CN116049604A - Method and device for determining locust adAN_SNtive area - Google Patents
Method and device for determining locust adAN_SNtive area Download PDFInfo
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Abstract
The application discloses a method and a device for determining a locust adAN_SNtive area, comprising the following steps: obtaining first life context data of a target area in a first breeding period; the data type of the first life environment data is determined by the growth characteristics of the locust in the first development period; obtaining second habitat data of the target region in a second development period; the data type of the second habitat data is determined by the growth characteristics of the locust in the second development stage; the first development period and the second development period respectively indicate different development stages of the locust; and determining a suitable growth area of the locust in the target area within a preset time period according to the first habitat data, the second habitat data and the locust occurrence data of a plurality of points in the target area, wherein the preset time period comprises a first development period and a second development period. The technical scheme of this application can screen out the part and take place less data of influence to the locust, can make the habitat data quality that this application obtained higher to the accuracy that makes the locust of utilizing this habitat data determination suitable living area is higher.
Description
Technical Field
The application relates to the technical field of computers, in particular to a method and a device for determining a locust adAN_SNtive area.
Background
The occurrence of locusts causes serious harm to the agriculture and animal industry, and can destroy large-area agriculture and animal crops in a short time. For example, grasslands exceeding 667 ten thousand hectares are statistically damaged by grassland locusts each year. Moreover, once grassland grasshopper bursts, many ecological environmental problems, such as grassland desertification, grassland degradation, etc., can be raised. Many measures have been taken to prevent the occurrence of the locusts, but the occurrence of the locusts is affected by various factors, such as grassland locusts affected by various factors of grassland type, weather conditions, soil, topography, etc. And the living area of the locust is huge, so that the monitoring and early warning difficulty of the locust is increased. At present, the monitoring and early warning of the locusts are carried out in a manual investigation mode, the living area of the locusts is large, the area of the area where the locusts possibly occur is also large, and the manual investigation mode can only investigate the locusts sending condition of partial point positions in the target area, so that the living condition of the locusts in the whole area can not be known.
Disclosure of Invention
In order to solve the technical problems, the application provides a method for determining a locust adaptive area in a target area, so as to know the survival condition of the locust in the target area.
In order to achieve the above object, the technical solution provided in the embodiments of the present application is as follows:
the embodiment of the application provides a method for determining a locust adAN_SNtive area, which comprises the following steps:
obtaining first life context data of a target area in a first breeding period; the data type of the first life environment data is determined by the growth characteristics of the locust in the first development period;
obtaining second habitat data of the target region in a second development period; the data type of the second habitat data is determined by the growth characteristics of the locust in the second development stage; the first development period and the second development period respectively indicate different development stages of the locust;
and determining a suitable growth area of the locust in the target area within a preset time period according to the first habitat data, the second habitat data and the locust occurrence data of a plurality of points in the target area, wherein the preset time period comprises a first development period and a second development period.
As a possible implementation manner, the preset time period further includes a third development period, and further includes:
obtaining third habitat data of the target region in a third development period; the data type of the third habitat data is determined by the growth characteristics of the locust in the third development stage;
determining a suitable growth area of the locust in the target area according to the first habitat data, the second habitat data and the locust generation data of a plurality of points in the target area, wherein the method comprises the following steps:
and determining the suitable growth area of the locusts in the target area according to the first habitat data, the second habitat data, the third habitat data and the locusts occurrence data of a plurality of points in the target area.
As a possible embodiment, the first development stage is an egg stage of the locust, the second development stage is a period of the locust, and the third development stage is an adult stage.
As a possible implementation manner, the first life environment data comprises ground surface minimum temperature data of the grasshopper egg period, precipitation data of the grasshopper egg period, soil salinity data of the grasshopper egg period and soil temperature data of the grasshopper egg period; the second habitat data comprises data of minimum temperature of the ground surface of the locusts in the period of the nymphs, data of soil salinity of the locusts in the period of the locusts, data of ground biomass of the locusts in the period of the nymphs and data of precipitation of the locusts in the period of the nymphs; the third habitat data includes adult stage surface temperature data.
