522results about How to "Improve inversion accuracy" patented technology

A method is disclosed for determining a position of a wellbore with respect to layer boundaries in earth formations. The method includes projecting a trajectory of the wellbore onto an initial model of the earth formations, selecting a segment of the trajectory and calculating along the segment expected responses of a well logging instrument. Differences between the expected responses and responses measured by the instrument along the segment are determined. The model is adjusted, the expected responses are recalculated and the differences are again determined. These are repeated until the differences fall below a selected threshold. In one embodiment, the trajectory of the wellbore can be adjusted to remain within a selected distance of a selected one of the layer boundaries.

The invention relates to a method for inversing land surface temperature from MODIS data, which can be applied in meteorology, environmental monitoring, land management, agricultural condition monitoring, disaster monitoring and other remote sensing application departments. The method comprises four steps: the first step is to calculate the transmittance of 31st and 32nd wave bands of MODIS through water vapor content of atmosphere. The second step is to calculate the emissivity of the 31st and the 32nd wave bands of the MODIS sensor through vegetation index NDVI. The third step is to simplify a radiation transmission equation. The fourth step is to carry out inversion calculation on the MODIS data and obtain the land surface target object temperature and the emissivity distribution situation, so that the method can be used in meteorological forecasting, environmental monitoring, agricultural condition monitoring, disaster monitoring and other departments.

The invention relates to a multi-scale seismic full-waveform inversion method based on a local adaptive convexification method. The method comprises steps: pre-processing is carried out, a zero value sequence serves as an initial value, and an initial speed model serves as a starting value; direct wave information is intercepted; forward modeling direct waves are obtained; an objective function inverted by a seismic source function is built; a direct wave residual and a direct wave residual back propagation wave field are obtained; an updating gradient and an updating direction of the seismic source function are calculated, and a step length is searched; the high-precision seismic source function obtained through inversion is outputted; attenuation time window processing is carried out; seismic data in the time window are simulated; local convexification processing and separation processing are carried out; a high-frequency component in an observation record is removed; a least square objective function is built, and a wave field residual is obtained; a residual back propagation wave field of the model space is obtained; the model updated gradient is obtained; the model updated direction is calculated, and the step length is searched; a multi-scale seismic full-waveform inversion result is outputted; and a final inversion result is outputted. The method is widely applied in the technical field of seismic exploration.

The invention relates to a constructing method for topographic correction vegetation index, comprising the following steps of: (1) carrying out radiative correction with different degrees according to obtained optical remote sensing image data source; (2) carrying out judgment and processing to nonvegetated dark matters; and (3) carrying out calculation to topographic correction vegetation index (TCVI). The method is adopted to construct the topographic correction vegetation index, thus making up the defect that the existing vegetation index can not eliminate topographic influence and eliminating the dependence to the topographic correction method based on DEM data. The invention can quantitatively and fast reflect the vegetable information of mountain areas only by needing two wave bands of data, namely an infrared wave band and a near-infrared wave band.

The invention discloses a sea fog all-time all-weather inversion method based on multispectral weather satellite information. According to the method, the influence of the diurnal change of sea surface temperature on the fog region identification is considered, a sea surface brightness temperature ambient field (clear sky composite map) (CSCM) is established aiming at the daytime and night respectively and independently according to the diurnal variation characteristic of the sea surface temperature, and a foundation is laid for accurate inversion of dissipation and concentration change in a satellite monitoring sea surface fog region; furthermore, the method aims at typical spectral characteristics of sea fog satellite monitoring at three different time intervals of daytime, night and morning and night, the optimized spectral combination and corresponding algorithm flow are respectively selected, and the all-time accurate identification of a sea surface fog region, a clear sky region and a cloud region is reliably realized.

