CN118313690A - Vegetation analysis method and system for ecological fragile area and grass seed recovery device - Google Patents

Abstract

The invention discloses a vegetation analysis method and system for an ecological fragile area and a grass seed recovery device, and relates to the technical field of ecological vegetation recovery, wherein the method and system comprise the steps of obtaining disturbance area information of power transmission and transformation project, and dividing a zonal area and a non-zonal area based on the disturbance area information of the power transmission and transformation project; analyzing the vegetation information of the regional area to obtain a first analysis result, and analyzing the vegetation information of the non-regional area to obtain a second analysis result; determining a typical vegetation community based on the first analysis result, and performing surface layer delicately soil analysis on the typical vegetation community to obtain a primary soil specificity index; performing anti-sensitivity calculation on the second analysis result based on the influence factors of the non-zonal region to obtain a repair coefficient; and correcting the primary soil specificity index according to the repair coefficient to obtain a regulation-grade soil specificity index, and determining vegetation recovery species based on the regulation-grade soil specificity index. The grass seed recovery device comprises the analysis system and a planting system matched with the analysis system, and completes grass seed configuration operation. The analysis result of the zonal area is combined with the repair result of the non-zonal area to serve as a screening foundation of vegetation restoration species, the influence of factors of the non-zonal area on vegetation construction is considered, the planting survival rate of the finally analyzed species can be improved, and the method is more suitable for rapid restoration construction of vegetation in power transmission and transformation projects of ecological fragile areas.

Description

Vegetation analysis method and system for ecological fragile area and grass seed recovery device

Technical Field

The invention relates to the technical field of ecological vegetation restoration, in particular to a vegetation analysis method and system for an ecological fragile area and a grass seed restoration device.

Background

In the construction process of power transmission and transformation engineering of a power grid, the natural ecological environment along the areas such as tower footing, transformer substations, construction roads and the like is subjected to larger pressure, and particularly the problems of landscape fragmentation, vegetation destruction, soil structure change, soil erosion and the like are extremely easy to cause in an ecologically fragile area. Therefore, research on environmental characteristics, vegetation characteristics and the like of the area is necessary to be carried out, the ecological environment due to construction disturbance is restored, and quick restoration of vegetation in power transmission and transformation engineering is realized.

At present, when analyzing the current situation of vegetation in an ecological fragile area, the influence of non-regional factors on vegetation construction is ignored, so that the analyzed plant species does not obtain higher survival rate, or recovery cost is greatly increased in order to preserve higher survival rate.

In view of this, the present application has been made.

Disclosure of Invention

The first object of the invention is to provide an analysis method and a system for vegetation in an ecological fragile area, wherein the analysis method and the system take the analysis result of a zonal area and the repair result of a non-zonal area into consideration as a screening foundation of vegetation restoration species, consider the influence of factors of the non-zonal area on vegetation construction, can improve the planting survival rate of the finally analyzed species, and are more suitable for rapid restoration construction of vegetation in power transmission and transformation engineering of the ecological fragile area;

the second object of the invention is to provide a grass seed recovery device in an ecologically vulnerable area, which can carry out adaptive planting and nutrient solution injection according to analysis results by using the analysis method and the system, and can carry out accurate and proper grass seed configuration operation in a disturbance area of power transmission and transformation engineering, thereby improving vegetation recovery rate.

Embodiments of the present invention are implemented as follows:

In a first aspect, a method for analyzing vegetation in an ecologically vulnerable area includes the steps of: acquiring disturbance area information of a power transmission and transformation project, and dividing a regional area and a non-regional area based on the disturbance area information of the power transmission and transformation project; analyzing the vegetation information of the regional area to obtain a first analysis result, and analyzing the vegetation information of the non-regional area to obtain a second analysis result; determining a typical vegetation community based on the first analysis result, and performing surface layer delicately soil analysis on the typical vegetation community to obtain a primary soil specificity index; performing anti-sensitivity calculation on the second analysis result based on the influence factors of the non-zonal region to obtain a repair coefficient; and correcting the primary soil specificity index according to the repair coefficient to obtain a regulation-grade soil specificity index, and determining vegetation recovery species based on the regulation-grade soil specificity index.

In an alternative embodiment, the anti-sensitivity calculation is performed on the second analysis result based on the influence factor of the non-zonal region, and the obtaining the repair coefficient includes the following steps: obtaining the types of the influence factors, and respectively carrying out sensitivity analysis on the second analysis result based on each type of the influence factors to obtain a plurality of sensitivity coefficients; and carrying out centralized processing on all the sensitivity coefficients to obtain the number of the sensitivity sets, calculating independent sensitivity based on the number of the sensitivity sets, and calculating the repair coefficients through the independent sensitivity.

In an alternative embodiment, calculating the independent sensitivities based on the number of sensitivity sets comprises the steps of: calculating offset distances of each sensitivity coefficient to the number of the sensitive sets to obtain offset distance data sets, and performing differential screening on subsets in the offset distance data sets to obtain differential data sets; performing end set classification on the differential data set to obtain a first differential subset and a second differential subset, and respectively calculating the quantity ratio of the first differential subset and the second differential subset to the differential data set to obtain a first proportion and a second proportion; and combining the first result and the second result, and giving the number of the sensitive sets to obtain independent sensitivity, wherein the first result is the product of the maximum value of the first difference subset and the first proportion, and the second result is the product of the maximum value of the second difference subset and the second proportion.

