CN115271343A - Method and system for monitoring and adjusting decision of crop planting structure in water-deficient area - Google Patents
Method and system for monitoring and adjusting decision of crop planting structure in water-deficient area Download PDFInfo
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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
Technical Field
The invention relates to the technical field of agricultural remote sensing, in particular to a method and a system for monitoring and adjusting decision of a crop planting structure in a water-deficient area.
Background
For a long time, people generally adopt artificial irrigation to develop land resources, but the existing cultivated land area is limited, especially in arid or semi-arid regions, large-area artificial cultivation and extensive farmland flood irrigation consume a large amount of water resources and cause large-area water and salt migration, recombination and accumulation in the regions, so that the high-yield farming and pasturing land area in the regions is in a sharp reduction situation. Therefore, effective monitoring of the acreage must be performed to guide reasonable crop planting configuration adjustments.
The current crop planting structure adjustment mainly depends on manual statistics of reported data, and on one hand, spatial position information of specific fields does not exist, and on the other hand, spatial coupling superposition analysis of groundwater water shortage change is lacked. The reported data is counted manually, so that the problems of low efficiency and low accuracy are obvious.
Aiming at the defects, a new method for guiding the crop planting in the water shortage area needs to be provided.
Disclosure of Invention
The invention provides a method and a system for monitoring and adjusting decision-making of a crop planting structure in a water shortage area, which are used for solving the defects that the adjustment guidance of the crop planting structure in the water shortage area mainly depends on manpower, and the efficiency and the accuracy are not high in the prior art.
In a first aspect, the present invention provides a method for monitoring and adjusting decision of crop planting structure in water-deficient areas, comprising:
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.
According to the method for monitoring and adjusting decision of the crop planting structure in the water shortage area, provided by the invention, the method for acquiring the gravity satellite data of the underground water shortage area comprises the following steps:
calling a gravity satellite data set through a Google map engine GEE;
extracting total groundwater reserves data in the gravity satellite data set, and screening relative change data of groundwater average values in a preset time period in the total groundwater reserves data;
converting the relative change data into a preset scale range through interpolation to obtain gravity satellite data of the underground water shortage region;
acquiring underground water observation record data;
carrying out spatial interpolation on the underground water observation record data by adopting a kriging interpolation method to obtain an underground water level distribution time sequence;
and superposing the gravity satellite data of the underground water shortage region and the underground water level distribution time sequence by a three-dimensional visualization and threshold value method, and analyzing to obtain the distribution map of the key underground water shortage region.
According to the method for monitoring and adjusting decision of the crop planting structure in the water shortage area, provided by the invention, the method for acquiring remote sensing image data of the 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 the crop planting in the large area comprises the following steps:
acquiring Zhou Nianna sentinel second image data of different crop planting areas in a first time period and a second time period through GEE;
image splicing, image cutting and preset waveband fusion calculation are carried out on the sentinel second image data in different crop planting areas, and image cloud removal is carried out by adopting the sentinel second preset waveband to obtain initial underground water-deficient area remote sensing image data;
carrying out fusion correction on the remote sensing image data of the initial underground water-deficient area, and carrying out mask processing on the remote sensing image data of the initial underground water-deficient area based on a preset cultivated land range to obtain the remote sensing image data of the underground water-deficient area;
screening third wave band data, fourth wave band data, eighth wave band data and eleventh wave band data of the sentinel second number in the remote sensing image data of the underground water-deficient area, and normalizing vegetation index, enhanced vegetation index, normalized water index, chlorophyll index, soil farming index and normalized farming index to obtain a vegetation index set of the remote sensing image data of the underground water-deficient area;
dividing the vegetation index set of the remote sensing image data of the underground water-deficient area into a large-area crop planting remote sensing data set based on the monthly time sequence combination of Zhou Nianna in the first time period and the second time period;
and classifying the large-area crop planting remote sensing data set by adopting a random forest classification method to obtain a large-area crop planting classification result.
