Method for detecting and analyzing trends of teleconnection-driven compound dry-hot risk hotspot regions in agricultural land, and device for detecting and analyzing trends of teleconnection-driven compound dry-hot risk hotspot regions in agricultural land

Abstract

To provide a method for detecting and analyzing trends of teleconnection-driven compound dry-hot risk hotspot regions in agricultural land and a device for detecting and analyzing trends of teleconnection-driven compound dry-hot risk hotspot regions in agricultural land, which relate to the technical field of extreme-climate recognition.SOLUTION: The method includes: obtaining hotspot regions of teleconnection-driven compound dry-hot events corresponding to multiple target time periods of a target analysis region: and performing trend analysis for an agricultural-land-area sequence on the basis of the hotspot regions of the teleconnection-driven compound dry-hot events corresponding to each target time period among the multiple target time periods of the target analysis region. The method realizes analysis for compound extreme dry-hot events.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present application relates to the technical field of extreme climate awareness, and in particular to a method and apparatus for detecting and trending teleconnection complex extreme dry hot risk hotspot areas in agricultural land. [Background technology]

[0002] Drought and extreme heat events are among the most devastating extreme weather events, and their simultaneous occurrence, i.e., compound extreme dry and hot events, can have devastating effects. As climate change becomes more severe in the future, the frequency, duration, and severity of compound extreme dry and hot events are predicted to increase. Extreme weather events occurring simultaneously at multiple locations within a certain time window can accumulate their impacts at multiple locations, placing additional strain on interconnected social and economic system networks.

[0003] In the prior art, climate network methods are a powerful tool for studying the complex interrelated characteristics of the climate system and have been successfully applied to the analysis, modeling, understanding, and prediction of various climate phenomena. Scholars have already used climate networks to explore the spatial teleconnection characteristics of weather and climate events, such as extreme precipitation, drought, and high temperatures. However, current studies of extreme weather and climate teleconnections have mostly focused on single-variable weather and climate events, with few examining the teleconnections of multivariable weather and climate events. Second, in recent years, there has been a rapid increase in research on the occurrence frequency, spatial extent, change trends, and future prediction of complex dry and hot events. Many scholars have also used statistical methods to quantify the impact of complex dry and hot events on agriculture and ecosystems. However, complex extreme dry and hot events occurring simultaneously in different regions have received little attention, and the risk of teleconnections resulting from complex extreme dry and hot events has been ignored. Finally, when constructing climate networks, most current studies use data from a complete time period, making it difficult to examine the change trends in the teleconnection characteristics of extreme weather and climate events.

[0004] How to detect hotspot areas of teleconnection complex extreme dry hot events and analyze their agricultural land trends is currently a technical challenge that needs to be resolved. Summary of the Invention [Problem to be solved by the invention]

[0005] The purpose of this application is to provide a method and apparatus for detecting and trending teleconnection complex extreme dry hot risk hotspot areas in agricultural land to solve the deficiencies existing in the prior art. [Means for solving the problem]

[0006] The present application provides a method for detecting and trending teleconnection complex extreme dry hot risk hotspot areas in agricultural land, the method comprising: Obtaining hotspot areas of teleconnection composite extreme dry hot events corresponding to each target time slot among a plurality of target time slots in a target study area, wherein the hotspot areas of teleconnection composite extreme dry hot events corresponding to any target time slot among the plurality of target time slots are calculated based on a directed network of composite extreme dry hot events corresponding to the target time slot, and the directed network of composite extreme dry hot events is obtained based on location information of composite extreme dry hot events occurring in the corresponding target time slot; and performing a trend analysis on the cropland area sequence based on hotspot areas of teleconnection composite extreme dry hot events corresponding to each target time period among a plurality of target time periods in the target study area.

[0007] According to the method for detecting and analyzing trends of teleconnection complex extreme dry hot events in agricultural land, the method for detecting and analyzing trends of teleconnection complex extreme dry hot events in agricultural land includes the steps of: Obtaining a plurality of composite extreme dry-hot events in a target time period of a target study area, and calculating the number of composite extreme dry-hot synchronous event pairs in the target study area, wherein the composite extreme dry-hot synchronous event pairs are for indicating that composite extreme dry-hot events at any two locations are synchronized; Perform a significance test on the composite extreme dry-hot synchronous event pairs in the target study area, and construct a directed network of composite extreme dry-hot events based on the test result, where the directed network includes multiple nodes, and each node corresponds to a location where the composite extreme dry-hot event occurs in the target study area; Calculating the degree index of each node in the directed network, and determining the location corresponding to the node whose degree index is greater than a preset threshold as the hotspot region of the teleconnection composite extreme dry hot event in the target time period.

[0008] According to the method for detecting and analyzing trends of teleconnection complex extreme dry hot risk hotspot areas in agricultural land of the present application, acquiring multiple complex extreme dry hot events in a target time period in a target examination area as described above includes: The method includes obtaining spatialized daily maximum temperature data and monthly self-calibrated Palmer Drought Severity Index data for a target time period in a target study area, and performing sorting based on the daily maximum temperature data and the monthly self-calibrated Palmer Drought Severity Index data to obtain a plurality of composite extreme dry-hot events for the target time period in the target study area.

[0009] According to the method for detecting and analyzing trends of teleconnection complex extreme dry hot risk hotspot areas in agricultural land of the present application, calculating the number of complex extreme dry hot synchronous event pairs in the target consideration area as described above includes: Determine whether the occurrence time interval of any two composite extreme dry-hot events in the target consideration area is greater than a preset delay time, and if there are two composite extreme dry-hot events in the target consideration area whose occurrence time interval is greater than a preset delay time, determine the two composite extreme dry-hot events as a composite extreme dry-hot synchronous event pair; and repeatedly performing the above steps to obtain a number of composite extreme dry-hot synchronous event pairs in the target study area.