In an alternative embodiment, the method further comprises the following steps before calculating the independent sensitivities based on the sensitivity set numbers: determining the ecological niche characteristics of each species in the non-zonal region, dimensionalizing the ecological niche characteristics of each species, and respectively calculating the dimensionality overlapping ratio; screening the source consumption species with the overlapping rate larger than a preset value, positioning the position of the source consumption species in the second analysis result, marking, and taking the sensitivity coefficient obtained based on the marked second analysis result as hidden data when the centralized processing is carried out, wherein the hidden data refer to data which are not counted in a sensitive set.

In an alternative embodiment, the influencing factor comprises at least one of soil thickness, soil texture, topography slope, surface runoff, groundwater burial depth.

In an alternative embodiment, calculating the repair coefficients by independent sensitivity includes the steps of: calculating independent sensitivities respectively from the numbers of the sensitive sets containing and not containing the hidden data, marking the independent sensitivities as dominant independent sensitivities and recessive independent sensitivities, and carrying out averaging treatment on the dominant independent sensitivities and the recessive independent sensitivities to obtain target independent sensitivities; and obtaining a corresponding value of the target independent sensitivity according to the comparison gradient table as a repair coefficient.

In an alternative embodiment, the surface layer delicatessen analysis of a typical vegetation population to obtain a primary soil specificity index comprises the steps of: obtaining the fixed soil quantity of a typical vegetation community, analyzing the condition of soil longitudinal distribution under the condition of the fixed soil quantity, constructing physicochemical property maps of soil on different surface, carrying out grid division on the physicochemical property maps, and defining physicochemical property parameters of each grid; and counting according to physicochemical property parameters related to grid points covered by the zone region to obtain comprehensive physicochemical parameters serving as primary soil specificity indexes.

In an alternative embodiment, the distance between each grid point and non-regional particles is calculated to obtain a distance distribution map; wherein, the non-regional particles refer to the sites where the source-consuming species are located; and giving a repair coefficient to the primary soil specificity index represented by each grid point to obtain a repair result, and giving a corresponding distance value in the distance distribution map as a weight to the repair result to obtain an adjustment grade soil specificity index.

In a second aspect, an ecologically vulnerable zone vegetation analysis system comprises: the first acquisition unit is used for acquiring disturbance area information of the power transmission and transformation project and dividing a regional area and a non-regional area based on the disturbance area information of the power transmission and transformation project; the first analysis unit is used for analyzing the vegetation information of the regional area to obtain a first analysis result, and analyzing the vegetation information of the non-regional area to obtain a second analysis result; the second analysis unit is used for determining a typical vegetation community based on the first analysis result, and performing surface layer delicately soil analysis on the typical vegetation community to obtain a primary soil specificity index; the first calculation unit is used for performing anti-sensitivity calculation on the second analysis result based on the influence factors of the non-zonal region to obtain a repair coefficient; and the second calculation unit is used for correcting the primary soil specificity index according to the repair coefficient to obtain a regulation-grade soil specificity index, and determining vegetation recovery species based on the regulation-grade soil specificity index.

The third aspect is that a grass seed recovery device for an ecological fragile area comprises the ecological fragile area vegetation analysis system and a planting system, wherein the planting system comprises a central controller, a planter in communication connection with the central controller, a grass seed configurator and a nutrition injector, the grass seed configurator is in communication connection with the ecological fragile area vegetation analysis system, and can output corresponding grass seeds to the planter according to an analysis result of the ecological fragile area vegetation analysis system; the planter is used for planting corresponding grass seeds in a target area, and the nutrition injector synchronously performs preconfigured nutrition liquid injection according to the planted grass seeds.

The embodiment of the invention has the beneficial effects that:

according to the vegetation analysis method and system for the ecological fragile area, provided by the embodiment of the invention, the power transmission and transformation project disturbance area is divided into the zonal area and the non-zonal area, the main soil specific index is analyzed by the zonal area and is used as a basic reference for grass seed screening, and then the repair index analyzed by the non-zonal area is a comprehensive analysis result aiming at different influencing factors, so that the soil specific index is endowed to obtain the grass seed screening index which is more suitable for the analysis area, thereby ensuring that the configured grass seeds are more suitable for the growth characteristics of the area and the survival rate is higher;

According to the ecological fragile area grass seed recovery device provided by the embodiment of the invention, the grass seed output and planting are carried out by utilizing the planting system in response to the analysis result of the analysis system, and meanwhile, the nutrition liquid is matched and injected, so that the online automatic grass seed configuration operation of the ecological fragile area is realized, the survival rate of vegetation grass seeds is ensured, and meanwhile, the difficulty and the strength of vegetation recovery work are greatly reduced;

In general, the vegetation analysis method, the vegetation analysis system and the grass seed recovery device for the ecological fragile area, which are provided by the embodiment of the invention, combine the analysis results of the non-regional area on the basis of the analysis results of the regional area, so that the final analysis results are more comprehensive, the vegetation analysis method, the vegetation analysis system and the grass seed recovery device can be more suitable for the planting growth characteristics of the ecological fragile area, the survival rate can be more ensured, and the vegetation planting recovery scene after the disturbance of the ecological fragile area due to the power transmission and transformation engineering construction is particularly suitable for meeting the ideas of ecological environment friendliness and green development.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings that are needed in the embodiments will be briefly described below, it being understood that the following drawings only illustrate some embodiments of the present invention and therefore should not be considered as limiting the scope, and other related drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.

FIG. 1 is a flow chart of main steps of an analysis method according to an embodiment of the present invention;

FIG. 2 is a flow chart of one of the main steps S400 shown in FIG. 1;

FIG. 3 is a flow chart of one of the substeps S420 of step S400 shown in FIG. 2;

FIG. 4 is a flow chart of one of the main steps S500 shown in FIG. 1;

fig. 5 is a modular connection diagram of an analysis system according to an embodiment of the present invention.

