CN115762062B

CN115762062B - Kiwi fruit garden meteorological disaster monitoring and early warning method and device

Info

Publication number: CN115762062B
Application number: CN202211393504.5A
Authority: CN
Inventors: 王景红; 张维敏; 李化龙; 柏秦凤; 郭建平
Original assignee: Shaanxi Provincial Agricultural Remote Sensing And Economic Crops Meteorological Service Center
Current assignee: Shaanxi Provincial Agricultural Remote Sensing And Economic Crops Meteorological Service Center
Priority date: 2022-11-08
Filing date: 2022-11-08
Publication date: 2024-01-23
Anticipated expiration: 2042-11-08
Also published as: CN115762062A

Abstract

The application provides a method and a device for monitoring and early warning weather disasters in a kiwi fruit garden, wherein predicted weather data in a future preset time period, which are obtained by predicting weather observation stations corresponding to a target area, are obtained through each interval of preset time length, so that kiwi fruit canopy temperature data in the future preset time period are obtained according to the predicted weather data and a kiwi fruit canopy temperature prediction model, then predicted temperature data of a target position on a kiwi fruit tree in the future preset time period are obtained according to the kiwi fruit canopy temperature data and a kiwi fruit target position temperature prediction model, and disaster information of the target position on the kiwi fruit tree in the kiwi fruit garden in the future preset time period is determined according to the predicted temperature data of the target position on the kiwi fruit tree and the corresponding relation between disaster grades of the target position on the kiwi fruit tree and the temperature range. The method realizes the timely and accurate prediction of the weather disaster information of the kiwi fruits.

Description

Kiwi fruit garden meteorological disaster monitoring and early warning method and device

Technical Field

The application relates to the technical field of kiwi fruit planting, in particular to a kiwi fruit garden meteorological disaster monitoring and early warning method and device.

Background

The planting area of kiwi fruits in Qin mountain areas of Shaanxi province is the largest concentrated good production area of China, the yield and the area of the kiwi fruits account for 1/3 of the total world, the yield of kiwi fruits of Shaanxi reaches 129.43 ten thousand tons by 2021, the planting area of kiwi fruits is 97.94 ten thousand mu, and the kiwi fruit industry is the dominant industry of local income increase and lean and rich increase.

With the increase of climate warming and extreme weather climate events, weather disasters such as high temperature heat injury, freezing injury and the like frequently occur, and the method has the characteristics of wide influence range, long duration and the like, and seriously influences the yield and the fruit quality of the kiwi fruits and influences the income increase of fruit farmers. If the method can forecast, early warn and prompt weather disasters as soon as possible and defend properly, adverse weather factors can be reasonably avoided to the maximum extent during the growth and development of the kiwi fruits, and the aims of high yield, stable yield and high quality are achieved.

At present, many times, a fruit grower still relies on experience and the like to judge whether a weather disaster occurs, and the method for judging whether the weather disaster occurs according to experience is inaccurate, and is difficult to determine the duration of the weather disaster, the influence degree of the weather disaster and the like, so that the fruit grower is difficult to prevent the weather disaster. Therefore, the method and the system can timely, accurately, normally and efficiently perform the early warning service of the kiwi fruit weather disasters, solve the key technical problem of inaccurate early warning of the kiwi fruit disasters, are key to weather disaster prevention, disaster reduction and relief work, and are effective measures for defending and reducing weather disaster losses.

Disclosure of Invention

The application provides a kiwi fruit garden meteorological disaster monitoring and early warning method and device, which solve the key technical problem of inaccurate kiwi fruit disaster early warning.

In a first aspect, the present application provides a method for monitoring and early warning weather disasters in a kiwi fruit garden, including:

acquiring predicted meteorological data in a future preset time period which is predicted by a meteorological observation station and corresponds to a target area at each interval preset time length, wherein the target area contains at least one kiwi fruit garden;

obtaining kiwi fruit canopy temperature data in a future preset time period according to the predicted meteorological data and the kiwi fruit canopy temperature prediction model;

according to the kiwi fruit canopy temperature data and the kiwi fruit target position temperature prediction model, obtaining predicted temperature data of a target position on a kiwi fruit tree in a future preset time period, wherein the kiwi fruit target position temperature prediction model is at least one of the following: a kiwi fruit surface temperature prediction model, a kiwi leaf surface temperature prediction model, a kiwi fruit branch temperature prediction model and a kiwi fruit root neck temperature prediction model;

according to the predicted temperature data of the target position on the kiwi fruit tree and the corresponding relation between the disaster grade of the target position on the kiwi fruit tree and the temperature range, disaster information of the target position on the kiwi fruit tree in the kiwi fruit garden in the target area in a preset time period in the future is determined, wherein the disaster information at least comprises one of the following items: disaster grade, disaster duration, disaster start time.

Optionally, before obtaining the kiwi fruit canopy temperature data in the future preset time period according to the predicted meteorological data and the kiwi fruit canopy temperature prediction model, the method further includes:

acquiring historical meteorological data of a preset sampling time point in a historical time period of a meteorological observation station corresponding to an area where a sample kiwi fruit garden is located, and actually detecting canopy historical temperature on the kiwi fruit tree at the preset sampling time point in the historical time period, wherein the canopy historical temperature comprises at least one of the following components: fruit surface history temperature, leaf surface history temperature, branch history temperature and root neck history temperature;

obtaining a kiwi fruit canopy temperature prediction model according to the historical meteorological data and the canopy historical temperature;

based on the canopy historical temperature and at least one of: the fruit surface historical temperature, the leaf surface historical temperature, the branch historical temperature and the root neck historical temperature are used for obtaining the kiwi fruit target position temperature prediction model.

Optionally, the obtaining, by the weather observation station corresponding to the target area, the predicted weather data in the future preset time period predicted by the weather observation station at each preset interval time period includes:

acquiring predicted meteorological data of a plurality of grid points in the target area within a future preset time period predicted by the meteorological observation station every interval preset time length;

According to the predicted meteorological data and the kiwi fruit canopy temperature prediction model, obtaining kiwi fruit canopy temperature data in a future preset time period comprises the following steps:

obtaining the kiwi fruit canopy temperature data in a future preset time period corresponding to each grid point according to the predicted meteorological data of each grid point in the target area and the kiwi fruit canopy temperature prediction model;

according to the kiwi fruit canopy temperature data and the kiwi fruit target position temperature prediction model, obtaining predicted temperature data of a target position on a kiwi fruit tree in a future preset time period comprises the following steps:

acquiring the predicted temperature data of the target position on the kiwi fruit tree in a future preset time period corresponding to each grid point according to the kiwi fruit canopy temperature data corresponding to each grid point and the kiwi fruit target position temperature prediction model;

according to the predicted temperature data of the target position on the kiwi fruit tree and the corresponding relation between the disaster grade of the target position on the kiwi fruit tree and the temperature range, determining disaster information of the target position on the kiwi fruit tree in the kiwi fruit garden in the target area in a preset time period in the future, including:

And determining disaster information of the target position on the kiwi fruit tree in the kiwi fruit garden corresponding to each grid point in a future preset time period according to the predicted temperature data of the target position on the kiwi fruit tree in the kiwi fruit garden corresponding to each grid point and the corresponding relation between the disaster grade of the target position on the kiwi fruit tree and the temperature range.

Optionally, the method further comprises:

obtaining a disaster prediction distribution diagram of a target position on a kiwi fruit tree in the kiwi fruit garden in the target area according to disaster information of the target position on the kiwi fruit tree in the kiwi fruit garden corresponding to each grid point;

and obtaining a disaster grade prediction distribution color map of the target position on the kiwi fruit tree in the kiwi fruit orchard of the target area according to the actual kiwi fruit orchard distribution map in the target area, the disaster prediction distribution map of the target position on the kiwi fruit tree in the kiwi fruit orchard of the target area and the color code corresponding to the disaster grade of the target position on the kiwi fruit tree.

