99 results about "Thermal infrared remote sensing" patented technology

The invention discloses a method for building a mountainous area surface temperature base line and application, and relates to the measurement and application of mountainous area surface temperature base lines. A transient temperature field distributed continuously in MODIS thermal infrared remote sensing image inversion spaces is combined with longitude and latitude raster data to build the annual average temperature linear estimation model of a weather station as the calibration model of the transient surface temperature field. The model corrects the transient temperature field to obtain the mountainous area surface temperature base line. In YunnanProvince with the mountain landform as the main landform, the temperature base line with a 90m*90m grid as a unit is built, the temperature distribution characteristics and rules of the area are reflected, and the average temperature base line value of a 90m*90m land parcel can be found out in a quantitative mode. The temperature base line is used as basic data to be combined with an expert scoring method to respectively build a Yunnan Province pine wilt disease occurrence risk pre-warning model and a Yunnan Province forest fire danger long-term forecast model.

The invention discloses a remote-sensing crop disease identification method based on time phase and spectrum information and a habitat condition. Multi-time-phase visible light-near infrared and thermal-infrared remote sensing images in a study area within a monitoring period are obtained and pretreatment is carried out on the images; with the remote sensing images after pretreatment, planting information of target crops is extracted by combining a certain kind of classification algorithm; and according to the visible light-near infrared and thermal-infrared remote sensing images, habitat information of disease monitoring is obtained, a disease area and a disease type of the target crops in the study area are determined by combining the time phase information of the target crops and the obtained habitat information, and severity of the disease is determined by using the spectrum information based on the determined disease area and disease type. According to the technical scheme, the remote sensing diagnosis precision of the crop disease can be improved effectively; and a reverse identification problem of remote sensing crop disease monitoring can be solved to a certain extent.

The invention discloses a method and system of thermal infrared remote sensing image super-resolution reconstruction based on a MAP algorithm, the method and system comprises the following steps: obtaining a segment of sequence thermal infrared band remote sensing images, wherein the sequence images comprise at least two frames of images; completing rectification by using the automatic extraction and matching based on a high precision automatic rectification method of angular point characteristics; achieving the super-resolution reconstruction of the sequence images by using the MAP algorithm, and putting forward an adaptive selection method of an edge penalty function threshold; carrying out application-oriented quality evaluation on target resolution images after reconstruction. According to the method and system of the thermal infrared remote sensing image super-resolution reconstruction based on the MAP algorithm, the high precision automatic rectification among images can be achieved, parameter threshold values can be selected adaptively, the interference of human factors can be reduced, the super-resolution reconstruction of real time can be achieved, and therefore the problems that thermal infrared remote sensing image resolution is low, a reconstruction method cannot achieve automation and is influenced by human factors seriously, speed is not high enough, reconstruction quality cannot be objectively and authentically evaluated in the prior art are solved.

The invention discloses a method of acquiring all-weather evapotranspiration by combining remote sensing and meteorological data, which comprises the following steps: remote sensing data are acquired; meteorological data are acquired; the CLDAS (China Meteorological Administration Land Data Assimilation System) data grid position to which each MODIS (Moderate Resolution Imaging Spectroradiometer) remote sensing pixel belongs is calculated for longitude and latitude matching; MODIS remote sensing pixels are traversed, whether a MODIS land surface temperature pixel contains a cloud is judged, and according to a judgment result, evapotranspiration of an MODIS cloud pixel and evapotranspiration of an MODIS cloudless pixel are estimated. The existing optical and thermal infrared remote sensing data are made full use of, the grid meteorological data are used, the defect that evapotranspiration can not be inversed in a cloud condition by purely using remote sensing data can be remedied, and all-weather evapotranspiration data can be provided.

