Desertification control method and system based on plant cultivation

Abstract

The invention discloses a desertification control method and system based on plant cultivation, and relates to the technical field of ecological engineering, the system comprises a control center, the control center is connected with a region acquisition module, an information processing module, a desertification analysis module and an intelligent control module; the method comprises the following steps: performing preliminary processing on desert geological data to obtain a local quantitative cardinal number segment, and performing graph replacement on a geological quantization coefficient according to the local quantitative cardinal number segment to obtain a quantization coefficient dynamic graph; performing initial matching on the plant comprehensive data according to the desert division blocks to obtain matching curve plant data, and performing coverage judgment on the matching curve plant data to obtain an interval matching proportion; performing scheme construction on block suitable plants through interval matching proportions to obtain a regional planting scheme, and constructing a virtual adjoint space to perform simulation optimization on the regional planting scheme to obtain an optimal planting plan; the control cost is saved by obtaining the control effect through the simulation scheme, the scheme generation speed is increased, and the ecological environment is improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of ecological engineering, and in particular to a desertification prevention and control method and system based on plant cultivation. BACKGROUND

[0002] Desertification is a global environmental problem that leads to the decline of land productivity, the deterioration of ecological environment, and the loss of biodiversity. Desertification not only affects the natural ecosystem, but also seriously threatens the survival environment of human beings and the sustainable development of social economy.

[0003] In recent years, although some progress has been made in the field of desertification prevention and control, the existing prevention and control methods generally have problems such as high cost, unstable effect, and poor sustainability. In particular, in the extremely arid desert areas, traditional plant cultivation methods often fail to work, therefore, developing a low-cost, high-efficiency, and sustainable desertification prevention and control method has become an urgent demand in the field of scientific research and environmental protection.

[0004] In view of the above problems, the present application provides a desertification prevention and control method based on plant cultivation, which selects suitable plant species, generates an initial planting scheme, and uses virtual space to simulate the effect of the scheme to obtain a planting scheme with the best prevention and control effect, aiming to improve the efficiency of desertification prevention and control, reduce the cost, and enhance the sustainability of the prevention and control effect. SUMMARY

[0005] The present application aims to provide a desertification prevention and control method and system based on plant cultivation.

[0006] The purpose of the present application can be achieved by the following technical solutions:

[0007] A desertification prevention and control system based on plant cultivation, comprising a control center, wherein the control center is connected with a region acquisition module, an information processing module, a desert analysis module, and an intelligent prevention and control module;

[0008] The region acquisition module is used for acquiring plant comprehensive data, acquiring desertification geological data of a desertification region, and dividing the desertification region into blocks;

[0009] The information processing module is used for preliminarily processing the desertification geological data to obtain a local quantitative base section, replacing the graph of the ground quality coefficient according to the local quantitative base section, and obtaining a quantitative coefficient dynamic graph;

[0010] The desert analysis module is used for initially matching the plant comprehensive data according to the desertification block division, obtaining matching curve plant data, and performing coverage determination on the matching curve plant data to obtain an interval matching proportion;

[0011] The intelligent prevention and control module is used for scheme construction on the suitable plants in the blocks through interval matching proportion, obtaining a regional planting scheme, constructing a virtual accompanying space to simulate and optimize the regional planting scheme, and obtaining an optimal planting plan.

[0012] Preferably, the process of collecting the plant comprehensive data and the desert geological data comprises:

[0013] The desertification area is geologically collected to obtain the desert geological data, and the collected desert geological data is time-labeled to obtain a collection time;

[0014] The desertification area is geologically divided according to the desert geological data to obtain desert division blocks;

[0015] The cultivated plants are matched and collected based on the desertification area and the desert geological data to obtain the plant comprehensive data.

[0016] Preferably, the process of preliminarily processing the desert geological data comprises:

[0017] A prevention and control cycle is set according to the collection time, and the desert geological data is quantitatively replaced based on the desert division blocks and the prevention and control cycle to obtain a geological quantization coefficient;

[0018] An extraction quantitative basis is set, and the extraction quantitative basis is limitedly transformed to obtain a transformation parameter;

[0019] The extraction quantitative basis is locally divided according to the transformation parameter to obtain a local quantitative basis segment.

[0020] Preferably, the process of graphically replacing the geological quantization coefficient according to the local quantitative basis segment comprises:

[0021] The local quantitative basis segment is obtained, and the geological quantization coefficient is butt-jointed and extracted according to the local quantitative basis segment to obtain a local quantization coefficient;

[0022] The local quantization coefficient is number-graph evolved based on the prevention and control cycle to obtain a quantization coefficient dynamic graph, and the quantization coefficient dynamic graph is curve-labeled to obtain a quantization coefficient curve.

