12 results about "Thermal infrared remote sensing" patented technology

The application relates to the technical field of image segmentation, in particular to a coal mine area ground fissure identification method and device.The method comprises the following steps: acquiring a visible light remote sensing image and a thermal infrared remote sensing image of a target coal mine area; constructing a ground fissure data set based on the visible light remote sensing image and the thermal infrared remote sensing image; constructing a ground fissure identification model based on a neural network, wherein the ground fissure identification model comprises a double-branch encoder, a feature extraction module and a decoder, and the double-branch encoder comprises a feature fusion module; iteratively training the ground fissure identification model according to the ground fissure data set; and identifying ground fissures in the to-be-detected visible light remote sensing image and the to-be-detected thermal infrared remote sensing image of the target coal mine area by using the trained ground fissure identification model to obtain a ground fissure identification result map.The application realizes accurate identification of ground fissures in a complex scene of a coal mine area by fusing visible light and thermal infrared dual-mode data.

The application discloses a kind of dam leakage passage digital twin systems and diagnostic methods based on flow-heat coupling inversion reconstruction, the diagnostic method includes: obtaining the time series thermal infrared remote sensing observation data of dam to be measured, environmental driving data and digital twin dam model;Under the assumption of no leakage, seepage-heat coupling simulation is carried out, and the benchmark temperature field that is continuous in space-time is generated;Based on the difference between time series thermal infrared remote sensing observation data and benchmark temperature field, extract thermal infrared anomaly index;Seepage-heat coupling inversion model containing physical constraint and structured constraint is constructed, and three-dimensional leakage parameter field inside dam is obtained by minimizing the difference between observation and simulation inversion;It is written back to digital twin dam model to carry out seepage stability calculation, and the leakage risk classification early warning result of dam is obtained.The application effectively solves the problem of ill-conditioned and environmental interference of thermal infrared inversion, realizes the structured reconstruction and risk quantitative evaluation of dam leakage passage.

This invention discloses an end-to-end land surface temperature retrieval method based on a multi-source heterogeneous data fusion network, comprising: acquiring visible light, near-infrared, and thermal infrared remote sensing images and land surface temperature label data; constructing a dataset by combining NCEP water vapor data with spatiotemporal interpolation resolution matching; building a cross-modal retrieval model that integrates normalization processing, differential feature extraction, a dual-stream encoder, and a U-Net decoder; completing model training and testing, verifying spatial generalization ability using non-overlapping independent region data, and retraining with parameter adjustments and sample additions if the standard is not met; introducing field-observed temperature as a physical constraint to calculate residuals, freezing the main network parameters, and fine-tuning only the linear layer at the end of the decoder to optimize the model; inputting multi-source data of the area to be inverted into the fine-tuned model to achieve high-resolution and high-precision land surface temperature retrieval. This invention achieves automated retrieval without atmospheric parameters, significantly improving the absolute accuracy and spatial detail of the retrieval results, and is suitable for large-scale monitoring of complex surfaces.

The application discloses a method for estimating power generation of a nuclear power plant by using a space-based thermal infrared remote sensing warm water discharge area map, and comprises the following steps: obtaining a thermal infrared image of a thermal imager of a target power plant adjacent water area, performing radiation calibration, calculating the brightness temperature of each wave band, and inversely calculating the water surface temperature field by using a split window algorithm; constructing a water body background temperature field and calculating a temperature rise field; performing threshold segmentation according to the temperature rise field, introducing multi-wave band consistency constraints and connected form prior constraints, generating a warm water discharge area map, and extracting a characteristic parameter set of the warm water discharge; combining flow field information and a water body heat exchange model, calculating the theoretical heat discharge power of the warm water discharge according to the characteristic parameter set, further inversely calculating the actual heat discharge power; establishing a mapping relationship between the actual heat discharge power and the unit electric power, inversely calculating the unit electric power, and performing time integration on the obtained unit electric power in a given time interval to obtain the power generation. The application can realize continuous, wide-area and traceable power generation estimation by using a space-based thermal imager.

The application discloses a kind of wheat scab monitoring methods based on satellite remote sensing, belong to remote sensing monitoring technical field, first obtain the remote sensing data and meteorological precipitation data of wheat planting area in predicted year and N years before predicted year, the remote sensing data include multispectral data and thermal infrared remote sensing data;Then the relative vigor index is calculated using the multispectral data;Using the multispectral data and thermal infrared remote sensing data obtains normalized surface temperature index;Using the meteorological precipitation data obtains normalized precipitation index;Finally, the relative vigor index, normalized surface temperature index and normalized precipitation index are used to calculate the wheat scab incidence index of predicted year;The application can better reduce the interference caused by the difference of wheat vigor in different regions in large-scale monitoring on scab monitoring model, improve the objectivity and practicability of scab remote sensing monitoring.

This invention discloses a method and device for geological disaster prevention and control of power transmission and transformation tower foundations, belonging to the field of landslide detection technology. The method involves: real-time acquisition of optical remote sensing images, radar remote sensing images, microwave remote sensing images, and thermal infrared remote sensing images; overlaying optical and radar remote sensing images to generate slope topographic spatial distribution data; analyzing vegetation growth status in the optical remote sensing images to obtain vegetation spatial distribution data; overlaying the slope topographic spatial distribution data and vegetation spatial distribution data to obtain topographic-vegetation coupled spatial distribution data, thereby determining the landslide sensitivity level of each preset grid unit and generating landslide sensitivity level spatial distribution data; and retrieving water storage spatial distribution data based on microwave and thermal infrared remote sensing images to assess the stability of the tower foundation area where the power transmission and transformation equipment is located, obtaining landslide level distribution data to determine control measures. This invention solves the problem of low accuracy in landslide detection in existing technologies.

