84 results about "Thermal infrared remote sensing" patented technology

The invention discloses a land degradation supervision method based on remote sensing monitoring, and relates to the technical field of land degradation monitoring. The method is used for solving the problems of hidden degradation risk identification and dynamic propagation simulation. According to a multi-temporal thermal infrared remote sensing image, daily variation characteristics of surface temperature are extracted through spectral analysis, a recessive salinization risk distribution map is constructed by combining measured data of soil salinity, and interference of vegetation coverage is overcome. And multi-source remote sensing and geographic data are fused, dominant driving factors significantly associated with the salting risk are screened, and the degeneration cause is clarified. And in combination with ecological restoration potential and treatment resource constraints, calculating an antagonism index of a driving factor and the restoration potential, and dividing degradation threat levels. And a natural hydrology and human activity dual-path propagation model is constructed, a risk space-time evolution process is simulated, and a future hotspot migration path and an optimal blocking window are predicted. According to the method, accurate early warning and active prevention and control of land degradation are realized through a technical chain of risk identification, driving analysis, threat grading and dynamic simulation.

The invention discloses a method for evaluating the influence of black land ecological barrier pattern evolution on agricultural climate and yield, and relates to the technical field of agricultural ecological environment monitoring and remote sensing model coupling. Comprising the following steps: S1, acquiring a high-resolution satellite image, microwave remote sensing earth surface humidity data, optical remote sensing vegetation coverage data and thermal infrared remote sensing earth surface temperature data of a target area; according to the method for evaluating the influence of the black land ecological barrier pattern evolution on the agricultural climate and the yield, the problem of lack of ecological-climate-agricultural system collaborative modeling in the traditional technology is solved. A high-resolution satellite image is used for analyzing a network topology structure of the protection forest, microwave and thermal infrared remote sensing are fused to invert'water, soil and gas generation 'multi-element parameters, and dynamic quantitative evaluation of ecological barrier spatial heterogeneity evolution on local climate and crop growth is realized in combination with a dynamic weight distribution and two-way nesting technology.

The invention discloses a geothermal abnormal point identification system based on remote sensing detection. The system comprises a data layer which collects thermal infrared remote sensing data, multispectral / hyperspectral remote sensing data, radar data, geological and topographic data, meteorological data and geophysical prospecting data; the processing layer is used for extracting key features, capturing dynamic changes of geothermal anomalies, distinguishing continuous geothermal anomalies and transient events, combining hyperspectral data and magnetotelluric sounding data, and constructing'earth surface-deep part 'associated features; the analysis layer is used for learning a diffusion rule of geothermal anomalies along a fault zone through a graph propagation model, taking a geothermal field heat conduction equation as a loss function constraint by utilizing a physical information neural network, jointly training a temperature field prediction model, constructing a deep three-dimensional geological structure based on gravity and geophysical prospecting data, and constructing a geologic structure model; constructing a geothermal anomaly detection model through the features provided by the processing layer to recognize geothermal anomaly points; and the output layer is used for generating a geothermal anomaly probability graph.

The invention discloses a glacier jump prediction and data sample enhancement management method, particularly relates to the field of glacier remote sensing monitoring, is used for solving the problem of accurate identification and processing of surface moraine covering type glacier local albedo abnormal effect, and aims at solving the problem of accurate identification and processing of the glacier local albedo abnormal effect by comprehensively analyzing the coupling relationship between spectrum and temperature and the spatial sensitivity of temperature gradient. And accurate identification and processing of the moraine covering glacier local albedo abnormal effect are realized. According to the method, main causes of albedo abnormity can be effectively distinguished, and an abnormal area is corrected in a targeted manner by scientifically selecting an optical and thermal infrared remote sensing fusion mode or an optical and radar remote sensing fusion mode, so that the glacier identification precision and the jump prediction accuracy are remarkably improved. Through multi-level remote sensing data correction and feature extraction, a high-precision data foundation is laid for subsequent analysis; in the process of generating an enhanced sample and optimizing a prediction model, the reliability and response speed of glacier jump prediction are further improved.