[0023] Preferably, the process of initially matching the plant comprehensive data according to the desert division blocks comprises:

[0024] The desert geological data corresponding to the desert division blocks is obtained, and the desert geological data is conditionally screened to obtain an environment suitable background;

[0025] The plant comprehensive data is adaptively classified according to the environment suitable background to obtain block suitable plants;

[0026] The limit of the quantization coefficient dynamic diagram is limited to obtain a curve fluctuation interval, the block suitable plant is matched according to the curve fluctuation interval, and matched curve plant data is obtained.

[0027] Preferably, the process of covering judgment on the matched curve plant data comprises:

[0028] The matched plant coefficient is obtained by quantization replacement of the matched curve plant data, and the local matched coefficient is obtained by docking extraction of the matched plant coefficient according to the local quantitative base section;

[0029] The plant quantization curve is obtained by number-graph evolution of the local matched coefficient through the quantization coefficient dynamic diagram, and the obtained plant quantization curve is uploaded to the quantization coefficient dynamic diagram;

[0030] The interval matching proportion is obtained by overlapping statistics of the plant quantization curve through the curve fluctuation interval.

[0031] Preferably, the process of constructing a scheme for the block suitable plant through the interval matching proportion comprises:

[0032] The same interval proportion sequence is obtained by position sorting of the interval matching proportion based on the block suitable plant.

[0033] The suitable plant comprehensive degree is obtained by ranking statistics of the same interval proportion sequence of the block suitable plant, the initial design scheme is obtained by scheme combination according to the suitable plant comprehensive degree.

[0034] The regional planting scheme is obtained by scheme set of the desertification region according to the initial design scheme.

[0035] Preferably, the process of simulating and optimizing the regional planting scheme by constructing a virtual accompanying space comprises:

[0036] The virtual accompanying space is constructed, the desertification region is mapped to the virtual accompanying space, and the accompanied desertification region is obtained.

[0037] The virtual suitable plant is obtained by virtual mapping of the block suitable plant through the virtual accompanying space.

[0038] The virtual suitable plant is obtained by virtual mapping of the block suitable plant through the virtual accompanying space.

[0039] Based on the above-mentioned desertification prevention and control system based on plant cultivation, the present application also provides a desertification prevention and control method based on plant cultivation, comprising the following steps:

[0040] Step one: collect plant comprehensive data, collect desertification area desert geological data, and divide desert blocks;

[0041] Step two: preliminary processing of desert geological data, obtaining local quantitative base section, according to the local quantitative base section, the graph is replaced, and the quantitative coefficient dynamic graph is obtained;

[0042] Step three: according to the desert division block, the initial matching of the plant comprehensive data is carried out, the matching curve plant data is obtained, the matching curve plant data is covered, and the interval matching proportion is obtained;

[0043] Step four: through the interval matching proportion, the scheme of the block suitable plant is constructed, the regional planting scheme is obtained, the virtual accompanying space is constructed, the regional planting scheme is simulated and optimized, and the best planting plan is obtained.

[0044] Compared with the prior art, the beneficial effects of the present application are:

[0045] The desertification area is divided into different geological feature partial blocks, the plant species suitable for planting is matched according to the geological environment characteristics of different desert blocks, the optimization of resource allocation and resource utilization efficiency is improved according to the geological environment characteristics of different blocks; at the same time, by reasonably selecting the plant species, the pressure on the soil, water resources and other environment can be reduced, and the risk of environmental damage can be reduced;

[0046] 2, according to the suitable planting plant of each desert block, all the planting schemes of the desertification area are generated, the virtual accompanying space is constructed to simulate the generated planting scheme, and the planting prevention and control effect is monitored, so as to obtain the planting scheme with the best prevention and control effect, the cost of actual planting test can be reduced through virtual simulation, the potential effect of different schemes can be predicted before actual planting, so as to reduce the risk of failure, at the same time, a large number of planting schemes can be quickly generated and tested, and the speed of screening and optimizing the scheme is improved. BRIEF DESCRIPTION OF DRAWINGS

[0047] In order to more clearly illustrate the technical scheme in the embodiments of the present application or the prior art, the drawings needed to be used in the embodiments or the prior art description will be briefly introduced below, and obviously, the drawings in the following description are only some embodiments of the present application, and those skilled in the art can obtain other drawings according to these drawings without creating any creative labor.

[0048] Figure 1 The schematic diagram of the present application. DETAILED DESCRIPTION

[0049] The technical solutions of the present application will be described clearly and completely below in connection with the embodiments, obviously, the described embodiments are only some of the embodiments of the present application, not all. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the present application.

[0050] As Figure 1 shown, a desertification prevention and control system based on plant cultivation includes a control center connected with a regional acquisition module, an information processing module, a desert analysis module and an intelligent prevention and control module.

