78 results about "Forest steppe" patented technology

The invention discloses a forest steppe fire risk assessment method and system, and belongs to the technical field of forest steppe fire prevention. The problem of high false alarm and missing report rate caused by lagging fire risk identification, weak multi-source data fusion and insufficient dynamic response in the prior art is solved. According to the technical scheme, the method comprises the following steps: deploying a ground sensing node array to obtain real-time environment data of a grassland region, fusing high-resolution satellite remote sensing and regional weather forecast data, and constructing a space-time aligned risk assessment data cube; establishing a grassland fire risk factor dynamic coupling model, and dynamically allocating factor weights in combination with the adaptive weight decision tree; generating a comprehensive risk index, carrying out nonlinear mapping to five risk levels, and linking a visual engine to generate a dynamic thermodynamic diagram and push the dynamic thermodynamic diagram to a command terminal; the system supports online updating of the model, and weight parameters are automatically optimized based on a new fire event. According to the invention, high-precision, real-time and spatialized evaluation is realized, the early warning capability and prevention and control decision efficiency are improved, and ecological and economic losses are reduced.

The invention relates to an ecological system carbon sink evaluation method, which comprises the steps of generating a continuous climate distribution grid based on a global ecological system type and climate element data, extracting multi-dimensional characteristic parameters of temperature, rainfall and a carbon sink value through an improved weighted K-means clustering algorithm, quantifying climate transition zone boundary fuzziness in combination with a covariance matrix, and evaluating the ecological system carbon sink evaluation result. Dynamically adjusting the weight of the spatial variation coefficient; a simulated annealing algorithm is utilized to optimize correlation between the division scale and the carbon sink response, and a multi-scale regression model is constructed to generate a high-precision carbon sink distribution diagram; further fusing the remote sensing vegetation index and the ground actual measurement data, and eliminating the evaluation error caused by the conflict between the boundary fuzziness and heterogeneity of the transition zone; according to the method, the problems of insufficient climate-ecology interaction dynamic response modeling and low boundary division precision in the prior art can be solved, the reliability of carbon sink evaluation in complex areas such as forest-grassland interlaced areas and coastal wetlands is remarkably improved, and scientific data support is provided for ecological restoration project site selection and carbon trading markets.

The invention discloses forest steppe fire extinguishing barrier foam and a preparation method thereof.The foam is prepared from 5%-20% of a material A, 0.5%-0.8% of a material B, 1.8%-3% of a coagulant and the balance water through a foam generation system; the material A is prepared from 1 to 10 parts of organic aggregate and 100 to 200 parts of inorganic aggregate; the material B is composed of 2-7 parts of a composite surfactant and 1-6 parts of a cross-linking agent; the coagulant is carbon dioxide gas. The inorganic aggregate is condensed under the action of hydrogen ions generated by dissolution of carbon dioxide to form colloidal particles, the colloidal particles are polymerized and crosslinked with the organic aggregate to form a gel skeleton of a three-dimensional network structure, the foam is converted into gel foam, and a heat-insulating and anti-burning barrier layer is formed on the surface of a combustible. The fire extinguishing agent is high in fire extinguishing efficiency, good in heat insulation effect and environment-friendly, and has wide application prospects in forest and grassland fire disasters.

The invention relates to the technical field of forest steppe fire emergency command, and discloses a forest steppe fire comprehensive monitoring and emergency command method and system. The method comprises the following steps: acquiring multi-source monitoring data of a satellite, an unmanned aerial vehicle and a ground sensor, and constructing a fire scene multi-dimensional feature vector through cooperative training and feature fusion; inputting the feature vectors into a physical simulation model to generate fire scene spreading speed and temperature gradient data; analyzing a terrain obstacle coefficient based on the spreading speed data and generating a helicopter no-fly zone coordinate and a passing attenuation factor; and solving and outputting a rescue unit deployment instruction through the scheduling matrix, and projecting a holographic image by using an augmented reality terminal to realize dynamic closed-loop feedback. Through deep fusion of a physical mechanism and reinforcement learning, the problem of separation of traditional fire prediction and resource scheduling is solved, intelligent decision-making of fire accurate prediction and emergency response is realized, and the accuracy and timeliness of fire prevention and control are remarkably improved.