As a possible embodiment, the method further includes:
obtaining fourth habitat data of the target area in a preset time period; the fourth habitat data includes elevation data, slope data, soil type data, and vegetation type data;
determining a suitable area of the locust in the target area according to the first habitat data, the second habitat data, the third habitat data and the locust occurrence data of a plurality of points in the target area, comprising:
and determining the suitable growth area of the locusts in the target area according to the first habitat data, the second habitat data, the third habitat data, the fourth habitat data and the locusts occurrence data of a plurality of points in the target area.
As a possible embodiment, the method further includes:
and determining contribution degrees of different data types to the suitable living area according to the first living environment data, the second living environment data, the third living environment data, the fourth living environment data and locust occurrence data of a plurality of points in the target area.
As one possible implementation, the target area includes: typical grasslands and meadow grasslands;
determining contribution degrees of different data types to the suitable living area according to the first living environment data, the second living environment data, the third living environment data, the fourth living environment data and locust occurrence data of a plurality of points in the target area, wherein the contribution degrees comprise:
and determining the contribution degree of different data types to the suitable growth area in the typical grassland and the contribution degree to the suitable growth area in the meadow grassland according to the first habitat data, the second habitat data, the third habitat data, the fourth habitat data and the locust generation data of a plurality of points in the target area.
According to the method for determining the locust adaptive area provided in the above embodiment, the present application further provides a device for determining the locust adaptive area, including:
the first obtaining module is used for obtaining first life environment data of the target area in a first development period; the data type of the first life environment data is determined by the growth characteristics of the locust in the first development period;
the second obtaining module is used for obtaining second habitat data of the target area in a second development period; the data type of the second habitat data is determined by the growth characteristics of the locust in the second development stage; the first development period and the second development period respectively indicate different development stages of the locust;
the determining module is used for determining the suitable growth area of the locust in the target area within a preset time period according to the first habitat data, the second habitat data and the locust generation data of a plurality of points in the target area, wherein the preset time period comprises a first development period and a second development period.
As a possible implementation manner, the preset time period further includes a third development period, and further includes:
the third obtaining module is used for obtaining third habitat data of the target area in a third development period; the data type of the third habitat data is determined by the growth characteristics of the locust in the third development stage;
the determining module is used for determining the suitable growth area of the locusts in the target area according to the first habitat data, the second habitat data, the third habitat data and the locusts occurrence data of a plurality of points in the target area.
As a possible embodiment, the first development stage is an egg stage of the locust, the second development stage is a period of the locust, and the third development stage is an adult stage.
As a possible implementation manner, the first life environment data comprises ground surface minimum temperature data of the grasshopper egg period, precipitation data of the grasshopper egg period, soil salinity data of the grasshopper egg period and soil temperature data of the grasshopper egg period; the second habitat data comprises data of minimum temperature of the ground surface of the locusts in the period of the nymphs, data of soil salinity of the locusts in the period of the locusts, data of ground biomass of the locusts in the period of the nymphs and data of precipitation of the locusts in the period of the nymphs; the third habitat data includes adult stage surface temperature data.
As a possible embodiment, the method further includes:
the fourth obtaining module is used for obtaining fourth habitat data of the target area in a preset time period; the fourth habitat data includes elevation data, slope data, soil type data, and vegetation type data;
the determining module is used for determining the suitable growth area of the locusts in the target area according to the first habitat data, the second habitat data, the third habitat data, the fourth habitat data and the locusts occurrence data of a plurality of points in the target area.
As a possible embodiment, the method further includes:
the contribution degree obtaining module is used for determining contribution degrees of different data types to the suitable living area according to the first living environment data, the second living environment data, the third living environment data, the fourth living environment data and locust generation data of a plurality of points in the target area.
As one possible implementation, the target area includes: typical grasslands and meadow grasslands;
the contribution degree obtaining module is used for determining contribution degrees of different data types to the suitable growth areas in the typical grassland and contribution degrees to the suitable growth areas in the meadow grassland according to the first habitat data, the second habitat data, the third habitat data, the fourth habitat data and the locust generation data of a plurality of points in the target area.
