91 results about "Ground surface temperature" patented technology

The invention provides a high-temporal-spatial-resolution surface temperature reconstruction system for urban thermal environment refined monitoring, and relates to the field of electric digital data processing. Comprising a multi-source heterogeneous data intelligent acquisition and preprocessing module, an urban thermal environment multi-dimensional feature knowledge modeling module, a physical constraint deep learning surface temperature reconstruction module and an intelligent monitoring early warning and decision support module. The multi-source heterogeneous data intelligent acquisition and preprocessing module is responsible for collecting and preprocessing various remote sensing and ground observation data, and the urban thermal environment multi-dimensional feature knowledge modeling module constructs a knowledge system of an urban underlying surface, a three-dimensional form and a thermal process. The physical constraint deep learning surface temperature reconstruction module is used for realizing accurate reconstruction of high temporal-spatial resolution surface temperature, and the intelligent monitoring early warning and decision support module converts a reconstruction result into visual display, risk early warning and regulation and control decision suggestions; according to the system, high-precision, physically consistent and interpretable urban surface temperature reconstruction can be realized.

The invention discloses a method for evaluating rock mass fracture freeze-thaw fracture damage risk based on surface temperature, which comprises the following steps: S1, carrying out data acquisition on a target area based on a multi-source sensor carried by an unmanned aerial vehicle platform, and obtaining fracture geometric parameters, daily surface minimum temperature, daily surface maximum temperature, daily temperature difference and fracture moisture conditions; s2, on the basis of the geometric parameters of the crack, constructing a crack frost heaving force analytical model; obtaining a quantitative relation between the stress intensity factor and the environment temperature; s3, the I-type fracture toughness of the target rock mass is measured, and the critical crack initiation temperature of the rock mass is determined; determining the number of critical freezing and thawing cycles; s4, on the basis of the daily earth surface minimum temperature, the daily temperature difference, the fracture moisture condition and the critical crack initiation temperature, the annual accumulated effective freezing and thawing cycle number is obtained; and calculating a freeze-thaw damage ratio, and carrying out risk quantification and grading. According to the invention, the problem of inaccurate evaluation caused by limitation to local monitoring and lack of an environment factor and material parameter integrated evaluation framework in the prior art is solved.

The invention discloses a surface temperature medium and long term forecasting method based on a multi-scale TransFuse pyramid network. The surface temperature medium and long term forecasting method comprises the steps of S1, acquiring original LST time sequence data and performing preprocessing; s2, constructing a three-dimensional time delay embedded feature tensor for the data preprocessed in the S1 by adopting a stepped cross-node tensor feature reconstruction method; s3, on the basis of the three-dimensional time delay embedded feature tensor constructed in the S2, meteorological features of different time scales are extracted in parallel through a dynamic multi-resolution convolution kernel group; s4, performing five-stage cascade operation on the meteorological features of different time scales extracted in the S3 to realize deep fusion of cross-scale features, and performing high-level semantic information integration through a global feature pyramid; and S5, finally outputting a multi-step prediction result through a regression prediction framework based on the fusion features obtained in the S4. According to the invention, an extensible technical normal form is effectively provided for high-precision meteorological prediction in a limited computing power scene, and important application potential is shown in actual business deployment.

The invention belongs to the technical field of data processing, and discloses a Mars rover non-contact trafficability estimation method and system based on thermal inertia, and the method comprises the steps: obtaining a ground surface temperature time sequence and environment parameters of a target region; constructing a thermal inertia estimation model, and inputting the earth surface temperature time sequence and the environmental parameters into the thermal inertia estimation model to obtain a thermal inertia estimation value of the fire soil; constructing a thermal inertia and trafficability index relation model, inputting the thermal inertia estimation value of the fire soil into the thermal inertia and trafficability index relation model, and outputting a predicted trafficability index; and determining a trafficability state grade according to the predicted trafficability index, and generating a navigation control suggestion, so that the Mars rover passes through the target area according to the Mars rover navigation control suggestion. According to the method, the trafficability index of the Mars rover is predicted by extracting the thermal inertia estimation value of the fire soil in the target area, the evaluation precision of the Mars rover passing through the target area can be effectively improved, and the driving safety of the Mars rover is ensured.

