121 results about "Temporal resolution" patented technology

The invention discloses a thunder approaching prediction method and device based on multi-source meteorological data, and particularly relates to the technical field of thunder disaster prediction.The method comprises the steps that standardization processing of temporal-spatial resolution unification is conducted on meteorological satellite data, radar data and lightning positioning data, and standardized temporal-spatial input data is generated; then spatial-temporal features are extracted through a depth separable 3D convolution module, and a compressed spatial-temporal feature graph is generated; then, a channel-space double attention mechanism (CPCA) is applied to the compressed feature map for feature optimization; and finally, processing the optimized feature map through a coding-decoding structure, and outputting a thunder and lightning probability distribution map. According to the method, the problem of spatial-temporal resolution difference and physical feature mismatching in multi-source data fusion is innovatively solved, the calculation efficiency is remarkably improved through a lightweight network architecture, the feature expression ability is enhanced by using an attention mechanism, and high-precision prediction of sudden thunder and lightning events is realized.

The invention relates to the technical field of remote sensing data processing and water environment monitoring, and discloses a black and odorous water body intelligent identification method based on a multi-source remote sensing image, and the method comprises the steps: firstly obtaining a first high-resolution remote sensing image, and extracting a global water body mask through a TransUNet model; secondly, removing non-target plaques based on geometric features and a basic spectrum rule; then, calculating a black and odorous water body index by using the second multispectral remote sensing image, and screening suspected black and odorous water bodies by combining adaptive threshold segmentation; further, performing fine classification confirmation on the suspected target by using a third high-frequency remote sensing image and an Officient Net model; and finally performing fusion output on the identification result. Through multi-source data collaboration and a coarse screening-fine classification multi-stage strategy, the limitation of insufficient spatial-temporal resolution of a single data source is overcome, and the positioning precision and the anti-interference capability of urban black and odorous water body recognition are improved.

The invention provides a power grid equipment large-range progressive real-time flood forecasting method based on a three-water-source Xinanjiang model, which abandons a basin homogenization hypothesis of a traditional lumped model, divides a target basin into subunits with spatial uniqueness and topological connectivity through a Thiessen polygon method, and accurately matches underlying surface spatial differentiation features; according to the method, the limitation of single parameter calibration is broken through, an NSGA-I I multi-objective optimization algorithm is adopted to be combined with historical flood data, a parameter optimization system containing multiple indexes such as a flood peak flow error and a peak present time error is constructed, a Pareto optimal solution set is generated, a parameter knowledge base is constructed in a classified mode, and the problem of poor parameter adaptability is solved; a geographically weighted regression method is used for fusing satellite remote sensing, ground rainfall station and hydrometric station data, a dynamic correction mechanism is established, model input is updated every 30 minutes, and the rainfall runoff calculation temporal-spatial resolution is remarkably improved; after subunit outlet flow riverway convergence calculation is completed based on a Muskingum method, power grid equipment space distribution and vulnerability threshold values are innovatively associated.

The invention relates to a geological disaster early warning algorithm based on hyperspectral and Internet of Things data fusion analysis, and relates to the technical field of geological disaster monitoring and early warning, the geological disaster early warning algorithm comprises the following steps: S1, preprocessing hyperspectral data and Internet of Things data, and respectively extracting spectral-spatial features and dynamic topology time sequence features; s2, fusing the spectrum-space features and the time sequence features to generate cross-modal joint features; s3, performing parameter optimization on the fusion features through a quantum-classical hybrid optimization algorithm, and calculating a disaster risk probability; and S4, based on the optimization result and the risk probability, executing an edge-cloud collaborative early warning decision. According to the method, through non-negative tensor ring decomposition of the hyperspectral data and dynamic topology modeling of the Internet of Things, the limitation of a traditional single data source in temporal-spatial resolution and physical relevance is solved, multi-dimensional joint extraction of spectrum-space-mechanical characteristics can be realized, and the characterization precision of a rock-soil body deformation evolution law is remarkably enhanced.