[0051] The regional acquisition module is used to acquire plant comprehensive data, acquire desert geological data of a desertification region, and divide desert blocks.

[0052] The information processing module is used to preliminarily process the desert geological data to obtain a local quantitative base section, replace a graph of a land quality coefficient according to the local quantitative base section, and obtain a quantitative coefficient dynamic graph.

[0053] The desert analysis module is used to initially match the plant comprehensive data according to the desert blocks to obtain matching curve plant data, perform coverage determination on the matching curve plant data, and obtain an interval matching proportion.

[0054] The intelligent prevention and control module is used to construct a scheme for suitable plants in a block according to the interval matching proportion to obtain a regional planting scheme, simulate and optimize the regional planting scheme by constructing a virtual accompanying space, and obtain an optimal planting plan.

[0055] In actual application, desertification refers to a process in which land productivity decreases, soil fertility degrades and vegetation coverage decreases, leading to gradual desertification of land. Desertification prevention and control is of great significance for maintaining ecological balance of the earth and ensuring human survival and development. In particular, by plant cultivation, vegetation coverage is increased, sand dunes are fixed, soil erosion is reduced, intelligent green prevention and control is performed, plant comprehensive data is acquired, a planting scheme corresponding to a desertification region is generated, and an optimal planting scheme is analyzed and applied to the desertification region to restore desertification land and maintain ecological balance. First, the regional acquisition module is used to acquire plant comprehensive data required for generating a planting scheme, and the specific process includes:

[0056] Desertification region is geologically collected to obtain desert geological data, and the collected desert geological data is time-labeled to obtain collection time.

[0057] The geological collection means collecting geological data of the desertification area to be prevented and treated, for determining different planting schemes for different geological features, and the desert geological data includes soil data, hydrological data, climate data, topographic data and ecosystem data;

[0058] The desertification area is divided geologically according to the obtained desert geological data, to obtain desert division blocks;

[0059] The obtained desert geological data is associated with the corresponding desert division blocks;

[0060] The geological division means that according to the desert geological data collected in the desertification area, a block of the same geological data can be divided into a block, which is recorded as a desert division block, indicating that the desert geological data in the desert division block is the same. For example, according to the soil data in the desert geological data, the area is divided into sandy desertification area, loamy desertification area and clay desertification area. According to the topographic data, the desert division area can be divided into plain area, hilly area and mountainous area. In particular, the planting scheme of each block will be developed according to its specific environmental characteristics to ensure that plants can adapt to local growth conditions and improve the treatment effect;

[0061] The cultivated plants are matched and collected based on the desertification area through the desert geological data, to obtain plant comprehensive data;

[0062] The cultivated plants means all plants that can be planted in the desertification area for desertification prevention and treatment, and the matching collection means collecting all comprehensive information of the cultivated plants, which is recorded as plant comprehensive data, including plant species, growth environment requirements, reproduction methods, ecological value, planting adaptive geology and disease and pest resistance. The planting adaptive geology means the type of land suitable for planting the plant, and the growth environment requirements means the necessary environmental material conditions for the normal growth of the plant.

[0063] The process of preliminarily processing the desert geological data to obtain a local quantitative base section includes:

[0064] The prevention and treatment cycle is set according to the obtained collection time, and the prevention and treatment cycle includes a plurality of collection times and is a pre-set time period;

[0065] The obtained desert geological data is quantified and replaced based on the desert division blocks according to the prevention and treatment cycle, to obtain a geological quantization coefficient;

[0066] The quantization replacement represents screening data related to plant planting in the obtained desert geological data and converting into signal form, i.e. into a land quality quantization coefficient, wherein the data related to plant planting includes climate data, soil data, water resource data, which are screened from soil data, hydrological data, climate data, topographic data and ecosystem data included in the desert geological data, the climate data includes but is not limited to temperature, precipitation, evaporation, light period, the soil data includes but is not limited to soil structure type, pH, fertility, salt content, the water resource data includes but is not limited to available fresh water amount, underground water level, irrigation amount; and the land quality quantization coefficient includes climate quantization coefficient, soil quantization coefficient, water resource quantization coefficient; in particular, the generated land quality quantization coefficient includes all the desert geological data collected in a prevention period, i.e. the desert geological data at each collection time point in the prevention period is represented as a sampling point of the signal, for example, taking temperature data as an example, the land quality quantization coefficient of temperature represents that the temperature at each collection time point in the prevention period is a sampling point of the signal;

[0067] Further, according to the desert geological data obtained by each geological collection, there is a corresponding land quality quantization coefficient, i.e. for different collection times, there are different land quality quantization coefficients;

