Ecological restoration prediction and disturbance restoration method for ecologically sensitive and fragile area in power grid construction

Abstract

The invention relates to the technical field of ecological restoration, and provides an ecological restoration prediction and disturbance restoration method for an ecologically sensitive and fragile area in power grid construction. A remote sensing image of the ecological sensitive fragile area is obtained, a first area with the real-time NDVI value lower than a preset NDVI value and a second area of the disturbed slash are determined, and the second area belongs to the first area; the first area and the second area are subjected to ecological environment detection, ecological detection data are determined, and the ecological detection data comprise vegetation distribution data and soil property state data; according to the vegetation distribution data, a first ecological package is configured, and the first ecological package is used for vegetation restoration; according to the soil property state data, a second ecological package is configured, and the second ecological package is used for soil property improvement; an ecological package configuration network based on ecological restoration prediction is built, and the ecological package configuration network comprises a vegetation restoration configuration layer, a soil improvement configuration layer and a restoration prediction layer.

Description

Technical Field

[0001] The present invention relates to the technical field of ecological restoration, and in particular to a method for ecological restoration prediction and disturbance restoration of ecologically sensitive and fragile areas in power grid construction. Background Art

[0002] At present, vegetation restoration in ecologically sensitive and fragile areas of power grids faces multiple challenges and difficult conditions. Problems such as soil barrenness, acidification, and insufficient nutrients have limited vegetation growth; the species composition and ecological functions of the sites disturbed by line engineering are incomplete, making it impossible to effectively maintain water and soil and achieve ecosystem restoration; and it is difficult to restore vegetation on steep slopes with inconvenient terrain. In the face of these difficult conditions, scientific microhabitat transformation and vegetation restoration technologies are needed to solve them in order to improve soil fertility, improve soil salinity, increase organic matter content, prevent wind erosion and soil erosion, and protect soil nutrient supply and quality, thereby promoting vegetation growth and ecosystem restoration. These problems have affected the growth of vegetation and the realization of ecological functions in ecologically sensitive and fragile areas of power grids, and have posed challenges to the requirements of environmental protection and engineering soil and water conservation.

[0003] After the completion of large-scale linear engineering projects, their destructive effects on the environment are significant, causing damage to the natural landscape, reduction of biodiversity, and severe fragmentation of animal and plant habitats. At the same time, they may also trigger and aggravate geological disasters and other problems. In order to meet these challenges, vegetation restoration has become a key measure for ecological restoration of power grid projects. This technology aims to stabilize easily eroded soils through the implementation of a series of engineering and plant measures, promote the restoration of stability and a virtuous cycle of the ecosystems through which the power grid passes, and reactivate their natural purification capabilities.

[0004] In the traditional power grid construction process, in order to meet the needs of large-scale construction machinery and material stacking, it is often necessary to cut down and clear the surface vegetation of forests or other ecosystems to open up vast exposed plots. Although the greening rate of the construction site can reach 80% to 90% through vegetation restoration efforts in the later stage of the project, this cannot rebuild a healthy ecosystem. Its structure is single, its functions are damaged, and the degree of ecological damage is far-reaching.

[0005] In recent years, the concept of natural restoration of ecosystems has emerged as a forward-looking ecological restoration concept. Under the guidance of this concept, the positive role of local species in long-term plant succession is utilized, and they can effectively "decompose invasive disasters". By introducing native plant species, it helps the rapid recovery of the structure and function of damaged ecosystems, so that they can return to their natural state before the disturbance as quickly as possible. However, its ecological restoration effect is unpredictable, and different restoration strategies cannot be used for different regions for personalized restoration. Summary of the invention

[0006] The present invention proposes an ecological restoration prediction and disturbance recovery method for ecologically sensitive and fragile areas in power grid construction, which is used to solve the problem that the effects of existing ecological restoration schemes cannot be predicted and different restoration strategies cannot be used for different areas for personalized restoration.

[0007] The present invention proposes a method for ecological restoration prediction and disturbance restoration in ecologically sensitive and fragile areas during power grid construction, comprising:

[0008] Acquire remote sensing images of ecologically sensitive and fragile areas, determine a first area where the real-time NDVI value is lower than a preset NDVI value and a second area of ​​the disturbance trace, wherein the second area belongs to the first area;

[0009] Performing ecological environment detection on the first area and the second area to determine ecological detection data, wherein the ecological detection data includes vegetation distribution data and soil quality status data;

[0010] According to the vegetation distribution data, a first ecological package is configured, wherein the first ecological package is used for vegetation restoration;

[0011] According to the soil state data, a second ecological package is configured, wherein the second ecological package is used for improving the soil quality;

[0012] Build an ecological package configuration network based on ecological restoration prediction, where the ecological package configuration network includes a vegetation restoration configuration layer, a soil improvement configuration layer, and a restoration prediction layer;

[0013] Inputting the ecological detection data of the first area into the ecological package configuration network, making an ecological restoration prediction, and determining a first ecological restoration strategy;

[0014] Inputting the ecological detection data of the second area into the ecological package configuration network, making ecological restoration predictions, and determining a second ecological restoration strategy;

[0015] The ecological detection data of the first area and the second area are input into the ecological package configuration network to make ecological restoration predictions and determine the third ecological restoration strategy.

