199 results about "Solar zenith angle" patented technology

The embodiment of the invention provides a new energy optical power correction method and system based on weather abrupt change prediction. The method comprises the following steps: identifying a cloud layer type contained in a target area, and obtaining a cloud layer type coverage rate; if the cumulonimbus coverage rate exceeds a first threshold value, predicting a cloud layer movement path in combination with the cloud layer movement vector field to obtain a first cloud layer coverage change sequence; if the layer cloud coverage rate exceeds a second threshold value, an irradiance attenuation coefficient is predicted based on the cloud layer thickness in the meteorological data and the solar altitude angle, and a second cloud layer coverage change sequence is obtained in combination with the ground aerosol optical thickness and the corrected irradiance attenuation coefficient; and monitoring real-time operation data of the power station, combining the first / second cloud layer coverage change sequence, predicting a matching relationship between a cloud layer moving direction and a power station power reduction area by adopting a double-flow Transform architecture, calculating a power fluctuation range corresponding to each power station power reduction area, dynamically adjusting power grid operation parameters of a target area, and determining the power grid operation parameters of the target area. The power grid stability is ensured.

The invention relates to the technical field of leaf nitrogen content estimation, in particular to a method for establishing a grassland plant nitrogen content monitoring model based on a remote sensing technology. The method comprises the following steps: controlling an unmanned aerial vehicle platform carrying a narrowband multispectral camera and a linear polarization camera, and collecting a spectral image sequence and a polarization image group at an observation window with a solar zenith angle of 30-40 degrees; extracting a reflectivity value of each wave band in the spectral image sequence, calculating a reflectivity first-order derivative and determining a red edge position offset; extracting horizontal and vertical polarization components in the polarization image group, calculating a polarization degree and constructing a polarization degree difference index; and identifying the center of the fecal spot by searching a pixel with a local maximum polarization degree difference index and red edge position offset blue shift exceeding a preset threshold value. According to the method, excrement spot recognition and remote sensing description of the nitrogen influence range thereof are achieved through double-index complementation of the red edge position offset and the polarization degree difference index.

The invention relates to the technical field of environmental shadow analysis, and discloses an environmental shadow analysis method for photovoltaic power station design, which comprises the following steps: collecting and preprocessing geographic space data of a photovoltaic power station; calculating a solar altitude angle and an azimuth angle based on the pre-processed parameters, and generating a three-dimensional solar direction vector; analyzing the geometric surface of the three-dimensional obstacle model, screening a visible surface patch according to a sun direction vector, and sampling effective projection points; dynamically updating the sun direction vector in a specified time period, and calculating shadow coordinates of projection points on the ground or an inclined plane in each time period; and generating shadow contours of all time periods and combining the shadow contours into a complete influence area. According to the invention, through the dynamic sun trajectory modeling and complex obstacle surface analysis technology and in combination with the multi-modal projection correction and Boolean operation merging strategy, high-precision analysis of shadow spatial-temporal distribution in a complex environment, multi-installation scene self-adaption and dynamic shielding influence quantitative evaluation are realized.

The invention belongs to the technical field of display equipment optimization, and discloses a display equipment brightness and color temperature control system based on ambient light adaptive adjustment, and the system comprises the steps: collecting multi-sensor data, constructing a polarization responsibility domain matrix, and generating a salt mist scattering field intensity graph; acquiring a solar altitude, and when the altitude meets an abnormal triggering condition, triggering low-angle light field reconstruction, generating an angle-region suppression mapping table, calculating a light compensation coefficient, and generating a suppression-compensation dual-channel instruction set; analyzing instruction conflicts, generating a driving instruction chain, and executing dynamic dimming; calculating a credibility index, freezing a partition voucher and activating a security mode when an abnormal state is triggered, and generating a verification report; and updating a polarization responsibility domain matrix, calibrating a salt mist scattering field intensity graph, optimizing an angle-region suppression mapping table, generating a new generation of control parameter set, and refreshing a final driving instruction chain.

