113 results about "Land management" patented technology

The invention discloses a rural land utilization evaluation system and method, and relates to the technical field of land management, and the system comprises a spatial analysis module which obtains a spatial distance value, a land utilization type value and a regional distribution value based on a land unit division result, carries out the superposition calculation of a spatial incidence relation matrix, and extracts the conflict intensity. According to the method, through comprehensive calculation of the spatial distance, the land utilization type and the regional distribution, the land conflict intensity and the dynamic characteristics thereof are quantitatively analyzed, the problem that the land resource conflict distribution is not clearly identified is solved, in the dynamic prediction process, the land dynamic characteristics are quantified through space and ecological connectivity difference operation, and the prediction accuracy is improved. According to the method, land utilization change requirements, economic value and ecological connectivity normalization processing and weighted calculation are effectively coped with, dynamic balance of economic benefits and ecological protection is achieved, limitation of single-dimension evaluation is avoided, and reasonable allocation of land resources is strengthened by adjusting the proportion of economic and ecological parameters through optimization verification and reducing evaluation deviation.

The invention relates to the technical field of urban planning, and particularly discloses an urban planning construction land management and control system based on big data, and the system comprises the steps: obtaining geological environment, landform, engineering construction and human activity data through multi-source data collection; multi-source data fusion analysis is adopted to construct a construction land comprehensive evaluation field including geological stability, engineering suitability and environmental bearing capacity; a development suitability partition is generated based on a density peak value spatial clustering method; updating the development suitability level by dynamically monitoring the verification process; according to the method, accurate analysis and early warning of the three-dimensional deformation field are realized, and scientificity and safety of urban planning in a complex geological environment are improved.

The invention discloses a dynamic black land soil nutrient prediction system based on satellite remote sensing and multi-source data fusion, and relates to the field of artificial intelligence, and the system comprises a data collection module which obtains multi-source data of black land soil, including satellite remote sensing data, ground sensor data, meteorological data and historical soil nutrient data; the feature extraction module is used for extracting feature information of soil nutrients; the prediction model module is used for constructing a soil nutrient dynamic prediction model and accurately predicting the soil nutrient dynamic state; the feedback optimization module is used for optimizing and updating the prediction model, continuously improving the performance of the model, improving the prediction precision and obtaining an optimized prediction model; the visualization module is used for visually displaying a prediction result, displaying spatial and temporal distribution of soil nutrients in the form of a map and a chart, and providing strategy support of fertilization suggestions and land management; according to the data storage and management module, a database stores different types of data, efficient query, updating and maintenance of the data are achieved, and the safety of the soil nutrient dynamic data is improved.

The invention provides an after-batch stock land data management method and system. The method comprises the steps of designing an after-batch stock land management database structure, and constructing a land supply data graph layer, a batch land data graph layer, a batch land data graph layer, a batch unsupplied land data graph layer, an overdue working land data graph layer and an idle land data graph layer; collecting multi-source data, performing preprocessing, problem treatment and quality inspection, and generating standardized land supply data and land batch data; constructing a land supply and approval database, and comparing and updating the land supply and approval database with data of a natural resource department system; generating a batch of unsupplied land, an overdue working land and an idle land data graph layer through overlay analysis, and constructing a batch stock land database; automatically updating graph and attribute data based on data such as territorial change investigation and the like; the functions of automatic reminding, land use unit interaction and space query are executed; and carrying out visual rendering and display on the database data, and superposing and displaying the batch stock land and planning and remote sensing image data. According to the invention, the intensive land utilization supervision efficiency can be improved.

The invention discloses an urban green land plant growth state monitoring and analyzing system and method, relates to the technical field of big data analysis, and can accurately track the health condition of plants in each sub-region and improve the scientificity and effectiveness of urban green land management through detailed region division and coordinate marking. By means of the plant growth simulation model and the ideal environment growth model which are constructed through the neural network, the system can dynamically predict the plant growth state and conduct personalized management on plant growth conditions in different areas. Various collection means such as environmental factors and remote sensing data are integrated, the growth state of urban green land plants is comprehensively monitored, and the limitation of a traditional method is overcome. By setting the state abnormality threshold and combining the growth deviation trend chart, the system can realize a real-time early warning mechanism, quickly identify potential growth abnormality and ensure that problems are found and solved in time, so that the monitoring error of the remote sensing technology is reduced, and the management efficiency is improved.