According to the method for guiding the crop planting in the water shortage area, provided by the invention, the method for obtaining the remote sensing image data of the 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 the crop planting in the large area to obtain the crop dominance degree graph comprises the following steps:
cutting and dividing the large-area crop planting classification result, and outputting different crop planting areas;
respectively calculating the ratio of the planting area of the different crops to the total cultivated area to obtain the ratio of the planting area of the different crops;
and drawing and outputting the crop dominance degree graph according to the different crop planting area occupation ratios.
In a second aspect, the present invention further provides a system for monitoring and adjusting decision of crop planting structure in water-deficient areas, comprising:
the first processing module is used for acquiring gravity satellite data of the underground water shortage region and combining underground water bit data space interpolation calculation to obtain an underground water key water shortage region distribution map;
the second processing module is used for acquiring remote sensing image data of the underground water-deficient area, carrying out vegetation index selection calculation on the remote sensing image data of the underground water-deficient area and carrying out remote sensing classification according to large-area crop planting to obtain a crop dominance degree map;
and the adjusting module is used for 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 adjusting guidance result.
In a third aspect, the present invention further provides an electronic device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement any one of the above methods for monitoring and adjusting decision of crop planting structure in water-deficient areas.
In a fourth aspect, the present invention also provides a non-transitory computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements a method for monitoring and adjusting decision-making for crop planting structures in water deficit regions as described in any one of the above.
In a fifth aspect, the present invention also provides a computer program product comprising a computer program, which when executed by a processor, implements a method for monitoring and adjusting decision-making of crop planting structures in water deficit regions as described in any one of the above.
According to the method and the system for monitoring and adjusting the decision of the crop planting structure in the water shortage area, provided by the invention, by utilizing multi-source remote sensing data, aiming at the groundwater shortage area, the groundwater level and other water lines, the rapid decline of groundwater and the remote sensing monitoring of the crop planting dominance degree are integrated, the crop planting decision is assisted, the efficiency of the remote sensing monitoring and decision of the crop planting dominance degree in the large area can be improved, and a powerful technical support is provided for reducing and controlling agricultural water and slowing down the decline trend of the groundwater level.
Drawings
In order to more clearly illustrate the technical solutions of the present invention or the prior art, the drawings needed for the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and those skilled in the art can also obtain other drawings according to the drawings without creative efforts.
FIG. 1 is a schematic flow chart of a method for monitoring and adjusting decision of a crop planting structure in a water-deficient area, provided by the invention;
FIG. 2 is a second schematic flow chart of the method for monitoring and adjusting decision of crop planting structure in water-deficient areas according to the present invention;
FIG. 3 is a schematic structural diagram of a system for monitoring and adjusting decision of crop planting structure in a water-deficient area, provided by the invention;
fig. 4 is a schematic structural diagram of an electronic device provided in the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention clearer, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings, and it is obvious that the described embodiments are some, but not all embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Aiming at the defects of the prior art, the invention excavates multi-space-time remote sensing image information and carries out statistical analysis through a Google Earth Engine (GEE) remote sensing large data platform, thereby providing reference for remote sensing monitoring of crop planting system and adjustment of planting structure in arid and semiarid region field scale.
Fig. 1 is a schematic flow chart of a method for monitoring and adjusting decision of a crop planting structure in a water-deficient area, as shown in fig. 1, including:
step 100: 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;
step 200: 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;
step 300: 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.
According to the invention, the original data processing of the water shortage area is respectively carried out through two branches, one is that GRACE gravity satellite data is adopted to invert the underground water reserve change in recent years, underground water level spatial interpolation is carried out by combining underground water level data of an underground water observation station, and underground water key water shortage area distribution maps which need key attention, such as an underground water funnel area, an underground water fast descending area and the like, are obtained; and secondly, aiming at the water shortage area, acquiring second-number influence data of the sentinel in the large area by adopting a GEE remote sensing large data platform, finishing image cloud removing operation by relying on QA60 wave band of the second-number sentinel in the GEE platform, selecting and calculating a certain number of vegetation indexes and partial wave band data in the second-number sentinel data in combination with the planting condition of regional crops to form a characteristic set, combining image data in a specified time period as a time sequence remote sensing data collection, and supervising and classifying the range of the target area by adopting a random forest algorithm to obtain a crop dominance map.
