Natural resource ecological protection and restoration engineering monitoring method

Abstract

The invention relates to the technical field of artificial intelligence, and discloses a natural resource ecological protection and restoration engineering monitoring method, which comprises the following steps: acquiring image data of an ecological region, and generating an environment change index of the ecological region according to the image data and a preset environment change index generation algorithm; generating an environment change type of the ecological region according to the environment change index; generating a species community and an ecological niche of the ecological region according to pre-acquired species data; generating a biological change index of the ecological region according to the species community and the ecological niche; and generating a monitoring report of the ecological region according to the environmental change type and the biological change index, and performing ecological protection and ecological restoration on the ecological region according to the monitoring report. According to the invention, the efficiency of natural resource ecological protection and restoration engineering monitoring can be improved.

Description

Technical Field

[0001] The present invention relates to the field of artificial intelligence technology, and in particular to a natural resource ecological protection and restoration engineering monitoring method. Background Art

[0002] As global climate change and ecological and environmental problems become increasingly severe, ecological protection and restoration projects are facing increasing pressure. In recent years, ecological restoration projects have been vigorously promoted, such as returning farmland to forest, returning pasture to grassland, and wetland restoration projects, but there are still many problems in the monitoring of these projects.

[0003] For example, the ecological restoration effect in some places is difficult to quantify, the restoration progress is unclear, or there are blind spots in the restoration process that cannot be corrected in time. In addition, due to imperfect monitoring technology, some projects cannot accurately assess the actual status of ecological resources, thus affecting the effectiveness of ecological protection. Therefore, improving the monitoring efficiency of natural resource ecological protection and restoration projects will not only help to ensure the smooth implementation of restoration measures, but also be crucial to achieving the ecological goals of sustainable development. Summary of the invention

[0004] The present invention provides a natural resource ecological protection and restoration project monitoring method, the main purpose of which is to solve the problem of low efficiency in natural resource ecological protection and restoration project monitoring.

[0005] To achieve the above-mentioned purpose, the present invention provides a natural resource ecological protection and restoration project monitoring method, comprising: Collect image data of the ecological region, and generate an environmental change index of the ecological region according to the image data and a preset environmental change index generation algorithm, wherein the preset environmental change index generation algorithm is: ; in, is the environmental change index of the ecoregion, is the land surface temperature of the ecoregion in question, is the vegetation coverage index of the ecoregion, is the Normalized Difference Vegetation Index for the ecoregion in question, is the weight coefficient of the interaction term, is the weight coefficient of the quadratic term, is the weight coefficient of each component of the environmental change index; generating an environmental change type of the ecological region according to the environmental change index; generating species communities and ecological niches of the ecoregion based on previously acquired species data; generating a biotic variation index for the ecoregion based on the species community and the ecological niche; A monitoring report of the ecological region is generated according to the environmental change type and the biological change index, and ecological protection and ecological restoration are carried out on the ecological region according to the monitoring report.

[0006] Optionally, generating the environmental change index of the ecological region according to the image data and a preset environmental change index generation algorithm includes: Performing data preprocessing on the image data to obtain preprocessed data of the image data; generating a normalized difference vegetation index for the ecoregion based on the preprocessed data; Generating a vegetation coverage index of the ecological region according to the normalized difference vegetation index; generating a land surface temperature of the eco-region based on the preprocessed data; The environmental change index of the ecological region is generated according to the normalized difference vegetation index, the vegetation coverage index, the land surface temperature and a preset environmental change index generation algorithm.

[0007] Optionally, generating a normalized difference vegetation index of the ecological region according to the preprocessed data includes: Extracting near infrared band data and red band data from the preprocessed data; The normalized difference vegetation index of the ecological region is generated according to the near-infrared band data, the red band data and a preset normalized difference vegetation index algorithm, wherein the preset normalized difference vegetation index algorithm is: ; in, is the Normalized Difference Vegetation Index for the ecoregion in question, represents the reflectivity in the near-infrared band data. Represents the reflectance in the red band data.

[0008] Optionally, generating the vegetation coverage index of the ecological region according to the normalized difference vegetation index includes: The vegetation coverage index of the ecological region is generated according to the normalized difference vegetation index and a preset vegetation coverage algorithm, wherein the preset vegetation coverage algorithm is: ; in, is the vegetation coverage index of the ecoregion, is the Normalized Difference Vegetation Index for the ecoregion in question, is the Normalized Difference Vegetation Index of bare land in the ecoregion, It is the normalized difference vegetation index of the fully vegetated area in the ecoregion.

