A method and device for expressing the correlation between ocean dynamic evolution and ENSO events

Abstract

The present invention discloses a method and device for expressing the association between ocean dynamic evolution and ENSO events. Based on object-oriented technology, an object expression of an abnormal ocean change process object is established, including a process object ID, process object attribute information, process object spatial information and process object time information; based on object-oriented technology, an ENSO object expression of an ENSO event is established, including an event object ID, event attribute information and event time information; based on a preset temporal topological relationship discrimination rule, a target temporal topological relationship between the abnormal ocean change process object and the ENSO object is established; based on the target temporal topological relationship, an association expression between the abnormal ocean change process object and the ENSO object is established. In the above process, an association expression between the abnormal ocean change process object and the ENSO object is established based on the target temporal topological relationship, and the association between the abnormal ocean change process object and the ENSO object is realized.

Description

Technical Field

[0001] The present invention relates to the field of geographic time-space mining and ocean space information technology, and in particular to a method and device for expressing the association between ocean dynamic evolution and ENSO events. Background Art

[0002] Abnormal changes in marine environmental elements refer to changes in marine environmental elements relative to the average state of long-term series, such as abnormal changes in the average monthly sea surface temperature, abnormal changes in the average seasonal sea surface salinity, etc., referred to as abnormal marine changes. Abnormal marine changes have regional clustering characteristics in space and evolutionary characteristics of generation, development and extinction in time. ENSO is a typical signal of global climate change and also has the evolutionary characteristics of generation, development and extinction. The occurrence and development of ENSO events affect the spatial distribution and temporal evolution of abnormal marine changes. Conversely, the spatiotemporal distribution and evolution characteristics of abnormal marine changes can also characterize the type and intensity of ENSO events.

[0003] In the existing technology, due to the lack of support for the expression method of spatiotemporal dynamic correlation, the current research on the relationship between the two is mainly based on qualitative analysis, which makes it difficult to finely characterize the relationship between the evolutionary structure of abnormal ocean changes and the type and intensity of ENSO events. Summary of the invention

[0004] In view of this, the present invention provides a method and device for expressing the association between ocean dynamic evolution and ENSO events, which is used to solve the problem that due to the lack of support for the spatiotemporal dynamic association expression method in the prior art, the current relationship between the two is mainly based on qualitative analysis, and it is difficult to finely describe the relationship between the evolution structure of abnormal ocean changes and the type and intensity of ENSO events. The specific scheme is as follows:

[0005] A method for expressing the association between ocean dynamic evolution and ENSO events, including:

[0006] Based on object-oriented technology, the object expression of the ocean abnormal change process object is established, including: process object ID, process object attribute information, process object spatial information and process object time information;

[0007] Based on object-oriented technology, the ENSO object expression of ENSO events is established, including: event object ID, event attribute information and event time information;

[0008] Determine the target temporal topological relationship between the ocean abnormal change process object and the ENSO object based on a preset temporal topological relationship discrimination rule;

[0009] Based on the target temporal topological relationship, an associated expression of the ocean abnormal change process object and the ENSO object is established.

[0010] The above method can optionally establish an object expression of the ocean abnormal change process object based on object-oriented technology, including:

[0011] Obtaining process object attribute information A1 of the abnormal ocean change process object, wherein A1={Name1, Type1, Value1}, Name1 represents the name of the abnormal ocean change process object, Type1 represents the type of the abnormal ocean change process object, and Value1 represents the attribute value of the abnormal ocean change process object;

[0012] Obtain the process object spatial information S of the abnormal ocean change process object, where S = {Structure, OriginalPlace, EvolvingPlace, ExtinctionPlace}

[0013] S = {Structure, OriginalPlace, EvolvingPlace, ExtinctionPlace)}, Structure represents the spatial evolution structure of the abnormal ocean change process object, OriginalPlace represents the source of the abnormal ocean change process object, EvolvingPlace represents the evolution area of ​​the abnormal ocean change process object, and ExtinctionPlace represents the extinction place of the abnormal ocean change process object;

[0014] Obtaining the process object time information T1 of the abnormal ocean change process object, wherein T1={Duration1, StartTime1, EndTime1, TimeScale1}, Duration1 represents the duration of the abnormal ocean change process object, StartTime2 represents the start time of the abnormal ocean change process object, EndTime1 represents the end time of the abnormal ocean change process object, and TimeScale1 represents the data observation scale of the abnormal ocean change process object;

[0015] A preset ocean abnormal change process object expression is constructed based on the attribute information A1, the spatial information S and the time information T1, and the ocean abnormal change process object expression is established, wherein the ocean abnormal change process object expression is:

[0016] Process object={POID,A1,S,T1}

[0017] Among them, Process object represents the expression of the abnormal ocean change process object, and POID represents the process object ID, which is used to identify the abnormal ocean change process object.

[0018] In the above method, optionally, obtaining the spatial information S of the abnormal ocean change process object includes:

[0019] Acquire the centroid position of the abnormal ocean change process object, perform kernel density analysis on the centroid position based on a kernel density analysis function, and obtain a kernel density spatial distribution map;

[0020] Determine the source, evolution area and disappearance area of ​​the abnormal ocean change process object based on the kernel density spatial distribution map;

[0021] Based on the preset evolution structure discrimination rules, the spatial evolution structure of the ocean abnormal change process object is determined.

[0022] The above method may optionally determine the spatial evolution structure of the ocean abnormal change process object based on a preset evolution structure discrimination rule, including:

[0023] If the ocean abnormal change process object only has a development relationship, the spatial evolution structure is evolution structure 1; or,

[0024] If the ocean abnormal change process object only has a development relationship and a merger relationship, the spatial evolution structure is an evolution structure 2; or,

[0025] If the object of the abnormal ocean change process only has a development relationship and a split relationship, the spatial evolution structure is an evolution structure 3; or,

[0026] If the ocean abnormal change process object has a development relationship, two merge relationships and two split relationships, the spatial evolution structure is evolution structure 4; or,

[0027] If the ocean abnormal change process object simultaneously has a development relationship, more than two merging relationships, and more than two splitting relationships, then the spatial evolution structure is evolution structure 5.