The invention relates to the technical field of land treatment, in particular to an organic fertilizer for improving the soil fertility of a sand land. Comprising the following raw materials in parts by weight: 3-12 parts of a microbial agent, 20-50 parts of volcanic rock, 5-12 parts of an additive, 32-45 parts of sodium bentonite, 12-18 parts of a functional agent, 5-25 parts of a modifier and 15-32 parts of a water retention material. By increasing organic matters in the soil, the viscosity of the soil is improved, the air permeability, water retention and permeability of the soil are improved, the formation of a soil aggregate structure is promoted, and the water and fertilizer retention capability of the sand soil is improved.

The invention discloses a mining area fine land identification method based on multi-mode fusion and first inflection point constraint. The method comprises the following steps: step A, downloading a research area satellite remote sensing image, constructing a strip mine area space range sample data set, training a DeepLabv3 + deep learning model, and predicting and delineating the maximum space range of a mining area in a research period; step B, acquiring mining area land utilization change data, constructing a time sequence change mode based on a land utilization type transfer relationship, and dividing the time sequence change mode into five types, namely a damaged area, a reclamation area, a reclamation degradation area, a building pressure occupation area and a water body pressure occupation area; and step C, preparing a mining area fine land utilization sample data set, establishing a multi-mode fusion and first inflection point constraint neural network model (MFFIC-Net), training the model to identify mining area annual fine land utilization types, and accurately tracking first transition time information of each type. Compared with the prior art, the mining area land utilization classification is further refined, the proposed MFFIC-Net model fuses long and short term memory and a feedback mechanism, and accurate identification of the land utilization type and the first change time is realized. A feedback mechanism enables the model to self-adjust a prediction result, the precision and the stability are improved, and multi-mode fusion enhances the adaptability of the model to a complex mining area environment. The mining area land utilization identification method provided by the invention is finer and more practical, can effectively identify key areas such as a damaged area, a reclamation area and an occupation area, and provides important technical support for ecological restoration and land management.

The invention discloses an agricultural planting intelligent management method and system based on the Internet of Things, and relates to the technical field of agricultural planting, and the method comprises the following steps: obtaining environment data in a farmland, and carrying out the feature extraction of the environment data, and obtaining environment feature data; analyzing the environment characteristic data by using a factor analysis algorithm to obtain key factors influencing crop growth; and constructing a demand prediction model, and predicting the growth demand of the crops at future moments by using the demand prediction model to obtain the optimal irrigation time and fertilization amount of the crops. According to the method, the environmental characteristic data is analyzed by using a factor analysis algorithm, so that agricultural managers can perform land management and crop planting in a targeted manner, unnecessary resource consumption is avoided, the demand of crops for resources such as water and fertilizer at the future moment can be predicted by constructing the demand prediction model, and the agricultural management efficiency is improved. Agricultural managers are helped to reasonably arrange irrigation and fertilization time, so that the yield and quality of crops are improved.

The invention relates to the technical field of soil remediation and saline-alkali soil treatment, and discloses a nano-carbon-based slow-release saline-alkali soil conditioner and a gradient controlled release method thereof.The formula comprises a layered nano-carbon matrix, a humic acid intercalation compound, a pH response type cross-linking agent, a calcium ion modifier and a phosphate radical modifier; the method comprises the following steps: constructing a self-regulation repair system for synchronously optimizing salt reduction, nutrient supply and ion balance through a three-dimensional synergistic mechanism of pH response type sodium ion targeted adsorption, microbial activity driven nutrient controlled release and calcium-sodium dynamic replacement. A nano carbon-humic acid layered composite structure is used for synergic desalination and slow-release fertilizer supply, a Ca < 2 + >-PO4 < 3-> gradient ion replacement system is combined for synchronous salt reduction and structure fixation, a pH response coating technology is used for realizing accurate release of nutrients triggered by microbial activity, and a three-dimensional interpenetrating network and graded pores are used for guaranteeing the long-acting stability of the material. And finally, multiple repairing functions are integrated into a single material.