The invention discloses a method for inversing the air temperature of a surface layer based on thermal infrared remote sensing. The method comprises the following steps of: (1) determining a fundamental form of a surface layer air temperature remote sensing inversion model; (2) establishing the surface layer air temperature remote sensing inversion model; (3) basing on different surface types of air temperature remote sensing inversion models; and (4) analyzing by using the scale effect of the remote sensing inversion model to obtain an optimal air temperature remote sensing inversion model. A spatial distribution graph of the near-surface layer air temperature can be quickly and accurately calculated by the method. Because the model is established by a regression analysis method in consideration of a surface energy balance process, the method has the advantages of both a theoretical model and a statistical model, high accuracy and high practicability.

The invention relates to a superglacial moraine covering type glacier identification method based on optical and thermal infrared remote sensing images, and belongs to the field of remote sensing geoscience application. According to the method, the thermal infrared wave band and the optical wave band of Landsat TM / ETM and remote sensing images are utilized, the data of a DEM (dynamic effect model) and the like is combined for carrying out identification on the superglacial moraine covering type glacier, firstly, the topical wave band of the TM / ETM images is subjected to atmosphere radiation correction and topography radiation correction, the thermal infrared wave band is used for carrying out ground surface temperature inversion, in addition, the normalization is carried out, then, the illumination region and the shade region are distinguished, and finally, a maximum likelihood method is utilized for respectively classifying the illumination region and the shade region of the images to obtain the types of ice, superglacial moraine covering type glacier, ice and rock debris mixed regions, shade, rock and the like. Compared with a traditional method, the superglacial moraine covering type glacier identification has the advantages that the thermal infrared waveband is introduced, the identification on the superglacial moraine covering type glacier is more accurate and efficient, and the results obtained by adopting the method provided by the invention are more reasonable in the aspect of data space resolution ratio resampling.

The invention discloses an all-weather surface temperature generation method and device based on machine learning. The method comprises: extracting an MODIS data set subjected to remote sensing inversion through an MODIS tool MRT; combining static meteorological satellite data with DEM topographic data of the ALOS satellite, and estimating and obtaining surface incident solar radiation; performingspatial aggregation on data sets with the same spatial scale, and taking the data sets and the MODIS data set as a machine learning training data set; constructing a surface temperature relation model through a random forest model; estimating the real temperature of the earth surface with the cloud coverage pixels; and combining the real earth surface temperature of the cloud-covered pixel with the data set of the cloudless-covered pixel to generate the all-weather earth surface temperature. According to the method, the problems that current thermal infrared remote sensing is easily influenced by cloud and mist, and a large number of blank value-lacking areas exist in surface temperature products are solved, cloud condition surface temperature estimation is achieved, and an important basis is provided for all-weather surface temperature product generation.

The invention discloses a remote sensing surface temperature spatial downscaling method based on normalized desert indexes. The method comprises the following steps: a, acquiring a multi-spectrum andthermal infrared remote sensing image which covers the range of a research area under a sunny condition, and preprocessing; b, upscaling a multi-spectral reflectivity image and a thermal infrared image to the same low resolution through a polymerization method, and constructing a new drought index according to the multi-spectral reflectivity image to represent the desert surface; c, carrying out temperature inversion on the preprocessed thermal infrared remote sensing image to obtain the surface temperature in the research area; d, taking a novel drought index, vegetation index, building indexand water body index as scale factors, establishing an earth surface temperature downscaling model with a random forest regression algorithm, and obtaining a high-resolution earth surface temperatureimage of the research area through the model; e, carrying out precision evaluation on the dimension reduction result. The method is beneficial for improving the dimension reduction precision in the desert area.

