method to obtain a groundwater level distribution time series;

Through three-dimensional visualization and a threshold method, the gravity satellite data of the underground water-shortage area and the time series of the distribution of the groundwater level are superimposed, and the distribution map of the key water-shortage area of the groundwater is obtained through analysis.

According to a method for crop planting structure monitoring and adjustment decision-making in water-deficient areas provided by the present invention, the remote sensing image data of underground water-deficient areas is acquired, the vegetation index is selected and calculated according to the remote sensing image data of underground water-deficient areas and according to the large area Remote sensing classification of crop planting, including:

Obtain Sentinel-2 image data of different crop planting areas in the first time period and the second time period of the anniversary through GEE;

Carry out image stitching, image cropping and preset band fusion calculation on the image data of Sentinel 2 in the different crop planting areas, and use the preset band of Sentinel 2 to perform image cloud removal to obtain the initial remote sensing image data of underground water-scarce areas;

performing fusion correction on the initial remote sensing image data of underground water-shortage areas, and performing mask processing on the initial remote-sensing image data of underground water-shortage areas based on the preset range of cultivated land to obtain the remote sensing image data of underground water-shortage areas;

Screen the third band data, fourth band data, eighth band data and eleventh band data of Sentinel-2 in the remote sensing image data of the underground water-deficient area, as well as the normalized difference vegetation index, enhanced vegetation index, normalized Water index, chlorophyll index, soil tillage index and normalized tillage index to obtain the vegetation index set of remote sensing image data of underground water-deficient areas;

Based on the monthly time-series combination of the first time period and the second time period within the anniversary, the vegetation index set of the remote sensing image data of the underground water-deficient area is divided into a large-area crop planting remote sensing data set;

The random forest classification method is used to classify the large-area crop planting remote sensing data set, and the classification result of the large-area crop planting is obtained.

According to a method for instructing crop planting in water-deficient areas provided by the present invention, the remote sensing image data of underground water-deficient areas is acquired, the vegetation index is selected and calculated according to the remote sensing image data of underground water-deficient areas, and the crops are classified according to the remote sensing of large-area crops, Get the crop dominance map, including:

Cutting and segmenting the crop planting classification results in the large area, and outputting the planting area of different crops;

Calculate the ratio of the planting area of different crops to the total area of cultivated land respectively to obtain the proportion of the planting area of different crops;

Drawing and outputting the crop dominance map according to the planting area ratio of the different crops.

In the second aspect, the present invention also provides a system for crop planting structure monitoring and adjustment decision-making in water-scarce areas, including:

The first processing module is used to obtain the gravity satellite data of the underground water-shortage area, and combine the spatial interpolation calculation of the groundwater level data to obtain the distribution map of the key water-shortage area of the groundwater;

The second processing module is used to obtain remote sensing image data of underground water-shortage areas, perform vegetation index selection and calculation on the remote-sensing image data of underground water-shortage areas, and obtain crop dominance degree maps according to the remote sensing classification of crop planting in large areas;

The adjustment module is used to synthesize the distribution map of key groundwater water shortage areas and the crop dominance map to obtain crop planting adjustment guidance results.

In a third aspect, the present invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and operable on the processor. When the processor executes the program, any of the above-mentioned The method of crop planting structure monitoring and adjustment decision-making in water-scarce areas is described.

In the fourth aspect, the present invention also provides a non-transitory computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the monitoring and monitoring of crop planting structures in water-scarce areas as described in any one of the above-mentioned Approaches to fine-tune decision-making.

In the fifth aspect, the present invention also provides a computer program product, including a computer program, and when the computer program is executed by a processor, the method for monitoring and adjusting decision-making of crop planting structure in any one of the above-mentioned water-scarce areas can be realized.

The method and system for crop planting structure monitoring and adjustment decision-making in water-deficient areas provided by the present invention, through the use of multi-source remote sensing data, aiming at groundwater water-deficient areas, comprehensively monitor groundwater contours, groundwater rapid decline, and crop planting dominance remote sensing monitoring, assist Crop planting decision-making can improve the efficiency of remote sensing monitoring and decision-making of crop planting dominance in large areas, and provide strong technical support for reducing and controlling agricultural water use to slow down the downward trend of groundwater levels.