The invention discloses a target area low-efficiency land extraction method and system based on multi-source big data, and belongs to the field of land management.The extraction method comprises the following specific steps that P1, data are collected from multiple sets of data sources in real time, all kinds of collected multi-source data are preprocessed, and then feature information of all kinds of preprocessed multi-source data is extracted; p2, based on the extracted various feature information, establishing a land use characterization matrix, and according to the established land use characterization matrix, establishing a low-efficiency land use discrimination model; according to the method, the land utilization condition can be depicted from multiple angles, the recognition accuracy and the feature extraction accuracy are improved, meanwhile, the low-efficiency land use recognition accuracy is improved, the terminal calculation cost is reduced, real-time updating and optimization are achieved, and the method can meet the land management requirements of different regions and cities.

The invention discloses an urban green land fine classification method based on a high-resolution remote sensing image. The method comprises the following steps: S1, obtaining a VHR image and monthly Sentinel-2 remote sensing time sequence data; s2, obtaining a greenbelt boundary sample and a greenbelt type sample according to the VHR image and monthly Sentinel-2 remote sensing time sequence data; s3, performing land parcel semantic segmentation on the greenbelt boundary sample to obtain urban greenbelt land parcels, and performing land parcel super-pixel segmentation to obtain super-pixel land parcels so as to obtain greenbelt classification land parcels; s4, performing plot time sequence feature extraction on the green land type samples to obtain time sequence feature pixels; s5, performing morphological feature calculation on the classified land parcels of the green land to obtain a land parcel morphological feature subset, and performing feature engineering extraction on the time sequence feature pixels to obtain a land parcel time sequence element feature subset; and S6, carrying out urban green land fine category classification by adopting a classifier to obtain a classification result. According to the method, fine classification can be accurately carried out on the urban green land, and technical support is provided for urban green land management and ecological protection in the future.

The invention relates to the technical field of land management and carbon circulation, and discloses a soil organic carbon estimation method based on a random forest and a lightweight gradient elevator. Soil organic carbon estimation is used as an entry point of carbon balance treatment and climate regulation, multiple machine learning model technologies are integrated, influence factors of soil data are mined and analyzed, and a soil organic carbon estimation model set is constructed and evaluated and analyzed, so that the soil organic carbon is estimated. A set of space-time adaptability model evaluation technical method integrating multi-source data and incorporating climatic factors is innovatively developed. According to the method provided by the invention, the generalization ability and the stability of the machine learning evaluation model are optimized, so that the precision and the efficiency of soil organic carbon estimation are improved, and a more accurate and efficient application method is provided for soil organic carbon estimation under different regions and environment conditions.

The invention provides a land full-life-cycle management knowledge graph construction and reasoning method, which comprises the following steps of: designing a mode layer of a land full-life-cycle management knowledge graph, and defining entities and relation expressions of the knowledge graph by utilizing the mode layer; carding related data into an entity and relation expression form, and constructing a land full life cycle management knowledge graph; and designing a business reasoning process based on the land full-life-cycle management knowledge graph according to an entity and relationship expression form, obtaining a reasoning result, constructing mode matching and rules, and explaining and optimizing the reasoning result in combination with context information in the land full-life-cycle management knowledge graph. According to the method, analysis and reasoning based on the knowledge graph can be provided for a user, the user is helped to make a more scientific land management decision in a changeable environment, and the value and utility of the knowledge graph in an actual scene are greatly improved.

The invention discloses a remote sensing positioning marking device for land management surveying and mapping, and particularly relates to the technical field of land management surveying and mapping, the remote sensing positioning marking device comprises a base and a mounting seat, the upper end of the base is fixedly connected with a supporting frame, and the inner surface of the base and the inner surface of the supporting frame are jointly provided with a fixing assembly; the upper end of the fixing assembly and the inner surface of the mounting base are jointly provided with a clamping protection assembly. According to the remote sensing positioning and marking device for land management surveying and mapping, through the arrangement of the supporting mechanism and the lifting mechanism, the base and the supporting frame are used for supporting, meanwhile, the height of the supporting frame is correspondingly adjusted, stable positioning and marking can be achieved in different terrains and under the ground, and meanwhile by adjusting the height of the supporting frame, the positioning and marking efficiency is improved. It is ensured that the device is always kept in the optimal working state, surveying and mapping precision and efficiency are improved, supporting force can be stably controlled in a hydraulic mode, equipment deviation or inclination caused by uneven ground is prevented, and surveying and mapping data accuracy and reliability are ensured.