The invention discloses a method for interplanting amorphophallus bulbifer through photovoltaic shading. The method comprises the steps that interplanting areas are established between photovoltaic array lines; the interplanting area is divided into a fixed shading area and a variable light-transmitting area according to the projection range of the photovoltaic panels, the fixed shading area is located in the area under the photovoltaic panels, and the variable light-transmitting area is located in a light-transmitting zone between the adjacent photovoltaic panels; planting furrows are formed in the fixed shading area according to the line spacing of 40-50 cm; selecting amorphophallus bulbifer tubers, and performing field planting on the planting bed; a sunshade net sliding rail system driven by a stepping motor is arranged in the variable light-transmitting area, an illumination intensity sensor is installed on a sliding rail, the sensor is connected with a controller, and the controller automatically adjusts the horizontal displacement of the sunshade net every day according to a solar altitude calculation model and real-time illumination data; and establishing an intelligent drip irrigation system. According to the method, a stable shading environment and appropriate soil humidity can be provided for the amorphophallus bulbifer, manual operation is reduced, the automation level of the interplanting process is improved, and the specific requirements of crops for the growth environment are met.

The invention provides a three-dimensional cloud type classification method, device and equipment based on multi-source meteorological data fusion, and a medium. The method comprises the following steps: acquiring satellite data, radar data, numerical mode data and ground observation data, and performing preprocessing; a three-dimensional cloud cover analysis method is adopted, the three-dimensional cloud cover of numerical mode data is used as a background field, and a multi-source data fused three-dimensional cloud cover lattice point field is formed; establishing and training a plurality of cloud type classification models by using an XGBOOST multi-classification method, and matching the corresponding cloud type classification models based on the diagnosis results of the solar elevation angle of each grid point of the multi-source data fused three-dimensional cloud cover grid point field at the monitoring moment and the cloud layer distribution in the vertical direction to obtain the cloud type classification of each cloud layer in the vertical direction. And generating a three-dimensional cloud type classification result to solve the problem that the three-dimensional cloud type classification monitoring is limited due to the lack of effective training samples due to the fact that only satellite data is used and cannot penetrate through the uppermost cloud layer to obtain a vertical structure.

The invention relates to the technical field of vegetable cultivation, and discloses an automatic light supplement control method and system for vegetable cultivation, and the method comprises the steps: determining the growth state of a vegetable crop based on crop image information and a crop growth model, and judging whether to execute a light supplement strategy or not according to a solar altitude, determining a backtracking light supplementing strategy or an initial light supplementing strategy according to the occurrence frequency of the growth state in the historical light supplementing database, determining target light supplementing data of the vegetable crops according to the number of the light supplementing data, and when the initial light supplementing strategy is determined, determining the target light supplementing data of the vegetable crops based on a recurrent neural network model, and analyzing the historical light supplement record to determine a light supplement swing factor of the light supplement lamp, adjusting the target light supplement data based on the light supplement swing factor, and performing light supplement on the vegetable crops according to the adjusted target light supplement data. According to the invention, the reliability of light supplement is ensured through the crop growth model and the light supplement swing factor.

The invention belongs to the technical field of photovoltaic power generation, and provides a photovoltaic module dip angle and azimuth angle optimization method and system based on hour electricity price, and the method comprises the steps: firstly determining a solar elevation angle and a solar azimuth angle according to a geographic position; determining an incident angle between sunlight and the surface of the photovoltaic module according to the solar elevation angle and the solar azimuth angle; then, according to the incident angle and the irradiation data, the hour effective radiation power of the photovoltaic module under any angle combination is determined, so that the total generation power is obtained; constructing a unit area annual income objective function by using the hour electricity price as a weight; and finally, according to the objective function, determining an optimal combination of the inclination angle and the azimuth angle of the photovoltaic module. Hour-level sun position calculation and incident angle radiation modeling are introduced, and a revenue function is constructed by taking the hour-by-hour electricity price as a weight, so that the optimal combination of the dip angle and the azimuth angle of the photovoltaic module under the optimal economical efficiency is realized.

