18 results about "Earth observation" patented technology

This invention proposes a satellite-ground collaborative mission management method for Earth observation space cloud services, belonging to the field of satellite application and management technology. This method first identifies three main roles in satellite-ground collaborative mission management; secondly, it selects a management mode based on the urgency and complexity of the needs; then, it generates mission plans and instructions for the remote sensing satellite constellation and telemetry and control station network, and executes the missions; finally, after mission execution, data is received through the space edge cloud service center and the ground station network, thereby achieving management under a cloud architecture. This method overcomes the shortcomings of existing methods, such as difficulty in coordinating satellite-ground missions, difficulty in coordinating multiple types of users, and slow data transmission speeds. It improves the collaborative management performance of remote sensing satellite missions under a satellite-ground integrated system and can meet the application requirements of rapid, accurate, and comprehensive remote sensing satellite mission planning and management.

Synthetic aperture radar (SAR) is a type of imaging technology that can be used for a wide range of applications, including Earth observation, mapping, object tracking, change detection (e.g., Arctic ice), natural disaster monitoring, and many other uses. A high-altitude unmanned aerial vehicle for performing synthetic aperture radar (SAR) imaging comprises a fuselage, wings attached to the fuselage to provide lift to the aircraft, one or more electric propellers to provide thrust to the aircraft, a SAR payload for SAR imaging the Earth's surface as the aircraft flies, solar cells to generate power to drive one or more electric propellers and operate the SAR payload, and one or more batteries to store the electrical energy generated by the solar cells.

This invention discloses a method and system for identifying planted and natural forests based on multi-source remote sensing and spatiotemporal joint optimization, belonging to the fields of remote sensing image processing, earth observation, and dynamic monitoring of forest ecology. Addressing the problems of high label noise and disordered temporal logic in existing technologies, this invention obtains high-purity training samples through multi-stage iterative purification by fusing CCDC mutation history and deep semantic features; obtains pixel-level confidence through independent initial classification by geographic partitioning; constructs an HMM model integrating ecological prior constraints and dynamic adaptive emission probabilities for Viterbi decoding; and performs constrained spatial restoration with cross-dimensional temporal security checks. This invention effectively suppresses temporal pseudo-variables and salt-and-pepper noise, achieving high-resolution thematic mapping year by year with no temporal logical contradictions and regular spatial patches, suitable for fine-grained forest classification and compliance monitoring of zero-deforestation laws in tropical and subtropical regions.

This invention discloses a space-ground coordinated radiometric characteristic calibration method for spaceborne active microwave sensors in the field of radar Earth observation technology. It constructs a space-ground coordinated calibration system consisting of a radiation reference source satellite and a ground calibration processing station. The method includes: determining the orbital parameters of the radiation reference source satellite; the satellite transmitting signals to the ground station in Earth observation mode, using a known RCS target on the ground to calibrate its own antenna gain and link gain; receiving signals from the satellite to be calibrated in Earth observation mode, accurately calculating and transmitting echo signals based on the calibrated parameters; and the satellite to be calibrated calibrating its own transmit / receive link gain based on the received echo signals. This invention can be widely applied to the on-orbit radiometric calibration of active microwave sensors such as synthetic aperture radar, altimeters, and microwave scatterometers, significantly improving calibration frequency and accuracy, supporting multi-band, high-stability quantitative remote sensing tasks, and providing reliable technical support for precise observation in fields such as ocean monitoring, weather forecasting, and topographic mapping.

This invention relates to the field of aerospace Earth observation and remote sensing imaging technology, and discloses a target-driven dual-camera heterogeneous payload dynamic cooperative aiming method and device. The device includes a base, a wide-area search unit, a high-precision staring unit, a field-of-view deflector, and a cooperative controller. The wide-area search unit and the high-precision staring unit are distributed forward and backward along the flight direction. The cooperative controller identifies potential targets and calculates their geographical locations. It calculates the delay time based on the physical distance and real-time velocity. The cooperative controller calculates the track-crossing swing angle based on the target's position and attitude and sends commands. The field-of-view deflector drives the high-precision staring unit to deflect to the track-crossing swing angle within the delay time. The cooperative controller triggers imaging at the end of the delay time. This invention achieves pointing adjustment and exposure synchronization through heterogeneous payload spatiotemporal coordination and a delay time window, realizing wide-area detection and high-resolution fine imaging of potential targets during a single flight.

There is provided a sinkage prediction device including: a variation data acquisition unit 10 analyzing time-series observation data measured by using an earth observation technology and acquiring horizontal direction variation data which is data indicating a horizontal direction variation on a ground surface; and a sinkage prediction unit 20 determining, based on the acquired horizontal direction variation data, whether at least one of the variation in the time axis and the variation in the space axis on the ground surface is in a predetermined state and predicting a location on the ground surface indicating the variation determined to be in the predetermined state as a potential sinkage location where there is a possibility of occurrence of sinkage, wherein it is possible to predict the location where the sinkage may be likely to occur by determining, based on the horizontal direction variation data obtained by analyzing the observation data measured by using the earth observation technology, whether the variation in the time axis or the variation in the space axis on the ground surface is in the predetermined state, by using the predetermined state related to the variation in the horizontal direction viewed on the ground surface where there is a sign that the sinkage is likely to occur as a determination criterion.

