Method for evaluating ecological health of coral reef by human activities based on noctilucent remote sensing sequence

Abstract

The invention relates to the technical field of satellite remote sensing, and discloses a method for evaluating the ecological health of human activities on coral reefs based on a noctilucent remote sensing sequence, which comprises the following steps: acquiring a noctilucent remote sensing image of a research sea area acquired by a satellite in a research time sequence, and taking the noctilucent remote sensing image as human activity data; obtaining a corrected sea area live coral coverage degree corresponding to the research time sequence after the sea temperature influence is eliminated; and carrying out partial correlation analysis on the corrected sea area live coral coverage and the luminous remote sensing image corresponding to the research time sequence to determine the influence of human activities on the live coral coverage. The technical problem that the influence of human activities on coral reef ecological health is difficult to evaluate in the prior art is solved.

Description

Technical Field

[0001] The invention relates to the field of satellite remote sensing technology, and in particular to a method for evaluating the ecological health of coral reefs based on human activities based on night light remote sensing sequences. Background Art

[0002] Corals have an extremely important impact on marine ecosystems. Coral reefs are not only one of the most diverse ecosystems on Earth, but also the habitat of many marine organisms. They play a key role in maintaining the balance of marine ecology. The following are some specific aspects of the impact of corals on the ecology:

[0003] Coral reefs provide habitats for a wide range of marine species, including fish, crustaceans, molluscs, sponges, echinoderms, etc. Coral reefs are one of the most biodiverse areas, with a large number of species. Coral reefs can attenuate the energy of waves, reduce erosion, and provide natural coastal protection for coastal communities. Coral reefs are important breeding and growth sites for many commercial and non-commercial fish, supporting global fisheries. Coral reefs can absorb carbon dioxide from the atmosphere, helping to slow global warming. Symbiotic algae in coral reefs produce oxygen through photosynthesis, which contributes to the oxygen cycle of the earth's atmosphere. Coral reefs provide valuable natural laboratories for studying the complexity and function of marine ecosystems.

[0004] According to relevant data, in the past few decades, the distribution of coral reefs in many areas around the world has decreased significantly. At the same time, the increase in artificial and industrial development in coastal areas will also put certain pressure on coral reef ecosystems. Although coral reef ecosystems only account for less than 1% of the ocean area, their biodiversity is the highest in the ocean.

[0005] Coral bleaching refers to the phenomenon that corals lose their symbiotic algae (mainly zooxanthellae), which causes the corals to turn white. The color of corals mainly comes from these symbiotic algae, which provide the nutrients needed for corals through photosynthesis. When corals are under stress, these symbiotic algae will be expelled or die, causing the corals to lose their bright colors and appear white or light. Causes of coral bleaching.

[0006] The recovery window for coral bleaching is the time period during which a coral reef is able to return to a healthy state after a bleaching event. This time period is critical to the survival of coral reefs as it determines whether corals can survive and reestablish their relationship with their symbiotic algae until environmental conditions improve.

[0007] Coral bleaching does not directly determine the mortality of corals. Corals can recover their symbiotic populations and restore their colors within a few months, avoiding individual deaths. However, it is worth noting that due to the intensification of human impacts, interference sources have been brought to coral recovery, resulting in a narrowing of the "recovery window" between frequent coral bleaching events, which will result in insufficient time for corals to recover. Therefore, there is still a lot of research to be done on the interference sources that slow down the "recovery window" of living coral vegetation.

[0008] The sources of disturbance that caused the reduction in live coral cover remain to be studied. Based on our research, there is reason to suspect that human activities, combined with global climate change, have become new sources of ecological disturbance stress and have a negative impact on coastal ecosystems. Therefore, for the sustainable development of marine resources and the construction of ecological civilization, it is crucial to control the damage of various types of stressors to coral reef ecology.

[0009] The main problems brought to the ocean by human activities and development include heavy metal pollution, persistent organic pollutants pollution, eutrophication, plastic waste, etc. Under the joint action of human activities and climate change, a series of problems such as ocean acidification and coral reef degradation have also emerged, which have affected the healthy development of offshore ecosystems to varying degrees. Due to the cumulative impact of human activities and considering the sensitive characteristics of coral reef ecosystems, the study believes that in order to explore the impact of human activities on coral reef ecosystems, it is necessary to find the correlation between the two from long time series and large spatiotemporal patterns.

[0010] Human activities take many forms. To study the impact of human activities on the ecological health of coral reefs, it is necessary to assess the intensity of human activities near coral reefs. However, assessing the intensity of human activities near coral reefs is very difficult because human activities include many types of activities, and the intensity of human activities is the result of the joint action of many human groups. Activity data is complex and inconsistent. At the same time, the data is not open, not shared, difficult to obtain, not global, and lacks strong detection and data reporting.

[0011] Therefore, in the technical field of studying the impact of human activities on the ecological health of coral reefs, data on human activities are seriously insufficient. As a result, due to the lack of human activity data, a technical bottleneck has been formed in the technical field of studying the impact of human activities on the ecological health of coral reefs, making it difficult to assess the impact of human activities on the ecological health of coral reefs. Summary of the invention

[0012] The main purpose of the present invention is to provide a method for assessing the ecological health of coral reefs based on human activities based on night light remote sensing sequences, aiming to solve the problem that the lack of human activity data has formed a technical bottleneck in the technical field of studying the impact of human activities on the ecological health of coral reefs, making it difficult to assess the impact of human activities on the ecological health of coral reefs.

[0013] To achieve the above purpose, the present invention provides a method for assessing the ecological health of coral reefs based on human activities based on night light remote sensing sequences, comprising the following steps:

[0014] Obtain night light remote sensing images of the research sea area collected by satellite in the research time series as human activity data;

[0015] Obtain the corrected live coral coverage in the sea area corresponding to the research time series after removing the influence of sea temperature;

[0016] Partial correlation analysis was performed on the corrected live coral coverage of the sea area and the night light remote sensing images corresponding to the study time series to determine the impact of human activities on the live coral coverage.

