127 results about "Snow cover" patented technology

The invention discloses a mountainous area accumulated snow area reconstruction method based on machine learning. The method comprises the steps that optical remote sensing data and topographic data are acquired and preprocessed; the optical remote sensing data comprises the MOD09GA data and the Landsat8OLI data; the preprocessing comprises terrain correction and accumulated snow recognition; taking an accumulated snow area generated by the Landsat8OLI data by using an accumulated snow recognition algorithm as a truth value label, and constructing a sample data set based on the preprocessed MOD09GA data and topographic data; dividing the sample data set into a training set and a verification set according to a proportion of 4: 1 so as to train and verify an XGBoost model; the XGBoost model improves the prediction performance by combining a plurality of decision trees; and performing accumulated snow area prediction on new input data by using the trained XGBoost model. According to the method, day-by-day 30-meter (m) accumulated snow area data can be produced, and the method has important research significance and value for mountainous area accumulated snow monitoring, hydrological process simulation and ecological system evolution.

The invention discloses a high-resolution peak accumulated snow depth inversion device and method based on a geographically weighted random forest, and the device comprises a data obtaining module which is used for obtaining the multi-source data of a research region, and the multi-source data comprise MODIS remote sensing accumulated snow data, Sentinel-1VV / VH backscattering data, topographic data, and meteorological station snow depth observation data; the high-resolution snow coverage data set construction module is used for processing the MODIS remote sensing snow data to obtain a high-resolution cloudless binary snow coverage data set; the feature construction module is used for constructing a comprehensive feature set containing a snow space-time process feature index, a back scattering feature index and a topographic feature index; and the model construction and analysis module is used for training a geographically weighted random forest model through the comprehensive feature set, and inverting the peak snow depth of the research area according to the optimal model. According to the invention, estimation of high-resolution peak snow depth can be realized.

The invention belongs to the technical field of regional hydrological numerical simulation, and particularly relates to a runoff simulation method, system and application of a loose coupling hydrological model based on glacier and non-glacier zones.The method comprises the steps that firstly, a glacier area and a non-glacier area are divided based on glacier cataloguing data and accumulated snow covering products, gridding processing is carried out through a digital elevation model, and a runoff simulation result is obtained; and performing hydrological process simulation on the non-glacier area and the glacier area by adopting a VIC model and a DETIM model respectively to realize differential modeling, and obtaining a basin total runoff simulation process through result fusion. Through the loose coupling framework, the problems of poor model expansibility and high reuse difficulty in traditional integrated modeling are solved, the simulation precision and deployment efficiency are improved, and the method is suitable for water resource evaluation and climate response research in the cold and cold mountainous area.

The invention discloses a high and cold slope disaster body segmentation method fusing optical and SAR images, and the method comprises the following steps: 1, carrying out the snow coverage normalization processing based on the visible light green light wave band and the short wave infrared wave band of an optical image, and generating an ice and snow mask through an expectation maximization algorithm and a Gaussian mixture model; 2, preprocessing the optical image and the SAR image; step 3, constructing a high and cold slope disaster body segmentation model based on a Transform network; 4, training the segmentation model by using Dice loss and cross entropy loss in a combined manner, and freezing parameters of an image encoder in the training process; and step 5, inputting the high and cold slope remote sensing image into the trained segmentation model, and outputting a segmentation result of the slope disaster body by the segmentation model. According to the method, the problems of large ice and snow interference and poor multi-source data collaboration in high and cold slope disaster body segmentation are solved, and the segmentation precision and the engineering applicability are improved.

A transport sled that is configured to receive and retain items such as but not limited to hunting gear, camping equipment and wild game within an interior cavity thereof. The transport sled includes a body having a bottom portion and a top portion wherein the top portion is hingedly secured to the bottom portion. The bottom portion is concave in form having an outer surface configured to slidably traverse across a snow covered surface. The top portion is hexagonal dome shaped forming an interior cavity. The top portion includes storage compartments operable to receive and retain items proximate thereto. The body includes stationary members movably coupled to the rear end of the body. The stationary members move between a first position and a second position wherein in the second position the teeth members of the stationary members engage the snow covered surface to inhibit movement of the transport sled.