The invention discloses a remote sensing model method for regional vegetation transpiration and soil evaporation inversion based on thermal infrared remote sensing. The remote sensing model method comprises the steps of 1, collecting and spatializing meteorological radiation data of a research area; 2, acquiring optical and thermal infrared remote sensing data; 3, preprocessing the optical remotesensing data; 4, conducting thermal infrared remote sensing data preprocessing and surface temperature inversion; 5, carrying out inversion calculation of surface biophysical parameters; 6, performingnight surface temperature downscaling calculation; 7, calculating the surface flux based on a single-layer remote sensing evapotranspiration model with a physical mechanism; 8, carrying out sensitiveheat flux cutting calculation based on a double-temperature-difference model; 9, calculating latent heat flux of vegetation and soil components; and 10, performing daily expansion calculation of vegetation transpiration and soil evaporation. According to the method, the problems of high difficulty and uncertainty of regional vegetation transpiration and soil evaporation inversion based on the surface temperature at present are solved.

The invention provides a method for monitoring the dynamic change of the urban heat island intensity. According to the method, a processing and analysis technology of a thermal infrared remote sensingimage and a high-resolution remote sensing image is utilized, a qualitative or quantitative relation among the change of the heat island intensity of a target area, the land coverage change and the landscape indexes is obtained through multi-data image processing and change analysis, so that the understanding on the aspects such as the change of the heat island intensity pattern caused by land utilization transformation in the processes of urban construction, transformation and renovation can be conveniently studied, and a reference is provided for implementation of the policy.

The invention relates to an SST inversion method and system based on Landsat 8 data. The method comprises that Landsat 8 optical and thermal-infrared remote sensing images and corresponding atmospheric contour data are read; on the basis of water-body and seawater emissivity data and a spectral response function of a Landsat 8 TIRS (Thermal Infrared Sensor), the atmospheric contour is used for driving, and channel brightness temperatures in the aerosphere top of two channels of the TIRS under different combined conditions of atmospheric conditions, SSTs and emissivities are simulated; and the obtained total atmospheric column water vapor content is used to divide the atmospheric column water vapor content into intervals, a split-window algorithm is used to construct SST inversion algorithms of the different water vapor content intervals, the SST is calculated, and a result is output. The system comprises a remote-sensing image reading module, an atmospheric water vapor data reading data, a data processing module and an SST inversion module. The system and method can be used to obtain high-precision SST.

The invention discloses a surface temperature multi-channel thermal infrared remote sensing inversion method. The method comprises the overall steps of acquiring the satellite observation brightness temperatures of N channels; arranging the satellite observation brightness temperatures of the N channels to obtain an N * (N-1) group of channel arrangement consisting of two different channel satellite observation brightness temperatures; selecting M groups from the N * (N-1) groups of channel arrangements, and obtaining the ground observation brightness temperature of M channels by applying an SW algorithm; collecting all available atmosphere information, and estimating atmosphere downlink radiance of the M channels; and based on the obtained ground observation brightness temperatures of theM channels and the estimated atmosphere downlink radiation brightness of the M channels, performing inversion by using a TES algorithm to obtain a final surface temperature and emissivity. Accordingto the surface temperature multi-channel thermal infrared remote sensing inversion method without any auxiliary information provided by the invention, the surface temperature and the emissivity can beobtained through inversion from multi-channel thermal infrared satellite remote sensing observation data at the same time, and the limitation of priori knowledge precision is avoided.

The invention discloses an agricultural drought remote sensing monitoring method, which comprises the following steps: 1) calculating enhanced vegetation index and land surface temperature according to surface reflectance and thermal infrared remote sensing images; 2) constructing an ETVDI model through the surface temperature and the enhanced vegetation index calculation result, and obtaining maximum value and minimum value of the surface temperature under the same enhanced vegetation index value and the number of pixel points at the points of same surface temperature values corresponding to different enhanced vegetation index values; and 3) carrying out polynomial fitting on the maximum value and minimum value corresponding to the same enhanced vegetation index value to obtain wet and dry boundary equations in the ETVDI model, and obtaining fitting parameters. The method overcomes the defect that a conventional TVDI model has vegetation index saturation easily in a dense vegetation area and the defect of uncertainty of wet and dry boundary equation fitting, thereby improving fitting precision; precision is higher in the expression aspect of temporal and spatial development of the drought; and the method can reflect the process of drought growing, development and elimination more truly, and provides reference for early warning and monitoring of the agricultural drought.

