32 results about "Short wave radiation" patented technology

A method for studying interannual variation of marine heatwaves in the South Indian Ocean includes: investigating spatial distribution features and linear variation trend features of marine heatwaves in the South Indian Ocean according to obtained data; analyzing the relationship between an intensity of marine heatwaves in the South Indian Ocean and an El Niño-Southern Oscillation (ENSO) process; analyzing a spatial evolution of marine heatwaves in the South Indian Ocean and sea surface temperature (SST) anomalies during an El Niño event; analyzing energy contribution of ocean and atmosphere to marine heatwave events during the El Niño event; investigating physical mechanisms of the marine heatwaves in the South Indian Ocean; and determining whether the marine heatwaves in the South Indian Ocean are influenced by shortwave radiation and latent heat modulated by the ENSO process. The present disclosure reveals that marine heatwaves occur during the El Niño event in the South Indian Ocean.

The invention provides a satellite solar short-wave radiation inversion method based on knowledge distillation, which relates to the field of solar short-wave radiation inversion, and comprises the following steps: collecting polar orbit satellite data, stationary satellite data, geographic information data and ground observation data; preprocessing the data to obtain input features and labels for training the teacher model and the student model; sorting the importance of the input features by using a random forest model, selecting key features, and removing non-key features; constructing a deep learning model by using the key features, and generating a teacher model of solar short-wave radiation inversion; and taking an output result of the teacher model as a soft label, introducing ground observation data as a hard label, and carrying out knowledge distillation to obtain a student model of solar short-wave radiation inversion. According to the technical scheme of the invention, the problems of data scarcity and high data acquisition cost caused by the fact that a model is constructed only depending on ground observation data in the prior art are solved, and the problem that the inversion precision completely based on satellite data is limited is solved.

The invention discloses an earth surface downlink short-wave radiation space downscaling method based on a super-resolution reconstruction technology, belongs to the technical field of meteorological data analysis, and solves the problems of insufficient solar radiation data space resolution and weak earth surface heterogeneity characterization capability in the prior art. Carrying out super-resolution reconstruction on the radiation data set by adopting a super-resolution combination model, and carrying out weighted fusion on a reconstructed data set output by the super-resolution combination model; according to the method, the output results of the multiple models are subjected to weighted fusion, weight optimization of the super-resolution sub-models is performed in combination with the high-resolution terrain factors, spatial downscaling from 5km to 1km resolution is finally realized, the spatial precision of the solar radiation data is remarkably improved on the basis of keeping the hour-level time resolution of the original data, and the accuracy of the solar radiation data is improved. And more earth surface heterogeneity information can be captured, and meanwhile, the high-time-resolution application requirement is met.

The invention discloses a method and device for predicting a non-uniform temperature field in an urban three-dimensional street canyon, and the method comprises the steps: constructing an urban three-dimensional street canyon model, and dividing the urban three-dimensional street canyon model into a plurality of surface regions; calculating sky view parameters of each surface area; generating a shadow distribution field of each surface area; according to the sky view parameter and the shadow distribution field of each surface area, obtaining a solar short-wave radiation flux and a ground long-wave radiation flux of each surface area; calculating sensible heat flux and latent heat flux of each surface area; generating a non-uniform temperature field according to the sensible heat flux, the latent heat flux, the solar short-wave radiation flux and the ground long-wave radiation flux of each surface area; dividing an illumination area and a shadow area based on the shadow distribution field of each surface area; and calculating the average temperature of the illumination area and the shadow area based on the non-uniform temperature field. According to the invention, real-time and accurate prediction of the non-uniform temperature field in the urban three-dimensional street and valley is realized, and consumption of computing resources is reduced.