[0016] Furthermore, the acquisition of remote sensing images of ecologically sensitive and fragile areas also includes:

[0017] Mark the power grid distribution in the geographic image data in advance to determine the power grid distribution information; the power grid distribution information includes power station distribution information, substation distribution information, distribution network center distribution information, transmission line path information, and distribution transformer distribution information;

[0018] Determine the first ecological detection area according to the power grid distribution information;

[0019] Obtain satellite remote sensing images of the first ecological detection area within a monitoring period and conduct an initial ecological assessment, wherein the monitoring period includes an ecological restoration period, and the ecological restoration period is not less than an iteration period of vegetation in the corresponding ecological detection area; the initial ecological assessment includes vegetation coverage assessment and vegetation coverage increase rate assessment;

[0020] Based on the initial ecological assessment, the second ecologically sensitive and vulnerable areas where the vegetation coverage is in a poor recovery state are identified; the poor recovery state includes: no recovery state, reduced vegetation coverage state and easy invasion state of vegetation coverage;

[0021] Based on the second ecologically sensitive and fragile area, the ecological conditions are marked and different types of ecologically sensitive and fragile areas are determined.

[0022] Further, the determining the first area where the real-time NDVI value is lower than the preset NDVI value includes:

[0023] Pre-set NDVI thresholds;

[0024] Extract spectral remote sensing data of ecologically sensitive and vulnerable areas in high temporal resolution periods;

[0025] Calculate NDVI using spectral remote sensing data to determine the target NDVI value;

[0026] Compare the target NDVI value with the NDVI threshold, generate a binary image, and mark the NDVI value comparison;

[0027] By comparing the marks, the temporal and spatial distribution of the area with low NDVI values ​​is determined and marked as the first area.

[0028] Furthermore, the second region is confirmed by the following steps:

[0029] Extracting image features on the first area and determining whether there are disturbance features; wherein the disturbance features are project trace features existing during the construction of the transmission line;

[0030] When disturbance characteristics exist, the corresponding ecologically sensitive and fragile area will be marked as the second area.

[0031] Furthermore, the ecological environment detection of the first area and the second area includes:

[0032] performing an ecological information extraction operation on the first region and the second region;

[0033] The ecological information extraction operation includes a vegetation distribution information extraction operation and a soil quality state detection information extraction operation, and both the vegetation distribution information extraction operation and the soil quality state detection information extraction operation include N detection sub-items;

[0034] The vegetation distribution information extraction operation performs feature extraction based on remote sensing images of the first area and the second area;

[0035] The soil quality state detection information extraction operation is used to perform experimental detection and extraction of soil quality data in vegetation distribution information where the vegetation coverage is lower than the target coverage;

[0036] According to the ecological information extraction operation, the vegetation distribution information and soil condition information of the first area and the second area are marked in turn to determine the ecological detection data.

[0037] Furthermore, configuring the first ecological package according to the vegetation distribution data includes:

[0038] Determine a vegetation growth plan corresponding to the restoration of vegetation coverage rate based on vegetation distribution data; wherein the vegetation growth plan includes a vegetation green manure plan and a vegetation distribution control plan, and the vegetation distribution data includes: vegetation sparseness data and vegetation type distribution data;

[0039] According to the vegetation growth plan, determining the first component parameter of the first ecological package;

[0040] Obtaining component ratio data required by the first ecological package based on the first component parameter, wherein the component ratio data includes: seed ratio, nutrient ratio and fertilizer ratio;

[0041] Among them, the component ratio data include: determining the nutrient ratio and fertilizer ratio based on vegetation sparseness data; determining the seed ratio based on vegetation type distribution data.

[0042] Furthermore, configuring the second ecological package according to the soil state data includes:

[0043] Obtain soil quality data, including organic matter data, microbial data, trace element data, and soil physical structure data;

[0044] According to the vegetation distribution data, determine the soil conditions corresponding to different vegetation distribution areas and generate regional soil data sets;

[0045] According to the regional soil data set, determine the second component parameters of the second ecological package corresponding to the regional needs;

[0046] Determine whether there are undesirable components in the second component parameters that conflict with the vegetation in the corresponding area;

[0047] After removing the bad components in the first component parameters, the configuration ratio of the second ecological package is generated.

[0048] Furthermore, the construction of an ecological package configuration network based on ecological restoration prediction includes:

[0049] Set vegetation related items and soil improvement items in sequence;

[0050] According to the vegetation related items, the vegetation gain assessment model is set to form the vegetation restoration configuration layer;

[0051] According to the soil improvement items, a soil improvement assessment model is set up to form a soil improvement configuration layer;

[0052] Setting a first evaluation index for the vegetation restoration configuration layer, a second evaluation index for the soil quality improvement configuration layer, and a third evaluation index for simultaneously improving vegetation and soil quality;

[0053] Generate a recovery prediction layer according to the first evaluation index, the second evaluation index and the third evaluation index;

[0054] Furthermore, the construction of an ecological package configuration network based on ecological restoration prediction includes:

[0055] Determine ecological demand items for ecological restoration according to the first area and the second area; wherein the ecological demand items include N ecological restoration sub-goals;

[0056] According to the ecological requirements, determine the configurable first ecological package and second ecological package;

[0057] According to the ecological restoration sub-goals, determine the composition parameters of the first ecological package and the second ecological package;

[0058] The component parameters of the first ecological package and the second ecological package, as well as the vegetation distribution and soil state data of the first area and the second area are input into the ecological package configuration network to determine the ecological package configuration data.