Icon: 600-an analysis system; 610-a first acquisition unit; 620-a first analysis unit; 630-a second analysis unit; 640-a first computing unit; 650-a second calculation unit.

Detailed Description

For the purpose of making the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is apparent that the described embodiments are some embodiments of the present invention, but not all embodiments of the present invention. The components of the embodiments of the present invention generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations.

Thus, the following detailed description of the embodiments of the invention, as presented in the figures, is not intended to limit the scope of the invention, as claimed, but is merely representative of selected embodiments of the invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.

It is to be understood that the terms "system," "apparatus," and/or "module" as used herein are intended to be one way of distinguishing between different components, elements, parts, portions, or assemblies of different levels. However, if other words can achieve the same purpose, the words can be replaced by other expressions.

As used herein and in the claims, the terms "a," "an," "the," and/or "the" are not specific to the singular, but may include the plural, unless the context clearly dictates otherwise. Generally, the terms "comprises" and "comprising" merely indicate that the steps and elements are explicitly identified, and they do not constitute an exclusive list, as other steps or elements may be included in a method or apparatus.

A flowchart is used in the present application to describe the operations performed by a system according to embodiments of the present application. It should be appreciated that the preceding or following operations are not necessarily performed in order precisely. Rather, the steps may be processed in reverse order or simultaneously. Also, other operations may be added to or removed from these processes.

Examples

The ecological fragile area generally has the characteristics of weak anti-interference capability, sensitivity to climate change and the like, such as ecological staggered area at the Mongolian area, complex terrain, changeable climate and uneven rainfall distribution. The north and southwest parts of the ecological system are respectively covered with forests and sand to form a composite ecological system of agriculture, forests, grazing and sand, and the ecological vulnerability of the ecological system is more obvious due to the pressure caused by artificial interference in recent years. In the construction of power transmission and transformation engineering of a power grid, particularly in Meng Dong ecological fragile areas, the problems of landscape crushing, vegetation destruction, soil structure change, soil erosion and the like are extremely easy to occur. In order to solve the problems, the analysis and research on the environmental characteristics and vegetation characteristics of the area are carried out, and the typical native meadow vegetation community of the area is screened to be used for recovering the meadow seeds, and although the survival rate of the meadow seeds at part of the area is higher, the survival rate of the meadow seeds at part of the area is lower, especially the negative topography part, the sunny slope/cloudy slope position, the shallow black soil humus layer position and the like. The reason for this is that in the previous vegetation recovery planting analysis process, characteristics of some non-regional grass seeds are not considered, so that the regional grass seeds are configured in the regions, and a higher survival rate is not obtained.

Referring specifically to fig. 1, the method for analyzing vegetation in an ecologically fragile area provided in this embodiment includes the following steps:

S100: acquiring disturbance area information of a power transmission and transformation project, and dividing a regional area and a non-regional area based on the disturbance area information of the power transmission and transformation project; the method comprises the steps of obtaining information such as the position, the area and the like of a geographical area related to power transmission and transformation engineering, for example, by field survey, determining the specific position of the area with ecological disturbance, and marking and drawing a contour on a map. The zonal area and the non-zonal area are divided based on the area occupied by the outline, wherein the zonal area refers to a continuous regional range with similar characteristics or ecological conditions in the geographic or ecological system, and the non-zonal area refers to a regional range which cannot be classified into any specific ecological zone or zone in the geographic or ecological system.

Dividing and scribing the regional area and the non-regional area through S100, and then collecting and analyzing the data of the divided areas in the field, namely, performing step S200: and analyzing the vegetation information of the zonal region to obtain a first analysis result, and analyzing the vegetation information of the non-zonal region to obtain a second analysis result. In the step, the first analysis result and the second analysis result are analysis data of vegetation information, and the first analysis result and the second analysis result contain basic inspection parameters of soil, grass seeds and the like.

S300: and determining a typical vegetation community based on the first analysis result, and performing surface-layer delicately soil analysis on the typical vegetation community to obtain a primary soil specificity index. The step represents that main vegetation information is determined by utilizing a first analysis result, and as the vegetation distribution of the area has regular or similar characteristics, most grass seeds have the same growth characteristics at the moment, especially according to the characteristic decision of the growth soil, the surface layer mature soil related to the main typical primary community of the area is required to be subjected to basic analysis, for example, the physicochemical properties of the fixed soil quantity, the soil layering distribution condition, the water storage capacity, the fertilizer retention condition and the like are analyzed, and a primary soil specificity index representing the soil of the area is obtained, wherein the index is used as a basic reference index for later grass seed screening.

Since the primary soil specific index was mainly used as the screening reference parameter for recovering grass seeds before, the survival rate of the finally selected primary grass seeds in the non-zoned area is not high, and therefore the reference parameter needs to be adjusted and corrected by combining the characteristics of the non-zoned area, namely, step S400 is performed: and performing anti-sensitivity calculation on the second analysis result based on the influence factors of the non-zonal region to obtain a repair coefficient. This step represents determining which kinds of influence factors on vegetation growth in the non-regional area, analyzing the influence condition of each influence factor on vegetation growth in the non-regional area, if the influence is larger, proving that the influence factors are more sensitive to vegetation growth, the vegetation has poorer sensitivity to the factors, and the sensitivity resistance of the vegetation to the growth in the non-regional area needs to be especially considered when the grass seeds are selected later.

