Method for determining the intensity of morphological changes in a gulf

Abstract

The application discloses a method for determining the intensity of morphological change of a bay, comprising the following steps: (1) obtaining multi-temporal remote sensing images based on 3S technology, extracting the coastline and reclamation information, and calculating the plane area of the bay, the coastline length, the shape index and the fractal dimension; (2) implementing three-level standardization processing: parameter-level standardization eliminates the dimensional difference, index-level standardization ensures the fairness of item weighting, and result-level standardization establishes a unified comparable scale; (3) constructing three item indexes of shape complexity intensity, coastline artificialization intensity and area reduction intensity; (4) distributing adaptive weights according to the dominant change characteristics of the research area, and outputting the comprehensive intensity after weighted summation and percentage normalization. Through the coupling of standardization and dynamic weight, the application breaks through the limitation of single index static description, is suitable for multi-bay horizontal comparison and long-time sequence vertical analysis, and can provide technical support for the prediction of the evolution trend of the bay and the accurate management of the coastal zone.

Description

Technical Field

[0001] This invention belongs to the field of coastal ecological environment monitoring, and specifically relates to a method for determining the intensity of bay morphological changes. Background Technology

[0002] Bays are key areas of interaction between land and sea, and their morphological changes directly reflect the combined effects of human land reclamation activities and natural evolution. In recent years, with the intensification of urbanization, port construction, and aquaculture activities in coastal areas, bay coastlines have become increasingly artificial, bay areas have continued to shrink, and bay morphology has become more complex, leading to increasingly prominent problems such as changes in bay hydrodynamic conditions and ecosystem degradation.

[0003] Existing research on bay morphological changes largely focuses on spatiotemporal comparative analysis of single indicators, such as interpreting bay area changes and coastline shifts using remote sensing images, or employing geometric indicators like the Shape Index of Bay (SIB) to describe the complexity of bay planar morphology. However, existing methods have the following shortcomings: First, they mostly remain at the qualitative or semi-quantitative descriptive level, lacking a quantitative and comprehensive evaluation index system for the intensity of bay morphological changes; second, existing indicators such as the shape index only reflect the static morphological characteristics of a certain time segment, failing to effectively integrate multi-source information such as coastline length changes, area reduction rates, and types of land reclamation activities, making it difficult to characterize the dynamic intensity of bay morphological changes over long time series; third, driven by land reclamation activities, bay morphological changes exhibit significant spatiotemporal heterogeneity, with different morphological response mechanisms in different sea areas (such as Bohai Bay, Laizhou Bay, and Liaodong Bay). Existing technologies have failed to establish differentiated intensity calculation models for different types of morphological changes, resulting in overly coarse evaluation results that are not conducive to precise management of bay resources and ecological protection decisions.

[0004] Therefore, there is an urgent need to establish a scientific and systematic method for determining the intensity of bay morphological changes, which can comprehensively integrate multi-dimensional parameters such as bay geometry, shoreline attributes, and human activities to achieve a quantitative and refined assessment of the intensity of bay morphological changes. Summary of the Invention

[0005] The technical problem to be solved by the present invention is to overcome the shortcomings of the prior art and provide a method for determining the intensity of bay morphological changes, thereby solving the technical problem that the existing assessment methods are too coarse and difficult to quantitatively characterize the intensity of dynamic changes in bay morphology.

[0006] To solve the above-mentioned technical problems, the technical solution adopted by the present invention is as follows:

[0007] A method for determining the intensity of bay morphological changes, characterized by comprising the following steps:

[0008] (1) Acquisition of basic geographic parameters: Using 3S technology, multi-temporal remote sensing images are processed to extract coastlines and identify the types and extent of land reclamation activities. The planar area (A), coastline length (P), shape index (SIB), and fractal dimension (D) of the bay are calculated for each period. f ).

[0009] (2) Parameter-level standardization: The area and shoreline length are dimensionless using the baseline ratio method; the shape index and fractal dimension are normalized using the range standardization method to eliminate the differences in dimensions and orders of magnitude between different parameters.