[0009] Optionally, generating the land surface temperature of the ecological region according to the preprocessed data includes: Extracting the radiation brightness data from the preprocessed data, and performing data correction on the radiation brightness data using preset atmospheric parameters to obtain corrected data of the radiation brightness data; The land surface temperature of the ecological region is generated according to the correction data and a preset land surface temperature algorithm, wherein the preset land surface temperature algorithm is: ; in, is the land surface temperature of the ecoregion in question, is the correction data, is the wavelength of the thermal infrared band, is Planck's constant, is the emissivity of the surface.

[0010] Optionally, generating the environmental change type of the ecological region according to the environmental change index includes: Determining a numerical range of the environmental change index; The environmental change type of the ecological region is generated according to the preset environmental type and the numerical range, wherein the environmental change type is stable, aggravated, mitigated and restored.

[0011] Optionally, generating the species community of the ecological region according to the pre-acquired species data includes: Extracting distribution characteristics of species in the ecological region based on pre-acquired species data; Performing pattern analysis on the ecological region according to the distribution characteristics to obtain a distribution pattern of the ecological region; The species community of the ecological region is generated according to the distribution pattern, wherein the species community includes: forest community, grassland community, wetland community and desert community.

[0012] Optionally, generating the ecological niche of the ecological region according to the pre-acquired species data includes: generating demand characteristics of species in the ecological region based on previously acquired species data; The interrelationships among the species are obtained, and the ecological niche of the ecological region is generated according to the demand characteristics and the interrelationships.

[0013] Optionally, generating the biological variation index of the ecological region according to the species community and the ecological niche includes: Quantifying the species community to obtain a quantitative value of the species community; Establishing a correlation relationship between the quantitative value and the ecological niche; A biological variation index of the ecological region is generated according to the association relationship, the quantitative value and the ecological niche.

[0014] Optionally, the performing data preprocessing on the image data to obtain preprocessed data of the image data includes: De-noising the image data, and performing radiation correction on the image data after the data denoising to obtain primary correction data of the ecological area; The primary correction data is geometrically corrected to obtain preprocessed data of the ecological region.

[0015] The present invention can calculate the environmental changes of the ecological region by collecting image data of the ecological region and using a preset environmental change index generation algorithm, can reflect the dynamic changes of the ecological environment in real time, can also detect environmental deterioration or restoration progress in time, generate species communities and ecological niches of the ecological region according to species data, can help more accurately evaluate the biodiversity and stability of the ecosystem, reduce the workload of manual investigation and analysis, and through the generation of biological change index, can quantify the changes of biological populations in the ecological region, provide data support for ecological protection and restoration, make ecological restoration measures more targeted and effective, avoid the errors and lags that may be caused by over-reliance on manual evaluation, and after generating a monitoring report, can help managers identify problem areas faster, and directly guide subsequent ecological protection and restoration work according to the data, reduce the complexity of manual analysis, can make the decision process more timely and accurate, and improve the scientific nature of decision-making. Therefore, the present invention proposes a natural resource ecological protection and restoration project monitoring method, which can solve the problem of low efficiency of natural resource ecological protection and restoration project monitoring. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 A schematic flow chart of a natural resource ecological protection and restoration engineering monitoring method provided in accordance with an embodiment of the present invention.

[0017] The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0018] 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.

[0019] The embodiment of the present application provides a natural resource ecological protection and restoration project monitoring method. The execution subject of the natural resource ecological protection and restoration project monitoring method includes but is not limited to at least one of the electronic devices such as a server and a terminal that can be configured to execute the method provided in the embodiment of the present application. In other words, the natural resource ecological protection and restoration project monitoring method can be executed by software or hardware installed on a terminal device or a server device. The server includes but is not limited to: a single server, a server cluster, a cloud server or a cloud server cluster, etc. The server can be an independent server, or it can be a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services and artificial intelligence platforms.

[0020] Reference Figure 1 FIG. 1 is a flow chart of a natural resource ecological protection and restoration project monitoring method provided by an embodiment of the present invention. In this embodiment, the natural resource ecological protection and restoration project monitoring method includes: S1. Collect image data of an ecological region, and generate an environmental change index of the ecological region according to the image data and a preset environmental change index generation algorithm.

[0021] In the embodiment of the present invention, the collecting of image data of the ecological area includes: selecting a collection platform and determining a collection frequency of the image data.

