Dynamic trajectory analysis framework construction method based on deviation degree-frequency-trend

Abstract

The invention discloses a dynamic trajectory analysis framework construction method based on deviation degree-frequency-trend, and belongs to the technical field of geographic element change trajectory identification, and the method comprises the following steps: calculating an interannual change rate, comparing the change condition of each region relative to the previous period, and calculating a deviation degree-frequency-trend-based dynamic trajectory analysis framework based on the interannual change rate; dividing the change trend of the geographic elements or phenomena into different grades; a directed edge change map is constructed based on calculation of the interannual change rate, and evolution paths of geographic elements or phenomena along with time are obtained based on a directed edge change map extraction method; and in combination with the deviation degree, the frequency and the trend index, geographic elements or phenomenon change tracks are identified and classified. The DFT frame effectively avoids the deviation caused by the regional scale difference in absolute value analysis by calculating the inter-annual change rate, namely the change amplitude in unit time, and ensures the fairness and scientificity of cross-regional dynamic comparison.

Description

Technical Field

[0001] The present invention relates to the technical field of identifying the change trajectories of geographical elements, and particularly to a method for constructing a dynamic trajectory analysis framework based on deviation-frequency-trend. Background Art

[0002] In recent years, the spatio-temporal dynamics research of geographical elements or phenomena has become a hot topic in the field of geographical science. A large number of studies have shown that the spatial distribution characteristics of geographical elements or phenomena (such as soil erosion intensity, land use / land cover change, urban heat island response, etc.) are not static, but show dynamic characteristics over time. This understanding has become a general consensus in the academic community, that is, the spatio-temporal dynamics of geographical elements or phenomena have a high degree of temporal and spatial dependence. However, this complex spatio-temporal dependence also poses new challenges to research methods and perspectives, requiring researchers to avoid splitting the connection between time and space when analyzing spatio-temporal changes.

[0003] With the continuous in-depth study of spatio-temporal dynamics, the existing research focuses generally on exploring the driving mechanisms behind geographical phenomena, while relatively less attention is paid to the exploration of spatio-temporal dynamics itself. More importantly, many studies tend to separate the quantity change trend from the spatial distribution change when analyzing spatio-temporal changes, which is contrary to the existing research consensus on the "indivisibility" of spatio-temporal dynamics. The limitations of this research paradigm may not only lead to a one-sided understanding of spatio-temporal change characteristics, but also limit the comprehensive understanding of the essence of geographical phenomena. Summary of the Invention

[0004] The purpose of the present invention is to provide a method for constructing a dynamic trajectory analysis framework based on deviation-frequency-trend (DFT) to address the problem that the existing technology in analyzing spatio-temporal changes tends to separate the quantity change trend from the spatial distribution change, which covers the calculation of the change rate, the construction of the trajectory path, and multi-dimensional classification analysis. The DFT framework effectively avoids the deviation caused by regional scale differences in the absolute value analysis by calculating the change rate between years, that is, the amplitude of change per unit time, ensuring the fairness and scientificity of cross-regional dynamic comparison. Through the integration of deviation, frequency, and trend, the dynamic changes of geographical elements or phenomena are characterized multi-dimensionally.

[0005] The technical solution of the present invention is as follows:

[0006] A method for constructing a dynamic trajectory analysis framework based on deviation-frequency-trend includes the following steps:

[0007] Calculate the inter-annual change rate to compare the change of each region relative to its previous period, and based on the inter-annual change rate, divide the change trend of geographical elements or phenomena into different levels;

[0008] Construct a directed edge change atlas based on the calculation of the annual change rate, and obtain the evolution path of geographical elements or phenomena over time based on the extraction method of the directed edge change atlas;

[0009] Combine the deviation, frequency and trend indicators to identify and classify the change trajectories of geographical elements or phenomena.