[0017] Optionally, the step of obtaining night light remote sensing images of the research sea area collected by the satellite in the research time series as human activity data includes:

[0018] Acquire a first night light remote sensing image of the research sea area collected by a first satellite in a first time series, wherein the first satellite is a DMSP / OLS satellite;

[0019] Acquire a second night light remote sensing image of the research sea area collected by a second satellite in a second time series, wherein the second satellite is a VIIRS-DNB satellite;

[0020] The first night light remote sensing image and the second night light remote sensing image are spliced ​​to obtain a night light remote sensing image corresponding to a research time series, wherein the research time series is a union of the first time series and the second time series.

[0021] Optionally, the step of performing splicing processing on the first night light remote sensing image and the second night light remote sensing image to obtain the night light remote sensing image corresponding to the research time series includes:

[0022] De-noising the second night light remote sensing image;

[0023] Calculate the total amount of light at night corresponding to each unit time in the first time series according to the first night light remote sensing image;

[0024] Calculate the second night light amount corresponding to each unit time in the second time series according to the second night light remote sensing image;

[0025] Obtaining the overlapping time series of the first time series and the second time series, determining the first local nighttime light total amount corresponding to the overlapping time series from the first nighttime light total amount, and determining the second local nighttime light total amount corresponding to the overlapping time series from the second nighttime light total amount;

[0026] According to the equal relationship between the first local night light total amount and the second local night light total amount, the second night light total amount corresponding to the second satellite is converted to the first night light total amount corresponding to the first satellite to obtain the night light total amount corresponding to the research time series expressed by the first satellite as a night light remote sensing image.

[0027] Optionally, the step of obtaining the corrected live coral coverage in the sea area corresponding to the research time series after removing the influence of sea temperature comprises:

[0028] Obtain the live coral coverage of the initial sea area corresponding to the research time series;

[0029] Obtain the sea temperature data corresponding to the research time series;

[0030] The series of changes in live coral cover affected by sea temperature were calculated based on sea temperature data;

[0031] According to the change sequence of live coral coverage affected by sea temperature, the initial live coral coverage of the sea area was corrected to obtain the corrected live coral coverage of the sea area corresponding to the research time series.

[0032] Optionally, the first time series is from the start year of the study to 2013, and the second time series is from 2012 to the end year of the study.

[0033] Optionally, the step of denoising the second night light remote sensing image includes:

[0034] The highest threshold and the lowest threshold of the denoising process are determined, and the denoising process is performed on each second night light remote sensing image collected in the second time series.

[0035] Optionally, the highest threshold and the lowest threshold of the denoising process are determined, and the denoising process is performed on each second night light remote sensing image collected in the second time series, as follows:

[0036] Determine the highest threshold L m ;

[0037] Determine the minimum threshold L t The value range of

[0038] Select several minimum thresholds L to be tested in the value range t ;

[0039] For each selected minimum threshold to be tested, the total amount of calibrated nighttime light in each sea area in the second nighttime light remote sensing image of the overlapping year of the first time series and the second time series is calculated using the following formulas (1) and (2):

[0040]

[0041] in, It represents the calibration effective pixel value of the jth grid of the i-th sea area in the second night light remote sensing image, i is the serial number of the sea area, 1≤i≤I, I is the total number of sea areas studied; DN ij Represents the effective pixel value of the jth grid in the i-th sea area in the second night light remote sensing image, 1≤j≤J, J is the number of grids in the studied sea area; Represents the total amount of calibrated nighttime light in the ith sea area in the second nighttime light remote sensing image;

[0042] Conduct significance analysis and correlation coefficient analysis on the total amount of calibrated nighttime lights in each sea area in the second nighttime light remote sensing image, and determine the lowest threshold to be tested with the best performance as the lowest threshold;

[0043] The lowest threshold is adopted and formula (1) is used to perform denoising on each second night light remote sensing image collected in the second time series. Formula (2) is used to calculate the total amount of calibrated night light in each sea area in each second night light remote sensing image collected in the second time series.

[0044] Optionally, the step of converting the second total amount of nighttime light corresponding to the second satellite to the first total amount of nighttime light corresponding to the first satellite according to the equal relationship between the first local total amount of nighttime light and the second local total amount of nighttime light, so as to obtain the total amount of nighttime light corresponding to the research time series expressed by the first satellite as the nighttime light remote sensing image, specifically includes:

[0045]

[0046] Among them, CR i represents the conversion ratio of the ith sea area; represents the average value of the total amount of nighttime light calculated by the first satellite in the i-th sea area in the overlapping time zone of the first time series and the second time series; represents the average value of the total amount of nighttime light calculated by the second satellite in the i-th sea area in the overlapping time zone of the first time series and the second time series;

[0047]

[0048] in, Indicates the total nighttime light of the first satellite in the i-th ocean area in the specified year in the second time series, VIIRS year,i represents the total amount of nighttime light from the second satellite in the i-th ocean area in the specified year in the second time series;

[0049] The total amount of nighttime light from the first satellite corresponding to the first time series and the total amount of nighttime light converted from the total amount of nighttime light from the second satellite corresponding to the second time series are combined as a nighttime light remote sensing image.

[0050] Optionally, in the step of performing partial correlation analysis on the corrected marine live coral coverage and the night light remote sensing images corresponding to the research time series to determine the impact of human activities on the live coral coverage, the partial correlation coefficient of the partial correlation analysis is calculated as follows:

[0051]

[0052] Among them, r HC.D is the partial correlation coefficient between human activity intensity H and live coral cover C under the influence of controlled weekly heat D; r HC represents the correlation coefficient between the intensity of human activities and the coverage of living corals; r HD represents the correlation coefficient between human activity intensity and weekly heat; r CD Represents the correlation coefficient between coral cover and weekly temperature.