[0022] In detail, the ecological regions refer to natural resource ecological regions that need to be protected and restored and natural resource ecological regions that have been initially protected and restored.

[0023] In detail, image data collection is a key step in obtaining information such as environmental changes and species distribution within ecological regions. Image data can be collected through a variety of technical means, including remote sensing satellite images, drone photography, and ground photography.

[0024] In detail, the collection platform includes but is not limited to: remote sensing satellites, drones and ground photography, wherein the remote sensing satellites can provide large-scale, high-resolution images of the earth's surface, which are suitable for ecological monitoring of large areas; the drones can provide lower-altitude, high-definition images, which are suitable for high-precision data collection in local areas, especially in difficult-to-reach or smaller ecological areas; the ground photography refers to the use of ground-based shooting equipment to obtain image data of local areas, which is usually used for close-range species monitoring and habitat status analysis.

[0025] Furthermore, multiple types of image data can be obtained through the acquisition platform, including but not limited to: optical images, infrared images, radar images and multispectral images, among which optical images can be data related to landscape features, vegetation coverage, land use types, etc. Infrared images are mainly used to monitor regional temperature changes, humidity changes and the behavior of nocturnal animals; multispectral images are used to analyze environmental characteristics such as vegetation health and soil moisture through different bands (such as red, blue, near infrared, etc.); radar images are used to penetrate clouds, monitor ground subsidence, water changes, etc.

[0026] Specifically, the frequency of image acquisition is set according to the rate of change of the ecological region. For example, in some rapidly changing areas, more frequent image acquisition may be required (such as once a month); in areas with stable ecological environment, a lower acquisition frequency (such as once a quarter) can be set.

[0027] At the same time, since changes in ecological regions may be seasonal, the collection time should take into account seasonal influences, such as changes in the four seasons of spring, summer, autumn and winter.

[0028] Furthermore, satellite remote sensing (such as Landsat, Sentinel, etc.), drone aerial images or high-resolution aerial images are used to ensure that the images cover the target ecological area and have a sufficient time span (multi-temporal data) to monitor ecological changes.

[0029] In an embodiment of the present invention, generating the environmental change index of the ecological region according to the image data and a preset environmental change index generation algorithm includes: De-noising the image data, and performing radiation correction on the image data after the data denoising to obtain primary correction data of the ecological area; Performing geometric correction on the primary correction data to obtain pre-processed data of the ecological region; generating a normalized difference vegetation index for the ecoregion based on the preprocessed data; Generating a vegetation coverage index of the ecological region according to the normalized difference vegetation index; generating a land surface temperature of the eco-region based on the preprocessed data; The environmental change index of the ecological region is generated according to the normalized difference vegetation index, the vegetation coverage index, the land surface temperature and a preset environmental change index generation algorithm.

[0030] In detail, image data denoising refers to the removal of random noise caused by sensors, weather and other factors, such as cloud effects and image blur, when processing remote sensing images, to ensure the clarity of image data; image data radiation correction refers to the correction of image data to eliminate radiation differences in image data from different sensors or at different time points to ensure the accuracy of the data.

[0031] Furthermore, radiometric correction refers to processing the radiometric deviation of images so that images from different time periods or different sensors can be compared.

[0032] In detail, the preset environmental change index generation algorithm is: ; in, is the environmental change index of the ecoregion, is the land surface temperature of the ecoregion in question, is the vegetation coverage index of the ecoregion, is the Normalized Difference Vegetation Index for the ecoregion in question, is the weight coefficient of the interaction term, is the weight coefficient of the quadratic term, It is the weight coefficient of each component of the environmental change index.

[0033] In detail, the weight coefficient of the interaction term represents the interaction effect between different parameters; the weight coefficient of the quadratic term is used to capture the nonlinear relationship of the parameters.

[0034] In detail, the environmental change index of the ecological region is calculated by combining parameters such as the normalized difference vegetation index (NDVI), fractional vegetation cover index (FVC), and land surface temperature (LST) with a preset algorithm. The index is used to quantitatively describe the changing trend of the ecological environment. The preset algorithm calculates the environmental change index by combining multiple environmental parameters (NDVI, FVC, and LST) with different weight coefficients.

[0035] In detail, generating the normalized difference vegetation index of the ecological region according to the preprocessed data includes: Extracting near infrared band data and red band data from the preprocessed data; The normalized difference vegetation index of the ecological region is generated according to the near-infrared band data, the red band data and a preset normalized difference vegetation index algorithm, wherein the preset normalized difference vegetation index algorithm is: ; in, is the Normalized Difference Vegetation Index for the ecoregion in question, represents the reflectivity in the near-infrared band data. Represents the reflectance in the red band data.