Therefore, a series of reinforcement parameters which can be paid attention to during grass planting configuration are obtained by utilizing the anti-sensitivity calculation results of all kinds of influence factors on the second analysis result respectively, and the reinforcement parameters are digitized or characterized into repair coefficients so as to be convenient for subsequent combination with basic reference indexes. In this embodiment, the influencing factors include at least one of soil thickness, soil texture, topography slope, surface runoff, and groundwater burial depth, and the parameters of the above categories are all limiting factors capable of influencing the growth of grass seeds, and of course, other influencing factors of some categories may be included in the general knowledge of the skilled in the art, and only some common categories are exemplified here to facilitate understanding of the above scheme by the skilled pre-warning person.

S500: and correcting the primary soil specificity index according to the repair coefficient to obtain a regulation-level soil specificity index, and determining vegetation recovery species based on the regulation-level soil specificity index. The step is characterized in that the digitized or characterized repair coefficient is utilized to endow primary soil with specific indexes, each index is adjusted, and vegetation recovery species meeting the index range are rescreened based on the adjustment level soil specific indexes, so that grass seed configuration operation in a disturbance area is carried out.

According to the technical scheme, the method is characterized in that the analysis result of one stage is corrected on the basis of planting configuration according to the grass seeds related to the typical meadow primary community, especially the characteristics of the considered regional area and the non-regional area are comprehensively analyzed, the influence factors of the non-regional area on vegetation growth are comprehensively analyzed, and finally, the grass seeds are screened and regulated according to the obtained comprehensive analysis result, so that the selected grass seeds have the growth characteristics of the regional area and the growth characteristics of the non-regional area, the vegetation recovery effect of the disturbance area can be obviously improved without adopting a plurality of high-cost survival means when the vegetation recovery construction operation is carried out, the water conservation acceptance special indexes in the power grid engineering field are ensured to be met, and the on-time acceptance of a power transmission and transformation engineering project is ensured.

Referring to fig. 2, the anti-sensitivity calculation of the second analysis result based on the influence factor of the non-zonal region, and the obtaining of the repair coefficient includes the following steps:

S410: obtaining the types of the influence factors, and respectively carrying out sensitivity analysis on the second analysis result based on each type of the influence factors to obtain a plurality of sensitivity coefficients; the method comprises the steps of firstly detecting growth influence on a second analysis result based on each type of influence factors (at least one of soil thickness, soil texture, topography slope, topography gradient, topography slope direction, surface runoff and groundwater burial depth), defining whether the second analysis result (vegetation information) is sensitive to the sensitive factors according to different influence degrees, and characterizing by artificially determined sensitivity coefficients. And then carrying out statistical analysis on the sensitivity coefficient.

S420: and carrying out centralized processing on all the sensitivity coefficients to obtain a sensitivity set number, calculating independent sensitivity based on the sensitivity set number, and calculating the repair coefficient through the independent sensitivity. The step is to perform centralized analysis on all the sensitivity coefficients, such as a mode of obtaining a mean value, a median value, a mode and the like, and then define independent sensitivity based on the obtained number of the sensitivity set, so as to represent the anti-sensitivity degree of a second analysis result to the influence factors.

The steps S410-S420 can be used to represent the restriction of each influencing factor in the non-banded region to the vegetation growth in the region, but considering that each influencing factor has different effects on the vegetation growth, for example, when the thickness of the black soil humus layer is low, the nutrient content is deficient, the fertility level is low, the meadow herbaceous plants are limited in growth, the tablelands, the beam and the hills are limited in growth, the soil water content is low, the groundwater is buried deeply, the valley and the valley are buried in the valley, the valley is buried in the valley, the water content is high, the groundwater is buried shallowly, and the plant community on the sunny slope is more drought-resistant than the sunny slope. At this time, the calculation of the independent sensitivity needs to consider the relatively extreme situation, so as to avoid the situation that the survival rate of grass seeds at the extreme positions is still not high.

Referring to fig. 3, the specific step S420 further includes the step of calculating the independent sensitivities based on the sensitivity sets, and further includes the steps of:

S422: calculating the offset distance of each sensitivity coefficient to the number of the sensitive sets to obtain an offset distance data set, and performing differential screening on a subset of the offset distance data set to obtain a differential data set; the step shows that each sensitivity coefficient is different from the sensitive set number, the sensitivity coefficient is defined as an offset distance, if the offset distance is larger, the number in the sensitive set is more extreme, or the sensitivity is abnormal or insensitive, one of the two extreme cases is different from the growth of the original meadow vegetation, and the other extreme case is close to the growth of the original meadow vegetation, so that more extreme cases need to be considered when the number in the sensitive set is determined, and further adjustment is carried out on the obtained number in the sensitive set, so that the difference between theoretical statistical calculation and actual conditions is reduced. The sensitivity coefficient outside a preset interval of the offset distance data set (for example, the range of the interval is manually determined) is screened, the screened sensitivity coefficient is obtained to form a differential data set, and then the subsequent steps are carried out.

S423: performing end set classification on the differential data set to obtain a first differential subset and a second differential subset, and respectively calculating the quantity ratio of the first differential subset to the differential data set to the second differential subset to the differential data set to obtain a first proportion and a second proportion; dividing the sensitivity coefficient in the differential data set, namely respectively collecting the data of the front section and the rear section of the preset interval to obtain a first differential subset and a second differential subset. And then calculating the proportion of the sensitive coefficients in the two subsets respectively, wherein the proportion is the percentage of the sensitive number of the differential subset and the total sensitive coefficient number, and two percentage values are obtained as a first proportion and a second proportion respectively.