[0053] Optionally, the method further includes:

[0054] The standardized total amount of nighttime lights in each sea area is calculated as follows:

[0055]

[0056] in, represents the total amount of standardized nighttime lights for the ith sea area in a specified year; represents the minimum value of the total amount of nighttime light in the ith sea area, represents the minimum value of the total amount of nighttime light in the i-th sea area, k represents the specified year; k∈[1,n], k represents the k-th year among the n years from the start year to the end year of the study.

[0057] In the technical solution of the present invention, in order to obtain long-term series of human activity data and study the impact of human activities on the ecological health of coral reefs, night light data obtained by satellite remote sensing technology is used as the data source of human activities. It is easy to understand that night lights are the result of the combined effects of human activities. For example, when human fishing activities occur near coral reefs, fishing lighting activities will occur, such as light-luring fishing boats. For another example, when human offshore operations occur near coral reefs, corresponding offshore lighting will also be generated. Therefore, in the present invention, the use of night light data to evaluate the intensity of human activities can well reflect the intensity of human activities. The stronger the night light data of the study sea area, the more frequent the human activities. Conversely, the weaker the night light data of the study sea area, the lower the intensity of human activities. Furthermore, the night light remote sensing images acquired by satellites can comprehensively reflect the overall night light situation of the study sea area, and can obtain long-term series of night light remote sensing images. In addition, the present invention also removes the influence of sea temperature from the live coral coverage data of the sea area corresponding to the research time series to obtain the corrected live coral coverage data of the sea area, thereby performing partial correlation analysis on the corrected live coral coverage of the sea area and the night light remote sensing images corresponding to the research time series respectively, to determine the influence of night light on the live coral coverage. Therefore, although the data of human activities are insufficient, the present invention can still analyze the influence of human activities in the sea area on the live coral coverage with respect to the night light remote sensing images of different time series, which is conducive to overcoming the technical problem in the prior art that it is difficult to evaluate the influence of human activities on the ecological health of coral reefs. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] Figure 1 The research sea area in the present invention is located as shown on the global map;

[0059] Figure 2 A night-light Earth picture constructed using night-light remote sensing images;

[0060] Figure 3 Coral Bleaching Weekly Heat (DHW) data from 1992 to 2020;

[0061] Figure 4 To study the proportion of total sea light volume under different minimum thresholds;

[0062] Figure 5 is the correlation coefficient and p-value between the total number of night lights of the second satellite and the total number of night lights of the first satellite under different minimum thresholds;

[0063] Figure 6 This is a scatter plot of coral cover and human activity intensity (expressed by ALANI) in Australian waters;

[0064] Figure 7This is a scatter plot of coral coverage and human activity intensity (expressed by ALANI) in Brazilian waters;

[0065] Figure 8 This is a scatter plot of coral cover and human activity intensity (expressed by ALANI) in the Caribbean Sea;

[0066] Fig. 9 This is a scatter plot of coral cover and human activity intensity (expressed by ALANI) in the East Asian seas;

[0067] Fig.10 This is a scatter plot of coral cover and human activity intensity (expressed by ALANI) in the eastern tropical Pacific.

[0068] Fig.11 This is a scatter plot of coral cover and human activity intensity (expressed by ALANI) in the Red Sea and the Gulf of Aden;

[0069] Fig.12 This is a scatter plot of coral coverage and human activity intensity (expressed by ALANI) in the ROPME waters;

[0070] Fig.13 This is a scatter plot of coral cover and human activity intensity (expressed by ALANI) in the South Asian Sea;

[0071] Fig.14 This is a scatter plot of coral cover and human activity intensity (expressed by ALANI) in the western Indian Ocean;

[0072] Fig.15 This is a scatter plot of coral cover and human activity intensity (expressed by ALANI) in the Pacific Ocean;

[0073] Fig.16 FIG. 1 is a flow chart of the first embodiment of the present invention.

[0074] The purpose, features and advantages of the present invention will be further described with reference to the accompanying drawings in conjunction with the embodiments. DETAILED DESCRIPTION

[0075] It should be understood that the specific embodiments described herein are only used to explain the present invention, and are not used to limit the present invention.

[0076] In the following description, suffixes such as "unit", "component" or "unit" used to represent elements are only used to facilitate the description of the present invention, and have no specific meanings. Therefore, "unit", "component" or "unit" can be used in a mixed manner.

[0077] See also Figures 1 to 16In a first embodiment of the present invention, a method for assessing the ecological health of coral reefs based on human activities based on night light remote sensing sequences is provided, comprising the following steps:

[0078] Step S10, obtaining night light remote sensing images of the research sea area collected by the satellite in the research time series as human activity data;

[0079] Step S20, obtaining the corrected live coral coverage in the sea area corresponding to the research time series after removing the influence of sea temperature;

[0080] Step S30, performing partial correlation analysis on the corrected sea area live coral coverage and night light remote sensing images corresponding to the research time series, so as to determine the impact of human activities on the live coral coverage.