[0010] According to the method for detecting and analyzing the trend of teleconnection complex extreme dry hot risk hotspot areas in agricultural land of the present application, the above-mentioned significance test is performed on the complex extreme dry hot synchronous event pairs in the target examination area, and a directed network of complex extreme dry hot events is constructed based on the test result. Determine a location where a composite extreme dry-hot event occurs in the target consideration area as a node, and perform a significance test on a composite extreme dry-hot synchronous event pair between two nodes in the target consideration area to obtain a significance threshold; If the number of composite extreme dry-hot synchronous event pairs between the two nodes is greater than the significance threshold, establishing a connection edge between the two nodes and constructing a directed network of composite extreme dry-hot events based on the established connection edge.

[0011] According to the method for detecting and analyzing trends in teleconnection complex extreme dry hot risk hotspot areas in agricultural land of the present application, performing trend analysis on agricultural land area sequences based on hotspot areas of teleconnection complex extreme dry hot events corresponding to each target time period among a plurality of target time periods in the target consideration area includes: The method includes overlaying agricultural land with hotspot areas of teleconnection composite extreme dry hot events corresponding to each target time period among a plurality of target time periods in the target consideration area, obtaining agricultural land areas with teleconnection composite extreme dry hot event risk in each target time period, and performing trend analysis on the agricultural land area sequence, wherein the agricultural land area sequence includes agricultural land areas with teleconnection composite extreme dry hot event risk in each target time period among the plurality of target time periods.

[0012] The present application further provides a teleconnection complex extreme dry hot risk hotspot area detection and trend analysis device in agricultural land, the device comprising: a detection module configured to obtain hotspot areas of teleconnection composite extreme dry hot events corresponding to each target time slot among a plurality of target time slots in a target consideration area, wherein the hotspot areas of teleconnection composite extreme dry hot events corresponding to any target time slot among the plurality of target time slots are calculated based on a directed network of composite extreme dry hot events corresponding to the target time slot, and the directed network of composite extreme dry hot events is obtained based on location information of composite extreme dry hot events occurring in the corresponding target time slot; and an analysis module configured to perform trend analysis on the cropland area sequence based on hotspot areas of teleconnection composite extreme dry hot events corresponding to each target time period among a plurality of target time periods in the target study area.

[0013] According to the detection and trend analysis device for teleconnection complex extreme dry hot risk hotspot areas in agricultural land of the present application, the detection module specifically: Obtaining a plurality of composite extreme dry-hot events in a target time period of a target study area, and calculating the number of composite extreme dry-hot synchronous event pairs in the target study area, wherein the composite extreme dry-hot synchronous event pairs are for indicating that composite extreme dry-hot events at any two locations are synchronized; Perform a significance test on the composite extreme dry-hot synchronous event pairs in the target study area, and construct a directed network of composite extreme dry-hot events based on the test result, where the directed network includes multiple nodes, and each node corresponds to a location where the composite extreme dry-hot event occurs in the target study area; The method is configured to calculate the degree index of each node in the directed network, and determine the locations corresponding to nodes whose degree index is greater than a preset threshold as hotspot regions of a teleconnection composite extreme dry hot event in the target time period.

[0014] The present application further provides a computer program product including a computer program / instruction, which, when executed by a processor, realizes the steps of the method for detecting and analyzing trends of teleconnection complex extreme dry hot risk hotspot areas in agricultural land described in any one of the above.

[0015] The present application further provides an electronic device including a memory, a processor, and a computer program stored in the memory and executable by the processor, which, when the processor executes the computer program, realizes the steps in any one of the above-described methods for detecting and analyzing trends of teleconnection complex extreme dry hot risk hotspot areas in agricultural land.

[0016] The present application further provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, realizes the steps of the method for detecting and analyzing trends of teleconnection complex extreme dry hot risk hotspot areas in agricultural land described above. [Effects of the Invention]

[0017] The method and apparatus for detecting and analyzing trends of teleconnection composite extreme dry hot risk hotspot areas in agricultural land according to the present application obtains hotspot areas of teleconnection composite extreme dry hot events corresponding to each target time period among a plurality of target time periods in a target consideration area, wherein the hotspot area of ​​the teleconnection composite extreme dry hot event corresponding to any target time period among the plurality of target time periods is calculated based on a directed network of the composite extreme dry hot event corresponding to the target time period, and the directed network of the composite extreme dry hot event is obtained based on location information of the composite extreme dry hot event occurring in the corresponding target time period, and performs trend analysis on the agricultural land area sequence based on the hotspot area of ​​the teleconnection composite extreme dry hot event corresponding to each target time period among the plurality of target time periods in the target consideration area. Therefore, the present application analyzes the teleconnection characteristics of multivariate extreme weather and climate events, i.e., composite extreme dry and hot events, identifies hotspot areas of composite extreme dry and hot events, and performs overlay analysis with agricultural land, thereby enabling the investigation of the teleconnection composite extreme dry and hot risks and their changing trends facing agricultural land on the entire globe or in certain regions, which is advantageous for the investigation and management of composite extreme dry and hot events, and the method is simple and easy to operate. [Brief explanation of the drawings]