[0059] The beneficial effects of the present invention are:

[0060] The present invention obtains remote sensing images and calculates real-time NDVI (normalized difference vegetation index) values, and the scheme can quickly identify the first area with poor vegetation conditions and the disturbed second area in the ecologically sensitive and fragile area. This real-time monitoring helps to find problem areas in time and take corresponding measures. Ecological detection data (including vegetation distribution data and soil state data) provide a quantitative assessment for ecological restoration. These data are the basis for scientifically configuring ecological packages and formulating restoration strategies, ensuring the pertinence and effectiveness of restoration work. According to the vegetation distribution data and soil state data, the first ecological package and the second ecological package are configured respectively, which can provide personalized solutions for specific problems in different regions (such as vegetation loss or soil degradation) and improve restoration efficiency; the constructed ecological package configuration network includes a vegetation restoration configuration layer, a soil improvement configuration layer and a restoration prediction layer. This hierarchical structure helps to systematically deal with complex ecological restoration problems and ensure that measures at all levels can be effectively implemented; through the ecological package configuration network, ecological restoration prediction can be carried out, and ecological restoration strategies can be determined for the first area, the second area and the combined area of ​​the two. This predictive method can plan restoration work in advance, reduce blindness, and improve the success rate of restoration. The formulation of the first, second and third ecological restoration strategies takes into account the specific conditions of different regions, achieving full coverage from single issues to comprehensive issues, which helps to achieve the overall recovery and long-term stability of the ecosystem.

[0061] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures particularly pointed out in the written description and the accompanying drawings.

[0062] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0063] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0064] Figure 1 A method flow chart of an ecological restoration prediction and disturbance restoration method for ecologically sensitive and fragile areas in power grid construction in an embodiment of the present invention;

[0065] Figure 2 A flowchart of remote sensing image processing of ecologically sensitive and fragile areas in an embodiment of the present invention;

[0066] Figure 3 The present invention is a flowchart of constructing an ecological package configuration network in an embodiment of the present invention. DETAILED DESCRIPTION

[0067] The preferred embodiments of the present invention are described below in conjunction with the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0068] like Figure 1 As shown, this embodiment provides a method for ecological restoration prediction and disturbance restoration in ecologically sensitive and fragile areas during power grid construction, including:

[0069] Acquire remote sensing images of ecologically sensitive and fragile areas, determine a first area where the real-time NDVI value is lower than a preset NDVI value and a second area of ​​the disturbance trace, wherein the second area belongs to the first area;

[0070] Performing ecological environment detection on the first area and the second area to determine ecological detection data, wherein the ecological detection data includes vegetation distribution data and soil quality status data;

[0071] According to the vegetation distribution data, a first ecological package is configured, wherein the first ecological package is used for vegetation restoration;

[0072] According to the soil state data, a second ecological package is configured, wherein the second ecological package is used for improving the soil quality;

[0073] Build an ecological package configuration network based on ecological restoration prediction, where the ecological package configuration network includes a vegetation restoration configuration layer, a soil improvement configuration layer, and a restoration prediction layer;

[0074] Inputting the ecological detection data of the first area into the ecological package configuration network, making an ecological restoration prediction, and determining a first ecological restoration strategy;

[0075] Inputting the ecological detection data of the second area into the ecological package configuration network, making ecological restoration predictions, and determining a second ecological restoration strategy;

[0076] The ecological detection data of the first area and the second area are input into the ecological package configuration network to make ecological restoration predictions and determine the third ecological restoration strategy.

[0077] The principle of the above technical solution is:

[0078] In the specific implementation process, firstly, remote sensing images of ecologically sensitive and vulnerable areas of the power grid are obtained through satellites, disturbance traces are identified on the remote sensing images, and image data of the area is obtained. In the specific identification of geographical features, two areas are determined according to the preset value of the real-time NDVI value. The first area is the area where the real-time NDVI value is lower than the preset NDVI value, and the second area is classified as the first area. This is because the second area is actually the disturbance trace generated by the first area. The NDVI value is the normalized vegetation index value, which is an index used for remote sensing image analysis. It quantifies vegetation coverage and growth vitality by measuring the difference between the reflectance of the near-infrared band and the red band.

[0079] In terms of ecological environment detection and determining ecological detection data, ecological environment detection will be carried out in these two areas. The process of ecological environment detection includes obtaining soil samples and conducting biological analysis on the samples to obtain ecological detection data. In actual implementation, field sampling and laboratory testing are required. The detected data includes vegetation distribution data and soil quality status data. Vegetation distribution data can be provided to the vegetation restoration configuration layer of the ecological package configuration network to help configure the corresponding vegetation. The soil quality status data determines how to configure the ecological package for soil improvement.

[0080] After configuring the vegetation and soil improvement eco-package, an eco-package configuration network based on ecological restoration prediction is built through the ecosystem process model (in actual implementation, the BIOME-BGC model and the CENTURY model are preferred. The BIOME-BGC model is a biosphere-biogeochemistry model used to simulate the cycle of carbon, nitrogen and water in the ecosystem, and is trained with the eco-package; the CENTURY model is a model that simulates the long-term soil carbon dynamics of grassland and farmland ecosystems. When the present invention is implemented, it is improved to a model that simulates ecosystems such as forests, and is also trained with eco-package samples). The ecological package configuration network includes three layers, namely the vegetation restoration configuration layer, the soil improvement configuration layer and the restoration prediction layer. The ecological package configuration network is used to carry out targeted ecological restoration predictions for different regions.

[0081] Finally, the ecological detection data of the first and second areas are obtained and input into the ecological package configuration network to make ecological restoration predictions. The ecological restoration strategy of each area is determined, and the strategy information is output for use in vegetation planting or soil improvement, generating specific ecological restoration strategies and targeted ecological protection measures.

[0082] Finally, the ecological detection data of the first and second areas are input into the ecological package configuration network again to perform ecological restoration prediction. The ecological restoration prediction can determine the third ecological restoration strategy and identify possible ecological problems. Then, when faced with ecological problems, corresponding protection measures are generated.