[0010] Furthermore, the deviation indicator records the degree of deviation of the change trajectory of geographical elements or phenomena during the research time series compared with the stable state, and measures the difference between the ecological state of each time phase and the stable state; the calculation formula of the deviation indicator is:

[0011]

[0012] where y i is the rank code of the change of geographical elements or phenomena in the i-th research time phase, and n is the number of research time phases; if the deviation D = 0, it means that the trajectory is in a stable state; if D ≥ 8, it indicates that the ecological process of this area deviates more from the stable state; if 0 < D < 8, it indicates that the ecological process is more stable.

[0013] Furthermore, the frequency indicator records the number of changes in the change trend of geographical elements or phenomena between adjacent years; the calculation formula of the frequency indicator is:

[0014]

[0015] where y i is the rank code of the change of geographical elements or phenomena in the i-th research time phase, · is the number of research time phases, I is the indicator function, when y i and y i+1 are different, the value of I is 1; otherwise it is 0; whenever the change rank codes of adjacent years are different, the frequency F increases by 1; the higher the value of F, the more frequent the change.

[0016] Furthermore, the trend indicator captures and describes the directionality of the change of geographical elements or phenomena over time during the research time series, that is, whether the change is increasing, decreasing or remaining stable; the calculation formula of the trend indicator is:

[0017]

[0018] where n is the number of research time phases, x i is the abscissa of the trajectory point, representing the extension of the time series; y i is the ordinate of the trajectory point, representing the rank code of the change of geographical elements or phenomena; if T = 0, it means that the ecological process is in a stable state without an obvious increasing or decreasing trend; T > 0 means that the geographical elements or phenomena show an increasing trend, and vice versa.

[0019] Furthermore, the inter-annual change rate reveals the change trend within each region. The calculation formula for the annual change rate is as follows:

[0020]

[0021] Where: V is the change rate of the geographical element or phenomenon between the t-th year and the (t - 1)-th year, and Ef t is the amount of the geographical element or phenomenon in the t-th year; Ef t-1 is the amount of the geographical element or phenomenon in the (t - 1)-th year.

[0022] Furthermore, the steps for classifying the change trend of geographical elements or phenomena into different levels are as follows:

[0023] According to the standard deviation SD of the change rate V in the time series, it is classified in sequence as: a large decrease V < -2SD%, a small decrease -2SD% ≤ V < -SD%, basically stable -SD% ≤ V < SD%, a small increase SD% ≤ V < 2SD%, a large increase V > 2SD%; the change categories are respectively coded as 1: large decrease, 2: small decrease, 3: basically stable, 4: small increase, and 5: large increase.

[0024] Furthermore, the method for extracting the change atlas based on directed edges includes the following steps:

[0025] Map the level coding of the change of geographical elements or phenomena onto a two-dimensional plane, where the ordinate represents different level codings of changes, and the abscissa represents the change stage within the time series from t - 1 to t;

[0026] Connect each vertex in chronological order; each directed edge points from the vertex of the level coding in the previous time phase to the vertex of the level coding in the later time phase;

[0027] Present the change trajectory of geographical elements in the form of a directed graph on the two-dimensional plane, visually showing the change process of this geographical element or phenomenon over time.

[0028] Furthermore, the deviation degree, frequency, and trend indicators are comprehensively analyzed in the time series through logical rules, and finally the change trajectory of geographical elements or phenomena is summarized into nine basic types.

[0029] Compared with the existing technologies, the beneficial effects of the present invention are:

[0030] 1. The DFT framework can not only effectively identify complex spatio-temporal evolution patterns, but also go beyond the limitations of simple spatio-temporal clustering and static proximity effect analysis in traditional methods, and can capture the detailed features of dynamic changes from multiple dimensions; the ability to comprehensively depict makes the DFT framework show high applicability and interpretability in the dynamic analysis of geographical elements or phenomena;

[0031] 2. The generalizability of the DFT framework makes it possible for it to be widely applied in various geographical research scenarios; based on the consensus that the spatio-temporal dynamics of geographical elements or phenomena have a high degree of temporal and spatial dependence, this framework can adapt to regional analyses at different scales (such as countries, provinces, cities) and characteristics (such as society, ecology, environment); as long as long-term sequence data of the target geographical element or phenomenon are obtained, the DFT framework can be used for systematic analysis; moreover, key parameters in the framework (such as time step, classification criteria, etc.) can be flexibly adjusted according to research needs and data characteristics to adapt to different research scenarios, thus ensuring the accuracy and effectiveness of the analysis results.