The application discloses a water body pollution detection method and system based on satellite thermal infrared remote sensing, and relates to the technical field of water body pollution detection. The method comprises the following steps: collecting thermal infrared remote sensing parameters, environmental monitoring parameters and geographical feature parameters, constructing a detection basic parameter set, and extracting an effective water body grid; combining the thermal infrared remote sensing parameters of the effective water body grid with the environmental monitoring parameters, dynamically optimizing temperature inversion model parameters, performing temperature inversion, and obtaining water body surface temperature; performing pollution-free grid screening based on the water body surface temperature, and obtaining water body thermal infrared reference parameters of the pollution-free grid; comparing the water body surface temperature with the water body thermal infrared reference parameters, identifying and extracting water body thermal anomaly grid parameters; and performing spatial feature analysis based on the water body thermal anomaly grid parameters, positioning a water body pollution discharge outlet, and obtaining a pollution diffusion range. The application effectively improves the precision of water body pollution detection and the accuracy of spatial positioning of the pollution discharge outlet.

The present application discloses a dry hot rock fracture identification multi-source information fusion and intelligent interpretation technology, specifically comprising the following steps: step one: data acquisition: collecting multi-source data including seismic reflection wave, well logging lithology parameter, electromagnetic anomaly data, thermal infrared remote sensing image, and establishing a dry hot rock reservoir physical property parameter database, step two: data preprocessing: denoising and migration correction are carried out on seismic data, well logging data is normalized, electromagnetic data is inverted resistivity distribution, and temperature anomaly area is extracted from thermal infrared image, the present application relates to the geothermal development technical field. The dry hot rock fracture identification multi-source information fusion and intelligent interpretation technology integrates geological, geophysical, remote sensing and drilling data and other multi-modal information, combines feature level and decision level fusion strategy, effectively makes up for the sensing blind area of single sensor, and pre-processes the data, effectively improves the inhibition ability of seismic wave noise, electromagnetic interference and complex environmental factors.

This invention discloses a method and system for inverting a continuous surface emissivity spectrum, relating to thermal infrared remote sensing parameter inversion technology. Focusing on the problem of emissivity spectrum inversion under hyperspectral thermal infrared remote sensing, this invention combines machine learning models with wavelet transform to achieve direct inversion of the surface emissivity spectrum. This invention not only fully utilizes the high precision and efficient computation of the random forest algorithm but also effectively captures the shape characteristics of the emissivity spectrum in the thermal infrared band, thereby alleviating the neglect of emissivity spectrum shape in traditional methods and avoiding the limitations of traditional methods such as dependence on atmospheric correction accuracy or difficulty in decoupling surface temperature and emissivity values. Therefore, this invention can directly invert high-precision, continuous, and complete surface emissivity spectra from observation data from spaceborne or airborne hyperspectral thermal infrared sensors, which has significant value for subsequent industry applications.

This invention discloses a method for identifying geothermal potential areas by integrating thermal infrared remote sensing and geothermal heat flow information, belonging to the field of geothermal potential area identification technology. The method includes the following steps: S1, constructing a dataset, including thermal infrared remote sensing data reflecting surface thermal information and heat flow data reflecting subsurface thermal information; S2, constructing a semantic segmentation model based on deep learning; S3, training the semantic segmentation model using the dataset; S4, using the trained semantic segmentation model to complete the identification of geothermal potential areas. This invention integrates thermal infrared remote sensing information and geothermal heat flow information, using a surface-subsurface joint feature extraction approach. Through deep learning, from data preprocessing to anomaly segmentation and potential classification, it achieves end-to-end training for geothermal potential area identification, forming a complete workflow for automatic delineation and potential classification of geothermal potential areas.

The application provides a cloud-based thermal infrared remote sensing method and system for extracting weak thermal anomaly candidates and suppressing false anomalies, belonging to the field of remote sensing image processing and computer vision. To solve the problem of how to ensure high recall rate of weak thermal anomalies and effectively suppress false anomaly candidates under low spatial resolution and complex observation conditions, and output candidate results with credibility description, the application constructs a candidate learning mechanism for cloud influence perception; introduces a gated false anomaly suppression mechanism to establish a continuous reliability modulation function based on candidate saliency; constructs a candidate probability map and a candidate region confidence index, so that the output result not only includes a candidate region set, but also contains corresponding credibility information. The application realizes the automatic extraction of weak thermal anomaly candidate regions and the suppression of false anomalies under the condition of cloud influence or complex ground surface background interference, providing reliable candidate input for subsequent fine positioning, cross-spectral consistency analysis or manual review.

This invention discloses an anomaly localization method and system for UAV thermal infrared remote sensing, relating to the field of UAV intelligent early warning technology. The method includes: obtaining candidate anomaly regions and confidence scores from thermal infrared target images through reasoning; obtaining a temperature matrix based on the absolute temperature values ​​at the image pixel coordinates; extracting the temperature sub-matrix at the corresponding position of the candidate anomaly region in the pixel coordinate system to determine the highest temperature of the candidate anomaly region; determining the final anomaly region based on the confidence score and the highest temperature of the candidate anomaly region; converting the pixel coordinates of the final anomaly region into a unit line-of-sight vector in the world coordinate system; and calculating the geographical location of the anomaly target by extending a set distance along the unit line-of-sight vector from the current position of the UAV. Temperature measurement is combined to verify the visual detection results to improve the reliability of the early warning; and UAV flight data is combined to estimate the geographical location of the anomaly target to enhance the practicality of the location information.