[0081] In the technical solution of the present invention, in order to obtain long-term series of human activity data and study the impact of human activities on the ecological health of coral reefs, night light data obtained by satellite remote sensing technology is used as the data source of human activities. It is easy to understand that night lights are the result of the combined effects of human activities. For example, when human fishing activities occur near coral reefs, fishing lighting activities will occur, such as light-luring fishing boats. For another example, when human offshore operations occur near coral reefs, corresponding offshore lighting will also be generated. Therefore, in the present invention, the use of night light data to evaluate the intensity of human activities can well reflect the intensity of human activities. The stronger the night light data of the study sea area, the more frequent the human activities. Conversely, the weaker the night light data of the study sea area, the lower the intensity of human activities. Furthermore, the night light remote sensing images acquired by satellites can comprehensively reflect the overall night light situation of the study sea area, and can obtain long-term series of night light remote sensing images. In addition, the present invention also removes the influence of sea temperature from the live coral coverage data of the sea area corresponding to the research time series to obtain the corrected live coral coverage data of the sea area, thereby performing partial correlation analysis on the corrected live coral coverage of the sea area and the night light remote sensing images corresponding to the research time series respectively, to determine the influence of night light on the live coral coverage. Therefore, although the data of human activities are insufficient, the present invention can still analyze the influence of human activities in the sea area on the live coral coverage with respect to the night light remote sensing images of different time series, which is conducive to overcoming the technical problem in the prior art that it is difficult to evaluate the influence of human activities on the ecological health of coral reefs.

[0082] like Figure 1 As shown, the research sea area of ​​the present invention may include the coral reef research area selected by the World Marine Ecological Zone (MEOW), including: South Asia Sea ( Figure 1 SouthAsia), Pacific( Figure 1 Central Pacific), Eastern Tropical Pacific ( Figure 1 China ETP), Caribbean ( Figure 1Caribbean), Australian waters ( Figure 1 Central Australia), Western Indian Ocean ( Figure 1 WIO), ROPME (Regional Organization for the Protection of the Marine Environment) Figure 1 ROPME), Red Sea and Gulf of Aden ( Figure 1 Central PERSGA), East Asian Sea ( Figure 1 Central EAS) and Brazilian waters ( Figure 1 Brazil).

[0083] Among them, the East Asian Sea (18.9663 million square kilometers) and the Pacific Ocean (30.7338 million square kilometers) have the largest areas. The research sea area can cover the area between longitude -180° to 180° and latitude -50° to 50°, and inland areas are excluded, such as Figure 1 To locate the research sea area as shown on the global map, at least one sea area can be selected from the above ten regions as the research sea area as needed.

[0084] In the present invention, the satellite refers to a satellite capable of collecting night light remote sensing images. From the night light remote sensing images collected by the satellite, the night light remote sensing images of the research sea area are extracted. Figure 2 Night light pictures constructed using night light remote sensing images can better reflect the situation of global human activities.

[0085] The present invention uses coral bleaching weekly heat (DHW) data to indicate the situation of large-scale coral bleaching in each study area. The DHW dataset is as follows Figure 3 To remove the interference of land, the ocean boundary data is used for masking.

[0086] The night light remote sensing image in the present invention refers to the night light remote sensing image.

[0087] Based on the first embodiment of the method for assessing the ecological health of coral reefs based on human activities based on night light remote sensing sequences of the present invention, in the second embodiment of the method for assessing the ecological health of coral reefs based on human activities based on night light remote sensing sequences of the present invention, step S10 includes:

[0088] Step S11, acquiring a first night light remote sensing image of a research sea area collected by a first satellite in a first time series, wherein the first satellite is a DMSP / OLS satellite;

[0089] Step S12, obtaining a second night light remote sensing image of the research sea area collected by a second satellite in a second time series, wherein the second satellite is a VIIRS-DNB satellite;

[0090] Step S13, performing stitching processing on the first night light remote sensing image and the second night light remote sensing image to obtain a night light remote sensing image corresponding to a research time series, wherein the research time series is a union of the first time series and the second time series.

[0091] The night light remote sensing images currently available from a single satellite have obvious time limitations. The ecological health changes of coral reefs are a long process, and the changes of about ten years have obvious limitations in characterizing its ecological health status. Therefore, it is of great significance to study the impact of long-term human activities on the ecological health of coral reefs. In this embodiment, the night light remote sensing images from two satellites are used for splicing.

[0092] In the prior art, the night light remote sensing images collected by the first satellite (DMSP / OLS satellite) and the second satellite (VIIRS-DNB satellite) respectively cannot be directly spliced ​​and used. This is because the images of the two satellites have partial time overlap and there are also differences between the images of the two satellites.

[0093] Specifically, the night light remote sensing images collected by the first satellite (DMSP / OLS satellite) are only up to 2013, and the night light remote sensing images collected by the second satellite (VIIRS-DNB satellite) only provide night light remote sensing images from 2012 to the present. Therefore, the night light remote sensing images provided by the first satellite alone cannot meet the needs of coral reef ecological health research in recent years; and the night light remote sensing images provided by the second satellite alone do not cover a long enough period of time to meet the needs of long-term research. Therefore, the present invention uses the first night light remote sensing image collected by the first satellite in the first time series, and the second night light remote sensing image collected by the second satellite in the second time series, and performs time-series splicing processing on the night light remote sensing images to obtain the night light remote sensing images corresponding to the research time series, thereby significantly extending the research time series.

[0094] In the present invention, the first time series is from the start year of the study (e.g., 1992) to 2013, that is, the present invention uses the first night light remote sensing image collected by the first satellite (DMSP / OLS satellite, Defense Meteorological Satellite Program / Operational Line Scanning System) from 1992 to 2013. The DMSP / OLS satellite is a meteorological satellite operated by the United States Air Force that can capture the night lights on the Earth's surface.

[0095] The VIIRS-DNB satellite is an advanced Earth-observing satellite system jointly developed by the National Oceanic and Atmospheric Administration (NOAA) and NASA that is capable of capturing nighttime lights on the Earth's surface.

[0096] Furthermore, the present invention uses the Coral Bleaching Weekly Heat (DHW) data from 1992 to 2020 to indicate the situation of large-scale coral bleaching in each study area. The DHW dataset is as follows Figure 3 Similarly, to remove the interference of land, the ocean boundary data is used for masking.