S424: and combining a first result and a second result, and giving the number of the sensitive set to obtain the independent sensitivity, wherein the first result is the product of the maximum value of the first difference subset and the first proportion, and the second result is the product of the maximum value of the second difference subset and the second proportion. This step represents the calculation of the total impact weight of the extreme case, for example, the impact weight of the first differential subset is the product of the first duty cycle and the first value of the first differential subset (the maximum value if the latter data and the minimum value if the former data) and the impact weight of the second differential subset is the product of the first value of the second duty cycle and the first value of the second differential subset, and this is used as the characterization data of the impact weight. And then combining the two results, such as difference combining, wherein the obtained result represents more extreme cases, so that the obtained result is endowed to the number of the sensitive set for adjustment, the number of the sensitive set is more matched with the actual result, and the actual situation can be more met when the subsequent index calculation is carried out.

The calculation considering the independent sensitivity is mainly based on the reaction of the relation between vegetation and planting environment, namely, the soil environment factor of the non-zone area is taken as the basis of the anti-sensitivity calculation. However, in the actual situation, there is also an influence of the interrelation between the finally screened grass seeds, so in order to ensure that a higher survival rate is obtained, on the basis of the scheme above, the interrelation between the grass seeds needs to be considered, so that the situation that the resource occupation overlapping rate is higher is avoided. That is, before the number of sensitive sets calculates the independent sensitivity, the method further comprises the following steps:

S421: determining the ecological niche characteristics of each species in the non-zonal region, dimensionalizing the ecological niche characteristics of each species, and respectively calculating the dimensionality overlapping ratio; screening consumable source species with the overlapping rate larger than a preset value, positioning the position of the consumable source species in the second analysis result, marking, and taking the sensitivity coefficient obtained based on the marked second analysis result as hidden data when centralized processing is carried out, wherein the hidden data refer to data which are not counted in the sensitive set. This step represents the consideration of the resource occupancy relationship between species in non-zonal regions from the niche characteristics (meaning the maximum resource location occupied by a species in space and time, which can reflect the relationship between species and species, species and environment), and the avoidance of niche overlap between species as much as possible.

Specifically, the niche characteristics of each species are dimensionalized (such as resource preference, feeding habit, space utilization, growth reproduction characteristics, physiological and behavioral characteristics, environmental response degree and the like), each dimension is defined in a readable manner, then the dimensions of all species are counted and dimensional overlapping rate calculation is obtained, if the sum of the overlapping rates of the dimensions of a certain species is larger than a preset value, the sum of the overlapping rates of the dimensions is defined as a consumed source species, the consumed source species can greatly influence the growth stability of other species, therefore, the consumed source species is independently positioned and marked in a second analysis result, the sensitivity coefficient obtained in the sensitivity analysis of marking is used as hidden data, namely, the species is not included in a final species screening basis, the situation that the survival rate of the rest of the grass species is low after the grass species is configured is avoided, and the stability of the whole community growth is unfavorable.

The residual sensitivity coefficient of the hidden data is used for calculating the number of the sensitive set, so that independent sensitivity is obtained, and the source consumption species with high relative resource overlapping rate can be removed in advance in such a way, so that the screening process of the last vegetation recovery species is not participated. On the basis of the above technical solution, considering that there may be an error in the preset value setting (the preset value is generally set by the thinking), in order to reduce the error degree, when the calculation participation of the source consumption species is completely excluded, the anti-sensitivity capability of the whole vegetation community cannot be truly represented, so in this embodiment, the number of the sensitive sets containing and not containing the hidden data is respectively calculated as the dominant independent sensitivity and the recessive independent sensitivity, and the dominant independent sensitivity and the recessive independent sensitivity are averaged to obtain the target independent sensitivity. According to the technical scheme, the obtained independent sensitivity degree of the target is better considered in consideration of the results between the actual and the target, and the situation that the independent sensitivity result is excessively distorted due to the fact that the sensitivity coefficient of the source consumption species is removed is avoided. It should be noted that, if the dominant independent sensitivity and the recessive independent sensitivity are not greatly different, only the dominant independent sensitivity may be calculated to obtain the repair coefficient.

S425: said calculating said repair coefficients from said independent sensitivities comprises the steps of: and obtaining a corresponding value of the target independent sensitivity according to a comparison gradient table, and taking the corresponding value as the repair coefficient. This step represents the parameters (non-single values) determined directly from the control gradient table (obtained from the previous ecological analysis test) as repair coefficients after obtaining the target independent sensitivity, thus participating in the combined calculation of the primary soil-specific index.

According to the technical scheme, a relatively real analysis result can be obtained in a non-regional area, the analysis result comprehensively considers the influence of extreme planting environments and source consumption species, good connection between a target and a model result can be achieved, and the obtained repair coefficient can be correspondingly endowed with a corresponding primary soil specificity index to obtain a more reliable result.