The invention discloses a portable urban thermal environment intelligent sensing method and equipment based on AR, and the method comprises the steps: collecting a panoramic RGB street scene image of a user visual angle through AR glasses, and synchronously obtaining the time, geographic position and meteorological parameters; mapping the RGB image and the environmental parameters into a panoramic infrared thermal image by using a generative adversarial network, and obtaining the radiation temperature of each pixel; projecting the panoramic heat map to a unit spherical surface taking a user as a center, calculating a long-wave radiation flux through spherical surface angle integration, and calculating a short-wave radiation flux based on a solar radiation model by combining a solar elevation angle and the like; and fusing the total radiation amount to calculate the average radiation temperature, and finally superposing the heat map and / or the average radiation temperature to a real or virtual environment through AR glasses or an intelligent terminal to realize spatialization thermal load visualization.

The invention discloses a deepwater net cage fish feeding control method and system, and the method comprises the steps: generating a cultured fish detail list in a target deepwater region according to the fish information, and carrying out the multi-round spiced salt denoising processing of the obtained image data of the target deepwater culture region, inputting the underwater light data into the water body thermal stratification model to obtain each deepwater hierarchy and short wave radiation data corresponding to each deepwater hierarchy; and analyzing and identifying the image data through an AI graph identification algorithm to obtain fish growth data, constructing a feeding amount control model according to a cultured fish detail list, the fish growth data and the short-wave radiation data, and generating a culture visualization report to realize feeding control of fishes in the target deepwater culture area. Fish growth and health are analyzed through image data, a feeding control model is constructed and optimized according to data such as the ammonia nitrogen content, the dissolved oxygen content and short wave radiation, feeding amount control is optimized, the fish growth speed is increased, the fish growth quality is improved, and long-term sustainable breeding is achieved.

The present invention discloses a quantitative analysis method of solar shortwave radiation of a tree canopy based on a computer simulation model, comprising: first, collecting tree laser point cloud data, combining machine vision algorithm to separate branches and leaves and segment single leaves on the tree laser point cloud, and using elliptical and cylindrical geometric units of appropriate size to fit each leaf and skeleton respectively to reconstruct a real model of the tree; secondly, using computer graphics methods, combining the longitude and latitude of the research site and time to simulate the incident light of the sun, and introducing the bidirectional reflection and transmission distribution function of physics and the Monte Carlo ray tracing algorithm to simulate the collision of reflected and transmitted light with leaves in the canopy; finally, according to the instrument measurement, the average roughness and refractive index of leaves of different tree species are obtained, and the shortwave radiation distribution calculation in the tree canopy and the light interception efficiency evaluation of the forest canopy are realized in combination with the ray tracing algorithm. The present invention can accurately obtain the interception amount of direct, reflected and transmitted light energy by the tree canopy.

The invention provides a cloud-air ground surface downlink short wave radiation estimation method. The method comprises the following steps: S1, collecting data and constructing a sample data set; s2, constructing a physically constrained multi-task learning model, and obtaining estimated values of two key parameters in the cloud-air radiation estimation model; s3, based on a cloud-air radiation estimation method in a physical model FARMS, in combination with key parameters estimated by a deep learning model, obtaining a cloud-air ground surface downlink short-wave radiation estimation value; s4, calculating a loss function based on the cloud-to-air ground surface downlink short-wave radiation estimation value and the ground observation value, adjusting parameters of the physically constrained multi-task learning model through loss value back propagation, and training to obtain an optimal cloud-to-air ground surface downlink short-wave radiation estimation model; and S5, based on the optimal cloud-air ground surface downlink short-wave radiation estimation model obtained by training, estimating the cloud-air ground surface downlink short-wave radiation estimation value of the target area. The method provided by the invention can improve the estimation precision of the earth surface downlink short-wave radiation under the cloud and air, and has good stability and interpretability.