The invention discloses a ground-air cooperative fire barrier opening method based on digital twinborn and neural networks, and belongs to the technical field of forest steppe fire prevention. Geographic information, weather and fire monitoring data are collected and preprocessed, and a digital twinborn model is constructed to simulate meteorological elements. And then constructing an evaluation index system to evaluate the fire risk, and dividing risk grades. An isolation belt is planned by adopting a genetic algorithm, and a parameter combination is explored through selection, crossing and mutation operations. During air-ground collaborative operation, the unmanned aerial vehicle guides construction, the helicopter lifts materials, and the scheme is monitored and adjusted in real time. The fire retardant effect is evaluated through simulation and actual data, the efficiency and the cost effectiveness are set up, and all links are optimized according to results. According to the method, the fire risk is accurately assessed, the isolation belt is scientifically planned, the ground-air collaborative operation efficiency is improved, dynamic monitoring and optimization are realized, the cost is reduced, and an effective means is provided for forest steppe fire prevention and control.

The invention discloses a forest steppe fire risk assessment method based on variable screening and machine learning, and the method comprises the steps: extracting environment factor variables from preprocessed historical fire remote sensing data, and carrying out the correlation analysis, thereby obtaining a correlation result; performing variable screening on the environmental factor variables based on the correlation result, a cable regression algorithm, a principal component analysis method and a stepwise regression method to obtain screened environmental factor variables; performing data division on the screened environment factor variables to obtain training data and test data, and performing model training and testing on a plurality of to-be-trained fire risk assessment models by using the training data and the test data until a plurality of fire risk assessment models are obtained; and determining an optimal fire risk assessment model based on the plurality of fire risk assessment models and the obtained historical fire records, and then performing inversion on the screened environmental factor variables to obtain a fire risk map of the forest steppe. According to the invention, the real fire risk condition can be accurately reflected.

The invention relates to the technical field of special-shaped pattern spot processing, and particularly discloses a special-shaped pattern spot processing method suitable for forest grass ecological comprehensive monitoring pattern spot investigation, and the method comprises the following steps: carrying out the closed operation of an original pattern spot; calculating a perimeter theoretical difference value before and after closed operation; calculating the actual difference value of the perimeters before and after operation; judging local long and narrow pattern spots; cutting a sharp angle pattern spot; compared with a traditional manual processing method or a simple general image processing method, the method has the advantages that a large number of special-shaped image spots can be processed in a shorter time, the requirement of a large-scale forest and grass ecological comprehensive monitoring project for data processing timeliness is met, and the method is suitable for large-scale forest and grass ecological comprehensive monitoring. And a guarantee is provided for timely mastering dynamic conditions of ecological systems of forests, grasslands, wetlands and deserts.

The invention discloses a forest and grassland fire risk assessment method based on a COPRAS model, and the method comprises the steps: determining disaster-causing factors of a forest and grassland fire, and dividing the disaster-causing factors into a combustible index, a meteorological condition index, a geographic and topographic index and a human activity index; performing screening and preprocessing on disaster-causing factors by using a principal component analysis method, extracting key indexes and constructing an evaluation index system; calculating a weight value of each evaluation index in the evaluation index system by adopting an analytic hierarchy process; based on the weight value of each evaluation index, constructing a forest steppe fire risk evaluation model based on a COPRAS model, and dividing forest steppe fire risk grades of the research area; performing precision verification on the forest steppe fire risk assessment model; and visualizing the forest steppe fire risk grade and the region division result of the research region. Therefore, the forest and steppe fire risk can be accurately evaluated, and the Greewing can better provide effective reference for predicting and preventing forest and steppe fire and formulating risk decision theory according to local conditions.