The invention provides a regional soil component detection method based on a remote sensing image, and belongs to the technical field of soil detection. Aiming at the problems that a traditional detection method depends on a single optical remote sensing image, is interfered by weather and vegetation, and is low in detection precision, low in efficiency, unguaranteed in data credibility and the like, radar and thermal infrared remote sensing data are introduced to be fused with an optical image, features are extracted through principal component analysis, a generative adversarial network is adopted to carry out hyperspectral image super-resolution reconstruction, and a high-resolution hyperspectral image is obtained. A genetic algorithm is utilized to realize adaptive wave band selection, a real-time atmospheric correction model is constructed, a recurrent neural network and a spatial convolutional neural network are utilized to mine spatio-temporal context information, a quantum computing acceleration algorithm is introduced, block chain management data is utilized, and unmanned aerial vehicle cooperative operation is combined. According to the method, the detection precision, efficiency and data credibility are remarkably improved, and the regional soil component detection process is effectively optimized.

The embodiment of the invention provides a coal field fire area gas and particulate matter monitoring method, device and equipment and a storage medium, and the method comprises the steps: carrying out the temperature inversion of thermal infrared remote sensing image data based on a preset temperature inversion algorithm, and obtaining a temperature abnormal region; based on a pre-constructed hyperspectral detection model, performing inversion on the soil moisture data, the chlorophyll content data and the vegetation coverage data to obtain a surface vegetation growth condition; based on the temperature abnormal area and the earth surface vegetation generation condition, a preset judgment model is adopted for judgment, and the fire combustion stage is determined; based on the acquired atmospheric monitoring data, determining a two-dimensional distribution condition of gas and particulate matters in each fire combustion stage; and based on the two-dimensional distribution condition, performing overlay analysis on the atmospheric monitoring data at different heights in the temperature abnormal region to obtain the three-dimensional distribution condition of the gas and the particulate matters. Therefore, the accurate judgment of the combustion condition of the fire area is improved, and the accuracy and reliability of gas and particulate matter monitoring are improved.

The invention discloses a riverway water temperature change trend prediction method based on remote sensing and water temperature inversion, and belongs to the field of riverway water temperature change trend prediction.The method comprises the steps that hydrological data of a riverway are obtained, thermal infrared remote sensing data, hydrological data and actually-measured water temperature data of all riverway sub-segments are aligned based on a time sequence and measuring point positions, and therefore the water temperature change trend of the riverway is obtained; meanwhile, adding air temperature data of each time to obtain a plurality of groups of time sequence alignment data sequences; performing filling processing on each group of time sequence alignment data sequences to obtain a plurality of groups of water temperature inversion data sequences; according to each group of water temperature inversion data sequences, discrete values are eliminated, and the average water temperature of each river subsection at each time is solved; iteratively solving the weight of each water temperature influence factor by using a BP neural network to obtain a water temperature prediction model; and obtaining a to-be-measured real condition, and obtaining a water temperature prediction result by using the water temperature prediction model. According to the method, the problem that water temperature inversion is greatly influenced by atmosphere, earth surface and solar radiation, so that the accuracy of a water temperature prediction result is not enough is solved.

A method for spatial reconstruction and downscaling of all-sky surface temperature belongs to the field of remote sensing science and technology. It contains the following main steps: acquisition and preprocessing of multi-source remote sensing data and atmospheric driven data, spatial reconstruction of all-sky surface temperature data, and spatial downscaling of all-sky surface temperature data. The operability and universality of the present invention in practical applications will promote the popularization and application of surface temperature data in the fields of climate change, dynamic monitoring and assessment of hydrological and ecological environment, land surface radiation budget and energy balance, and further promote the development of thermal infrared remote sensing science.