According to the technical scheme, the application has the following beneficial effects:
the embodiment of the application provides a method for determining a locust adAN_SNtive area, which comprises the following steps: obtaining first life context data of a target area in a first breeding period; the data type of the first life environment data is determined by the growth characteristics of the locust in the first development period; obtaining second habitat data of the target region in a second development period; the data type of the second habitat data is determined by the growth characteristics of the locust in the second development stage; the first development period and the second development period respectively indicate different development stages of the locust; and determining a suitable growth area of the locust in the target area within a preset time period according to the first habitat data, the second habitat data and the locust occurrence data of a plurality of points in the target area, wherein the preset time period comprises a first development period and a second development period.
Therefore, according to the method for determining the locust adaptive growth zone, the first habitat data in the first development period and the second habitat data in the second development period are obtained through the growth characteristics of the locust in the first development period and the second development period. And then, according to the first habitat data and the second habitat data, determining the suitable habitat area of the locust in the target area within a preset time period, so that the survival condition of the locust in the whole area can be known. Further, according to the technical scheme, according to different development stages of the locust, data affecting the locust in the stage are determined, and compared with the situation that the habitat data are directly collected, the data with small influence on the locust by parts can be screened out. For example, the data type a may have a larger effect on only the locust in the first development period, and the data type a may be collected as the first habitat data only in the first development period, and the data a may not be included in the second habitat data corresponding to the second development period. Therefore, the quality of the habitat data obtained by the method is higher, and the accuracy of determining the locust suitable growth area by using the habitat data is higher.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, and it is obvious that the drawings in the following description are some embodiments of the present application, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a flowchart of a method for determining a locust adaptive area according to an embodiment of the present application;
FIG. 2 is a schematic diagram of contribution of different data types to a suitable area in a meadow grassland according to an embodiment of the present application;
FIG. 3 is a schematic diagram of contribution of different data types to a suitable area in a typical grassland according to an embodiment of the present application;
fig. 4 is a schematic diagram of a method for determining a locust adaptive area according to an embodiment of the present application;
fig. 5 is a schematic diagram of a device for determining a locust adaptive area according to an embodiment of the present application.
Detailed Description
In order to better understand the solution provided by the embodiments of the present application, before describing the method provided by the embodiments of the present application, a scenario of application of the solution of the embodiments of the present application is described.
The occurrence of grasslands and locusts causes serious harm to the agriculture and animal husbandry, and can destroy large-area agriculture and animal husbandry crops in a short time. It is counted that grasslands exceeding 667 ten thousand hectares per year are damaged by grassland locusts. Moreover, once grassland grasshopper bursts, many ecological environmental problems, such as grassland desertification, grassland degradation, etc., can be raised. At present, many measures are taken to prevent grassland locusts from happening, but the grassland locusts are affected by various factors such as grassland types, meteorological conditions, soil, topography and the like, and the grassland area is huge, so that the monitoring and early warning difficulty of the grassland locusts is increased. At present, the monitoring and early warning of grassland locusts are carried out mostly through a manual investigation mode, but the grassland area of China is wide, the grassland locusts are huge in generation area, and the manual investigation mode can only investigate the locusts at partial point positions in the grassland, so that the locusts in the whole area are not known.
In order to solve the above technical problems, an embodiment of the present application provides a method for determining a locust adaptive area, including: obtaining first life context data of a target area in a first breeding period; the data type of the first life environment data is determined by the growth characteristics of the locust in the first development period; obtaining second habitat data of the target region in a second development period; the data type of the second habitat data is determined by the growth characteristics of the locust in the second development stage; the first development period and the second development period respectively indicate different development stages of the locust; and determining a suitable growth area of the locust in the target area within a preset time period according to the first habitat data, the second habitat data and the locust occurrence data of a plurality of points in the target area, wherein the preset time period comprises a first development period and a second development period.