[0018] In order to more clearly explain the embodiments of the present application or the technical solutions in the prior art, the drawings necessary for the description of the embodiments or the prior art will be briefly described below. Of course, the drawings in the following description are only some embodiments of the present application, and those skilled in the art can further obtain other drawings based on these drawings without creative work. [Figure 1] This is the first flowchart of the method for detecting and analyzing trends in teleconnection complex extreme dry hot risk hotspot areas in agricultural land according to the present application. [Figure 2]This is the second flowchart of the method for detecting and analyzing trends in teleconnection complex extreme dry hot risk hotspot areas in agricultural land according to the present application. [Figure 3] 1 is a schematic diagram of the spatial distribution of node degrees in a directed network according to the present application; [Figure 4] FIG. 1 is a schematic diagram of the trend of teleconnection composite extreme dry-hot risk for agricultural land according to the present application. [Figure 5] 1 is a schematic diagram of the structure of the teleconnection composite extreme dry hot risk hotspot area detection and trend analysis device in agricultural land according to the present application; [Figure 6] 1 is a schematic diagram of the structure of an electronic device according to the present application. DETAILED DESCRIPTION OF THE INVENTION

[0019] In order to make the objectives, technical solutions and advantages of the present application clearer, the technical solutions of the present application will be described clearly and completely below with reference to the drawings in the present application. Of course, the described embodiments are not all embodiments, but only some embodiments of the present application. Based on the embodiments in the present application, all other embodiments that a person skilled in the art can obtain without any creative work fall within the scope of protection of the present application.

[0020] The terms "first," "second," and the like in the specification and claims of this application are intended to distinguish between similar objects and not to describe a particular order or chronology. Terms used in this manner are interchangeable where appropriate, so that embodiments of the present disclosure may be implemented in an order other than that illustrated or described herein. It should be understood that objects distinguished by "first," "second," and the like are generally of the same type and the number of objects is not limited; for example, the first object may be one or more. Furthermore, "and / or" in the specification and claims indicates at least one of the connected objects, and the symbol " / " generally indicates an "or" relationship between the related objects before and after.

[0021] Hereinafter, with reference to the drawings, a method for detecting and analyzing trends of teleconnection complex extreme dry hot risk hotspot areas in agricultural land according to an embodiment of the present application will be described in detail through specific embodiments and application scenarios.

[0022] FIG. 1 is a flowchart of the method for detecting and analyzing trends of teleconnection complex extreme dry hotspot areas in agricultural land according to the present application. As shown in FIG. 1, the method for detecting and analyzing trends of teleconnection complex extreme dry hotspot areas in agricultural land according to the present application includes steps 100 and 200.

[0023] In step 100, a hotspot area of ​​a teleconnection composite extreme dry hot event corresponding to each target time slot among a plurality of target time slots in a target consideration area is obtained, wherein the hotspot area of ​​the teleconnection composite extreme dry hot event corresponding to any target time slot among the plurality of target time slots is calculated based on a directed network of the composite extreme dry hot event corresponding to the target time slot, and the directed network of the composite extreme dry hot event is obtained based on location information of the composite extreme dry hot event occurring in the corresponding target time slot.

[0024] Specifically, Figure 2 is a flowchart part 2 of the method for detecting and analyzing trends in teleconnection complex extreme dry hot risk hotspot areas in agricultural land according to the present application. As shown in Figure 2, step 100 specifically includes steps 210, 220, and 230.

[0025] In step 210, obtain multiple composite extreme dry-hot events in a target time period of a target consideration area, and calculate the number of composite extreme dry-hot synchronous event pairs in the target consideration area, where the composite extreme dry-hot synchronous event pair is for indicating that the composite extreme dry-hot events at any two locations are synchronous.

[0026] In addition, since the hotspot area of ​​the teleconnection composite extreme dry hot event corresponding to each target time period among multiple target time periods in the target study area is to be obtained, this embodiment describes obtaining the hotspot area of ​​the teleconnection composite extreme dry hot event in one target time period in the target study area.

[0027] Specifically, step 210 specifically includes step 210a and step 210b.

[0028] In step 210a, spatialized daily maximum temperature data and monthly self-calibrated Palmer Drought Severity Index data are obtained in a target time period of a target study area, and sorting is performed based on the daily maximum temperature data and monthly self-calibrated Palmer Drought Severity Index data to obtain multiple composite extreme dry and hot events in the target time period of the target study area.

[0029] In addition, this application will be explained based on the following: 1979-2022 is a complete time period formed from multiple target time periods, and the entire land area of ​​the Earth is the target study area. Daily maximum temperature data and monthly self-calibrated Palmer drought severity index data for the entire land area of ​​the Earth from 1979-2022, as well as data on the proportion of cultivated land area for the entire Earth from 2000-2003 are obtained.

[0030] In one embodiment, daily maximum temperature data and drought index data are first collected and used to define a composite extreme dry hot event. Hourly temperature data in the atmospheric reanalysis dataset is downloaded and acquired, with an original spatial resolution of 0.25° × 0.25°. The downloaded initial data is then processed to obtain daily maximum temperature data. Self-calibrated Palmer Drought Severity Index data is downloaded and acquired, with an original spatial resolution of 0.5° × 0.5°. To simplify calculations, the daily maximum temperature data and drought index data are interpolated to 2.5° × 2.5° using nearest neighbor interpolation. The preprocessed daily maximum temperature data and drought index data are used to recognize a composite extreme dry hot event. A high temperature event is defined as a daily maximum temperature exceeding the 90th percentile of the calendar day corresponding to the grid point for three or more consecutive days. A drought event is defined as a self-calibrated Palmer Drought Severity Index value less than -2. The simultaneous occurrence of a drought and a high temperature event is recognized as a composite extreme dry hot event. For each grid point with a latitude and longitude of 2.5°, identify the composite extreme dry and hot events that occurred between 1979 and 2022. i The sequence of occurrence times of the composite extreme dry and hot events recognized in x i} x=1, ..., ni where, ni is the grid point i is the total number of combined dry-hot events in t x i is the grid point i in x The occurrence time of the composite extreme dry hot event.