[0036] In detail, for NDVI, the red and near-infrared band data at different time points are used to calculate the NDVI value to determine the change in vegetation coverage.

[0037] In detail, NDVI is calculated using red band and near-infrared band data to measure the coverage of surface vegetation. Its value range is usually between -1 and 1, with high values ​​indicating dense vegetation and low values ​​indicating non-vegetation covered areas such as bare soil or water bodies.

[0038] In detail, generating the vegetation coverage index of the ecological region according to the normalized difference vegetation index includes: The vegetation coverage index of the ecological region is generated according to the normalized difference vegetation index and a preset vegetation coverage algorithm, wherein the preset vegetation coverage algorithm is: ; in, is the vegetation coverage index of the ecoregion, is the Normalized Difference Vegetation Index for the ecoregion in question, is the Normalized Difference Vegetation Index of bare land in the ecoregion, It is the normalized difference vegetation index of the fully vegetated area in the ecoregion.

[0039] In detail, the fractional vegetation cover index (FVC) reflects the degree of vegetation coverage in a certain area, and the larger the value, the more vegetation coverage. The index is calculated based on the NDVI value, combining the NDVI values ​​of bare land and complete vegetation cover.

[0040] In detail, the pixel binary model based on NDVI assumes that the pixel consists of two parts: bare land and vegetation covered land. The vegetation coverage is the proportion of the green vegetation part in the pixel area. Since NDVI is calculated from the spectral information of the ground objects received by the remote sensing sensor, it can reflect the surface coverage. Therefore, the pixel NDVI value can be expressed as a weighted combination of the spectral information contributed by the bare soil part and the spectral information contributed by the green vegetation part. Among them, NDVI is the normalized vegetation index value of the pixel. is the bare soil NDVI value, is the NDVI value of the area with complete vegetation coverage.

[0041] Further, It should be the NDVI value of pure vegetation pixels, usually close to 1; It is the NDVI value of pure bare soil pixel, which is usually close to 0.

[0042] Furthermore, due to the influence of various factors such as climate, temperature, and topography, and There will be spatial variations, so it is necessary to select reasonable maximum and minimum values ​​within a given confidence interval. Usually, the vegetation index pixel values ​​are mainly concentrated between 5% and 95%. The model confidence level can be set to 95% and determined through repeated comparative analysis. and The distribution of vegetation coverage can be calculated by using the numerical value of

[0043] In detail, generating the land surface temperature of the ecological region according to the preprocessed data includes: Extracting the radiation brightness data from the preprocessed data, and performing data correction on the radiation brightness data using preset atmospheric parameters to obtain corrected data of the radiation brightness data; The land surface temperature of the ecological region is generated according to the correction data and a preset land surface temperature algorithm, wherein the preset land surface temperature algorithm is: ; in, is the land surface temperature of the ecoregion in question, is the correction data, is the wavelength of the thermal infrared band, is Planck's constant, is the emissivity of the surface.

[0044] In detail, the pre-processed data is generated based on commonly used remote sensing data sources, including Landsat series satellites (such as Landsat 8), MODIS (Moderate Resolution Imaging Spectroradiometer), etc. These satellites can provide observation data in the thermal infrared band.

[0045] Furthermore, the calculation of LST is mainly based on the radiation brightness of the satellite thermal infrared band (usually the thermal infrared band). LST represents the actual temperature of the surface and is usually calculated using the thermal infrared band data in remote sensing images. LST is an important indicator for studying surface thermal characteristics, climate change, etc.

[0046] In detail, the radiance is affected by the atmosphere, so atmospheric correction is needed to eliminate atmospheric interference, especially the influence of substances such as water vapor and carbon dioxide. The data can be corrected using preset atmospheric parameters (such as temperature, humidity, air pressure, etc.).

[0047] Furthermore, the calculation of LST also needs to take into account the emissivity of the surface, because the emissivity of different surface cover types is different, for example, the emissivity of water bodies, deserts, vegetation, and urban surfaces are all different.

[0048] S2. Generate the environmental change type of the ecological region according to the environmental change index.

[0049] In the embodiment of the present invention, generating the environmental change type of the ecological region according to the environmental change index includes: Determining a numerical range of the environmental change index; The environmental change type of the ecological region is generated according to the preset environmental type and the numerical range, wherein the environmental change type is stable, aggravated, mitigated and restored.