The invention provides a thermal effect quantitative evaluation method and system based on the surface type. comprise the following steps: acquiring thermal infrared remote sensing image data, and inverting the actual surface temperature of a to-be-measured area; taking reflectivity data of visible light, near infrared and other wavebands as a reference image, and carrying out panchromatic multispectral waveband fusion on the reference image to obtain a fused image; carrying out surface classification, and determining components and grades of the surface classification; based on the elastic network regression model, obtaining regression coefficients of different surface types to the surface temperature; determining the influence of the components of the surface type on the regional heat effect; and determining the theoretical average surface temperature of different surface types under each component level and the influence of the spatial pattern on the regional heat effect. Accordingto the embodiment, the optimized elastic network regression model is introduced, and the influence of the surface type components on the LST is stripped from the influence of the surface type space structure on the LST, so that the quantitative evaluation of the surface main type heat effect is realized, and the evaluation accuracy is effectively improved.

The invention discloses a method for obtaining field evapotranspiration of field scale, comprising the following steps: S1. space registration is carried out to thermal infrared remote sensing data of original spatial resolution and visible light remote sensing data of the original spatial resolution; S2. sub-pixel temperature is calculated by utilizing the thermal infrared remote sensing data and the visible light remote sensing data whichare treated with space registration; S3. field parameters including albedo, specific emittance and vegetation coverage are calculated by utilizing the visible light remote sensing data of the original spatial resolution; S4. the field net radiation flux is calculated according to the albedo, the specific emittance and the sub-pixel temperature; S5. soil heat flux is calculated by utilizing the field net radiation flux and the vegetation coverage; and S6. the field sensible heat flux H is calculated, and the field evapotranspiration of the field scale can be calculated according to the field sensible heat flux, the field net radiation flux, the soil heat flux and field energy equilibrium equation. By adopting the method in the invention, the field evapotranspiration of the field scale can be obtained.

The invention belongs to the technical field of remote sensing application, and particularly relates to a method for converting microwave remote sensing surface temperature to thermal infrared remote sensing land surface temperature. A physical method suitable for a bare-ground area is provided based on a soil heat conduction equation. The method comprises the steps of data preprocessing; GLDAS data calibration; equivalent temperature generation; conversion from microwave remote sensing surface temperature to thermal infrared remote sensing land surface temperature, wherein land surface temperature which has the same physical significance as thermal infrared remote sensing land surface temperature is generated through passive microwave remote sensing data. The method can be universally applied to existing passive microwave remote sensing inversion land surface temperature algorithms. By the adoption of the method, the precision of the algorithms in inversion of bare-ground area surface temperature is improved.

The invention provides an all-weather surface temperature generation method integrating thermal infrared and reanalysis data, which is realized on the basis of random forest integrated thermal infrared remote sensing and reanalysis data. The method specifically comprises the following steps: performing data preprocessing and space-time matching; implementing a time algorithm; implementing a spacealgorithm; and generating the final 1km all-weather surface temperature. According to the invention, reanalysis data is introduced, a long surface temperature and related observation data can be provided, the data is integrated with thermal infrared satellite remote sensing to obtain all-weather surface temperature with long time sequence and high temporal-spatial resolution. The obtained surfacetemperature has good consistency with a traditional thermal infrared satellite remote sensing surface temperature product, and through the inspection of the actually measured surface temperature, theprecision is within an acceptable range, the image quality is higher, more space detail information of the surface temperature can be displayed, and the overall quality and precision are superior to those of a method for integrating thermal infrared satellite remote sensing data and passive microwave data.