A hyperspectral soil nutrient inversion method based on WBL-ResNet, belonging to the field of intelligent interpretation of remote sensing images, consists of an MSFE module and a WBL-ResNet model. The MSFE module effectively captures different levels and details in hyperspectral images, enhancing the model's ability to express hyperspectral data and improving the efficiency of training and the accuracy of inversion. The design of WBL-ResNet residual connections reduces the gradient vanishing problem in deep network training, helping to maintain the learning stability of the network as its depth increases. A weighted balanced loss function is adopted, and through the design of Gaussian kernel function and variance weighting, higher weights are assigned to sparsely labeled samples, improving the inversion ability for sparse labels. This invention can accurately, quickly, and stably complete soil nutrient inversion in hyperspectral Earth observation scenarios, realizing contactless monitoring of farmland soil nutrient status using remote sensing methods.

Systems, methods, and computer-readable media for vessel identification are provided. The system includes a data storage device storing: a database of optical oblique images each containing a known candidate vessel having a known unique vessel identifier; and an optical nadir satellite image containing an unknown vessel. The system further includes a processor configured to execute a nadir-oblique image matcher configured to: compare, via a neural network, the nadir image to oblique images in the database including determining a similarity score between the nadir image and a respective oblique image; output, via the neural network, a ranked list of the oblique images based on the determined similarity scores; and assign a known unique vessel identifier to the nadir image based on the ranked list.

This invention belongs to the field of Earth observation and data processing technology, and relates to a method for estimating the magnitude of strong earthquakes based on unsupervised learning clustering weighting, addressing the problem of insufficient accuracy in magnitude estimation in existing technologies. The method first collects peak surface deformation (PGD) and peak surface deformation (PGV) data and epicentral distance from seismic monitoring stations; constructs a magnitude regression equation, and performs cluster analysis on the observed features using the FCM unsupervised learning clustering algorithm, adaptively determining the observation weight factors based on the degree of difference between the cluster centers and the benchmark cluster centers; then, the cluster weights are introduced into a robust estimation model, and sequential weighted least squares calculation is performed using the IGG3 equivalent weight function to obtain the fused magnitude. This invention combines unsupervised clustering adaptive weighting with robust estimation to rapidly estimate the magnitude of strong earthquakes with complex fault structures, significantly improving the accuracy, stability, and reliability of strong earthquake magnitude estimation.

This application belongs to the field of remote sensing Earth observation technology, specifically involving a method and system for multi-target extraction from large-format remote sensing images. The method includes: S1 large-format overlapping sliding window segmentation; S2 cross-modal spatial mapping and geometric prior cue generation; S3 adaptive segmentation objective function based on spatial prior constraints; S4 affine reconstruction from local pixel coordinates to global coordinates; and S5 weighted fusion of overlapping region mask confidence and final result generation. A large-scale visual language multimodal model serves as the semantic parsing front end, while a large-scale segmentation model serves as the pixel-level decoding back end. The two are connected through spatial prior cueing, and the entire process is driven by multi-turn dialogue using natural language, achieving end-to-end high-precision automatic extraction of ground features.

The application discloses a kind of remote sensing satellite sun orientation planning method and device, the method includes: S1, obtaining the information set of earth observation task;S2, the information set of earth observation task is handled, and satellite can obtain the information set of earth observation task;S3, the earth observation action sequence in the satellite can obtain the information set of earth observation task is spliced, and satellite observation action sequence is obtained;S4, action insertion processing is carried out to the satellite observation action sequence, and satellite execution action sequence is obtained.The application realizes dynamic development sun orientation while carrying out the task such as earth observation, reaches the requirement of energy balance.

This disclosure provides a method, apparatus, and storage medium for multi-parameter, multi-band joint remote sensing inversion of aerosol optical properties, relating to the fields of Earth observation and remote sensing technology. The method includes acquiring observational data of multi-band atmospheric top-layer reflectivity from satellites and ground-based observation station aerosol parameter ground truth data; constructing dynamic observation features and static background features based on the observational data and multi-source auxiliary data, respectively; using the aerosol parameter ground truth data as training labels, inputting the dynamic observation features into a first-stage learning inversion model for multi-task joint inversion, outputting initial prediction results for aerosol multi-parameters, and generating predictive statistical features; fusing the static background features and predictive statistical features into a second-stage learning inversion model for correction, outputting the inversion results for aerosol multi-parameters. This addresses the shortcomings of existing technologies, such as single inversion parameters, susceptibility to missing measurements and spatial fragmentation under bright or complex surfaces, and insufficient generalization ability of single-data-driven models.