Description of drawings

In order to more clearly illustrate the present invention or the technical solutions in the prior art, the accompanying drawings that need to be used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the accompanying drawings in the following description are the present invention. For some embodiments of the invention, those skilled in the art can also obtain other drawings based on these drawings without creative effort.

Fig. 1 is one of the schematic flow charts of the method for crop planting structure monitoring and adjustment decision-making in water-scarce areas provided by the present invention;

Fig. 2 is the second schematic flow chart of the method for crop planting structure monitoring and adjustment decision-making in water-scarce areas provided by the present invention;

Fig. 3 is the structural representation of the system of crop planting structure monitoring and adjustment decision-making in the water-scarce area provided by the present invention;

Fig. 4 is a schematic structural diagram of an electronic device provided by the present invention.

Detailed ways

In order to make the purpose, technical solutions and advantages of the present invention clearer, the technical solutions in the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the present invention. Obviously, the described embodiments are part of the embodiments of the present invention , but not all examples. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without creative efforts fall within the protection scope of the present invention.

Aiming at the deficiencies of the prior art, the present invention uses the Google Earth Engine (GEE) remote sensing big data platform to mine multi-temporal and spatial remote sensing image information and perform statistical analysis to provide remote sensing monitoring and monitoring of crop planting systems at the field scale in arid and semi-arid areas. Planting structure adjustment provides a reference.

Fig. 1 is one of the schematic flow charts of the method for crop planting structure monitoring and adjustment decision-making in water-scarce areas provided by the present invention, as shown in Fig. 1 , comprising:

Step 100: Obtain the gravity satellite data of underground water-scarce areas, combine the groundwater level data with spatial interpolation calculations, and obtain the distribution map of key water-shortage areas of groundwater;

Step 200: Obtain remote sensing image data of underground water-shortage areas, perform vegetation index selection and calculation on the remote-sensing image data of underground water-shortage areas, and classify crops according to remote sensing in large areas to obtain a crop dominance map;

Step 300: Combining the distribution map of key groundwater water shortage areas and the crop dominance map to obtain crop planting adjustment guidance results.

The present invention processes the original data of the water-shortage area through two branches. One is to use GRACE gravity satellite data to invert the change of groundwater storage in recent years, and to interpolate the groundwater level in combination with the groundwater level data of the groundwater observation station to obtain the groundwater funnel The distribution map of key groundwater water-scarce areas that need to be paid attention to, such as areas with rapid decline in groundwater levels and other areas; the second is for water-scarce areas, using the GEE remote sensing big data platform to obtain large-area Sentinel No. 2 impact data, and relying on Sentinel in the GEE platform The QA60 band of No. 2 completed the image cloud removal operation, combined with the regional crop planting conditions, selected and calculated a certain number of vegetation indices, and part of the band data in the Sentinel No. 2 data, combined to form a feature set, and then combined with the image data of the specified time period as The time-series remote sensing data is collected, and then the random forest algorithm is used to supervise and classify the range of the target area to obtain the crop dominance map.

Combining the distribution map of key groundwater water shortage areas and the crop dominance map obtained above, compare and analyze the crop dominance map with groundwater contours and the distribution of rapidly declining groundwater levels to assist crop planting adjustment decisions in different regions and create thematic maps.

It should be noted that the GEE platform has a global-scale remote sensing database and provides a cloud platform that can perform online visualization calculation and analysis processing. This platform can access satellite images and other data in the earth observation data database, and provide sufficient computing power To process these data, GEE can quickly and batch process a large number of images. With the development of satellite gravity detection technology, new observation methods are provided for the earth's gravity field with high precision and high temporal and spatial resolution, making it possible to monitor the total global groundwater storage and its changes by using the earth's time-varying gravity field. The earth's gravity field is a basic physical field that reflects the density distribution and movement state of the earth's surface and interior matter. Its changes reflect the migration and redistribution of fluid mass in the earth system, including the atmosphere, ocean, and land water. The atmosphere, ocean, surface water, and glaciers are deducted. After quality, the rest mainly reflects the total groundwater storage on land, and the GRACE satellite can be used to monitor the change of groundwater storage.