[0050] In detail, the environmental change index is a quantitative indicator used to describe the degree of environmental change in an ecoregion, and the generated ECI value is usually within a certain numerical range. In order to effectively classify the type of environmental change, it is necessary to first determine the numerical range of the index.

[0051] For example, the environmental change index may be between 0 and 1, or have a wider range, and the appropriate numerical range can be set according to the characteristics of different ecological regions.

[0052] In detail, the preset environmental types are defined based on existing ecological theories or experimental data. They usually describe different trends and states of ecological environmental changes. By combining with the numerical range of the Environmental Change Index (ECI), the environmental changes in ecological regions can be classified into different types.

[0053] In detail, stable environmental change means that when the environmental change index is within the normal fluctuation range, it means that the environmental change in the ecological region is small and maintains the expected ecological state; intensified environmental change means that when the environmental change index increases significantly, it means that the ecological region is facing greater environmental pressure or mutation, which may be due to extreme weather events, climate change or the impact of human activities; mitigation environmental change means that when the environmental change index shows a downward trend, it means that the environmental change in the ecological region tends to slow down, which may be due to environmental protection measures, natural recovery or other factors; recovery environmental change means that when the environmental change index shows a restorative change, it means that the environment of the ecological region is recovering in a stable direction after experiencing major changes.

[0054] Furthermore, in order to map the Environmental Change Index (ECI) to different types of change, it is usually necessary to classify them according to a preset standard value range. The following is a possible classification method (the specific values ​​are adjusted according to actual data or research standards): Stable: When the ECI value is within a certain range, it means that the environmental change is minimal and the ecosystem is in a stable state. For example: 0 ≤ ECI ≤ 0.2.

[0055] Aggravated: A high ECI value indicates severe environmental degradation or deterioration. This may be due to overexploitation, pollution, etc. Usually the ECI value is close to the upper limit of its range. For example: 0.8 < ECI ≤ 1.0.

[0056] Mitigation: The ECI value is moderate, indicating that the trend of environmental degradation has slowed down or eased. It usually indicates that environmental change has shown a certain degree of positive transformation. For example: 0.5 < ECI ≤ 0.8.

[0057] Restoration: A low ECI value indicates that the environment is gradually recovering, possibly due to the implementation of restoration or protection measures. For example: 0.2 < ECI ≤ 0.5.

[0058] Assume that the environmental change index calculated for a certain ecological region at different time points or under different conditions is as follows: Time point 1: ECI = 0.15 (stable) Time point 2: ECI = 0.85 (extreme) Time point 3: ECI = 0.65 (slowed down) Time point 4: ECI = 0.40 (recovery type) According to this numerical range and the division of change types, the environmental index values ​​in different time periods or different regions can be classified into the above four types of changes.

[0059] S3. Generate species communities and ecological niches of the ecological region based on pre-acquired species data.

[0060] In an embodiment of the present invention, generating the species community of the ecological region according to the pre-acquired species data includes: Extracting distribution characteristics of species in the ecological region based on pre-acquired species data; Performing pattern analysis on the ecological region according to the distribution characteristics to obtain a distribution pattern of the ecological region; The species community of the ecological region is generated according to the distribution pattern, wherein the species community includes: forest community, grassland community, wetland community and desert community.

[0061] In detail, the pre-acquired species data include information on the types, distribution, quantity, habitat characteristics, etc. of various organisms such as plants, animals, and microorganisms. The data acquisition methods may include field surveys, remote sensing monitoring, drone scanning, and sensor collection of existing biodiversity databases.

[0062] In detail, extracting the distribution characteristics of species in the ecological region based on the pre-acquired species data refers to obtaining species data within a certain range, which may include information such as the name, quantity, distribution location, habitat, and climate conditions of the species. By analyzing these data, the distribution characteristics of species in the ecological region can be extracted. For example, spatial distribution characteristics, temporal distribution characteristics, and environmental association characteristics. Extracting these distribution characteristics helps to understand the spatial layout of species in the ecological region and their adaptability to the environment.

[0063] Furthermore, the distribution patterns of different species within ecological regions can be analyzed to identify the habitat preferences of species. For example, some species may prefer humid areas, while others prefer arid or alpine environments.

[0064] In detail, the ecological region is subjected to pattern analysis according to the distribution characteristics to obtain the distribution pattern of the ecological region, and the species are divided into different community types. Common community types may include: forest community, grassland community, wetland community and desert community, wherein the forest community includes a variety of trees, shrubs, ground cover plants, etc., the grassland community includes herbaceous plants, some small animals, etc., the wetland community includes wetland plants, aquatic organisms, etc., adapted to the wetland environment, and the desert community is adapted to the plant and animal communities in arid and desert areas.