Therefore, according to the method for determining the locust adaptive growth zone, the first habitat data in the first development period and the second habitat data in the second development period are obtained through the growth characteristics of the locust in the first development period and the second development period. That is, according to the technical scheme of the application, according to different development stages of the locust, the data affecting the locust in the stage is determined, and compared with the data directly collecting habitat, the data with small influence on the locust by the part can be screened out by the technical scheme of the application. For example, the data type a may have a larger effect on only the locust in the first development period, and the data type a may be collected as the first habitat data only in the first development period, and the data a may not be included in the second habitat data corresponding to the second development period. Therefore, the quality of the habitat data obtained by the method is higher, and the accuracy of determining the locust suitable growth area by using the habitat data is higher.
In order to make the above objects, features and advantages of the present application more comprehensible, embodiments accompanied with figures and detailed description are described in further detail below.
Referring to fig. 1, a flowchart of a method for determining a locust-like zone is provided.
As shown in fig. 1, the method for determining a locust adaptive area provided in the embodiment of the present application includes:
s101: obtaining first life context data of a target area in a first breeding period; the data type of the first life data is determined by the growth characteristics of the locust in the first development stage.
It should be noted that, the first life data in the embodiment of the present application may include various types of data during the first development period, such as precipitation data, soil salinity data, soil temperature data, ground minimum temperature data, ground biomass data, ground average temperature data, altitude data, gradient data, slope data, soil type data, and vegetation type data. The types of habitat data affecting the locust are different at different stages of its development. Thus, the present application can determine habitat data affecting the locust in the first development stage of the locust based on the growth characteristics of the locust in the first development stage. The first development stage indicates a development stage of the locust, and as an example, may be any one of an egg stage, an nymph stage, and an adult stage of the locust.
S102: obtaining second habitat data of the target region in a second development period; the data type of the second habitat data is determined by the growth characteristics of the locust in the second development stage; the first development stage and the second development stage respectively indicate different development stages of the locust.
It should be noted that the second habitat data in the embodiments of the present application may include various types of data during the second development period, such as precipitation data, soil salinity data, soil temperature data, ground minimum temperature data, ground biomass data, ground average temperature data, altitude data, gradient data, slope data, soil type data, and vegetation type data. The types of habitat data affecting the locust are different at different stages of its development. Thus, the present application can determine habitat data affecting the locust in the second developmental stage of the locust based on the growth characteristics of the locust in the second developmental stage. The second development stage indicates one of the development stages of the locust, and as an example, may be any one of the egg stage, the nymph stage, and the adult stage of the locust.
S103: and determining a suitable growth area of the locust in the target area within a preset time period according to the first habitat data, the second habitat data and the locust occurrence data of a plurality of points in the target area, wherein the preset time period comprises a first development period and a second development period.
It should be noted that, in the embodiment of the present application, locust generation data of multiple points in the target area may be acquired manually. When the locust is found to occur at the point by manpower, that is, the locust exists, or the locust density is larger than the preset density, the locust is judged to occur at the point. The preset time period in the embodiment of the present application may be one year. Because of the difference of the environmental factors such as the annual climate of the target area, the method can be used for respectively calculating the adAN_SNtive areas of the locusts in the area, so that the method can be used for exploring the change of the adAN_SNtive areas of the locusts in the time dimension, and is beneficial to the prevention and control of the locusts by related personnel.
The suitable growth area of the locust obtained in the embodiment of the application indicates the distribution condition of the locust in the area within the preset time period, so that technicians can know the survival condition of the locust in the whole area. Further, according to the technical scheme, the data of the locust influencing in the stage are determined according to different development stages of the locust, and compared with the data of the habitat directly collected, the data of the locust influencing in the stage can be screened out. For example, the data type a may have a larger effect on only the locust in the first development period, and the data type a may be collected as the first habitat data only in the first development period, and the data a may not be included in the second habitat data corresponding to the second development period. Therefore, the quality of the habitat data obtained by the method is higher, and the accuracy of determining the locust suitable growth area by using the habitat data is higher.