The invention discloses a photovoltaic power prediction method based on a stationary satellite neural network model, and belongs to the technical field of photovoltaic power prediction, and the method comprises the steps: obtaining base station radiation historical observation data, satellite historical observation data and ground meteorological historical observation data, carrying out the space-time matching of all the obtained data, and obtaining a prediction result; performing fusion enhancement on the satellite historical observation data and the ground meteorological historical observation data to obtain enhanced fusion features; constructing an earth surface short wave radiation prediction model, taking the enhanced fusion features as input, and taking base station radiation historical observation data as target output for training; future satellite parameters are obtained and input into the trained earth surface short wave radiation prediction model, and a future earth surface short wave radiation value can be predicted; and based on the obtained future earth surface short wave radiation value, combining the position information of the photovoltaic power station to predict the output power of the photovoltaic module. Therefore, the prediction of the output power of the photovoltaic module can be realized.

The present invention relates to a shortwave radiation full-factor integrated remote sensing estimation method and system, wherein the method comprises: using the albedo of the acquired remote sensing observation data as the input of a pre-constructed simulation library, obtaining the radiation brightness of the blue, green and red bands at the top of the atmosphere or a certain height based on the atmospheric parameters in the simulation library; comparing the radiation brightness obtained by the simulation library with the radiation brightness of the acquired remote sensing observation data, and then matching the atmospheric parameters that meet the preset conditions in the simulation library according to the comparison result; and analyzing and obtaining the full elements of shortwave radiation according to the albedo and the atmospheric parameters that meet the preset conditions. The present invention proposes a new idea of ​​shortwave radiation full-factor integrated remote sensing estimation, which can realize the synchronous and high-precision estimation of 8 types of shortwave radiation through the radiation brightness data of simulation data and remote sensing data, and the present invention does not require atmospheric parameters such as cloud detection and aerosols, and is applicable to all weather and global scales.

The present invention provides a method for estimating downward shortwave radiation from a cloud-space surface, comprising: S1. collecting data and constructing a sample data set; S2. constructing a multi-task learning model with physical constraints to obtain estimated values ​​of two key parameters in the cloud-space radiation estimation model; S3. based on the cloud-space radiation estimation method in the physical model FARMS, combined with the key parameters estimated by the deep learning model, obtaining the estimated value of downward shortwave radiation from the cloud-space surface; S4. based on the estimated value of downward shortwave radiation from the cloud-space surface and the ground observation value, calculating the loss function, adjusting the parameters of the multi-task learning model with physical constraints by back propagation of the loss value, and training to obtain the optimal cloud-space surface downward shortwave radiation estimation model; and S5. based on the optimal cloud-space surface downward shortwave radiation estimation model obtained by training, estimating the estimated value of downward shortwave radiation from the cloud-space surface in the target area. The method of the present invention can improve the estimation accuracy of downward shortwave radiation from the surface under the cloud-space, and has good stability and interpretability.

The invention provides an ultrashort wave radiation source distributed positioning method and system, and relates to the technical field of ultrashort wave radiation source positioning, and the method comprises the steps: constructing a heterogeneous unmanned plane group comprising a control node and a monitoring node; based on a multi-agent reinforcement learning algorithm, respectively configuring differentiated decision strategies for the control nodes and the monitoring nodes so as to guide the heterogeneous unmanned aerial vehicle group to perform collaborative search in the task area; a plurality of monitoring nodes are utilized to synchronously acquire signal characteristic parameters of a radiation source, the signal characteristic parameters from a plurality of spatially distributed monitoring nodes are aggregated, and a positioning result of the radiation source is obtained through calculation. According to the invention, the problem of how to realize high-precision and high-efficiency distributed positioning of the ultra-short wave radiation source through intelligent cooperation of heterogeneous clusters under the condition that the load, endurance and communication capability of the unmanned aerial vehicle are limited is solved.

The invention discloses a radiometer support and device and an unmanned aerial vehicle, and relates to the technical field of unmanned aerial vehicles. The radiometer support comprises a holder body, a connecting support and an instrument mounting support; the connecting bracket is mounted at one end of the holder body; and the instrument mounting bracket is detachably connected with the connecting bracket. The holder body is utilized to ensure the overall stability of the bracket, so that the stable use of the carried radiometer is ensured. And the connecting bracket is designed to be detachably connected and matched with the instrument mounting bracket, so that different instrument mounting brackets can be replaced according to needs, detection instruments such as long-wave radiometers and short-wave radiometers of different specifications can be conveniently mounted, and the applicability is better.