The invention discloses a fire extinguishing agent special for forests and grassland, and belongs to the technical field of fire extinguishing agents. The fire extinguishing agent special for the forest grassland comprises the following components in parts by weight: 2-6 parts of a surfactant, 10-35 parts of modified blast furnace slag, 10-15 parts of organic modified ettringite, 0.5-4 parts of a foaming agent, 0.5-2 parts of a foam stabilizer, 0-10 parts of polyethylene glycol, 0-10 parts of urea, 0.5-1.0 part of a corrosion inhibitor, 3-5 parts of a composite flame retardant and 50-80 parts of water. The modified blast furnace slag is obtained by modifying blast furnace slag subjected to acid and alkali treatment by adopting carboxymethyl cellulose; the organic modified ettringite is modified by adopting tannic acid. According to the fire extinguishing agent special for the forest grassland, the raw materials are environmentally friendly and degradable, the cost is low, fire extinguishing and degradation can be rapidly conducted, fire spreading is effectively restrained, smoldering fire reburning is prevented, residues obtained after fire extinguishing are beneficial to vegetation recovery and water and soil loss prevention, the water utilization rate is increased, and the fire extinguishing agent can be suitable for any fire fighting equipment.

The invention provides a forest steppe fire situation real-time correction and simulation prediction method, which comprises the steps that a three-dimensional grid map of a fire scene is constructed, and three-dimensional fire scene data comprises grid terrain data and grid combustible data of each grid; the method comprises the following steps: acquiring meteorological data and a live wire range in real time, and executing a prediction process: correcting the meteorological data through an interpolation algorithm or a CFD model, correcting the live wire range through a historical prediction live wire, and inputting the corrected live wire range, the corrected meteorological data and three-dimensional fire scene data into a live wire prediction model, and when new meteorological data and the live wire range are obtained next time, the predicted live wire range is not output, and the prediction process is executed again. According to the application, correction is carried out every time the new meteorological data and the live wire range are obtained, so that the obtained live wire range is closer to the real evolution process of the live wire range when the live wire prediction model is applied to carry out live wire range prediction in a plurality of time periods.

The present invention relates to the field of forest and grassland fire fighting, and more particularly to a mobile fire barrier installation device suitable for use in forest and grassland fires. This mobile fire barrier installation device, suitable for use in forest and grassland fires, features an ingenious design. The installation vehicle advances while mobile fire barriers are laid. Furthermore, the mobile fire barriers are firmly nailed to the ground, preventing them from being blown away by the microclimate wind at the fire scene. The entire installation process requires no human intervention, significantly improving the efficiency of fire barrier installation and reducing both labor intensity and installation costs.

The application provides a forest and grassland fire early identification and positioning method based on infrared thermal imaging and visible light fusion, and belongs to the technical field of forest and grassland resource protection and ecological safety monitoring. The method comprises the following steps: synchronously collecting infrared and visible light images and recording the space-time information of a monitoring platform; performing pixel-level registration on the two images; extracting a thermal anomaly suspected area from the infrared image based on a dynamic background temperature field, and extracting a smoke suspected area from the visible light image based on color, texture and motion features; performing spatial correlation analysis on the suspected areas extracted from the two channels, and combining the area growth rate and temperature rise rate of continuous multiple frames to construct a fire evolution model to confirm a fire point; calculating the three-dimensional geographic coordinates of the fire point based on the photogrammetry collinear equation and a digital elevation model; and generating and outputting alarm information containing the three-dimensional coordinates and fire intensity. The application realizes early and accurate identification and positioning of forest and grassland fires, and significantly reduces the false alarm rate.