[0068] An extraction quantization basis is set, and the extraction quantization basis is in the form of a function, and a suitable wavelet function is selected according to the signal characteristics of the land quality quantization coefficient, wherein the wavelet function includes but is not limited to Haar wavelet, Morlet wavelet and Coiflets wavelet;

[0069] The obtained extraction quantization basis is subjected to a limited transformation to obtain a transformation parameter;

[0070] The limited transformation represents controlling the extraction quantization basis to perform stretching and translation transformation in the time dimension and the frequency dimension, and the distance of the stretching and translation transformation is counted to obtain the transformation parameter;

[0071] The extraction quantization basis is locally divided according to the obtained transformation parameter to obtain a local quantization basis segment;

[0072] The local division represents equally dividing the extraction quantization basis according to the transformation parameter to obtain local quantization basis segments with equal lengths, and the number of the local quantization basis segments is equal to the transformation parameter.

[0073] The local quantization basis segment is obtained, and the land quality quantization coefficient is extracted according to the obtained local quantization basis segment to obtain a local quantization coefficient;

[0074] The docking extraction represents that the local quantization base segments are respectively folded with the ground quality coefficient according to the order of local segmentation, until all the local quantization base segments are folded with the ground quality coefficient, the obtained local quantization coefficient segments are summed based on the ground quality coefficient, and the local quantization coefficient is obtained, wherein the corresponding folding represents that the local quantization base segment is convolved with the ground quality coefficient;

[0075] Further, there is a corresponding local quantization coefficient for each ground quality coefficient;

[0076] Based on the control cycle, the obtained local quantization coefficient is subjected to numerical graph evolution to obtain a quantization coefficient dynamic graph, and the quantization coefficient dynamic graph is subjected to curve marking to obtain a quantization coefficient curve;

[0077] The numerical graph evolution represents that all local quantization coefficients corresponding to the collection time are converted into signal curves in the control cycle, which are denoted as quantization coefficient curves, and the converted quantization coefficient curves are uploaded into the same two-dimensional rectangular coordinate system to obtain a quantization coefficient dynamic graph, wherein the horizontal axis of the two-dimensional rectangular coordinate system represents the collection time, and the intersection point of each collection time point and the quantization coefficient curve represents the sampling value;

[0078] In particular, for the same desert division block, one quantization coefficient dynamic graph is generated in one control cycle, that is, the quantization coefficient dynamic graph corresponding to the desert division block includes signal curves of all local quantization coefficients corresponding to climate data, soil data, and water resource data, such as temperature quantization coefficient curve, precipitation quantization coefficient curve, evaporation quantization coefficient curve, and light period quantization coefficient curve.

[0079] The desert analysis module is used to initially match the plant comprehensive data according to the desert division block to obtain matching curve plant data, and to perform coverage determination on the matching curve plant data to obtain an interval matching proportion, and the specific process includes:

[0080] Obtain the desert geological data corresponding to the desert division block, and perform conditional screening on the obtained desert geological data to obtain an environment suitable background, wherein the conditional screening represents that the soil data and climate data suitable for planting plants are screened out from the desert geological data corresponding to the desert division block, that is, the environment suitable background, including but not limited to soil chemical properties, soil physical properties, block temperature, precipitation, and evaporation;

[0081] According to the obtained environment suitable background, the plant comprehensive data is classified to obtain a block suitable plant;

[0082] The adaptive classification representation matches the suitable plant comprehensive data according to the obtained environment suitable background, that is, the block suitable plant, but the specific planting density and planting requirements are uncertain, so it is necessary to generate a suitable planting scheme according to the block suitable plant for the desert division region; for example, according to the desert division region of the desert geological data, it is a mountainous area, and combined with the environment suitable background of the mountainous area, if the mountainous area is a saline-alkali block, then the plants that can be matched to the suitable plants in the plant comprehensive data can be red willow, sea buckthorn, and sand date;

[0083] Obtain the quantization coefficient dynamic graph, limit the obtained quantization coefficient dynamic graph, and obtain the curve fluctuation interval;

[0084] The limit representation indicates that the fluctuation range of each quantization coefficient curve in the quantization coefficient dynamic graph is counted, that is, the highest point and the lowest point of the quantization coefficient curve are marked, and two straight lines parallel to the horizontal axis are drawn from the highest point and the lowest point of the quantization coefficient curve, respectively. The interval range between the two straight lines is recorded as the curve fluctuation interval, and each quantization coefficient curve has a corresponding curve fluctuation interval. According to a plurality of curve fluctuation intervals, the planting scheme suitable for the desert division block can be determined;

[0085] Obtain plant comprehensive data, and match the block suitable plant according to the obtained curve fluctuation interval, to obtain matched curve plant data;

[0086] The category matching indicates that the curve fluctuation interval of the quantization coefficient curve corresponding to the different categories of desert geological data collected according to the desert division block is obtained. The category of the curve fluctuation interval corresponding to the desert geological data is matched with the category matched in the plant comprehensive data contained in the block suitable plant. For each curve fluctuation interval, the corresponding matching curve plant data of the plant can be matched; for example, the temperature corresponding curve fluctuation interval matches the temperature requirement in the growth environment requirement of the plant comprehensive data of sea buckthorn, that is, the temperature requirement in the growth environment requirement in the plant comprehensive data is recorded as the matching curve plant data.