Optionally, the historical meteorological data detected at a preset sampling time point in a historical time period of a meteorological observation station corresponding to an area where the sample kiwi fruit garden is located, and the actual detected canopy historical temperature on the kiwi fruit tree at the preset sampling time point in the historical time period, and at least one of the following: fruit surface history temperature, leaf surface history temperature, branch history temperature and root neck history temperature, include:

Acquiring historical meteorological data corresponding to different weather types, and actually detected canopy historical temperature on the kiwi fruit tree, wherein the historical temperature is at least one of the following: fruit surface history temperature, leaf surface history temperature, branch history temperature and root neck history temperature;

according to the historical meteorological data and the canopy historical temperature on the kiwi fruit tree, the canopy temperature prediction model of the kiwi fruit garden is obtained, and the method comprises the following steps:

obtaining a kiwi fruit garden canopy temperature prediction model corresponding to different weather types according to historical meteorological data corresponding to different weather types and the actually detected canopy historical temperature on the kiwi fruit tree;

determining a predicted weather type corresponding to the predicted weather data according to the predicted weather data;

determining a kiwi fruit canopy temperature prediction model corresponding to the predicted weather type according to the predicted weather type;

and obtaining the kiwi fruit canopy temperature data in a future preset time period according to the predicted meteorological data and the kiwi fruit canopy temperature prediction model corresponding to the predicted weather type.

Optionally, in summer, the weather type is sunny, cloudy or rainy;

in winter, the weather type is a sunny day and a non-sunny day, wherein the non-sunny day comprises cloudy, rainy and snowy days.

Optionally, determining disaster information of the target position on the kiwi fruit tree in the kiwi fruit garden in the target area in a future preset time period according to the predicted temperature data of the target position on the kiwi fruit tree and the corresponding relation between the disaster level of the target position on the kiwi fruit tree and the temperature range, including:

determining at least one kiwi fruit variety actually planted in the target area;

according to the corresponding relation between each kiwi fruit variety actually planted in the target area, the predicted temperature data of the target position on the kiwi fruit tree and the disaster grade and the temperature range of the target position on the kiwi fruit tree associated with each kiwi fruit variety, determining the disaster information of the kiwi fruit orchard at the target position of each kiwi fruit variety in the target area in a future preset time period.

Optionally, the kiwi fruit canopy temperature prediction model is a unitary linear regression model, the kiwi fruit surface temperature prediction model and the kiwi fruit leaf surface temperature prediction model are both exponential models, the kiwi fruit branch temperature prediction model is a unitary linear regression model, and the kiwi fruit root neck temperature prediction model is a unitary linear regression model.

Optionally, in summer, the kiwi fruit target position temperature prediction model includes: a kiwi fruit surface temperature prediction model and/or a kiwi fruit surface temperature prediction model;

in winter, the kiwi fruit target position temperature prediction model comprises: a kiwi fruit branch temperature prediction model and/or a kiwi fruit root neck temperature prediction model.

In a second aspect, the application provides a kiwi fruit orchard weather disaster monitoring and early warning device, including:

the acquisition module is used for acquiring predicted meteorological data in a future preset time period which is predicted by a meteorological observation station corresponding to a target area every interval preset time length, wherein the target area contains at least one kiwi fruit garden;

the first prediction module is used for obtaining the kiwi fruit canopy temperature data in a future preset time period according to the predicted meteorological data and the kiwi fruit canopy temperature prediction model;

the second prediction module is used for obtaining predicted temperature data of a target position on the kiwi fruit tree in a future preset time period according to the kiwi fruit canopy temperature data and a kiwi fruit target position temperature prediction model, wherein the kiwi fruit target position temperature prediction model is at least one of the following: a kiwi fruit surface temperature prediction model, a kiwi leaf surface temperature prediction model, a kiwi fruit branch temperature prediction model and a kiwi fruit root neck temperature prediction model;

The determining module is used for determining disaster information of the target position on the kiwi fruit tree in the kiwi fruit orchard in the target area in a preset time period in the future according to the predicted temperature data of the target position on the kiwi fruit tree and the corresponding relation between the disaster grade of the target position on the kiwi fruit tree and the temperature range, wherein the disaster information at least comprises one of the following items: disaster grade, disaster duration, disaster start time.

Optionally, the method further comprises: a model training module;

the model training module is used for before the first processing module obtains the kiwi fruit canopy temperature data in a future preset time period according to the predicted meteorological data and the kiwi fruit canopy temperature prediction model:

Optionally, when the obtaining module obtains the predicted meteorological data in the future preset time period predicted by the meteorological station corresponding to the target area in each interval preset time length, the obtaining module is specifically configured to:

the first prediction module is specifically used for obtaining the kiwi fruit canopy temperature data in a future preset time period according to the predicted meteorological data and the kiwi fruit canopy temperature prediction model:

the second prediction module is specifically configured to, when obtaining predicted temperature data of a target position on a kiwi fruit tree within a preset time period in the future according to the kiwi fruit canopy temperature data and a kiwi fruit target position temperature prediction model:

the determining module is used for determining disaster information of a target position on a kiwi fruit tree in a kiwi fruit garden in the target area in a preset time period in the future according to the predicted temperature data of the target position on the kiwi fruit tree and the corresponding relation between the disaster grade of the target position on the kiwi fruit tree and the temperature range, and is specifically used for:

Optionally, the method further comprises: a processing module;

the processing module is used for obtaining a disaster prediction distribution diagram of the target position on the kiwi fruit tree in the kiwi fruit garden in the target area according to the disaster information of the target position on the kiwi fruit tree in the kiwi fruit garden corresponding to each grid point;

Optionally, the model training module obtains historical meteorological data detected at a preset sampling time point in a historical time period of a meteorological observation station corresponding to an area where the sample kiwi fruit garden is located, and the actual detected canopy historical temperature on the kiwi fruit tree at the preset sampling time point in the historical time period and at least one of the following: the fruit surface history temperature, the leaf surface history temperature, the branch history temperature and the root neck history temperature are specifically used for:

the model training module is specifically used for obtaining the kiwi fruit garden canopy temperature prediction model according to the historical meteorological data and the canopy historical temperature on the kiwi fruit tree:

Optionally, in summer, the weather type is sunny, cloudy or rainy;

Optionally, the determining module is configured to determine, according to predicted temperature data of a target position on the kiwi fruit tree and a correspondence between a disaster level of the target position on the kiwi fruit tree and a temperature range, disaster information of the target position on the kiwi fruit tree in the kiwi fruit orchard in the target area within a preset time period in the future, where the determining module is specifically configured to:

In a third aspect, an embodiment of the present application provides an electronic device, including: at least one processor and memory;

the memory stores computer-executable instructions; the at least one processor executes the computer-executable instructions stored in the memory to perform the method according to the preset item in the first aspect of the embodiments of the present application.

In a fourth aspect, an embodiment of the present application provides a computer readable storage medium, where a program instruction is stored, where the program instruction, when executed by a processor, implements a method according to the preset item in the first aspect of an embodiment of the present invention.

In a fifth aspect, embodiments of the present application provide a program product, where the program product includes a computer program stored in a readable storage medium, where at least one processor of an electronic device may read the computer program from the readable storage medium, and where the at least one processor executes the computer program to cause the electronic device to implement a method according to the preset item in the first aspect of the embodiments of the present application.