The invention discloses a hydrothermal vein type gold deposit alteration zoning remote sensing identification method, and the method specifically comprises the following steps: S1, carrying out multi-platform remote sensing cooperative interpretation, and obtaining the initial alteration zoning information of a regional scale. According to the hydrothermal vein type gold deposit alteration zoning remote sensing identification method, through organic combination of multi-platform remote sensing cooperative interpretation and unmanned aerial vehicle fine mineral mapping, cross-scale detection from regional scale preliminary alteration zoning identification to target region scale alteration lithofacies accurate delineation is realized; the problems that a traditional remote sensing method is single in scale and insufficient in precision in alteration zoning recognition are effectively solved. According to the method, the complementation advantages of multi-temporal optical remote sensing, synthetic aperture radar and thermal infrared remote sensing data are utilized, accurate recognition of key altered minerals is achieved in combination with hyperspectral data of the unmanned aerial vehicle, and the certainty of alteration zoning boundaries and the accuracy of lithofacies classification are remarkably improved.

The invention discloses a multi-source information fusion and intelligent interpretation technology in hot dry rock fracture identification, and the technology specifically comprises the following steps: 1, data collection: collecting multi-source data including seismic reflected waves, logging lithologic parameters, electromagnetic abnormal data and thermal infrared remote sensing images, and building a hot dry rock reservoir physical property parameter database, and 2, data preprocessing: carrying out denoising and offset correction on seismic data, normalizing logging data, inverting resistivity distribution of electromagnetic data, and extracting a temperature abnormal region of a thermal infrared image. The invention relates to the technical field of geothermal development. According to the multi-source information fusion and intelligent interpretation technology in hot dry rock fracture identification, by integrating multi-modal information such as geology, geophysics, remote sensing and drilling data and combining a feature level and decision level fusion strategy, a sensing blind area of a single sensor is effectively made up, the data are preprocessed, and the recognition accuracy is improved. And the capability of effectively inhibiting complex environmental factors such as seismic wave noise and electromagnetic interference is improved.

The invention provides a soybean growth monitoring method based on satellite remote sensing, and relates to the technical field of crop growth monitoring, and the method specifically comprises the steps: setting two monitoring nodes according to a soybean growth period, and collecting multispectral and thermal infrared remote sensing images and normal growth leaf area density and stem diameter sample data; a soybean area and a non-soybean area are distinguished by using a vegetation index threshold, cloud / shadow pixels are eliminated by using a multiband combination-threshold method, effective pixels are screened, and two types of remote sensing data are matched. Extracting leaf area density, canopy temperature and collaborative inversion stem diameter from the effective data; calculating the relative growth rate of the two types of indexes based on samples, and constructing a collaborative growth reference equation and a residual standard deviation; and substituting the growth rate of the planting area into an equation to obtain a theoretical value, calculating a deviation value, and judging the soybean growth state by combining the comparison between the deviation and a normal fluctuation interval and the positive and negative characteristics of the growth rate.

The invention provides an aerial target height inversion method based on thermal infrared hyperspectral satellite data, which can be applied to the technical field of thermal infrared remote sensing. The method is applied to a height inversion system, the height inversion system comprises at least one height inversion model, and the method comprises the following steps: acquiring thermal infrared hyperspectral satellite data for an aerial target object; according to the thermal infrared hyperspectral satellite data, target object temperature, atmospheric condition information and background ground object information are determined, the atmospheric condition information represents atmospheric conditions of the position where the aerial target object is located, and the background ground object information represents information of background ground objects below the position where the aerial target object is located; determining a target height inversion model corresponding to the thermal infrared hyperspectral satellite data from at least one height inversion model according to the atmospheric condition information, the background ground feature information and the target object temperature; and inputting thermal infrared hyperspectral satellite data into the target height inversion model, and outputting a target height for the aerial target object.