[0087] According to the obtained curve fluctuation interval, the matching curve plant data is determined, and the interval matching proportion is obtained;

[0088] It needs to be further explained that in the specific implementation process, the coverage determination indicates that the curve fluctuation interval and the corresponding matching curve plant data are calculated for the coincidence degree proportion, that is, the percentage of the matching curve plant data in the curve fluctuation interval. By converting the matching curve plant data into the same data form as the curve fluctuation interval corresponding to the quantization coefficient curve, that is, the plant quantization curve, the specific process includes:

[0089] Quantize the obtained matching curve plant data, and obtain the matching plant coefficient;

[0090] obtaining a local quantitative base section, performing docking extraction on the matching plant coefficient according to the obtained local quantitative base section, and obtaining a local matching coefficient;

[0091] performing numerical-graph evolution on the local matching coefficient through the quantitative coefficient dynamic graph, obtaining a plant quantitative curve, and uploading the obtained plant quantitative curve to the quantitative coefficient dynamic graph, wherein the plant quantitative curve represents a signal curve in the same form as the quantitative coefficient curve generated according to the local matching coefficient in the quantitative coefficient dynamic graph, that is, the plant quantitative curve;

[0092] performing overlapping statistics on the plant quantitative curve through the curve fluctuation interval, and obtaining an interval matching proportion;

[0093] The overlapping statistics represent that the plant quantitative curve and the corresponding curve fluctuation interval are compared in range, and the curve width corresponding to the part of the plant quantitative curve that is greater than the highest point straight line of the quantitative coefficient curve or less than the lowest point straight line of the quantitative coefficient curve is obtained, that is, the distance of the sampling points corresponding to that part of the plant quantitative curve is recorded as the over-quantitative curve interval, for example, there is part of the plant quantitative curve greater than the highest point straight line of the quantitative coefficient curve between sampling points c1 and c5, then the sampling point width between c1 and c5 is recorded as the over-quantitative curve interval, if the widths of two sections of sampling points are discontinuous, then the widths of the two sections are added to form the over-quantitative curve interval;

[0094] performing global comparison on the plant quantitative curve according to the obtained over-quantitative curve interval, and obtaining an interval matching proportion, wherein the global comparison represents obtaining the starting sampling point and the terminal sampling point of the plant quantitative curve, obtaining the global sampling distance, that is, the width of the plant quantitative curve in the quantitative coefficient dynamic graph, obtaining the interval matching proportion according to the obtained global sampling distance and the over-quantitative curve interval, and recording the obtained interval matching proportion as Z, wherein, , CL represents the over-quantitative curve interval, CJ represents the global sampling distance, the obtained interval matching proportion is expressed in percentage, that is, the obtained interval matching proportion represents the coincidence degree in the desert geological data provided in the desert division block and the plant comprehensive data required by the block suitable plant, for example, taking the curve fluctuation interval corresponding to the temperature in the desert division block as an example, the temperature interval matching proportion of Hippophae rhamnoides is 80%, which means that the temperature requirement of Hippophae rhamnoides suitable for growth can be met in 80% of the range of the desert division block.

[0095] In particular, the obtained interval matching proportion is associated with the corresponding block suitable plant, and for each block suitable plant, there is a corresponding interval matching proportion for each type of plant comprehensive data, which represents the coverage degree of the desert geological data corresponding to the desert division block that meets the plant comprehensive data.

[0096] The interval matching proportion is matched to the suitable plant of the obtained block to construct a scheme, and a regional planting scheme is obtained;

[0097] It needs to be further explained that in the specific implementation process, the scheme construction means generating all possible and plantable plant schemes in the desert block according to the different interval matching proportions of each block suitable plant, and the specific process includes:

[0098] The interval matching proportion is matched to the suitable plant of the obtained block to construct a scheme, and a regional planting scheme is obtained;