The beneficial effects of this application are as follows:

according to the method and the device for monitoring and early warning the weather disasters of the kiwi fruit garden, the predicted weather data in the future preset time period, which are obtained through prediction by the weather observation station corresponding to the target area, are obtained through each preset time period, so that the kiwi fruit canopy temperature data in the future preset time period are obtained according to the predicted weather data and the kiwi fruit canopy temperature prediction model, the predicted temperature data of the target position on the kiwi fruit tree in the future preset time period are obtained according to the kiwi fruit canopy temperature data and the kiwi fruit target position temperature prediction model, and the disaster information of the target position on the kiwi fruit tree in the kiwi fruit garden in the target area in the future preset time period is determined according to the predicted temperature data of the target position on the kiwi fruit tree and the corresponding relation between the disaster grade of the target position on the kiwi fruit tree and the temperature range. The method realizes the timely and accurate prediction of the weather disaster information of the kiwi fruits, so that fruit farmers can take preventive measures in advance, and the loss caused by the weather disasters is reduced.

In addition, the embodiment predicts the temperature data of the kiwi fruit crown by predicting the weather data, then obtains the predicted temperature data of the target position on the kiwi fruit tree according to the kiwi fruit crown temperature data, thus, the outside temperature data (namely, the related temperature data detected by the weather observation station) is converted into the small environment inside the kiwi fruit garden by utilizing the kiwi fruit crown temperature data, in the small environment inside the kiwi fruit garden, compared with the outside temperature data, the predicted temperature data of the target position on the kiwi fruit tree has stronger relevance with the kiwi fruit crown temperature data, and the kiwi fruit crown is generally 1.8 meters, compared with the leaf surface, the branch and the root neck position, the kiwi fruit crown temperature has stronger relevance with the outside temperature, therefore, in the embodiment, the predicted kiwi fruit crown temperature is obtained by the kiwi fruit crown temperature prediction model and the predicted weather data, and the predicted kiwi fruit crown temperature of the target position on the kiwi fruit tree is obtained according to the kiwi fruit crown temperature prediction model, so that the obtained predicted temperature data of the target position on the kiwi fruit tree is more accurate.

Drawings

In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, a brief description will be given below of the drawings that are needed in the embodiments or the prior art descriptions, and it is obvious that the drawings in the following description are some embodiments of the present application, and that other drawings can 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 monitoring and early warning weather disasters in a kiwi fruit garden according to an embodiment of the present disclosure;

FIG. 2 is a flowchart of a method for obtaining a temperature prediction model according to an embodiment of the present application;

FIG. 3 is a graph showing the relationship between the temperature of the fruit surface of kiwi fruit and the temperature of the canopy of kiwi fruit according to one embodiment of the present application;

FIG. 4 is a graph showing the relationship between the temperature of the leaf surface of the kiwi fruit and the temperature of the canopy of the kiwi fruit according to an embodiment of the present application;

fig. 5 is a flowchart of a method for monitoring and early warning weather disasters in a kiwi fruit garden according to another embodiment of the present disclosure;

fig. 6 is a schematic structural diagram of a device for monitoring and early warning weather disasters in a kiwi fruit garden according to an embodiment of the present disclosure;

fig. 7 is a schematic structural diagram of an electronic device according to an embodiment of the present application.

Detailed Description

For the purposes of making the objects, technical solutions and advantages of the embodiments of the present application more clear, the technical solutions in the embodiments of the present application are clearly and completely described below, and it is obvious that the described embodiments are some embodiments of the present application, but not all embodiments. All other embodiments, which can be made by one of ordinary skill in the art without inventive effort, are also within the scope of the present application based on the embodiments herein.

Fig. 1 is a flowchart of a method for monitoring and early warning weather disasters in a kiwi fruit garden according to an embodiment of the present application, where an execution subject of the method in this embodiment may be, for example, a server, and as shown in fig. 1, the method shown in this embodiment includes:

s101, acquiring predicted meteorological data in a future preset time period, which is obtained by predicting a meteorological observation station corresponding to a target area, in a preset time period at intervals.

Wherein, the target area contains at least one kiwi fruit garden.

Specifically, the target area is described by taking the western city, zhou county, shaanxi and the Bao chicken city, eyebrow county as examples, wherein the western city, zhou county and the Bao chicken city, eyebrow county are kiwi planting places.

For the week to the county of the western security city, the weather office may acquire the predicted weather data within a future preset time period predicted by the week to the county weather observation station, for example, the current time is 2022, 9, 20, 17, 20 minutes, and the predicted weather data within the preset time period may be acquired after 2022, 9, 20, 17, 20 minutes, for example, the predicted weather data including the remaining time of 2022, 9, 20, and the whole point time within the future 15 days may be acquired, or the predicted weather data may be selectively acquired at any one or more of the remaining time of 2022, 9, 20, and the future 15 days.

Wherein the weather data is changed in real time, it is necessary to periodically acquire the predicted weather data within a preset time period in the future, for example, every half an hour, or 1 hour, etc.

And for the Bao-chicken city and county, acquiring predicted meteorological data in a future preset time period, which is predicted by a Bao-chicken city and county meteorological observation station, from the Bao-chicken city and county meteorological bureau at preset time intervals.

S102, acquiring the kiwi fruit canopy temperature data in a future preset time period according to the predicted meteorological data and the kiwi fruit canopy temperature prediction model.

Specifically, the kiwi fruit canopy temperature prediction model is a model of the association relation between weather temperature data and kiwi fruit canopy temperature.

And inputting the obtained predicted meteorological data at one or more moments in a future preset time period into a kiwi fruit canopy temperature prediction model to obtain corresponding kiwi fruit canopy temperature data.

For example, when the current time is 2022, 9, 20 and 8 days, the predicted meteorological data obtained from the left time of 2022, 9, 20 days and the whole point time within 15 days in the future are input into the kiwi fruit canopy temperature prediction model, and the kiwi fruit canopy temperature data obtained from the left time of 2022, 9, 20 days and the whole point time within 15 days in the future are obtained.

The detecting personnel can select a specific time point according to needs to obtain the temperature data of the kiwi fruit canopy at the specific time point, for example, when the current time is 2022, 9, 20 and 8 days, at this time, if the detecting personnel want to know the temperature of the kiwi fruit canopy at 2022, 9, 22 and 8 days, the obtained temperature data in the predicted meteorological data at 2022, 9, 22 and 8 days is input into a kiwi fruit canopy temperature prediction model to obtain the temperature of the kiwi fruit canopy at 2022, 9, 22 and 8 days.

When the predicted meteorological data in the future preset time period is updated, the updated predicted meteorological data in the future preset time period is input into the kiwi fruit canopy temperature prediction model, corresponding kiwi fruit canopy temperature data are obtained, and accordingly the obtained kiwi fruit canopy temperature data are updated.

The canopy temperature of the kiwi fruits planted in Zhou county and the canopy temperature of the kiwi fruits planted in Mi county are respectively obtained by adopting the method.

S103, according to the kiwi fruit canopy temperature data and the kiwi fruit target position temperature prediction model, acquiring predicted temperature data of a target position on a kiwi fruit tree in a future preset time period.

The kiwi fruit target position temperature prediction model is at least one of the following: a kiwi fruit surface temperature prediction model, a kiwi fruit leaf surface temperature prediction model, a kiwi fruit branch temperature prediction model and a kiwi fruit root neck temperature prediction model.

Specifically, the kiwi fruit surface temperature prediction model, the kiwi fruit leaf surface temperature prediction model, the kiwi fruit branch temperature prediction model and the kiwi fruit root neck temperature prediction model are respectively a kiwi fruit surface temperature, a kiwi fruit leaf surface temperature, a kiwi fruit branch temperature, a kiwi fruit root neck temperature and a kiwi fruit canopy temperature.