The invention provides an ice and snow product inversion method and device based on a geological resource hyperspectral satellite, and relates to the technical field of remote sensing data processing.The inversion method comprises the steps that remote sensing image data and auxiliary data of a research area are obtained through the geological resource hyperspectral satellite, the remote sensing image data are preprocessed, and the preprocessed remote sensing image data are obtained; obtaining real reflectivity and spectral data of the earth surface; using a multilevel decision tree accumulated snow recognition algorithm to generate an accumulated snow range data product; obtaining a normalized snow index according to the spectral data; inputting the real earth surface reflectivity and the auxiliary data into a preset snow water equivalent inversion model to obtain snow water equivalent data; and inputting the auxiliary data, the normalized snow index and the remote sensing image data into a preset deep belief network to obtain accumulated snow area proportion data. According to the invention, based on the high-frequency observation capability of a geological resource hyperspectral satellite, high-precision ice and snow product inversion is realized under a complex terrain condition through the combination of a satellite remote sensing technology and a machine learning algorithm.

The invention belongs to the field of new energy power generation power prediction, and discloses a photovoltaic power prediction method in a snow covering scene and a related device. The prediction method comprises the steps of obtaining numerical weather forecast data, an accumulated snow coverage rate and an accumulated snow thickness forecast value in a snow covering scene in a prediction time period; inputting the numerical weather forecast data, the snow coverage rate and the snow thickness forecast value in the snow covering scene in the forecast time period into a pre-trained snow covering loss rate forecast model to obtain a loss rate forecast value; based on the loss rate prediction value, calculating to obtain a photovoltaic power prediction value in a snow covering scene in a prediction time period; wherein the pre-trained snow covering loss rate prediction model takes a DHKELM network as a basic training model, and is obtained by adopting layered unsupervised training. According to the method, the accuracy of photovoltaic power prediction under the snow covering condition is improved by predicting the snow covering rate and the snow thickness and fusing a physical mechanism and data driving.

The invention discloses a forest accumulated snow albedo inversion method, and relates to the technical field of remote sensing, and the method comprises the steps: selecting a forest accumulated snow bidirectional reflection model SFBR2 as a forward model; extracting a forest accumulated snow area through the ground cover type product and the accumulated snow cover product; randomly generating a plurality of sample points in the forest accumulated snow area, and extracting input features of all the sample points; based on the input feature sample and the forest snow bi-directional reflection model SFBR2, an optimization algorithm is adopted for inversion to obtain a target variable; constructing a training data set in combination with the input features and the target variables; training a random forest model based on the constructed data set, and adopting a grid search algorithm for optimization; and a long-term time sequence image set containing input features is constructed on a GEE platform, the optimized random forest model is applied to the image set, and the albedo of the black space and the white space of the forest accumulated snow is accurately inverted. According to the method, the precision and the calculation speed of an inversion result can be remarkably improved.

The invention discloses a remote monitoring method and system for a photovoltaic power station, and a computing device, relates to the technical field of photovoltaic power generation, and solves the problem that in the prior art, dust or accumulated snow covering the surface of a photovoltaic module of the photovoltaic power station is not considered when the generating capacity of the photovoltaic power station is predicted. The light transmittance is reduced; and the generating capacity is reduced. The method comprises the following steps: extracting historical data of a photovoltaic power station in a statistical period and data features of the historical data; inputting the data features into a prediction model, and predicting the generating capacity of the target time period; performing abnormal prediction detection according to a difference relationship between the predicted generating capacity and the actual generating capacity to obtain an evaluation label of the predicted generating capacity; if the evaluation label of the predicted generating capacity is abnormal, correcting the predicted generating capacity by constructing a correction factor to obtain the corrected predicted generating capacity; and if the corrected evaluation label of the predicted generating capacity is normal, remote monitoring of the photovoltaic power station is completed.

The utility model relates to the technical field of snowsweepers, in particular to a driving gear box for a snowplow, which comprises a first shell, a second shell is movably connected to the surface of the first shell, a fixing bolt is movably connected to the surface of the second shell, and a mounting screw hole is in threaded connection to the surface of the fixing bolt. And the surface of the first shell is fixedly connected with a snow-proof cover. The oil cup is in threaded connection with the upper cover, the upper cover is movably connected with the pressure spring, the upper cover is in threaded connection with the adjusting nut, the oil cup is fixedly connected with the needle valve, the adjusting nut is fixedly connected with the reset spring, the oil cup is fixedly connected with the filter screen, the oil cup is fixedly connected with the connecting block, the oil cup is filled with lubricating oil, and the button is opened. And the transparent pipe can continuously drip lubricating oil to the fourth gear, so that manual oil brushing after the second shell is disassembled is not needed, and meanwhile, the dripping speed of the lubricating oil can be adjusted by rotating the adjusting nut.