[0032] 3. The dynamic trajectory analysis framework based on deviation-frequency-trend, with its systematic, multi-dimensional and multi-scale characteristics, breaks through the limitations of traditional spatio-temporal dynamic research methods and provides new ideas for the analysis of the dynamic changes of complex geographical phenomena. Its innovation is reflected in the comprehensive description of spatio-temporal dynamics, the revelation of multi-scale effects and the structured modeling of the dynamic change process. In the future, with the further development of spatio-temporal big data technology, the DFT framework is expected to be popularized and applied in more fields, providing more powerful tool support for the spatio-temporal dynamic research of geographical phenomena. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] Figure 1 It is a flowchart of the method of this application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0034] It should be noted that relational terms such as "first" and "second" are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "comprise", "include" or any other variant thereof are intended to cover a non-exclusive inclusion, such that a process, method, article or device comprising a series of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article or device. Without further limitation, an element defined by the phrase "comprising a..." does not exclude the presence of additional identical elements in the process, method, article or device comprising the element.

[0035] The features and performance of the present invention will be further described in detail below in conjunction with embodiments.

[0036] Please refer to Figure 1 , a method for constructing a dynamic trajectory analysis framework based on deviation-frequency-trend, which is used to identify and quantify the change trajectory of geographical elements or phenomena over time. It includes the following steps:

[0037] To accurately evaluate the dynamic changes of geographical elements or phenomena in different regions during the research time series, calculate the annual change rate to compare the changes of each region relative to the previous period, rather than directly comparing the measurement values of geographical elements or phenomena, reveal the internal change trends of each region, and ensure that the understanding of the dynamic process of geographical elements or phenomena fully considers regional differences, so as to avoid ignoring the unique dynamics of geographical elements or phenomena in different regions.

[0038] The annual change rate reveals the internal change trends of each region. The calculation formula of the annual change rate is as follows:

[0039]

[0040] Where: V is the change rate of geographical elements or phenomena between the t-th year and the (t - 1)-th year, and Ef t is the amount of geographical elements or phenomena in the t-th year; Ef t-1 is the amount of geographical elements or phenomena in the (t - 1)-th year.

[0041] Based on the annual change rate, the change trends of geographical elements or phenomena are divided into different levels:

[0042] According to the standard deviation SD of the change rate V in the time series, they are successively divided into: a large decrease V < -2SD%, a small decrease -2SD% ≤ V < -SD%, basically stable -SD% ≤ V < SD%, a small increase SD% ≤ V < 2SD%, a large increase V > 2SD%; the change categories are respectively coded as 1: a large decrease, 2: a small decrease, 3: basically stable, 4: a small increase, and 5: a large increase.

[0043] Construct a directed edge change map based on the calculation of the annual change rate; to deeply analyze the dynamic change characteristics of geographical elements or phenomena, based on the extraction method of the directed edge change map, to clearly depict the evolution path of geographical elements or phenomena over time;

[0044] The extraction method of the directed edge change map includes the following steps:

[0045] Map the level codes of the changes of geographical elements or phenomena onto a two-dimensional plane, where the ordinate represents different level codes of changes, and the abscissa represents the change stages within the time series from t - 1 to t;

[0046] Geographical elements or phenomena are divided into five level codes (1 - 5), where 1 represents a large decrease and 5 represents a large increase. The change level of geographical elements or phenomena at each time node is regarded as a vertex.

[0047] Connect the vertices in chronological order; each directed edge points from the vertex of the level code in the previous time phase to the vertex of the level code in the later time phase;

[0048] The changing trajectory of geographical elements is presented on a two-dimensional plane through a directed graph, intuitively showing the changing process of the geographical elements or phenomena over time.