The land surface temperature is an important parameter of the physical process of interaction between the earth and the atmosphere and is widely applied to the research of hydrology, meteorology, global carbon balance and global change. The relationship between the radiation brightness of two thermal infrared channels is directly established to replace the simplified Planck function for solving a radiation transmission equation set, an atmospheric parameter (the specific value of atmospheric downward radiation to atmospheric upward radiation) is also introduced to enhance the accuracy of the simplified radiation transmission equation, a split window algorithm based on the radiation brightness (RBSWA) is put forward and the algorithm is applied to MODIS data land surface temperature retrieval. Compared with the conventional split window algorithm based on the brightness temperature, the land surface temperature retrieval accuracy of the RBSWA is enhanced for about 0.5K. The principle of the method is also suitable for other thermal infrared remote sensing data.

The invention discloses a method for detecting a marine moving target of a thermal infrared remote sensing image based on multi-feature fusion. The method comprises the following steps of carrying out sea-land segmentation on a thermal infrared image to obtain a sea area image; utilizing a priori segmentation parameter to carry out multi-scale segmentation on the sea area image to obtain an object; extracting brightness and geometrical characteristics of the object obtained by segmentation; and carrying out decision tree classification on a segmentation object through corresponding classification rules which are obtained by respectively carrying out contrast training on the obtained brightness and the geometrical characteristics of the segmentation object in order to realize detection of the marine moving target. The method utilizes the thermal infrared remote sensing image as a data source, so that the defects of failure of a visible / near-infrared multispectral image at night, difficulty in visual interpretation of an SAR image, complicated processing steps and the like in the existing method can be made up to be beneficial to detection of a detection result, so that the accuracy of information is further improved; the obtained temperature information is extracted based on the marine moving target obtained by detection to be beneficial to judgement of state of the marine moving target.

The invention provides a farmland evapotranspiration estimation method and system. The farmland evapotranspiration estimation method comprises S1, obtaining remote sensing image data and meteorological data of farmland; S2, calculating latent heat flux, net radiation flux and soil heat flux based on the remote sensing image data and the meteorological data of the farmland; and S3, estimating the evapotranspiration value based on the latent heat flux, the net radiation flux and the soil heat flux. With respect to the farmland evapotranspiration estimation method and system, by fully combining the meteorological data, optical remote sensing and thermal infrared remote sensing, the physical basis is clear, the spatial resolution is high, and the reliability of the estimation result is higher.

The invention discloses a method of satellite thermal-infrared remote-sensing in-orbit scaling and satellite remote-sensing temperature product onsite verification, and the method is realized via synchronous skin temperature and surface temperature measuring devices of the water body. The method comprises the steps that 1) in a water area corresponding to certain pixel in a satellite remote-sensing image, the synchronous skin temperature and surface temperature measuring devices of the water body are arranged into a grid-shaped observation array of equal interval, and a 3D temperature actually measured value near a water surface and atmosphere interface is obtained; 2) different 3D temperature actually measured values are counted and calculated to obtain the average skin temperature and the average surface temperature of the water area; and 3) a MODTRAN model or an LBLRSTM model is used to simulate infrared radiation transmission between the sea surface and a satellite, and in-orbit scaling is carried out on a satellite thermal infrared sensor synchronous with onsite temperature measurement, or onsite verification is carried out on a satellite remote sensing temperature product. Thus, the method can be used to overcome difficulties of space mismatch and time asynchronism between actual measurement data and remote sensing data in satellite thermal-infrared remote-sensing in-orbit scaling and satellite remote-sensing temperature product onsite verification.

The invention discloses an extraction method for offshore industrial warm discharge water based on aerial remote sensing. The method comprises the following concrete steps: 1) calculating atmospheric parameters by utilizing MODTRAN5.3 software, inputting the atmospheric parameters to a simplified form of an atmospheric radiative transfer equation and subjecting aerial thermal infrared remote sensing data to sea-surface temperature inversion to transform a radiation brightness temperature of a pixel into a temperature; 2) comparing the sea-surface temperature obtained by inversion in the step 1) with a synchronously-measured ground temperature, calculating an error of temperature inversion results, and correcting the results by utilizing the synchronously-measured ground temperature if the error is greater than 0.5 K; 3) extracting a temperature-rising area by using an image segmentation technology; and 4) simulating a sea-surface natural temperature in the temperature-rising area based on a sea-surface temperature in a non-temperature-rising area, subtracting the simulated sea-surface natural temperature in the temperature-rising area with the sea-surface temperature in the same area so as to obtain the temperature-rising value of the temperature-rising area. The extraction method provided by the invention has the following advantages: inversion accuracy is high; and the needs of the offshore industrial warm discharge water for temporal resolution and spatial resolution are met.