[0031] Furthermore, agricultural land data is collected. Raster data of the agricultural land area ratio for the time period 2000-2003 is obtained, and the spatial resolution of the data is 0.025° x 0.025°. The area of ​​a 0.025° x 0.025° grid across the entire Earth is calculated using the spherical trigonometric formula. The calculation formula is as follows: TIFF2025175990000002.tif1577Here, R is the radius of the Earth, 6371 km, Δλ is the difference in longitude, here 0.025°, φ1 and φ2 are the southern and northern latitude boundaries of the grid, respectively.

[0032] In step 210b, determine whether the occurrence time interval of any two composite extreme dry-hot events in the target consideration area is greater than a preset delay time, and if there are two composite extreme dry-hot events in the target consideration area whose occurrence time interval is greater than a preset delay time, determine the two composite extreme dry-hot events as a composite extreme dry-hot synchronous event pair; The above steps are repeated to obtain the number of composite extreme dry-hot synchronous event pairs in the target study area.

[0033] In one embodiment, the observation grid points i and j For grid points i Combined Extreme Dry and Hot Event in x and grid points j Combined Extreme Dry and Hot Event in y The delay between x,y i,j =t x i -t y j Observation grid points i and j , characteristic time interval τ x,y i,j is defined as half the occurrence time difference between an event and its immediate predecessor or successor in the composite dry-hot event sequence at two grid points, i.e., TIFF2025175990000003.tif24112 at the same time τ max =10 is defined as the maximum synchronization time interval.

[0034] |d x,y i,j |<τx,y i,j , and |d x,y i,j |<τ max Then, the observation grid points i Events in x and observation grid points j Events in y are considered to be a pair of synchronous events. The directionality of the synchronization can be defined by considering the order in which the combined extreme dry and hot events occurred at the two observation grid points. The direction is determined by the time interval d between the occurrence of the events. x,y i,j The direction is determined by the observation grid point, which is oriented from the event that occurred earlier to the event that occurred later. i and j The number of synchronization event pairs between i and j is expressed by the following equation, where i → j is the synchronization direction between the grid points i to grid points j indicates a preference for TIFF2025175990000004.tif23106Here, |·| indicates the absolute value, and ||·|| indicates that the cardinality of the set is to be found.

[0035] In step 220, a significance test is performed on the composite extreme dry-hot synchronous event pairs in the target consideration area, and a directed network of composite extreme dry-hot events is constructed based on the test results, where the directed network includes multiple nodes, and one node corresponds to one location where the composite extreme dry-hot event occurs in the target consideration area.

[0036] Specifically, step 220 specifically includes step 220a and step 220b.

[0037] In step 220a, a location where a composite extreme dry-hot event occurs in the target consideration area is determined as a node, and a significance test is performed on the composite extreme dry-hot synchronous event pair between two nodes in the target consideration area to obtain a significance threshold.

[0038] In step 220b, if the number of composite extreme dry-hot synchronous event pairs between the two nodes is greater than the significance threshold, establish a connection edge between the two nodes, and build a directed network of composite extreme dry-hot events based on the established connection edge.

[0039] In one embodiment, a significance test is performed on the synchronization features of the composite extreme dry and hot events based on the idea of ​​random shuffling. First, an arbitrary grid point i For the above recognized composite extreme dry-hot event sequence {t x i} x=1, ..., ni Random shuffling is performed on the randomly generated complex extreme dry-hot event sequence {t x i} null x=1, ..., ni The shuffling operation is performed for all grid points, and the number of synchronous event pairs between any two grid points is calculated based on the shuffled composite extreme dry-hot event sequence in accordance with step 102. The shuffling process is repeated a preset number of times, 2000 times in this embodiment, and the number of synchronous event pairs calculated based on the shuffled event sequence at any two grid points i → j is 2000. i→j Obtain the calculated ES i→j 95th percentile Δ 0.95 i→j Let be the threshold for the number of composite extreme dry-hot event pairs.

[0040] The longitude and latitude grid points where the data are located are used as nodes of the network, and the ES calculated for the composite extreme dry and hot event isi→j ES calculated by 2000 zero models ij 95th percentile Δ 0.95 i→j If it is larger, the synchronization relationship of the composite extreme dry-hot event from node i to j is considered to be significant, and establishes a connection edge directed from i to j between the two nodes.

[0041] The constructed directed network of complex extreme dry and hot events is expressed using an adjacency matrix, TIFF2025175990000005.tif2074 where δ ij is the Kronecker delta, TIFF2025175990000006.tif1545A ij = 1, it explains that there is a connecting edge pointing from observation grid point i to j, and A ij = 0 explains that there is no connecting edge pointing from observation grid point i to j.

[0042] In step 230, the in-degree index of each node in the directed network is calculated, and the location corresponding to the node whose in-degree index is greater than a preset threshold is determined as the hotspot region of the teleconnection composite extreme dry hot event in the target time period.

[0043] In one embodiment, Figure 3 is a schematic diagram of the spatial distribution of the in-degree of a node in a directed network according to the present application. Referring to Figure 3, the in-degree of a node in a directed network is the total number of directed edges pointing to the node. The calculation formula is as follows: TIFF2025175990000007.tif2846 where K in jis the in-degree of node j, N is the total number of nodes in the network, and A is the adjacency matrix of the directed network. In the composite extreme dry-hot synchronous network, nodes with large in-degree usually occur composite extreme dry-hot events after other nodes and are influenced by other regions. Therefore, we define the geographical locations represented by nodes whose in-degree values ​​exceed the 80th percentile of the in-degrees of all nodes in the network as hotspot regions of teleconnection composite extreme dry-hot risk.