[0099] The position sorting means sorting the same type of interval matching proportion in descending order to obtain the same type of interval matching proportion sequence, that is, the same type of interval matching proportion sequence is the different block suitable plant corresponding to the same type of interval matching proportion, for example, for the temperature same type of interval matching proportion sequence, the sorting is the temperature interval matching proportion of different plant species, which represents the sorting of the matching degree of the required growth temperature of different plant types and the desert block, the earlier the sorting, the more suitable the temperature conditions provided by the desert block interval meet the temperature growth conditions required by the block suitable plant, and the more suitable it is to be planted in the block;

[0100] The same type of interval matching proportion sequence of the block suitable plant is ranked and counted to obtain the comprehensive degree of the suitable plant, and the ranking and counting means that the ranking of the same type of interval matching proportion sequence of the same block suitable plant is counted according to the order of the same type of interval matching proportion sequence, and the sum of the counted rankings is summed to obtain the comprehensive degree of the suitable plant, and the comprehensive degree of the suitable plant is denoted as , i represents the number of block suitable plants, that is, different types of plants, i = 1, 2, 3, …, u, u is a positive integer; for example, the temperature same type of interval matching proportion sequence of Hippophae rhamnoides Linn. is ranked as m1, the humidity same type of interval matching proportion sequence is ranked as m2, the pH same type of interval matching proportion sequence is ranked as m3, and the remaining same type of interval matching proportion sequences are ranked as m4, m5, m6, m7, …, v, wherein v represents the total number of same type of interval matching proportion sequences, then the comprehensive degree of the suitable plant of Hippophae rhamnoides Linn. = m1+m2+m3+m4+…+v;

[0101] According to the obtained suitable plant comprehensive degree, a scheme combination is performed to obtain an initial design scheme, the scheme combination representing that a plant species required to be planted in the desert division block is obtained according to the suitable plant comprehensive degree of each block suitable plant, that is, the initial design scheme, wherein the combination is performed to represent that all suitable plant comprehensive degrees are sorted in descending order to obtain a suitable comprehensive degree sequence, and a corresponding block suitable plant is selected in sequence according to the order of the suitable comprehensive degree sequence to generate a planting scheme, that is, the initial design scheme, for example, the known suitable comprehensive degree sequence is Haloxylon ammodendron, Hippophae rhamnoides, Salix psammophila, Populus euphratica, flower stick and Elaeagnus angustifolia, and the initial planting scheme has six kinds, and the desert division block plants Haloxylon ammodendron, Hippophae rhamnoides, Salix psammophila, Populus euphratica, flower stick and Elaeagnus angustifolia, and each plant generates one initial design scheme;

[0102] According to the initial design scheme, a scheme set is performed on the desert division block in the desertification area to obtain a regional planting scheme; then for each desert division block, there are several initial design schemes, and then for several desert division blocks included in the desertification area, different planting schemes can be composed, that is, each desert division block selects one initial design scheme to jointly compose the regional planting scheme of the desertification area, for example, the desertification area is divided into three desert division blocks w1, w2 and w3, there are 6 initial design schemes for w1, 4 initial design schemes for w2, and 5 initial design schemes for w3, and then the desertification area can generate 6*4*5=120 regional planting schemes in total, and then for so many schemes, further screening is required to obtain the most suitable planting scheme for the desertification area, and the planting details inside each regional planting scheme are different, and different planting details will also affect the planting effect, so it is required to simulate the regional planting scheme and adjust various details in the regional planting scheme to obtain the best planting effect, so as to obtain the planting scheme with the best prevention and control effect, wherein the planting details represent the change of the planting condition of the same scheme species in different blocks, for example, the planting details are the change of planting density, the change of planting length, the change of irrigation water quantity and the change of planting cost;

[0103] A virtual accompanying space is constructed to simulate and optimize the regional planting scheme to obtain the best planting plan;

[0104] It needs to be further explained that in the specific implementation process, the simulation and optimization process includes:

[0105] The virtual accompanying space is constructed, and the virtual accompanying space is a virtual space capable of simulation, and provides space for the simulation planting of the regional planting scheme of the desertification area;

[0106] The obtained desertification area is mapped to a virtual accompanying space to obtain an accompanying desert area, the accompanying desert area is marked based on a desert division block to obtain an accompanying division block, the accompanying desert area represents a virtual area that is completely identical to the structure and function of the desertification area in reality in the virtual accompanying space, and the position of the desert division block is marked as the accompanying division block;

[0107] The block suitable plants are virtually mapped through the virtual accompanying space to obtain virtual suitable plants, which represent that all block suitable plants in the regional planting scheme are converted into the virtual accompanying space, facilitating scheme simulation, and the function and structure of the virtual suitable plants are completely identical to those of the block suitable plants in reality;

[0108] The accompanying desert area is simulated and planted based on the virtual suitable plants and the regional planting scheme to obtain an adjusted regional planting scheme, the obtained adjusted regional planting scheme is monitored for effect to obtain a virtual cultivation effect, and the obtained virtual cultivation result is optimized and screened based on the virtual accompanying space to obtain an optimal planting plan;