The invention discloses a highway ice and snow covered pavement traffic safety risk grade prediction method. The method comprises the following steps: firstly, collecting vehicle operation data, meteorological data and road information data; then, dynamic response generated in the braking or accelerating process of the vehicle is analyzed, key parameters such as the speed, the acceleration and the braking force of the vehicle are combined, and the numerical value of the road surface friction coefficient is estimated; afterwards, environmental factors such as ice and snow, temperature and snowfall intensity are comprehensively considered, the road adhesion coefficient obtained through estimation is corrected, a numerical value better fitting the actual road condition is obtained, and road adhesion coefficient data finally used for risk assessment are calculated; and then, in combination with the corrected road adhesion coefficient under the ice and snow weather condition, carrying out detailed analysis on the adhesion coefficients of different areas by applying a risk assessment function. According to the method, low-cost, high-frequency and wide-coverage attachment coefficient estimation is realized, and the comprehensive risk condition of the ice and snow covered pavement can be reflected more comprehensively and stereoscopically.

The invention provides an electric car hood and a heating control method thereof, the electric car hood comprises a hood outer plate and a hood inner plate which are arranged in a stacked mode, and a reinforcing part clamped between the hood inner plate and the hood outer plate, and the reinforcing part is made of an electric heating material so as to generate heat in an electrified state. According to the electric car hood, on one hand, accumulated snow covering the hood can be conveniently melted, and the influence of the accumulated snow on the sight of a car driver is reduced; and on the other hand, the reinforcer has certain rigidity, and the overall structural rigidity of the electric car hood can be improved.

The invention relates to the technical field of meteorological short-term climate prediction, and discloses a temperature prediction method based on hybrid space-time neural network and multi-scale feature fusion. The method comprises the following steps: acquiring a historical temperature data sequence and a multi-source meteorological data sequence, wherein the multi-source meteorological data sequence comprises wind speed data, soil temperature data, snow cover data and sea temperature data; strict time sequence feature extraction is conducted on the historical temperature data sequence, a temperature short-term fluctuation feature set and a temperature long-term trend feature set are obtained, and it is ensured that only historical information is used without data leakage through strict time sequence feature extraction; and on the basis of the multi-source meteorological data sequence, the temperature short-term fluctuation feature group and the temperature long-term trend feature group, predicating through an improved LSTM neural network to obtain predicated temperature data of a preset number of days in the future. The accuracy of temperature prediction is improved by constructing a temperature short-term fluctuation feature group and a temperature long-term trend feature group during temperature prediction.

This invention discloses a machine learning-based method for reconstructing snow cover area in mountainous areas, comprising: acquiring and preprocessing optical remote sensing data and topographic data; the optical remote sensing data includes MOD09GA data and Landsat8OLI data; the preprocessing includes topographic correction and snow cover identification; using the snow cover area generated from the Landsat8OLI data using a snow cover identification algorithm as the ground truth label, and constructing a sample dataset based on the preprocessed MOD09GA data and topographic data; dividing the sample dataset into a training set and a validation set at a 4:1 ratio to train and validate an XGBoost model; the XGBoost model improves prediction performance by combining multiple decision trees; and using the trained XGBoost model to predict snow cover area on new input data. This method can generate daily 30-meter (m) snow cover area data, which has important research significance and value for mountainous snow cover monitoring, hydrological process simulation, and ecosystem evolution.

The utility model relates to the technical field of battery replacing stations, in particular to an automatic ramp structure of a battery replacing station, which comprises a bottom plate, an angle adjusting mechanism is arranged in the middle of the top of the bottom plate, two lug plates are fixedly connected to the left side of the top of the bottom plate in a front-back symmetry manner, a fixing plate is rotatably connected between the two lug plates through a rotating shaft, and a ramp plate is fixedly connected to the top of the fixing plate. According to the utility model, through the arrangement of the angle adjusting mechanism, the angle adjustment of the ramp plate is realized, the angle of the ramp plate can be conveniently adjusted according to the height of a chassis of a battery changing vehicle, the phenomenon of bottom supporting during battery changing is avoided, the working efficiency is improved, and the working efficiency is improved. The application range of the device is expanded, the electric heating pipe is turned on through the thermolator, accumulated snow covering the top of the ramp plate is melted through heat generated by the electric heating pipe, the situation that the vehicle slips on the ramp during battery replacement is avoided, the accumulated snow does not need to be manually cleaned, and time and labor are saved.