And (3) integrating the obtained distribution diagram of the key water shortage area of the underground water and the crop dominance degree diagram, comparing and analyzing the crop dominance degree diagram with the distribution of the groundwater equal water level line and the underground water level rapid descending area, assisting the crop planting adjustment decision of different areas and making thematic maps.
It should be noted that the GEE platform has a global remote sensing database, provides a cloud platform capable of performing online visual computation and analysis processing, and can access data in satellite images and other earth observation data databases and provide sufficient computing power to process the data, and the GEE can rapidly process a large number of images in batches. With the development of satellite gravity detection technology, a new observation means is provided for the earth gravity field with high precision and high space-time resolution, so that the monitoring of the total storage capacity of the global underground water and the change thereof by utilizing the earth time-varying gravity field becomes possible. The earth gravity field is a basic physical field which reflects the density distribution and motion state of substances on the surface layer and inside the earth, the change of the earth gravity field reflects the mass transfer and redistribution of fluid of an earth system, including atmosphere, ocean, land water and the like, after the mass of the atmosphere, the ocean, surface water and glaciers is deducted, the rest mainly reflects the total storage capacity of the land underground water, and the storage capacity change of the underground water can be monitored by using a GRACE satellite.
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 degree remote sensing monitoring aiming at groundwater shortage areas, assists crop planting decision, can improve the efficiency of crop planting dominance degree remote sensing monitoring and decision making in large areas, and provides powerful technical support for reducing and controlling agricultural water consumption and slowing down groundwater level decline.
Based on the above embodiment, the obtaining of gravity satellite data of the underground water shortage region and the calculation of spatial interpolation of underground water bit data to obtain the distribution map of the important underground water shortage region includes:
calling a gravity satellite data set through a Google map engine GEE;
extracting total groundwater reserves data in the gravity satellite data set, and screening relative change data of groundwater average values in a preset time period in the total groundwater reserves data;
converting the relative change data into a preset scale range through interpolation to obtain gravity satellite data of the underground water shortage region;
acquiring underground water observation record data;
performing spatial interpolation on the underground water observation record data by adopting a kriging interpolation method to obtain an underground water level distribution time sequence;
and superposing the gravity satellite data of the underground water shortage region and the underground water level distribution time sequence by a three-dimensional visualization and threshold value method, and analyzing to obtain the distribution map of the key underground water shortage region.
Specifically, the invention calls a GRACE Tellus satellite data set through a GEE platform, and takes total groundwater reserves obtained based on GRACE satellites and relative change data relative to the average value of the previous 10 years as a basic data set for analyzing groundwater level change, wherein dimension division is carried out by taking time resolution as one month and spatial resolution as 0.5 degrees.
And then, acquiring observation record data of the underground water observation points in recent years through underground water level observation stations in various places, counting the conditions of the average value, the variance and the like of discrete underground water observation point data, and analyzing a time change curve.
And then carrying out spatial interpolation on the data of the underground water level value by using a kriging interpolation method, carrying out spatial expression in a GIS (geographic information system) to obtain a time sequence underground water level distribution map so as to calculate the annual average buried depth data of the underground water in the research area. The kriging interpolation method is a method for unbiased optimal estimation of regional variables in a limited region based on a variation function theory and structural analysis, and the application range of the kriging interpolation method is that the regional variables have spatial correlation, namely if the variation function and structural analysis result shows that the regional variables have spatial correlation, the kriging interpolation method can be used for interpolation or extrapolation.