[0083] The beneficial effects of the above technical solution are:

[0084] The present invention can quickly identify the first area with poor vegetation conditions and the disturbed second area in the ecologically sensitive and fragile area by acquiring remote sensing images and calculating real-time NDVI (normalized difference vegetation index) values. This real-time monitoring helps to find problem areas in time and take corresponding measures. Ecological detection data (including vegetation distribution data and soil state data) provide a quantitative assessment for ecological restoration. Scientific configuration of ecological packages and formulation of restoration strategies ensure the pertinence and effectiveness of restoration work. According to the vegetation distribution data and soil state data, the first ecological package and the second ecological package are configured respectively, which can provide personalized solutions for specific problems in different regions (such as vegetation loss or soil degradation) and improve restoration efficiency; the constructed ecological package configuration network includes a vegetation restoration configuration layer, a soil improvement configuration layer and a restoration prediction layer. This hierarchical structure helps to systematically deal with complex ecological restoration problems and ensure that measures at all levels can be effectively implemented; through the ecological package configuration network, ecological restoration prediction can be carried out, and ecological restoration strategies can be determined for the first area, the second area and the combined area of ​​the two. This predictive method can plan restoration work in advance, reduce blindness, and improve the success rate of restoration. The formulation of the first, second and third ecological restoration strategies takes into account the specific conditions of different regions and achieves full coverage from single issues to comprehensive issues, thereby assisting the overall recovery and long-term stability of the ecosystem.

[0085] As an embodiment of the present invention: Figure 2 As shown, the acquisition of remote sensing images of ecologically sensitive and fragile areas also includes:

[0086] Mark the power grid distribution in the geographic image data in advance to determine the power grid distribution information; the power grid distribution information includes power station distribution information, substation distribution information, distribution network center distribution information, transmission line path information, and distribution transformer distribution information;

[0087] Determine the first ecological detection area according to the power grid distribution information;

[0088] Obtain satellite remote sensing images of the first ecological detection area within a monitoring period and conduct an initial ecological assessment, wherein the monitoring period includes an ecological restoration period, and the ecological restoration period is not less than an iteration period of vegetation in the corresponding ecological detection area; the initial ecological assessment includes vegetation coverage assessment and vegetation coverage increase rate assessment;

[0089] Based on the initial ecological assessment, the second ecologically sensitive and vulnerable areas where the vegetation coverage is in a poor recovery state are identified; the poor recovery state includes: no recovery state, reduced vegetation coverage state and easy invasion state of vegetation coverage;

[0090] Based on the second ecologically sensitive and fragile area, the ecological conditions are marked and different types of ecologically sensitive and fragile areas are determined.

[0091] The principle of the above technical solution is:

[0092] In the specific implementation, the grid distribution information is pre-marked in the geographic image data to mark the grid distribution in the ecological improvement area, for example: including 1 power station, 3 substations, 5 distribution network centers, 10 transmission line paths and several distribution transformers. The first ecological detection area is determined based on the grid distribution information, and the range is the area within 500 meters on both sides of the transmission line. Acquiring remote sensing images and initial ecological assessments is to obtain satellite remote sensing images of the first ecological detection area within an ecological restoration cycle (assuming 1 year). The remote sensing images are analyzed to obtain the initial ecological assessment results: for example: the vegetation coverage rate is 60%, and the vegetation coverage increase rate is 5%. The second ecologically sensitive and fragile area is determined based on the initial ecological assessment results. For example: it is found that the vegetation coverage rate on both sides of a certain section of the transmission line is less than 50%, and the vegetation coverage increase rate is less than 3%, which is determined to be a poor recovery state. The area is determined as the second ecologically sensitive and fragile area. The ecological status labeling is to label the ecological status of the second ecologically sensitive and fragile area, which is divided into three categories: areas with no recovery, areas with reduced vegetation coverage, and areas with easily invaded vegetation coverage.

[0093] The beneficial effects of the above technical solution are:

[0094] The present invention monitors the ecological environment around the power grid in a targeted manner to improve the ecological protection effect. Through remote sensing technology, large-scale, rapid and efficient ecological monitoring is achieved to reduce manpower and material costs. Based on the vegetation coverage rate and increase rate, the ecological restoration status is scientifically evaluated to provide a basis for subsequent ecological governance.

[0095] As an embodiment of the present invention, the step of determining the first area where the real-time NDVI value is lower than the preset NDVI value includes:

[0096] Pre-set NDVI thresholds;

[0097] Extract spectral remote sensing data of ecologically sensitive and vulnerable areas in high temporal resolution periods;

[0098] Calculate NDVI using spectral remote sensing data to determine the target NDVI value;

[0099] Compare the target NDVI value with the NDVI threshold, generate a binary image, and mark the NDVI value comparison;

[0100] By comparing the marks, the temporal and spatial distribution of the area with low NDVI values ​​is determined and marked as the first area.

[0101] The principle of the above technical solution is:

[0102] In the actual implementation process, the NDVI threshold is set in advance to determine the ecologically sensitive and fragile areas. The threshold is set to ensure that the calculation results have a certain stability, because only when the NDVI value is significantly lower than the preset threshold will it be identified as an ecologically sensitive and fragile area.

[0103] Extract spectral remote sensing data of ecologically sensitive and fragile areas in high temporal resolution periods. It uses remote sensing technology to obtain data from corresponding areas from different time periods. NDVI calculation uses red and near-infrared band data to calculate NDVI values. NDVI is an indicator of vegetation growth status and vegetation coverage. Usually in ecologically sensitive and fragile areas, NDVI values ​​are positively correlated with vegetation biomass, leaf area index (LAI), etc. In high-temporal resolution remote sensing data, periodic changes in vegetation can be observed, such as the beginning, peak, and end of the growing season. Therefore, in ecologically sensitive and fragile areas, as vegetation grows, NDVI values ​​usually rise, showing a positive correlation.