In the embodiment of the application, the growth stage of the locust can be further divided into three development stages. The preset time period in the present application may also include a third development period. The method and the device can obtain the third habitat data of the target area in the third development period; the data type of the third habitat data is determined by the growth characteristics of the locust in the third development stage. And then determining the suitable growth area of the locusts in the target area according to the first habitat data, the second habitat data, the third habitat data and the locusts occurrence data of a plurality of points in the target area. As an example, the first development stage is an egg stage of the locust, the second development stage is an nymph stage of the locust, and the third development stage is an adult stage.
In practical applications, the first life-time data may include ground surface minimum temperature data of the locust egg stage, precipitation data of the locust egg stage, soil salinity data of the locust egg stage, and soil temperature data of the locust egg stage. The second habitat data may include ground surface minimum temperature data of the locusts, soil salinity data of the locusts, ground biomass data of the locusts, and precipitation data of the locusts. The third habitat data may include adult stage surface temperature data.
As a possible implementation manner, the embodiment of the present application may further obtain fourth habitat data of the target area within the preset time period. Specifically, the fourth habitat data includes elevation data, grade data, slope data, soil type data, and vegetation type data. Accordingly, the embodiment of the application can determine the suitable growth area of the locust in the target area according to the first habitat data, the second habitat data, the third habitat data, the fourth habitat data and the locust generation data of a plurality of points in the target area. It should be noted that, the fourth habitat data generally has a full-stage effect on the locust, so the fourth habitat data may be obtained in the whole preset period of time instead of determining the time for obtaining the fourth habitat data according to the growth stage of the locust.
As a possible implementation manner, the embodiment of the present application may further determine contribution degrees of different data types to the suitable living area according to the first living environment data, the second living environment data, the third living environment data, the fourth living environment data, and locust occurrence data of multiple points in the target area. In this way, the data types in the first and second habitat data in step S101 and step S102 may be optimized according to the contribution degrees of different data types to the adaptive region.
As one possible implementation manner, the adaptive region provided in the embodiment of the present application includes: typical grasslands and meadow grasslands. According to the embodiment of the application, the contribution degree of different data types to the suitable area in the typical grassland and the contribution degree to the suitable area in the meadow grassland are determined according to the first habitat data, the second habitat data, the third habitat data, the fourth habitat data and the locust generation data of a plurality of points in the target area.
As shown in fig. 2, a schematic diagram of contribution degrees of different data types to an adaptive region in meadow grassland is provided in the embodiment of the present application.
As shown in fig. 3, a schematic diagram of contribution of different data types to a suitable area in a typical grassland is provided in an embodiment of the present application.
As shown in fig. 2 and 3, the abscissa in the schematic diagrams represents different data types, the ordinate is the contribution degree (in percentage), and five histograms are corresponding to each data type on the ordinate, and the five histograms represent the contribution degrees of 2018, 2019, 2020, 20201 and 2022 from left to right respectively. Wherein the abscissa includes minimum temperature of locust egg period (EMinLST), minimum temperature of locust bean period (NMinLST), precipitation of locust egg period (EPre), soil salinity of locust egg period (ESI), soil temperature of locust egg period (EST), soil salinity of locust bean period (NSI), overground biomass of locust bean period (NAB), precipitation of locust bean period (NPre), surface average temperature of adult period (ameannlst), altitude (Elevation), slope (Slope), slope direction (Aspect), soil type (Soiltype) and vegetation type (Vegtype).