Furthermore, underground water volume change monitoring data of the gravity satellite data and underground water bit data spatial interpolation are compared, and underground water change trends and change conditions are analyzed and monitored. And performing superposition analysis on the two, setting areas with fast groundwater decline and areas with low groundwater level in recent years as important groundwater shortage areas through three-dimensional visualization and threshold value method, and making important water shortage area distribution maps.
According to the invention, the big data of the underground water shortage zone is obtained through the gravity satellite, and the accurate key water shortage zone distribution map can be obtained through preprocessing and analysis.
Based on any one of the above embodiments, the obtaining of the remote sensing image data of the underground water-deficient area, the vegetation index selection calculation of the remote sensing image data of the underground water-deficient area and the remote sensing classification according to the large-area crop planting comprise:
acquiring Zhou Nianna sentinel second image data of different crop planting areas in a first time period and a second time period through GEE;
image splicing, image cutting and preset waveband fusion calculation are carried out on the sentinel second image data in different crop planting areas, and image cloud removal is carried out by adopting the sentinel second preset waveband to obtain initial underground water-deficient area remote sensing image data;
carrying out fusion correction on the remote sensing image data of the initial underground water-deficient area, and carrying out mask processing on the remote sensing image data of the initial underground water-deficient area based on a preset cultivated land range to obtain the remote sensing image data of the underground water-deficient area;
screening third wave band data, fourth wave band data, eighth wave band data and eleventh wave band data of the sentinel second number in the remote sensing image data of the underground water-deficient area, and normalizing vegetation index, enhanced vegetation index, normalized water index, chlorophyll index, soil farming index and normalized farming index to obtain a vegetation index set of the remote sensing image data of the underground water-deficient area;
dividing the vegetation index set of the remote sensing image data of the underground water-deficient area into a large-area crop planting remote sensing data set based on the monthly time sequence combination of Zhou Nianna in the first time period and the second time period;
classifying the large-area crop planting remote sensing data set by adopting a random forest classification method to obtain a large-area crop planting classification result;
cutting and dividing the large-area crop planting classification result, and outputting different crop planting areas;
respectively calculating the ratio of the planting area of the different crops to the total cultivated area to obtain the ratio of the planting area of the different crops;
and drawing and outputting the crop dominance degree graph according to the different crop planting area occupation ratios.
Specifically, the time of 8 months per year is determined as the key time for distinguishing different planted crops according to the crop growth climate calendar, namely 3-8 months and 11-12 months per year, and the 8-month sentinel second image is acquired through the GEE remote sensing data cloud platform to form time sequence characteristics for distinguishing different planted crops.
Just because of the sentinel second image data acquired based on the GEE platform, the image data has better overall quality, is the atmospheric bottom layer reflectivity data subjected to atmospheric correction, and is subjected to orthorectification and sub-pixel level geometric fine correction.
And screening high-quality image data of the internal circumference of the target area through the GEE platform, completing image splicing, image cutting, wave band calculation and fusion calculation in the GEE platform after screening is completed, and performing image cloud removing operation by adopting a QA60 wave band in the sentinel II to obtain the remote sensing image data of the initial underground water-deficient area.
And then downloading and exporting the remote sensing image data of the initial underground water-deficient area to ENVI software for fusion and correction, masking the image of the research area by using the open cultivated land range, removing other areas except cultivated land, finishing image preprocessing and obtaining the remote sensing image data of the underground water-deficient area.
Then, selecting typical representative vegetation indexes from the remote sensing image data of the underground water shortage area for calculation, wherein the typical representative vegetation indexes comprise: normalized Difference Vegetation Index (NDVI), enhanced Vegetation Index (EVI), normalized Difference Water Index (NDWI), chlorophyll Index (Green chlorophyl Vegetation Index, GCVI), soil farming Index (STI), and Normalized farming Index (NDTI).