The invention provides a visual celestial navigation method based on sun centroid extraction and sea-sky-line fitting. Belongs to the application of image processing technology in the field of celestial navigation. The method mainly comprises the steps of extracting a high-precision sea-sky-line by using a textural feature segmentation and Canny-Hough transform combined algorithm, and extracting a sky region based on a sea-sky-line segmentation result. A solar facula image candidate region and a sun candidate contour are constructed through a sky region, a dual optimization strategy of region similarity screening and facula feature scoring is proposed, and sub-pixel-level sun centroid coordinate calculation is realized by combining an intensity weighted center method and nonlinear least square two-dimensional Gaussian model fitting. And further constructing a camera coordinate system space vector through the orthogonal projection point of the sea-sky-line and the sun centroid, calculating a sun elevation angle based on a vector included angle, and performing angle compensation by adopting an atmospheric refraction correction model. And finally, fusing multi-moment observation data through a sun shift line positioning method, completing autonomous calculation of the ship position, and improving the positioning precision.

The invention relates to the field of meteorological prediction, in particular to a multispectral-based all-day sea fog detection method, and solves the problems of failure of a morning and evening period detection algorithm, insufficient sea fog and low cloud distinguishing precision, split algorithm flow and lack of systematicness in the current sea fog detection field. The method specifically comprises the following steps: acquiring satellite data, preprocessing the satellite data, and calculating a solar zenith angle SZA of each pixel; distributing each pixel to a corresponding processing mode according to the value of the SZA; on the basis of the distributed processing mode, adaptive spectrum preliminary screening of the corresponding mode is executed, and a preliminary screening binary mask is generated; based on the processing mode, performing regional texture consistency analysis on the primarily screened binary mask to effectively relieve low cloud interference; and performing post-processing optimization on the reserved sea fog area, and outputting a final sea fog detection result. High-precision and high-stability detection of all-day sea fog can be achieved, good performance is still kept in the morning and night transition period, and sea fog and low clouds can be effectively distinguished.

The invention provides a photovoltaic array dynamic adjustment method based on artificial intelligence shadow detection and prediction. According to the method, a multi-modal data set is formed by collecting photovoltaic array operation and maintenance related data, accurate recognition of a shadow area is achieved through quantization feature enhancement and a dynamic space attention mechanism, shadow boundary coordinates are determined, and the shadow coverage rate is calculated. Further calculating the shadow expansion speed and propagation time according to the shadow boundary coordinates, the solar altitude and the shelter parameters, and predicting the shadow coverage range. Meanwhile, the hot spot risk is quantified through the temperature difference between the shadow area and the non-shadow area and the shadow duration, and graded early warning is triggered. And dynamically adjusting the output voltage of the photovoltaic array based on the shadow coverage rate, and tracking the maximum power point through a particle swarm optimization algorithm. In addition, in combination with a shadow prediction result, the angle of the photovoltaic panel is mechanically adjusted to avoid a shadow area. According to the invention, the power generation efficiency of the photovoltaic array under the shadow shielding condition is improved, and the stability and safety of the system are enhanced.

The invention relates to the technical field of automobile body paint weather resistance testing, in particular to a sunlight self-following reflection system and a control method, and the sunlight self-following reflection system comprises a buried support, a rotation driving mechanism, a rotation platform and a mirror reflection mechanism. The rotary driving mechanism rotates by 360 degrees in a horizontal plane through a driving unit, so that the direction of a vehicle head is always aligned with a solar azimuth angle; the mirror reflection mechanism adjusts the pitching angle of a reflection plate through a micro motor, and it is ensured that sunlight is projected to the surface of a vehicle body with a preset standard irradiance value. The system further comprises an air supply mechanism and an online measuring instrument which are used for cooling, dedusting and tracking the position of the sun in real time. According to the invention, test errors caused by solar altitude changes and regional differences can be eliminated, and the comparability and repeatability of test results are significantly improved.

The invention discloses a polar region daytime sea fog / low cloud detection method and device based on multi-source polar orbit satellites and a medium. The method comprises the steps that remote sensing image data collected by the multi-source polar orbit satellites are acquired and preprocessed; calculating a sea surface identification index by using data of two preset wave bands in the preprocessed remote sensing image data, and jointly removing areas related to seawater and sea ice / snow in the preprocessed remote sensing image data according to the sea surface identification index and near-infrared wave band reflectivity data in the remote sensing image data; for each pixel of a third preset wave band in the remote sensing image data from which the seawater, the sea ice and the snow are removed, calculating a gray-level co-occurrence matrix of the pixels, and counting a plurality of texture features based on the gray-level co-occurrence matrix; and inputting the statistical texture feature values corresponding to the remote sensing images corresponding to all polar orbit satellites into the trained random forest model, identifying and removing medium and high clouds in the random forest model, and obtaining sea fog / low clouds as the remainder. The influence of satellite difference and solar altitude angle change on the method is small.