The present invention utilizes multi-source remote sensing data, aims at groundwater shortage areas, integrates groundwater contours, groundwater rapid decline, and crop planting dominance remote sensing monitoring, assists crop planting decision-making, and can improve the efficiency of remote sensing monitoring and decision-making of crop planting dominance in large areas , to provide strong technical support for reducing and controlling agricultural water use to slow down the downward trend of groundwater levels.

Based on the above embodiments, the acquisition of the gravity satellite data of the underground water-shortage area, combined with the spatial interpolation calculation of the groundwater level data, obtains the distribution map of the key water-shortage area of the groundwater, including:

Call the gravity satellite dataset through Google map engine GEE;

Extracting the total groundwater storage data in the gravity satellite data set, and screening the relative change data of the groundwater average value in the preset time period in the total groundwater storage data;

Converting the relative change data to a preset scale range by interpolation to obtain the gravity satellite data of the underground water-shortage area;

Obtain groundwater observation record data;

Carrying out spatial interpolation to the groundwater observation record data by Kriging interpolation method to obtain a groundwater level distribution time series;

Through three-dimensional visualization and a threshold method, the gravity satellite data of the underground water-shortage area and the time series of the distribution of the groundwater level are superimposed, and the distribution map of the key water-shortage area of the groundwater is obtained through analysis.

Specifically, the present invention invokes the GRACE Tellus satellite data set through the GEE platform, based on the total groundwater storage obtained by the GRACE satellite, and the relative change data relative to the average value of the previous 10 years as the basic data set for analyzing groundwater level changes. Here, the time-resolved The rate is one month, and the spatial resolution is 0.5° for dimension division.

Then through the groundwater level observation stations in various places, the observation record data of the groundwater observation points in recent years are obtained, the average value and variance of the discrete groundwater observation point data are counted, and the time change curve is analyzed.

Then Kriging interpolation method is used to interpolate the data of groundwater level value, which is expressed in GIS to obtain time series groundwater level distribution map to calculate the annual average buried depth data of groundwater in the study area. The kriging interpolation method here, also known as the spatial local interpolation method, is a method for unbiased optimal estimation of regionalized variables in a limited area based on the variation function theory and structural analysis. The scope of application is that there is spatial correlation in regionalized variables, that is, if the results of variance function and structural analysis show that there is spatial correlation in regionalized variables, kriging interpolation can be used for interpolation or extrapolation.

Further, by comparing the groundwater volume change monitoring data of the gravity satellite data and the spatial interpolation of the groundwater level data, the trend and situation of groundwater change are analyzed and monitored. The superimposed analysis of the two is carried out, and through three-dimensional visualization and the threshold method, the areas with rapid groundwater decline and low groundwater levels in recent years are set as key water-shortage areas of groundwater, and the distribution map of key water-shortage areas is made.

The present invention acquires large data of underground water-shortage areas through gravity satellites, and performs preprocessing and analysis, so as to obtain a relatively accurate distribution map of key water-shortage areas.

Based on any of the above-mentioned embodiments, the acquisition of remote sensing image data of underground water-shortage areas, the selection and calculation of vegetation index for the remote sensing image data of underground water-shortage areas, and the remote sensing classification of crop planting in large areas include:

Obtain Sentinel-2 image data of different crop planting areas in the first time period and the second time period of the anniversary through GEE;

Carry out image stitching, image cropping and preset band fusion calculation on the image data of Sentinel 2 in the different crop planting areas, and use the preset band of Sentinel 2 to perform image cloud removal to obtain the initial remote sensing image data of underground water-scarce areas;

performing fusion correction on the initial remote sensing image data of underground water-shortage areas, and performing mask processing on the initial remote-sensing image data of underground water-shortage areas based on the preset range of cultivated land to obtain the remote sensing image data of underground water-shortage areas;

Screen the third band data, fourth band data, eighth band data and eleventh band data of Sentinel-2 in the remote sensing image data of the underground water-deficient area, as well as the normalized difference vegetation index, enhanced vegetation index, normalized Water index, chlorophyll index, soil tillage index and normalized tillage index to obtain the vegetation index set of remote sensing image data of underground water-deficient areas;