The invention discloses a land utilization change comprehensive feature analysis method based on multi-source heterogeneous data fusion, and relates to the technical field of remote sensing and geographic information processing. Building volume, building density, night light, surface temperature and population density are aligned under unified coordinates and resolution; constructing an average building height according to volume / density and coding and recording quality; uniform noctilucence is realized through partition three-order mapping; interpolation is carried out by adopting fractional learning under the missing measurement mask, and pixel-level uncertainty is output; uniformizing the annual temperature; extrapolation is carried out through multi-scale space-time small block coding-decoding containing flux conservation and Laplace constraint, and uncertainty is given; implementing uncertainty weighted principal components according to the five indexes to obtain a comprehensive strength index; concentric buffering, set splitting regression and partial response confidence band recognition threshold values are combined. The method has the advantages of cross-period comparability, physical consistency, traceable uncertainty and the like.

The invention discloses a debris flow prediction method based on multi-source remote sensing, and the method comprises the following steps: 1, data acquisition and preprocessing: obtaining target region data through satellite remote sensing, and eliminating terrain shadow interference; step 2, feature extraction: extracting vegetation coverage and surface temperature from the optical image, extracting deformation magnitude and time sequence from InSAR data, and extracting gradient, slope direction, curvature and terrain humidity index from DEM terrain data; 3, performing multi-dimensional feature fusion, and constructing a multi-dimensional feature vector; 4, model construction: establishing a debris flow susceptible area identification model, and fusing the vegetation-terrain coupling characteristics of the optical image, the deformation dynamic characteristics of the InSAR and the terrain stability characteristics of the terrain data; 5, carrying out susceptibility partitioning and early warning, dividing risk grades based on probability values output by the model, and triggering graded early warning responses; according to the method, the multi-dimensional feature space is constructed through the collaborative interaction of the multi-source remote sensing data and the fused data.

The invention discloses a marking method and system for a geothermal abnormal target area, and the method comprises the steps: generating a surface temperature distribution diagram according to the remote sensing thermal infrared data of a target area, and marking a first-stage geothermal abnormal target area; a temperature measurement network is arranged in the first-stage geothermal abnormal target area, ground temperature measurement data are collected, and a shallow ground temperature distribution diagram is generated; marking a secondary geothermal abnormal target area by combining the shallow ground temperature distribution diagram and the ground surface temperature distribution diagram; and obtaining geothermal information of the second-stage geothermal abnormal target area, marking a drilling position according to the geothermal information, drilling the drilling position, collecting deep geological data, and inputting the deep geological data into a pre-trained geothermal geological model to obtain a target geothermal abnormal target area output by the geothermal geological model. According to the method, through comprehensive analysis and processing of multiple data, the accuracy and reliability of marking of the geothermal abnormal target area are improved.

The application discloses a kind of urban heat island network construction method based on multilevel thermal field recursive decomposition in the technical field of urban climate analysis, including obtaining seamless summer average ground surface temperature grid data of initial area, the multidimensional environmental driving factor data required for building thermal resistance surface;Based on mean-standard deviation threshold method, the continuous ground surface temperature field of the initial area is multilevel recursive decomposition, and the main level heat island source is identified, and the nested secondary heat island source is recursively identified inside the main level heat island source, and the hierarchical nested heat island network structure is constructed.The application realizes the accurate decomposition of multilevel heat island source by using mean, standard deviation threshold value for recursive calculation of continuous ground surface temperature field, can effectively identify cross-scale heat island connection pinch point and heat island connection barrier, can realize the hierarchical construction of urban heat island network, and is conducive to improving the management efficiency of urban heat island.