This invention discloses a method and system for emergency early warning of snowmelt floods based on snowmelt simulation, belonging to the field of data processing technology. The method includes: acquiring a preset snow cover in a preset area, performing multi-feature acquisition to obtain preset snow cover features; acquiring a preset environment in the preset area, performing multi-feature acquisition to obtain preset environment features; acquiring historical snowmelt runoff information of the preset area and generating a preset runoff map; rendering the preset snow cover features and preset environment features onto the preset runoff map to obtain a three-dimensional snow cover model; analyzing weather forecast information to obtain a weather-based snowmelt index; performing snowmelt simulation on the three-dimensional snow cover model to obtain a snowmelt simulation record; obtaining a snowmelt flood risk index and matching it with a risk warning scheme for early warning. This invention solves the problems of insufficient effective early warning for snowmelt flood risks and low reliability of early warning basis in existing technologies, achieving the effect of quantifying risks through model simulation and improving the accuracy of early warnings.

The invention discloses a photovoltaic snow covering depth and power loss forecasting method and system based on multi-source data fusion, and belongs to the technical field of photovoltaic power forecasting. The problems of high-precision accumulated snow influence assessment, short-term risk early warning and power loss quantitative prediction of a photovoltaic system in cold and alpine regions are solved. The method comprises the following steps: selecting three numerical weather forecasting modes, namely a global forecasting system operated by the National Environmental Forecasting Center, a wind energy and solar energy forecasting system of the China Meteorological Administration and a unified mode weather forecast of the British Meteorological Administration, acquiring weather forecasting data, performing unified space-time interpolation, abnormal value correction and unit conversion, and then performing set averaging to obtain a set average value; ensemble forecast data is obtained; based on a temperature-irradiance condition and a friction force mechanism, an accumulated snow covering model is constructed, a photovoltaic panel snow covering range and photovoltaic power loss are obtained, early warning information of snow covering time, duration and power loss is generated through matching of station longitude and latitude and national grid forecasting, and photovoltaic snow covering depth and power loss forecasting based on multi-source data fusion is completed.

The application discloses a distribution box with anti-freezing function, which comprises a box body and a box cover, the box body is internally provided with a heating mechanism, the box cover is provided with a mounting seat and an air outlet mechanism rotatably mounted in the mounting seat, and the air outlet mechanism can spray the high-temperature gas generated by the heating mechanism in a changeable form along the outer surface of the box cover. The distribution box has the advantages that: 1. the heating mechanism can firstly improve the surface temperature of the box cover to melt the bottom layer of snow on the surface of the box cover; 2. the air outlet mechanism can lead the high-temperature gas generated by the heating mechanism out of the box body and spray the high-temperature gas in a changeable form along the outer surface of the box cover, so that the snow on the box cover can be melted in a multi-dimensional manner, the melting process of the whole snow is accelerated, and a thick snow layer is avoided; and the application is dedicated to solving the problem of snow covering on the box cover of the distribution box, preventing the thick snow layer from causing frost in the distribution box and affecting the reliability and continuity of power supply, and preventing the box cover from being in a low-temperature and high-humidity environment for a long time and reducing the service life.

To provide a snow melting device which is easy to install and low in running cost.SOLUTION: The snow melting device includes a sheet-like or plate-like snow melting member and an LED light source arranged on the lower surface side of the snow melting member at a predetermined distance, and melts snow cover on the upper surface side by warming the snow melting member with light emitted from the LED light source. According to the present invention, it is possible to provide a snow-melting system that is easy to install and low in running cost. In addition, since the snow-melting member has water permeability, hydrophilicity, or water absorbability, it is possible to promote removal or evaporation of water generated by melting of snow, and it is possible to more efficiently melt snow.SELECTED DRAWING: Figure 1

This application discloses a method and system for identifying and assessing foreign object impacts on rail vehicles based on multimodal fusion. It constructs a multi-source monitoring data and operating environment parameter dataset by acquiring image information, structural vibration response information, and impact acoustic information of multiple key structural parts of the rail vehicle, combined with operating parameters, ambient temperature, and track snow cover information obtained from the onboard positioning system. Based on this, a multimodal fusion analysis method is used to identify foreign object impact events, determining the time of foreign object occurrence, impact time, and impact characteristic parameters. Furthermore, the impact load is calculated based on the foreign object's size and material parameters, and the foreign object's entrainment capacity and critical size range are analyzed using an aerodynamic adsorption model. Finally, statistical analysis of the impact events is performed, and the risk level of key structural parts is assessed. This application enables accurate identification and quantitative analysis of foreign object impact behavior on rail vehicles during winter ice and snow, improving operational safety.