The invention provides an airborne high-precision imaging system and method for a single-photon unmanned aerial vehicle, and relates to the field of airborne imaging systems, and the system comprises a jitter collection unit for real-time attitude sensing, a signal collection and emission unit for high-speed transceiving control, a two-dimensional scanning unit for spatial scanning, and a motion compensation unit for real-time data processing. And the main control unit is used for overall planning of global time sequence control. The signal acquisition unit adopts a transmitting-receiving integrated coaxial optical structure, and a dynamic light leakage suppression mechanism is introduced. The jitter acquisition unit is integrated with a high-frequency inertial measurement unit IMU, the sampling frequency of the jitter acquisition unit is higher than the laser pulse frequency through a compensation algorithm, and the three-axis attitude and deflection angle data of the airframe in a dynamic environment are acquired in real time with high time resolution. The motion compensation unit carries out the registration of an IMU coordinate system, a laser radar coordinate system and an earth fixed coordinate system, solves the instantaneous attitude of each laser pulse receiving and transmitting moment, carries out the calibration of the position information of a photon event, and solves the point cloud motion distortion.

The invention relates to a multi-source meteorological data fusion technology, and discloses an air temperature reconstruction method fusing data of a micro-meteorological device, which improves the temporal-spatial resolution and precision of ground temperature under a complex terrain. The method comprises the following steps: densely deploying micrometeorological devices in a complex terrain area to obtain high-frequency observation data, carrying out quality control, and carrying out hierarchical processing in two dimensions of space and time by taking pattern forecast grid point data as an initial background field: in the spatial dimension, dynamically updating a fusion weight for grid points with observation stations by using geographical weighted regression, and carrying out data fusion; a residual machine learning model is combined with multi-topographic feature correction for grid points without observation stations, and a high-precision space fusion background field is generated; in the time dimension, errors after space fusion are decoupled into a trend term and a periodic term, an autoregressive integral moving average model is used for predicting a trend, a Fourier algorithm is used for correcting a periodic phase, and then time dimension machine learning correction is carried out on a grid point of an observation-free station. And finally, complete-process automatic, high-temporal-spatial-resolution and low-error complex terrain area air temperature reconstruction is realized.

The invention discloses an underwater target detection method and system based on multiband sonar data generation, and the method comprises the steps: generating synthetic sonar data through real sonar data, and carrying out the expansion training of an underwater target detection model through a reasonable real sonar data and synthetic sonar data mixing strategy. The generative adversarial network for generating the synthetic sonar data comprises a generator and a discriminator. And the generator is used for receiving the Mel spectrogram corresponding to the real sonar data, realizing multi-scale feature capture of the sonar waveform based on the multi-band processing module and the multi-receptive field residual block design, and outputting the synthesized sonar data consistent with the real sonar data in time resolution. The discriminator comprises two substructures, namely a multi-period discriminator and a multi-scale discriminator, which are respectively used for capturing the periodicity and detail consistency of the sonar signal in different time periods and time scales, and enhancing the multi-level discrimination capability of the authenticity of the generated data.

A method for estimating typhoon structural parameters by fusing spaceborne GNSS reflectometer data and radiometer data, which relates to the technical fields of data fusion and typhoon monitoring. The method comprises: acquiring GNSS-R reflectometer data and radiometer data; filtering typhoon data from the GNSS-R reflectometer data and the radiometer data to obtain filtered GNSS-R reflectometer data and radiometer data; performing data spatio-temporal matching on the filtered GNSS-R reflectometer data and radiometer data to obtain a spatio-temporally matched region; performing data fusion processing on the spatio-temporally matched region to obtain fused data; and performing typhoon structural parameter estimation on the obtained fused data to obtain structural parameters of a typhoon at each development stage. Fused data of spaceborne GNSS-R reflectometer data and radiometer data is used for typhoon structural parameter estimation, such that the temporal resolution and accuracy of parameter estimation can be improved, and the algorithm complexity is low.

A method for non-contact modal analysis uses an optical sensing device such as a video camera. Unlike traditional modal analysis, requiring accelerometers or force sensors to measure the modal characteristics of a structure and animate the motion of a wireframe model of the test structure, the inventive system mathematically modifies the original video recordings by filtering, amplifying, and modifying the playback rate or applying modal shape mask or vectors to produce modified video to show motion at each modal frequency. This provides animated mode shapes with higher spatial and temporal resolution that possible with the traditional approach of using wireframe model animations.