The invention relates to the related technical field of ship safety and pollution prevention, in particular to an oil spill area measuring and calculating method based on improved edge detection, and the method comprises the steps: obtaining a thermal infrared remote sensing image of an oil film region through the cruise monitoring of an unmanned aerial vehicle, and processing the collected thermal infrared image; the thermal infrared image is measured and calculated by adopting an improved Canny algorithm to obtain the final area of an oil spilling region, the measured and calculated actual area of the oil spilling region is visually displayed, and the improved Canny algorithm effectively eliminates impurity information under the condition of ensuring the completeness of edge information features, so that the accuracy of the oil spilling region is improved, and the accuracy of the oil spilling region is improved. And in the aspect of oil film area edge main information response, the accuracy of edge identification is improved while the identification efficiency is ensured.

The invention provides a transformer substation noise traceability and diffusion simulation method fusing multi-source remote sensing data. Belongs to the technical field of power environment protection and remote sensing science. The method comprises the following steps: acquiring thermal infrared remote sensing image data of a transformer substation, after preprocessing, finding out a temperature anomaly region of main noise source equipment by using a temperature anomaly recognition algorithm, determining the position of the main noise source equipment in combination with equipment layout information, and generating position data of the noise source equipment; a laser radar is used for scanning a transformer substation and surrounding areas to obtain high-precision point cloud data, the high-precision point cloud data are processed to generate high-precision digital elevation model data, and a transformer substation three-dimensional scene model containing detailed topographic features and noise source positions is constructed in combination with noise source equipment position data. Temperature abnormity of main noise source equipment is identified by means of thermal infrared images, noise sources of specific equipment such as a main transformer and an electric reactor can be accurately positioned, equipment-level traceability is realized, the situation that traceability is difficult in a traditional method is changed, and a clear direction is provided for targeted noise treatment.

The invention discloses an FY4A AGRI surface temperature-based mountain air temperature direct reduction rate spatial-temporal distribution estimation method, which comprises the following steps of: acquiring FY4A AGRI thermal infrared remote sensing surface temperature and influence factor data thereof, and preprocessing to obtain data under a 4km resolution ratio; performing spatial dimension reconstruction on the surface temperature missing data by adopting a random forest regression algorithm, and performing time dimension smoothing on a spatial dimension reconstruction result by adopting an S-G filter to obtain a surface temperature space-time dimension reconstruction result; constructing a surface temperature downscaling model by using a random forest regression algorithm, and reducing the resolution ratio of the surface temperature from 4km to 1km; the influence of the altitude on the surface temperature is separated, and the standardized surface temperature is calculated; and establishing a linear regression relationship between the standardized surface temperature and the altitude by adopting a sliding window method, and calculating a regression coefficient, so as to obtain an air temperature direct reduction rate. And necessary data and technical support are provided for related research fields such as weather forecast and climate model application.

The invention provides a simulation design method of an urban ecological corridor, which comprises the following steps: S1, collecting a multi-temporal thermal infrared remote sensing image of a city to be simulated and designed and preprocessing to obtain a core heat island node; s2, heat resistance surface construction is carried out based on different surface types, a heat transfer resistance surface is obtained, and the different surface types comprise a digital elevation model, an impervious surface index, a normalized vegetation index, a normalized building index, a normalized water body index and a gradient; s3, taking the core heat island node as a network end point, searching a communication path with the lowest resistance on a heat transmission resistance surface, and obtaining an urban heat island corridor; and S4, on the basis of the urban land utilization data, ecological lands of forests, wetlands, large parks and water bodies serve as candidate ecological source lands, ecological connection paths are constructed from the angle of ecological connectivity by adopting the S2 and the S3, and the urban ecological corridor is obtained.

The invention relates to the technical field of image segmentation, in particular to a coal mine area ground fracture 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 fracture data set based on the visible light remote sensing image and the thermal infrared remote sensing image; a ground fracture recognition model is constructed based on the neural network, the ground fracture recognition 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 fracture recognition model according to the ground fracture data set; and performing ground fracture identification on the visible light remote sensing image to be detected and the thermal infrared remote sensing image to be detected of the target coal mine area by using the trained ground fracture identification model to obtain a ground fracture identification result map. According to the method and the device, the visible light and thermal infrared bimodal data are fused, so that accurate identification of the ground fissures is realized in a complex scene of a coal mine area.