In some embodiments, referring to fig. 4, the performing a surface layer delicatessen analysis on the representative vegetation population, obtaining a primary soil specificity means comprises the steps of:

s510: obtaining the fixed soil quantity of the typical vegetation community, analyzing the condition of soil longitudinal distribution under the fixed soil quantity, constructing physicochemical property maps of soil on different surface, carrying out grid division on the physicochemical property maps, and defining physicochemical property parameters of each grid; the method comprises the steps of expressing a typical original meadow vegetation community in a region screened based on climate environment characteristics and soil characteristics aiming at a zonal region, and carrying out soil specificity analysis based on surface layer delicatessen characteristics in the region, specifically, firstly, fixing soil quantity in the region, longitudinally layering parameters of the depth of the soil under the fixed soil quantity, taking different soil quantities at different depths as one type of basic index, taking physical and chemical property parameters of the soil as another type of basic index, so as to realize mutual coordinate correspondence, and constructing a physical and chemical property map. The physical and chemical property parameters presented by the soil quantity of the layer can be reflected in each unit area on the map, and the parameters are, for example, texture, density, volume weight, pH value, organic matter content, nutrient content and the like. Each unit can be displayed in a grid division mode, namely, the physicochemical property map is grid-divided, and the grid size is adaptively selected according to the data calculation complexity, so that the physicochemical property of the soil in each grid area can be defined by parameters (such as digital definition and visual definition).

S520: and counting according to physicochemical property parameters related to grid points covered by the zonal region to obtain comprehensive physicochemical parameters serving as the primary soil specificity index. The step represents that the physicochemical property parameters in all grids covered in the zone area to be analyzed are subjected to statistical treatment, such as cluster analysis (hierarchical clustering, density clustering, cluster clustering and the like), and the analysis result is used as comprehensive physicochemical parameters to characterize the specificity of soil in the whole area, namely, is used as a primary soil specificity index.

The primary soil specificity index obtained through the technical scheme is combined with the repair coefficient one by one, and finally the adjustment grade soil specificity index is obtained. In the process, on the basis of the mode that all primary soil specific indexes are combined with the repair coefficients equally, factors which influence linear or nonlinear changes of the degree can be considered when the factors are combined with the repair coefficients, namely, the closer to the non-zonal area, the more the factors are required to be combined for adjustment, so that the obtained final result can show relatively reliable survival rate of grass seeds. Thus, in some embodiments, step S500 further comprises the steps of:

S530: calculating the distance between each grid point and each non-regional particle to obtain a distance distribution map; wherein, the non-regional particles refer to the sites where the source-consuming species are located; this step is shown by starting with each grid point and calculating its distance to non-area particles, which are the points where the source species are located (in the case of one source species, emphasis is defined here, and in the case of multiple source species, to their middle point). By taking the non-regional particles as the end point, the method considers that the overlapping rate of the source consumption species and the residues thereof is higher, has the growth characteristics of most species and is typical, so that a distance distribution diagram formed by all distances is obtained, and the method has more real fitting property, thereby being more suitable for the species change regularity in the region when the repair coefficient is adjusted.

S540: and giving the repair coefficient to the primary soil specificity index represented by each grid point to obtain a repair result, and giving the corresponding distance value in the distance distribution map as a weight to the repair result to obtain the adjustment grade soil specificity index. This step represents that when the repair coefficient is combined with the primary soil-specific index (single physicochemical property parameter) within the grid point, the distance value is simultaneously given as a weight (ratio to the longest distance or the specified value) in proportion, so that the adjustment parameter of each grid point is obtained, and the adjustment parameters of all grid points are integrated as the adjustment-level soil-specific index, so that the grass seeds meeting the index range are determined. It should be noted that, the soil-specific index of the adjustment level is gradually distributed in the disturbance area, and presents similar properties in the zonal area, so that it can be determined that typical original grass seeds are configured, the closer to the non-zonal area, the grass seeds determined by the soil-specific index with larger difference after adjustment are required to be determined, and the grass seeds determined by the larger difference index are required to be considered for configuration in the non-zonal area.

Through the scheme, species diversity, community structures, population distribution characteristics in communities and the like in investigation plots of areas of different disturbance sites of the whole power transmission and transformation project are subjected to correlation analysis between species and habitat factors by using a quantitative ecological statistical analysis method, vegetation recovery species suitable for ecologically sensitive fragile areas are screened out by combining regional and non-regional environmental characteristic conditions and primary vegetation types, and the screened vegetation recovery species also show different differences, particularly similar circle-layer changes in transition from the regional areas to the non-regional areas.

In this embodiment, an ecological fragile area vegetation analysis system 600 is further provided, referring to a modularized schematic diagram of the ecological fragile area vegetation analysis system 600 in fig. 5, which is mainly used for dividing functional modules of the ecological fragile area vegetation analysis system 600 according to the embodiment of the method described above. For example, each functional module may be divided, or two or more functions may be integrated into one processing module. The integrated modules may be implemented in hardware or in software functional modules. It should be noted that, the division of the modules in the present invention is illustrative, and is merely a logic function division, and other division manners may be implemented in practice. For example, in case that the respective functional modules are divided with the respective functions, fig. 5 shows only a system/apparatus schematic diagram, wherein the ecologically vulnerable zone vegetation analysis system 600 may include a first acquisition unit 610, a first analysis unit 620, a second analysis unit 630, a first calculation unit 640, and a second calculation unit 650. The functions of the respective unit modules are explained below.

The first obtaining unit 610 is configured to obtain power transformation project disturbance area information, and divide a regional area and a non-regional area based on the power transformation project disturbance area information.

And a first analysis unit 620, configured to analyze the vegetation information of the area to obtain a first analysis result, and analyze the vegetation information of the non-area to obtain a second analysis result.

A second analysis unit 630 for determining a typical vegetation community based on the first analysis result, performing surface-layer delicatessen analysis on the typical vegetation community, and obtaining a primary soil-specific index; in some embodiments, the second analysis unit 630 is further configured to obtain a fixed soil amount of the typical vegetation community, analyze a soil longitudinal distribution condition under the fixed soil amount, construct a physicochemical property map of soil on different surface, grid the physicochemical property map, and define physicochemical property parameters for each grid; and counting according to physicochemical property parameters related to grid points covered by the zonal region to obtain comprehensive physicochemical parameters serving as the primary soil specificity index.