[0049] For example, assuming that the change level code of a geographical element or phenomenon (such as soil erosion intensity) in a certain area has been "3" during the study period (8 time phases from 1990 to 2022), that is, the change range is between -SD% and SD%, it means that the feature remains basically stable. At this time, its change trajectory can be regarded as a "steady state map". All vertices are coded as 3, and the directed edges between each time phase form a straight trajectory, indicating that the changes in the geographical elements or phenomena in this area tend to be stable. Through the construction of this directed edge change map, not only can the change patterns of geographical elements or phenomena in different regions (such as increase and decrease, stable state) be clarified, but also data support can be provided for subsequent trajectory classification and evolution trend analysis.

[0050] In order to further identify the dynamic phase characteristics of geographical elements or phenomena, the change trajectories of geographical elements or phenomena are identified and classified by combining deviation, frequency and trend indicators.

[0051] The deviation index records the deviation of the change trajectory of geographical elements or phenomena in the research time series from the stable state, measures the difference between the ecological state of each phase and the stable state, and evaluates the stability of the ecological process. The calculation formula of the deviation index is:

[0052]

[0053] Among them, y i is the level code of the change of geographical elements or phenomena in the i-th research phase, and n is the number of research phases; if the deviation D = 0, it means that the trajectory is in a stable state; if D ≥ 8, it means that the ecological process in the area deviates more from the stable state; if 0 <D<8,则表明生态过程越趋于平稳。

[0054] The frequency index records the number of changes in the trend of geographical elements or phenomena between adjacent years; this index reflects the frequency of changes in characteristic trends. The calculation formula for the frequency index is:

[0055]

[0056] Among them, y i is the level code of the change of geographical elements or phenomena in the i-th research phase, n is the number of research phases, I is the indicator function, and when y i and i+1 If they are not the same, the value of I is 1; otherwise it is 0; whenever the change level codes of adjacent years are different, the frequency F increases by 1; the higher the value of F, the more frequent the changes.

[0057] Trend indicators capture and describe the directionality of the changes in geographical elements or phenomena over time within the study time series, that is, whether the changes are increasing, decreasing, or remaining stable; they are used to identify long-term change patterns, and the slope of the best-fit line for the trajectory points of each trajectory is determined through a linear regression model. The calculation formula for the trend indicator is as follows:

[0058]

[0059] where n is the number of study time phases, and x i is the abscissa of the trajectory point, representing the extension of the time series; y i is the ordinate of the trajectory point, representing the rank coding of the changes in geographical elements or phenomena; if T = 0, it indicates that the ecological process is in a stable state without an obvious increasing or decreasing trend; if T > 0, it indicates that the geographical elements or phenomena show an increasing trend, and vice versa for a decreasing trend.

[0060] Through logical rules, the deviation degree, frequency, and trend indicators are comprehensively analyzed in the time series, and finally, the change trajectories of geographical elements or phenomena are summarized into nine basic types. As shown in Table 1:

[0061] Table 1 Decision logic rules for the DFT of the change trajectories of geographical elements or phenomena

[0062]

[0063] Note: Dmedian and Fmedian respectively represent that the division criteria for the deviation degree and frequency are the 50th percentile (median) of their data sets. The median is selected as the division criterion for the deviation degree and frequency because its stability makes it unaffected by extreme values and can effectively reflect the symmetry of the data, thus ensuring that the analysis results are more accurate and representative.

[0064] The above-described embodiments only express the specific implementation manners of the present application, and their descriptions are relatively specific and detailed, but they should not be construed as limiting the protection scope of the present application. It should be noted that for those of ordinary skill in the art, without departing from the concept of the technical solution of the present application, several deformations and improvements can still be made, and these all belong to the protection scope of the present application.

Claims

1. A method for constructing a dynamic trajectory analysis framework based on deviation-frequency-trend, characterized in that It includes the following steps: Calculate the inter-annual change rate to compare the changes in each region relative to the previous period. Based on the inter-annual change rate, divide the change trends of geographical elements or phenomena into different levels; Construct a directed-edge change atlas based on the calculation of the inter-annual change rate, and obtain the evolution path of geographical elements or phenomena over time based on the extraction method of the directed-edge change atlas; Combine the deviation, frequency, and trend indicators to identify and classify the change trajectories of geographical elements or phenomena.