[0104] Then the spectral remote sensing data is subjected to NDVI calculation to determine the target NDVI value, that is, the remote sensing data is mathematically processed to calculate the NDVI value of each pixel.

[0105] The target NDVI value is compared with the NDVI threshold to generate a binary image, and the NDVI value comparison mark is performed, which is to convert the NDVI value into a binary image and then generate a comparison mark by comparison.

[0106] By comparing the marks, the temporal and spatial distribution of the area with low NDVI values ​​is determined and marked as the first area. This is to determine the area with low NDVI values ​​based on the results of the comparison marks and mark it as the first area.

[0107] The beneficial effects of the above technical solution are:

[0108] The present invention determines the power grid distribution area with poor ecological environment through the above NDVI value, and marks it as the first area, and performs regional division and regional identification in space and geographic information. Through the identification of the first area, it is also possible to exclude areas belonging to the power grid area but with good ecological environment, and accurately determine the area of ​​ecological restoration.

[0109] As an embodiment of the present invention, the second area is confirmed by the following steps:

[0110] Extracting image features on the first area and determining whether there are disturbance features; wherein the disturbance features are project trace features existing during the construction of the transmission line;

[0111] When disturbance characteristics exist, the corresponding ecologically sensitive and fragile area will be marked as the second area.

[0112] The principle of the above technical solution is:

[0113] In the specific implementation process, the image features on the first area are extracted, and it is determined whether there are disturbance features. The disturbance traces can be divided according to the image features to achieve the division of the first area and the second area. If there are obvious interference features in the first area, it means that there is environmental interference in the area, which is also the premise for the division of the second area.

[0114] If disturbance features exist in the first area, the corresponding first area will be marked as the second area. The disturbance features can accurately distinguish various areas and determine the areas that need ecological restoration prediction and disturbance restoration work.

[0115] The beneficial effects of the above technical solution are:

[0116] The present invention can determine the sensitive and fragile area that needs ecological restoration in the first area, thereby realizing the precise positioning of ecological restoration.

[0117] As an embodiment of the present invention: the ecological environment detection of the first area and the second area includes:

[0118] performing an ecological information extraction operation on the first region and the second region;

[0119] The ecological information extraction operation includes a vegetation distribution information extraction operation and a soil quality state detection information extraction operation, and both the vegetation distribution information extraction operation and the soil quality state detection information extraction operation include N detection sub-items;

[0120] The vegetation distribution information extraction operation performs feature extraction based on remote sensing images of the first area and the second area;

[0121] The soil quality state detection information extraction operation is used to perform experimental detection and extraction of soil quality data in vegetation distribution information where the vegetation coverage is lower than the target coverage;

[0122] According to the ecological information extraction operation, the vegetation distribution information and soil condition information of the first area and the second area are marked in turn to determine the ecological detection data.

[0123] The principle of the above technical solution is:

[0124] In a specific implementation, the ecological information extraction operation includes: performing the ecological information extraction operation on the first area and the second area. The ecological information extraction operation includes the following N detection items:

[0125] Vegetation distribution information extraction operations (N=5) include: a. Vegetation type identification b. Vegetation coverage calculation c. Vegetation density analysis d. Vegetation health assessment e. Vegetation growth trend analysis;

[0126] The soil state detection information extraction operation (N=3) includes: a. soil moisture detection b. soil erosion degree assessment c. soil fertility analysis;

[0127] Feature extraction includes: based on the remote sensing images of the first area and the second area, using machine learning and image processing technology to extract features. For example, by analyzing the spectral features, texture features, and geometric features of the remote sensing images, the vegetation type can be identified and the vegetation coverage can be calculated.

[0128] Soil quality detection includes: for soil quality data with vegetation coverage lower than the target coverage (e.g. 50%) in vegetation distribution information, experimental detection and extraction is performed. This may include field sampling and laboratory analysis to obtain data such as soil moisture, erosion degree and fertility.

[0129] Marking the ecological detection data includes: marking the vegetation distribution information and soil state information of the first area and the second area in sequence according to the result of the ecological information extraction operation to form an ecological detection data set. For example, it may be marked that the vegetation coverage rate of a certain area is 40%, the soil moisture is medium, and the soil erosion degree is mild.

[0130] The beneficial effects of the above technical solution are:

[0131] The present invention can comprehensively understand the ecological status of a region through multiple detection items. Remote sensing technology can quickly cover a large area and improve detection efficiency. Regular ecological detection can be carried out to help monitor the progress of ecological restoration and provide data support for sustainable ecological management.

[0132] As an embodiment of the present invention: configuring the first ecological package according to the vegetation distribution data includes:

[0133] Determine a vegetation growth plan corresponding to the restoration of vegetation coverage rate based on vegetation distribution data; wherein the vegetation growth plan includes a vegetation green manure plan and a vegetation distribution control plan, and the vegetation distribution data includes: vegetation sparseness data and vegetation type distribution data;

[0134] According to the vegetation growth plan, determining the first component parameter of the first ecological package;

[0135] Obtaining component ratio data required by the first ecological package based on the first component parameter, wherein the component ratio data includes: seed ratio, nutrient ratio and fertilizer ratio;

[0136] Among them, the component ratio data include: determining the nutrient ratio and fertilizer ratio based on vegetation sparseness data; determining the seed ratio based on vegetation type distribution data.

[0137] The principle of the above technical solution is:

[0138] In the specific implementation process, a plant growth plan corresponding to the restoration of vegetation coverage will be formulated based on the vegetation distribution data. The plant growth plan includes two sub-plans, namely the plant green fertilizer plan and the plant distribution management plan. The plant green fertilizer plan will include a series of plant fertilizer formulas to provide the required nutrients during the plant growth process. The plant distribution management plan includes a series of management measures to ensure that plants can grow healthily and form a stable ecosystem.