To explore the differences in the major influencing factors (data types) affecting typical grasslands and meadow grasslands, the present application may perform a knife cut test on the importance of each factor and consider factors that cumulatively contribute more than 80% as the major influencing factors. The estimation of the relative percentage contribution of all environmental variables suggests that the main influencing factors have differences in two grasslands and different years. The same factors that play an important role in grassland locust development are also among the data factors. In meadow grasslands, EST, vegetation type, soil type and slope direction are important factors affecting grassland locust habitat distribution for five years. As shown in FIGS. 2 and 3, ESTs are the most important factors affecting the regions of metaplasia in 2021 and 2022, accounting for 36% and 32.8%, respectively. In 2018 and 2022, vegetation type is the second major contributor. Soil type at 2021 is also a second important contributor. In addition to 2021, NPre also makes an important contribution, with NPre being the largest contributor in 2019. Altitude also has a significant impact on grassland locust development in 2018, 2019 and 2020, even the highest contribution in 2018 and the second contribution in 2019. AMeanLST, EMinLST, ESI and EPre have had effects on 2019, 2018, 2020 and 2022, respectively. In particular, in 2020, ESI contributed most. In a typical grassland, vegetation type, EST, soil type and NPre are important factors affecting grassland locust distribution within 5 years. Furthermore, vegetation types contribute second in 2018, 2019, 2020, and 2021. The EST contribution is greatest at 2021. NPre was top in 2018 and 2020. Furthermore, epre also contributes most to the contributions in 2019 and 2022. In 2018, 2020 and 2022, altitude is an important factor. In 2018 to 2022, EST, vegetation type and soil type are all important factors for meadow and typical grasslands, compared to the contribution of this factor in meadow and typical grasslands. NPre is also considered an important factor for both meadows, as it has no significant effect on meadow only at 2021. However, there is also a difference between these two grasslands. For topographical factors, slope plays a more important role in meadow prairies, while the effect of slope is more pronounced in typical prairies. For meteorological factors, EPre contributes more in typical grasslands.
Referring to fig. 4, a schematic diagram of a method for determining a locust adaptive area according to an embodiment of the present application is shown.
As shown in fig. 4, the method for determining the grasshopper suitable area provided by the embodiment of the application can extract raw data of four aspects of weather, soil, vegetation and topography from the weather data, the remote sensing data and the topography data. And screening out the habitat data corresponding to each locust development period from the original data according to a plurality of locust development periods, such as the locust egg period (egg), the locust nymph period (locust nymph period) and the adult period (adult). The types of habitat data may include surface temperature, precipitation, soil salinity, soil type, vegetation type, above-ground biomass, elevation, slope, and slope. And then carrying out correlation calculation on the obtained habitat data, removing data types with too high correlation, and inputting the rest data into a Maxent (maximum entropy) model to obtain main influencing factors of grassland locust adaptation area spatial distribution characteristics, grassland locust adaptation area time distribution characteristics, typical grasslands and meadow grasslands. The technician can adjust grassland locust prevention and control according to the data.
According to the method for determining the locust adaptive growth zone, through the growth characteristics of the locust in the first development period and the locust in the second development period, the first habitat data in the first development period and the second habitat data in the second development period are obtained. That is, according to the technical scheme of the application, according to different development stages of the locust, the data affecting the locust in the stage is determined, and compared with the data directly collecting habitat, the data with small influence on the locust by the part can be screened out by the technical scheme of the application. Therefore, the quality of the habitat data obtained by the method is higher, and the accuracy of determining the locust suitable growth area by using the habitat data is higher. In addition, the change trend of the locust suitable area in the target area can be known according to the distribution of the locust suitable area in the target area in a plurality of time periods. The contribution degree of different data types to the suitable region in the typical grassland or meadow grassland can be generated, so that the optimization of the data types in the habitat data is facilitated.
According to the method for determining the locust adaptive area provided by the embodiment, the application also provides a device for determining the locust adaptive area.
Referring to fig. 5, the diagram is a schematic diagram of a device for determining a locust adapting area according to an embodiment of the present application.
As shown in FIG. 5, the device for determining the locust-suitable area provided by the present application comprises:
a first obtaining module 100 for obtaining first life context data of a target region in a first development period; the data type of the first life environment data is determined by the growth characteristics of the locust in the first development period;
a second obtaining module 200 for obtaining second habitat data of the target area during a second development period; the data type of the second habitat data is determined by the growth characteristics of the locust in the second development stage; the first development period and the second development period respectively indicate different development stages of the locust;
the determining module 300 is configured to determine, according to the first habitat data, the second habitat data, and the locust occurrence data of a plurality of points in the target area, a suitable growth area of the locust in a preset time period in the target area, where the preset time period includes a first development period and a second development period.
As a possible implementation manner, the preset time period further includes a third development period, and further includes: the third obtaining module is used for obtaining third habitat data of the target area in a third development period; the data type of the third habitat data is determined by the growth characteristics of the locust in the third development stage; the determining module is used for determining the suitable growth area of the locusts in the target area according to the first habitat data, the second habitat data, the third habitat data and the locusts occurrence data of a plurality of points in the target area.