The invention relates to the technical field of meteorological observation, in particular to a solar radiation prediction method and device based on multi-source satellite data fusion, an electronic device and a storage medium. And an end-to-end deep learning prediction model is constructed, so that a dark start prediction blind area caused by visible light deficiency before and after sunrise is effectively overcome, continuous prediction in all days, especially in a dawn period, is realized, and the prediction coverage capability is expanded. And secondly, regional adaptability parameter calibration is carried out on the physical inversion model, so that the localization precision of a historical reference radiation field is improved, and a more reliable training basis is provided for the prediction model. Finally, the output solar radiation prediction product with high temporal-spatial resolution and physical consistency can directly support key businesses such as photovoltaic power station output prediction and power grid climbing management, and the practicability and reliability of the prediction result are enhanced.

This application relates to the field of medical image processing technology, and provides a method, apparatus, device, and storage medium for reconstructing ECT images. This allows for more thorough capture of subtle changes in the concentration distribution of radioactive tracers at high temporal resolution, helping to reduce image noise levels and improve image quality. This application obtains a first ECT image sequence; the first ECT image sequence is obtained by scanning with an ECT scanning device; the first ECT image sequence is input into a pre-constructed intermediate frame prediction network to obtain an estimated second ECT image sequence; using the estimated second ECT image sequence as a priori image, a target second ECT image sequence is reconstructed; the estimated second ECT image sequence and the target second ECT image sequence belong to the second ECT image sequence; the temporal resolution of the second ECT image sequence is higher than that of the first ECT image sequence.

The invention relates to a high-precision land carbon flux reconstruction method based on four-dimensional space-time deep learning. The method comprises the steps of obtaining a multi-source heterogeneous data set and performing preprocessing; constructing a four-dimensional space-time deep learning model architecture which is sequentially connected with a multi-scale space-time feature extraction module, a space-time feature fusion module, a prediction layer and an uncertainty quantization layer from input to output, and taking the preprocessed multi-source heterogeneous data set as input and a carbon flux reconstruction result as output; constructing a loss function, adopting a hierarchical learning rate strategy and introducing a cosine annealing scheduler, and training a four-dimensional space-time deep learning model architecture based on the preprocessed multi-source heterogeneous data set to obtain a four-dimensional space-time deep learning model; and obtaining a carbon flux data reconstruction set, and inputting the four-dimensional space-time deep learning model to generate a carbon flux reconstruction result. By adopting the method, multi-source heterogeneous data can be effectively integrated, the complex spatial-temporal dynamic characteristics of the carbon flux are captured, and accurate reconstruction of the land carbon flux with high spatial-temporal resolution is realized.

The invention relates to a method for demarcating an underground water reserve area. The method comprises the following steps: acquiring and tagging remote sensing, geological survey, monitoring well and Internet of Things data; the heterogeneous data is subjected to normalization preprocessing, and space-time and physical quantity unification is achieved; semantic annotation, feature completion and causal relationship modeling are performed based on a knowledge graph, and data integrity and internal relation are improved; the reliability of multi-source data is improved by adopting contradiction detection and confidence evaluation; self-adaptive weighted multi-source data fusion is realized through a dynamic weight mechanism; and constructing an adaptive graph neural network model to carry out dynamic time sequence prediction and spatial partition analysis of groundwater reserves. According to the method, the precision and temporal-spatial resolution of groundwater reserve estimation can be remarkably improved, the robustness to abnormity and environmental fluctuation is improved, and scientific decision and intelligent management can be realized.

The invention relates to the technical field of biomedical imaging, and discloses a photoacoustic-ultrasonic volume imaging method and system based on an annular ultrasonic array, and the method comprises the steps: reconstructing a two-dimensional photoacoustic image and a two-dimensional ultrasonic image; after photoacoustic imaging and ultrasonic synthetic aperture imaging of one imaging plane are completed, the annular ultrasonic array is moved in the direction perpendicular to the imaging plane, photoacoustic images and ultrasonic images of all the imaging planes are repeatedly executed on the next imaging plane, rebuilt and stacked, and a three-dimensional photoacoustic volume image and a three-dimensional ultrasonic volume image are formed; performing spatial pulse response deconvolution processing on the three-dimensional photoacoustic volume image; and fusing the processed three-dimensional photoacoustic volume image and the three-dimensional ultrasonic volume image to generate a three-dimensional bimodal volume image. According to the invention, high-time-resolution opto-acoustic-ultrasonic bimodal three-dimensional imaging is realized by using an annular ultrasonic array and motion scanning, and the high spatial resolution of the image is further ensured through a series of technologies.