[0044] In step 200, a trend analysis is performed on the cropland area sequence based on the hotspot areas of the teleconnection composite extreme dry hot events corresponding to each target time period among a plurality of target time periods in the target study area.

[0045] Specifically, step 200 specifically includes: The method includes overlaying agricultural land with hotspot areas of teleconnection composite extreme dry hot events corresponding to each target time period among a plurality of target time periods in the target consideration area, obtaining agricultural land areas with teleconnection composite extreme dry hot event risk in each target time period, and performing trend analysis on the agricultural land area sequence, wherein the agricultural land area sequence includes agricultural land areas with teleconnection composite extreme dry hot event risk in each target time period among the plurality of target time periods.

[0046] In this embodiment, taking the complete period 1979-2022 as an example, to examine the change trend of the teleconnection composite extreme dry and hot risk in agricultural land, a 5-year time window is used to slide and extract the complete composite extreme dry and hot event sequence, obtaining composite extreme dry and hot event sequences for 40 time periods from 1979-1983, 1980-1984, ..., 2018-2022. The 5-year time window can ensure that there are enough composite extreme dry and hot events within each window to support the calculation of event synchronization, and also ensure that there is enough time window to support the analysis of time trend changes.

[0047] The above steps are used to obtain the hotspot area of ​​the teleconnection composite extreme dry hot risk in each time window. The hotspot area is then subjected to nearest neighbor resampling to generate a 0 / 1 binarized raster in a 0.025° x 0.025° grid format, where 1 indicates that the location is a teleconnection composite extreme dry hot risk hotspot area and 0 indicates that it is a non-teleconnection composite extreme dry hot risk hotspot area. The binarized raster of the hotspot area, the cropland ratio data, and the 0.025° x 0.025° grid area data are multiplied by the corresponding location, and all rasters are summed to obtain the cropland area of ​​the teleconnection composite extreme dry hot risk in each time window.

[0048] In this embodiment, the trend test uses the Mann-Kendall method and Sen gradient. Specifically, given a time sequence x1, x2, … ,x n On the other hand, the calculation method of the Sen gradient β is as follows. TIFF2025175990000008.tif2167Here, the magnitude of the gradient indicates the magnitude of the trend.

[0049] The calculation formula for the Mann-Kendall method is as follows: TIFF2025175990000009.tif6981 where Q is the constructed test statistic, Z is the standardized test statistic, and var(Q) represents the variance of Q. For a given significance level α, |Z|>Z 1-α / 2 If the significance level is 0, the change trend of the time sequence at the significance level is significant.

[0050] Figure 4 is a schematic diagram of the trend of teleconnection composite extreme dry and hot risk of agricultural land according to the present application. The results of trend analysis on the agricultural land area sequence can be seen in Figure 4. Note that the method according to the present application can be applied to agricultural land all over the world or to agricultural land in any region.

[0051] This embodiment can quantitatively represent the teleconnection risk of complex extreme dry and hot events in agricultural land and its development characteristics from a complex network perspective by examining the synchronous relationship between global complex extreme dry and hot events in different time windows. It is easy to operate and can be flexibly applied to the detection and management of teleconnection risks of other weather and climate events.

[0052] The above is a description of the steps in the method for detecting and analyzing trends for teleconnection composite extreme dry hot events in agricultural land according to the present application. As can be seen from the description of the steps, the method for detecting and analyzing trends for teleconnection composite extreme dry hot events in agricultural land according to the present application includes obtaining hotspot areas of teleconnection composite extreme dry hot events corresponding to each target time slot among a plurality of target time slots in a target consideration area, wherein the hotspot areas of teleconnection composite extreme dry hot events corresponding to any of the plurality of target time slots are calculated based on a directed network of the composite extreme dry hot events corresponding to the target time slot, and the directed network of the composite extreme dry hot events is obtained based on location information of composite extreme dry hot events occurring in the corresponding target time slot, and performing a trend analysis on agricultural land area sequences based on the hotspot areas of teleconnection composite extreme dry hot events corresponding to each target time slot among the plurality of target time slots in the target consideration area. Therefore, the present application analyzes the teleconnection characteristics of multivariate extreme weather and climate events, i.e., composite extreme dry and hot events, identifies hotspot areas of composite extreme dry and hot events, and performs overlay analysis with agricultural land, thereby enabling the investigation of the teleconnection composite extreme dry and hot risks and their changing trends facing agricultural land on the entire globe or in certain regions, which is advantageous for the investigation and management of composite extreme dry and hot events, and the method is simple and easy to operate.

[0053] Note that, in the method for detecting and analyzing trends of teleconnection complex extreme dry hot risk hotspot areas in agricultural land according to an embodiment of the present application, the execution body may be a device for detecting and analyzing trends of teleconnection complex extreme dry hot risk hotspot areas in agricultural land, or may be a control module for executing the method for detecting and analyzing trends of teleconnection complex extreme dry hot risk hotspot areas in agricultural land in the device for detecting and analyzing trends of teleconnection complex extreme dry hot risk hotspot areas in agricultural land. In the embodiment of the present application, the device for detecting and analyzing trends of teleconnection complex extreme dry hot risk hotspot areas in agricultural land will be described using an example in which the device for detecting and analyzing trends of teleconnection complex extreme dry hot risk hotspot areas in agricultural land executes the method for detecting and analyzing trends of teleconnection complex extreme dry hot risk hotspot areas in agricultural land.