The present application provides a method, device, electronic device and storage medium for measuring snow depth. The method includes: obtaining first signal parameters of a first GNSS antenna and second signal parameters of a second GNSS antenna; determining a first peak frequency and a first peak power spectral density of the first GNSS antenna according to the first signal parameters, and determining a second peak frequency and a second peak power spectral density of the second GNSS antenna according to the second signal parameters; calculating a first height between the first GNSS antenna and the snow surface according to the first peak frequency, and calculating a second height between the second GNSS antenna and the snow surface according to the second peak frequency; respectively performing weighted processing on the first height and the second height based on the first peak power spectral density and the second peak power spectral density to obtain a first reference height; and determining the snow depth of the snow covering the land surface based on the first reference height and a second reference height when the land surface is not covered with snow.

The utility model discloses a hand-operated control opening and closing assembly and a passenger ladder platform awning, and belongs to the technical field of passenger ladder platform awnings. According to the technical scheme, aiming at the problem that an existing electric opening and closing device is high in maintenance cost, a nested structure of a movable shell on the outer wall of a fixed rod and a sliding rod is matched with a rack and gear meshing transmission mechanism, and manual rotation torque is converted into horizontal push-pull motion of the sliding rod; a synchronous wheel transmission assembly is arranged to connect the rotating shaft and the movable pipe, and manual driving control is achieved through an adjusting rod-fixed disc-spring mechanism; a conical top end support, a rotating rod and a supporting rod are adopted to form an awning framework, and a movable sleeve supporting mechanism is matched to prevent canvas from drooping. According to the awning, the adjusting rod is manually rotated to drive the transmission system, the rotating rod drives the canvas to be unfolded or folded, countersunk mounting holes are formed in the base to facilitate fixation, and conical flow guide structures are adopted at the joints of all components. The device is suitable for rain and snow shielding scenes of airport passenger ladder platforms.

The invention discloses an accumulated snow multi-mode integration method based on TC covariance, and the method comprises the following steps: (1) employing atmosphere forced data to drive different land surface modes of CLM, Noah and Noah-MP, and carrying out the simulation of accumulated snow in different land surface modes; (2) based on a TC covariance method, calculating variances and covariances of accumulated snow simulation in different regions in different modes, and calculating weights of different modes in different regions according to the variances and the covariances; and step (3), according to the calculated accumulated snow weights simulated in different areas in different modes, performing accumulated snow multi-mode integration. According to the invention, errors caused by multi-mode integration of a single mode in an area with large errors can be reduced, and the precision of multi-mode snow accumulation simulation is improved.

The utility model provides a cleaning device for a vehicle sensor of an automatic driving vehicle, and the cleaning device comprises a fixed support, a self-heating glass assembly and a windscreen wiper; the self-heating glass assembly and the windscreen wiper are installed in front of the vehicle sensor through the fixing support. The self-heating glass assembly is composed of a glass lens and a heat-conducting resistor and used for melting ice and snow into water in the low-temperature and high-cold environment. The windscreen wiper is composed of a wiping strip and a wiping strip support and used for cleaning stains and melted water on the self-heating glass assembly. According to the cleaning device for the vehicle sensor, the self-heating glass assembly covers the vehicle sensor, ice and snow covering the vehicle sensor under the extreme conditions of low temperature, high cold and the like can be effectively melted, meanwhile, the windscreen wiper is used for removing melted water and stains, the cleaning effect of the cleaning device for the vehicle sensor is optimized, and the cleaning effect of the vehicle sensor is improved. Normal use of the vehicle sensor under extreme conditions is guaranteed, and the application scene of the automatic driving vehicle is widened.

The present invention discloses a method and system for emergency treatment and analysis of snowmelt non-point source pollution, relating to the field of data processing technology. The method comprises: collecting basic regional information of a target area; dividing the area based on the basic regional information; parsing the basic regional information to generate land use data, soil type data, soil property data, and historical meteorological data; using a SWAT model to obtain non-point source pollution simulation results; collecting snow cover data of the target area; and predicting snowmelt floods based on the snow cover data and the basic regional information using a WRF-driven two-layer grid overlay model to obtain prediction results; and conducting emergency management based on the prediction results and the non-point source pollution simulation results. The present invention solves the technical problems of low intelligence and low management accuracy in the prior art for emergency decision-making regarding snowmelt non-point source pollution, thereby achieving the technical effect of improving the efficiency and management quality of emergency treatment of snowmelt non-point source pollution.