Industrial thermal pollution seriously harms urban ecological environment quality, while great manpower and material resources need to be consumed for field investigation of factories, and there is noiron and steel plant extraction method and process based on remote sensing means at present. Aiming at the problems, the invention discloses an iron and steel plant remote sensing extraction method based on industrial production activity characteristics. The method comprises the following steps: 1) carrying out Landsat8 remote sensing image radiation correction and surface temperature remote sensing inversion; 2) counting a surface temperature value distribution condition of a whole scene thermal infrared image, and determining a final threshold value of a first 4%-5% high temperature interval in the image; 3) carrying out I-type thermal anomaly identification: extracting and vectorizing a high-temperature region of the first 4%-5% temperature interval in the whole scene thermal infraredremote sensing image; 4) calculating an average value and a standard deviation according to the surface temperature value distribution condition of the whole scene thermal infrared image; 5) carryingout II-type thermal anomaly identification: extracting and vectorizing an abnormal change region of which the temperature change difference value in the same season is greater than a sum of the average value and a half standard deviation (i.e. Value is greater than mu+sigma / 2); and 6) fusing thermal anomaly extraction results, i.e., solving a union set of the I-type thermal anomaly identificationresult and the II-type thermal anomaly identification result to obtain a final thermal anomaly extraction result so as to lock a suspected iron and steel plant in a city.

The embodiment of the invention provides a complex underlying surface water body identification method and a complex underlying surface black and odorous water body prediction method. Spectral difference and temperature difference of water and background information in the target area are fully considered; combining the road information map, the land utilization information map, the multispectralremote sensing image and the thermal infrared remote sensing image of the target area, the water body distribution information in the target area is identified, and information such as asphalt roads,black roofs and combustion traces is excluded from the obtained water body distribution information, so that the identification result is more accurate, and the black and odorous water body is accurately predicted on the basis.

The invention discloses a method for detecting high-temperature thermal abnormality based on thermal infrared remote sensing data. The method comprises the following steps of performing atmosphere correction, so as to obtain the reflection rate of a visible light wave band and the spectrum radiation brightness of a thermal infrared wave band; removing a water body in an image through water body masking; calculating the brightness temperature of each wave band; calculating the thermal abnormality index; extracting the thermal abnormality point; comparing with a high-resolution image, and verifying the accuracy. The method has the advantages that the thermal abnormality point with temperature being 400K or above can be quickly extracted, and the confidence degree about the extracted point capable of determining the existence of the thermal abnormality reaches 90% or above; the index accuracy is high, the operation is simple and rapid, the extracting accuracy is higher at night, and the method can be used for quickly extracting thermal abnormality according to the data at night.

The invention discloses a wheat scab monitoring method based on satellite remote sensing, and belongs to the technical field of remote sensing monitoring, and the method comprises the steps: firstly obtaining the remote sensing data and meteorological rainfall data of a wheat planting region in a predicted year and N years before the predicted year, wherein the remote sensing data comprise multispectral data and thermal infrared remote sensing data; calculating a relative growth vigor index by utilizing the multispectral data; obtaining a normalized surface temperature index by using the multispectral data and the thermal infrared remote sensing data; obtaining a normalized precipitation index by using the meteorological precipitation data; and finally, calculating the wheat scab incidenceindex of the predicted year by utilizing the relative growth vigor index, the normalized earth surface temperature index and the normalized rainfall index. According to the method, the interference of the difference of wheat growth vigor in different areas in large-scale monitoring on the gibberellic disease monitoring model can be well reduced, and the objectivity and practicability of gibberellic disease remote sensing monitoring are improved.