The NDVI can quantitatively represent photosynthetic capacity, water stress and vegetation productivity, the EVI can reduce soil reflectivity and enhance the contrast between bare land and vegetation, the NDWI is sensitive to the moisture content of the earth surface and is also an important vegetation index for extracting water, the GCVI has strong response to the fertilizer application condition in the farmland range of a target area, and the STI is a reason for identifying the effective index of cultivated land, namely the vegetation index is often used for extracting vegetation or vegetation information and the like.
On the basis of the 6 vegetation indexes, 4 wave band data of B3, B4, B8 and B11 of a sentinel II are additionally selected as a vegetation index set of remote sensing image data of the underground water-deficient area for remote sensing classification of different planting modes.
Further, 8 months of time sequence combination of 11-12 months and 3-8 months and 10 vegetation index (NDVI, EVI, NDWI, GCVI, STI, NDTI6, B3, B4, B8 and B11) characteristics per month are combined, and a total of 80 characteristics are put into a random forest classifier to classify the large-area crop planting.
Taking a southern plain underground water funnel area of a certain area as an example, a random forest algorithm is adopted to classify and investigate different crop planting distribution conditions of crops one season in one year and two seasons in one year, the classification result F1-score of the crops one season in one year reaches 95.97%, the classification result F1-score of the crops two seasons in one year reaches 98.70%, and the remote sensing monitoring requirement of the crop planting distribution on the field scale can be met.
The method defines the dominance degree of crops, namely the ratio of the crop planting area to the total cultivated land area, reflects the proportion of different crop planting systems in a certain range, cuts and segments the remote sensing monitoring result of the crop planting distribution on the field scale by taking a delimited area as a basic unit, counts the classification results of different crops in the delimited area range by using an Arcgis software area tabulation tool, and calculates the dominance degree of the crop planting. It can be understood that the distribution of the crop planting system in different areas can be visually seen on the basis of the divided areas, and a crop planting dominance graph is drawn.
Finally, comparing the crop dominance map with the distribution map of the key water shortage area of the underground water, and combining the information of water level lines such as the underground water and the like, the auxiliary crop planting adjustment decision and suggestion can be provided for achieving the purpose of water-saving planting.
Taking a southern underground water funnel area of a certain plain as an example, comparing field block scale single-season and double-season crop classification results, a one-year and two-season crop dominance map of the certain plain funnel area and a deep-layer underground water burial depth distribution map of the certain plain, it can be seen that the main underground water funnel area crop types are mainly crops one season in one year, the two-season crop dominance degree in one year is lower, but some funnel area crop types are still mainly crops two seasons in one year. In the core area of the underground water funnel area, the proportion of crops in two seasons of one year is large, large agricultural water is needed, the underground water level is not kept favorably, and the planting of the crops in two seasons of one year is reduced by taking the crops as a key management and control area; in the marginal area of the underground water funnel area, the planting proportion of crops in two seasons of one year is slightly smaller, and the underground water level is kept by reducing the planting of the crops in two seasons of one year as a secondary control area.
The second flow diagram of the method for monitoring and adjusting decision-making by using the crop planting structure in the water-deficient area shown in fig. 2 comprises the complete steps of the scheme of the invention:
(1) Acquiring gravity satellite data of an underground water-deficient area and calculating underground water change;
(2) Spatial interpolation of underground water bit data;
(3) Drawing an important water shortage area of underground water;
(4) Acquiring a multi-space-time satellite remote sensing image based on a GEE platform;
(5) Calculating a satellite remote sensing vegetation index;
(6) Remote sensing monitoring is carried out on the planting of the large-area crops;
(7) Making a map of the dominance degree of crop planting on a field scale;
(8) And adjusting and deciding the planting dominance of the crops in the large area.
The invention provides a method for assisting crop planting decision aiming at an underground water shortage area, integrating underground water equal water level lines, quick underground water descending and crop planting dominance remote sensing monitoring, and can improve the efficiency of crop planting dominance remote sensing monitoring and decision making in a large area and provide technical support for reducing and controlling agricultural water and slowing down the descending trend of the underground water level.