[0139] Secondly, the first parameter in the first ecological package needs to be determined according to the formulated plant growth plan. The first parameter will be the main factor affecting the entire ecosystem, which will determine the speed of plant growth and the choice of plant species.

[0140] Then, it is necessary to obtain the proportion data of various plant ingredients required by the first ecological package based on the first parameter. The proportion data in the ingredients include seed proportion, nutrient proportion and fertilizer proportion. The proportion of ingredients is calculated based on the plant distribution data and plant sparsity data. For example, if it is found that the plant sparseness in a certain area is high, then the proportion of fertilizer may need to be increased to promote plant growth. On the contrary, if the plant sparseness is low, then the proportion of nutrients may need to be increased to support plant growth. Similarly, if there are specific plant species in a certain area, the proportion of ingredients should be adjusted accordingly to ensure that these plants can grow healthily in the area.

[0141] Finally, the specific amount of each ingredient needs to be determined. This is achieved by conducting a detailed survey of each area. For example, if it is found that the plant sparseness in a certain area is high, more fertilizer is used to promote the growth of plants. At the same time, it is also necessary to pay attention to the nutritional needs of the plants and promote the healthy growth of plants according to the nutritional needs. According to the specific situation, a plant growth and management plan that is most suitable for the area is formulated.

[0142] The beneficial effects of the above technical solution are:

[0143] When configuring eco-packages, Bungma can set them according to the vegetation sparseness and vegetation species distribution, and reasonably set the component proportions based on the most important components in the eco-package, to assist the ecological restoration area in achieving an eco-package configuration plan that better meets its environmental and ecological needs.

[0144] As an embodiment of the present invention: configuring the second ecological package according to the soil state data includes:

[0145] Obtain soil quality data, including organic matter data, microbial data, trace element data, and soil physical structure data;

[0146] According to the vegetation distribution data, determine the soil conditions corresponding to different vegetation distribution areas and generate regional soil data sets;

[0147] According to the regional soil data set, determine the second component parameters of the second ecological package corresponding to the regional needs;

[0148] Determine whether there are undesirable components in the second component parameters that conflict with the vegetation in the corresponding area;

[0149] After removing the bad components in the first component parameters, the configuration ratio of the second ecological package is generated.

[0150] The principle of the above technical solution is:

[0151] In the specific implementation process, the soil conditions corresponding to different vegetation distribution areas are determined based on the plant distribution data. The soil conditions can be obtained through field surveys of various areas or historical data and experimental data. For example, it is found that the plant sparseness in some areas is high, indicating that the soil may be relatively poor and lack sufficient organic matter. It is found that other areas may have too much salt or alkali, or the soil is too acidic, which may have an adverse effect on plant growth.

[0152] Next, based on the regional soil data set, the second component parameters of the second ecological package required for the corresponding area can be determined. The second component parameters will be an important factor affecting plant growth, which will determine whether the plant can grow healthily in the current environment. For example, if the soil salinity in a certain area is found to be too high, it may be necessary to reduce the use of fertilizers to prevent the plant from absorbing too much salt and causing growth stunting.

[0153] Then, it is necessary to check whether there are any undesirable components in the second parameter that conflict with the vegetation in the corresponding area. If so, these undesirable components need to be removed to avoid their negative impact on plant growth.

[0154] Finally, according to the processed parameters, the configuration ratio of the second ecological package can be generated. The configuration ratio determines the growth of plants in different areas. In actual implementation, these ratios are regularly fine-tuned according to actual conditions to ensure the healthy growth of plants.

[0155] The beneficial effects of the above technical solution are:

[0156] The second eco-bag of the present invention is used to analyze the soil quality and remove undesirable components in the eco-bag, so that the second eco-bag is more in line with the soil quality.

[0157] As an embodiment of the present invention: Figure 3 As shown, the construction of an ecological package configuration network based on ecological restoration prediction includes:

[0158] Set vegetation related items and soil improvement items in sequence;

[0159] According to the vegetation related items, the vegetation gain assessment model is set to form the vegetation restoration configuration layer;

[0160] According to the soil improvement items, a soil improvement assessment model is set up to form a soil improvement configuration layer;

[0161] Setting a first evaluation index for the vegetation restoration configuration layer, a second evaluation index for the soil quality improvement configuration layer, and a third evaluation index for simultaneously improving vegetation and soil quality;

[0162] A restoration prediction layer is generated according to the first evaluation index, the second evaluation index, and the third evaluation index.

[0163] The principle of the above technical solution is:

[0164] In the specific implementation, it is necessary to build an ecological package configuration network based on ecological restoration prediction. The ecological package configuration network consists of three layers, namely vegetation association items, soil improvement items and ecological restoration configuration layer.

[0165] At the level of vegetation related items, a vegetation gain assessment model is set up to evaluate the growth and restoration effect of plants. The gain assessment model includes multiple evaluation indicators such as plant growth rate and vegetation coverage.

[0166] Next, at the soil improvement project level, a soil improvement evaluation model was set up to evaluate the effectiveness of soil improvement measures. The soil improvement evaluation model includes multiple evaluation indicators such as soil fertility and water retention capacity.

[0167] Then, at the ecological restoration configuration level, the results of the above two models were integrated to obtain a comprehensive evaluation index, which reflects the comprehensive effects of plant growth and soil improvement measures.

[0168] Finally, when generating the restoration prediction layer, the first, second and third evaluation indicators are combined to obtain the final ecological restoration prediction results to provide decision-making and improvement and optimization of restoration plans for ecological restoration work.