A first calculation unit 640, configured to perform anti-sensitivity calculation on the second analysis result based on the influence factor of the non-zonal region, to obtain a repair coefficient; in some embodiments, the first calculating unit 640 is further configured to obtain a category of the influence factors, and perform sensitivity analysis on the second analysis result based on each category of influence factors, so as to obtain a plurality of sensitivity coefficients; and carrying out centralized processing on all the sensitivity coefficients to obtain a sensitivity set number, calculating independent sensitivity based on the sensitivity set number, and calculating the repair coefficient through the independent sensitivity. Simultaneously, the method is also used for determining the ecological niche characteristics of each species in the non-regional area, dimensionalizing the ecological niche characteristics of each species and respectively calculating the dimensionality overlapping rate; screening a source consumption species with the overlapping rate larger than a preset value, positioning the position of the source consumption species in the second analysis result, marking, and taking a sensitivity coefficient obtained based on the marked second analysis result as hidden data when centralized processing is carried out, wherein the hidden data refer to data which are not counted in the sensitive set; calculating the offset distance of each sensitivity coefficient to the number of the sensitive sets to obtain an offset distance data set, and performing differential screening on a subset of the offset distance data set to obtain a differential data set; performing end set classification on the differential data set to obtain a first differential subset and a second differential subset, and respectively calculating the quantity ratio of the first differential subset to the differential data set to the second differential subset to the differential data set to obtain a first proportion and a second proportion; and combining the first result and the second result, and giving the number of the sensitive set to obtain the independent sensitivity. Calculating independent sensitivities respectively from the sensitive sets containing and not containing the hidden data, recording the independent sensitivities as dominant independent sensitivities and recessive independent sensitivities, and carrying out averaging treatment on the dominant independent sensitivities and the recessive independent sensitivities to obtain target independent sensitivities; and obtaining a corresponding value of the target independent sensitivity according to a comparison gradient table, and taking the corresponding value as the repair coefficient.

And a second calculating unit 650, configured to correct the primary soil specific index according to the repair coefficient, obtain a regulatory grade soil specific index, and determine a vegetation recovery species based on the regulatory grade soil specific index. In some embodiments, the second computing unit 650 is further configured to calculate a distance between each of the grid points and the non-regional particles to obtain a distance profile; and giving the repair coefficient to the primary soil specificity index represented by each grid point to obtain a repair result, and giving the corresponding distance value in the distance distribution map as a weight to the repair result to obtain the adjustment grade soil specificity index.

The embodiment also discloses a device for recovering grass seeds in an ecologically vulnerable zone, which comprises a planting system and the ecologically vulnerable zone vegetation analysis system, wherein the planting system comprises a central controller, and a planter, a grass seed configurator and a nutrition injector which are in communication connection with the central controller, the grass seed configurator is in communication connection with the ecologically vulnerable zone vegetation analysis system, and can output corresponding grass seeds to the planter according to the analysis result of the ecologically vulnerable zone vegetation analysis system, for example, the grass seed configurator is provided with a feed bin, a feed channel and a transfer bin, the feed bin is internally provided with native species (the types and the quantity of the native species can be gradually optimized according to the number of configuration wheels), after responding to the analysis result of the ecologically vulnerable zone vegetation analysis system, the transfer device capable of driving the feed bin transfers corresponding grass seeds singly or in batches into the feed channel, and then transfers the corresponding grass seeds to the transfer bin to a planting position, and waits for a next instruction. At this time, the planter is used for planting corresponding grass seeds in a target area, namely, the planter is used for planting grass seeds in a transfer bin on site, and the nutrition injector synchronously performs preconfigured nutrient solution injection according to the planted grass seeds, so that grass seed configuration operation is completed.

Through the technical scheme, the vegetation analysis system is utilized to analyze the functional indexes of the vegetation and the physical and chemical property indexes of soil layers in different areas, the advantages and the recovery directions of available original resources are explored, the cost of recovery work can be greatly saved, the period of recovery work is shortened, a relatively good effect is obtained in the quick recovery work of the vegetation suitable for power transmission and transformation engineering, and the stability and the functionality of an ecological system are further ensured.

In the above embodiments, it may be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented in software, may be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When loaded and executed on a computer, produces a flow or function in accordance with embodiments of the present application, in whole or in part. The computer may be a general purpose computer, a special purpose computer, a computer network, or other programmable apparatus. The computer instructions may be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another computer-readable storage medium, for example, the computer instructions may be transmitted from one website site, computer, server, or data center to another website site, computer, server, or data center by wired or wireless means. The computer readable storage medium may be any available medium that can be accessed by a computer or a data storage device such as a server, data center, etc. that contains an integration of one or more available media. The usable medium may be a magnetic medium (e.g., floppy disk, hard disk, tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., solid state disk (sol id STATE DISK, SSD)), etc.

Embodiments of the present application are described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

It will be apparent to those skilled in the art that various modifications and variations can be made to the embodiments of the present application without departing from the spirit and scope of the application. Thus, if such modifications and variations of the embodiments of the present application fall within the scope of the claims and the equivalents thereof, the present application is also intended to include such modifications and variations.