The system for monitoring and adjusting the planting structure of the crops in the water-deficient area provided by the invention is described below, and the system for monitoring and adjusting the planting structure of the crops in the water-deficient area described below and the method for monitoring and adjusting the planting structure of the crops in the water-deficient area described above can be correspondingly referred to.
Fig. 3 is a schematic structural diagram of a system for monitoring and adjusting decision of crop planting structure in a water-deficient area, 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 for acquiring gravity satellite data of the underground water shortage region, and combining underground water bit data spatial interpolation calculation to obtain an underground water key water shortage region distribution map; the second processing module 32 is used for acquiring remote sensing image data of the underground water-deficient area, carrying out vegetation index selection calculation on the remote sensing image data of the underground water-deficient area and carrying out remote sensing classification according to large-area crop planting to obtain a crop dominance degree map; the adjusting module 33 is used for integrating the distribution map of the key water shortage area of the underground water and the crop dominance map to obtain a crop planting adjusting 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 degree remote sensing monitoring aiming at groundwater shortage areas, assists crop planting decision, can improve the efficiency of crop planting dominance degree remote sensing monitoring and decision making in large areas, and provides powerful technical support for reducing and controlling agricultural water consumption and slowing down groundwater level decline.
Fig. 4 illustrates a physical structure diagram of an electronic device, which may include, as shown in fig. 4: a processor (processor) 410, a communication Interface 420, a memory (memory) 430 and a communication bus 440, wherein the processor 410, the communication Interface 420 and the memory 430 are communicated with each other via the communication bus 440. The processor 410 may invoke logic instructions in the memory 430 to perform a method of crop planting structure monitoring and adjustment decisions for a water deficit region, the method comprising: 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.
In addition, the logic instructions in the memory 430 may be implemented in the form of software functional units and stored in a computer readable storage medium when the software functional units are sold or used as independent products. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
In another aspect, the present invention also provides a computer program product, the computer program product comprising a computer program, the computer program being stored on a non-transitory computer readable storage medium, wherein when the computer program is executed by a processor, the computer is capable of executing the method for monitoring and adjusting decision of crop planting structure in water shortage area provided by the above methods, the method comprising: 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.
In yet another aspect, the present invention also provides a non-transitory computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements a method for monitoring and adjusting decision-making of crop planting structures in water deficit regions provided by performing the above methods, the method comprising: acquiring gravity satellite data of an underground water shortage region, and combining underground water bit data spatial interpolation calculation to obtain a distribution map of an underground water key water shortage region; 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 above-described embodiments of the apparatus are merely illustrative, and the units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment. One of ordinary skill in the art can understand and implement it without inventive effort.
Through the above description of the embodiments, those skilled in the art will clearly understand that each embodiment can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware. With this understanding in mind, the above-described technical solutions may be embodied in the form of a software product, which can be stored in a computer-readable storage medium such as ROM/RAM, magnetic disk, optical disk, etc., and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the methods described in the embodiments or some parts of the embodiments.
Finally, it should be noted that: the above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (7)
1. A method for monitoring and adjusting decision of crop planting structure in water-deficient areas is characterized by comprising the following steps:
acquiring gravity satellite data of an underground water shortage region, and combining underground water bit data spatial interpolation calculation to obtain a distribution map of an underground water key water shortage region;
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.
2. The method for monitoring and adjusting decision-making of crop planting structure in water deficit region according to claim 1, wherein the obtaining of gravity satellite data of underground water deficit region and the obtaining of distribution map of important water deficit region of underground water in combination with spatial interpolation calculation of ground water bit data comprises:
calling a gravity satellite data set through a Google map engine GEE;
extracting total groundwater reserves data in the gravity satellite data set, and screening relative change data of groundwater average values in a preset time period in the total groundwater reserves data;
converting the relative change data into a preset scale range through interpolation to obtain gravity satellite data of the underground water shortage region;
acquiring underground water observation record data;
performing spatial interpolation on the underground water observation record data by adopting a kriging interpolation method to obtain an underground water level distribution time sequence;
and superposing the gravity satellite data of the underground water shortage region and the underground water level distribution time sequence by a three-dimensional visualization and threshold value method, and analyzing to obtain the distribution map of the key underground water shortage region.