[0010] (3) Calculation of the intensity of change of each item: Based on the standardized parameters, the three item indicators are calculated respectively:

[0011] (3a) Shape Complexity Intensity (Rs): Characterizes the rate at which the planar morphology of a bay tends to become more complex. The calculation formula is:

[0012]

[0013] In the formula, R s The intensity of the bay's shape complexity is represented by ΔSIB, which is the change in the shape index during the study period. SIB = P is the length of the bay's coastline (km), A is the bay's surface area (km²); Δt is the time span (years), SIB base The base period shape index is α, and the shoreline fractal dimension correction coefficient is α= D f To study the fractal dimension of the shoreline at the end of the research period, Df0 is the fractal dimension of the shoreline at the baseline period;

[0014] (3b) Shoreline artificialization intensity (Rp): Characterizes the degree of shoreline artificialization caused by human activities. The calculation formula is:

[0015]

[0016] In the formula, R p ΔL represents the intensity of shoreline artificialization, and ΔL represents the change in shoreline length (km) during the study period. base L represents the shoreline length (km) at the baseline period. artif To determine the length of the artificial shoreline (km) at the end of the study period, L total To determine the total shoreline length (km) at the end of the study period, β is the weighting coefficient for shoreline length changes, determined by the analytic hierarchy process, with a value ranging from 0.5 to 0.8.

[0017] (3c) Area Reduction Intensity (Ra): Characterizes the intensity of bay area loss caused by land reclamation, distinguishing the impact of different utilization types. The calculation formula is:

[0018]

[0019] In the formula, R a Let μ represent the intensity of bay area reduction, i represent the i-th type of land reclamation activity, and μ represent the intensity of bay area reduction. i The morphological influence weight coefficient for the i-th type of land reclamation activity is determined by the analytic hierarchy process (AHP), ΔA. i Let A be the area change (km²) caused by the i-th type of land reclamation activity. base The area of ​​the bay in the baseline period (km²)

[0020] (4) The method for determining the intensity of bay morphological changes as described above, preferably, the types of reclamation activities mentioned in step (3) include aquaculture, transportation land, industrial and mining land, agricultural land, urban land, land to be utilized, and salt fields, with a morphological influence weight μ. i Determined through expert scoring or fitting of historical samples.

[0021] (5) Index-level standardization: The calculated intensity values ​​of the three sub-items (Rs, Rp, Ra) are again standardized by range standardization to map them to a unified numerical range and eliminate differences in physical meaning;

[0022] (6) Comprehensive Intensity Calculation and Normalization: Based on the dominant driving characteristics of bay morphological changes in the study area (such as reclamation, port construction, or natural siltation), weights (ω1, ω2, ω3) are assigned to the three standardized sub-indicators, and the weighted sum is used to obtain the original comprehensive intensity R; finally, the final intensity value R ∈ [0, 100] is obtained by percentage normalization.

[0023] (7) Determine the total intensity R of the bay morphological changes in the study area. The specific formula is as follows:

[0024]

[0025] In the formula, ω1, ω2, and ω3 are the weighting coefficients of the intensity of bay shape complexity, the intensity of shoreline artificialization, and the intensity of bay area reduction, respectively, and ω1+ω2+ω3=1.

[0026] (8) The method for determining the intensity of bay morphological changes as described above, preferably, the method for determining the weight coefficients ω1, ω2, and ω3 in step (6) is as follows: when the study area is mainly characterized by the expansion of aquaculture salt fields, ω3>ω2>ω1; when the study area is mainly characterized by industrial and mining and port construction, ω2>ω3>ω1; when the study area is mainly characterized by the morphological complexity caused by the combined effects of natural siltation and reclamation, ω1>ω2>ω3.