Taking predicted temperature data of predicted kiwi fruit noodles as an example for explanation:

and respectively inputting the predicted left time of the day of 9 and 20 of 2022 and the temperature data of the canopy of the kiwi fruit at the whole point time within 15 days into a kiwi fruit surface temperature prediction model to obtain the predicted temperature data of the kiwi fruit surface at the whole point time within 9 and 20 of 2022 and 15 days.

When the monitoring personnel want to check the predicted temperature data of the kiwi fruit surface at any time point of 9 months 22 days 2022, the kiwi fruit canopy temperature data at the moment closest to the time point can be taken as the kiwi fruit canopy temperature data at the time point. For example, if the predicted temperature data of the kiwi fruit crown at the whole time of 2022, 9 and 22 is obtained, and the monitoring person wants to check the predicted temperature data of the kiwi fruit face 25 minutes at 2022, 9 and 22 and 11, the monitoring person selects the predicted temperature data of the kiwi fruit crown at 2022, 9 and 22 and 11 to obtain the predicted temperature data of the kiwi fruit face 25 minutes at 2022, 9 and 22 and 11.

By adopting the method, at least one of the following fruit orchards of Zhou county kiwi fruits and eyebrow county kiwi fruits is obtained respectively: kiwi fruit surface temperature, kiwi fruit leaf surface temperature, kiwi fruit branch temperature, kiwi fruit root neck temperature.

In summer, the branches and leaves of the kiwi fruits grow out, and the result shows that the temperature of the surfaces of the kiwi fruits and the temperature of the surfaces of the kiwi fruits need to be monitored at the moment, so that the temperature prediction model of the target positions of the kiwi fruits in summer selects the temperature prediction model of the surfaces of the kiwi fruits and the temperature prediction model of the surfaces of the kiwi fruits.

In winter, the branches and leaves of the kiwi fruits fall off, and only branches and root necks are reserved, at this time, the temperature of the kiwi fruits branches and the temperature of the kiwi fruit root necks need to be monitored, so that the kiwi fruit target position temperature prediction model selects a kiwi fruit branch temperature prediction model and a kiwi fruit root neck temperature prediction model in winter.

S104, determining disaster information of the target position on the kiwi fruit tree in the kiwi fruit garden in a target area in a preset time period in the future according to the predicted temperature data of the target position on the kiwi fruit tree and the corresponding relation between the disaster grade of the target position on the kiwi fruit tree and the temperature range.

Wherein the disaster information includes at least one of: disaster grade, disaster duration, disaster start time.

Specifically, the kiwi fruits have different bearing capacities to the temperature at different positions, so the temperatures at different positions of the kiwi fruits respectively correspond to the corresponding relation between disaster grades and temperature ranges. Wherein, table 1-table 4 are respectively the disaster grade corresponding to the kiwi fruit leaf surface, kiwi fruit branch and kiwi fruit root neck and the corresponding relation of the temperature range. Table 3 shows the correspondence between disaster grades and temperature ranges corresponding to the temperatures of kiwi fruit branches in the green flavor and Xu Xiang kiwi fruit varieties.

TABLE 1 disaster grade to temperature range correspondence for leaf surface temperature (LT)

Temperature range	Legend color	Disaster grade
			LT≤30℃	Green colour	Is suitable for
30℃～39℃	Yellow colour	Mild heat injury
			39℃～45℃	Red color	Moderate heat injury
LT>45℃	Brown color	Severe heat injury

TABLE 2 correspondence between disaster level and temperature range for fruit surface temperature (NT 1)

Temperature range	Legend color	Disaster grade
			NT1≤47℃	Green colour	Is suitable for
47℃～49℃	Yellow colour	Light sunburn
			49℃～51℃	Red color	Moderate sunscald
NT1>51℃	Brown color	Heavy sunscald

TABLE 3 correspondence between disaster grade and temperature Range for Branch temperature (NT 2)

TABLE 4 disaster grade to temperature Range correspondence for root Neck Temperature (NTs)

Temperature range	Legend color	Disaster grade
			NTs≥-8℃	Green colour	Level 0
-11℃～-8℃	Light green	Level 1
			-13℃～-11℃	Yellow colour	Level 2
-14℃～-13℃	Deep yellow	3 grade
			-50℃～-14℃	Red color	Grade 4
NTs<-15℃	Brown color	Grade 5

The disaster information for predicting the fruit surface of kiwi fruit will be described as an example.

After the predicted temperature data of the kiwi fruit surfaces at the whole time in the year 2022, the 9 and 22 are obtained, the temperature interval where the predicted temperature data of each kiwi fruit surface is located in the corresponding relation between the disaster grade of the kiwi fruit surface and the temperature range is determined, and therefore the disaster grade corresponding to the predicted temperature data of each kiwi fruit surface is determined according to the disaster grade corresponding to the temperature interval.

For the disaster starting time, because the predicted meteorological data in a future preset time period are obtained, the time point of the predicted temperature of the kiwi fruit surface obtained each time is determined, so that the starting time of the kiwi fruit surface reaching the disaster grade corresponding to the predicted temperature of the kiwi fruit surface and the disaster duration time can be determined, and the disaster information corresponding to the predicted temperature data of the kiwi fruit surface can be determined.

For example, in summer, the predicted temperature data of the kiwi fruit surface at 2022, 7, 21 and 12, which is predicted to be obtained by the weather observation station at 2022, 7, 19 and 12, is 46 ℃, the predicted temperature data of the kiwi fruit surface at 2022, 7, 21 and 13, which is predicted to be obtained, is 47 ℃, which means that the temperature grade of the kiwi fruit surface at 2022, 7, 21 and 13 is mild sunburn;

The predicted temperature data of the kiwi fruit noodles at 2022, 7, 21 and 14, which are predicted to be obtained by a weather observation station at 2022, 7, 19 and 12, show that the temperature grade of the kiwi fruit noodles is still mild sunburn at 2022, 7, 21 and 14;

the predicted temperature data of the kiwi fruit noodles at 2022, 7, 21 and 15, which are predicted by a weather observation station at 2022, 7, 19 and 12, are 48.6 ℃ respectively, which indicates that the temperature grade of the kiwi fruit noodles is still mild sunburn at 2022, 7, 21 and 15;

the predicted temperature data of the kiwi fruit surface at 2022, 7, 19 and 16, which are predicted to be obtained by the weather observation station at 2022, 7, 19 and 12, are 49.2 ℃ respectively, which means that when the temperature grade of the kiwi fruit surface at 2022, 7, 19 and 16 becomes moderate day-burn, the start time of the mild day-burn of the temperature grade of the kiwi fruit surface is 2022, 7, 19 and 13, the end time is 2022, 7, 19 and 16, the duration of the light day-burn of the kiwi fruit surface is 3 hours, and the temperature grade of the moderate day-burn of the kiwi fruit surface is 2022, 7, 19 and 16.

The temperature of the kiwi fruit surface obtained by prediction is updated when the weather prediction data is updated because the weather prediction data is updated every preset time interval.

After disaster information is obtained, the disaster information can be broadcasted in weather forecast of a target area, short messages containing the disaster information can be sent to fruit growers, the disaster information can be broadcasted in kiwi fruit gardens, and the fruit growers can be informed in time, so that the fruit growers can take preventive measures in advance. The method of notifying the fruit growers is not limited in this embodiment.

Wherein, optionally, the kiwi fruit has a plurality of varieties, and the same target position on different varieties has different capacities to bear the temperature, so that the disaster grade of the same target position on different varieties may be different under the same temperature. Thus, one implementation of S104 includes S1041 and S1042:

s1041, determining at least one kiwi fruit variety actually planted in a target area.