[0028] The above method can optionally establish an ENSO object expression of ENSO events based on object-oriented technology, including:

[0029] Acquire event attribute information A2 of the ENSO event, where:

[0030] A2 = {Name2, Type2, Intensity2}, Name2 represents the name of the ENSO event, Type2 represents the type of the ENSO event, and Intensity2 represents the intensity of the ENSO event;

[0031] The event time information T2 of the ENSO event is obtained, where:

[0032] T2 = {Duration2, StartTime2, EndTime2, TimeScale2}, Duration2 represents the duration of the ENSO event, StartTime2 represents the start time of the ENSO event, EndTime2 represents the end time of the ENSO event, and TimeScale2 represents the observation scale of the ENSO event;

[0033] A preset ENSO object expression is constructed based on the event attribute information A2 and the event time information T2 to establish the ENSO object expression, wherein the preset ENSO object expression is:

[0034] ENSO = {EID, A2, T2}

[0035] Among them, ENSO is the ENSO object expression of the ENSO event, and EID is the event object ID, which is used to uniquely identify the ENSO event.

[0036] The above method may optionally determine the target temporal topological relationship between the ocean abnormal change process object and the ENSO object based on a preset temporal topological relationship discrimination rule, including:

[0037] If the ocean abnormal change process object and the ENSO object have the same start time and different end time, that is, (Po st =Eo et )∩(Po et ≠Eo et ), then the target temporal topological relationship between the two is co-occurrence, where Po st Indicates the start time of the abnormal ocean change process object, Po et Indicates the end time of the abnormal ocean change process object, Eo st Indicates the start time of the ENSO object, Eo et Indicates the end time of the ENSO object; or

[0038] If the ENSO object occurs when the ocean abnormal change process object ends, or the ocean abnormal change process object occurs when the ENSO object occurs, that is, (Po st =Eo et )∪(Po et =Eo st ), then the target temporal topological relationship between the two is successive occurrence; or,

[0039] If the ocean abnormal change process object and the ENSO object have the same start time and the same end time, that is, (Po st =Eos t)∩(Po et =Eo et ), then the target temporal topological relationship between the two is the same occurrence; or,

[0040] If the ocean abnormal change process object and the ENSO object have the same end time and different start time, that is, (Po st ≠Eo st )∩(Po et =Eo et ), then the target temporal topological relationship between the two ends together; or,

[0041] If the start time of the abnormal ocean change process object is later than the start time of the ENSO object, and the end time of the abnormal ocean change process object is earlier than the end time of the ENSO object, or the start time of the abnormal ocean change process object is earlier than the start time of the ENSO object, and the end time of the abnormal ocean change process object is later than the end time of the ENSO object, that is, ((Po st <Eo st )∩(Po et >Eo et ))∪((Po st >Eo st )∩(Po et <Eo et )), then the target temporal topological relationship between the two is a containment relationship; or,

[0042] If the start time of the abnormal ocean change process object is later than the start time of the ENSO object and earlier than the end time of the ENSO object, or the end time of the abnormal ocean change process object is earlier than the start time of the ENSO object and later than the end time of the ENSO object, that is, ((Po st <Eo st )∩(Po st >Eo et ))∪((Po et <Eo st )∩(Po et >Eo et )), then the target temporal topological relationship between the two is an overlapping relationship; or,

[0043] If the ENSO object occurs T unit time after the end of the abnormal ocean change process object, or the abnormal ocean change process object occurs T unit time after the end of the ENSO object, that is, (Po st ≤Eo et +T)∪(Po et ≥Eoet +T), then the target temporal topological relationship between the two is occurrence-after-occurrence (T).

[0044] The above method, optionally, establishes an associated expression of the ocean abnormal change process object and the ENSO object based on the target temporal topological relationship, including:

[0045] Establishing an association table between the abnormal ocean change process object and the ENSO object based on the target temporal topological relationship, wherein the association table includes: the abnormal ocean change process object ID, the ENSO object ID, the target temporal topological relationship and the target temporal topological relationship ID;

[0046] The abnormal ocean change process object is linked based on the ocean process ID, and the ENSO object is linked based on the ENSO object.

[0047] A device for expressing the correlation between ocean dynamic evolution and ENSO events, comprising:

[0048] The first establishment module is used to establish the object expression of the ocean abnormal change process object based on object-oriented technology, including: process object ID, process object attribute information, process object space information and process object time information;

[0049] The second building module is used to build the ENSO object expression of the ENSO event based on the object-oriented technology, including: event object ID, event attribute information and event time information;

[0050] A determination module, used to determine the target temporal topological relationship between the ocean abnormal change process object and the ENSO object based on a preset temporal topological relationship discrimination rule;

[0051] The third establishing module is used to establish the associated expression of the ocean abnormal change process object and the ENSO object based on the target temporal topological relationship.

[0052] In the above device, optionally, the first establishing module includes:

[0053] A first acquisition unit is used to acquire process object attribute information A1 of the abnormal ocean change process object, wherein A1={Name1, Type1, Value1}, Name1 represents the name of the abnormal ocean change process object, Type1 represents the type of the abnormal ocean change process object, and Value1 represents the attribute value of the abnormal ocean change process object;

[0054] The second acquisition unit is used to acquire the process object spatial information S of the abnormal ocean change process object, wherein:

[0055] S={Structure, OriginalPlace, EvolvingPlace, ExtinctionPlace}

[0056] S = {Structure, OriginalPlace, EvolvingPlace, ExtinctionPlace)}, Structure represents the spatial evolution structure of the abnormal ocean change process object, OriginalPlace represents the source of the abnormal ocean change process object, EvolvingPlace represents the evolution area of ​​the abnormal ocean change process object, and ExtinctionPlace represents the extinction place of the abnormal ocean change process object;

[0057] The third acquisition unit is used to acquire the process object time information T1 of the abnormal ocean change process object, wherein T1={Duration1, StartTime1, EndTime1, TimeScale1}, Duration1 represents the duration of the abnormal ocean change process object, StartTime1 represents the start time of the abnormal ocean change process object, EndTime1 represents the end time of the abnormal ocean change process object, and TimeScale1 represents the data observation scale of the abnormal ocean change process object;

[0058] The first establishing unit is used to construct a preset ocean abnormal change process object expression based on the attribute information A1, the spatial information S and the time information T1, and establish the ocean abnormal change process object expression, wherein the ocean abnormal change process object expression is:

[0059] Process object={POID,A1,S,T1}

[0060] Among them, Process object represents the expression of the abnormal ocean change process object, and POID represents the process object ID, which is used to identify the abnormal ocean change process object.