The invention discloses a near-surface air temperature data downscaling method driven by multi-source collaborative variables, which relates to the technical field of air temperature data processing and comprises the steps of data preprocessing, sample division, downscaling model construction and air temperature data processing. The method comprises the following steps: firstly, introducing cloud cover, long / short wave radiation, display / latent heat flux and other elements as collaborative variables based on a mode output statistical thought, generating a multi-dimensional multi-source variable data set, and performing preprocessing such as resampling to form a complete data set; carrying out sample division and balance by adopting K-fold cross validation and a first-time adaptive decline algorithm to obtain a total training set and an independent validation set; stable and effective features are screened, and then three types of models including an elastic network, a Bayesian optimization random forest and a neural architecture search-based long and short term memory network are constructed; the to-be-processed data is input into the model to generate high-resolution air temperature data, the data precision is ensured through multi-dimensional verification, systematic deviation is effectively restrained, nonlinear correlation and extreme air temperature correction capacity are enhanced, the space-time stability is improved, and the method is suitable for climatic analysis, ecological environment evaluation and other scenes.

The invention provides a short-wave radiation source time difference positioning method based on transfer learning and a deep neural network, and belongs to the field of radio monitoring and positioning. According to the method, a short-wave time difference positioning system is established, an ionosphere model is used for calculating related parameters to obtain simulation data, actual data are provided through a monitoring station, and the two kinds of data are subjected to identical preprocessing. Then, training a deep neural network by using the preprocessed simulation data to realize high-precision positioning under a simulation condition; model and parameter migration is carried out on the network through migration learning, the network is improved, the network is trained through preprocessed actual data to finely adjust parameters, and finally high-precision positioning of the short-wave radiation source under the actual condition is achieved. According to the method, the problem that the positioning error is large due to the fact that the time-varying property and the distance difference of the ionosphere are influenced by noise in the existing short wave positioning technology is effectively solved, and the problem that the use of a neural network method is limited due to insufficient data volume under the actual condition is also solved.

The invention belongs to the field of communication, and particularly discloses a method for calculating the coverage area of an ultra-short wave radiation source on a fluctuating ground, which comprises the following steps of: S1, acquiring a mathematical elevation map of a simulation area, dividing the map into grids according to resolution, and generating a data matrix containing an elevation value and a landform value of each grid point; s2, according to the position of a radiation source and the position of any receiving point in a simulation area, calculating a propagation path between the radiation source and the receiving point based on the data matrix, and extracting an elevation vector, a landform vector and a distance vector on the propagation path; s3, calling a radio wave propagation model to calculate signal loss values on all propagation paths; s4, calculating the signal arrival power of the receiving point; by introducing the digital elevation model and the radio wave propagation model, elevation map data of any area can be loaded and calculated, the radio wave propagation effect of the ultra-short wave radiation source can be simulated and calculated, accurate calculation of ultra-short wave signal coverage under the rugged topography is realized, and the layout position of the communication radiation source is optimized.

The invention provides a photovoltaic prediction method and device based on remote sensing data, a medium and electronic equipment, and relates to the technical field of power grids. Obtaining terrain elevation data under a preset resolution; performing terrain correction according to the terrain elevation data; after terrain correction, short-wave radiation data are predicted according to satellite remote sensing data; and obtaining photovoltaic power generation power through a prediction model according to the short-wave radiation data and the meteorological environment data. And a photovoltaic power station power prediction model is constructed, and accurate prediction of the photovoltaic power station power is realized. And accurate prediction of the photovoltaic power generation power is realized.