Specifically, the variety of the kiwi fruit planted in each kiwi fruit garden in the target area is determined.

S1042, determining the disaster information of the kiwi fruit garden at the target position of each kiwi fruit variety in the target area according to the corresponding relation between each kiwi fruit variety actually planted in the target area, the predicted temperature data of the target position on the kiwi fruit tree and the disaster grade and the temperature range of the target position on the kiwi fruit tree associated with each kiwi fruit variety.

Specifically, taking the temperature of the kiwi fruit branches as an example for illustration, as shown in table 3, table 3 shows disaster grades corresponding to the kiwi fruit branch parts of different varieties at the same temperature, when the disaster grades are determined, the varieties of the kiwi fruits are determined, and then disaster information of the kiwi fruit variety branch parts is determined.

According to the method, the predicted meteorological data in a future preset time period, which are obtained through the prediction of the meteorological observation station corresponding to the target area, are obtained through each interval preset time period, so that the kiwi fruit canopy temperature data in the future preset time period are obtained according to the predicted meteorological data and the kiwi fruit canopy temperature prediction model, then the predicted temperature data of the target position on the kiwi fruit tree in the future preset time period are obtained according to the kiwi fruit canopy temperature data and the kiwi fruit target position temperature prediction model, and the disaster information of the target position on the kiwi fruit tree in the kiwi fruit orchard in the target area in the future preset time period is determined according to the predicted temperature data of the target position on the kiwi fruit tree and the corresponding relation between the disaster grade of the target position on the kiwi fruit tree and the temperature range. The method realizes the timely and accurate prediction of the weather disaster information of the kiwi fruits, so that fruit farmers can take preventive measures in advance, and the loss caused by the weather disasters is reduced.

In addition, the embodiment predicts the temperature data of the kiwi fruit crown by predicting the meteorological data, then obtains the predicted temperature data of the target position on the kiwi fruit tree according to the temperature data of the kiwi fruit crown, thus, the outside temperature data (namely, the related temperature data detected by the meteorological observation station) is converted into the small environment inside the kiwi fruit garden by utilizing the temperature data of the kiwi fruit crown, in the small environment inside the kiwi fruit garden, compared with the outside temperature data, the predicted temperature data of the target position on the kiwi fruit tree has stronger relevance with the temperature data of the kiwi fruit crown, and the kiwi fruit crown is generally 1.8 meters, compared with the leaf surfaces, the fruit branches and the root neck positions, the temperature of the kiwi fruit crown has stronger relevance with the outside temperature, therefore, in the embodiment, the kiwi fruit crown temperature is obtained by utilizing the kiwi fruit crown temperature prediction model and the predicted meteorological data, and the predicted temperature data of the target position on the kiwi fruit tree are obtained according to the temperature prediction model of the kiwi fruit crown position and the kiwi fruit crown temperature, so that the obtained predicted temperature data of the target position on the kiwi fruit tree is more accurate.

Fig. 2 is a flowchart of a temperature prediction model obtaining method according to an embodiment of the present application. The execution main body of the temperature prediction model acquisition method shown in fig. 2 may be the same as the execution main body of the kiwi fruit garden weather hazard monitoring and early warning method shown in fig. 1, or the execution main body of the temperature prediction model acquisition method shown in fig. 2 may be different from the execution main body of the kiwi fruit garden weather hazard monitoring and early warning method shown in fig. 1.

As shown in fig. 2, the method shown in this embodiment includes:

s201, acquiring historical meteorological data detected at a preset sampling time point in a historical time period of a meteorological observation station corresponding to an area where a sample kiwi fruit garden is located, and actually detecting canopy historical temperature on the kiwi fruit tree at the preset sampling time point in the historical time period, wherein the historical temperature is at least one of the following: fruit surface history temperature, leaf surface history temperature, branch history temperature and root neck history temperature.

Specifically, the sample kiwi fruit garden can be any kiwi fruit garden in the county or the eyebrow county, for example, or can be any kiwi fruit garden in other areas.

For example, weather data (i.e., historical weather data) detected by weather observation stations from week to county, 8, 10, 12, 14, 16 and 17 times per day, and detected canopy temperatures (canopy historical temperatures), fruit surface temperatures (i.e., fruit surface historical temperatures), leaf surface temperatures (i.e., leaf surface historical temperatures) at 8, 10, 12, 14, 16 and 17 times per day are acquired within 5 months-9 months each year in two years 2020 and 2021.

Acquiring meteorological data (i.e. historical meteorological data) detected by a week-to-county meteorological observation station, and detected canopy temperatures (canopy historical temperatures), branch temperatures (i.e. branch historical temperatures), root neck temperatures (i.e. root neck historical temperatures) at 0, 2, 4, 6, 8, 18, 20 and 22 times per day in 12 months 2019, 12 months in the next year, and in 12 months 2020, 2 months per day.

The application does not limit the number of sampling time points and the time length of the interval between adjacent time sampling points, and only needs at least one of historical meteorological data, canopy historical temperature and the following: the sampling time points of the fruit surface historical temperature, the leaf surface historical temperature, the branch historical temperature and the root neck historical temperature are in one-to-one correspondence. I.e., historical meteorological data at 9/1/8 2020 and canopy historical temperature at 9/1/8 2020, at least one of: the fruit surface historical temperature, the leaf surface historical temperature, the branch historical temperature and the root neck historical temperature are in one-to-one correspondence.

The method is characterized in that new leaves grow out of the kiwi fruits in about 5 months and the results are about 6 months each year, so that the historical meteorological data, canopy historical temperature, fruit surface historical temperature and leaf surface historical temperature in the period of 5 months to 9 months are obtained in 5 months to 9 months each year by adopting the method, and a kiwi fruit canopy temperature prediction model, a kiwi fruit surface temperature prediction model and a kiwi leaf surface temperature prediction model corresponding to summer are obtained;

generally, about 10 months per year, kiwi fruit is not present on kiwi fruit trees, and leaves fall off when entering winter, so that the method is adopted to obtain historical meteorological data, canopy historical temperature, branch historical temperature and root neck historical temperature in the period of 11 months to 2 months of the next year in 11 months to 2 months of the year, thereby obtaining a kiwi fruit canopy temperature prediction model, a kiwi fruit branch temperature prediction model and a kiwi fruit root neck temperature prediction model corresponding to winter.

S202, obtaining a kiwi fruit canopy temperature prediction model according to historical meteorological data and canopy historical temperature.

Specifically, historical meteorological data is used as an independent variable, canopy historical temperature is used as a dependent variable, a plurality of groups of historical meteorological data and canopy historical temperature are input into an initial kiwi fruit canopy temperature prediction model, and the kiwi fruit canopy temperature prediction model is obtained through training. The kiwi fruit canopy temperature prediction model is a unitary linear regression model.

The kiwi fruit canopy temperature prediction model in summer is as follows: ta=0.8817x+3.7152, r ² ＝0.9098。

Wherein X is the current day weather data to be detected directly from the weather observation station or the predicted weather data predicted from the current day weather data detected by the weather observation station.

R ² Indicating the credibility, R of the kiwi fruit canopy temperature prediction model ² The absolute value of the kiwi fruit canopy temperature prediction model is closer to 1, and the reliability of the kiwi fruit canopy temperature prediction model is higher, the kiwi fruit canopy temperature predicted and obtained according to the kiwi fruit canopy temperature prediction model is closer to the actual fruit surface temperature.

0.8817 and 3.7152 are parameters obtained by training an initial kiwi canopy temperature prediction model with sets of historical meteorological data and canopy historical temperatures.

In winter, the kiwi fruit canopy temperature prediction model is: ta=1.0222x+0.369, r ² ＝0.9148。

S203, according to the canopy history temperature and at least one of the following: fruit surface historical temperature, leaf surface historical temperature, branch historical temperature and root neck historical temperature, and obtaining a kiwi fruit target position temperature prediction model.