Based on the monthly time-series combination of the first time period and the second time period within the anniversary, the vegetation index set of the remote sensing image data of the underground water-deficient area is divided into a large-area crop planting remote sensing data set;

The random forest classification method is used to classify the large-area crop planting remote sensing data set to obtain the large-area crop planting classification result;

Cutting and segmenting the crop planting classification results in the large area, and outputting the planting area of different crops;

Calculate the ratio of the planting area of different crops to the total area of cultivated land respectively to obtain the proportion of the planting area of different crops;

Drawing and outputting the crop dominance map according to the planting area ratio of the different crops.

Specifically, according to the crop growth phenology calendar, the present invention determines the time of 8 months per year as the key time for distinguishing different crops, which are March-August and November-December each year, and are obtained through the GEE remote sensing data cloud platform The 8-month Sentinel-2 images constitute time-series features, which are used to distinguish different crops.

Because of the Sentinel-2 image data obtained based on the GEE platform, the overall quality of the image data is good. It is the albedo data of the bottom layer of the atmosphere that has been atmospherically corrected, and has undergone orthorectification and sub-pixel geometric precision correction.

The annual high-quality image data in the target area is screened through the GEE platform. After the screening is completed, the image mosaic, image cropping, band calculation and fusion calculation are completed in the GEE platform, and the QA60 band in the Sentinel 2 is used for image removal. Cloud operation, the initial Remote sensing image data of underground water-scarce areas.

Then download and export the remote sensing image data of the initial underground water-shortage area to ENVI software for fusion and correction, and then use the public range of cultivated land to mask the image of the study area, remove other areas other than cultivated land, and complete image preprocessing to obtain the underground water-shortage area. Remote sensing image data of water areas.

Then, typical representative vegetation indices were selected from the remote sensing image data of underground water-scarce areas for calculation, including: Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), normalized Normalized Difference Water Index (NDWI), Chlorophyll Vegetation Index (GCVI), Soil Tillage Index (STI) and Normalized Difference Tillage Index (NDTI).

Among them, NDVI can quantitatively characterize photosynthetic capacity, water stress and vegetation productivity. EVI can reduce soil reflectance and enhance the contrast between bare land and vegetation. NDWI is sensitive to surface water content and is also an important vegetation index for extracting water bodies. GCVI It has a strong response to the application of fertilizers in the range of cultivated land in the target area, and STI is an effective index for identifying cultivated land. The vegetation index is often used for the extraction of vegetation or vegetation information.

On the basis of the above 6 vegetation indices, the 4 band data of B3, B4, B8 and B11 of Sentinel-2 were added as the collection of vegetation indices of remote sensing image data of underground water-scarce areas, which were used for remote sensing classification of different planting methods.

Further, the 8-month time series combination of November-December and March-August and the feature combination of 10 vegetation indices (NDVI, EVI, NDWI, GCVI, STI, NDTI6, B3, B4, B8, B11) per month , a total of 80 features were put into the random forest classifier for large-scale crop planting classification.

Taking the groundwater funnel area in the southern plain of a certain area as an example, the random forest algorithm was used to classify the one-season crops and two-year crops to investigate the planting distribution of different crops. The F1-score of the one-season crop classification reached 95.97%. The F1-score of the crop classification results for the two seasons of the year reaches 98.70%, which can meet the requirements of remote sensing monitoring of crop planting distribution on the field scale.

The invention defines the crop dominance degree, that is, the ratio of the crop planting area to the total area of cultivated land, which reflects the proportion of different crop planting systems within a certain range, and takes the delineated area as the basic unit, and the remote sensing monitoring results of crop planting distribution on the field scale Carry out cutting and segmentation, and use the Arcgis software area tabulation tool to count the classification results of different crops within the planned area, and calculate the crop planting dominance. It is understandable that the distribution of crop planting systems in different regions can be visually seen based on the demarcated area, and the crop planting dominance map can be drawn.