[0097] Based on the second embodiment of the method for assessing the ecological health of coral reefs based on human activities based on night light remote sensing sequences of the present invention, in the third embodiment of the method for assessing the ecological health of coral reefs based on human activities based on night light remote sensing sequences of the present invention, step S13 includes:

[0098] Step S131, performing denoising processing on the second night light remote sensing image;

[0099] Step S132, calculating the first nighttime light total amount corresponding to each unit time in the first time series according to the first nighttime light remote sensing image;

[0100] Step S133, calculating the second nighttime light total amount corresponding to each unit time in the second time series according to the second nighttime light remote sensing image;

[0101] Step S134, obtaining the overlapping time series of the first time series and the second time series, determining the first local nighttime light total amount corresponding to the overlapping time series from the first nighttime light total amount, and determining the second local nighttime light total amount corresponding to the overlapping time series from the second nighttime light total amount;

[0102] Step S135, based on the equal relationship between the first local night light total amount and the second local night light total amount, convert the second night light total amount corresponding to the second satellite to the first night light total amount corresponding to the first satellite, so as to obtain the night light total amount corresponding to the research time series expressed by the first satellite as a night light remote sensing image.

[0103] The above unit time may be one year.

[0104] The research method consists of two parts.

[0105] First, the night light remote sensing images provided by the first satellite (DMSP / OLS satellite) are already denoised images. Therefore, it is only necessary to remove the background noise from the night light remote sensing images collected by the second satellite (VIIRS-DNB satellite). The denoised images are used to record the annual human activity intensity of all study sea areas by calculating the total night light amount (TNL). The total night light amount in the overlapping years of VIIRS-DNB and DMSP / OLS is corrected and spliced ​​into a sequence of the average luminous intensity (ALANI) of artificial light sources per square kilometer in the sea area from the start year of the study to the end year of the study (for example, 1992 to the present). At the same time, a mask is used to extract the average weekly heat value (DHW) data of each study sea area, and a DHW average value sequence from the start year of the study to the end year of the study (for example, 1992 to the present) is constructed.

[0106] Afterwards, correlation analysis and partial correlation analysis were performed on the data series of live coral coverage in each study sea area from the start year to the end year of the study (for example, 1992 to the present) with the series of the above-mentioned night light remote sensing images and the series of average weekly heat values ​​of bleaching. The correlation between the annual change of live coral coverage and the series of night light remote sensing images and the weekly heat values ​​of bleaching was obtained, as well as the correlation between the annual change of live coral coverage and the average luminous intensity (ALANI) series of artificial light sources per square kilometer in the sea area after eliminating the influence of weekly heat values ​​of bleaching.

[0107] Specifically, the first night light remote sensing image of the research sea area collected by the first satellite in the first time series refers to the first night light remote sensing image obtained by annually averaging the night light remote sensing images collected by the first satellite according to the effective pixel value (DN value) in each year of the first time series. Therefore, a corresponding first night light remote sensing image is generated for each year in the first time series, so that the first night light remote sensing images corresponding to all years in the first time series form a first night light remote sensing image sequence.

[0108] Similarly, the second night light remote sensing image of the research sea area collected by the second satellite in the second time series refers to the second night light remote sensing image obtained by annually averaging the night light remote sensing images collected by the second satellite according to the effective pixel value (DN value) in each year of the second time series. Therefore, a corresponding second night light remote sensing image is generated for each year in the second time series, so that the second night light remote sensing images corresponding to all years in the second time series form a second night light remote sensing image sequence.

[0109] We use the total nighttime light (TNL) in the study area as a parameter reflecting the human activity index in the sea area. Since the study area is all distributed in the tropics and subtropics, there is no need to consider the auroral effect of VIIRS images.

[0110] Based on the first to third embodiments of the method for assessing the ecological health of coral reefs based on human activities using night light remote sensing sequences of the present invention, in the fourth embodiment of the method for assessing the ecological health of coral reefs based on human activities using night light remote sensing sequences of the present invention, step S20 includes:

[0111] Step S21, obtaining the live coral coverage of the initial sea area corresponding to the research time series;

[0112] Step S22, obtaining sea temperature data corresponding to the research time series;

[0113] Step S23, calculating the variation sequence of live coral coverage affected by the sea temperature according to the sea temperature data;

[0114] Step S24, correcting the initial sea area live coral coverage according to the live coral coverage variation sequence affected by the sea temperature, so as to obtain the corrected sea area live coral coverage corresponding to the research time series.

[0115] Specifically, the first time series is from the research start year (the research start year in the present invention is set as needed, for example, 1992) to 2013, and the second time series is from 2012 to the research end year (the research end year in the present invention is set as needed, for example, 2024).

[0116] Based on the third embodiment of the method for assessing the ecological health of coral reefs based on human activities based on night light remote sensing sequences of the present invention, in the fifth embodiment of the method for assessing the ecological health of coral reefs based on human activities based on night light remote sensing sequences of the present invention, step S131 includes:

[0117] Step S131a, determining the highest threshold and the lowest threshold of the denoising process, and performing denoising on each second night light remote sensing image collected in the second time series.

[0118] The preprocessing process of night light remote sensing images is the image threshold denoising process. In order to eliminate the noise in the VIIRS-DNB band and weaken the diffusion effect caused by VIIRS, we need to select an appropriate threshold to process the DN value.