[0065] In an embodiment of the present invention, generating the ecological niche of the ecological region according to the pre-acquired species data includes: generating demand characteristics of species in the ecological region based on previously acquired species data; The interrelationships among the species are obtained, and the ecological niche of the ecological region is generated according to the demand characteristics and the interrelationships.

[0066] In detail, the demand characteristics include the environmental conditions, resource types and other ecological factors required by the species during its growth, reproduction and survival, including: space requirements, climate requirements, resource requirements and growth cycle requirements.

[0067] In detail, ecological niche refers to the "functional role" of a species in an ecosystem, including the species' resource utilization patterns, spatial distribution, and relationships with other species. The ecological niche of each species is defined by its position and function in the environment, involving the characteristics and patterns of resource utilization (such as food, water, habitat, etc.).

[0068] In addition, it is also necessary to consider the interactions between species and other species, such as predation, competition, symbiosis, etc. Obtaining these interactions between species helps to analyze how species affect each other's ecological niches and living conditions through these interactions.

[0069] Furthermore, the ecological niche refers not only to the role and position of a species in an ecosystem, but also to its demand for resources, its interaction with other species, and its ability to adapt to the environment. According to the characteristics of each species' needs, it is matched with the environmental conditions of the ecological region to determine its suitable habitat range and resource requirements. The relationship between species (such as competition, predation, symbiosis, etc.) will affect the niche of species within the ecological region. For example, if two species compete for the same resources, their niches may overlap, resulting in a reduction in the living space of one of the species. On the contrary, if there is a symbiotic relationship between species, their niches may complement each other and form a more stable community.

[0070] S4. Generate a biological change index for the ecological region based on the species community and the ecological niche.

[0071] In an embodiment of the present invention, generating the biological change index of the ecological region according to the species community and the ecological niche includes: Quantifying the species community to obtain a quantitative value of the species community; Establishing a correlation relationship between the quantitative value and the ecological niche; A biological variation index of the ecological region is generated according to the association relationship, the quantitative value and the ecological niche.

[0072] Specifically, species communities need to be quantified. A species community is a collection of species that grow and live together in a certain ecological region. The purpose of quantification is to convert these biological groups into numerical indicators for further analysis and comparison.

[0073] Suppose there are five species of plants (A, B, C, D, E) in a forest area. Quantification may consider the following: record the population of each plant (for example, A has 200 plants, B has 150 plants, C has 100 plants, D has 50 plants, and E has 30 plants); calculate the relative biomass of each plant (for example, A accounts for 40% of the biomass, B accounts for 30%, C accounts for 15%, D accounts for 10%, and E accounts for 5%). Through these quantitative data, the quantitative value of the species community is obtained.

[0074] In detail, the ecological niche of each species is associated with its quantitative value in the community based on the ecological requirements of each species (such as temperature, humidity, light, etc.) and the quantitative data of the species community. For example, the ecological niche of species A may require a warm and humid environment, while species B is adapted to dry areas. These ecological characteristics can be combined with quantitative values ​​such as relative density and species richness of species to establish associations through regression analysis or other statistical methods.

[0075] Assume that plant A is adapted to a humid environment and plant B is adapted to a dry environment. According to the results of the quantitative processing, the number of plant A is higher in the humid season, while the number of plant B is higher in the dry season. Through association analysis, the change pattern of species communities between the humid and dry seasons can be obtained.

[0076] Furthermore, by combining the quantitative values ​​with the ecological niche relationship, the biological change index is calculated to reflect the biodiversity, species changes and ecological health status of the ecological region.

[0077] Suppose that in a certain ecological region, the following data is obtained through quantitative processing: the number of a species community increases from 500 to 600 within a year. The niche analysis shows that the habitat requirements of the species in the wet season are very suitable. The environmental conditions have changed, which may promote the increase in the number of species. Based on the correlation between these quantitative data and the niche, the biological change index can be obtained, such as: If the biomass of all species in the area has generally increased over time, the Biotic Change Index may indicate that the ecoregion is in good health and the ecosystem is tending towards stability.

[0078] If the index reflects species loss or overgrowth, it may indicate that the ecosystem is out of balance and biodiversity is threatened.