Finally, by comparing the crop dominance map and the distribution map of key groundwater water shortage areas, combined with information such as groundwater and other water levels, in order to achieve the purpose of water-saving planting, auxiliary crop planting adjustment decisions and suggestions can be put forward.

Taking the groundwater funnel area in the southern part of a plain area as an example, comparing the classification results of single- and double-crop crops at the field scale, the dominance map of two-season crops in a funnel area of a plain, and the distribution map of deep groundwater and other water burial depths in a plain, it can be seen that the main The crop types in the groundwater funnel area are mainly one-season crops a year, and the dominance of two-season crops is low, but there are also some crop types in the funnel area that are still dominated by two-season crops a year. In the core area of the groundwater funnel area, the two-season crops in a year account for a large proportion, which requires a large amount of agricultural water, which is not conducive to the maintenance of groundwater levels. It is recommended to reduce the planting of two-season crops in a key control area; In the fringe area of the area, and the proportion of two-season crops is slightly small, it is recommended to reduce the planting of two-season crops as a secondary control area to maintain the groundwater level.

The second schematic flow diagram of the method for crop planting structure monitoring and adjustment decision-making in the water-deficient area shown in Figure 2 includes the complete steps of the scheme of the present invention:

(1) Acquisition of gravity satellite data and calculation of groundwater changes in underground water-scarce areas;

(2) Spatial interpolation of groundwater level data;

(3) Mapping of key water-shortage areas of groundwater;

(4) Acquisition of multi-temporal and spatial satellite remote sensing images based on the GEE platform;

(5) Calculation of satellite remote sensing vegetation index;

(6) Remote sensing monitoring of crop planting in large areas;

(7) Mapping of crop planting dominance on the field scale;

(8) Decision-making to adjust the dominance of crop planting in large areas.

The present invention proposes a method for assisting crop planting decision-making in areas where groundwater is short of water, comprehensive groundwater contours, groundwater rapid decline, and crop planting dominance remote sensing monitoring, which can improve the efficiency of remote sensing monitoring and decision-making of crop planting dominance in large areas. And control agricultural water use to slow down the trend of groundwater level decline to provide technical support.

The system of crop planting structure monitoring and adjustment decision-making in the water-deficient area provided by the present invention is described below, the system of crop planting structure monitoring and adjustment decision-making in the water-deficient area described below is the same as the crop planting structure monitoring and adjustment decision-making in the water-deficient area described above The methods can be referred to each other.

Fig. 3 is a schematic structural diagram of a system for crop planting structure monitoring and adjustment decision-making in water-scarce areas provided by the present invention, as shown in Fig. 3 , including: a first processing module 31, a second processing module 32 and an adjustment module 33, wherein:

The first processing module 31 is used to obtain the gravity satellite data of the underground water-shortage area, combined with the spatial interpolation calculation of the groundwater level data, to obtain the distribution map of the key water-shortage area of the groundwater; the second processing module 32 is used to obtain the remote sensing image data of the underground water-short area, and The remote sensing image data of the underground water-shortage area is selected and calculated according to the vegetation index and classified according to the remote sensing of crop planting in a large area to obtain a crop dominance map; the adjustment module 33 is used to synthesize the distribution map of the key water-shortage areas of the groundwater and the crop dominance Fig. 1 shows the results of crop planting adjustment guidance.

The present invention utilizes multi-source remote sensing data, aims at groundwater shortage areas, integrates groundwater contours, groundwater rapid decline, and crop planting dominance remote sensing monitoring, assists crop planting decision-making, and can improve the efficiency of remote sensing monitoring and decision-making of crop planting dominance in large areas , to provide strong technical support for reducing and controlling agricultural water use to slow down the downward trend of groundwater levels.