The invention discloses a method for regulating and controlling a thermal environment by an urban form under coupling of human eyes and a bird's-eye view angle. The method comprises the following steps of: inverting a surface temperature based on a radiation transfer equation method and a Landsat-8 remote sensing image; carrying out fine extraction on urban ground feature information fused with multi-modal data; constructing a three-dimensional comprehensive representation system of the urban form under the coupling of a bird's-eye view angle and a human eye view angle; establishing an urban surface temperature prediction model fusing an urban two-dimensional form, an urban three-dimensional form in a bird's-eye view angle and an urban three-dimensional form in a human eye view angle under different spatial scales; and an optimal configuration method for regulating and controlling the surface thermal environment by the urban form under the fine scale and the rough scale is explored. According to the method, a scientific basis can be provided for quantitative regulation and control and space planning optimization of the urban thermal environment, and the effects of refined cooling and thermal environment improvement under urban space structure optimization and greening configuration adjustment are achieved.

This invention relates to the field of image sensing data processing and discloses a method for diagnosing the thermal environment of blue-green spaces in cold-region cities based on multispectral remote sensing. The method includes the following steps: acquiring multispectral remote sensing images, three-dimensional building elevations, and solar apparent shape parameters; calculating the illumination shading coefficient of blue-green space pixels to form a three-dimensional dynamic shadow mask; constructing a microscopic phase transition evolution operator using the sensitivity gradient of radiation intensity in different polarization directions and mid-infrared reflectivity; inputting the mask and operator into the thermal infrared radiation measurement equation to reconstruct the dynamic surface temperature; solving the surface energy balance equation based on the dynamic surface temperature, separating the latent heat storage of phase transition energy, and constructing a latent heat buffer index; and performing a comprehensive diagnosis of the thermal environment health based on this index. This invention effectively overcomes the temperature measurement errors caused by complex shading and phase state interweaving, accurately isolates the latent heat energy of phase transition, and achieves precise positioning and objective quantitative diagnosis of microclimate anomalies in cold-region cities.

The invention relates to the technical field of infrared detection, and discloses a high-precision infrared surface temperature measuring device and method, and the device comprises at least one infrared sensor which is used for measuring the target temperature and the cavity temperature; the infrared optical lens penetrates through an infrared radiation signal and prevents mosquitoes from entering the device; a camera unit that captures and acquires an underlying surface image; the light intensity measuring unit is used for measuring environment radiation; and the control part is used for reading the target temperature and the cavity temperature measured by the infrared sensor, acquiring the underlying surface image shot by the camera, acquiring the voltage value of the light intensity measuring unit and acquiring the real-time time of the system. An infrared optical lens is additionally arranged on the structure, and the target temperature is corrected through an infrared optical lens energy compensation algorithm. The camera device based on underlying surface identification identifies the type of the underlying surface through an image and estimates a corresponding emissivity value; through linear fitting of environmental radiation energy, the target temperature is corrected by using the emissivity and the environmental radiation, and the measurement precision is improved.

The application discloses a kind of spatiotemporal modeling ground surface temperature downscaling method and system considering energy constraint, comprising: 1) acquisition and preprocessing of multi-source remote sensing and meteorological data;2) feature grouping and spatiotemporal feature tensor construction;3) time feature and spatial feature extraction;4) spatiotemporal feature modeling and high-resolution ground surface temperature estimation;5) loss construction and cross-scale consistency constraint;6) model iterative training and result output.The application breaks through the modeling limitation of time variation law and spatial detail description in the prior art, realizes the collaborative promotion of time continuity and spatial fine expression of ground surface temperature.On this basis, the overall temperature deviation and the problem of insufficient physical rationality commonly existing in the prior art are also effectively avoided, and the application is significantly superior to the prior art in terms of timing stability, spatial accuracy and physical reliability.