The invention relates to a method for precisely measuring an earth gravitational field, in particular to a satellite gravity inversion method based on a double-satellite spatial three-dimensional interpolation principle. An earth disturbing potential (obtained by computing an inter-satellite speed of a GRACE satellite K wave band measuring instrument, a satellite orbit position and a satellite orbit speed of a global positioning system (GPS) receiver, a satellite nonconservative force of an accelerometer and a satellite three-dimensional attitude data of a fixed star sensitive device) which is positioned on a gravity double-satellite orbit with a relatively irregular spatial position is interpolated three-dimensionally onto a reference spherical surface with a relatively regular spatial position and uniform grid division, so that the earth gravitational field is precisely and quickly inversed. By the method, satellite gravity inversion precision is high, physical meaning in the resolving process is clear, the computing speed is high, requirements on performance of a computer are low, and the method is sensitive to high-frequency signals in the gravitational field, so that the double-satellite spatial three-dimensional interpolation method is an effective method for resolving the earth gravitational field with high precision and high spatial resolution.

The invention provides a micro-seismic source location and velocity model simultaneous inversion method, and belongs to the field of source locating in micro-seismic monitoring. The method comprises the following steps: (1) picking up the first arrival time of a micro-seismic event; (2) building an initial velocity model based on acoustic logging data, and acquiring the initial source location and origin time of earthquake of the micro-seismic event; (3) calculating the theoretical travel time of the micro-seismic event based on two-point ray tracing, and building a joint tomography equation set; (4) solving the joint tomography equation set, and working out the parameter update amount delta(u), delta(x) and delta(tau); (5) judging whether termination conditions are met, turning to step (6) if the termination conditions are met, or, using the parameter update amount to update the velocity model, the source location and the origin time of earthquake and turning to step (3); and (6) outputting the final velocity model, source location and origin time of earthquake.

The invention discloses a crop biomass inversion method based on a SEBAL-HJ model. The crop biomass inversion method is characterized by comprising the following steps: S1, acquiring HJ-1 CCD, IRS images and elevation data DEM in a research plot, and carrying out geometric fine revision to the images; S2, inversing a land surface albedo, NDVI, SR, land surface emissivity and inversing land surface temperature; S3, calculating net radiation flux according to inversion results in the S2, and further calculating soil heat flux on the basis; S4, calculating sensible heat flux through cyclic reduction; S5, calculating the coefficient of evaporation ratio and obtaining evapotranspiration per day through space-time dimension expansion; S6, inversing fPAR on the basis of vegetative cover indexes NDVI and SR; S7, inversing NPP according to the inversion results of evapotranspiration per day in the step S5 and the inversion results of fPAR in the step S6; and S8, obtaining crop biomass through the accumulation of NPP after space-time reconstruction. According to the invention, the high-precision inversion of crop biomass is achieved, and the amount of calculation is relatively smaller.

The invention discloses a method for inverting a near-surface velocity model by utilizing preliminary waveforms. The method comprises acoustic wave equation-based wave field forward modeling and steepest descent-based waveform inversion technologies, and comprises the following steps of 1, extracting time-domain preliminary waveform records and an initial model; 2, calculating a simulated wave field and a wave field residual by utilizing acoustic wave equation staggered grid finite-difference forward modeling simulation; 3, reversely propagating the wave field residual to obtain a retransmission wave field; 4, calculating a gradient of a target function by utilizing the retransmission wave field and a forward propagation wave field, and calculating an updating step length; 5, updating a speed model; 6, inspecting whether the speed model is consistent with an iteration stopping condition, outputting the speed model if the speed model is consistent with the iteration stopping condition, otherwise returning to the step 2, and continuing iterative updating. According to the method, a wave equation theory-based full-waveform inversion technology is used as reference, and preliminary waves with higher energy and more stable waveforms are used for inversion, so that the multiplicity of solutions of full-waveform inversion is reduced, and the inversion stability and the calculation efficiency are improved; the accuracy of static correction and shallow depth imaging is improved.

The invention provides a forest aboveground biomass inversion method fused with spectrum and texture features and a forest aboveground biomass inversion system fused with the spectrum and texture features. The method comprises the following steps of calculating an aboveground biomass of a research region sample plot so as to obtain a sample plot biomass observation value; performing geometric correction and radiometric correction on high-resolution remote-sensing image panchromatic data and multispectral data; respectively performing statistical regression on the sample plot biomass observation value and a corresponding spectrum feature vegetation index, and selecting a spectrum feature inversion model; extracting various texture feature variables under different windows, respectively performing statistical regression on the sample plot biomass observation value and the corresponding texture feature variables, and selecting a texture feature inversion model; determining a weight through a sensitivity analysis of a spectrum key factor and a texture key factor, constructing a spectrum texture feature combination inversion model of the biomass, and realizing the forest aboveground biomass inversion. The method and the system provided by the invention have the advantages that the spectrum features and the texture features are fused, and the advantages of the spectrum features and the texture features for biomass inversion are fully exerted, so that the quantitative inversion precision of a forest aboveground biomass is effectively improved.