The invention discloses a facility agriculture land use system, and relates to the technical field of facility agriculture land use, and the system comprises a vector data processing unit which generates an initial pattern spot data set with a coincidence degree identifier; the field intelligent proof unit is used for generating a proof data packet with a unique file number; the third-level joint review unit is used for performing third-level review; the structured achievement management unit is used for establishing an associated index and a structured database; and the cross-module data pushing unit is used for outputting an audit completion voucher and realizing a data closed loop. According to the method, a systematic architecture of vector data processing, field intelligent proof, three-level joint review, structured achievement management and cross-module data pushing is constructed, pattern spot extraction, proof verification and trend analysis intelligentization are achieved through an AI algorithm, a typed template, layered review and an automatic pushing mechanism are used, and the system and the method are suitable for large-scale popularization and application. The problems that traditional facility agriculture land management is scattered in data, split in process and low in efficiency are solved, and a traceable integrated management closed loop is formed.

The invention discloses an optimal configuration method for land utilization of a cultivated wasteland in a salinization irrigation area, which mainly comprises two parts of land utilization quantity demand and cultivated wasteland spatial layout, and utilizes a method of coupling a water-salt equilibrium model SALTMOD and a land utilization CLUE-S model. The method comprises the following steps: combining an appropriate tillage and waste land ratio based on irrigation and drainage regulation and control and cultivated land salinity control with land utilization space distribution, and systematically exploring an appropriate salt wasteland space dynamic regulation and control scheme suggestion considering land utilization development and regional salinity income and expenditure balance from quantity constraint and space configuration; certain technical and data support is provided for saline-alkali soil treatment in arid and semi-arid irrigated areas.

The invention discloses a land degradation process and spatial effect analysis method for centralized photovoltaic development in a plateau area. A plurality of ecological system evaluation methods such as a multi-source heterogeneous data set and an improved CASA model are adopted, a plateau surface cover change mechanism and centralized photovoltaic development characteristics are combined, and four types of land degradation processes including land cover, land productivity, desertification and vegetation conditions are selected for single-element evaluation; a comprehensive evaluation framework is constructed based on a new perspective of land degradation balance (LDN). Meanwhile, a buffer area analysis method is introduced to carry out spatial effect evaluation, and land degradation characteristics under different spatial distances are quantified. According to the method, the influence of photovoltaic power station construction on land cover and ecological environment can be comprehensively and deeply evaluated and analyzed, accurate and detailed land degradation analysis information is provided, the optimization of land management and protection strategies is facilitated, and the difficulty of a quantitative characterization method for photovoltaic development ecological environment influence and spatial heterogeneity thereof is solved.

The invention relates to the technical field of land measurement, and provides a land resource land management measuring device which comprises two mounting boxes and a fixing frame, positioning marking assemblies are mounted in the two mounting boxes, sleeves are welded and fixed to the top end faces of the mounting boxes, adjusting rods are slidably connected in the sleeves, and the adjusting rods are movably connected with the fixing frame. A laser range finder is fixed in the fixing frame through bolts, a laser transmitter and a laser receiver are mounted on the laser range finder, a folding protection assembly is mounted in the fixing frame, the positioning marking assembly comprises a storage box and a connecting cylinder, a guide groove is formed in the side end of the connecting cylinder, and a positioning mark is mounted in the guide groove. A center rod and a supporting rod are welded and fixed to the bottom end of the connecting cylinder, a sliding block is hinged to the bottom end of the supporting rod, and the sliding block is slidably connected to the top of the pressing plate in a limited mode. By means of the technical scheme, the problem that in the prior art, a land measurement device cannot conduct automatic and stable fixed-point marking work on the measurement starting point and the measurement end point is solved.

The invention belongs to the field of land planning, and discloses a land space planning-oriented land utilization simulation method and system, electronic equipment and a storage medium, and the method comprises the steps: collecting land utilization form current situation data, social economic data and environmental data, and carrying out the spatialization processing and data preprocessing through a GIS, and obtaining the preprocessed data; constructing a multi-target optimization weight of land utilization planning by using a multi-standard decision analysis method; constructing a land utilization change model based on the GIS, the preprocessed data and the multi-objective optimization weight; and inputting a land utilization form, and performing simulation by using the land utilization change model to obtain a land utilization simulation result. The method is helpful for reasonable planning and utilization of land resources, has important significance for promoting sustainable development, optimizing land resource allocation and improving land utilization efficiency, and also provides powerful scientific support for land management decision.