As a possible embodiment, the first development stage is an egg stage of the locust, the second development stage is a period of the locust, and the third development stage is an adult stage.
As a possible implementation manner, the first life environment data comprises ground surface minimum temperature data of the grasshopper egg period, precipitation data of the grasshopper egg period, soil salinity data of the grasshopper egg period and soil temperature data of the grasshopper egg period; the second habitat data comprises data of minimum temperature of the ground surface of the locusts in the period of the nymphs, data of soil salinity of the locusts in the period of the locusts, data of ground biomass of the locusts in the period of the nymphs and data of precipitation of the locusts in the period of the nymphs; the third habitat data includes adult stage surface temperature data.
As a possible embodiment, the method further includes: the fourth obtaining module is used for obtaining fourth habitat data of the target area in a preset time period; the fourth habitat data includes elevation data, grade data, slope data, soil type data, and vegetation type data. The determining module is used for determining the suitable growth area of the locusts in the target area according to the first habitat data, the second habitat data, the third habitat data, the fourth habitat data and the locusts occurrence data of a plurality of points in the target area.
As a possible embodiment, the method further includes: the contribution degree obtaining module is used for determining contribution degrees of different data types to the suitable living area according to the first living environment data, the second living environment data, the third living environment data, the fourth living environment data and locust generation data of a plurality of points in the target area.
As one possible implementation, the target area includes: typical grasslands and meadow grasslands; the contribution degree obtaining module is used for determining contribution degrees of different data types to the suitable growth areas in the typical grassland and contribution degrees to the suitable growth areas in the meadow grassland according to the first habitat data, the second habitat data, the third habitat data, the fourth habitat data and the locust generation data of a plurality of points in the target area.
According to the determining device for the locust suitable growth area, through the growth characteristics of the locust in the first development period and the locust in the second development period, the first habitat data in the first development period and the second habitat data in the second development period are obtained. That is, according to the technical scheme of the application, according to different development stages of the locust, the data affecting the locust in the stage is determined, and compared with the data directly collecting habitat, the data with small influence on the locust by the part can be screened out by the technical scheme of the application. Therefore, the quality of the habitat data obtained by the method is higher, and the accuracy of determining the locust suitable growth area by using the habitat data is higher. In addition, the change trend of the locust suitable area in the target area can be known according to the distribution of the locust suitable area in the target area in a plurality of time periods. The contribution degree of different data types to the suitable region in the typical grassland or meadow grassland can be generated, so that the optimization of the data types in the habitat data is facilitated.
From the above description of embodiments, it will be apparent to those skilled in the art that all or part of the steps of the above described example methods may be implemented in software plus necessary general purpose hardware platforms. Based on such understanding, the technical solutions of the present application may be embodied essentially or in a part contributing to the prior art in the form of a software product, which may be stored in a storage medium, such as a ROM/RAM, a magnetic disk, an optical disk, etc., including several instructions to cause a computer device (which may be a personal computer, a server, or a network communication device such as a media gateway, etc.) to perform the methods described in the embodiments or some parts of the embodiments of the present application.
It should be noted that, in the present description, each embodiment is described in a progressive manner, and each embodiment is mainly described in a different manner from other embodiments, and identical and similar parts between the embodiments are all enough to refer to each other. For the method disclosed in the embodiment, since it corresponds to the system disclosed in the embodiment, the description is relatively simple, and the relevant points refer to the system part.
It should also be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
The foregoing description of the disclosed embodiments, as well as many modifications to those embodiments to enable any person skilled in the art to make or use the disclosure, will be readily apparent to those of ordinary skill in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the disclosure. Thus, the present application is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (10)
1. A method for determining a suitable area of a locust, comprising:
obtaining first life context data of a target area in a first breeding period; the data type of the first life environment data is determined by the growth characteristics of the locust in the first development period;
obtaining second habitat data of the target region in a second development period; the data type of the second habitat data is determined by the growth characteristics of the locust in the second development period; the first development stage and the second development stage respectively indicate different development stages of the locust;
and determining a suitable growth area of the locust in a preset time period in the target area according to the first habitat data, the second habitat data and the locust occurrence data of a plurality of points in the target area, wherein the preset time period comprises the first development period and the second development period.