FIG. 4 illustrates a schematic diagram of the physical structure of an electronic device. As shown in FIG. 4, the electronic device may include: a processor (processor) 410, a communication interface (Communications Interface) 420, a memory (memory) 430 and a communication bus 440, Wherein, the processor 410 , the communication interface 420 , and the memory 430 communicate with each other through the communication bus 440 . The processor 410 can call the logic instructions in the memory 430 to implement the method for monitoring and adjusting the crop planting structure in water-scarce areas. The method includes: acquiring gravity satellite data in underground water-scarce areas, and combining the spatial interpolation calculation of groundwater level data to obtain groundwater Distribution map of key water-shortage areas; obtain remote sensing image data of underground water-shortage areas, perform vegetation index selection and calculation on the remote-sensing image data of underground water-shortage areas, and obtain crop dominance map according to remote sensing classification of crop planting in large areas; synthesize the groundwater The distribution map of the key water-scarce areas and the crop dominance map are used to obtain the crop planting adjustment guidance results.

In addition, the above logic instructions in the memory 430 may be implemented in the form of software function units and be stored in a computer-readable storage medium when sold or used as an independent product. Based on this understanding, the essence of the technical solution of the present invention or the part that contributes to the prior art or the part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including Several instructions are used to make a computer device (which may be a personal computer, a server, or a network device, etc.) execute all or part of the steps of the methods described in various embodiments of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), magnetic disk or optical disk and other media that can store program codes. .

On the other hand, the present invention also provides a computer program product. The computer program product includes a computer program that can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can The method for monitoring and adjusting decision-making of crop planting structure in water-scarce areas provided by the above-mentioned methods includes: obtaining gravity satellite data of underground water-scarce areas, and combining the spatial interpolation calculation of groundwater level data to obtain the distribution map of key water-scarce areas of groundwater; Obtain remote sensing image data of underground water-shortage areas, perform vegetation index selection calculation on the remote-sensing image data of underground water-shortage areas, and obtain crop dominance map according to the remote sensing classification of large-scale crop planting; synthesize the distribution map of key water-shortage areas of groundwater and The crop dominance map obtains crop planting adjustment guidance results.

In yet another aspect, the present invention also provides a non-transitory computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, it is implemented to perform the monitoring and monitoring of crop planting structures in water-scarce areas provided by the above methods. A method for adjusting decision-making, the method comprising: obtaining gravity satellite data of underground water-shortage areas, and combining the spatial interpolation calculation of groundwater level data to obtain a distribution map of key water-shortage areas of groundwater; obtaining remote sensing image data of underground water-shortage areas, The vegetation index is selected and calculated according to the regional remote sensing image data, and the crop dominance map is obtained according to the remote sensing classification of crop planting in large areas; the distribution map of key groundwater water shortage areas and the crop dominance map are combined to obtain the crop planting adjustment guidance results.

The device embodiments described above are only illustrative, and the units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in One place, or it can be distributed to multiple network elements. Part or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment. It can be understood and implemented by those skilled in the art without any creative efforts.

Through the above description of the implementations, those skilled in the art can clearly understand that each implementation can be implemented by means of software plus a necessary general hardware platform, and of course also by hardware. Based on this understanding, the essence of the above technical solution or the part that contributes to the prior art can be embodied in the form of software products, and the computer software products can be stored in computer-readable storage media, such as ROM/RAM, magnetic discs, optical discs, etc., including several instructions to make a computer device (which may be a personal computer, server, or network device, etc.) execute the methods described in various embodiments or some parts of the embodiments.

Finally, it should be noted that: the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: it can still be Modifications are made to the technical solutions described in the foregoing embodiments, or equivalent replacements are made to some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims (7)