This application relates to a distributed storage method for large-scale GRIB grid data. The method includes: a GRIB objectification technique based on encoding features, which treats the entire GRIB message as an object data body and self-describing information as metadata, achieving native support for grid fields of arbitrary sizes; a core metadata dataset definition technique based on virtual keys, which maps each GRIB message in the GRIB file to a single storage object and maps the self-describing information in the GRIB message to the metadata of the object storage; and fully utilizing the independent and distributed storage characteristics of GRIB objects, employing distributed parallel pipeline processing to leverage the advantages of distributed computing, thereby significantly improving the distributed parallel processing efficiency of large-scale grid data. This application solves the problems of coarse granularity, poor consistency, and low access efficiency in traditional retrieval methods, and can be widely applied to Earth observation, numerical weather prediction, and big data analysis scenarios.

This invention belongs to the interdisciplinary field of smart agriculture and Earth observation information technology, and discloses a method and system for assessing the climate resilience of high-standard farmland based on multi-source remote sensing data. The method acquires long-term multi-source data of the target high-standard farmland area and a control area, and performs standardized preprocessing; based on multi-source remote sensing and auxiliary data, it calculates resistance index, resilience index, and stability index for identified climate events; it integrates the three indices to construct a comprehensive climate resilience index, and performs a significant difference test based on the control area to verify the construction effectiveness; it extracts engineering characteristic factors of the target area, establishes a nonlinear attribution model between these factors and the resistance and resilience indices, and quantifies the contribution of each engineering characteristic factor to climate resilience. This invention deeply integrates multi-source remote sensing technology, time series analysis, spatial statistics, and machine learning algorithms, realizing a closed loop from monitoring to diagnosis.

Computer systems and methods for maritime surveillance and identification of unknown vessels are provided. The system includes at least one data storage device storing: a database of known optical nadir satellite images each containing a known candidate vessel having a known unique vessel identifier; and an unknown optical nadir satellite image containing an unknown vessel. The system also includes at least one processor configured to execute a nadir-nadir image matcher configured to: compare, via a neural network, the unknown nadir image to a plurality of known nadir images in the database, the comparing including determining a similarity score indicating a similarity level between the unknown nadir image and a respective known nadir image; output, via the neural network, a ranked list of the known nadir images based on the determined similarity scores; and assign a known unique vessel identifier to the unknown nadir image based on the ranked list.

This invention discloses a near-real-time monitoring method for mid-season crop phenology and types based on dense temporal series data, belonging to the interdisciplinary field of satellite remote sensing Earth observation and agricultural information technology. The method includes: acquiring HLS imagery to construct a dense temporal series dataset; recursively updating the dataset using the Stochastic Continuous Change Detection (S-CCD) algorithm; fitting the vegetation index temporal characteristic curve for each pixel based on the S-CCD results to predict the phenological stage of the current year; classifying pixels into stable, uncertain, and variable classes, with the stable and uncertain classes inheriting historical planting types; training a random forest model using automatically selected stable class samples to classify the variable classes, and performing Bayesian temporal fusion with previous probability maps to determine the final crop type; fusing the results with vector plots and automatically publishing them through a network service. This invention achieves high-precision and high-efficiency dynamic monitoring of phenology and types within the crop growth cycle, supporting near-real-time weekly updates.

The application discloses a light and small super-high resolution wide-width spaceborne SAR system, which comprises a signal processor, a frequency synthesizer, a transmitting channel, a multi-channel receiving channel, a multi-channel internal scaler, a power supply and distribution unit, a beam forming network, a phased array feed and a parasol reflector; the light and small parasol reflector antenna combined with the phased array feed is used in a multi-channel multi-beam receiving mode to realize beam scanning receiving in the distance direction; and the whole surveying and mapping band is covered by switching different channels to receive. The system has the advantages of light weight, small size, low power consumption and low heat consumption, the imaging resolution can reach the centimeter level, the action distance is in the kilometer level, and the system has great significance for high-resolution earth observation.

A system and method for satellite imaging are provided. The system includes a first satellite, a trailing satellite, and a ground terminal. The first satellite acquires synthetic aperture radar (SAR) image data in a first predetermined signal frequency band at a first imaging location and transmits the SAR image data to a ground terminal. The ground terminal determines a second imaging location from the SAR image data and transmits the second imaging location to the trailing satellite. The trailing satellite acquires higher resolution image data in a second predetermined signal frequency band at the second imaging location and transmits the image data to the ground terminal. Systems and methods for satellite imaging are also provided in which a first satellite captures image data and processes the image data onboard to generate a processed product which is transmitted to a receiving terminal at a ground terminal or on a second satellite.