The invention relates to a remote sensing monitoring method and system for a capacity change of an iron and steel enterprise. According to the method provided by the invention, with thermal infrared remote sensing data, inversion of a thermal environment field of an iron and steel enterprise is carried out; thermal abnormal time change characteristics and spatial distribution change characteristics of the iron and steel enterprise are analyzed; and on the basis of the thermal abnormal time change characteristics and spatial distribution change characteristics of the iron and steel enterprise, a capacity change remote sensing monitoring algorithm for an iron and steel enterprise is constructed to monitor the capacity change situation of the iron and steel enterprise. On the basis of the specific thermal environment characteristics of the iron and steel enterprise and a spectral response rule of the iron and steel enterprise at a thermal infrared waveband, precise remote sensing monitoring of the capacity change of the iron and steel enterprise is realized.

The invention discloses a method for inverting topsoil volumetric water content by employing multi-temporal observation data of a geostationary meteorological satellite. The method mainly includes: a soil moisture inversion model is built; the land surface temperature and net surface shortwave radiation are inverted in a quantification manner by employing the data of the geostationary meteorological satellite, dimensionless treatment is performed on the land surface temperature and the net surface shortwave radiation, ellipse fitting is performed on the multi-temporal land surface temperature and the net surface shortwave radiation, an ellipse parameter corresponding to each pixel is obtained, and the parameters are regarded as input data of the soil moisture inversion model; an acquisition method of model coefficients is obtained; and specific requirements of dimensionless treatment are imposed on the land surface temperature and the net surface shortwave radiation. According to the method, the problems caused by the lack of polar orbiting satellite data information of the conventional optical and thermal infrared remote sensing soil moisture inversion method are solved.

The invention discloses a mine and solid waste landfill automatic extraction method and device based on remote sensing data, and belongs to the field of environment monitoring. The method comprises the following steps: acquiring a sub-meter remote sensing image and a thermal infrared remote sensing image, calculating a normalized vegetation index and a specific value building index by using the sub-meter remote sensing image, and extracting a non-vegetation coverage area and a non-building area; inversing the surface temperature by using the thermal infrared remote sensing image, fitting a normal distribution curve based on a surface temperature value, and extracting a high-temperature abnormal region; based on the high-temperature abnormal area extraction result, removing vegetation coverage areas and building areas, and obtaining pattern spot information of mines and solid waste landfills; and establishing a classification model, carrying out secondary classification on the information of the mine and the solid waste landfill, and obtaining the mine and the solid waste landfill through grid vectorization processing. According to the invention, automatic extraction of the mine and the solid waste landfill is realized, the labor cost and the time cost are greatly reduced, the working efficiency is improved, and technical support is provided for environmental pollution source supervision.

The invention belongs to the technical field of ground thermal infrared remote sensing information extraction, and particularly relates to a temperature / emissivity inversion method suitable for groundthermal infrared data. The method comprises the following steps: 1, selecting a to-be-measured sample and a ground thermal infrared data measuring instrument; 2, selecting a sample thermal infrared data measurement environment and time; 3, calculating atmospheric downlink radiant heat infrared radiance data; 4, acquiring thermal infrared radiance data of the sample; 5, selecting a sample temperature distribution range; 6, calculating black body thermal infrared radiance data; 7, calculating emissivity values of the sample at different temperatures; 8, calculating the emissivity curve smoothness of the sample at different temperatures and determining the real temperature; 9, calculating the emissivity value of the sample at the real temperature. The method can accurately invert the groundobject temperature and emissivity information based on the ground thermal infrared remote sensing data, and provides an important technical means for the fields of exploration of uranium, polymetallicand other mineral resources, environmental monitoring, target identification and the like.