The invention relates to the technical field of remote sensing data processing, and provides a soil humidity data missing filling method, which comprises the following steps: acquiring a soil humidity data sequence corresponding to ESA CCI soil humidity data to be filled, the multi-source soil humidity related data comprises surface temperature data, a normalized vegetation index, rainfall data, digital elevation model data, soil texture data, soil humidity reanalysis data and ground verification data. And inputting the soil humidity data sequence into a trained soil humidity data missing filling model to obtain a filling data result corresponding to the ESA CCI soil humidity data to be filled, the soil humidity data missing filling model being obtained by carrying out transfer learning training according to a pre-training set and a fine tuning training set. The soil humidity data missing filling model comprises a time convolutional network module, a bidirectional long short-term memory network module, a self-attention mechanism module and an output module.

The invention discloses a surface temperature remote adjustment method and system based on boiler heat supply, and relates to the technical field of temperature adjustment. Similarity comparison is carried out on a thermal field structure description unit constructed at the current moment and a plurality of thermal field structure description units stored in a historical thermal state feature library; screening out a plurality of historical state frames matched with the current thermodynamic state, calculating a comprehensive similarity score between the current thermodynamic state and each candidate historical state frame, and selecting the historical state frame with the maximum comprehensive similarity score as an optimal matching reference state of the current thermodynamic state; and based on the historical heat supply parameters corresponding to the optimal matching reference state, the current actual environment change and the real-time thermal demand difference are combined, and a current heat supply adjustment strategy is deduced through an adaptive parameter compensation algorithm. According to the adjusting system, through multi-modal data fusion and intelligent analysis, the accuracy and self-adaptability of boiler heat supply adjustment are remarkably improved.

The application provides a loess hilly vegetation disease and pest remote sensing monitoring and evaluation method and device, relates to the technical field of remote sensing monitoring and evaluation methods, and comprises the following steps: calculating the coverage of vegetation by using a double threshold plane method, taking the coverage of vegetation of each grid area as a correction term of ground surface temperature; constructing a temperature difference anomaly index of each grid area; based on the temperature difference anomaly index and transpiration efficiency index of each grid area, calculating the transpiration efficiency index of each grid area by using a vegetation temperature difference method, constructing a vegetation classification model by using a logistic regression method, and classifying each grid area according to a preset threshold value to distinguish a risk grid area and a normal grid area. A prediction model is constructed through the statistical relationship between the vegetation index and the ground surface temperature, the temperature difference anomaly index is quantified, early stress signals of vegetation that are difficult to find can be recognized, the transpiration efficiency is introduced to comprehensively evaluate the water utilization of vegetation, and through a dynamic threshold value and a statistical model, potential risk grids can be recognized before the outbreak of diseases and pests.

The application belongs to the technical field of data processing, and discloses a Mars rover non-contact passability prediction method and system based on thermal inertia, which comprises the following steps: obtaining the ground temperature time sequence and environmental parameters of a target area; constructing a thermal inertia estimation model, inputting the ground temperature time sequence and environmental parameters into the thermal inertia estimation model, and obtaining the thermal inertia estimation value of the soil; constructing a thermal inertia and passability index relationship model, inputting the thermal inertia estimation value of the soil into the thermal inertia and passability index relationship model, and outputting a predicted passability index; determining the passability state level according to the predicted passability index, and generating a navigation control suggestion, so that the Mars rover passes the target area according to the navigation control suggestion of the Mars rover. The application can effectively improve the evaluation accuracy of the Mars rover passing the target area by extracting the thermal inertia estimation value of the soil of the target area to predict the passability index of the Mars rover, and ensures the driving safety of the Mars rover.

This invention relates to the field of natural gas pipeline safety treatment technology, and provides a method, apparatus, electronic device, and storage medium for obtaining frost heave in permafrost areas. The method includes: determining a surface temperature function; determining a constant temperature at a first depth below the surface; constructing a finite element model of the permafrost region calculation area based on the surface temperature function, the first depth, and the constant temperature; applying boundary conditions to the finite element model to obtain the time it takes for a freezing front to reach the lower edge of each grid layer in an M-layer grid from the surface down within the time range of the surface temperature function, as well as the temperature gradient at the location of the freezing front; and determining the frost heave based on the time and the temperature gradient. This method enables rapid and accurate determination of frost heave, providing fundamental data for the safety assessment of buried pipelines.