3. The method for monitoring and adjusting decision of crop planting structure in water-deficient area according to claim 1, wherein the steps of obtaining remote sensing image data of underground water-deficient area, carrying out vegetation index selection calculation on the remote sensing image data of underground water-deficient area and carrying out remote sensing classification according to large-area crop planting comprise:
acquiring Zhou Nianna sentinel second image data of different crop planting areas in a first time period and a second time period through GEE;
image splicing, image cutting and preset waveband fusion calculation are carried out on the sentinel second image data in different crop planting areas, and image cloud removal is carried out by adopting the sentinel second preset waveband to obtain initial underground water-deficient area remote sensing image data;
performing fusion correction on the remote sensing image data of the initial underground water shortage region, and performing mask processing on the remote sensing image data of the initial underground water shortage region based on a preset cultivated land range to obtain the remote sensing image data of the underground water shortage region;
screening third wave band data, fourth wave band data, eighth wave band data and eleventh wave band data of the sentinel second number in the remote sensing image data of the underground water-deficient area, and normalizing vegetation index, enhanced vegetation index, normalized water index, chlorophyll index, soil farming index and normalized farming index to obtain a vegetation index set of the remote sensing image data of the underground water-deficient area;
dividing the vegetation index set of the remote sensing image data of the underground water-deficient area into a large-area crop planting remote sensing data set based on the monthly time sequence combination of Zhou Nianna in the first time period and the second time period;
and classifying the large-area crop planting remote sensing data set by adopting a random forest classification method to obtain a large-area crop planting classification result.
4. The method for monitoring and adjusting decision of crop planting structure in water-deficient area according to claim 3, wherein the obtaining of remote sensing image data of underground water-deficient area, the vegetation index selection calculation of the remote sensing image data of underground water-deficient area and the remote sensing classification according to the large area crop planting to obtain the crop dominance map comprises:
cutting and dividing the large-area crop planting classification result, and outputting different crop planting areas;
respectively calculating the ratio of the planting area of the different crops to the total cultivated area to obtain the ratio of the planting area of the different crops;
and drawing and outputting the crop dominance degree graph according to the different crop planting area occupation ratios.
5. A system for monitoring and adjusting decision of crop planting structure in water shortage area is characterized by comprising:
the first processing module is used for acquiring gravity satellite data of the underground water shortage region and combining underground water bit data space interpolation calculation to obtain an underground water key water shortage region distribution map;
the second processing module is used for acquiring remote sensing image data of the underground water-deficient area, carrying out vegetation index selection calculation on the remote sensing image data of the underground water-deficient area and carrying out remote sensing classification according to large-area crop planting to obtain a crop dominance degree map;
and the adjusting module is used for 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 adjusting guidance result.
6. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor when executing the program implements a method of crop planting structure monitoring and adjustment decision making in a water deficit region according to any one of claims 1 to 4.
7. A non-transitory computer readable storage medium having stored thereon a computer program, wherein the computer program when executed by a processor implements a method for crop planting structure monitoring and decision making in a water deficit region according to any one of claims 1 to 4.
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| CN117315486A (en) * | 2023-10-30 | 2023-12-29 | 武汉理工大学 | Channel greenbelt monitoring method and device, electronic equipment and storage medium |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN117315486A (en) * | 2023-10-30 | 2023-12-29 | 武汉理工大学 | Channel greenbelt monitoring method and device, electronic equipment and storage medium |
| CN117315486B (en) * | 2023-10-30 | 2024-05-14 | 武汉理工大学 | Channel greenbelt monitoring method and device, electronic equipment and storage medium |
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