A Short-Wave Radiation (SWR) system comprising: (i) a light assembly, comprising at least one light source and being configured to: (a) illuminate a front side of an ionization target with first illumination; and (b) illuminate a back side of the ionization target with second illumination; (ii) a controller, configured to control the light assembly for illuminating the ionization target from the front side of the ionization target using the first illumination and at least partly concurrently illuminating the ionization target from the back side of the ionization target using the second illumination; and (iii) an optical assembly configured to collect SWR emitted from the front side of the ionization target and to direct the collected SWR toward a designated beam direction of the SWR system, wherein the SWR emitted from the front side results from a target illumination scheme that comprises at least the first illumination and the second illumination.

The invention discloses an outdoor space pedestrian thermal comfort detection, evaluation and improvement method based on an unmanned aerial vehicle low-altitude remote sensing technology, and relates to the field of outdoor thermal environment detection and transformation. A thermal infrared image and a multispectral image of a three-dimensional surface of an urban complex scene are synchronously obtained from multiple angles, original images are processed in batches, and characteristic parameter space distribution representing multi-scene surface optics, openness and thermophysical attributes and a thermophysical field representing ideal three-dimensional diffusion surface long and short wave radiation are obtained. In combination with synchronously observed sun and sky radiation and near-earth meteorological parameters, an index view ball method and a ray tracing technology are utilized to generate pedestrian average radiation temperature and outdoor thermal comfort index distribution with high spatial resolution. Aiming at pedestrian thermal comfort evaluation results in different scenes, the invention provides a method for improving the thermal comfort current situation of a specific case by using automatic machine learning so as to improve the thermal comfort of a human body near the ground.

The present invention discloses a portable AR-based intelligent perception method and device for urban thermal environment. The method comprises the following steps: using AR glasses to collect panoramic RGB street view images from the user's perspective, and synchronously obtaining time, geographic location, and meteorological parameters; using a generative adversarial network to map the RGB images and environmental parameters into a panoramic infrared thermal map, and obtaining the radiation temperature of each pixel; projecting the panoramic thermal map onto a unit sphere centered on the user, and calculating the long-wave radiation flux by integrating the spherical angles; and calculating the short-wave radiation flux based on a solar radiation model using the solar altitude angle and other factors; fusing the total radiation to calculate the average radiation temperature, and finally superimposing the thermal map and / or the average radiation temperature on a real or virtual environment through AR glasses or a smart terminal to achieve spatialized heat load visualization.

The utility model discloses an energy-saving window for a passive house, which comprises a main frame, and the inner wall of the main frame is fixedly connected with first glass, second glass, third glass and fourth glass respectively. Through mutual cooperation of the first glass, the second glass, the third glass and the fourth glass, special coating films on the surfaces of the first glass, the second glass, the third glass and the fourth glass can reflect indoor long-wave radiation, reduce heat loss to the outside, allow solar short-wave radiation to enter the inside, realize natural lighting and solar heat gain, reduce heat transfer through the heat insulation strips, and improve the heat efficiency. According to the energy-saving window for the passive house, the heat insulation performance of the energy-saving window for the passive house is improved, the sealing performance between the first glass and the main frame and between the fourth glass and the main frame can be improved by arranging a first sealing rubber strip, external dust is prevented from entering the main frame, and inert gas can be filled into an inflation pipe by arranging the inflation pipe and a sealing plug; inert gas can slow down loss of heat on the surface of glass in the main frame.

The present application belongs to the technical field of remote sensing data processing, and specifically relates to a terrain correction method for surface radiation in mountainous areas, including: S10, obtaining plane surface radiation data of the same period, wherein the plane surface radiation data includes short-wave radiation data and / or long-wave radiation data of the plane surface; S20, inputting the plane surface radiation data into a pre-established mountainous area radiation correction model to obtain the mountainous area surface radiation; wherein the mountainous area radiation correction model is a mathematical model that outputs the mountainous area surface radiation after correcting the plane surface radiation by a preset radiation correction coefficient; the radiation correction coefficient is determined based on the pixel area and the corresponding mountainous area surface. Correcting the mountainous area radiation by the correction method of the present application not only has a small amount of calculation and high efficiency, but also the radiation correction result obtained is more accurate.