[0027] The beneficial effects of this invention are as follows:

[0028] (1) Three-level standardization eliminates the differences in dimensions and orders of magnitude across the entire chain; (2) Standardization-weight dynamic coupling avoids the dominance of abnormal driving factors; (3) Percentage results support horizontal comparisons of multiple bays and vertical comparisons of different time periods. Attached Figure Description

[0029] Figure 1 A flowchart of a preferred embodiment of the present invention; Detailed Implementation Plan

[0030] Example 1: Using the method of the present invention to assess the intensity of bay morphological changes in the Bohai Sea and its sub-regions from 1980 to 2020

[0031] 1. Data and Preprocessing: Landsat remote sensing images from 1980 and 2020 were acquired. After radiometric calibration, atmospheric correction and geometric fine correction, the coastline was extracted using the MNDWI index combined with manual correction, and the extent of land reclamation was interpreted.

[0032] 2. Parameter Calculation and Primary Standardization: Calculate the bay area, coastline length, shape index (SIB), and fractal dimension (D) for both periods. f The area and coastline length were standardized using baseline period ratios, and the SIB and D ratios were standardized. f Range standardization was performed. (1) Coastline extraction accuracy: RMSE < 10.4m, OA 85%-93%, Kappa 84.5%-90.9%. (2) Reclamation extraction accuracy: OA 85%-93%, PA / UA ≥ 80% except for swamps / land to be utilized, area uncertainty ± 0.15km².

[0033] 3. Calculation of individual strength components:

[0034] Table 1. Changes in basic morphological parameters of the Bohai Sea and its sub-regional bays (1980-2020)

[0035] SIB 1980 2.1 1.3 1.5 2.1 2020 3.7 2.8 3.5 2.5 1980-2020 1.6 1.4 2.0 0.4 fractal dimension 1980 1.1 1.0 1.1 1.1 2020 1.2 1.1 1.5 1.2 1980-2020 0.1 0.1 0.4 0.1 Total shoreline length (km) 1980 1962.0 450.1 335.6 1183.8 2020 3520.3 1252.0 767.5 1509.2 1980-2020 1558.3 802.0 432.0 325.5 Artificial shoreline length (km) 1980 742.1 256.2 183.9 302.3 2020 3141.7 1145.7 611.7 1384.7 1980-2020 2399.6 889.5 427.8 1082.4 <![CDATA[Gulf area km 2 > 1980 77200.6 13654.6 6787.8 35462.9 2020 73968.2 12528.5 5886.0 34296.7 1980-2020 -3232.4 -1126.2 -901.8 -1166.2

[0036] Table 2. Changes in the area of ​​reclamation types in the Bohai Sea and its sub-bays (1980-2020)

[0037] Aquaculture 674.0 183.9 326.3 163.8 Transportation land 284.9 83.9 127.9 73.1 Industrial and mining land 226.1 66.5 101.5 58.0 farmland 18.9 3.4 12.0 3.5 Urban land 44.7 12.9 20.6 11.3 Land to be utilized 223.6 62.6 105.7 55.3 Salt fields 172.3 39.7 95.3 37.2

[0038] Taking Laizhou Bay as an example (1980-2020, Δt=40a):

[0039] (1) Shape complexity intensity: Rs = ((SIB) 2020 - SIB 1980 () / 40) × (1 / SIB) 1980 ) × (Df 2020 / Df 1980= 0.023

[0040] (2) Intensity of shoreline artificialization (take β=0.6): Rp = 0.6 × ((L 2020 - L 1980 ) / L 1980 ) / 40 + 0.4× (L artif 2020 / L total 2020) = 0.156

[0041] (3) Area reduction intensity (weight μ of reclamation type) i (Assigned based on experience): Ra = Σ [μ i × (ΔA i / A1980)] / 40 = 0.089

[0042] 4. Standardization and Synthesis at the Index Level: The intensity values ​​of the three sub-items of Laizhou Bay were compared with the extreme values ​​of other bays in the Bohai Sea, and range standardization was performed, yielding Ṝs=0.65, Ṝp=0.63, Ṝa=0.56. Based on the characteristics of Laizhou Bay, which is dominated by port construction and reclamation, weights were set as ω1=0.25, ω2=0.40, ω3=0.35. Weighted summation: R = 0.25×0.65 +0.40×0.63 + 0.35×0.56 = 0.613

[0043] 5. Final Results: Based on the extreme value range of all assessed objects and normalized to a percentage scale, the intensity score of the bay morphological change in Laizhou Bay from 1980 to 2020 was 54.3. This result can be quantitatively compared with that of Bohai Bay (68.2) and Liaodong Bay (42.6) during the same period, reflecting the intensity gradient of the impact of human activities on different bays.