The invention provides a method, a device and equipment for predicting influence of marsh vegetation change on surface temperature, and belongs to the technical field of ecological remote sensing and climate effect evaluation. The method comprises the following steps: firstly, determining vegetation pixel distribution as a research area range in an unchanged marsh wetland distribution range; a year-by-year and multi-year average growth season data set is constructed through a maximum value synthesis and arithmetic mean method; in the grid units, the pixels are divided into a high value group and a low value group according to the multi-year average growth season leaf area indexes, the difference value between the multi-year average growth season leaf area indexes of all the pixels in the high value group and the low value group and the average surface temperature value is calculated, and then the surface temperature change degree caused by the marsh wetland vegetation coverage change is quantified; and finally, realizing accurate prediction of future surface temperature influence in combination with a vegetation change trend on a pixel scale.

The invention discloses a stationary satellite surface emissivity collaborative inversion method based on background field reconstruction, and belongs to the technical field of satellite remote sensing information processing, and the method comprises the steps: constructing a background field of surface temperature and atmospheric temperature space structure collaborative constraint, employing a three-dimensional variational assimilation cost function to assimilate the actually measured surface temperature of a surface meteorological observation station, and calculating the surface emissivity of a stationary satellite. The obtained surface temperature analysis field is used as a surface temperature initial guess field for inverting surface emissivity by a one-bit variation inversion cost function; generating a ground surface emissivity background field by using the ground surface emissivity in the ground surface element historical data set, and constructing a ground surface item background error covariance matrix capable of representing a coupling relationship between the ground surface emissivity and the ground surface temperature based on the ground surface element historical data set so as to construct a one-dimensional variation inversion cost function; and the inversion of the surface emissivity can be realized by combining the satellite observation brightness temperature of the clear sky observation pixel observed by the infrared window area channel of the stationary orbit radiation imager, so that the inversion level of the surface emissivity is improved.

The invention relates to an urban forest cooling function baseline construction and attenuation recovery evaluation method and system. The method comprises the following steps: acquiring day-by-day meteorological data of a research area to identify starting and ending dates of an extreme high temperature event; acquiring urban forest coverage distribution information in the research area and near-surface air temperature data or surface temperature data in a first date range, and calculating urban forest cooling efficiency data of each date in the first date range; calculating statistical characteristics of the urban forest cooling efficiency data of all dates of the beforehand reference period; determining the maximum attenuation value and date of the cooling efficiency during the extreme high-temperature event; and calculating the statistical characteristics of the urban forest cooling efficiency data of each sliding window by using the sliding windows, and calculating the recovery time and rate of urban forest cooling efficiency attenuation according to the baseline and a preset discrimination condition. It is ensured that attenuation is caused by the extreme high-temperature event, and the attenuation degree and the recovery process of the cooling function under the influence of the extreme high-temperature event are quantified.

The invention relates to a construction site polluted soil treatment system and method, and belongs to the technical field of pollution treatment. The construction site contaminated soil treatment system comprises a heating well, a recovery treatment device, an extraction well, a vacuum generation device, a heat insulation layer, a lifting device, a sensor group and a control module. The heating well is arranged under the ground of a polluted area; the extraction well comprises a first section arranged under the ground of the polluted area and a second section exposed out of the ground; the heat insulation layer covers the ground of the polluted area; the sensor group detects the surface temperature of each position in the polluted area; the control module compares and determines the position with the highest surface temperature as a high-concentration point according to the surface temperature of each position; and the lifting device is controlled to lift the heat insulation layer covering the area between the high-concentration point and the second section, so that a flow channel is formed between the lifted heat insulation layer and the ground. According to the construction site polluted soil treatment system, directional flow guide can be achieved, and high-concentration airflow can be obtained.