[0119] Based on the fifth embodiment of the method for assessing the ecological health of coral reefs based on human activities based on night light remote sensing sequences of the present invention, in the sixth embodiment of the method for assessing the ecological health of coral reefs based on human activities based on night light remote sensing sequences of the present invention, step S131a includes:

[0120] Step Sa, determine the highest threshold L m ;

[0121] Step Sb, determine the minimum threshold L t The value range of

[0122] Step Sc, select several minimum thresholds L to be tested in the value interval t ;

[0123] Step Sd, using each selected minimum threshold to be tested, respectively, to calculate the total amount of calibrated nighttime light in each sea area in the second nighttime light remote sensing image of the overlapping year of the first time series and the second time series through the following formulas (1) and (2):

[0124]

[0125] in, It represents the calibration effective pixel value of the jth grid of the i-th sea area in the second night light remote sensing image, i is the serial number of the sea area, 1≤i≤I, I is the total number of sea areas studied; DN ij Represents the effective pixel value of the jth grid in the i-th sea area in the second night light remote sensing image, 1≤j≤J, J is the number of grids in the studied sea area; Represents the total amount of calibrated nighttime light in the ith sea area in the second nighttime light remote sensing image;

[0126] Step Se, performing a significance analysis and a correlation coefficient analysis on the total amount of calibrated nighttime lights in each sea area in the second nighttime light remote sensing image, and determining the lowest threshold to be tested with the best performance as the lowest threshold;

[0127] In step Sf, the minimum threshold is used to perform denoising on each second night light remote sensing image collected in the second time series using formula (1), and the total amount of calibrated night light in each sea area in each second night light remote sensing image collected in the second time series is calculated using formula (2).

[0128] In this embodiment, Beijing, Shanghai, and Guangzhou are considered to be the three largest and most developed cities in China. Therefore, in theory, the pixel values ​​of other sea areas should not exceed the highest DN value (about 235) of the three megacities. Similarly, human activities in large water bodies such as oceans also use the highest threshold (L m =235) as the highest threshold for correcting outliers.

[0129] However, the lowest threshold value needs to be further selected through experiments. In this embodiment, the threshold value (L t ∈[0, 0.9]) are used as experimental thresholds. For example, the ten thresholds are: 0, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8 and 0.9.

[0130] I can be determined according to the total number of sea areas to be studied. In this embodiment, the study sea areas are the ten largest sea areas. Therefore, I is 10.

[0131] Since the second satellite was launched in April 2012, the second satellite lacks night light image data from January to March 2012. However, the night light remote sensing images of the first and second satellites overlap in time throughout 2013. Therefore, the following correlation analysis will only be conducted on the night light remote sensing image data of 2013.

[0132] Figure 4 It is the proportion of the total amount of light in each sea area when different minimum thresholds are selected. From this figure, we can see that when the minimum threshold is 0.3, the proportion of each sea area tends to be stable, which shows that when 0.3 is selected as the minimum threshold, the noise in the ocean area can be excluded to the maximum extent and the valid pixels can be retained.

[0133] To further confirm the selection of the minimum threshold, the present invention calculated the total night light (TNL) from the night light remote sensing data of each sea area in 2013 and then performed Pearson correlation analysis on the TNL of the same sea area in the same year calculated by the original DMSP according to the threshold [0-0.9]. Figure 5 It was found that when the minimum threshold was 0.3, the Pearson correlation coefficient between the TNL calculated by the DMSP original data and the TNL calculated by VIIRS for each sea area was the largest and the correlation was most significant.

[0134] Based on the third embodiment of the method for assessing the ecological health of coral reefs based on human activities based on night light remote sensing sequences of the present invention, in the seventh embodiment of the method for assessing the ecological health of coral reefs based on human activities based on night light remote sensing sequences of the present invention, step S135 specifically includes:

[0135]

[0136] Among them, CR i represents the conversion ratio of the ith sea area; represents the average value of the total amount of nighttime light calculated by the first satellite in the i-th sea area in the overlapping time zone of the first time series and the second time series; represents the average value of the total amount of nighttime light calculated by the second satellite in the i-th sea area in the overlapping time zone of the first time series and the second time series;

[0137]

[0138] Among them, DMSP year,i Indicates the total nighttime light of the first satellite in the i-th ocean area in the specified year in the second time series, VIIRS year,i represents the total amount of nighttime light from the second satellite in the i-th ocean area in the specified year in the second time series;

[0139] The total amount of nighttime light from the first satellite corresponding to the first time series and the total amount of nighttime light converted from the total amount of nighttime light from the second satellite corresponding to the second time series are combined as a nighttime light remote sensing image.

[0140] The overlapping time region of the first time series and the second time series includes the whole year of 2012 and part of the time range of 2013.

[0141] Based on the first embodiment of the method for assessing the ecological health of coral reefs based on human activities using night light remote sensing sequences of the present invention, in the eighth embodiment of the method for assessing the ecological health of coral reefs based on human activities using night light remote sensing sequences of the present invention, in step S30, the partial correlation coefficient of the partial correlation analysis is calculated as follows:

[0142]

[0143] Among them, r HC.D is the partial correlation coefficient between human activity intensity H and live coral cover C under the influence of controlled weekly heat D; r HC represents the correlation coefficient between the intensity of human activities and the coverage of living corals; r HD represents the correlation coefficient between human activity intensity and weekly heat; r CD Represents the correlation coefficient between coral cover and weekly temperature.

[0144] The present invention calibrates the total amount of nighttime lights and averages the area of ​​each sea area to obtain the average artificial nighttime light intensity (ALANI) per square kilometer to indicate the intensity of human activities under the nighttime light remote sensing indication of each sea area. The study sea area is masked by the maximum value of the grid effective pixel value (DN value) in the annual coral bleaching weekly heat data to obtain the annual average value of the coral bleaching weekly heat of each sea area to indicate the temperature stress suffered by the coral coverage, which is used as an environmental variable to analyze the influence of the average artificial nighttime light intensity ALANI per square kilometer on the live coral coverage under the influence of the temperature stress suffered by the live coral coverage.

[0145] In the present invention, the correlation analysis between the average artificial night light intensity (ALANI) per square kilometer and the coral coverage adopts the Spearman Rank Correlation Analysis method and the Partial Correlation Analysis method. The correlation coefficient is a non-parametric rank correlation measure used to evaluate the monotonic correlation strength between two variables. The coefficient is realized by calculating the rank of the data after sorting the data sequence, and it is insensitive to outliers, so it is more suitable for ecological analysis. Partial correlation analysis measures the linear correlation degree between two variables in multiple variables under the condition of controlling the influence of other variables, and the partial correlation coefficient is an indicator describing the degree, so it is more reasonable and reliable to use the partial correlation coefficient to describe the intrinsic connection between ecological indicators.