[0061] In the above device, optionally, the second establishing module includes:

[0062] A fourth acquisition unit is used to acquire event attribute information A2 of the ENSO event, wherein A2={Name2, Type2, Intensity2}, Name2 represents the name of the ENSO event, Type2 represents the type of the ENSO event, and Intensity2 represents the intensity of the ENSO event;

[0063] A fifth acquisition unit is used to acquire event time information T2 of the ENSO event, wherein T2={Duration2, StartTime2, ENdTime2, TimeScale2}, Duration2 represents the duration of the ENSO event, StartTime2 represents the start time of the ENSO time, EndTime2 represents the end time of the ENSO event, and TimeScale2 represents the observation scale of the ENSO event;

[0064] The second establishing unit is used to construct a preset ENSO object expression based on the attribute information A2 and the time information T2, and establish the ENSO object expression, wherein the preset ENSO object expression is:

[0065] ENSO = {EID, A2, T2}

[0066] Among them, ENSO is the ENSO object expression of the ENSO event, and EID is the event object ID, which is used to uniquely identify the ENSO event.

[0067] Compared with the prior art, the present invention has the following advantages:

[0068] The present invention discloses a method and device for expressing the association between ocean dynamic evolution and ENSO events. Based on object-oriented technology, an object expression of an abnormal ocean change process object is established, including a process object ID, process object attribute information, process object spatial information and process object time information; based on object-oriented technology, an ENSO object expression of an ENSO event is established, including an event object ID, event attribute information and event time information; based on a preset temporal topological relationship discrimination rule, a target temporal topological relationship between the abnormal ocean change process object and the ENSO object is established; based on the target temporal topological relationship, an association expression between the abnormal ocean change process object and the ENSO object is established. In the above process, an association expression between the abnormal ocean change process object and the ENSO object is established based on the target temporal topological relationship, and the association between the abnormal ocean change process object and the ENSO object is realized. BRIEF DESCRIPTION OF THE DRAWINGS

[0069] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0070] Figure 1 A flow chart of a method for expressing the association between ocean dynamic evolution and ENSO events disclosed in an embodiment of the present application;

[0071] Figure 2 A schematic diagram of an object evolution relationship of an abnormal ocean change process disclosed in an embodiment of the present application;

[0072] Figure 3 A schematic diagram of an object evolution structure of an abnormal ocean change process disclosed in an embodiment of the present application;

[0073] Figure 4 A schematic diagram of the temporal topological relationship between an abnormal ocean change process object and an ENSO object disclosed in an embodiment of the present application;

[0074] Figure 5 A schematic diagram of the association between an abnormal ocean change process object and an ENSO object disclosed in an embodiment of the present application;

[0075] Figure 6 This is a structural block diagram of a device for expressing the association between ocean dynamic evolution and ENSO events disclosed in an embodiment of the present application. DETAILED DESCRIPTION

[0076] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0077] The above description of the disclosed embodiments enables one skilled in the art to implement or use the present invention. Various modifications to these embodiments will be apparent to one skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but rather to the widest scope consistent with the principles and novel features disclosed herein.

[0078] The present invention discloses a method and device for expressing the association between the dynamic evolution of the ocean and ENSO events, which are applied to the process of associating the dynamic evolution of the ocean with ENSO events. Abnormal changes in the ocean are an important part of global climate change, and ENSO is a typical signal of global climate change. The occurrence and development of ENSO events affect the spatial distribution of abnormal changes in the ocean and their evolution in time. Conversely, the spatiotemporal distribution and evolution characteristics of abnormal changes in the ocean can also characterize the type and intensity of ENSO events. Existing studies have shown that the spatiotemporal structure of the source, merger, splitting occurrence area and extinction area of ​​abnormal changes in ocean surface temperature is closely related to the type of ENSO event (CP type ENSO, EP type ENSO); the merger, splitting and other behaviors of abnormal changes in ocean surface temperature are closely related to the enhancement and weakening of ENSO events. Therefore, the spatiotemporal evolution characteristics of abnormal changes in the ocean provide new ideas for research on the identification and prediction of ENSO events.

[0079] The abnormal changes in the ocean have regional clustering characteristics in space, and the spatial structure and attributes have the process characteristics of generation and disappearance in time. The formal expression is shown in formula (1). The abnormal changes in the ocean are composed of three elements: space (S1), attribute (A1) and time (T1). The space expresses the spatial structure s of the abnormal changes in the ocean. The spatial structure changes with time and is a function of time; the attribute expresses the attribute characteristics a of the abnormal changes in the ocean. The attribute characteristics change with time and are a function of time; time is the duration of the abnormal changes in the ocean, and the start time t is used. s1 and end time t e1 Express.

[0080] MAV=f(S1,A1,T1)

[0081] S1=f(s,t)t∈T1

[0082] A1=f(a,t)t∈T1

[0083] T1=[t s1 :t e1 ] (1)

[0084] An ENSO event is defined as an index sequence in which the ENSO index is greater than a specific threshold for 5 consecutive months or more. The formal expression is shown in formula (2). An ENSO event consists of two elements: the ENSO index (I) and time (T2). The ENSO index expresses the intensity of the ENSO event i, which changes over time and is a function of time; the time expresses the start time t of the ENSO event s2 and end time t e2 .

[0085] ENSO=f(I,T2)

[0086] I=f(i,t)t∈T2

[0087] T2=[t s2 :t e2 ] (2)

[0088] Formula (2) shows that ENSO events do not have spatial information, but the spatial information of ocean anomaly changes is crucial to the identification of changes in the intensity and types of ENSO events. In addition, the duration of ENSO events and ocean anomaly changes is generally inconsistent. Therefore, there are challenges in expressing the spatiotemporal correlation between ocean anomaly changes and ENSO events.

[0089] ENSO events and abnormal ocean changes have coupling correlation characteristics. In the early days, the spatiotemporal characteristics of marine environmental elements were mainly used to identify and analyze ENSO events. For example, the monthly average sea surface temperature anomaly values ​​in the El Nino1-4 region were used to determine whether the El Nino event / La Nina event occurred, and the region where the anomaly values ​​occurred first (El Nino1-4 region) was used to further identify the type of ENSO event: EP type or CP type. With the in-depth study of ENSO events, it was found that it is difficult to accurately identify the type of ENSO event and the mechanism of ENSO using the information of abnormal ocean changes in relatively fixed spatial areas. It is necessary to use the spatiotemporal dynamic information of abnormal ocean changes, such as: using the order of occurrence of abnormal sea surface temperature changes in the El Nino region to redefine the ENSO event index; using the spatial movement characteristics of abnormal sea surface temperature changes to identify the type of ENSO event, etc.

[0090] At present, based on satellite remote sensing data and geographic big data mining technology, a large amount of ocean abnormal change information on a global scale has been obtained, and the use of the spatiotemporal dynamic information of ocean abnormal changes to carry out ENSO event research also has great application potential. However, there are differences between ocean abnormal changes and ENSO events in terms of spatiotemporal dimensions and the scale of occurrence time, which brings challenges to the study of the correlation pattern between the two.