The invention aims to provide a strip mine soil heavy metal pollution range evaluation method for solving the problems of the existing soil heavy metal pollution range evaluation technology. The method comprises the steps of sampling point arrangement, sampling and detection, vertical depth heavy metal distribution simulation, heavy metal distribution estimation in different depth horizontal extension directions, and heavy metal distribution contour line making. According to the method provided by the invention, the heavy metal distribution conditions of different depths corresponding to different positions of the strip mine pollution source can be obtained according to the known pollutant content information of the soil sampling point, so that the heavy metal distribution isopleth of the soil pollution area in the vertical direction and the horizontal direction is made; and a land treatment mode or a reclamation mode of the mine can be guided through the isoline of heavy metal distribution.

The invention relates to the technical field of soil improvement and ecological restoration, and discloses an ultra-stable mineralization in-situ salt fixation method for improvement of saline-alkali soil in an arid region and application of the ultra-stable mineralization in-situ salt fixation method. The invention provides a method for improving northwest inland saline-alkali soil based on combination of an ultra-stable mineralized in-situ salt-fixing soil conditioner, precise partitioning, biological improvement and salt-tolerant plant planting. According to the method, a salt elimination foundation is created through physical soil preparation, firstly, the soil alkalization degree and the salt content are rapidly reduced through an ultra-stable mineralization in-situ salt fixation soil conditioner, the physical structure of the soil is improved, and then rapid salt elimination and alkali inhibition, fertility cultivation and ecological reconstruction of the saline-alkali soil are finally achieved by constructing different plant planting modes and establishing a stable vegetation system. And a sustainable saline-alkali soil comprehensive treatment mode with good effect and low cost is formed.

The invention discloses a method for evaluating the composite obstacle degree of southern red and yellow soil degraded soil and application. By constructing the southern red and yellow soil composite obstacle index, systematic quantitative evaluation of acid, thin, plate and sticky main soil obstacles is achieved, and the limitation of a traditional single index and a subjective weighting method is broken through. The method is driven by large-scale soil data and has scientificity, objectivity and generalizability. The southern red and yellow soil degraded soil compound obstacle index provided by the invention can reveal dominant obstacle factors formed by compound obstacles, can support agricultural production and land management, and has important significance for soil obstacle diagnosis and agricultural improvement.

The invention relates to the cross technical field of land resource management and information technology, in particular to a land management system and method based on a GIS system and big data analysis, and the system comprises a data layer, a support layer and an application layer. The data layer comprises a multi-source data collection module and a GIS spatial database; the support layer comprises a big data processing engine, a GIS analysis tool set and a machine learning modeling platform, the application layer comprises an intelligent supervision module, a planning auxiliary module and a decision support module, and the system is suitable for intelligent management and decision support of land resource investigation, planning, protection and development of a full life cycle.

The application discloses a kind of based on unmanned aerial vehicle auxiliary land type identification management method and system, it is related to land type identification technical field, including through unmanned aerial vehicle collection land remote sensing image, and processing and feature extraction, strengthen the land type features in image;Land type identification model is constructed, land type identification standard is set, input is according to the land type feature image after strengthening training and analysis, obtain land type identification result;The identification result is rechecked and corrected, according to the land type after correction is authenticated and managed.The application obtains high-resolution ground surface image using unmanned aerial vehicle, can clearly show the detailed features of ground surface, improve identification accuracy, can obtain image at any time and is not affected by factors such as cloud cover, night lighting etc.Improve identification precision, ensure the accuracy of identification result, help land management and planning, have important application value for disaster emergency, environmental protection and other tasks.

This invention presents 8 groundbreaking technique utilizing nano-zeolite, sourced from natural zeolite, natural kaolin, and water treatment sludge, to effectively remediate degraded or acidic soils. Acidic soils pose significant challenges to agricultural productivity, hindering crop growth and nutrient availabili The application of nanozeolite addresses these issues by reducing soil acidity, which fosters a more favorable pH environment for plant development. Additionally, nano-zeolite enhances nutrient retention, ensuring that essential minerals remain accessible to crops. ዘ5 porous structure facilitates improved water retention and aeration, further promoting soil health. This innovative approach not only revitalizes degraded lands but also aligns with sustainable agricultural practices, reducing the reliance on chemical fertilizers and contributing to environmental conservation. By transforming waste materials into a valuable resource, this invention offers a practical solution to soil degradation challenges faced by farmers and land managers.