The invention discloses a forest grass live wire real-time extraction method, relates to the technical field of deep neural networks, and solves the problems of low live wire real-time extraction efficiency and low processing speed when an unmanned aerial vehicle monitors a forest grass fire. The method comprises the steps that 1, a control terminal obtains an unmanned aerial vehicle forest grass fire scene real-time return image; 2, performing data preprocessing on the unmanned aerial vehicle forest grass fire scene real-time returned image to obtain preprocessed data; the preprocessing comprises frame splitting processing and image size normalization; 3, performing real-time reasoning on the preprocessed data by using an improved lightweight and efficient forest and grass live wire segmentation model LiFE-BONet to obtain a binary segmentation image containing a live wire and a background; and step 4, carrying out frame combination processing on the binary segmented images containing the live line and the background, and carrying out combination in sequence to obtain segmented images corresponding to the forest grass fire scene images which are input and returned by the unmanned aerial vehicle in real time. The scheme has a good application prospect in the field of forest steppe fire monitoring and emergency response.

1. The name of the product of this design: Special fire-fighting suit for forest and grassland (with aluminum foil). 2. Purpose of this product with design: This product with design is used for safety protection. 3. The design key points of this appearance design product are: the combination of shape, pattern and color. 4. The picture or photo that best illustrates the key points of the design: refer to Figure 1 for the combined state. 5. The design for which protection is sought includes color. 6. This design product is a thin product, and the left, right, top and bottom views of Kit 1 and Kit 2 are omitted.

The application provides a kind of Internet of Things empowerment's unmanned plane global inspection data management method and system, it is related to fire danger monitoring technical field, the method includes: when determining as high fire danger grade, corresponding unmanned plane inspection task is generated according to the position and range of early warning area, unmanned plane inspection terminal is controlled from unmanned plane airport autonomous take-off, flies to target early warning area according to preset inspection route and real-time collection fire-related data, correlation analysis is carried out to inspection data, fire danger factor data and fire danger grade evaluation data, fire development trend is deduced through intelligent analysis algorithm, and inspection report and decision suggestion are generated.The application not only improves the accuracy and response efficiency of forest grassland fire danger early warning, but also realizes the whole-process response closed loop from fire danger monitoring and early warning to fire comprehensive analysis and disposal.

The invention provides an airborne comprehensive management system and method applied to a fire extinguishing medium putting platform. The system comprises an outer part system, a photoelectric operation handle, input equipment, a comprehensive management computer, data recording equipment and display equipment, the outer part system is used for acquiring real-time data of the airplane in a fire extinguishing medium putting task; the photoelectric operation handle is used for determining a shooting control instruction; the input equipment is used for receiving an external operation instruction; the comprehensive management computer is used for determining interface display information according to the state analysis result of each external system and the photoelectric sensing picture; determining a putting parameter according to the external operation instruction, and determining a putting control signal according to the putting parameter; the data recording equipment is used for storing the data; and the display equipment is used for displaying the interface display information. The airborne integrated management system provided by the invention can ensure the operation efficiency in emergency fire extinguishing rescue scenes such as forests, grasslands and mountainous regions.

The invention relates to the technical field of natural resource protection and ecological system management, and discloses a method and a system for constructing a three-dimensional dynamic model of forest grass wet and waste areas based on digital twinning, and the method comprises the steps: obtaining multispectral image data and environment readings of forest, grassland, wetland and desert areas; performing feature data primary processing to obtain vegetation coverage information and environment variable data; performing species distribution boundary labeling to obtain a species distribution boundary; performing pattern correlation analysis to obtain a preliminary relation matrix; if the association strength of the water level parameter and the desertification parameter in the preliminary relation matrix is higher than a preset strength threshold value, calculating a correction coefficient of the water level parameter and the desertification parameter; carrying out weight balance to obtain a balance relation matrix; time sequence deviation detection and stability verification are carried out, and an ecological change simulation framework is determined. According to the method, comprehensive analysis of complex ecological systems such as forests, grasslands, wetlands and deserts can be realized, and dynamic monitoring and protection are carried out.