[0109] The simulated planting represents that the virtual suitable plants corresponding to the regional planting scheme are placed in the corresponding accompanying division block in the order of the obtained regional planting scheme, and the planting details are adjusted according to the desert geological data of the desert division block and the plant comprehensive data of the virtual suitable plants, and the planting details of each adjustment are recorded as an adjusted regional planting scheme, for example, the first regional planting scheme generated for the desertification area can be adjusted g times according to the desert geological data and the plant comprehensive data, and then the g adjusted regional planting schemes are recorded and marked as the adjusted regional planting scheme, such as changing the planting density of the virtual suitable plants, changing the planting density under the premise of meeting the desert geological data of the desert division block and the plant comprehensive data of the virtual suitable plants, and each change is recorded as an adjusted regional planting scheme;

[0110] The effect of the adjusted regional planting scheme is monitored through the virtual accompanying space to obtain a virtual cultivation effect, wherein the effect monitoring represents that the plant planting control effect is recorded after the adjusted regional planting scheme is implemented in the accompanying desert area in the virtual accompanying space, the planting control effect includes but is not limited to vegetation coverage, soil erosion rate, soil moisture content, plant diversity, greenhouse gas emission, water use efficiency, and economic benefit; in particular, the obtained virtual cultivation effect is recorded in the form of scores, and is scored based on a full score of 100 points, for example, the vegetation coverage of a certain adjusted regional planting scheme of the accompanying desert area is 70 points, the soil erosion rate is 68 points, the soil moisture content is 89 points, and the plant diversity is 88 points;

[0111] The obtained virtual cultivation effects are ranked in descending order to obtain a same-effect sequence, which represents the ranking of the scores of one virtual cultivation effect of the different adjustment area planting schemes, and for the same-effect sequence of the vegetation coverage, it is the ranking of the vegetation coverages of all the adjustment area planting schemes;

[0112] The best planting plan is obtained by analogy screening of the same-effect sequence based on the adjustment area planting scheme;

[0113] The analogy screening means that the rankings of the virtual cultivation effects of all the same-effect sequences of the adjustment area planting scheme are obtained, and the rankings are summed to obtain a planting effect degree, wherein the planting effect degree is the sum of the rankings of different virtual cultivation effects in the corresponding same-effect sequence;

[0114] The obtained planting effect degree is associated with the corresponding adjustment area planting scheme, the planting effect degrees are ranked in descending order, and the adjustment area planting scheme corresponding to the first-ranked planting effect degree is recorded as the best planting plan.

[0115] Based on the above-mentioned desertification prevention and control system based on plant cultivation, the application further provides a desertification prevention and control method based on plant cultivation, comprising the following steps:

[0116] Step one: collecting plant comprehensive data, collecting desert geological data of the desertification area, and dividing the desert into blocks;

[0117] Step two: preliminarily processing the desert geological data to obtain a local quantitative base section, replacing the graph of the geological quantization coefficient according to the local quantitative base section, and obtaining a quantization coefficient dynamic graph;

[0118] Step three: initially matching the plant comprehensive data according to the desert division blocks to obtain matching curve plant data, performing coverage determination on the matching curve plant data to obtain an interval matching proportion;

[0119] Step four: constructing a scheme for the block suitable plants through the interval matching proportion to obtain a regional planting scheme, simulating and optimizing the regional planting scheme by constructing a virtual accompanying space to obtain a best planting plan.

[0120] The preferred embodiments disclosed above are only used to help explain the application. The preferred embodiments do not describe all the details, nor limit the application to the specific implementation. Obviously, according to the content of the specification, many modifications and changes can be made. The specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the application, so that those skilled in the art can well understand and utilize the application. The application is limited by the claims and their entire scope and equivalents.

Claims

1. A desertification control system based on plant cultivation, comprising a control center, characterized in that, The control center is connected to a regional data acquisition module, an information processing module, a desert analysis module, and an intelligent prevention and control module. The regional data acquisition module is used to collect comprehensive plant data, collect desert geological data of desertified areas, and divide desert areas into blocks. The information processing module is used to perform preliminary processing on desert geological data to obtain local quantitative base segments, and to perform graphical replacement on the geological quantification coefficients based on the local quantitative base segments to obtain dynamic graphs of quantification coefficients. The desert analysis module is used to perform initial matching of comprehensive plant data according to desert division blocks, obtain matching curve plant data, perform coverage determination on matching curve plant data, and obtain interval matching ratio. The intelligent prevention and control module is used to construct a plan for suitable plants in a block by matching the proportion of intervals, obtain a regional planting plan, construct a virtual accompanying space to simulate and optimize the regional planting plan, and obtain the best planting plan.