[0079] S5. Generate a monitoring report of the ecological region according to the environmental change type and the biological change index, and perform ecological protection and ecological restoration on the ecological region according to the monitoring report.

[0080] In an embodiment of the present invention, the monitoring report of the ecological region is generated according to the environmental change type and the biological change index, including: judging whether the ecosystem of the region is deteriorating or whether certain protection measures or natural recovery forces are taking effect according to the environmental change type and the biological change index; and evaluating key indicators such as the risk of species loss and changes in species richness of the ecological region according to changes in the biological change index to obtain a monitoring report.

[0081] In an embodiment of the present invention, the ecological protection and ecological restoration of the ecological region according to the monitoring report includes: pointing out the current health status of the ecological region according to the results of the monitoring report, and providing early warning of possible ecological crises (such as ecological degradation, species extinction, etc.).

[0082] In detail, ecological protection measures include: protecting key species, restoring ecological functions, and preventing the invasion of alien species. Among them, protecting key species means taking measures to protect endangered or important species based on the loss or reduction of species in the monitoring report. For example, establishing protected areas, restricting fishing, and implementing species ex situ protection. Restoring ecological functions means that if the monitoring report shows that certain ecological functions (such as water purification, carbon storage, etc.) are threatened, these ecological functions can be restored by increasing vegetation cover, restoring wetlands, etc. Preventing the invasion of alien species means identifying invasive species in monitoring reports and taking measures to prevent or control the spread of alien species, such as setting up isolation zones, weeding, or species migration.

[0083] In detail, ecological restoration measures include: taking targeted restoration measures according to the type of environmental change analyzed in the report. For example, if soil degradation is serious, soil improvement and vegetation restoration can be implemented; if water pollution is serious, water purification and wetland restoration can be carried out; according to the recovery capacity of the ecosystem and the biological change index, ecological engineering measures are taken, such as restoring native vegetation, repairing river or lake ecosystems, and increasing biological habitats; combined with the ecological function analysis of the monitoring report, targeted ecological function reconstruction is carried out. For example, if a certain area lacks important water purification functions, the water purification function can be restored by repairing wetlands or planting aquatic plants.

[0084] The present invention can calculate the environmental changes of the ecological region by collecting image data of the ecological region and using a preset environmental change index generation algorithm, can reflect the dynamic changes of the ecological environment in real time, can also detect environmental deterioration or restoration progress in time, generate species communities and ecological niches of the ecological region according to species data, can help more accurately evaluate the biodiversity and stability of the ecosystem, reduce the workload of manual investigation and analysis, and through the generation of biological change index, can quantify the changes of biological populations in the ecological region, provide data support for ecological protection and restoration, make ecological restoration measures more targeted and effective, avoid the errors and lags that may be caused by over-reliance on manual evaluation, and after generating a monitoring report, can help managers identify problem areas faster, and directly guide subsequent ecological protection and restoration work according to the data, reduce the complexity of manual analysis, can make the decision process more timely and accurate, and improve the scientific nature of decision-making. Therefore, the present invention proposes a natural resource ecological protection and restoration project monitoring method, which can solve the problem of low efficiency of natural resource ecological protection and restoration project monitoring.

[0085] It is obvious to those skilled in the art that the present invention is not limited to the details of the above exemplary embodiments, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0086] The embodiments of the present application can acquire and process relevant data based on artificial intelligence technology. Artificial Intelligence (AI) is the theory, method and technology of using digital computers or machines controlled by digital computers to simulate, extend and expand human intelligence, perceive the environment, acquire knowledge and use knowledge to obtain the best results.

[0087] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solution of the present invention can be modified or replaced by equivalents without departing from the spirit and scope of the technical solution of the present invention.

Claims

1. A natural resource ecological protection and restoration project monitoring method, characterized in that: The method comprises: Collect image data of the ecological region, and generate an environmental change index of the ecological region according to the image data and a preset environmental change index generation algorithm, wherein the preset environmental change index generation algorithm is: ； in, is the environmental change index of the ecoregion, is the land surface temperature of the ecoregion in question, is the vegetation coverage index of the ecoregion, is the Normalized Difference Vegetation Index for the ecoregion in question, is the weight coefficient of the interaction term, is the weight coefficient of the quadratic term, is the weight coefficient of each component of the environmental change index; generating an environmental change type of the ecological region according to the environmental change index; generating species communities and ecological niches of the ecoregion based on previously acquired species data; generating a biotic variation index for the ecoregion based on the species community and the ecological niche; A monitoring report of the ecological region is generated according to the environmental change type and the biological change index, and ecological protection and ecological restoration are carried out on the ecological region according to the monitoring report.