The invention relates to the technical field of street lamp use, in particular to a liftable rod arm multi-scene application street lamp pole device and an operation method thereof. The liftable rod arm multi-scene application street lamp pole device comprises a lamp pole base, a lifting connecting rod is slidably arranged in the lamp pole base in the height direction of the lamp pole base, and a lamp is installed on the lifting connecting rod; a power generation mechanism which changes in a self-adaptive mode and is electrically connected with the lamp is installed on the lifting connecting rod. Aiming at solar altitude change caused by season change, the adjusting disc is rotated to drive the solar panel to synchronously perform angle deflection around the lifting connecting rod. The process can correct the included angle between the solar panel and the sunlight in real time, effectively reduce the deviation degree of the two, ensure that the solar panel can be always aligned with the sun trajectory in different seasons of spring, summer, autumn and winter, and capture the illumination energy to the maximum extent.

The invention belongs to the field of satellite remote sensing fire monitoring, and discloses a satellite remote sensing forest fire initial fire point monitoring method, which comprises the following steps: acquiring satellite data as input data; reading the zenith angle of the sun in the satellite data, and judging the time period as a day time period, a night time period and a morning and night junction time period; the solar zenith angle, the sensor zenith angle and the like need to be read in daytime period data so as to filter solar flares; carrying out simple cloud detection on data in all time periods by utilizing 11-micron channel brightness temperature and 11-4-micron channel brightness temperature, expanding an adaptive window by taking a suspected initial fire point pixel as a center, and calculating 4-micron channel brightness temperature difference, 11-micron channel brightness temperature difference and 4-11-micron channel brightness temperature difference of a background pixel by utilizing a time sequence method; and counting the mean value and the standard deviation of the background pixels, and confirming and extracting a forecast initial fire point by using a normal distribution starting point algorithm. According to the method, the timeliness and accuracy of early warning of the fire disaster are improved, and important technical support is provided for forest fire prevention decision making.

The invention relates to a method, a device and equipment for determining an autonomous wake-up moment of a lunar rover and a medium, and the method comprises the steps: determining a current wake-up interval according to historical wake-up moment data of the lunar rover at a current moment and solar altitude forecast; according to the current wake-up interval and a pre-constructed relation model, determining a required incident angle sequence corresponding to the lunar surface patroller at the current moment; generating an actual incident angle sequence corresponding to the current wake-up interval according to the solar altitude forecast and the dormancy attitude parameters of the lunar surface patroller; and according to the required incident angle sequence and the actual incident angle sequence, determining the autonomous wake-up time of the lunar surface patroller. Through the method provided by the invention, full-autonomous wake-up moment determination based on historical data dynamic correction and orbit forecast accurate calculation is realized, the prediction accuracy of the wake-up moment is effectively improved, the dependence on ground measurement and control is reduced, and the method can adapt to complex in-orbit environments such as solar wing performance degradation and day-moon distance periodic change.

The invention discloses an optical scanning radiometer in-orbit dark background long time series data extraction method and system, and the method comprises the steps: obtaining cold air observation data and solar zenith angle data from an optical scanning radiometer, and generating a channel-level cold air observation data set and a channel-level solar zenith angle data set. According to the channel-level cold air observation data set and the channel-level solar zenith angle data set, various screening methods are adopted to generate to-be-selected schemes and screening data sets of the to-be-selected schemes. For each to-be-selected scheme, calculating a statistical mean value and data volatility based on a screening data set of the to-be-selected scheme, calculating a dark background representative value of the to-be-selected scheme, and determining a mean value sorting sequence number and a volatility sorting sequence number; and determining an optimal dark background value scheme by adopting a weighted assignment method according to the mean sorting sequence number and the volatility sorting sequence number. Therefore, according to the in-orbit dark background long-time-sequence data extraction method of the optical scanning radiometer, long-time-sequence stable extraction is achieved, and the remote sensing data radiometric calibration precision is remarkably improved.