[0146] The present invention adopts partial correlation analysis to obtain the partial correlation between the intensity of human activities and the coral coverage in each sea area after eliminating the influence of the weekly heat of coral bleaching. In order to explore the direct relationship between the intensity of human activities H and the coral coverage C after controlling the environmental variable weekly heat D, the Spearman partial correlation analysis method is adopted.

[0147] Through the above analysis, we can obtain a result including the correlation coefficient between the average artificial night light intensity (ALANI) per square kilometer in each sea area and the coral coverage, as well as the partial correlation coefficient between ALANI and coral coverage after eliminating the influence of DHW.

[0148] In order to further analyze the phased characteristics of coral coverage changes, the present invention uses a time series analysis method to analyze the annual change rate of coral coverage, indicating the annual average speed of coral coverage decline and increase:

[0149]

[0150] Where ΔC t Indicates the relative value of year t to year C t-1 Percent change in coral cover per year, C t represents the coral cover in year t, C t-1 Represents the coral cover in year t-1. The annual change in cover is calculated by the above formula, and the stages of coral cover increase and decrease are divided according to the positive and negative changes. Specifically, when the coral cover increases, we define it as the "Coral Cover Recovery Stage (CRP)"; when the coral cover decreases, we define it as the "Coral Cover Decline Stage (CDP)".

[0151] Based on the fourth embodiment of the method for assessing the ecological health of coral reefs based on human activities based on night light remote sensing sequences of the present invention, in the ninth embodiment of the method for assessing the ecological health of coral reefs based on human activities based on night light remote sensing sequences of the present invention, the method further includes:

[0152] Step S40, calculate the standardized total amount of nighttime lights in each sea area in the following manner:

[0153]

[0154] in, represents the total amount of standardized nighttime lights for the ith sea area in a specified year; represents the minimum value of the total amount of nighttime light in the ith sea area, represents the minimum value of the total amount of nighttime light in the i-th sea area, k represents the specified year; k∈[1,n], k represents the k-th year among the n years from the start year to the end year of the study.

[0155] For example, when the starting year of the study is 1992 and the ending year of the study is 2024, there are 33 years in total, n=33.

[0156] In the period-based research, considering that the average artificial night light intensity (ALANI) per square kilometer in different sea areas is different and difficult to compare horizontally, it is necessary to standardize the calibrated total night light data. Through the above formula (6), we can calculate the standardized total night light (calibrated DMSP value) for each sea area to solve the problem of inconsistency in factors such as area in each research sea area.

[0157] The study used Spearman correlation analysis to calculate the correlation between the intensity of human activities in each sea area (using the average artificial night light intensity per square kilometer (ALANI) to express the intensity of human activities) and coral cover, and used partial correlation analysis to remove the influence of coral bleaching weekly heat (DHW) to analyze the correlation between ALANI and coral cover. The results are shown in Tables 1 and Figure 6-15 The Australian waters and the Eastern Tropical Pacific (ETP) showed a strong negative Spearman correlation between ALANI and coral cover, indicating that higher ALANI was associated with lower coral cover. Even after adjusting for the effect of DHW, the negative correlation remained strong, suggesting that human activities may be an important independent stressor for coral health in these regions.

[0158] Table 1 Correlation analysis results between coral coverage and human activity intensity in various sea areas

[0159]

[0160] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art can be embodied in the form of a software product, which is stored in a computer-readable storage medium (such as ROM / RAM, magnetic disk, optical disk) as described above, and includes a number of instructions for enabling a terminal device to enter the method described in each embodiment of the present invention.

[0161] In the description of this specification, the description with reference to the terms "an embodiment", "another embodiment", "other embodiments", or "first embodiment to Xth embodiment" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, method steps or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

[0162] It should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or system 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, article or system. In the absence of further restrictions, an element defined by the sentence "comprises a ..." does not exclude the existence of other identical elements in the process, method, article or system including the element.

[0163] The serial numbers of the above embodiments of the present invention are only for description and do not represent the advantages or disadvantages of the embodiments.

[0164] The above are only preferred embodiments of the present invention, and are not intended to limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made using the contents of the present invention specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A method for assessing the ecological health of coral reefs based on human activities based on night light remote sensing sequences, characterized in that: The steps include: Obtain night light remote sensing images of the research sea area collected by satellite in the research time series as human activity data; Obtain the corrected live coral coverage in the sea area corresponding to the research time series after removing the influence of sea temperature; Partial correlation analysis was performed on the corrected live coral coverage of the sea area and the night light remote sensing images corresponding to the study time series to determine the impact of human activities on the live coral coverage.

2. The method for assessing the ecological health of coral reefs based on human activities based on night light remote sensing sequences according to claim 1 is characterized in that: The step of obtaining the night light remote sensing images of the research sea area collected by the satellite in the research time series as human activity data includes: Acquire a first night light remote sensing image of the research sea area collected by a first satellite in a first time series, wherein the first satellite is a DMSP / OLS satellite; Acquire a second night light remote sensing image of the research sea area collected by a second satellite in a second time series, wherein the second satellite is a VIIRS-DNB satellite; The first night light remote sensing image and the second night light remote sensing image are spliced ​​to obtain a night light remote sensing image corresponding to a research time series, wherein the research time series is a union of the first time series and the second time series.