[0091] Abnormal ocean changes have three-dimensional characteristics in space and time (space, time, attributes): spatial structure and attribute characteristics that change over time; ENSO events are two-dimensional change characteristics (attributes, time): ENSO intensity that changes over time. Although ENSO events do not have spatial information, the spatial structure of abnormal ocean changes and their evolution characteristics are crucial to ENSO events. At the same time, on a time scale, ENSO events and abnormal ocean changes have different life cycles (duration ranges), and their occurrence times are not synchronized. Therefore, the correlation expression between abnormal ocean changes and ENSO events needs to solve the following two problems: 1) In the time dimension, how to establish the correlation expression between ENSO events and abnormal ocean changes to solve the problem of asynchrony between the two in time; 2) How to establish the correlation expression between ENSO event types and the dynamic evolution of abnormal ocean changes to characterize the spatiotemporal evolution structure of abnormal ocean changes under different ENSO event types.

[0092] In the prior art, abnormal changes in marine environmental elements refer to changes in marine environmental elements relative to the average state of a long-term series, such as abnormal monthly average changes in sea surface temperature, abnormal seasonal average changes in sea surface salinity, etc., referred to as abnormal marine changes. Abnormal marine changes have regional clustering characteristics in space and evolutionary characteristics of generation, development and extinction in time. ENSO is a typical signal of global climate change, and also has evolutionary characteristics of generation, development and extinction. The occurrence and development of ENSO events affect the spatial distribution and temporal evolution of abnormal marine changes. Conversely, the spatiotemporal distribution and evolutionary characteristics of abnormal marine changes can also characterize the type and intensity of ENSO events. Due to the lack of support for the expression method of spatiotemporal dynamic correlation, the current relationship research between the two is mainly based on qualitative analysis, and it is difficult to finely characterize the relationship between the evolutionary structure of abnormal marine changes and the type and intensity of ENSO events. Based on the above problems, the present invention provides a method for expressing the association between ocean dynamic evolution and ENSO events. The execution process of the method is as follows: Figure 1 As shown, the steps include:

[0093] S101. Based on object-oriented technology, an object expression of an abnormal ocean change process object is established, including: process object ID, process object attribute information, process object space information and process object time information;

[0094] In the embodiment of the present invention, object-oriented technology is used to abstract the complete life cycle process (Formula (1)) of the generation, development and extinction of the spatial structure and attribute characteristics of the abnormal changes in the ocean into a spatiotemporal object, which is called the abnormal change process object of the ocean. The abnormal change process object of the ocean includes the spatial object of the data observation scale and the evolution relationship of the spatial object before and after the data observation scale.

[0095] In the data observation scale of the previous and next moments, there are four evolutionary relationships between ocean space objects: development, merger, split, and split-merge, which are called ocean object evolutionary relationships. The schematic diagram of the four evolutionary relationships is as follows Figure 2 shown.

[0096] Further, the process object attribute information A1 of the abnormal ocean change process object is obtained, wherein A1={Name1, Type1, Value1}, Name1 represents the name of the abnormal ocean change process object, Type1 represents the type of the abnormal ocean change process object, and Value1 represents the attribute value of the abnormal ocean change process object;

[0097] For the attribute information A1, the name Name1 is automatically named according to the marine environment element + serial number. For example, the process object name based on the sea surface temperature is SST process object 1, SST process object 2, and so on. The type Type1 is represented by the numbers 0 and 1. 0 represents the process object whose attribute value is higher than the average value, and 1 represents the process object whose attribute value is lower than the average value. The attribute value Value1 is obtained by calculating the average attribute values ​​of all state objects belonging to the process object.

[0098] Obtain the process object spatial information S of the abnormal ocean change process object, where S = {Structure, OriginalPlace, EvolvingPlace, ExtinctionPlace}

[0099] S = Structure, OriginalPlace, EvolvingPlace, ExtinctionPlace)}, Structure represents the spatial evolution structure of the abnormal ocean change process object, OriginalPlace represents the source of the abnormal ocean change process object, EvolvingPlace represents the evolution area of ​​the abnormal ocean change process object, and ExtinctionPlace represents the extinction place of the abnormal ocean change process object;

[0100] With respect to the process object spatial information S, the source / evolution area / extinction area is obtained from the ocean abnormal change process object. Specifically: 1) Obtain the centroid position (OriginalCentroids) of the ocean space object corresponding to the start time of the ocean abnormal change process object / the centroid position (EvolvingCentroids) of the ocean space object corresponding to the moment when the ocean abnormal change process object undergoes evolutionary behavior (merger, split, split and merge) / the centroid position (ExtinctionCenroids) of the ocean space object corresponding to the moment when the ocean abnormal change process object disappears; 2) Use the kernel density analysis function to perform kernel density analysis on the centroid positions (OriginalCentroids / EvolvingCentroids / ExtinctionCenroids) to obtain a kernel density spatial distribution map;

[0101] In the embodiment of the present invention, the kernel density analysis function is a spatial analysis function, and its principle is that the kernel density value at the centroid position is the largest, and as the distance from the centroid position increases, the spatial kernel density value gradually decreases. The final spatial kernel density value is the sum of the kernel density values ​​of all centroid positions in the spatial position, and the corresponding kernel density spatial distribution map is the kernel density spatial distribution map of the centroid position.

[0102] The calculation function of spatial kernel density analysis is: KernelDensity(input_PointFeatures,inputsearch_radius,output Raster,output cellsize).

[0103] In the embodiment of the present invention, for the kernel density spatial distribution map, there are a source kernel density spatial distribution map, an evolution region kernel density spatial distribution map and a disappearance site spatial distribution kernel density distribution map.

[0104] Furthermore, high kernel density areas are obtained in the corresponding kernel density distribution map, which are defined as the source, evolution area and extinction area of ​​the abnormal change process object in the ocean. The specific definition process is as follows: Usually, a threshold is set based on empirical analysis to obtain high-density areas from the kernel density distribution map, thereby obtaining the source, evolution area and extinction area of ​​the abnormal change process. The high-density area is an area with a large kernel density value in the kernel density spatial distribution map. Preferably, the threshold is set to 0.07.