[0044] This embodiment verifies that the three-level standardization system can effectively eliminate dimensional differences and achieve accurate horizontal comparison of multiple bays.

Claims

1. A method for determining the intensity of bay morphological changes, characterized in that, Includes the following steps: (1) Based on multi-temporal remote sensing images, extract coastline and reclamation information, and calculate the bay's planar area, coastline length, shape index and fractal dimension; (2) Perform parameter-level standardization on the above parameters to eliminate dimensional differences; (3) Based on the standardized parameters, calculate the three sub-indices: shape complexity intensity, shoreline artificialization intensity, and area reduction intensity. (4) Standardize the three sub-indicators at the indicator level and map them to a unified numerical range; (5) Based on the dominant driving characteristics of bay morphological changes in the study area, adaptive weights are assigned, and after weighted summation and percentage normalization, the intensity value of bay morphological changes is obtained.

2. The method according to claim 1, characterized in that, (2) In the parameter-level standardization: the area and shoreline length are dimensionless using the baseline ratio method; the shape index and fractal dimension are normalized using the range standardization method.

3. The method according to claim 1, characterized in that, The formula for calculating the shape complexity intensity Rs is: In the formula, R s The intensity of the bay's shape complexity is represented by ΔSIB, which is the change in the shape index during the study period. SIB = P is the length of the bay's coastline (km), A is the bay's surface area (km²), Δt is the time span (years), and SIB is the bay's area. base The base period shape index is α, and the shoreline fractal dimension correction coefficient is α= D f To study the fractal dimension of the coastline at the end of the research period, Df0 is the fractal dimension of the coastline at the baseline period; where ΔSIB is the change in the shape exponent, SIB base The base period shape index, Δt is the study period, and D is the shape index. f Let be the fractal dimension at the end of the period, and Df0 be the fractal dimension at the baseline period.

4. The method according to claim 1, characterized in that, The formula for calculating the shoreline artificialization intensity Rp is: Where ΔL is the change in shoreline length, L base L represents the shoreline length at the baseline period. artif End-of-term artificial shoreline length, L total The total shoreline length at the end of the period is given by β, which is a weighting coefficient ranging from 0.5 to 0.

8.

5. The method according to claim 1, characterized in that, The formula for calculating the area reduction intensity Ra is: Where μ i Let ΔA be the weight of the morphological influence of the i-th type of land reclamation activity. i A represents the change in area caused by this type of activity. base This represents the surface area of ​​the bay during the baseline period.

6. The method according to claim 5, characterized in that, The types of land reclamation activities include aquaculture, transportation land, industrial and mining land, agricultural land, urban land, land awaiting utilization, and salt fields. The morphological influence weight μi is determined by expert scoring or historical sample fitting.

7. The method according to claim 1, characterized in that, The standardization of the indicators adopts the range standardization method, which maps the three sub-indicators to the interval [0,1].

8. The method according to claim 1, characterized in that, The adaptive weights are set based on the dominant change characteristics of the study area, which include reclamation, port construction, or natural siltation.

9. The method according to claim 1, characterized in that, The formula for the percentage system normalization is: In the formula, ω1, ω2, and ω3 are the weighting coefficients of the intensity of bay shape complexity, the intensity of shoreline artificialization, and the intensity of bay area reduction, respectively, and ω1+ω2+ω3=1.

10. The method for determining the intensity of bay morphological change according to claim 9, characterized in that, The weighting coefficients ω1, ω2, and ω3 mentioned in the formula are determined as follows: when the study area is mainly characterized by the expansion of aquaculture salt fields, ω3>ω2>ω1; when the study area is mainly characterized by shoreline artificialization and port construction, ω2>ω3>ω1; when the study area is mainly characterized by the complex morphology caused by the combined effects of natural siltation and reclamation, ω1>ω2>ω3.

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