[0054] It should be noted that in the embodiments of the present application, the methods for detecting and analyzing trend of teleconnection complex extreme dry hotspot risk areas in farmland shown in the drawings of each method above are all illustratively described with reference to one of the drawings in the embodiments of the present application. When specifically implemented, the methods for detecting and analyzing trend of teleconnection complex extreme dry hotspot risk areas in farmland shown in the drawings of each method above may be implemented in combination with any other combinable drawings exemplified in the above embodiments, and no further description will be given here.

[0055] The following describes the detection and trend analysis device for teleconnection complex extreme dry hot risk hotspot areas in agricultural land related to the present application, and the above-mentioned detection and trend analysis method for teleconnection complex extreme dry hot risk hotspot areas in agricultural land described below can be referred to correspondingly.

[0056] FIG. 5 is a schematic diagram of the structure of the teleconnection complex extreme dry hot spot risk detection and trend analysis device for agricultural land according to the present application. As shown in FIG. 5, the teleconnection complex extreme dry hot spot risk detection and trend analysis device for agricultural land according to the present application: a detection module 501 configured to obtain hotspot areas of teleconnection composite extreme dry hot events corresponding to each target time slot among a plurality of target time slots in a target consideration area, wherein the hotspot areas of the teleconnection composite extreme dry hot events corresponding to any target time slot among the plurality of target time slots are calculated based on a directed network of the composite extreme dry hot events corresponding to the target time slot, and the directed network of the composite extreme dry hot events is obtained based on location information of the composite extreme dry hot events occurring in the corresponding target time slot; and an analysis module 502 configured to perform trend analysis on the cropland area sequence based on hotspot areas of teleconnection composite extreme dry hot events corresponding to each target time slot among a plurality of target time slots in the target study area.

[0057] The detection and trend analysis device for teleconnection composite extreme dry hot risk hotspot areas in agricultural land of the present application obtains hotspot areas of teleconnection composite extreme dry hot events corresponding to each target time period among multiple target time periods in a target consideration area, wherein the hotspot area of ​​the teleconnection composite extreme dry hot event corresponding to any target time period among the multiple target time periods is calculated based on a directed network of the composite extreme dry hot event corresponding to the target time period, and the directed network of the composite extreme dry hot event is obtained based on location information of the composite extreme dry hot event occurring in the corresponding target time period, and performs trend analysis on the agricultural land area sequence based on the hotspot area of ​​the teleconnection composite extreme dry hot event corresponding to each target time period among the multiple target time periods in the target consideration area. Therefore, the present application analyzes the teleconnection characteristics of multivariate extreme weather and climate events, i.e., composite extreme dry and hot events, identifies hotspot areas of composite extreme dry and hot events, and performs overlay analysis with agricultural land, thereby enabling the investigation of the teleconnection composite extreme dry and hot risks and their changing trends facing agricultural land on the entire globe or in certain regions, which is advantageous for the investigation and management of composite extreme dry and hot events, and the method is simple and easy to operate.

[0058] Based on the above embodiment, in this embodiment, the detection module 501 specifically: Obtaining a plurality of composite extreme dry-hot events in a target time period of a target study area, and calculating the number of composite extreme dry-hot synchronous event pairs in the target study area, wherein the composite extreme dry-hot synchronous event pairs are for indicating that composite extreme dry-hot events at any two locations are synchronized; Perform a significance test on the composite extreme dry-hot synchronous event pairs in the target study area, and construct a directed network of composite extreme dry-hot events based on the test result, where the directed network includes multiple nodes, and each node corresponds to a location where the composite extreme dry-hot event occurs in the target study area; The method is configured to calculate the degree index of each node in the directed network, and determine the locations corresponding to nodes whose degree index is greater than a preset threshold as hotspot regions of a teleconnection composite extreme dry hot event in the target time period.

[0059] Based on the above embodiment, in this embodiment, the device further includes an acquisition module, and the acquisition module specifically includes: The method is configured to obtain spatialized daily maximum temperature data and monthly self-calibrated Palmer Drought Severity Index data in a target time period of a target study area, and perform sorting based on the daily maximum temperature data and the monthly self-calibrated Palmer Drought Severity Index data to obtain a plurality of composite extreme dry-hot events in the target time period of the target study area.

[0060] Based on the above embodiment, in this embodiment, the device further includes a calculation module, and the calculation module specifically: Determine whether the occurrence time interval of any two composite extreme dry-hot events in the target consideration area is greater than a preset delay time, and if there are two composite extreme dry-hot events in the target consideration area whose occurrence time interval is greater than a preset delay time, determine the two composite extreme dry-hot events as a composite extreme dry-hot synchronous event pair; and repeatedly performing the above steps to obtain a number of composite extreme dry-hot synchronous event pairs in the target study area.

[0061] Based on the above embodiment, in this embodiment, the device further includes a construction module, and the construction module specifically includes: Determine a location where a composite extreme dry-hot event occurs in the target consideration area as a node, and perform a significance test on a composite extreme dry-hot synchronous event pair between two nodes in the target consideration area to obtain a significance threshold; If the number of composite extreme dry-hot synchronous event pairs between the two nodes is greater than the significance threshold, establishing a connection edge between the two nodes and constructing a directed network of composite extreme dry-hot events based on the established connection edge.

[0062] Based on the above embodiment, in this embodiment, the analysis module 502 specifically: The method is configured to overlay agricultural land with hotspot areas of teleconnection composite extreme dry hot events corresponding to each target time period among a plurality of target time periods in the target consideration area, obtain agricultural land areas with teleconnection composite extreme dry hot event risk in each target time period, and perform trend analysis on the agricultural land area sequence, wherein the agricultural land area sequence includes agricultural land areas with teleconnection composite extreme dry hot event risk in each target time period among the plurality of target time periods.