[0105] Finally, the spatiotemporal evolution structure is obtained from the abnormal ocean change process object. Specifically: 1) According to the development, merger, split, split-merger relationship and the number of occurrences of the abnormal ocean change process object, five types of evolution structure are defined. The evolution structure is expressed by the spatial position of the process object at the time of generation, the spatial position of the evolution relationship, and the spatial position of the extinction time. The schematic diagram of the evolution structure type is shown in the figure below: Figure 3 As shown; 2) according to the evolution relationship type and number of abnormal ocean changes, establish the preset evolution structure discrimination principle of the abnormal ocean change process object; 3) according to the preset evolution structure discrimination rule, obtain the spatial evolution structure of the abnormal ocean change process object.

[0106] The preset evolution structure discrimination rule is as follows:

[0107] If the ocean abnormal change process object only has a development relationship, the spatial evolution structure is evolution structure 1; or,

[0108] If the ocean abnormal change process object only has a development relationship and a merger relationship, the spatial evolution structure is an evolution structure 2; or,

[0109] If the object of the abnormal ocean change process only has a development relationship and a split relationship, the spatial evolution structure is an evolution structure 3; or,

[0110] If the ocean abnormal change process object has a development relationship, two merge relationships and two split relationships, the spatial evolution structure is evolution structure 4; or,

[0111] If the ocean abnormal change process object simultaneously has a development relationship, more than two merging relationships, and more than two splitting relationships, then the spatial evolution structure is evolution structure 5.

[0112] Obtaining the process object time information T1 of the abnormal ocean change process object, wherein T1={Duration1, StartTime1, EndTime1, TimeScale1}, Duration1 represents the duration of the abnormal ocean change process object, StartTime1 represents the start time of the abnormal ocean change process object, EndTime1 represents the end time of the abnormal ocean change process object, and TimeScale1 represents the data observation scale of the abnormal ocean change process object;

[0113] Based on the process object attribute information A1, the process object spatial information S and the process object time information T1, a preset ocean abnormal change process object expression is constructed to establish the ocean abnormal change process object expression, wherein the ocean abnormal change process object expression is:

[0114] Process object={POID,A1,S,T1}(3)

[0115] Wherein, Process ibject represents the expression of the abnormal ocean change process object, and POID represents the process object ID, which is used to identify the abnormal ocean change process object.

[0116] S102. Based on object-oriented technology, establish an ENSO object expression of the ENSO event, including event object ID, event attribute information and event time information;

[0117] In the embodiment of the present invention, the event attribute information A2 of the ENSO event is obtained, wherein A2={Name2, Type2, Intensity2}, Name2 represents the name of the ENSO event, Type2 represents the type of the ENSO event, and Intensity2 represents the intensity of the ENSO event.

[0118] For the event attribute information A2, the name Name2 can be set based on experience or specific circumstances, and is not specifically limited in the embodiment of the present invention. For the type Type2 and the intensity Intensity2, relevant experience values ​​are obtained by integrating existing literature.

[0119] The event time information T2 of the ENSO event is obtained, where:

[0120] T2={Duration2, StartTime2, EndTime2, TimeScale2}, Duration2 represents the duration of the ENSO event, StartTime2 represents the start time of the ENSO event, EndTime2 represents the end time of the ENSO event, and TimeScale2 represents the observation scale of the ENSO event.

[0121] For the event time information T2, according to the ENSO event definition, the first month corresponding to the ENSO event is the start time StartTime2 of the ENSO event, and the last month is the end time EndTime2. The difference between the two is the duration Duration2, and the ENSO event scale TimeScale2: month.

[0122] A preset ENSO event object expression is constructed based on the event attribute information A2 and the event time information T2, and the ENSO event object expression is established, wherein the preset ENSO object expression is:

[0123] ENSO={EID,A2,T2} (4)

[0124] Among them, ENSO is the ENSO object expression of the ENSO event, and EID is the event object ID, which is used to uniquely identify the ENSO event.

[0125] S103, determining a target temporal topological relationship between the ocean abnormal change process object and the ENSO object based on a preset temporal topological relationship discrimination rule;

[0126] In the embodiment of the present invention, Allen's 13 temporal relationships are used (include / are included by: During and its inverse; start / are started by: Starts and its inverse; end / are ended by: Finsishes and its inverse; before / after: before and its inverse; overlap / are overlapped by: overlap and its inverse; meet / are connected to: Meets and its inverse; Equal: the same) to calculate the temporal topological relationship between the abnormal ocean change process object and the ENSO object, and establish an associated expression between the two. The specific steps are: 1) According to Allen's temporal relationship, 7 temporal topological relationships between the abnormal ocean change process object and the ENSO object are defined, which are: co-occurrence, successive occurrence, common end, inclusion, overlap, and successive occurrence (T). The schematic diagram of the temporal topological relationship is shown in the figure. Figure 4 shown.

[0127] Design the temporal topological relationship discrimination rules for the ocean abnormal change process object and the ENSO object, obtain the start time and end time of the ocean abnormal change process object and the ENSO object, and calculate the temporal topological relationship between the two. The start time and end time of the ocean abnormal change process object are recorded as: Post and Poet; the start time and end time of the ENSO object are recorded as: Eost and Eoet. The preset temporal topological relationship discrimination rules are as follows:

[0128] If the ocean abnormal change process object and the ENSO object have the same start time and different end time, that is, (Po st =Eo st )∩(Po et ≠Eo et ), then the target temporal topological relationship between the two is co-occurrence, where Po st Indicates the start time of the abnormal ocean change process object, Po et Indicates the end time of the abnormal ocean change process object, Eo st Indicates the start time of the ENSO object, Eo etIndicates the end time of the ENSO object; or

[0129] If the ENSO object occurs when the ocean abnormal change process object ends, or the ocean abnormal change process object occurs when the ENSO object occurs, that is, (Po st =Eo et )∪(Po et =Eo st ), then the target temporal topological relationship between the two is successive occurrence; or,

[0130] If the ocean abnormal change process object and the ENSO object have the same start time and the same end time, that is, (Po st =Eo st )∩(Po et =Eo et ), then the target temporal topological relationship between the two is the same occurrence; or,

[0131] If the ocean abnormal change process object and the ENSO object have the same end time and different start time, that is, (Po st ≠Eo st )∩(Po et =Eo et ), then the target temporal topological relationship between the two ends together; or,

[0132] If the start time of the abnormal ocean change process object is later than the start time of the ENSO object, and the end time of the abnormal ocean change process object is earlier than the end time of the ENSO object, or the start time of the abnormal ocean change process object is earlier than the start time of the ENSO object, and the end time of the abnormal ocean change process object is later than the end time of the ENSO object, that is, ((Po st <Eo st )∩(Po st >Eo et ))∪((Po et <Eo st )∩(Po et >Eo et )), then the target temporal topological relationship between the two is a containment relationship; or,

[0133] If the start time of the abnormal ocean change process object is later than the start time of the ENSO object and earlier than the end time of the ENSO object, or the end time of the abnormal ocean change process object is earlier than the start time of the ENSO object and later than the end time of the ENSO object, that is, ((Po st <Eo st )∩(Po st>Eo et ))∪((Po et <Eo st )∩(Po et >Eo et )), then the target temporal topological relationship between the two is an overlapping relationship; or,

[0134] If the ENSO object occurs T unit time after the end of the abnormal ocean change process object, or the abnormal ocean change process object occurs T unit time after the end of the ENSO object, that is, (Po st ≤Eo et +T)∪(Po et ≥Eo et +T), then the target temporal topological relationship between the two is occurrence-after-occurrence (T).