The invention discloses a regional ionosphere temporal-spatial resolution refinement method, which comprises the following steps: acquiring real-time GIM data, a solar activity index and a geomagnetic activity index, inputting the data into a trained forecasting model, and outputting a VTEC mean value of a grid center point; calculating an STEC value based on the output VTEC mean value; the training of the forecasting model comprises the following steps: acquiring original GIM data and CORS observation value data, and respectively preprocessing the original GIM data and the CORS observation value data to obtain GIM-VTEC calculated based on the GIM data and puncture point VTEC calculated based on the CORS observation value data; the GIM-VTEC obtained through preprocessing and the puncture point VTEC are matched according to the time and the grid range; acquiring a solar activity index and a geomagnetic activity index, matching the solar activity index and the geomagnetic activity index with the matched VTEC data according to time, and constructing a training sample set; constructing a BP neural network, taking time, longitude, latitude, GIM-VTEC, a solar activity index and a geomagnetic activity index as input, and taking a puncture point VTEC obtained by calculating CORS observation value data as output; and training is carried out on the constructed training sample set, and a trained forecasting model is output.

The present application relates to photostabilized or “self-healing” dyes that are constructed by attaching an azoaryl unit to a parent dye such that its optical properties are improved, particularly its optical properties that are most relevant in highly-demanding imaging, including instant brightness, signal stability, photon budget, and rate of detecting localisations. Therefore the compounds of the invention can be useful for high-performance imaging, e.g. delivering higher spatial and temporal resolution, within a shorter experimental acquisition time, and with more confidence, whether in oxygen-free conditions or in aerated conditions.

The invention relates to the technical field of water ecological environment remote sensing monitoring, in particular to a river total nitrogen concentration remote sensing estimation method based on multi-source data fusion, and the method comprises the following steps: S1, obtaining and processing total nitrogen measured data, and unifying time and a coordinate reference system; s2, processing the Landsat 8 / 9 image, and extracting water body reflectivity and remote sensing indexes; s3, ERA5-Land meteorological data are acquired, and derivation indexes are calculated; s4, DEM elevation data are extracted; s5, fusing the multi-source data to generate a table type data set; s6, screening sensitive indexes based on SHAP and correlation; s7, constructing and evaluating an inversion model; s8, extracting an MNDWI water body mask; s9, generating a feature stack and inverting and outputting a total nitrogen concentration diagram; according to the method, through fusion of multi-source data, construction of a high-precision inversion model and a cloud platform automatic processing flow, high-temporal-spatial-resolution, stable and reproducible remote sensing estimation of the total nitrogen concentration of the river is realized, and the monitoring efficiency and the application value are effectively improved.

The invention discloses a method for inverting a cloud condensation nucleus number concentration profile based on a laser radar and a neural network. The method comprises the following steps: collecting multi-wavelength laser radar data including a backscattering coefficient vertical profile, an extinction coefficient vertical profile, a laser radar ratio and a depolarization ratio; the method comprises the following steps: acquiring an atmospheric temperature profile and a water vapor mixing ratio profile which are in time-space synchronization with multi-wavelength laser radar data, performing grid alignment on a vertical height, and constructing a multi-channel input feature set for each preset target supersaturation ratio; and constructing a convolutional neural network profile inversion model, taking the multi-channel input feature set as input and the cloud condensation nucleus number concentration profile data as output, training the model, and obtaining the trained convolutional neural network profile inversion model. According to the method, the limitation of continuous, high-precision and high-temporal-spatial-resolution detection of CCN number concentration vertical distribution is overcome, and key data support is provided for the fields of weather forecast, climate models, artificial influence weather and the like.

The invention discloses a space-time fusion method for lake chlorophyll a concentration remote sensing inversion, and relates to the technical field of environment monitoring. Wherein a plurality of chlorophyll a concentration inversion graphs are generated through multi-source satellite data, space, time and attribute three-dimensional features are extracted based on the plurality of chlorophyll a concentration inversion graphs, and finally collaborative fusion of multi-dimensional features is realized through a tensor fusion mechanism. Thus, through integration of multi-source remote sensing images, high temporal-spatial resolution extraction of the lake surface chlorophyll a is realized, cooperative utilization of multi-dimensional features is completed in a decision-making layer, fundamental bottlenecks of a traditional fusion method in the aspects of physical significance transparency and data universality are overcome, the temporal-spatial change trend of lake water quality parameters can be further mastered, and the method is suitable for being applied to lake water quality monitoring. And the development of lake water environment research is further promoted.