2. The method for constructing a dynamic trajectory analysis framework based on deviation-frequency-trend according to claim 1, wherein The deviation indicator records the degree of deviation of the change trajectory of geographical elements or phenomena during the research time series compared to the stable state, and measures the difference between the ecological state of each time phase and the stable state; the calculation formula of the deviation indicator is: where y i is the rank code of the change of geographical elements or phenomena at the i-th research time phase, and n is the number of research time phases; if the deviation degree D = 0, it means that the trajectory is in a stable state; if D ≥ 8, it indicates that the ecological process in this area deviates more from the stable state; if 0 < D < 8, it indicates that the ecological process is more tending to be stable.

3. A method for constructing a dynamic trajectory analysis framework based on deviation-frequency-trend, as claimed in claim 2, wherein The frequency indicator records the number of changes in the change trend of geographical elements or phenomena between adjacent years; the calculation formula of the frequency indicator is: where y i is the rank code of the geographical elements or phenomenon changes in the i-th research phase, n is the number of research phases, I is the indicator function. When y i and y i+1 are different, the value of I is 1; otherwise it is 0; whenever the change rank codes of adjacent years are different, the frequency F increases by 1; the higher the value of F, the more frequent the change is.

4. A method for constructing a dynamic trajectory analysis framework based on deviation-frequency-trend according to claim 3, characterized in that The trend indicator captures and describes the directionality of the change of geographical elements or phenomena over time during the research time series, that is, whether the change is increasing, decreasing, or remaining stable; the calculation formula of the trend indicator is: where n is the number of research time phases, and x i is the abscissa of the trajectory point, representing the extension of the time series; y i is the ordinate of the trajectory point, representing the rank code of the change of geographical elements or phenomena; if T = 0, it means that the ecological process is in a stable state without an obvious increasing or decreasing trend; if T > 0, it means that the geographical elements or phenomena show an increasing trend, and vice versa for a decreasing trend.

5. A method for constructing a dynamic trajectory analysis framework based on deviation-frequency-trend, as claimed in claim 1, wherein The inter-annual change rate reveals the change trend within each region, and the calculation formula of the annual change rate is: Where: V is the change rate of the geographical element or phenomenon between the t-th year and the (t - 1)-th year, and Ef t is the quantity of the geographical element or phenomenon in the t-th year; Ef t-1 is the quantity of the geographical element or phenomenon in the (t - 1)-th year.

6. A method for constructing a dynamic trajectory analysis framework based on deviation-frequency-trend, according to claim 1 or 5, characterized in that The division of the change trends of geographical elements or phenomena into different levels includes the following steps: According to the standard deviation SD of the change rate V in the time series, it is divided into: a large decrease V < -2SD%, a small decrease -2SD% ≤ V < -SD%, basically stable -SD% ≤ V < SD%, a small increase SD% ≤ V < 2SD%, a large increase V > 2SD%; the change categories are respectively coded as 1: large decrease, 2: small decrease, 3: basically stable, 4: small increase, and 5: large increase.

7. A method for constructing a dynamic trajectory analysis framework based on deviation - frequency - trend, according to claim 6, wherein The extraction method of the directed-edge change atlas includes the following steps: Map the level codes of the changes in geographical elements or phenomena onto a two-dimensional plane, where the ordinate represents different level codes of changes, and the abscissa represents the change stages within the time series from t - 1 to t; Connect each vertex in chronological order; each directed edge points from the vertex of the level code in the previous time phase to the vertex of the level code in the later time phase; Present the change trajectory of geographical elements in a two-dimensional plane in the form of a directed graph, and intuitively display the change process of this geographical element or phenomenon over time.

8. A method for constructing a dynamic trajectory analysis framework based on deviation-frequency-trend, as claimed in claim 1, wherein The deviation, frequency, and trend indicators are comprehensively analyzed in the time series through logical rules, and finally the change trajectories of geographical elements or phenomena are summarized into nine basic types.

Images