3. The method for assessing the ecological health of coral reefs based on human activities based on night light remote sensing sequences according to claim 2 is characterized in that: The step of performing splicing processing on the first night light remote sensing image and the second night light remote sensing image to obtain the night light remote sensing image corresponding to the research time series includes: De-noising the second night light remote sensing image; Calculate the total amount of light at night corresponding to each unit time in the first time series according to the first night light remote sensing image; Calculate the second night light amount corresponding to each unit time in the second time series according to the second night light remote sensing image; Obtaining the overlapping time series of the first time series and the second time series, determining the first local nighttime light total amount corresponding to the overlapping time series from the first nighttime light total amount, and determining the second local nighttime light total amount corresponding to the overlapping time series from the second nighttime light total amount; According to the equal relationship between the first local night light total amount and the second local night light total amount, the second night light total amount corresponding to the second satellite is converted to the first night light total amount corresponding to the first satellite to obtain the night light total amount corresponding to the research time series expressed by the first satellite as a night light remote sensing image.

4. The method for assessing the ecological health of coral reefs based on human activities based on night light remote sensing sequences according to claim 1, characterized in that: The step of obtaining the corrected sea area live coral coverage corresponding to the research time series after removing the influence of sea temperature comprises: Obtain the live coral coverage of the initial sea area corresponding to the research time series; Obtain the sea temperature data corresponding to the research time series; The series of changes in live coral cover affected by sea temperature was calculated based on sea temperature data; According to the change sequence of live coral coverage affected by sea temperature, the initial live coral coverage of the sea area was corrected to obtain the corrected live coral coverage of the sea area corresponding to the research time series.

5. The method for assessing the ecological health of coral reefs based on human activities based on night light remote sensing sequences according to claim 2 is characterized in that: The first time series is from the start year of the study to 2013, and the second time series is from 2012 to the end year of the study.

6. The method for assessing the ecological health of coral reefs based on human activities based on night light remote sensing sequences according to claim 3 is characterized in that: The step of denoising the second night light remote sensing image comprises: The highest threshold and the lowest threshold of the denoising process are determined, and the denoising process is performed on each second night light remote sensing image collected in the second time series.

7. The method for assessing the ecological health of coral reefs based on human activities based on night light remote sensing sequences according to claim 6 is characterized in that: Determine the highest threshold and the lowest threshold of the denoising process, and perform denoising on each second night light remote sensing image collected in the second time series, as follows: Determine the highest threshold L m ; Determine the minimum threshold L t The value range of Select several minimum thresholds L to be tested in the value range t ; For each selected minimum threshold to be tested, the total amount of calibrated nighttime light in each sea area in the second nighttime light remote sensing image of the overlapping year of the first time series and the second time series is calculated using the following formulas (1) and (2): in, It represents the calibration effective pixel value of the jth grid of the i-th sea area in the second night light remote sensing image, i is the serial number of the sea area, 1≤i≤I, I is the total number of sea areas studied; DN ij Represents the effective pixel value of the jth grid in the i-th sea area in the second night light remote sensing image, 1≤j≤J, J is the number of grids in the studied sea area; Represents the total amount of calibrated nighttime light in the ith sea area in the second nighttime light remote sensing image; Conduct significance analysis and correlation coefficient analysis on the total amount of calibrated nighttime lights in each sea area in the second nighttime light remote sensing image, and determine the lowest threshold to be tested with the best performance as the lowest threshold; The lowest threshold is adopted and formula (1) is used to perform denoising on each second night light remote sensing image collected in the second time series. Formula (2) is used to calculate the total amount of calibrated night light in each sea area in each second night light remote sensing image collected in the second time series.

8. The method for assessing the ecological health of coral reefs based on human activities based on night light remote sensing sequences according to claim 3 is characterized in that: The step of converting the second total amount of nighttime light corresponding to the second satellite to the first total amount of nighttime light corresponding to the first satellite according to the equal relationship between the first local total amount of nighttime light and the second local total amount of nighttime light, so as to obtain the total amount of nighttime light corresponding to the research time series expressed by the first satellite as the nighttime light remote sensing image, specifically includes: Among them, CR i represents the conversion ratio of the ith sea area; represents the average value of the total amount of nighttime light calculated by the first satellite in the i-th sea area in the overlapping time zone of the first time series and the second time series; represents the average value of the total amount of nighttime light calculated by the second satellite in the i-th sea area in the overlapping time zone of the first time series and the second time series; in, Indicates the total nighttime light of the first satellite in the i-th ocean area in the specified year in the second time series, VIIRS year,i represents the total amount of nighttime light from the second satellite in the i-th ocean area in the specified year in the second time series; The total amount of nighttime light from the first satellite corresponding to the first time series and the total amount of nighttime light converted from the total amount of nighttime light from the second satellite corresponding to the second time series are combined as a nighttime light remote sensing image.

9. The method for assessing the ecological health of coral reefs based on human activities based on night light remote sensing sequences according to claim 1, characterized in that: In the step of performing partial correlation analysis on the corrected marine live coral coverage and night light remote sensing images corresponding to the research time series to determine the impact of human activities on the live coral coverage, the partial correlation coefficient of the partial correlation analysis is calculated as follows: Among them, r HC.D is the partial correlation coefficient between human activity intensity H and live coral cover C under the influence of controlled weekly heat D; r HC represents the correlation coefficient between the intensity of human activities and the coverage of living corals; r HD represents the correlation coefficient between human activity intensity and weekly heat; r CD Represents the correlation coefficient between coral cover and weekly temperature.

10. The method for assessing the ecological health of coral reefs based on human activities based on night light remote sensing sequences according to claim 4, characterized in that: The method further comprises: The standardized total amount of nighttime lights in each sea area is calculated as follows: in, represents the total amount of standardized nighttime lights for the ith sea area in a specified year; represents the minimum value of the total amount of nighttime light in the ith sea area, represents the minimum value of the total amount of nighttime lights in the i-th sea area, k represents the specified year; k∈[1,n], k represents the k-th year among the n years from the start year to the end year of the study.

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