The invention belongs to the technical field of photovoltaic power generation, and discloses a distributed roof photovoltaic module maximum generating capacity arrangement method and system, and the method comprises the steps: obtaining the position information and image information of a project location, and carrying out the calculation to obtain a solar altitude angle and a solar azimuth angle; calculating to obtain a shadow union set according to the altitude angle and the azimuth angle of the sun; based on the shadow union set, obtaining an available area of the final arrangeable component; and after the available area is obtained, carrying out optimal position arrangement on the photovoltaic module by taking the maximum generating capacity and the highest coverage rate as targets. According to the distributed roof photovoltaic module maximum generating capacity arrangement method, on the premise that design safety is guaranteed, the photovoltaic module arrangement design period can be greatly shortened, and the land utilization rate and the generating efficiency can be further improved through algorithm optimization.

The application provides a method, device, equipment and medium for reducing image shooting requirements, and relates to the field of computer vision. The method comprises: collecting multi-view images of a scene to be rendered; sampling on a camera ray corresponding to a given pixel point to obtain a sampling point coordinate and a view direction; calculating a hour angle h, an declination δ' and a solar elevation angle θ s , a solar azimuth angle Φ s , obtaining a global light direction vector, and encoding; encoding the shooting time of the image; inputting the sampling point coordinate, the view direction, the light encoding and the time encoding into a neural network to obtain the color and the volume density of the sampling point under the corresponding view; obtaining the final predicted pixel color by using volume rendering, calculating the color loss; and updating the neural network parameters by back propagation. The application can weaken or even eliminate the influence of light changes on outdoor shooting, and reduce the shooting requirements of neural radiance field images.

The application provides a photovoltaic array dynamic adjustment method based on artificial intelligence shadow detection and prediction. The method forms a multi-modal data set by collecting photovoltaic array operation and maintenance related data, uses quantumized feature enhancement and dynamic spatial attention mechanism to realize accurate identification of shadow area, determines shadow boundary coordinates and calculates shadow coverage. Further, according to the shadow boundary coordinates, the solar elevation angle and the shelter parameter, the shadow expansion speed and the propagation time are calculated, and the shadow coverage range is predicted. At the same time, the risk of hot spot is quantified by the temperature difference between the shadow area and the non-shadow area and the shadow duration, and the graded warning is triggered. Based on the shadow coverage rate, the photovoltaic array output voltage is dynamically adjusted, and the maximum power point is tracked through the particle swarm optimization algorithm. In addition, combined with the shadow prediction result, the angle of the photovoltaic panel is adjusted mechanically to avoid the shadow area. The application improves the power generation efficiency of the photovoltaic array under the condition of shadow shielding, and enhances the stability and safety of the system.

The invention provides a troposphere anisotropy-considered real-time PPP positioning method, and relates to the technical field of satellite navigation and positioning, and the method comprises the following steps: S01, receiving real-time GNSS observation data, broadcast ephemeris data and precision correction data, carrying out detection and restoration of clock slip and cycle slip, data quality control and preprocessing of antenna phase correlation errors on the data to obtain a preprocessed data set; s02, calculating the solar altitude after atmospheric refraction correction according to each preprocessed data set and the geographic position and observation time of the observation station corresponding to each data set; and S03, based on the solar altitude and the satellite altitude. According to the method, solar altitude parameters are introduced, the troposphere anisotropy effect caused by solar radiation is effectively modeled, and the precision and convergence speed of real-time precise single-point positioning are remarkably improved.