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 present application relates to a multi-source remote sensing driven precision irrigation and fertilization method and an integrated mobile operation system, aiming at the problems of large environmental heterogeneity influence, poor data consistency, delayed feedback and low execution adaptability of multi-source remote sensing in farmland irrigation and fertilization strategy making. The method establishes a multi-source spatio-temporal alignment observation data set through physical preprocessing of satellite, unmanned aerial vehicle and thermal infrared remote sensing images and environmental label data, realizes unified mapping from physical characteristics to crop stress semantic space by using a lightweight semantic encoder, carries out abnormal source elimination combined with semantic consistency measurement and mismatch detection, and realizes adaptive and closed-loop decision making according to crop growth stages and stress types by integrating historical feedback and dynamic correction of model parameters. The present application improves the accuracy, environmental robustness and response timeliness of farmland irrigation and fertilization strategy, and is conducive to the optimization of intelligent operation.

The present invention provides a method and device for inverting a thermal infrared hyperspectral surface temperature emissivity spectrum, and relates to the field of thermal infrared remote sensing technology. The method comprises: obtaining satellite remote sensing data of a thermal infrared hyperspectral spectrum, performing cloud detection on the satellite remote sensing data, screening out valid data without cloud coverage, and extracting the entrance pupil radiance and entrance pupil brightness temperature from the valid data; using a thermal infrared hyperspectral atmospheric correction model to perform atmospheric correction on the entrance pupil radiance and entrance pupil brightness temperature, and inverting to obtain the surface exit radiance and surface exit brightness temperature; based on the surface exit radiance and surface exit brightness temperature, using a pre-constructed emissivity sparse dictionary to reconstruct the emissivity spectrum; and using a pre-established minimum value empirical constraint to limit the value of the reconstructed emissivity spectrum, and simultaneously inverting to obtain the surface temperature and the surface emissivity spectrum. The present invention can realize the simultaneous inversion of the surface temperature and the surface emissivity spectrum in the 8-14μm thermal infrared spectrum.

The invention provides a remote sensing and crop growth model-based field corn irrigation water demand calculation method. The method comprises the following steps of: constructing a microwave scattering model based on microwave remote sensing data, and constructing a thermal inertia model based on thermal infrared remote sensing data; learning a non-linear mapping relation between remote sensing data and ground actually-measured multi-layer soil moisture through a deep neural network, optimizing key parameters of a multi-source fusion model, and establishing calibration parameter values and soil moisture content parameter values of the multi-source fusion model under different hierarchies; on the basis of the difference of different soil layer moisture demands in different growth stages of the corn, the water amount needing irrigation is calculated in combination with a multi-layer soil moisture calculation result; according to the possible rainfall in the preset time period, combining the area of the region to obtain predicted rainfall; according to the intelligent irrigation decision-making system for the field corn, the remote sensing technology, the crop physiological model and meteorological prediction are organically combined, and a complete and practical intelligent irrigation decision-making system for the field corn is formed.

The utility model discloses a dam leakage identification test device based on different temperature differences, which relates to the technical field of dam leakage identification tests and comprises a supporting table, a model groove is mounted at the top of the supporting table, and a heat preservation irradiation assembly is mounted at the top of the model groove through a hinge. The heat preservation irradiation assembly is used for providing heat for generating temperature difference, the heat preservation irradiation assembly comprises a protective shell, a through groove and a heating irradiation lamp, the protective shell is installed at the top of the model groove through a hinge, the through groove is formed in the front face of the protective shell, and the heating irradiation lamp is installed on the top slope of the protective shell in a penetrating mode. According to the utility model, the heating irradiation lamp irradiates the dam surface after being electrified, so that the temperature of the dam surface rises, and different temperature differences are formed between the temperature of the dam surface and the water temperature of the leakage water outlet, so that the effect of different temperature differences on dam leakage identification of the test device is researched, and the minimum temperature difference index is determined; and the support is provided for the thermal infrared remote sensing technology embankment patrol risk inspection.