Claims (10)

1. The vegetation analysis method for the ecological fragile area is characterized by comprising the following steps of:

acquiring disturbance area information of a power transmission and transformation project, and dividing a regional area and a non-regional area based on the disturbance area information of the power transmission and transformation project;

Analyzing the vegetation information of the zonal region to obtain a first analysis result, and analyzing the vegetation information of the non-zonal region to obtain a second analysis result;

Determining a typical vegetation community based on the first analysis result, and performing surface layer delicately soil analysis on the typical vegetation community to obtain a primary soil specificity index;

Performing anti-sensitivity calculation on the second analysis result based on the influence factors of the non-zonal region to obtain a repair coefficient;

And correcting the primary soil specificity index according to the repair coefficient to obtain a regulation-level soil specificity index, and determining vegetation recovery species based on the regulation-level soil specificity index.

2. The method for analyzing vegetation in an ecologically vulnerable area according to claim 1, wherein the anti-sensitivity calculation is performed on the second analysis result based on the influence factor of the non-zonal area, and the repair coefficient is obtained by the steps of:

Obtaining the types of the influence factors, and respectively carrying out sensitivity analysis on the second analysis result based on each type of the influence factors to obtain a plurality of sensitivity coefficients; and carrying out centralized processing on all the sensitivity coefficients to obtain a sensitivity set number, calculating independent sensitivity based on the sensitivity set number, and calculating the repair coefficient through the independent sensitivity.

3. The method of claim 2, wherein calculating the independent sensitivities based on the number of sets of sensitivities comprises the steps of:

calculating the offset distance of each sensitivity coefficient to the number of the sensitive sets to obtain an offset distance data set, and performing differential screening on a subset of the offset distance data set to obtain a differential data set;

Performing end set classification on the differential data set to obtain a first differential subset and a second differential subset, and respectively calculating the quantity ratio of the first differential subset to the differential data set to the second differential subset to the differential data set to obtain a first proportion and a second proportion;

And combining a first result and a second result, and giving the number of the sensitive set to obtain the independent sensitivity, wherein the first result is the product of the maximum value of the first difference subset and the first proportion, and the second result is the product of the maximum value of the second difference subset and the second proportion.

4. The method of claim 3, further comprising the step of, prior to calculating the independent sensitivities based on the number of sensitivity sets:

determining the ecological niche characteristics of each species in the non-zonal region, dimensionalizing the ecological niche characteristics of each species, and respectively calculating the dimensionality overlapping ratio; screening consumable source species with the overlapping rate larger than a preset value, positioning the position of the consumable source species in the second analysis result, marking, and taking the sensitivity coefficient obtained based on the marked second analysis result as hidden data when centralized processing is carried out, wherein the hidden data refer to data which are not counted in the sensitive set.

5. The method of claim 2, wherein the impact factor comprises at least one of soil thickness, soil texture, land slope, surface runoff, and groundwater burial depth.

6. The method of claim 4, wherein said calculating said repair coefficients from said independent sensitivities comprises the steps of:

calculating independent sensitivities respectively from the sensitive sets containing and not containing the hidden data, recording the independent sensitivities as dominant independent sensitivities and recessive independent sensitivities, and carrying out averaging treatment on the dominant independent sensitivities and the recessive independent sensitivities to obtain target independent sensitivities; and obtaining a corresponding value of the target independent sensitivity according to a comparison gradient table, and taking the corresponding value as the repair coefficient.

7. The method of claim 6, wherein the performing surface layer delicately soil analysis on the representative vegetation population to obtain a primary soil specificity comprises the steps of:

obtaining the fixed soil quantity of the typical vegetation community, analyzing the condition of soil longitudinal distribution under the fixed soil quantity, constructing physicochemical property maps of soil on different surface, carrying out grid division on the physicochemical property maps, and defining physicochemical property parameters of each grid;

And counting according to physicochemical property parameters related to grid points covered by the zonal region to obtain comprehensive physicochemical parameters serving as the primary soil specificity index.

8. The method of claim 7, wherein the distances between each grid point and the non-regional particles are calculated to obtain a distance profile; wherein, the non-regional particles refer to the sites where the source-consuming species are located;

And giving the repair coefficient to the primary soil specificity index represented by each grid point to obtain a repair result, and giving the corresponding distance value in the distance distribution map as a weight to the repair result to obtain the adjustment grade soil specificity index.

9. An ecologically vulnerable zone vegetation analysis system comprising:

the first acquisition unit is used for acquiring disturbance area information of the power transmission and transformation project and dividing a regional area and a non-regional area based on the disturbance area information of the power transmission and transformation project;

the first analysis unit is used for analyzing the vegetation information of the regional area to obtain a first analysis result, and analyzing the vegetation information of the non-regional area to obtain a second analysis result;

A second analysis unit for determining a typical vegetation community based on the first analysis result, performing surface-layer delicatessen analysis on the typical vegetation community, and obtaining a primary soil specificity index;

The first calculation unit is used for performing anti-sensitivity calculation on the second analysis result based on the influence factors of the non-zonal region to obtain a repair coefficient;

And the second calculation unit is used for correcting the primary soil specificity index according to the repair coefficient to obtain a regulation-level soil specificity index, and determining vegetation recovery species based on the regulation-level soil specificity index.

10. The device for recovering the grass seeds in the ecological fragile area is characterized by comprising the vegetation analysis system in the ecological fragile area according to claim 9, and further comprising a planting system, wherein the planting system comprises a central controller, and a planter, a grass seed configurator and a nutrition injector which are in communication connection with the central controller, and the grass seed configurator is in communication connection with the vegetation analysis system in the ecological fragile area and can output corresponding grass seeds to the planter according to the analysis result of the vegetation analysis system in the ecological fragile area; the planter is used for planting corresponding grass seeds in a target area, and the nutrition injector synchronously performs preconfigured nutrient solution injection according to the planted grass seeds.