The invention relates to the technical field of photovoltaic power generation equipment, and discloses photovoltaic power generation equipment with a light following function, which comprises a photovoltaic panel, a vertical overturning driving mechanism, a rotating seat, a horizontal rotating driving mechanism, a base and an intelligent control module, after the rotating seat is rotatably arranged on the base, the rotating seat is driven by a horizontal rotating driving mechanism arranged on the base to rotate horizontally at a low speed, and after the photovoltaic panel is arranged on the rotating seat in an up-down turnover mode, the photovoltaic panel is driven by a vertical turnover driving mechanism arranged on the rotating seat to turn over up and down. The intelligent control module controls the vertical overturning driving mechanism and the horizontal rotation driving mechanism to work, and then the photovoltaic panel is driven to implement the light following effect. Compared with the prior art, the device has the advantages that through two-degree-of-freedom movement of horizontal rotation and vertical pitching, whole-course tracking of the solar altitude angle and the solar azimuth angle is achieved, and the sunlight receiving rate and the power generation efficiency of a photovoltaic panel are remarkably improved.

The application discloses a kind of floating offshore solar radiation measurement data correction method and system, it includes the following steps: obtaining the pitch angle and roll angle of floating offshore solar radiation measurement system;Obtain the unit normal vector of the measuring plane pointing to the sky in the horizontal plane rectangular coordinate system;Calculate the angle between the measuring plane and the horizontal plane;Get horizontal plane solar zenith angle and azimuth angle;Construct the unit vector along the direction of sunlight incidence pointing to the sun;Correct the zenith angle;Calculate the horizontal plane scattered irradiance value;The horizontal plane total irradiance saved by floating offshore solar radiation measurement system is corrected, and the corrected horizontal plane total irradiance is obtained.The measurement data of the floating offshore solar radiation measurement system is corrected by the application, the measurement error caused by the inclination of the measurement platform caused by wind and wave is reduced, and more accurate measurement data is provided for the evaluation of offshore light resources and the planning of offshore photovoltaic power station.

The application discloses a kind of inclined surface hourly solar radiation calculation method and related equipment, belong to solar energy resource assessment and building energy saving technical field.The method includes: obtaining horizontal plane solar radiation data and space-time information, and the inclination and azimuth of target inclined surface;Calculate solar elevation angle, solar incidence angle, clear sky index and horizontal plane scattering radiation ratio;Two scattering radiation conversion coefficients are obtained by using two basic models respectively;At least according to clear sky index, horizontal plane scattering radiation ratio and solar incidence angle to determine dynamic weight;Two scattering radiation conversion coefficients are weighted and summed with dynamic weight, to obtain combined scattering radiation conversion coefficient, and then obtain inclined surface hourly solar total radiation.The method is combined by dynamic weight based on weather state and solar position real-time change to two basic models with obvious difference in weather adaptability, overcome the limitation that single model is only accurate under certain weather, and does not depend on multi-regional long-term measured data, improve the calculation accuracy and applicability under all weather types.

This invention discloses a method and system for evaluating the complementarity of wind and solar resources based on physically embedded deep learning, belonging to the field of resource assessment. The method includes: acquiring meteorological elements and digital elevation model data for the target area; calculating the elevation change rate between adjacent grids, distinguishing between flat and non-flat areas based on the IGC algorithm, and extracting terrain features separately; generating periodic features of solar altitude angle through radiation data, and concatenating them with terrain features to obtain fused features; constructing a physically embedded NODE-SA-ConvLSTM model, combining a self-attention mechanism to capture the global dependencies of wind and solar elements, and outputting wind speed and radiation prediction results; using a constant error compensation mechanism to perform sliding balance correction on the prediction residuals; and quantifying the complementarity of regional wind and solar resources through a wind-solar complementarity coefficient. This invention, by introducing a physically embedded mechanism and continuous-time modeling, effectively improves the accuracy and stability of wind and solar resource prediction, realizing the complementary evaluation of wind and solar resource endowments.

This invention provides a method, apparatus, electronic device, and storage medium for calculating cloud judgment parameters. The method includes: determining the satellite position vector, solar vector, and satellite attitude matrix in the cloud judgment time inertial frame based on the time interval between the current time and the cloud judgment time; calculating the position information of the ground imaging point corresponding to each pixel after the time interval based on the satellite payload installation information, pixel line-of-sight information, and the satellite position vector and satellite attitude matrix in the cloud judgment time inertial frame; and calculating the cloud judgment parameters for each ground imaging point based on the position information of the ground imaging point corresponding to each pixel after the time interval and the solar vector in the cloud judgment time inertial frame. The cloud judgment parameters include at least one of the following: satellite zenith angle, solar zenith angle, geographic latitude and longitude, and relative azimuth angle. This solution can provide cloud judgment parameters for the cloud judgment process of satellite payloads.