[0063] 6 illustrates a schematic diagram of an entity structure of an electronic device, and as shown in FIG. 6, the electronic device may include a processor 610, a communications interface 620, a memory 630, and a communications bus 640, where the processor 610, the communications interface 620, and the memory 630 communicate with each other via the communications bus 640. The processor 610 can invoke logic instructions in the memory 630 to perform a method for detecting and trending teleconnection complex extreme dry hot risk hotspot areas in agricultural land, the method including: Obtaining hotspot areas of teleconnection composite extreme dry hot events corresponding to each target time slot among a plurality of target time slots in a target study area, wherein the hotspot areas of teleconnection composite extreme dry hot events corresponding to any target time slot among the plurality of target time slots are calculated based on a directed network of composite extreme dry hot events corresponding to the target time slot, and the directed network of composite extreme dry hot events is obtained based on location information of composite extreme dry hot events occurring in the corresponding target time slot; and performing a trend analysis on the cropland area sequence based on hotspot areas of teleconnection composite extreme dry hot events corresponding to each target time period among a plurality of target time periods in the target study area.

[0064] Furthermore, the logic instructions in the memory 630 may be implemented in the form of a software functional unit, or may be stored in a computer-readable storage medium when sold or used as an independent product. Based on this understanding, the technical solution of the present application, its essence, or a portion contributing to the prior art, or a portion of the technical solution, may be embodied in the form of a software product, and the computer software product is stored in a storage medium and includes several instructions for causing a computer device (e.g., a personal computer, a server, a network device, etc.) to perform all or some of the steps of the methods described in each embodiment of the present application. The storage medium includes various media capable of storing program code, such as a U disk, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0065] Meanwhile, the present application further provides a computer program product including a computer program stored in a computer-readable storage medium, the computer program including program instructions, which, when executed by a computer, can cause the computer to execute the method for detecting and analyzing trends of teleconnection complex extreme dry hot risk hotspot areas in agricultural land according to any of the above aspects, the method including: Obtaining hotspot areas of teleconnection composite extreme dry hot events corresponding to each target time slot among a plurality of target time slots in a target study area, wherein the hotspot areas of teleconnection composite extreme dry hot events corresponding to any target time slot among the plurality of target time slots are calculated based on a directed network of composite extreme dry hot events corresponding to the target time slot, and the directed network of composite extreme dry hot events is obtained based on location information of composite extreme dry hot events occurring in the corresponding target time slot; and performing a trend analysis on the cropland area sequence based on hotspot areas of teleconnection composite extreme dry hot events corresponding to each target time period among a plurality of target time periods in the target study area.

[0066] On the other hand, the present application further provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, performs the method for detecting and analyzing trends of teleconnection complex extreme dry hot risk hotspot areas in agricultural land according to each of the above aspects, and the method includes: Obtaining hotspot areas of teleconnection composite extreme dry hot events corresponding to each target time slot among a plurality of target time slots in a target study area, wherein the hotspot areas of teleconnection composite extreme dry hot events corresponding to any target time slot among the plurality of target time slots are calculated based on a directed network of composite extreme dry hot events corresponding to the target time slot, and the directed network of composite extreme dry hot events is obtained based on location information of composite extreme dry hot events occurring in the corresponding target time slot; and performing a trend analysis on the cropland area sequence based on hotspot areas of teleconnection composite extreme dry hot events corresponding to each target time period among a plurality of target time periods in the target study area.

[0067] The above-described embodiments of the device are merely exemplary. The units described herein as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, i.e., they may be located in one place or distributed across multiple network units. The objectives of the technical solutions of the present embodiments can be achieved by selecting some or all of the modules herein according to actual needs. Those skilled in the art can understand and implement the same without any creative effort.

[0068] From the above description of the embodiments, it will be clear to those skilled in the art that each embodiment may be realized by combining software with a necessary common hardware platform, or by hardware. Based on this understanding, the essence of the above technical proposals, or portions that contribute to the prior art, may be embodied in the form of a software product. The computer software product may be stored in a computer-readable storage medium, such as a ROM / RAM, a magnetic disk, or an optical disk, and includes several instructions for causing a computer device (e.g., a personal computer, a server, or a network device) to execute the methods described in each embodiment or several portions of the embodiments.

[0069] Finally, it should be explained that the above embodiments are only for explaining the technical solutions of the present application, and are not intended to limit the same. Although the present application has been described in detail with reference to the above embodiments, it should be understood by those skilled in the art that it is still possible to modify the technical solutions described in each of the above embodiments or replace some of the technical features with equivalents, and such modifications or replacements will not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of each of the embodiments of the present application.

Claims

1. Obtaining hotspot areas of teleconnection composite extreme dry hot events corresponding to each target time slot among a plurality of target time slots in a target study area, wherein the hotspot areas of teleconnection composite extreme dry hot events corresponding to any target time slot among the plurality of target time slots are calculated based on a directed network of composite extreme dry hot events corresponding to the target time slot, and the directed network of composite extreme dry hot events is obtained based on location information of composite extreme dry hot events occurring in the corresponding target time slot; A method for detecting and analyzing trends of teleconnection composite extreme dry hot risk hotspot areas in agricultural land, comprising: performing trend analysis on agricultural land area sequences based on hotspot areas of teleconnection composite extreme dry hot events corresponding to each target time period among a plurality of target time periods in the target consideration area.