The present invention provides a digital simulation method for village and town settlements based on cellular automata. First, basic data on village and town settlement development is collected, cleaned, and refined. The decisions and behaviors of various stakeholders are dynamically captured through a multi-agent system and incorporated into a preliminary analysis. These basic data and analysis results are input into a cellular automaton based on machine learning, and ultimately the transformation rules of the cellular automaton are learned. Cell states are iteratively updated according to these rules to simulate and record land behavior changes over time. The land use conversion probability of each cell is calculated, and land use change trends are analyzed. Land development projects are randomly selected using a parallel Monte Carlo method, and the total land supply is determined. Finally, a determination is made as to whether the total supply meets a preset supply threshold. If not, iterative adjustments are made. If so, the results are summarized and visualized. This method provides a systematic, intelligent, and efficient solution for complex land management needs.

The invention provides a seed coating and sowing all-in-one machine for sand control, which belongs to the technical field of agricultural sowing and comprises a frame, an advancing mechanism, a sowing mechanism and a coating mechanism. A traveling mechanism is arranged on the frame, a seeding mechanism is arranged on the frame, the traveling mechanism comprises two traveling wheels which are symmetrically arranged, a rolling wheel is arranged between the two traveling wheels, the rolling wheel is connected with the traveling wheels through a sliding piece, convex blocks are uniformly and fixedly connected to the rolling wheel in the circumferential direction, and the ends, away from the rolling wheel, of the convex blocks are sharp; two auxiliary wheels are symmetrically arranged on the frame, and the seeding mechanism is positioned between the auxiliary wheels and the rolling wheel. The integrated equipment is pulled through an external power source, seed coating and sowing can be carried out at the same time, meanwhile, the rolling wheel can be driven to roll on soil, the soil becomes compact, multi-ridge cultivation can be carried out, and therefore the survival rate of seeds after sowing is increased, and large-area sand land treatment is achieved.

The invention relates to the field of land management, in particular to a land element optimal configuration decision system and method based on artificial intelligence, and the system comprises a land remote sensing module, a region segmentation module, a development prediction module, a virtual merging module and a configuration decision module. The region segmentation module is used for generating development regions and calculating shape coefficients, the development prediction module is used for calculating output efficiency of land grids, the virtual merging module is used for merging adjacent development regions, and the configuration decision module is used for planning development types of conflicting grids. The low-efficiency utilization caused by land dispersion is avoided, the land utilization efficiency is improved, the land development and management cost is reduced, the scientificity and accuracy of land allocation are ensured, and efficient utilization of land resources and coordinated development of the ecological environment are achieved.

The invention relates to the field of hydrological disaster risk assessment, and discloses a man-made signal identification and future estimation method for hydrological drought risks, and the method comprises the steps: collecting data; hydrological drought identification; hydrological drought occurrence probability trend quantification; quantification of contribution of human climate change and human water taking and land management change; human activity signal detection of hydrological drought occurrence probability; hydrological drought attribution risk score quantification; identifying human activity signals in hydrological drought based on a signal-to-noise ratio criterion; the uncertainty source of the future hydrological drought occurrence probability trend is quantified; according to the method, the global hydrological drought occurrence risk change in historical and future periods under the influence of human activities is evaluated, and the human activity signals in the global hydrological drought occurrence risk change are identified, so that the understanding of the global hydrological drought risk change and influence mechanism is enhanced, and a scientific basis is provided for making a hydrological drought disaster prevention and reduction decision.

The utility model discloses a desert and saline-alkali land treatment system. The system comprises a coal gangue powder preparation and air compression system arranged in a coal mine coal gangue storage yard, a coal gangue solid-liquid mixture preparation and application system arranged in desert and saline-alkali soil areas to be treated, and a powder conveying pipeline system for connecting the coal gangue powder preparation and air compression system and the coal gangue solid-liquid mixture preparation and application system. Coal gangue is made into powder through a crusher, a screw feeder, a compressed air station and the like, and the powder is conveyed remotely. A solid-liquid mixture is prepared through powder collection, agent addition, solid-liquid mixing and the like in a treatment area, and then the solid-liquid mixture is applied and scattered through a ditching applying and scattering vehicle, an under-pressure winding and unwinding system and a dragging hose.