[0169] The beneficial effects of the above technical solution are:

[0170] The present invention configures a network through an ecological package to conduct a comprehensive evaluation of vegetation restoration and soil quality improvement, judge the results of soil improvement, and make an expected judgment on ecological restoration.

[0171] As an embodiment of the present invention: the construction of an ecological package configuration network based on ecological restoration prediction includes:

[0172] Determine ecological demand items for ecological restoration according to the first area and the second area; wherein the ecological demand items include N ecological restoration sub-goals;

[0173] According to the ecological requirements, determine the configurable first ecological package and second ecological package;

[0174] According to the ecological restoration sub-goals, determine the composition parameters of the first ecological package and the second ecological package;

[0175] The component parameters of the first ecological package and the second ecological package, as well as the vegetation distribution and soil state data of the first area and the second area are input into the ecological package configuration network to determine the ecological package configuration data.

[0176] The principle of the above technical solution is:

[0177] In the specific implementation process, it is necessary to determine the goals and priorities of ecological restoration according to the ecological demand items of different areas (first area and second area). The ecological demand items are used as the requirements for formulating the ecological package configuration strategy to determine which specific ecological restoration measures need to be taken and the priority of these measures.

[0178] Then, according to the determined ecological demand items, the configurable first ecological package and the second ecological package are determined respectively. The two ecological packages will be the tools ultimately used for ecological restoration work.

[0179] Next, it is necessary to determine the composition parameters of each ecological package according to different ecological restoration sub-goals. The composition parameters include the proportions and ratios of seeds, nutrients, fertilizers and other substances, which will directly affect the effect of ecological restoration.

[0180] Finally, the component parameters of the first and second eco-packages, as well as the vegetation distribution and soil state data of the first and second regions, are input into the pre-built eco-package configuration network. The eco-package configuration network calculates the adaptability and effectiveness of each eco-package configuration data, thereby providing the best eco-package configuration recommendation.

[0181] The beneficial effects of the above technical solution are:

[0182] The present invention can predict ecological restoration through an ecological package configuration network and formulate the most reasonable suggestions and plans for ecological restoration.

[0183] As an embodiment of the present invention: the ecological package configuration network determines the ecological restoration strategy through the following steps:

[0184] According to the restoration attribute of the ecological data in the ecological detection data, the first ecological package and the second ecological package are divided into matching schemes of corresponding attributes, so that the ecological package configuration network can simulate the execution result of the matching scheme; and / or,

[0185] According to the loading ratio scheme input by the user, the forecast data of the loading ratio scheme is determined.

[0186] The principle of the above technical solution is:

[0187] In specific implementation, the ecological package configuration network will match the first ecological package with the second ecological package according to the restoration properties of the ecological data in the ecological detection data. In this process, the restoration properties of the ecological package are accurately identified, because the restoration properties determine how to optimize the function of the ecosystem. For example, if the drought resistance property of the ecological package is identified, it is necessary to emphasize the use of drought-resistant plants in the matching, so as to improve the self-regulation ability of the ecosystem.

[0188] Secondly, if the user has special needs or already has a ratio plan, we can also accept the user's input and use their plan directly. The key to this process is that the input data needs to be verified to ensure that it complies with ecological laws and will not have a negative impact on the ecosystem.

[0189] Finally, through these two steps, the ecological package configuration network can generate a complete set of ecological restoration strategies. Ecological restoration strategies can be optimized according to the natural restoration properties of the ecosystem or customized according to user needs.

[0190] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention belong to the scope of the present invention and its equivalent technologies, the present invention is also intended to include these changes and variations.

Claims

1. A method for predicting ecological restoration and restoring disturbances in ecologically sensitive and fragile areas during power grid construction, characterized in that: include: Acquire remote sensing images of ecologically sensitive and fragile areas, determine a first area where the real-time NDVI value is lower than a preset NDVI value and a second area of ​​the disturbance trace, wherein the second area belongs to the first area; Performing ecological environment detection on the first area and the second area to determine ecological detection data, wherein the ecological detection data includes vegetation distribution data and soil quality status data; According to the vegetation distribution data, a first ecological package is configured, wherein the first ecological package is used for vegetation restoration; According to the soil state data, a second ecological package is configured, wherein the second ecological package is used for improving the soil quality; Build an ecological package configuration network based on ecological restoration prediction, where the ecological package configuration network includes a vegetation restoration configuration layer, a soil improvement configuration layer, and a restoration prediction layer; Inputting the ecological detection data of the first area into the ecological package configuration network, making an ecological restoration prediction, and determining a first ecological restoration strategy; Inputting the ecological detection data of the second area into the ecological package configuration network, making ecological restoration predictions, and determining a second ecological restoration strategy; The ecological detection data of the first area and the second area are input into the ecological package configuration network to make ecological restoration predictions and determine the third ecological restoration strategy.

2. The method for predicting ecological restoration and restoring disturbances in ecologically sensitive and fragile areas during power grid construction according to claim 1, characterized in that: The step of obtaining remote sensing images of ecologically sensitive and fragile areas also includes: Mark the power grid distribution in the geographic image data in advance to determine the power grid distribution information; the power grid distribution information includes power station distribution information, substation distribution information, distribution network center distribution information, transmission line path information, and distribution transformer distribution information; Determine the first ecological detection area according to the power grid distribution information; Obtain satellite remote sensing images of the first ecological detection area within a monitoring period and conduct an initial ecological assessment, wherein the monitoring period includes an ecological restoration period, and the ecological restoration period is not less than an iteration period of vegetation in the corresponding ecological detection area; the initial ecological assessment includes vegetation coverage assessment and vegetation coverage increase rate assessment; Based on the initial ecological assessment, the second ecologically sensitive and vulnerable areas where the vegetation coverage is in a poor recovery state are identified; the poor recovery state includes: no recovery state, reduced vegetation coverage state and easy invasion state of vegetation coverage; Based on the second ecologically sensitive and fragile area, the ecological conditions are marked and different types of ecologically sensitive and fragile areas are determined.