[0135] S104. Establishing an associated expression between the ocean abnormal change process object and the ENSO object based on the target temporal topological relationship.

[0136] In the embodiment of the present invention, the target temporal topological relationship between the abnormal ocean change process object and the ENSO object is used to establish an associated expression between the two. The expression schematic diagram is as follows: Figure 5 The ocean abnormal change process object table includes:

[0137] POID: string; Process Type: String; Attribute Value: double; StartTime: Date; EndtTime: Date; Duration: double; TimeScale: double; EvolvingStructure: Int; OrginalPlace: shp; EvolvingPlace: shp; ExtinctionPlace: shp.

[0138] The ENSO object table includes:

[0139] EID: String; ENSOType: int; Intensity Value: double; StartTime: Date, EndtTime: Date; Duration: double; TimeScale: double.

[0140] The association table between the ocean abnormal change process object and the ENSO object includes:

[0141] RelationshipID: String; POID: String; EID: string; Relationship: String.

[0142] The association table of the abnormal ocean change process object and the ENSO object mainly stores the topological relationship between the two. The process object ID is responsible for linking the abnormal ocean change process object table, and the ENSO object ID is responsible for linking the ENSO object table.

[0143] The present invention discloses a method for expressing the association between ocean dynamic evolution and ENSO events. Based on object-oriented technology, an object expression of an abnormal ocean change process object is established, including a process object ID, process object attribute information, process object spatial information and process object time information; based on object-oriented technology, an ENSO object expression of an ENSO event is established, including an event object ID, event attribute information and event time information; a target temporal topological relationship between an abnormal ocean change process object and an ENSO object is established based on a preset temporal topological relationship discrimination rule; and an associated expression between an abnormal ocean change process object and an ENSO object is established based on the target temporal topological relationship. In the above process, an associated expression between an abnormal ocean change process object and an ENSO object is established based on the target temporal topological relationship, thereby realizing the association between an abnormal ocean change process object and an ENSO object.

[0144] In the embodiment of the present invention, the evolution scale of abnormal ocean changes is taken as the basic unit, a topological relationship discrimination rule between the abnormal ocean change process object and the ENSO object is designed, and a spatiotemporal correlation expression method oriented to the evolution process is established to realize the correlation expression of the dynamic evolution (evolution structure, source, extinction place, evolution area) of the abnormal ocean change process object and the ENSO event.

[0145] Furthermore, in the embodiment of the present invention, the temporal topological relationship between the ocean abnormal change process object and the ENSO object is established with the evolution process as the analysis scale. This technology ensures that the temporal topological relationship contains the dynamic evolution information of the ocean abnormal change process object; the spatiotemporal correlation expression method with the temporal topological relationship as the link depicts the coupling correlation mode between the ENSO event and the dynamic evolution of the ocean abnormal change, and provides technical support for the identification and prediction of ENSO events and the analysis of the ocean spatiotemporal dynamic mechanism. It has broad application prospects in global climate change research and analysis of the dynamic mechanism of the marine environment.

[0146] Based on the above-mentioned method for expressing the association between ocean dynamic evolution and ENSO events, an embodiment of the present invention further provides an apparatus for expressing the association between ocean dynamic evolution and ENSO events. The structural block diagram of the apparatus is as follows: Figure 6 As shown, including:

[0147] A first establishing module 201 , a second establishing module 202 , a determining module 203 and a third establishing module 204 .

[0148] in,

[0149] The first establishing module 201 is used to establish an object expression of an abnormal ocean change process object based on object-oriented technology, including: process object ID, process object attribute information, process object space information and process object time information;

[0150] The second establishing module 202 is used to establish an ENSO object expression of the ENSO event based on object-oriented technology, including event object ID, event attribute information and event time information;

[0151] The determination module 203 is used to determine the target temporal topological relationship between the ocean abnormal change process object and the ENSO object based on a preset temporal topological relationship discrimination rule;

[0152] The third establishing module 204 is used to establish an associated expression between the ocean abnormal change process object and the ENSO object based on the target temporal topological relationship.

[0153] The present invention discloses a device for expressing the association between ocean dynamic evolution and ENSO events. Based on object-oriented technology, an object expression of an abnormal ocean change process object is established, including a process object ID, process object attribute information, process object spatial information and process object time information; based on object-oriented technology, an ENSO object expression of an ENSO event is established, including an event object ID, event attribute information and event time information; a target temporal topological relationship between an abnormal ocean change process object and an ENSO object is established based on a preset temporal topological relationship discrimination rule; and an associated expression between an abnormal ocean change process object and an ENSO object is established based on the target temporal topological relationship. In the above process, an associated expression between an abnormal ocean change process object and an ENSO object is established based on the target temporal topological relationship, thereby realizing the association between an abnormal ocean change process object and an ENSO object.

[0154] In the embodiment of the present invention, the first establishing module 201 includes:

[0155] A first acquiring unit 205 , a second acquiring unit 206 , a third acquiring unit 207 and a first establishing unit 208 .