2. The method of claim 1, wherein the preset time period further comprises a third development period, further comprising:
obtaining third habitat data of the target region in a third development period; the data type of the third habitat data is determined by the growth characteristics of the locust in the third development stage;
the determining the suitable growth area of the locust in the target area according to the first habitat data, the second habitat data and the locust generation data of a plurality of points in the target area comprises:
and determining a suitable growth area of the locusts in the target area according to the first habitat data, the second habitat data, the third habitat data and the locusts occurrence data of a plurality of points in the target area.
3. The method of claim 2, wherein the first developmental stage is an egg stage of a locust, the second developmental stage is an nymph stage of a locust, and the third developmental stage is an adult stage.
4. A method according to claim 3, wherein the first habitat data comprises ground surface minimum temperature data of the egg stage of the locust, precipitation data of the egg stage of the locust, soil salinity data of the egg stage of the locust and soil temperature data of the egg stage of the locust; the second habitat data comprises ground surface minimum temperature data of the locusts in the period of the locusts, soil salinity data of the locusts in the period of the locusts, ground biomass data of the locusts in the period of the locusts and precipitation data of the locusts in the period of the locusts; the third habitat data includes adult stage surface temperature data.
5. The method as recited in claim 2, further comprising:
obtaining fourth habitat data of the target area in the preset time period; the fourth habitat data includes elevation data, grade data, slope data, soil type data, and vegetation type data;
the determining the suitable growth area of the locust in the target area according to the first habitat data, the second habitat data, the third habitat data and the locust generation data of a plurality of points in the target area comprises:
and determining a suitable growth area of the locusts in the target area according to the first habitat data, the second habitat data, the third habitat data, the fourth habitat data and the locusts occurrence data of a plurality of points in the target area.
6. The method as recited in claim 5, further comprising:
and determining contribution degrees of different data types to the suitable living area according to the first living environment data, the second living environment data, the third living environment data, the fourth living environment data and locust generation data of a plurality of points in the target area.
7. The method of claim 6, wherein the target region comprises: typical grasslands and meadow grasslands;
the determining the contribution degree of different data types to the suitable living area according to the first living environment data, the second living environment data, the third living environment data, the fourth living environment data and locust generation data of a plurality of points in the target area comprises the following steps:
determining contribution degrees of different data types to the suitable living areas in the typical grassland and contribution degrees of different data types to the suitable living areas in the meadow grassland according to the first habitat data, the second habitat data, the third habitat data, the fourth habitat data and locust generation data of a plurality of points in the target area.
8. A device for determining a suitable area for a locust, comprising:
the first obtaining module is used for obtaining first life environment data of the target area in a first development period; the data type of the first life environment data is determined by the growth characteristics of the locust in the first development period;
the second obtaining module is used for obtaining second habitat data of the target area in a second development period; the data type of the second habitat data is determined by the growth characteristics of the locust in the second development period; the first development stage and the second development stage respectively indicate different development stages of the locust;
the determining module is used for determining the suitable growth area of the locust in the target area within a preset time period according to the first habitat data, the second habitat data and the locust occurrence data of a plurality of points in the target area, and the preset time period comprises the first development period and the second development period.
9. The apparatus of claim 8, wherein the preset time period further comprises a third development period, further comprising:
the third obtaining module is used for obtaining third habitat data of the target area in a third development period; the data type of the third habitat data is determined by the growth characteristics of the locust in the third development stage;
the determining module is configured to determine a suitable growth area of the locust in the target area according to the first habitat data, the second habitat data, the third habitat data, and the locust occurrence data of a plurality of points in the target area.
10. The device of claim 9, wherein the first developmental stage is an egg stage of a locust, the second developmental stage is an nymph stage of a locust, and the third developmental stage is an adult stage.
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