The invention relates to a forest steppe combustible moisture content detection method, and relates to the field of combustible moisture content detection.The forest steppe combustible moisture content detection method comprises the steps that a combustible sample to be detected is weighed and then put into a container, and the container is put into a high-low temperature test box; setting the temperature and humidity of a high-low temperature test box and the wind speed of an airflow generator; acquiring atmospheric humidity, atmospheric temperature and wind speed for recording weather elements; adding quantitative water into the container, and recording the volume of the added water and the hygrometer value of the combustible; dividing the collected data set into a training set, a verification set and a test set; calculating input parameters by using a neural network, and adjusting the input parameters to receive atmospheric temperature, humidity, wind speed and combustible humidity parameters as input; a training set is used for training a model, hyper-parameters of the model are adjusted through a verification set, an optimization algorithm is utilized, network weight is updated, an error between a predicted value and the actual moisture content is minimized, and the problem that the moisture content of the combustible is not accurately measured is solved.

The application discloses a forest and grassland fire smoke and fire point simultaneous detection method. The method obtains visible light and infrared band images of a target area, registers and synthesizes into multi-band synthetic data; the data is input into a pre-trained multi-modal smoke and fire simultaneous detection network for feature extraction, the network adopts a feature fidelity down-sampling module containing a fixed kernel low-pass filter and average pooling during down-sampling, and is combined with a cross-layer connected background suppression and smoke and fire focusing module, a multi-scale smoke and fire shape perception module and a smoke and fire space information rearrangement amplification module for joint processing; finally, according to the feature channel set, the smoke and the fire point area are respectively located, and a fire monitoring distribution map is generated by superposition. The application realizes the simultaneous detection and mutual verification of multi-modal features of smoke and fire, effectively overcomes the loss problem of small fire points and smoke plume details, and improves the accuracy of early fire warning.

The utility model relates to the technical field of forest and grassland fire prevention, and discloses a fire retardant spraying device for forest and grassland fire prevention, which comprises a base, moving wheels are fixedly connected to four corners of the bottom end of the base, a connecting seat is fixedly connected to the left side of the base, and a protective sleeve is fixedly connected to the top end of the base. And a flame retardant placing box is arranged in the protective sleeve. According to the fire retardant spraying device for forest steppe fire prevention, by arranging the fixing plate, the limiting plate, the reinforcing plate, the rotating rod, the fixing base and the outer inserting plate, dismounting and mounting operation is convenient, convenience is provided for transportation, meanwhile, fixing force is enhanced, it is ensured that the fire retardant containing box does not shake or even fall off during use, use safety is enhanced, and the fire retardant spraying device is worthy of popularization and application. The problems that a box for storing flame retardants and equipment are fixed together and are inconvenient to detach, a large storage space is needed during transportation, meanwhile, the flexibility between structures is limited, and regular maintenance and detection are inconvenient are solved.

The application relates to a forest and grassland fire risk intelligent early warning method, system, device and medium. The method comprises the following steps: acquiring meteorological data and combustible moisture content and other multi-source heterogeneous data of a target area; extracting and fusing meteorological features, terrain features and vegetation features to form fire risk feature data; performing grid processing and weighted calculation on the feature data to obtain a real-time fire risk index and perform grade mapping, and combining historical data and weather forecasts to perform timing prediction to obtain a future fire risk grade; automatically identifying a high-risk area based on an evaluation result to generate an analysis report containing risk distribution and prevention measure suggestions; and matching an early warning template according to an analysis result to push precise early warning information to relevant areas and objects. The method can effectively solve the problems of insufficient data fusion, prediction lag and extensive early warning in the traditional early warning mode through multi-source data deep fusion, dynamic evaluation and intelligent analysis, and improve the active prevention capability of forest and grassland fires.