The invention relates to a two-dimensional staggered array MIMO (Multiple Input Multiple Output) radar system for monitoring dynamic deformation of a bridge, which realizes decoupling of spatial resolution and time resolution by adopting a two-dimensional staggered array MIMO radar hardware architecture and replacing traditional mobile synthetic aperture with static virtual aperture synthesis through integrated design. According to the system, a continuous virtual area array is synthesized through transmitting and receiving arrays which are in non-uniform sparse arrangement, and high-resolution three-dimensional imaging of a bridge monitoring area is realized in combination with an FMCW signal processing and near-field three-dimensional imaging algorithm; and carrying out pixel-level processing on the serialized three-dimensional complex image by using a rapid time sequence interference and deformation extraction module to obtain a high-precision deformation sequence. The method does not need a mechanical scanning part, has the advantages of high environmental robustness, low hardware cost, flexible deployment and the like, and can provide panoramic and high-precision four-dimensional dynamic deformation field data for bridge structure state evaluation.

The invention discloses a near-infrared two-region dual-channel fluorescent nanoprobe as well as a preparation method and application thereof, and relates to the technical field of biomedical imaging. A nano probe A and a nano probe B included in the near-infrared two-region dual-channel fluorescent nano probe are both of a core-shell structure, two NIR-IIb fluorescent nano probes adaptive to different excitation wavelengths (808 nm and 980 nm) are constructed by precisely regulating and controlling the types and proportions of lanthanide elements, dual-channel imaging is achieved, limitation of a single excitation wavelength is broken through, spectral crosstalk is eliminated, and the near-infrared two-region dual-channel fluorescent nano probe has the advantages of high sensitivity, high sensitivity, high sensitivity and the like. The method has the characteristics of material uniformity and biological safety. The near-infrared IIb region dual-channel imaging system has the characteristics of high temporal-spatial resolution and signal separation, and has significant application value in the field of living body multi-target synchronous observation. Compared with a traditional two-photon microscope technology, the imaging method has a wider observation view field, a local craniotomy operation does not need to be carried out on an experimental mouse, and physiological trauma is remarkably reduced.

This invention belongs to the field of remote sensing technology and relates to a method for predicting canopy combustible moisture content (CFMC) by combining remote sensing CFMC products and meteorological data. Specifically, through global two-stage sensitivity analysis, key input parameters for different tree species in the MEDFATE model are identified. Using these parameters, a cost function is constructed to measure the error between the CFMC simulated by the MEDFATE ecophysical process model and the CFMC measured in the field, achieving species-based localized correction of MEDFATE. Then, through four-dimensional variational data assimilation technology, the remote sensing CFMC product is combined with the localized MEDFATE. This achieves enhanced CFMC simulation, improving the accuracy of MEDFATE CFMC simulation while also increasing the temporal resolution of remote sensing data and the spatial resolution of the MEDFATE model. With accurate meteorological forecast data, effective daily CFMC prediction of vegetation can be achieved.

This invention discloses a device and method for detecting boundary changes in a video wall splicing mirror, relating to the field of optical inspection technology. The detection device includes a contact sensing structure, a non-contact optical structure, and a processor arranged relative to the video wall splicing mirror body. The detection of boundary changes in the video wall splicing mirror is achieved based on the contact sensing structure and the non-contact optical structure. Furthermore, when using the contact sensing structure, the edge sensor readings are corrected by introducing a mounting arm length parameter, eliminating Abbe errors caused by the misalignment of the mounting reference plane and the optical neutral plane, thus improving the accuracy and reliability of the contact detection. An event sensor is introduced into the non-contact optical structure; this event sensor can typically capture transient events of edge changes with microsecond-level time resolution, making it suitable for real-time detection in dynamic environments. In addition, the contact sensing structure and the non-contact optical structure can serve as backups for each other, improving the reliability of the detection device.