[0156] in,

[0157] The first acquisition unit 205 is used to acquire process object attribute information A1 of the abnormal ocean change process object, wherein A1={Name1, Type1, Value1}, Name1 represents the name of the abnormal ocean change process object, Type1 represents the type of the abnormal ocean change process object, and Value1 represents the attribute value of the abnormal ocean change process object;

[0158] The second acquisition unit 206 is used to acquire the process object spatial information S of the abnormal ocean change process object, wherein:

[0159] S={Structure, OriginalPlace, EvolvingPlace, ExtinctionPlace}

[0160] S = {Structure, OriginalPlace, EvolvingPlace, ExtinctionPlace)}, Structure represents the spatial evolution structure of the abnormal ocean change process object, OriginalPlace represents the source of the abnormal ocean change process object, EvolvingPlace represents the evolution area of ​​the abnormal ocean change process object, and ExtinctionPlace represents the extinction place of the abnormal ocean change process object;

[0161] The third acquisition unit 207 is used to acquire the process object time information T1 of the ocean abnormal change process object, wherein T1={Duration1, StartTime1, EndTime1, TimeScale1}, Duration1 represents the duration of the ocean abnormal change process object, StartTime1 represents the start time of the ocean abnormal change process object, EndTime1 represents the end time of the ocean abnormal change process object, and TimeScale1 represents the data observation scale of the ocean abnormal change process object; the first establishment unit 208 is used to construct a preset ocean abnormal change process object expression based on the attribute information A1, the spatial information S and the time information T1, and establish the ocean abnormal change process object expression, wherein the ocean abnormal change process object expression is:

[0162] Process object = {POID, A1, S, T1}, wherein Process object represents the expression of the abnormal ocean change process object, and POID represents the process object ID, which is used to identify the abnormal ocean change process object.

[0163] In the embodiment of the present invention, the second establishing module 202 includes:

[0164] A fourth acquiring unit 209 , a fifth acquiring unit 210 and a second establishing unit 211 .

[0165] in,

[0166] The fourth acquisition unit 209 is used to acquire event attribute information A2 of the ENSO event, wherein A2={Name2, Type2, Intensity2}, Name2 represents the name of the ENSO event, Type2 represents the type of the ENSO event, and Intensity2 represents the intensity of the ENSO event;

[0167] The fifth acquisition unit 210 is used to acquire the event time information T2 of the ENSO event, wherein T2={Duration2, StartTime2, EndTime2, TimeScale2}, Duration2 represents the duration of the ENSO event, StartTime2 represents the start time of the ENSO time, EndTime2 represents the end time of the ENSO event, and TimeScale2 represents the observation scale of the ENSO event;

[0168] The second establishing unit 211 is used to construct a preset ENSO object expression based on the attribute information A2 and the time information T2 to establish the ENSO object expression, wherein the preset ENSO object expression is:

[0169] ENSO = {EID, A2, T2}

[0170] Among them, ENSO is the ENSO object expression of the ENSO event, and EID is the event object ID, which is used to uniquely identify the ENSO event.

[0171] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that include computer-usable program code.

[0172] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0173] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0174] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process in the computer or other programmable device. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0175] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0176] The memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0177] Computer readable media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. Information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include temporary computer readable media (transitory media), such as modulated data signals and carrier waves.

[0178] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0179] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code.

Claims

1. A method for expressing the association between ocean dynamic evolution and ENSO events, characterized in that: include: Based on object-oriented technology, the object expression of the ocean abnormal change process object is established, including: process object ID, process object attribute information, process object spatial information and process object time information; Based on object-oriented technology, the ENSO object expression of ENSO events is established, including: event object ID, event attribute information and event time information; Determine the target temporal topological relationship between the ocean abnormal change process object and the ENSO object based on a preset temporal topological relationship discrimination rule; Establishing an associated expression between the ocean abnormal change process object and the ENSO object based on the target temporal topological relationship; Based on object-oriented technology, the object expression of the abnormal ocean change process object is established, including: Obtaining process object attribute information A1 of the abnormal ocean change process object, wherein A1={Name1, Type1, Value1}, Name1 represents the name of the abnormal ocean change process object, Type1 represents the type of the abnormal ocean change process object, and Value1 represents the attribute value of the abnormal ocean change process object; Obtain the process object spatial information S of the abnormal ocean change process object, wherein: S={Structure, OriginalPlace, EvolvingPlace, ExtinctionPlace}, Structure Represents the spatial evolution structure of the abnormal ocean change process object, OriginalPlace represents the source of the abnormal ocean change process object, EvolvingPlace represents the evolution area of ​​the abnormal ocean change process object, and ExtinctionPlace represents the extinction place of the abnormal ocean change process object; Obtaining the process object time information T1 of the abnormal ocean change process object, wherein T1={Duration1, StartTime1, EndTime1, TimeScale1}, Duration1 represents the duration of the abnormal ocean change process object, StartTime1 represents the start time of the abnormal ocean change process object, EndTime1 represents the end time of the abnormal ocean change process object, and TimeScale1 represents the data observation scale of the abnormal ocean change process object; A preset ocean abnormal change process object expression is constructed based on the attribute information A1, the spatial information S and the time information T1, and the ocean abnormal change process object expression is established, wherein the ocean abnormal change process object expression is: Process object={POID,A1,S,T1} Wherein, Process object represents the expression of the abnormal ocean change process object, and POID represents the process object ID, which is used to identify the abnormal ocean change process object; Based on object-oriented technology, the ENSO object expression of ENSO events is established, including: Acquire event attribute information A2 of the ENSO event, wherein A2={Name2, Type2, Intensity2}, Name2 represents the name of the ENSO event, Type2 represents the type of the ENSO event, and Intensity2 represents the intensity of the ENSO event; Obtaining the event time information T2 of the ENSO event, wherein T2={Duration2, StartTime2, EndTime2, TimeScale2}, Duration2 represents the duration of the ENSO event, StartTime2 represents the start time of the ENSO time, EndTime2 represents the end time of the ENSO event, and TimeScale2 represents the observation scale of the ENSO event; A preset ENSO object expression is constructed based on the event attribute information A2 and the event time information T2 to establish the ENSO object expression, wherein the preset ENSO object expression is: ENSO = {EID, A2, T2} Wherein, ENSO is the ENSO object expression of the ENSO event, and EID is the event object ID, which is used to uniquely identify the ENSO event; Determining the target temporal topological relationship between the ocean abnormal change process object and the ENSO object based on a preset temporal topological relationship discrimination rule includes: If the ocean abnormal change process object and the ENSO object have the same start time and different end time, that is, (Po st =Eo st )∩(Po et ≠Eo et ), then the target temporal topological relationship between the two is co-occurrence, where Po st Indicates the start time of the abnormal ocean change process object, Po et Indicates the end time of the abnormal ocean change process object, Eo st Indicates the start time of the ENSO object, Eo et Indicates the end time of the ENSO object; or If the ENSO object occurs when the ocean abnormal change process object ends, or if the ocean abnormal change process object occurs when the ENSO object ends, that is, (Po st =Eo et )∪(Po et =Eo st ), then the target temporal topological relationship between the two is successive occurrence; or, If the ocean abnormal change process object and the ENSO object have the same start time and the same end time, that is, (Po st =Eo st )∩(Po et =Eo et ), then the target temporal topological relationship between the two is the same occurrence; or, If the ocean abnormal change process object and the ENSO object have the same end time and different start time, that is, (Po st ≠Eo st )∩(Po et =Eo et ), then the target temporal topological relationship between the two ends together; or, If the start time of the abnormal ocean change process object is later than the start time of the ENSO object, and the end time of the abnormal ocean change process object is earlier than the end time of the ENSO object, or the start time of the abnormal ocean change process object is earlier than the start time of the ENSO object, and the end time of the abnormal ocean change process object is later than the end time of the ENSO object, that is, ((Po st <Eo st )∩(Po et >Eo et ))∪((Po st >Eo st )∩(Po et <Eo et )), then the target temporal topological relationship between the two is a containment relationship; or, If the start time of the abnormal ocean change process object is later than the start time of the ENSO object and earlier than the end time of the ENSO object, or the end time of the abnormal ocean change process object is earlier than the start time of the ENSO object and later than the end time of the ENSO object, that is, ((Po st <Eo st )∩(Po st >Eo et ))∪((Po et <Eo st )∩(Po et >Eo et )), then the target temporal topological relationship between the two is an overlapping relationship; or, If the ENSO object occurs T unit time after the end of the abnormal ocean change process object, or the abnormal ocean change process object occurs T unit time after the end of the ENSO object, that is, (Po st ≤Eo et +T)∪(Po et ≥Eo et +T), then the target temporal topological relationship between the two is occurrence (T); Establishing the associated expression of the abnormal ocean change process object and the ENSO object based on the target temporal topological relationship includes: Establishing an association table between the abnormal ocean change process object and the ENSO object based on the target temporal topological relationship, wherein the association table includes: the abnormal ocean change process object ID, the ENSO object ID, the target temporal topological relationship and the target temporal topological relationship ID; The abnormal ocean change process object is linked based on the abnormal ocean change process object ID, and the ENSO object is linked based on the ENSO object ID.