The invention discloses an artificial intelligence ultra-short-term surface solar radiation prediction method based on satellite data. The artificial intelligence ultra-short-term surface solar radiation prediction method comprises the following steps: S1, collecting stationary satellite multi-channel remote sensing data and meteorological station data; s2, collecting geographical environment feature data; s3, constructing a dynamic NDVI coupling factor; s4, preprocessing data, and performing projection conversion and angle cosine conversion; s5, performing model training optimization on the ultra-short-term surface solar radiation prediction logic; and S6, obtaining and applying an ultra-short-term surface solar radiation prediction model. According to the invention, multi-party data information is integrated, a dynamic NDVI coupling factor is introduced innovatively, and the sensitivity under a low solar altitude condition is improved; an all-sky earth surface solar radiation estimation method is constructed, the frequency and the space coverage of radiation inversion are remarkably improved, and the method is suitable for short-term and imminent forecasting requirements under complex weather conditions; the ultra-short-term surface solar radiation prediction can be accurately provided, the prediction accuracy is extremely high, and the model has excellent prediction performance, generalization ability and engineering practicability.

The invention discloses a polar axis type solar direct radiation spectrum measurement method and system, belongs to the technical field of solar direct radiation spectrum measurement, and aims to solve the problems that an existing measurement system depends on complex double-axis tracking, has many errors, is high in maintenance cost and is insufficient in latitude adaptability. The system comprises a polar axis rotating reflector and a solar spectrum measurement system, the polar axis rotating reflector directly radiates and reflects the sun with the solar elevation angle of + / -23.5 degrees and the solar azimuth angle of + / -90 degrees to the measurement system, and measurement is achieved in combination with a spectrum reconstruction model. The spectral resolution is superior to 2 nm, the single-point error ranges from-6.83% to 6.61%, the area error ranges from-0.03% to 0.05%, the space-time uniformity is larger than or equal to 99.92%, the structure is simplified, all-year-round all-latitude high-precision measurement without moving tracking is achieved, and the method is suitable for the fields of solar energy development, climate change research and the like.

The application relates to the field of weather prediction, in particular to a full-time sea fog detection method based on multispectrum, which solves the problems of invalid detection algorithm in the morning and evening period, insufficient precision in distinguishing sea fog and low clouds and lack of systematicness in the current sea fog detection field. Specifically, the method comprises the following steps: acquiring satellite data and performing pretreatment, calculating the solar zenith angle (SZA) of each pixel; according to the value of the SZA, each pixel is assigned to a corresponding processing mode; based on the assigned processing mode, adaptive spectral preliminary screening of the corresponding mode is performed to generate a preliminary screening binary mask; based on the processed mode, regional texture consistency analysis is performed on the preliminary screening binary mask to effectively alleviate the low cloud interference; the retained sea fog area is post-processed and optimized to output the final sea fog detection result. The application can realize high-precision and high-stability detection of full-time sea fog, still maintains good performance in the morning and evening transition period, and can effectively distinguish sea fog and low clouds.

The present invention discloses a method and system for simulating the bidirectional reflectance of a rice canopy. The method comprises setting canopy vertical structure parameters and canopy component parameters according to the growth stage and growth characteristics of the rice, inputting the two parameters into a SAIL model, constructing a rice canopy radiation transmission model, and then inputting the soil reflectance, leaf area of ​​each vertical layer, leaf reflectance and leaf transmittance of different vertical layers, incident specular radiation ratio, simulated rice leaf inclination distribution function, solar zenith angle, observation zenith angle, and observation azimuth angle of each rice canopy growth stage into the constructed rice canopy radiation transmission model to simulate the canopy reflectance of the rice at each growth stage. Compared with the traditional canopy radiation transmission model, the present invention introduces rice canopy component parameters and quantitatively characterizes the heterogeneous distribution characteristics of the canopy vertical structure, significantly improving the simulation accuracy of the bidirectional reflectance of the canopy at each growth stage of the rice.