1. A method for crop planting structure monitoring and adjustment decision-making in water-scarce areas, characterized in that it comprises: Obtain gravity satellite data of underground water-shortage areas, combine with groundwater level data spatial interpolation calculations, and obtain the distribution map of key water-shortage areas of groundwater; Obtain the remote sensing image data of the underground water-deficient area, perform vegetation index selection calculation on the remote-sensing image data of the underground water-deficient area, and classify according to the remote sensing of crop planting in a large area to obtain a crop dominance map; Combining the distribution map of key groundwater water shortage areas and the crop dominance map, a crop planting adjustment guidance result is obtained. 2. The method for crop planting structure monitoring and adjustment decision-making in water-scarce areas according to claim 1, characterized in that, said acquisition of underground water-shortage area gravity satellite data, in conjunction with groundwater level data spatial interpolation calculations, to obtain groundwater key water shortages Area distribution map, including: Call the gravity satellite dataset through Google map engine GEE; Extracting the total groundwater storage data in the gravity satellite data set, and screening the relative change data of the groundwater average value in the preset time period in the total groundwater storage data; Converting the relative change data to a preset scale range by interpolation to obtain the gravity satellite data of the underground water-shortage area; Obtain groundwater observation record data; Carrying out spatial interpolation to the groundwater observation record data by Kriging interpolation method to obtain a groundwater level distribution time series; Through three-dimensional visualization and a threshold method, the gravity satellite data of the underground water-shortage area and the time series of the distribution of the groundwater level are superimposed, and the distribution map of the key water-shortage area of the groundwater is obtained through analysis. 3. The method for crop planting structure monitoring and adjustment decision-making in the water-deficient area according to claim 1, characterized in that, the remote sensing image data of the underground water-deficient area is obtained, and the vegetation index is carried out to the remote-sensing image data of the underground water-deficient area Select calculations and classification by remote sensing of crop cultivation in large areas, including: Obtain Sentinel-2 image data of different crop planting areas in the first time period and the second time period of the anniversary through GEE; Carry out image stitching, image cropping and preset band fusion calculation on the image data of Sentinel 2 in the different crop planting areas, and use the preset band of Sentinel 2 to perform image cloud removal to obtain the initial remote sensing image data of underground water-scarce areas; performing fusion correction on the initial remote sensing image data of underground water-shortage areas, and performing mask processing on the initial remote-sensing image data of underground water-shortage areas based on the preset range of cultivated land to obtain the remote sensing image data of underground water-shortage areas; Screen the third band data, fourth band data, eighth band data and eleventh band data of Sentinel-2 in the remote sensing image data of the underground water-deficient area, as well as the normalized difference vegetation index, enhanced vegetation index, normalized Water index, chlorophyll index, soil tillage index and normalized tillage index to obtain the vegetation index set of remote sensing image data of underground water-deficient areas; Based on the monthly time-series combination of the first time period and the second time period within the anniversary, the vegetation index set of the remote sensing image data of the underground water-deficient area is divided into a large-area crop planting remote sensing data set; The random forest classification method is used to classify the large-area crop planting remote sensing data set, and the classification result of the large-area crop planting is obtained. 4. The method for crop planting structure monitoring and adjustment decision-making in the water-deficient area according to claim 3, characterized in that, the remote sensing image data of the underground water-deficient area is obtained, and the vegetation index is carried out to the remote-sensing image data of the underground water-deficient area Select the calculation and classify according to the remote sensing of crop planting in large areas to obtain the crop dominance map, including: Cutting and segmenting the crop planting classification results in the large area, and outputting the planting area of different crops; Calculate the ratio of the planting area of different crops to the total area of cultivated land respectively to obtain the proportion of the planting area of different crops; Drawing and outputting the crop dominance map according to the planting area ratio of the different crops. 5. A system for crop planting structure monitoring and adjustment decision-making in water-scarce areas, characterized in that it includes: The first processing module is used to obtain the gravity satellite data of the underground water-shortage area, and combine the spatial interpolation calculation of the groundwater level data to obtain the distribution map of the key water-shortage area of the groundwater; The second processing module is used to obtain remote sensing image data of underground water-shortage areas, perform vegetation index selection and calculation on the remote-sensing image data of underground water-shortage areas, and obtain a crop dominance map according to the remote sensing classification of crop planting in large areas; The adjustment module is used to synthesize the distribution map of key groundwater water shortage areas and the crop dominance map to obtain crop planting adjustment guidance results. 6. An electronic device comprising a memory, a processor and a computer program stored on the memory and operable on the processor, wherein the processor according to claim 1 is implemented when executing the program. A method for monitoring and adjusting decision-making of crop planting structure in water-scarce areas described in any one of 4 to 4. 7. A non-transitory computer-readable storage medium on which a computer program is stored, wherein the computer program is implemented when the computer program is executed by a processor to plant crops in water-scarce areas as claimed in any one of claims 1 to 4. Methods for structural monitoring and adjustment decision-making.

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