The utility model belongs to the technical field of silimor brick, especially relates to a heat -insulating structure of nanometer modified silimor brick, including silimor brick base body, still include: coating heat -insulating layer, coating heat -insulating layer sets up in the circumferential side of silimor brick base body, the circumferential side of coating heat -insulating layer is provided with self -cleaning coating, the circumferential side of self -cleaning coating sets up surface functional layer, the top of silimor brick base body is provided with a plurality of recesses, can reflect most solar short -wave radiation, and under the light through photocatalytic decomposition surface pollutant, realize self -cleaning, block water vapor and acidic gas simultaneously, and effectively reduce the heat conduction efficiency, long -wave thermal radiation can also be blocked, the recess of top strengthens and mortar's occlusion, reduces the brick joint gap, and can guide rainwater to discharge, avoid water absorption and lead to the rise of thermal conductivity coefficient, the whole device passes through the synergies of each layer, effectively blocks heat transfer from reflection, conduction, convection three aspects, keeps long -term functional stability simultaneously.

The invention discloses a numerical weather mode multi-source data assimilation method based on a GNSS (Global Navigation Satellite System) water vapor chromatography result, which relates to the field of weather forecast and numerical weather modes and comprises the following steps: arranging a numerical weather mode in a target area; collecting multi-source data of the target area, wherein the multi-source data comprises GNSS water vapor chromatography data, satellite data, radar data and observation data of a ground meteorological station, a sonde and an aircraft; performing data assimilation on each item of data in the multi-source data, and converting the multi-source data into a unified data format; and permutation and combination are carried out on all parameterization schemes of cloud microphysics, cumulus convection, a boundary layer, a land surface and a long and short wave radiation process in the numerical weather mode, the actual operation effect of each scheme combination is evaluated, and an optimal parameterization scheme is obtained through screening. According to the multi-source data assimilation method, the initial field of the numerical weather mode can be improved, so that the weather forecast precision is improved.

The present invention discloses a method and system for controlling feeding of deep-water cage fish, the method comprising generating a detailed list of farmed fish in a target deep-water area according to fish information, performing multiple rounds of pepper and salt denoising on the acquired image data of the target deep-water farm area, inputting underwater light data into a water body thermal stratification model to obtain each deep-water layer and short-wave radiation data corresponding to each deep-water layer; analyzing and identifying the image data through an AI image recognition algorithm to obtain fish growth data, constructing a feeding amount control model according to the detailed list of farmed fish, fish growth data and short-wave radiation data, and generating a farming visualization report to realize feeding control of fish in the target deep-water farm area. The present invention analyzes fish growth and health through image data, constructs and optimizes a feeding control model according to data such as ammonia nitrogen content, dissolved oxygen content and short-wave radiation, optimizes feeding amount control, so as to improve fish growth rate and quality, and realize long-term sustainable farming.

A building external thermal radiation monitoring device disclosed by the present invention comprises a main controller, a communicator and at least one detection mechanism, the detection mechanism comprises a main frame body, a short-wave radiation sensor, a long-wave radiation sensor and a sub-controller, and the short-wave radiation sensor and the long-wave radiation sensor are both arranged on the top side of the main frame body. The short-wave radiation sensor and the long-wave radiation sensor are electrically connected with the sub-controller respectively; the sub-controller is used for acquiring detection data of the short-wave radiation sensor and the long-wave radiation sensor respectively; the communicator is in signal connection with the main controller and each sub-controller, and the main controller is used for determining each detection point according to a target building, so that at least one detection mechanism is arranged in each detection point; and the main controller is used for acquiring detection data of the detection mechanism in each detection point through the communicator. According to the technical scheme provided by the invention, the data accuracy is further improved, and the actual application requirements of the existing thermal radiation monitoring technology are better met.