The application relates to an axle box spring snow cover sleeving device and a working method, which comprises a feeding mechanism, a lifting component, a supporting piece, a transfer mechanism, a first horizontal moving mechanism, a vertical moving mechanism and a suction disc assembly, a sleeving mechanism, a lifting mechanism, a second horizontal moving mechanism, a swing mechanism and a supporting opening mechanism.

This invention relates to a method for the layout of charging facilities that embeds cold-region features and integrates across scales, belonging to the field of electric vehicle charging facility planning and spatial optimization technology. Addressing the shortcomings of existing technologies in fully considering the constraints of low temperatures and snow cover in cold regions and insufficient linkage between urban and community scales, leading to poor matching of layout needs and fairness, this method first collects multi-scale data and performs downscaling and spatial alignment. Second, it constructs a four-dimensional feature set at the urban scale, corrects the weights using a cold-region intensity factor, and identifies highly imbalanced areas. Then, it transfers these features to the community scale to identify dual-objective hotspot grids and uses a GWR-XGBoost model to evaluate micro-spatial adaptability. Finally, it constructs a multi-objective layout optimization model considering cold-region and safety constraints to solve for the Pareto optimal layout scheme, achieving a 10m-level layout at the community scale. This invention is applicable to the field of electric vehicle charging facility planning and spatial optimization in cold-region cities.

The invention belongs to the technical field of porcelain insulator equipment, and discloses a porcelain insulator with an ice and snow prevention cover structure, which is technically characterized by comprising a core column, an umbrella disc is arranged on the surface of the core column, a fixed cover is fixedly mounted on the surface of the core column, and a plurality of groups of protective covers are sleeved in the fixed cover. A positioning mechanism matched with the protective cover is arranged in the fixing cover, the positioning mechanism comprises a guiding assembly and an adjusting assembly, a cleaning mechanism is arranged on the upper surface of the umbrella disc, the cleaning mechanism comprises a sweeping assembly and a driving assembly, and the guiding assembly and the adjusting assembly are arranged to be matched with each other, so that the umbrella disc is cleaned. The relative positions of the protective covers and the umbrella disc can be conveniently adjusted, when protection is not needed, the protective covers are integrally located on the outer side of the umbrella disc, interference to the umbrella disc is avoided, when protection is needed, the protective covers are integrally connected to the outer side of the umbrella disc in a sleeving mode, all-directional closed protection can be conducted on the umbrella disc, and accumulated snow is effectively prevented from being generated on the surface of the umbrella disc.

The invention discloses a polar region ship navigation monitoring and management device, which comprises a monitoring body, a first frame, a second frame, an adjusting assembly, a deicing assembly and a snow sweeping assembly, and is characterized in that the first frame and the second frame are arranged on two sides of the monitoring body, play a role in protecting the monitoring body and provide supporting force at the same time; the adjusting assembly is arranged on the first frame and used for adjusting the horizontal direction and the height direction of the monitoring body to achieve adjustment of the monitoring range. The deicing assembly is arranged between the first frame and the second frame and used for removing accumulated snow and ice on the side wall of the monitoring body. The snow sweeping assembly is arranged on the second frame and used for removing accumulated snow and ice at the camera port of the monitoring body 1. According to the device, the monitoring angle of the monitoring body can be adjusted, monitoring in a larger range is achieved, meanwhile, ice and snow covering the monitoring body can be effectively removed in time according to environment information, and effective management of the operation state of the monitoring body is kept.

This invention relates to the field of lidar snow depth estimation technology, specifically providing a hemispherical-scale snow depth estimation method and system based on spaceborne lidar. The method includes: downloading and preprocessing snow cover-related data collected by the spaceborne lidar within a preset hemispherical scale; obtaining snow cover period and snowless period light segments within the preset hemispherical scale based on the preprocessed snow cover-related data; obtaining the intersection points of the snow cover period and snowless period light segments using a dynamic discrimination rule based on a slope-limited intersection point distance threshold; obtaining snow depth values ​​based on the intersection points and a snow depth estimation model; and correcting the snow depth values ​​based on a snow depth reference error model to obtain corrected snow depth values, thus completing the hemispherical-scale snow depth estimation based on spaceborne lidar. This invention is not limited by factors such as altitude or cost when generating snow depth data, and can compensate for sparse station snow depth data. It plays an important role in verifying the authenticity of snow depth products, constructing snow cover models, and measuring snow depth in high-altitude mountainous areas.