2. The desertification control system based on plant cultivation according to claim 1, characterized in that, The process of collecting comprehensive plant data and desert geological data includes: Geological data was collected from desertified areas to obtain desert geological data, and the collected desert geological data was time-stamped to obtain the collection time. Based on desert geological data, desertification areas are geologically divided to obtain desert division blocks; Based on desertification areas, cultivated plants are matched and collected using desert geological data to obtain comprehensive plant data.

3. A desertification control system based on plant cultivation according to claim 2, characterized in that, The preliminary processing of desert geological data includes: The prevention and control cycle is set according to the collection time. Based on the prevention and control cycle, the desert geological data is quantified and replaced by dividing the desert into blocks to obtain the geological quantification coefficient. Set the extraction quantitative base, apply a limiting transformation to the extraction quantitative base, and obtain the transformation parameters; The extracted quantitative base number is locally segmented based on the transformation parameters to obtain local quantitative base number segments.

4. A desertification control system based on plant cultivation according to claim 3, characterized in that, The process of graphically replacing geological quantification coefficients based on local quantitative base segments includes: Obtain local quantitative base segments, and extract geological quantitative coefficients based on these segments to obtain local quantitative coefficients. Based on the prevention and control cycle, the local quantitative coefficient is transformed into a digital graph to obtain a dynamic graph of the quantitative coefficient. The dynamic graph of the quantitative coefficient is then marked with curves to obtain the quantitative coefficient curve.

5. A desertification control system based on plant cultivation according to claim 4, characterized in that, The process of initial matching of plant data based on desert area division includes: Obtain desert geological data corresponding to the desert division blocks, filter the desert geological data according to conditions, and obtain environmentally suitable backgrounds; Based on the suitable environmental background, the comprehensive plant data is adapted and classified to obtain suitable plants for the block; Limit the dynamic graph of the quantification coefficient to obtain the curve fluctuation range, and match the suitable plant species in the block according to the curve fluctuation range to obtain the matching curve plant data.

6. A desertification control system based on plant cultivation according to claim 5, characterized in that, The process of determining the coverage of plant data based on the matching curve includes: The plant data of the matching curve is quantified and replaced to obtain the matching plant coefficient. The matching plant coefficient is then extracted based on the local quantitative base segment to obtain the local matching coefficient. The local matching coefficients are transformed by a dynamic graph of quantification coefficients to obtain the plant quantification curve, and the obtained plant quantification curve is uploaded to the dynamic graph of quantification coefficients. By performing overlap statistics on plant quantitative curves within the curve fluctuation range, the interval matching ratio is obtained.

7. A desertification control system based on plant cultivation according to claim 6, characterized in that, The process of constructing a suitable plant scheme for a block based on the proportion of interval matching includes: Based on the suitable plants in each block, the interval matching ratio is sorted by position to obtain a sequence of interval ratios of the same type; Ranking and statistically analyzing the proportion of similar suitable plants in the block to obtain the comprehensive suitability score, and combining schemes based on the comprehensive suitability score to obtain the initial design scheme; Based on the initial design scheme, the desert area is divided into blocks, and a set of schemes is obtained to obtain regional planting schemes.

8. A desertification control system based on plant cultivation according to claim 7, characterized in that, The process of constructing a virtual accompanying space to simulate and optimize regional planting schemes includes: Construct a virtual accompanying space, map the desertified area to the virtual accompanying space, and obtain the accompanying desert area; Virtual suitable plants are obtained by virtually mapping suitable plants in the block using a virtual accompanying space; Based on the regional planting scheme, the planting of suitable virtual plants is simulated in the desert area to obtain the regional planting scheme. The effect of the obtained regional planting scheme is monitored to obtain the virtual cultivation effect. Based on the virtual accompanying space, the obtained virtual cultivation results are optimized and screened to obtain the best planting plan.

9. A desertification control method based on a plant cultivation-based desertification control system according to any one of claims 1 to 8, characterized in that, Includes the following steps: Step 1: Collect comprehensive plant data, collect desert geological data of desertified areas, and divide desert areas into blocks; Step 2: Perform preliminary processing on desert geological data to obtain local quantitative base segments. Based on the local quantitative base segments, perform graphical replacement on the geological quantification coefficients to obtain a dynamic graph of the quantification coefficients. Step 3: Perform initial matching of plant data based on desert area division to obtain matching curve plant data, and determine the coverage of matching curve plant data to obtain the interval matching ratio. Step 4: Construct a plan for suitable plants in the block by matching the proportion of intervals, obtain a regional planting plan, construct a virtual accompanying space to simulate and optimize the regional planting plan, and obtain the best planting plan.

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