2. The method according to claim 1, characterized in that Acquiring the spatial information S of the abnormal ocean change process object includes: Acquire the centroid position of the abnormal ocean change process object, perform kernel density analysis on the centroid position based on a kernel density analysis function, and obtain a kernel density spatial distribution map; Determine the source, evolution area and disappearance area of ​​the abnormal ocean change process object based on the kernel density spatial distribution map; Based on the preset evolution structure discrimination rules, the spatial evolution structure of the ocean abnormal change process object is determined.

3. The method according to claim 2, characterized in that Based on a preset evolution structure discrimination rule, determining the spatial evolution structure of the abnormal ocean change process object includes: If the ocean abnormal change process object only has a development relationship, the spatial evolution structure is evolution structure 1; or, If the ocean abnormal change process object only has a development relationship and a merger relationship, the spatial evolution structure is an evolution structure 2; or, If the object of the abnormal ocean change process only has a development relationship and a split relationship, the spatial evolution structure is an evolution structure 3; or, If the ocean abnormal change process object has a development relationship, two merge relationships and two split relationships, the spatial evolution structure is evolution structure 4; or, If the ocean abnormal change process object simultaneously has a development relationship, more than two merging relationships, and more than two splitting relationships, then the spatial evolution structure is evolution structure 5.

4. A device for expressing the association between ocean dynamic evolution and ENSO events, characterized in that: The method for expressing the association between ocean dynamic evolution and ENSO events as claimed in claim 1 comprises: The first establishment module is used to establish the object expression of the ocean abnormal change process object based on object-oriented technology, including: process object ID, process object attribute information, process object space information and process object time information; The second building module is used to build the ENSO object expression of the ENSO event based on the object-oriented technology, including: event object ID, event attribute information and event time information; A determination module, used to determine the target temporal topological relationship between the ocean abnormal change process object and the ENSO object based on a preset temporal topological relationship discrimination rule; A third establishing module is used to establish an associated expression between the ocean abnormal change process object and the ENSO object based on the target temporal topological relationship; The first establishment module includes: A first acquisition unit is used to acquire process object attribute information A1 of the abnormal ocean change process object, wherein A1={Name1, Type1, Value1}, Name1 represents the name of the abnormal ocean change process object, Type1 represents the type of the abnormal ocean change process object, and Value1 represents the attribute value of the abnormal ocean change process object; A second acquisition unit is used to acquire the process object spatial information S of the abnormal ocean change process object, wherein S={Structure, OriginalPlace, EvolvingPlace, ExtinctionPlace}, Structure represents the spatial evolution structure of the abnormal ocean change process object, OriginalPlace represents the source of the abnormal ocean change process object, EvolvingPlace represents the evolution area of ​​the abnormal ocean change process object, and ExtinctionPlace represents the extinction place of the abnormal ocean change process object; The third acquisition unit is used to acquire the process object time information T1 of the abnormal ocean change process object, wherein T1={Duration1, StartTime1, EndTime1, TimeScale1}, Duration1 represents the duration of the abnormal ocean change process object, StartTime1 represents the start time of the abnormal ocean change process object, EndTime1 represents the end time of the abnormal ocean change process object, and TimeScale1 represents the data observation scale of the abnormal ocean change process object; The first establishing unit is used to construct a preset ocean abnormal change process object expression based on the attribute information A1, the spatial information S and the time information T1, and establish the ocean abnormal change process object expression, wherein the ocean abnormal change process object expression is: Process object={POID,A1,S,T1} Wherein, Process object represents the expression of the abnormal ocean change process object, and POID represents the process object ID, which is used to identify the abnormal ocean change process object; The second establishment module includes: A fourth acquisition unit is used to acquire event attribute information A2 of the ENSO event, wherein A2={Name2, Type2, Intensity2}, Name2 represents the name of the ENSO event, Type2 represents the type of the ENSO event, and Intensity2 represents the intensity of the ENSO event; A fifth acquisition unit is used to acquire event time information T2 of the ENSO event, wherein T2={Duration2, StartTime2, EndTime2, TimeScale2}, Duration2 represents the duration of the ENSO event, StartTime2 represents the start time of the ENSO time, EndTime2 represents the end time of the ENSO event, and TimeScale2 represents the observation scale of the ENSO event; The second establishing unit is used to construct a preset ENSO object expression based on the attribute information A2 and the time information T2, and establish the ENSO object expression, wherein the preset ENSO object expression is: ENSO = {EID, A2, T2} Among them, ENSO is the ENSO object expression of the ENSO event, and EID is the event object ID, which is used to uniquely identify the ENSO event.

Images