The invention discloses a fire extinguishing agent special for forest and grassland in the technical field of fire extinguishing agents for forest and grassland. The fire extinguishing agent comprises the following components in parts by weight: 2-3.5 parts of a surfactant, 60-75 parts of a high-concentration flame retardant, 1-2 parts of a high-strength penetrant, 0.5-1.0 part of a composite thickener, 3-5 parts of a stabilizer, 0.5-1 part of a crosslinking aid, 2-4 parts of a hydrophobic component, 1-2 parts of an anti-blocking agent and 15-20 parts of deionized water. According to the fire extinguishing agent special for the forest grassland, the added high-strength penetrating agent and the added composite thickening agent can be attached to the periphery of the grassland, so that the fire extinguishing agent is not prone to being blown away by air waves or strong wind formed by big fire, the fire extinguishing agent can directly reach the root of a fire source, the fire extinguishing speed and efficiency are improved, the using amount of the fire extinguishing agent is reduced, and the fire extinguishing cost is reduced; and ammonium dihydrogen phosphate is added as a flame retardant, so that re-combustion of a forest fire can be effectively prevented, or the re-combustion time of the forest fire can be remarkably prolonged, and more time is provided for manually cleaning a fire scene to ensure that the forest fire is completely extinguished.

The invention relates to screening of special species of ecological communities in different environments, and provides a method for screening special species of communities by comprehensively applying richness-distribution indexes and random inspection. According to the method, a richness-distribution index and random inspection are comprehensively applied, random differences between samples among groups and between samples in the groups are eliminated, and specific species and dominant species of the environment are screened out. The screened specific species and dominant species can be used as environmental markers, and the colonies can be typed through the special species. The ecological communities involved in the invention comprise macroscopic ecological communities (such as farmlands, orchards, forests, grassland, coral reefs and the like) and microbial ecological communities (animals, plants and environmental microorganisms, especially human flora micro-ecological communities). For a macroscopic ecological community, the screened special species can be used as a monitoring index of an environmental state. For the microscopic ecological community, the screened special species can be used as an index for monitoring the state of the host and diagnosing diseases.

The invention provides a fire extinguishing equipment carrying scheduling method and system based on unmanned aerial vehicle forest grass fire scene perception, and relates to the technical field of fire rescue scheduling. Fire scene perception data returned by an unmanned aerial vehicle is received and analyzed, and a modular scheduling strategy is generated and then is sent to an equipment standardization warehouse through a 5G network; analyzing the modular scheduling strategy to obtain K carrying tasks, then carrying out scheduling personnel distribution, and carrying out modular loading and deployment of equipment by taking the K carrying tasks as constraints to obtain a target scheduling equipment set; the equipment risk monitoring cloud is activated, and a communication link between the equipment set and the equipment risk monitoring cloud is constructed based on the 5G network to carry out operation fault identification and early warning, so that the problems of unreasonable resource configuration, low scheduling efficiency and lagging emergency response in the fire extinguishing scheduling process are solved, and efficient scheduling and dynamic optimization of fire extinguishing resources are realized. And therefore, the response speed and the fire extinguishing efficiency of forest and grassland fire disasters are greatly improved.

The invention provides a multi-mode burned area detection method which is suitable for the technical field of forest / grassland burned area detection. The method comprises the following steps: acquiring remote sensing observation data of a target burned area, including data before and after a fire in the same area; performing feature extraction on the target burned area remote sensing observation data to obtain target multi-dimensional feature data; the target multi-dimensional feature data are input into a pre-trained target semantic segmentation model for burned area detection, burned area detection data are obtained, and the target semantic segmentation model can process burned area remote sensing observation data in multiple modes; and the target semantic segmentation model comprises a memory buffer area, so that the model can continuously learn, and the model is adaptively updated and optimized according to the new modal data to relieve the problem of disastrous forgetting. The invention further provides a multi-mode burned area detection device, equipment and a medium.

The application discloses a kind of based on digital twin and neural network ground-air coordination fire prevention isolation belt opening method, belong to forest and prairie fire prevention technical field.First, collect geographic information, meteorological, fire monitoring data and pre-process, construct digital twin model simulation meteorological element.Then, construct evaluation index system to evaluate fire risk, and divide risk level.Genetic algorithm is used to plan the isolation belt, and the parameter combination is explored through selection, crossover and mutation operation.When ground-air coordination is carried out, the unmanned aerial vehicle guides the construction, the helicopter hoists the materials, and the scheme is adjusted in real time.The fire resistance effect, opening efficiency and cost benefit are evaluated through simulation and actual data, and each link is optimized according to the results.The method accurately evaluates the fire risk, scientifically plans the isolation belt, improves the efficiency of ground-air coordination, realizes dynamic monitoring and optimization, reduces the cost, and provides an effective means for forest and prairie fire prevention and control.