Specifically, for example, the canopy historical temperature may be used as an independent variable, the fruit surface historical temperature may be used as an independent variable, the canopy historical temperature and the fruit surface historical temperature may be input into an initial kiwi fruit surface temperature prediction model, and the kiwi fruit surface temperature prediction model is obtained through training, wherein the kiwi fruit surface temperature prediction model is an exponential model, and the kiwi fruit surface temperature prediction model is an exemplary: nT1= 0.2486Ta ^1.4906 Wherein Ta is the canopy temperature at 180cm on the kiwi fruit tree. Wherein 0.2486 and 1.4906 are parameters obtained by training an initial kiwi fruit surface temperature prediction model based on canopy historical temperature and fruit surface historical temperature.

The relation diagram between the kiwi fruit surface temperature and the kiwi fruit canopy temperature shown by the kiwi fruit surface temperature prediction model is shown in fig. 3.

The method used when the kiwi fruit surface temperature prediction model is obtained is adopted to obtain the kiwi fruit leaf surface temperature prediction model, the kiwi fruit branch temperature prediction model and the kiwi fruit root neck temperature prediction model, and the detailed description is omitted here.

Wherein, kiwi fruit foliar temperature predictive model is the exponential model, and exemplary kiwi fruit foliar temperature predictive model is: lt=0.725 Ta ^1.1382 . Wherein, 0.725 and 1.1382 are parameters obtained by training an initial kiwi leaf surface temperature prediction model according to canopy history temperature and leaf surface history temperature.

The graph of the relationship between the kiwi leaf surface temperature and the kiwi canopy temperature shown by the kiwi leaf surface temperature prediction model is shown in fig. 4.

The kiwi fruit branch temperature prediction model is a unitary linear regression model, and exemplary kiwi fruit branch temperature prediction models are: nT2= 1.0311Ta-2.2821. Wherein 1.0311 and 2.2821 are parameters obtained by training an initial kiwi fruit branch temperature prediction model according to canopy historical temperature and branch historical temperature.

Wherein, kiwi fruit root neck temperature predictive model is the linear regression model of unitary, and exemplary kiwi fruit root neck temperature predictive model is: nts=1.6799ta+3.48. Wherein 1.6799 and 3.48 are parameters obtained by training an initial kiwi fruit root neck temperature prediction model according to the canopy history temperature and the root neck history temperature.

Optionally, in order to improve accuracy of disaster information prediction, a kiwi fruit canopy temperature prediction model, a kiwi fruit face temperature prediction model, a kiwi fruit leaf surface temperature prediction model, a kiwi fruit branch temperature prediction model, a kiwi fruit root neck temperature prediction model corresponding to different weather types may be obtained, that is, one possible implementation manner of S201 is as follows:

And at least one of the obtained historical meteorological data, the actual detected canopy historical temperature on the kiwi fruit tree and the following: the fruit surface historical temperature, the leaf surface historical temperature, the branch historical temperature and the root neck historical temperature are classified according to different weather types, and historical meteorological data corresponding to different weather types, the actual detected canopy historical temperature on the kiwi fruit tree and at least one of the following are obtained: fruit surface history temperature, leaf surface history temperature, branch history temperature and root neck history temperature.

Correspondingly, obtaining a kiwi fruit garden canopy temperature prediction model corresponding to different weather types, and at least one of the following: a kiwi fruit surface temperature prediction model, a kiwi fruit leaf surface temperature prediction model, a kiwi fruit branch temperature prediction model and a kiwi fruit root neck temperature prediction model. The method for obtaining the model may refer to the above embodiment, and will not be described herein.

Optionally, in summer, the weather types may be classified into a sunny day, a cloudy day, or a rainy day, and in winter, the weather types may be classified into a sunny day and a non-sunny day, and the non-sunny day may include a cloudy day, a rainy day, and a snowy day. Of course, the weather type may be selected according to actual needs, which is not limited in this application.

Therefore, when disaster information of a target position on the kiwi fruit tree is predicted, the weather type is determined according to the predicted meteorological data, so that a kiwi fruit orchard canopy temperature prediction model corresponding to the weather type and at least one of the following are selected: the accuracy of prediction is improved by the aid of the kiwi fruit surface temperature prediction model, the kiwi fruit leaf surface temperature prediction model, the kiwi fruit branch temperature prediction model and the kiwi fruit root neck temperature prediction model.

Fig. 5 is a flowchart of a method for monitoring and early warning weather disasters in a kiwi fruit garden according to another embodiment of the present application, as shown in fig. 5, the method shown in the embodiment includes:

s501, acquiring predicted meteorological data of a plurality of grid points in a target area in a future preset time period which is predicted by a meteorological observation station every preset time period.

Specifically, the prediction meteorological data of the grid points of the region from the week to the county is obtained from the meteorological office, wherein the grid points are obtained by carrying out grid dotting on the region from the week to the county, namely, the region from the week to the county is divided into a plurality of grids, and the centers of the grids are grid points.

S502, obtaining the kiwi fruit canopy temperature data in a future preset time period corresponding to each grid point according to the predicted meteorological data of each grid point in the target area and the kiwi fruit canopy temperature prediction model.

Specifically, the predicted meteorological data of each lattice point is input into the kiwi fruit canopy temperature prediction model to obtain the kiwi fruit canopy temperature data corresponding to each lattice point, and the specific method can refer to S202, which is not described herein.

S503, according to the temperature data of the kiwi fruit canopy and the kiwi fruit target position temperature prediction model corresponding to each grid point, obtaining the predicted temperature data of the target position on the kiwi fruit tree in a future preset time period corresponding to each grid point.

Specifically, the temperature data of the kiwi fruit canopy corresponding to each lattice point is input to at least one of the following: in the kiwi fruit surface temperature prediction model, the kiwi fruit leaf surface temperature prediction model, the kiwi fruit branch temperature prediction model and the kiwi fruit root neck temperature prediction model, the predicted temperature data of the corresponding position on the kiwi fruit tree is obtained, and the specific method can refer to S203 and is not repeated here.

S504, according to the predicted temperature data of the target position on the kiwi fruit tree in the kiwi fruit garden corresponding to each grid point and the corresponding relation between the disaster grade of the target position on the kiwi fruit tree and the temperature range, disaster information of the target position on the kiwi fruit tree in the kiwi fruit garden corresponding to each grid point in a preset time period in the future is determined.

Specifically, disaster information of the target position on the kiwi fruit tree in the grid where each grid point is located is obtained according to the predicted temperature data of the target position on the kiwi fruit tree in each grid point, wherein the specific method can refer to S204 and is not described herein.

It should be noted that, the area where the county is located includes an area where kiwi fruits are not planted, so when the predicted meteorological data on the lattice is obtained from the meteorological office, the predicted meteorological data on the lattice is also obtained for the area where the kiwi fruits are not planted, and disaster information of the area where the kiwi fruits are not planted can be preset disaster information, wherein the disaster level in the preset disaster information is 0 level, that is, the level which does not cause damage to the target position on the kiwi fruit tree.

The method comprises the steps of obtaining the predicted meteorological data of each grid point in a target area, namely performing grid point processing on the target area, dividing the target area into a plurality of small grids, reducing errors of the predicted meteorological data of the areas where the grids are located, and considering the factors such as the topography, the climate type, the surrounding environment and the like corresponding to the grid points when the meteorological data of the grid points are obtained, so that the predicted meteorological data of each grid point is further improved, and the accuracy of disaster information prediction of the target positions on the kiwi fruit trees in the kiwi fruit orchard corresponding to the grid points is further improved.