The invention discloses a multi-scale heterogenous remote sensing data collaborative water quality inversion method, computer equipment and a medium, and belongs to the technical field of water quality remote sensing monitoring. S3, an inversion model is constructed, and the step S3 comprises the steps of S31, wave band combination optimization and correlation analysis; s32, constructing a multi-scale heterogeneous remote sensing data collaborative fusion inversion model; and S33, multi-source data collaborative wave band selection and model determination. According to the method, high-frequency and high-spatial-resolution water quality inversion is realized, the spatial-temporal resolution and precision are improved, a more comprehensive and accurate water quality inversion model is constructed, the robustness of the model in a turbid water body and an eutrophicated water body is remarkably improved, the adaptability to a complex water body is enhanced, and the method is suitable for large-scale popularization and application. An efficient and economical technical means is provided for water quality inversion in a complex water body environment, and the method has remarkable low cost and universality.

The present technology relates to a light detection device and a ranging system that enable ranging accuracy to be improved. This light detection device is provided with: a readout circuit that outputs detection signals indicating the timing at which a light-receiving element detected reflected light resulting from the reflection of emitted light by an object; a time to digital converter (TDC) that counts time on the basis of the detection signals output from the readout circuit; a histogram generation unit that generates a histogram on the basis of the output of the TDC based on the detection signals; a first multiplexer that inputs, into a signal path between the readout circuit and the TDC, measurement signals for measuring propagation delay of signals in at least a portion of the signal path in time units smaller than the temporal resolution of the TDC; a propagation delay measurement unit that measures propagation delay on the basis of the output of the TDC based on the measurement signals in time units smaller than the temporal resolution of the TDC; and a correction unit that, on the basis of measurement results from the propagation delay measurement unit, corrects the output of the TDC based on the detection signals or the output of the histogram generation unit. The present technology can be applied, for instance, to a direct ToF type ranging device.

This invention discloses a method for refining the spatiotemporal resolution of the regional ionosphere, comprising: acquiring real-time GIM data, solar activity index, and geomagnetic activity index and inputting them into a trained forecast model, outputting the mean VTEC value of the grid center point; calculating the STEC value based on the output mean VTEC value; training the forecast model includes: acquiring raw GIM data and CORS observation data and preprocessing them respectively to obtain GIM-VTEC calculated based on GIM data and puncture point VTEC calculated based on CORS observation data; matching the preprocessed GIM-VTEC and puncture point VTEC according to time and grid range; acquiring solar activity index and geomagnetic activity index and matching them with the matched VTEC data according to time to construct a training sample set; constructing a BP neural network with time, longitude, latitude, GIM-VTEC, solar activity index, and geomagnetic activity index as inputs, and puncture point VTEC calculated from CORS observation data as output; training on the constructed training sample set and outputting the trained forecast model.

A process for charge detection mass spectrometry includes: acquiring a time-varying signal representative of a current induced on a detector by oscillatory motion of ions within a trapping region; processing the time-varying signal to derive a frequency of the oscillating motion; generating resonant ion selective time overview (STORI) data representing a relationship of STORIreal value to time and a relationship of STORIimag value to time based on the amplitude of the time-varying signal and the derived frequency of the oscillatory motion; regenerating STORI data based on a change in the frequency of the oscillatory motion over time; and determining a state of charge of the ion based on the regenerated STORI data.

1. The name of the design product: Raman and Mie scattering temperature and humidity aerosol lidar. 2. The use of the design product: for high spatial and temporal resolution vertical distribution measurement of atmospheric temperature, humidity and aerosol. 3. The design points of the design product: in shape. 4. The picture or photo that best shows the design points: perspective view.

The invention provides an urban wind speed monitoring and assimilation method and system based on tree swing features. The system comprises an image acquisition module, an image processing and feature extraction module, a model training and storage module, a wind speed inversion module, a data assimilation module and a data storage and visualization module. Comprising the following steps: deploying a camera in a target area; collecting a tree image sequence by using a camera; extracting swing characteristic parameters of different tree species based on the tree image sequence; constructing swing-wind speed mapping models of different tree species based on the swing characteristic parameters of different tree species and tree attributes; inverting urban wind speed distribution based on the swing-wind speed mapping model; and assimilating the wind speed distribution into an urban wind field mode. The method has the advantages that urban-scale refined wind speed monitoring is achieved through existing camera resources, the spatial-temporal resolution of wind speed data is improved, and powerful support is provided for urban meteorological service, disaster prevention and reduction and the like.