The invention relates to the technical field of biological control, in particular to a forest and grassland pest control device which comprises a box body and a fixing plate, two long-strip-shaped holes are formed in the fixing plate, the box body is slidably connected into the long-strip-shaped holes through two sliding blocks, stirring equipment is installed in the box body, and the stirring equipment is arranged in the fixing plate. The stirring equipment comprises a rack plate, a rotating shaft and stirring rods, the rack plate is slidably connected to the fixing plate and fixedly connected with the sliding block, the rotating shaft is rotatably connected to the side wall of the box body, and the multiple stirring rods are annularly arrayed at the end, away from the rack plate, of the rotating shaft; according to the stirring device, when the stirring rod rotates along with the rotating shaft, a liquid medicine mixture in the box body can be continuously stirred, so that the situation that the purity of liquid medicine in the box body is not uniform due to precipitation of medicine is avoided.

The application provides a forest and grassland fire ground-air cooperative fire extinguishing efficiency evaluation method and system, wherein the method comprises the following steps: acquiring an influence factor system related to ground-air cooperative fire extinguishing evaluation; constructing a scale experiment system based on the influence factor system and obtaining a mapping relationship between prototype parameters and scale parameters; acquiring a range of scale experiment parameters based on the mapping relationship and multiple level grades of the influence factors; obtaining multiple experiment parameter combinations based on the range of the scale experiment parameters; acquiring sensor data through ground-air cooperative fire extinguishing scale experiments based on the multiple experiment parameter combinations; obtaining multiple key data of each experiment parameter combination based on the sensor data; obtaining fire extinguishing efficiency values corresponding to each experiment parameter combination based on the multiple key data; and obtaining optimal ground-air cooperative fire extinguishing parameter combinations under different fire scenes based on the fire extinguishing efficiency values, which improves the standardization, scientificity and universality of fire extinguishing efficiency evaluation and provides reliable technical support for efficient disposal of forest and grassland fires.

The present application relates to the field of fire fighting technology, in particular to a space-air-ground cooperative intelligent forest and grassland fire fighting robot cluster, which comprises a space-air-ground integrated monitoring unit, a short-range fire extinguishing control unit, a decision-making generation unit, a remote fire extinguishing control unit and an aftereffect evaluation unit. The present application eliminates the monitoring blind area through the mutual complementation of the three monitoring means in the time-space dimension, realizes the full autonomous flight of the fire extinguishing unmanned aerial vehicle in the initial stage and the execution of small-area fire extinguishing by remote bomb launching, and the whole process does not need to enter the dangerous area of the fire field, and the high-cost cluster rocket fire extinguishing system remotely launches the fire extinguishing bomb to execute the out-of-control large-area fire extinguishing, which is conducive to the optimal allocation of tactical resources, avoids excessive damage, makes the combat economy of the whole system reach the best, and on the other hand, adapts to different complex terrains and extreme fire conditions.

The present application relates to the field of intelligent fire risk alarm, and specifically discloses a fire monitoring and alarm system and method based on intelligent fire risk level assessment, which uses artificial intelligence technology based on the field of deep learning to extract and analyze features of forest remote sensing images and forest meteorological data of a predetermined time period to obtain classification results representing forest fire risk levels, and judge whether to issue an alarm with high-risk fire risk information based on the fire risk level shown. In this way, based on the assessment and forecast of forest and grassland fire risk levels, fire risks in high-risk areas can be intelligently identified and discovered, and alarm information can be generated, which can avoid false alarms and missed alarms caused by human subjective factors.