3. The method for predicting ecological restoration and restoring disturbances in ecologically sensitive and fragile areas during power grid construction according to claim 1, characterized in that: Determining the first area where the real-time NDVI value is lower than the preset NDVI value includes: Pre-set NDVI thresholds; Extract spectral remote sensing data of ecologically sensitive and vulnerable areas in high temporal resolution periods; Calculate NDVI using spectral remote sensing data to determine the target NDVI value; Compare the target NDVI value with the NDVI threshold, generate a binary image, and mark the NDVI value comparison; By comparing the marks, the temporal and spatial distribution of the area with low NDVI values ​​is determined and marked as the first area.

4. A method for predicting ecological restoration and restoring disturbances in ecologically sensitive and fragile areas during power grid construction according to claim 3, characterized in that: The second area is confirmed by the following steps: Extracting image features on the first area and determining whether there are disturbance features; wherein the disturbance features are project trace features existing during the construction of the transmission line; When disturbance characteristics exist, the corresponding ecologically sensitive and fragile area will be marked as the second area.

5. The method for predicting ecological restoration and restoring disturbances in ecologically sensitive and fragile areas during power grid construction according to claim 1, characterized in that: The ecological environment detection of the first area and the second area includes: performing an ecological information extraction operation on the first region and the second region; The ecological information extraction operation includes a vegetation distribution information extraction operation and a soil quality state detection information extraction operation, and both the vegetation distribution information extraction operation and the soil quality state detection information extraction operation include N detection sub-items; The vegetation distribution information extraction operation performs feature extraction based on remote sensing images of the first area and the second area; The soil quality state detection information extraction operation is used to perform experimental detection and extraction of soil quality data in vegetation distribution information where the vegetation coverage is lower than the target coverage; According to the ecological information extraction operation, the vegetation distribution information and soil condition information of the first area and the second area are marked in turn to determine the ecological detection data.

6. The method for predicting ecological restoration and restoring disturbances in ecologically sensitive and fragile areas during power grid construction according to claim 1, characterized in that: The configuring of the first ecological package according to the vegetation distribution data includes: Determine a vegetation growth plan corresponding to the restoration of vegetation coverage rate based on vegetation distribution data; wherein the vegetation growth plan includes a vegetation green manure plan and a vegetation distribution control plan, and the vegetation distribution data includes: vegetation sparseness data and vegetation type distribution data; According to the vegetation growth plan, determining the first component parameter of the first ecological package; Obtaining component ratio data required by the first ecological package based on the first component parameter, wherein the component ratio data includes: seed ratio, nutrient ratio and fertilizer ratio; Among them, the component ratio data include: determining the nutrient ratio and fertilizer ratio based on vegetation sparseness data; determining the seed ratio based on vegetation type distribution data.

7. A method for predicting ecological restoration and restoring disturbances in ecologically sensitive and fragile areas during power grid construction according to claim 6, characterized in that: The second ecological package is configured according to the soil state data, including: Obtain soil quality data, including organic matter data, microbial data, trace element data, and soil physical structure data; According to the vegetation distribution data, determine the soil conditions corresponding to different vegetation distribution areas and generate regional soil data sets; According to the regional soil data set, determine the second component parameters of the second ecological package corresponding to the regional needs; Determine whether there are undesirable components in the second component parameters that conflict with the vegetation in the corresponding area; After removing the bad components in the two-component parameters, the configuration ratio of the second ecological package is generated.

8. The method for predicting ecological restoration and restoring disturbances in ecologically sensitive and fragile areas during power grid construction according to claim 1, characterized in that: The construction of an ecological package configuration network based on ecological restoration prediction includes: Set vegetation related items and soil improvement items in sequence; According to the vegetation related items, the vegetation gain assessment model is set to form the vegetation restoration configuration layer; According to the soil improvement items, a soil improvement assessment model is set up to form a soil improvement configuration layer; Setting a first evaluation index for the vegetation restoration configuration layer, a second evaluation index for the soil quality improvement configuration layer, and a third evaluation index for simultaneously improving vegetation and soil quality; A restoration prediction layer is generated according to the first evaluation index, the second evaluation index, and the third evaluation index.

9. The method for predicting ecological restoration and restoring disturbances in ecologically sensitive and fragile areas during power grid construction according to claim 1, characterized in that: The construction of an ecological package configuration network based on ecological restoration prediction includes: Determine ecological demand items for ecological restoration according to the first area and the second area; wherein the ecological demand items include N ecological restoration sub-goals; According to the ecological requirements, determine the configurable first ecological package and second ecological package; According to the ecological restoration sub-goals, determine the composition parameters of the first ecological package and the second ecological package; The component parameters of the first ecological package and the second ecological package, as well as the vegetation distribution and soil state data of the first area and the second area are input into the ecological package configuration network to determine the ecological package configuration data.

10. The method for ecological restoration prediction and disturbance restoration in ecologically sensitive and fragile areas in power grid construction according to claim 1, characterized in that: The ecological package configuration network determines the ecological restoration strategy through the following steps: According to the restoration attribute of the ecological data in the ecological detection data, the first ecological package and the second ecological package are divided into matching schemes of corresponding attributes, so that the ecological package configuration network can simulate the execution result of the matching scheme; and / or, According to the loading ratio scheme input by the user, the forecast data of the loading ratio scheme is determined.

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