Optionally, in order to more intuitively display disaster information of a target position on a kiwi fruit tree in a kiwi fruit garden in a target area, on the basis of the above embodiment, a method of the present application may further include:

s505, according to disaster information of the target positions on the kiwi fruit trees in the kiwi fruit orchard corresponding to each grid point, acquiring disaster prediction distribution diagrams of the target positions on the kiwi fruit trees in the kiwi fruit orchard in the target area.

Specifically, determining the number of grid points, then utilizing buffer software to manufacture a grid point map corresponding to a target area, enabling the disaster level of a target position on a kiwi fruit tree in a kiwi fruit garden corresponding to each grid point to be corresponding to a grid corresponding to the grid point on the grid point map obtained by grid formation of the target area, and establishing association between the duration of the disaster and the starting time of the disaster of each grid point and the grid corresponding to the grid point, so that a disaster prediction distribution diagram of the target position on the kiwi fruit tree in the kiwi fruit garden in the target area is obtained.

S506, obtaining a disaster grade prediction distribution color scale map of the target position on the kiwi fruit tree in the kiwi fruit orchard of the target area according to the actual kiwi fruit orchard distribution map of the target area, the disaster prediction distribution map of the target position on the kiwi fruit tree in the kiwi fruit orchard of the target area and the color scale corresponding to the disaster grade of the target position on the kiwi fruit tree.

Specifically, the actual kiwi fruit garden distribution map in the target area and the disaster prediction distribution map of the target position on the kiwi fruit tree in the kiwi fruit garden in the target area are subjected to layer superposition, so that disaster information corresponding to the kiwi fruit garden in each position in the target area can be determined. As shown in tables 1 to 4, the color codes corresponding to different disaster grades at different positions on the kiwi fruit tree are different, so that in order to more intuitively display the disaster grades corresponding to the kiwi fruit orchards at all positions in the target area, the color codes corresponding to different disaster grades at different positions on the kiwi fruit tree can be attached to the superimposed distribution diagram, and a disaster grade prediction distribution color code map of the target position on the kiwi fruit tree in the kiwi fruit orchards of the target area is obtained.

Fig. 6 is a schematic structural diagram of a kiwi fruit garden weather disaster monitoring and early warning device according to an embodiment of the present application, as shown in fig. 6, the kiwi fruit garden weather disaster monitoring and early warning device according to the embodiment includes: an acquisition module 601, a first prediction module 602, a second prediction module 603, and a determination module 604. Optionally, the kiwi fruit orchard weather disaster monitoring and early warning device can further include: model training module 605. Optionally, the kiwi fruit orchard weather disaster monitoring and early warning device can further include: a processing module 606.

The obtaining module 601 is configured to obtain predicted meteorological data in a future preset time period obtained by meteorological prediction corresponding to a target area every interval preset time period, where the target area contains at least one kiwi fruit garden;

the first prediction module 602 is configured to obtain, according to the predicted meteorological data and the kiwi fruit canopy temperature prediction model, kiwi fruit canopy temperature data in a preset time period in the future;

the second prediction module 603 is configured to obtain, according to the kiwi fruit canopy temperature data and the kiwi fruit target position temperature prediction model, predicted temperature data of a target position on a kiwi fruit tree within a preset time period in the future, where the kiwi fruit target position temperature prediction model is at least one of the following: a kiwi fruit surface temperature prediction model, a kiwi leaf surface temperature prediction model, a kiwi fruit branch temperature prediction model and a kiwi fruit root neck temperature prediction model;

the determining module 604 is configured to determine disaster information of a target position on a kiwi fruit tree in a kiwi fruit garden in a target area within a preset time period in the future according to a corresponding relationship between predicted temperature data of the target position on the kiwi fruit tree and a disaster level and a temperature range of the target position on the kiwi fruit tree, where the disaster information at least includes one of: disaster grade, disaster duration, disaster start time.

Optionally, before the first processing module 602 obtains the kiwi fruit canopy temperature data in the future preset time period according to the predicted meteorological data and the kiwi fruit canopy temperature prediction model, the model training module 605 is configured to:

acquiring historical meteorological data of a preset sampling time point in a historical time period of a meteorological observation station corresponding to an area where a sample kiwi fruit garden is located, and actually detecting canopy historical temperature on the kiwi fruit tree at the preset sampling time point in the historical time period, wherein the canopy historical temperature is at least one of the following: fruit surface history temperature, leaf surface history temperature, branch history temperature and root neck history temperature;

obtaining a kiwi fruit canopy temperature prediction model according to historical meteorological data and canopy historical temperature;

based on the canopy historical temperature and at least one of: fruit surface historical temperature, leaf surface historical temperature, branch historical temperature and root neck historical temperature, and obtaining a kiwi fruit target position temperature prediction model.

Optionally, when the obtaining module 601 obtains the predicted meteorological data in the future preset time period predicted by the meteorological station corresponding to the target area at intervals of the preset time length, the method is specifically used for:

The first prediction module 602 is specifically configured to, when obtaining the kiwi fruit canopy temperature data in a future preset time period according to the predicted meteorological data and the kiwi fruit canopy temperature prediction model:

the second prediction module 603 is specifically configured to, when acquiring predicted temperature data of a target position on a kiwi fruit tree within a preset time period in the future according to the kiwi fruit canopy temperature data and the kiwi fruit target position temperature prediction model:

according to the temperature data of the kiwi fruit canopy corresponding to each grid point and the kiwi fruit target position temperature prediction model, obtaining predicted temperature data of a target position on a kiwi fruit tree in a future preset time period corresponding to each grid point;

the determining module 604 is specifically configured to, when determining disaster information of a target position on a kiwi fruit tree in a kiwi fruit garden in a target area within a preset time period in the future according to a corresponding relationship between predicted temperature data of the target position on the kiwi fruit tree and disaster level and temperature range of the target position on the kiwi fruit tree:

Optionally, the processing module 606 is configured to obtain a disaster prediction distribution diagram of a target position on a kiwi fruit tree in the kiwi fruit garden in the target area according to disaster information of the target position on the kiwi fruit tree in the kiwi fruit garden corresponding to each lattice point;

and obtaining a disaster level prediction distribution color map of the target position on the kiwi fruit tree in the kiwi fruit orchard of the target area according to the actual kiwi fruit orchard distribution map in the target area, the disaster prediction distribution map of the target position on the kiwi fruit tree in the kiwi fruit orchard of the target area and the color codes corresponding to the disaster level of the target position on the kiwi fruit tree.

Optionally, the model training module 605 obtains historical meteorological data detected at a preset sampling time point in a historical time period of a meteorological observation station corresponding to an area where the sample kiwi fruit garden is located, and a canopy historical temperature on the kiwi fruit tree actually detected at the preset sampling time point in the historical time period, and at least one of the following: the fruit surface history temperature, the leaf surface history temperature, the branch history temperature and the root neck history temperature are specifically used for:

Acquiring historical meteorological data corresponding to different weather types, and actually detected canopy historical temperature on a kiwi fruit tree, wherein the historical temperature is at least one of the following: fruit surface history temperature, leaf surface history temperature, branch history temperature and root neck history temperature;

model training module 605 is specifically used when obtaining kiwi fruit orchard canopy temperature predictive model according to historical meteorological data and canopy historical temperature on the kiwi fruit tree:

obtaining a kiwi fruit garden canopy temperature prediction model corresponding to different weather types according to the historical meteorological data corresponding to different weather types and the actually detected canopy historical temperature on the kiwi fruit tree;

according to the predicted weather data, determining a predicted weather type corresponding to the predicted weather data;

Optionally, in summer, the weather type is sunny, cloudy or rainy;

in winter, the weather types are sunny days, non-sunny days, including cloudy, rainy and snowy days.