The embodiment of the invention provides a soil moisture inversion method and device based on ZY1F satellite multi-load feature fusion, and is applied to the technical field of remote sensing information processing. The method comprises the following steps: acquiring ZY1F satellite multi-load data including AHSI hyperspectral data, VNIC multispectral data and IRS thermal infrared data in a target area; the method comprises the following steps: carrying out collaborative preprocessing on ZY1F satellite multi-load data to generate preprocessed VNIC fusion data, AHSI surface reflectance data and surface temperature data, and respectively carrying out feature extraction to generate a VNIC feature set, an AHSI feature set and an IRS feature set; carrying out feature set scale fusion and optimization processing on the feature set to generate a discriminative feature set; and inputting the discriminative feature set into a pre-constructed soil moisture inversion model, and outputting a soil moisture inversion product. In this way, cross-load feature importance screening and self-adaptive optimization can be carried out, and therefore high-precision soil moisture inversion is achieved for different earth surfaces and time sequences.

The application relates to the technical field of intelligent sensors, and discloses a method and system for detecting appearance defects of a covered soil type liquefied hydrocarbon storage tank. The method comprises the following steps: acquiring ground surface temperature distribution data above a soil layer, generating an initial temperature sequence and separating a medium-high frequency disturbance component, determining a soil heat capacity delay effect parameter and correcting the temperature sequence; a super-temperature difference threshold value is used to strip the soil thermal physical influence to obtain a pure thermal anomaly signal; a thermal distribution law is restored and mapped to a three-dimensional coordinate system of the storage tank to determine a preliminary defect boundary; a gradient is calculated to accurately locate a corrosion layer damage position, heat insulation attribute data and a fire risk assessment model are fused to generate an early warning report containing a defect position, a risk level and a processing suggestion. The method can realize accurate and efficient detection of appearance defects of the storage tank and meet the high-precision and continuity requirements of safety monitoring.

The application discloses a spring tea low-temperature frost monitoring and disaster early warning method, which comprises the following steps: S1, obtaining the ground surface temperature, air humidity and air temperature at the sampling points distributed in a tea garden; S2, calculating the canopy temperature at each sampling point; S3, carrying out gridization on the tea garden, and obtaining the canopy temperature of each grid point by adopting an inverse distance weighted interpolation algorithm based on the canopy temperature of each sampling point; S4, calculating the temperature mean value of all the canopy temperatures, and judging whether the temperature mean value is greater than a preset mean value; if yes, returning to the step S1 after a preset time length, otherwise, entering the step S5; S5, calculating the temperature drop speed according to a plurality of continuous temperature mean values; S6, judging whether the temperature drop speed is less than a preset threshold value; if yes, starting a film covering device and an anti-frost fan; otherwise, entering the step S7; S7, starting the film covering device and the anti-frost fan, and switching the inlet end of a drip irrigation pipe to be communicated with a hot air heating system, and the hot air is introduced into the ground surface of the tea garden.

The application provides a method, device and equipment for evaluating spatial thermal effect under heat exposure, and relates to the technical field of geographic environment data processing. The method comprises the following steps: acquiring green infrastructure patches in a target region; performing spatial feature analysis on the green infrastructure patches to obtain a cooling supply index under different scenarios; acquiring population data and thermal environment data in the target region, obtaining a target model according to the population data and the thermal environment data, and obtaining population data with a second spatial resolution through the target model; obtaining a thermal risk index under different scenarios according to the population data with the second spatial resolution and surface temperature data; and evaluating the heat balance state of the target region according to the cooling supply index and the thermal risk index, identifying a spatial region of a target category, and obtaining a spatial thermal effect evaluation result. The scheme of the application evaluates the heat balance state of the target region, quantifies regional losses caused by high temperature, and provides targeted spatial reconstruction strategies.