The application provides a near real-time fire point dynamic monitoring method, device, equipment and medium, relates to the technical field of infrared remote sensing monitoring, and the method comprises the following steps: acquiring thermal infrared remote sensing data and land cover product of a forest and grass monitoring area, and performing data preprocessing; the thermal infrared remote sensing data is segmented to obtain tile data, and cloud extraction is performed based on the tile data; the extracted cloud is used for mask of the thermal infrared remote sensing data, and the medium infrared band and the far infrared band are segmented to obtain an isothermal graph spot layer; the isothermal graph spot layer is masked through water body and building area corresponding to the land cover product; the masked isothermal graph spot is comprehensively identified based on the statistical characteristics of the isothermal graph spot and the comparison characteristics of the isothermal graph spot and adjacent background graph spots, and a fire point detection result in the forest and grass monitoring area is obtained. The application alleviates the technical problems of pixel-by-pixel identification, large amount of calculation, low efficiency and limited precision in the prior art.

The present invention discloses an angle effect correction method for geostationary meteorological satellite thermal infrared surface temperature data, which belongs to the field of thermal infrared remote sensing technology. The present invention first obtains geostationary satellite thermal infrared remote sensing surface temperature data of the target area and converts it to the target coordinate system; then calculates the angle parameters of each pixel based on the satellite sub-satellite data; performs system error elimination processing on the nighttime surface temperature data of two satellites screened based on the satellite zenith angle; then uses the nighttime surface temperature data to simplify the kernel-driven model and solve the emissivity kernel parameters; solves the solar nuclear coefficient and hotspot height based on the daytime surface temperature data at multiple consecutive moments, and combines the solved parameters to obtain vertical observations of each pixel. The present invention can quickly and accurately solve the parameters of the kernel-driven model and then accurately solve the vertically observed surface temperature, overcoming the defects of the traditional method such as large data demand, low calculation efficiency, and low accuracy, and can serve a large number of thermal infrared remote sensing surface temperature application scenarios.

The invention discloses a granite identification method and device based on SDGSAT-1 satellite thermal infrared remote sensing, and the method comprises the steps: carrying out the preprocessing of obtained SDG SAT-1 satellite thermal infrared remote sensing data, and obtaining a remote sensing image of a research region; establishing a corresponding relation between mineral spectral curve characteristics of the research area and a satellite sensor spectral domain; according to the remote sensing image and the mineral spectrum curve in the corresponding relation, a GTI granite index graph is extracted through a GTI granite index formula, and according to the GTI granite index graph, a granite distribution result graph meeting the preset precision is extracted by combining an image segmentation and edge detection method.

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.

The invention discloses a ship thermal infrared wake detection method based on a rhombus prediction frame YOLO model, and the method comprises the steps: replacing a conventional rectangular frame with a rotatable rhombus prediction frame, and positioning a wake candidate region through the center coordinate of a rhombus, the length of a diagonal line, and a rotation angle; thirdly, Gaussian filtering denoising is carried out on the candidate area, potential line segments are detected in combination with line support domain growth and rectangular fitting, effective line segments are screened through the false alarm number and the Euclidean distance, and the image is segmented based on gray average and variance binaryzation; and finally, extracting a continuous wake contour through edge detection, and fitting and optimizing morphological parameters in combination with a recursive broken line. By utilizing the method, the wake target on the thermal infrared remote sensing image can be quickly detected, the wake contour can be accurately fitted, the detailed form information can be acquired, and the method is particularly suitable for the application requirement of real-time monitoring of the sea surface moving target.