Optionally, the determining module 604 is configured to determine, according to the predicted temperature data of the target position on the kiwi fruit tree and the correspondence between the disaster level of the target position on the kiwi fruit tree and the temperature range, disaster information of the target position on the kiwi fruit tree in the kiwi fruit garden in the target area within the preset time period in the future, where the determining module is specifically configured to:

determining at least one kiwi fruit variety actually planted in a target area;

according to the corresponding relation between the disaster grade and the temperature range of each kiwi fruit variety actually planted in the target area, the predicted temperature data of the target position on the kiwi fruit tree and the disaster grade and the temperature range of the target position on the kiwi fruit tree associated with each kiwi fruit variety, determining the disaster information of the kiwi fruit orchard at the target position of each kiwi fruit variety in the target area in a future preset time period.

Optionally, the kiwi fruit canopy temperature prediction model is a unitary linear regression model, the kiwi fruit face temperature prediction model and the kiwi fruit leaf face temperature prediction model are both exponential models, the kiwi fruit branch temperature prediction model is a unitary linear regression model, and the kiwi fruit root neck temperature prediction model is a unitary linear regression model.

The kiwi fruit garden weather disaster monitoring and early warning device can be used for executing the technical scheme in the method embodiments, and the implementation principle and the technical effect are similar and are not repeated here.

Fig. 7 is a schematic structural diagram of an electronic device provided in an embodiment of the present application, where the electronic device is, for example, a server, and as shown in fig. 7, the electronic device in this embodiment may include: at least one processor 701 and a memory 702. Fig. 7 shows an electronic device, for example, a processor.

Wherein,

a memory 702 for storing programs. In particular, the program may include program code including computer-operating instructions. The memory 702 may include high-speed random access memory (random access memory, RAM) and may also include non-volatile memory (non-volatile memory), such as at least one disk memory.

The processor 701 is configured to execute the computer-executed instructions stored in the memory 702, so as to implement the method for monitoring and early warning a weather disaster in a kiwi fruit garden shown in any one of the embodiments.

The processor 701 may be a central processing unit (Central Processing Unit, CPU), or a specific integrated circuit (Application Specific Integrated Circuit, ASIC), or one or more integrated circuits configured to implement embodiments of the present application.

Alternatively, in a specific implementation, if the memory 702 and the processor 701 are implemented independently, the memory 702 and the processor 701 may be connected to each other and communicate with each other through the bus 703. The bus may be an industry standard architecture (Industry Standard Architecture, ISA) bus, an external device interconnect (Peripheral Component, PCI) bus, or an extended industry standard architecture (Extended Industry Standard Architecture, EISA) bus, among others. The buses may be divided into address buses, data buses, control buses, etc., but do not represent only one bus or one type of bus.

Alternatively, in a specific implementation, if the memory 702 and the processor 701 are integrated on a single chip, the memory 702 and the processor 701 may perform the same communication through an internal interface.

The electronic device described in the embodiment may be used to execute the technical solutions in the embodiments of the methods described in the embodiments, and the implementation principle and the technical effects are similar, and are not repeated here.

The embodiment of the application also provides a computer readable storage medium, and the computer readable storage medium stores program instructions, wherein the program instructions are executed by a processor to realize the kiwi fruit garden meteorological disaster monitoring and early warning method according to any one of the embodiments of the invention.

The embodiment of the application also provides a program product, which comprises a computer program, wherein the computer program is stored in a readable storage medium, at least one processor of the electronic device can read the computer program from the readable storage medium, and the at least one processor executes the computer program to enable the electronic device to implement the kiwi fruit garden weather disaster monitoring and early warning method according to any one of the embodiments of the application.

An embodiment of the present application provides a chip system, including: the system comprises a processor and a memory, wherein the memory stores computer execution instructions, and the processor executes the computer execution instructions stored in the memory, so that the processor executes the kiwi fruit garden weather disaster monitoring and early warning method.

Those of ordinary skill in the art will appreciate that: all or part of the steps for implementing the method embodiments described above may be performed by hardware associated with program instructions. The foregoing program may be stored in a computer readable storage medium. The program, when executed, performs steps including the method embodiments described above; and the aforementioned storage medium includes: read-Only Memory (ROM), random access Memory (random access Memory, RAM), magnetic or optical disk, and the like, which can store program codes.

Finally, it should be noted that the above embodiments are merely for illustrating the technical solution of the present application, and are not limiting; although the present application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art will understand; the technical scheme described in the foregoing embodiments can be modified or some or all of the technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit of the corresponding technical solutions from the scope of the technical solutions of the embodiments of the present application.

Claims

1. The method for monitoring and early warning weather disasters in kiwi fruit orchards is characterized by comprising the following steps:

2. The method according to claim 1, wherein before obtaining the kiwi fruit canopy temperature data within the future preset time period according to the predicted meteorological data and the kiwi fruit canopy temperature prediction model, further comprises:

3. The method according to claim 1, wherein the obtaining, for each preset time period, predicted weather data within a future preset time period predicted by a weather observation station corresponding to the target area includes:

4. A method according to claim 3, further comprising:

5. The method according to claim 2, wherein the acquiring of the historical meteorological data detected at a preset sampling time point in a historical period of a meteorological observation station corresponding to an area where a sample kiwi fruit garden is located, and the actual detection of the canopy historical temperature on the kiwi fruit tree at the preset sampling time point in the historical period, and at least one of the following: fruit surface history temperature, leaf surface history temperature, branch history temperature and root neck history temperature, include:

Acquiring historical meteorological data corresponding to different weather types, and actually monitored canopy historical temperature on the kiwi fruit tree, wherein the historical canopy temperature comprises at least one of the following components: fruit surface history temperature, leaf surface history temperature, branch history temperature and root neck history temperature;

obtaining a kiwi fruit garden canopy temperature prediction model corresponding to different weather types according to historical meteorological data corresponding to different weather types and the actually monitored canopy historical temperature on the kiwi fruit tree;

6. The method of claim 5, wherein the weather type is sunny, cloudy, or rainy in summer;

7. The method according to claim 1, wherein determining disaster information of the target position on the kiwi fruit tree in the kiwi fruit garden in the target area within the future preset time period according to the predicted temperature data of the target position on the kiwi fruit tree and the correspondence between the disaster level of the target position on the kiwi fruit tree and the temperature range comprises:

8. The method of any one of claims 1-7, wherein the kiwi fruit canopy temperature prediction model is a unitary linear regression model, the kiwi fruit face temperature prediction model and the kiwi fruit leaf surface temperature prediction model are both exponential models, the kiwi fruit branch temperature prediction model is a unitary linear regression model, and the kiwi fruit root neck temperature prediction model is a unitary linear regression model.

9. The method of any one of claims 1-7, wherein the kiwi fruit target location temperature prediction model comprises, during summer: a kiwi fruit surface temperature prediction model and/or a kiwi fruit surface temperature prediction model;

10. Kiwi fruit orchard weather disaster monitoring early warning device, its characterized in that includes:

the first processing module is used for obtaining the kiwi fruit canopy temperature data in a future preset time period according to the predicted meteorological data and the kiwi fruit canopy temperature prediction model;

the second processing module is used for acquiring predicted temperature data of a target position on a kiwi fruit tree in a future preset time period according to the kiwi fruit canopy temperature data and a kiwi fruit target position temperature prediction model, wherein the kiwi fruit target position temperature prediction model is at least one of the following: a kiwi fruit surface temperature prediction model, a kiwi leaf surface temperature prediction model, a kiwi fruit branch temperature prediction model and a kiwi fruit root neck temperature prediction model;