The invention relates to a time-domain airborne electromagnetic method motion noise detection apparatus and an inhibition method. The apparatus comprises an air portion and a ground portion. The air portion comprises a helicopter, air data collection equipment, a transmitting coil, a preamplifier, a z component receiving coil and an attitude sensor. The ground portion comprises GPS ground data collection equipment, a three-component fluxgate and a preamplifier. The ground portion and the air portion realize time synchronization through GPS. Compared to the prior art, by using the apparatus and the method in the invention, the single attitude sensor is used so that an attitude detection function is realized and a detection apparatus amount is reduced; a data size is decreased and a data processing rate is increased; a three-component fluxgate measurement geomagnetic field is used as a background magnetic field so that advantages of high precision, high real-time performance and convenient operation are possessed; the GPS is used to realize time synchronization of data receiving; based on coincident data, working personnel can conveniently carry out on-site data processing and analysis and corresponding compensative measures are used so that a purpose of inhibiting the motion noise is reached.

The invention discloses a remote sensing data-based leaf area indexes (LAI) inversion method for winter wheat in different growth periods. The method comprises the following steps of obtaining LAI actual measurement data; obtaining remote sensing data and performing preprocessing; dividing the whole growth period of the winter wheat into three stages, selecting five vegetation indexes NDVI, EVI, EVI2, RVI and OSAVI to perform LAI inversion of the winter wheat in the whole growth period and the different growth periods, and analyzing a relationship, in unary linear, exponential, logarithmic and power function forms, between the LAI actual measurement data and each vegetation index; comparing different index inversion results of the winter wheat in the different growth periods; and obtaining an optimal index inversion and fitting model of the winter wheat in the different growth periods according to the comparison of the different index inversion results of the winter wheat in the different growth periods. The method shows that GF-1 data has a very good application prospect in crop growth remote sensing research, and the situation that Chinese agricultural remote sensing monitoring depends on foreign data for a long term can be effectively improved.

The invention discloses a gravity multi-interface inversion method. The method comprises the following steps: obtaining information of an observation point, a gravity observation value, an initial model scope, underground medium information, to-be-inversed layer position information, and regularization weights of each model functional portion; performing mesh generation on an underground medium; calculating a gravity effect of each cylindrical body for the observation point after the mesh generation of an initial model, performing accumulation, and obtaining a gravity forward modeling value; according to the gravity observation value and the gravity forward modeling value, calculating a mismatch function F1(x); calculating a total variation function F2(x); calculating a model interface inversion deviation function F3(x); according to calculation results, the regularization weights lambda2 to lambda3 of each model functional portion and the mismatch function F1(x), constructing a target function: F(x)=F1(x)+ lambda2F2(x)+ lambda3F3(x); and enabling the target function to be the smallest by use of an iteration method. Through such a mode, the gravity multi-interface inversion method can have quite good inversion precision and efficiency.

The invention relates to a method for realizing oil-gas detection by applying a long-offset distance transient electromagnetic array method. The method comprises the following steps: firstly, carrying out ATEM (analytical transmission electron microscopy) observation on a detection region to acquire data; selecting measuring points without obvious distortion or negative anomaly of electric field components while an induced polarization field is not stripped, utilizing the ATEM data for inversion, and acquiring a high-resolution lamellar specific resistance model in a detection region; then carrying out ATEM forward operation to obtain transient induced electric field or magnetic field attenuation curves of all the measuring points in the detection region; substracting the electric field or magnetic field component attenuation curve acquired during forward operation by the actually observed ATEM electric field or magnetic field component attenuation curve at the same observation time point to obtain a time domain induced polarization spectrum; applying a time domain induced polarization method for inversion to obtain the polarizability of an underground medium; and carrying out detection and evaluation on an oil-gas reservoir by utilizing the specific resistance and polarizability parameters. According to the invention, the accuracy and reliability of exploration on the oil-gasreservoir by utilizing an electromagnetic method are greatly enhanced, the working efficiency is improved, and the exploration cost is lowered.