2. The natural resource ecological protection and restoration project monitoring method according to claim 1, characterized in that: The step of generating the environmental change index of the ecological region according to the image data and a preset environmental change index generation algorithm includes: Performing data preprocessing on the image data to obtain preprocessed data of the image data; generating a normalized difference vegetation index for the ecoregion based on the preprocessed data; Generating a vegetation coverage index of the ecological region according to the normalized difference vegetation index; generating a land surface temperature of the eco-region based on the preprocessed data; The environmental change index of the ecological region is generated according to the normalized difference vegetation index, the vegetation coverage index, the land surface temperature and a preset environmental change index generation algorithm.

3. The natural resource ecological protection and restoration project monitoring method according to claim 2, characterized in that: Generating the normalized difference vegetation index of the ecological region according to the preprocessed data includes: Extracting near infrared band data and red band data from the preprocessed data; The normalized difference vegetation index of the ecological region is generated according to the near-infrared band data, the red band data and a preset normalized difference vegetation index algorithm, wherein the preset normalized difference vegetation index algorithm is: ； in, is the Normalized Difference Vegetation Index for the ecoregion in question, represents the reflectivity in the near-infrared band data. Represents the reflectance in the red band data.

4. The natural resource ecological protection and restoration project monitoring method according to claim 2, characterized in that: Generating the vegetation coverage index of the ecological region according to the normalized difference vegetation index includes: The vegetation coverage index of the ecological region is generated according to the normalized difference vegetation index and a preset vegetation coverage algorithm, wherein the preset vegetation coverage algorithm is: ； in, is the vegetation coverage index of the ecoregion, is the Normalized Difference Vegetation Index for the ecoregion in question, is the Normalized Difference Vegetation Index of bare land in the ecoregion, It is the normalized difference vegetation index of the fully vegetated area in the ecoregion.

5. The natural resource ecological protection and restoration project monitoring method according to claim 2, characterized in that: Generating the land surface temperature of the ecological region according to the preprocessed data includes: Extracting the radiation brightness data from the preprocessed data, and performing data correction on the radiation brightness data using preset atmospheric parameters to obtain corrected data of the radiation brightness data; The land surface temperature of the ecological region is generated according to the correction data and a preset land surface temperature algorithm, wherein the preset land surface temperature algorithm is: ； in, is the land surface temperature of the ecoregion in question, is the correction data, is the wavelength of the thermal infrared band, is Planck's constant, is the emissivity of the surface.

6. The natural resource ecological protection and restoration project monitoring method according to claim 1, characterized in that: Generating the environmental change type of the ecological region according to the environmental change index includes: Determining a numerical range of the environmental change index; The environmental change type of the ecological region is generated according to the preset environmental type and the numerical range, wherein the environmental change type is stable, aggravated, mitigated and restored.

7. The natural resource ecological protection and restoration project monitoring method according to claim 1, characterized in that: Generating the species community of the ecological region according to the pre-acquired species data includes: Extracting distribution characteristics of species in the ecological region based on pre-acquired species data; Performing pattern analysis on the ecological region according to the distribution characteristics to obtain a distribution pattern of the ecological region; The species community of the ecological region is generated according to the distribution pattern, wherein the species community includes: forest community, grassland community, wetland community and desert community.

8. The natural resource ecological protection and restoration project monitoring method according to claim 1, characterized in that: Generating the ecological niche of the ecological region according to the pre-acquired species data includes: generating demand characteristics of species in the ecological region based on previously acquired species data; The interrelationships among the species are obtained, and the ecological niche of the ecological region is generated according to the demand characteristics and the interrelationships.

9. The natural resource ecological protection and restoration project monitoring method according to any one of claims 1 to 8, characterized in that: The step of generating the biological variation index of the ecological region according to the species community and the ecological niche comprises: Quantifying the species community to obtain a quantitative value of the species community; Establishing a correlation relationship between the quantitative value and the ecological niche; A biological variation index of the ecological region is generated according to the association relationship, the quantitative value and the ecological niche.

10. The natural resource ecological protection and restoration project monitoring method according to claim 2, characterized in that: The performing data preprocessing on the image data to obtain preprocessed data of the image data includes: De-noising the image data, and performing radiation correction on the image data after the data denoising to obtain primary correction data of the ecological area; The primary correction data is geometrically corrected to obtain preprocessed data of the ecological region.

Images