The invention discloses an ozone concentration forecasting method, which utilizes air quality observation data of 326 cities throughout the country, processes abnormal and missing data, and reanalyzes relative humidity, precipitation, boundary layer height, short-wave radiation, sea level air pressure, wind direction, wind speed and dew point in the data in combination with ERA5. A high-quality database used for supporting deep learning is established, graph structures are established with cities and provinces as nodes respectively, and the spatial dependency relationship between the nodes is adjusted in a self-adaptive mode through a dynamic learnable edge weight mechanism; self-adaptively updating the edge weight according to the input spatio-temporal characteristics, and further quantifying and analyzing the propagation path of ozone among different regions; and key meteorology and precursor factors are dynamically identified through a channel attention mechanism. According to the invention, the accuracy and real-time performance of ozone forecasting are improved, and transmission paths and driving factors thereof between regions can be disclosed; and scientific basis and technical support are provided for ozone pollution prevention and control and regional joint prevention and joint control.

This invention discloses a parametric simulation method for ocean forecasting based on cross-density vertical mixing processes, comprising: Step 1, acquiring a three-dimensional multivariate marine environmental field, water depth data, vortex trajectory dataset, vortex kinetic energy data, and atmospheric driving field. The environmental field includes sea surface height, ocean temperature, ocean salinity, and meridional and zonal current velocities; the atmospheric driving field includes wind speed, sea surface pressure, 2-meter temperature, sea surface temperature, shortwave radiation, cloud component, precipitation, and relative humidity; Step 2, introducing vortex horizontal asymmetry, constructing a parametric ocean model based on cross-density vertical mixing processes, and calculating the vertical mixing coefficient; Step 3, constructing a regional ocean model based on the regional ocean numerical model ROMS, and verifying the vertical mixing coefficient; Step 4, performing ocean forecasting using the parametric ocean model based on cross-density vertical mixing processes. This invention links vertical mixing with the influence of vortex horizontal asymmetry, improving the accuracy of multi-element ocean simulation.

The invention relates to the technical field of forest evapotranspiration measurement, and discloses a forest evapotranspiration measurement method and device. The measuring device comprises a sensor combination of which the installation position is adaptive to the height of a forest canopy, a soil short-wave radiation sensing element adaptive to the height of forest surface soil, and a soil temperature and humidity sensing element adaptive to the height of forest lower soil. The method comprises the following steps: calculating canopy transpiration based on energy balance according to canopy short-wave radiation information, air temperature information and leaf surface average temperature information; acquiring soil short-wave radiation information based on the soil short-wave radiation sensing element, acquiring soil temperature and humidity information based on the soil temperature and humidity sensing element, and calculating under-forest soil evaporation according to the soil short-wave radiation information and the soil temperature and humidity information based on a soil hydrothermal dynamic state; the forest evapotranspiration is calculated based on the double-source evapotranspiration theory according to the canopy evapotranspiration and the under-forest soil evapotranspiration, and the method is accurately applicable to different forest ecological vegetation types and different soil texture conditions.

The invention discloses a preparation method of sodium-doped coal-based yellow fluorescent carbon dots, and belongs to the technical field of coal-based carbon nanomaterials. The preparation method of the sodium-doped coal-based yellow fluorescent carbon dots comprises the following steps: adding bituminous coal into a mixed solution of concentrated nitric acid and hydrogen peroxide, carrying out a first mixing reaction, adding sodium hydroxide, adjusting the pH value to be neutral, and carrying out a second mixing reaction to obtain a coal sample; a coal sample is added into water to prepare a bituminous coal mixed solution, then the bituminous coal mixed solution is subjected to cavitation stripping treatment, and the sodium-doped coal-based yellow fluorescent carbon dots are obtained. The coal-based carbon dots with yellow fluorescence are prepared, the bottleneck that the fluorescence of the coal-based carbon dots is generally blue is broken through, the fluorescence wavelength of the coal-based carbon dots is prolonged, damage of short-wave radiation to biological tissues is avoided, the color gamut range of the coal-based carbon dots is expanded, and the application range of the coal-based carbon dots is widened. And the fluorescent requirements of flexible quantum dot display, a warm-color white LED light source, full-spectrum catalysis and the like on long wavelength are met.