2. The above-mentioned obtaining a hot spot area of ​​a teleconnection composite extreme dry hot event corresponding to each target time period among a plurality of target time periods in a target study area includes: Obtaining a plurality of composite extreme dry-hot events in a target time period of a target study area, and calculating the number of composite extreme dry-hot synchronous event pairs in the target study area, wherein the composite extreme dry-hot synchronous event pairs are for indicating that composite extreme dry-hot events at any two locations are synchronized; Perform a significance test on the composite extreme dry-hot synchronous event pairs in the target study area, and construct a directed network of composite extreme dry-hot events based on the test result, where the directed network includes a plurality of nodes, and each node corresponds to a location where the composite extreme dry-hot event occurs in the target study area; calculating the degree index of each node in the directed network, and determining the location corresponding to the node whose degree index is greater than a preset threshold as a hotspot region of a teleconnection composite extreme dry hot event in the target time period. The method for detecting and analyzing trends of teleconnection complex extreme dry hot risk hotspot areas in agricultural land as claimed in claim 1.

3. The aforementioned acquisition of a plurality of composite extreme dry and hot events in a target time period of a target study area includes: The method includes acquiring spatialized daily maximum temperature data and monthly self-calibrated Palmer Drought Severity Index data in a target time period of a target study area, and performing sorting based on the daily maximum temperature data and the monthly self-calibrated Palmer Drought Severity Index data to obtain a plurality of composite extreme dry and hot events in the target time period of the target study area. The method for detecting and analyzing trends of teleconnection complex extreme dry hot risk hotspot areas in agricultural land as claimed in claim 2.

4. Calculating the number of composite extreme dry-hot synchronous event pairs in the target study area includes: Determine whether the occurrence time interval of any two composite extreme dry-hot events in the target consideration area is greater than a preset delay time, and if there are two composite extreme dry-hot events in the target consideration area whose occurrence time interval is greater than the preset delay time, determine the two composite extreme dry-hot events as a composite extreme dry-hot synchronous event pair; and repeatedly performing the steps to obtain a number of composite extreme dry-hot synchronous event pairs in the target study area. The method for detecting and analyzing trends of teleconnection complex extreme dry hot risk hotspot areas in agricultural land as described in claim 3.

5. The above-mentioned performing a significance test on the composite extreme dry and hot synchronous event pairs in the target study area and constructing a directed network of composite extreme dry and hot events based on the test result includes: Determine a location where a composite extreme dry-hot event occurs in the target consideration area as a node, and perform a significance test on a composite extreme dry-hot synchronous event pair between two nodes in the target consideration area to obtain a significance threshold; and if the number of composite extreme dry-hot synchronous event pairs between the two nodes is greater than the significance threshold, establishing a connection edge between the two nodes and constructing a directed network of composite extreme dry-hot events based on the established connection edge. The method for detecting and analyzing trends of teleconnection complex extreme dry hot risk hotspot areas in agricultural land as claimed in claim 2.

6. The above-mentioned performing trend analysis on the cropland area sequence based on the hot spot area of ​​the teleconnection composite extreme dry hot event corresponding to each target time period among the plurality of target time periods in the target study area, and overlaying agricultural land with hotspot areas of teleconnection composite extreme dry hot events corresponding to each target time period among a plurality of target time periods in the target study area, obtaining the area of ​​agricultural land at risk of the teleconnection composite extreme dry hot event in each target time period, and performing trend analysis on the sequence of agricultural land areas, wherein the sequence of agricultural land areas includes the area of ​​agricultural land at risk of the teleconnection composite extreme dry hot event in each target time period among the plurality of target time periods. The method for detecting and analyzing trends of teleconnection complex extreme dry hot risk hotspot areas in agricultural land as claimed in claim 1.

7. a detection module configured to obtain hotspot areas of teleconnection composite extreme dry hot events corresponding to each target time slot among a plurality of target time slots in a target consideration area, wherein the hotspot areas of teleconnection composite extreme dry hot events corresponding to any target time slot among the plurality of target time slots are calculated based on a directed network of composite extreme dry hot events corresponding to the target time slot, and the directed network of composite extreme dry hot events is obtained based on location information of composite extreme dry hot events occurring in the corresponding target time slot; and an analysis module configured to perform trend analysis on agricultural land area sequences based on hotspot areas of teleconnection composite extreme dry hot events corresponding to each target time period among a plurality of target time periods in the target consideration area.

8. Specifically, the detection module: Obtaining a plurality of composite extreme dry-hot events in a target time period of a target study area, and calculating the number of composite extreme dry-hot synchronous event pairs in the target study area, wherein the composite extreme dry-hot synchronous event pairs are for indicating that composite extreme dry-hot events at any two locations are synchronized; Perform a significance test on the composite extreme dry-hot synchronous event pairs in the target study area, and construct a directed network of composite extreme dry-hot events based on the test result, where the directed network includes a plurality of nodes, and each node corresponds to a location where the composite extreme dry-hot event occurs in the target study area; calculating an in-degree index for each node in the directed network, and determining a location corresponding to a node whose in-degree index is greater than a preset threshold as a hotspot region of a teleconnection composite extreme dry hot event in the target time period. The apparatus for detecting and trending teleconnection complex extreme dry hot risk hotspot areas in agricultural land as claimed in claim 7.

9. 10. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable by the processor, wherein when the processor executes the computer program, the electronic device realizes the method for detecting and analyzing trends of teleconnection complex extreme dry hot risk hotspot areas in agricultural land described in any one of claims 1 to 6.

10. A non-transitory computer-readable storage medium having a computer program stored thereon, the non-transitory computer-readable storage medium being characterized in that, when the computer program is executed by a processor, the non-transitory computer-readable storage medium realizes the method for detecting and analyzing trends in teleconnection complex extreme dry hot risk hotspot areas in agricultural land described in any one of claims 1 to 6.

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