The present application belongs to the technical field of surface water heat flux inversion, in particular to a multi-temporal surface water heat flux collaborative inversion method, device and medium. The method comprises: calculating the change rate of surface radiation with vegetation coverage by using multi-temporal remote sensing surface temperature; realizing multi-temporal remote sensing surface temperature collaborative decomposition; solving the joint balance equation of multi-temporal water heat flux and its components; and inverting multi-temporal surface sensible heat flux, water heat flux and its components. The present application realizes multi-temporal surface temperature joint decomposition based on surface temperature and vegetation coverage time series information, thereby proposing a new idea of multi-temporal surface water heat flux joint cutting sharing reference temperature, establishing multi-temporal balance equation considering surface water heat flux and its components, overcoming the deficiency that current remote sensing model is only suitable for single temporal surface water heat flux inversion, improving the efficiency of surface water heat flux remote sensing estimation, and providing technical services for climate change, agricultural production, ecological construction, water resources management and the like.

The invention relates to the technical field of freezing ring science, and provides a near-surface icing risk dynamic assessment method for a complex mountainous area, and the method comprises the steps: introducing a radiation terrain factor, an accumulated snow albedo inhibition mechanism, and air cooling correction for a rasterized weather and surface temperature input field, and constructing an energy index; integrating rainfall, snow melting, humidity, wettability and other elements to obtain a humidity index; and introducing a persistent background index of an annual / seasonal scale as a background enhancement factor, thereby integrating the energy index, the humidity index, the background enhancement factor and the icing phase state indication to obtain a corresponding icing risk score. Therefore, a systematic process framework from data preprocessing, physical mechanism diagnosis and hydrological process constraint to risk comprehensive assessment can be provided, and the risk of near-surface icing in a complex mountainous area can be assessed efficiently and accurately.

The invention discloses an urban land surface coverage classification system based on a multispectral remote sensing technology, and relates to the technical field of spectral spatial data calculation. The system obtains land surface temperature data of a target area and a sub-area and calculates the change rate difference of the land surface temperature data; carrying out first-level correction on the initial contribution degree by utilizing a material thermal tuning coefficient; and performing second-level space coupling correction according to the correlation coefficient of the temperature change of the marked sub-region and the adjacent region, and finally generating an accurate urban surface heat contribution report. According to the method, the transformation of the urban thermal environment contribution from static recognition to dynamic quantitative evaluation is realized, and the accuracy, fineness and practical value of an evaluation result are remarkably improved. The technical problem that the spatial correlation dynamic evaluation adjustment accuracy of urban surface classification thermal contribution is insufficient is solved.

The present application provides a kind of shallow coal seam hidden fire source full field monitoring and early warning method and system, belong to coal spontaneous combustion fire monitoring and early warning technical field, comprising: S1: obtain thermal infrared image and visible light image data;S2: eliminate redundant thermal imaging frame and fuzzy thermal imaging frame;S3: get preliminary ground temperature field distribution;S4: distinguish open fire source and suspicious area, and mark position;S5: obtain the ground temperature gradient distribution and indicating gas concentration data of suspicious area, obtain the ground temperature data, underground temperature data, indicating gas data and radioactive radon content data escaping from detection hole;S6: establish the identification index of hidden fire source;S7: establish hidden fire source grading risk standard;S8: output early warning result.This method realizes full-time, full field, three-dimensional monitoring, improves accuracy and reliability, realizes intelligent grading early warning and decision support, enhances environmental adaptability and automation level.

The invention discloses an urban heat island area and heat source point identification method and system, and the method comprises the steps: obtaining multi-source remote sensing data at the same transit time, carrying out the preprocessing of the multi-source remote sensing data, and obtaining the map auxiliary data of a research area; key parameter inversion is carried out on the preprocessed multi-source remote sensing data, wherein the key parameters comprise land surface temperature, vegetation indexes and impervious surface information; according to the inversed surface temperature, vegetation index and impervious surface information, calculating heat island intensity indexes, including global heat island intensity based on suburban reference temperature and local heat island intensity based on distance weighted neighborhood temperature; and carrying out heat island area division based on the global heat island intensity, and identifying a microscopic heat source point based on the local heat island intensity. According to the method, a complete technical chain of global-local collaborative heat island identification is constructed, and the defect that only'districts' can be identified and'point sources' are difficult to identify in previous researches is overcome.