The invention provides a method of predicting reservoir fractures based on offset vector tile seismic pre-stack gather data. The reservoir fracture development density and fracture azimuth are directly inverted based on offset vector tile seismic data containing azimuth information. The defects of the conventional narrow-azimuth pre-stack seismic fracture prediction technology, such as low inversion accuracy and low spatial resolution, are overcome. More comprehensive and complete offset and azimuth information can be retained. More suitable seismic data is provided for azimuth anisotropy research. The method is more advantageous to the identification of fault, fracture and reservoir air water variation characteristics.

The invention belongs to the field of wave remote sensing technology, and particularly relates to a method for conducting X wave band navigation radar wave parameter inversion through a band-pass filter based on a novel wave dispersion relation, wherein sea clutter images are obtained through navigation radar so that wave parameter inversion can be conducted. The method comprises the steps that radar image data are collected; radar images are preprocessed; Fourier transform is conducted on an image sequence under a Cartesian coordinate system, so that a three-dimensional wave number frequency image spectrum of the radar images is obtained; wave spectrum information is extracted; wave information inversion is achieved. Influence on the dispersion relation by the ship speed is kept by the filter, the problem that the band pass of a traditional broadband-pass filter is increased along with increase of the movement speed is effectively solved, and therefore filtering can be conducted under the condition that a radar platform is moved along with movement of a ship. In band pass boundary derivation of the novel filter, an approximate value of any quantity is avoided, calculation errors are reduced, influence on the band pass boundary is avoided, band width calculation is more accurate, and wave inversion accuracy is improved.

The invention provides an inversion method for an extinction coefficient of an aerosol based on a Raman-Mie scattering laser radar, comprising the steps of: Step 1: obtaining an echo signal of a Ramanchannel in the Raman-Mie scattering laser radar, and determining an lidar ratio of the aerosol by Ansmann method, that is, obtaining the extinction coefficient and a backscattering coefficient of theaerosol by using Raman method; Step 2: obtaining an echo signal of a Mie channel in the Raman-Mie scattering laser radar, and inverting a distribution profile of the extinction coefficient of the aerosol based on Fernald method; and Step 3: correcting, based on an inversion result of the Raman method in step 1, key parameters required to invert the distribution profile of the extinction coefficient by using the Mie scattering method in step 2, that is, a boundary value of the extinction coefficient of the aerosol, thereby improving the inversion precision of the distribution profile of the extinction coefficient of the Mie scattering channel. According to the inversion method for the extinction coefficient of the aerosol based on the Raman-Mie scattering laser radar provided by the invention, high-precision detection of aerosols is achieved by combining the characteristics of Raman scattering and Mie scattering.

The invention relates to a multi-domain frequency-division parallel multi-scale full-waveform inversion method. A smooth initial model is established by using time-domain empirical mode decomposition full-waveform inversion; a high-precision initial model is established by using frequency-division parallel Laplace-Fourier-domain full-waveform inversion; and then an underground high-precision speed model is established again by using frequency-division parallel frequency-domain multi-scale full-waveform inversion. During the whole process, a dynamic random coding strategy is employed, so that the inversion rate is accelerated and the crosstalk noises inside a super gun can be suppressed. According to the invention, multi-domain combined inversion, frequency-division parallel and dynamic random focus coding strategies are used during the underground speed inversion process. Under the circumstances of low frequency deficiency and poor initial models, the smooth initial model is established by using time-domain empirical mode decomposition full-waveform inversion, so that the full-waveform inversion cycle skipping phenomenon is avoided. And during the inversion process, the master-slave parallel calculation method is used, so that the calculation efficiency of full-waveform inversion is improved substantially and the inversion precision is enhanced.

The invention discloses a gas state quantitative analyzer based on the extended Kalman filtering theory for simultaneous online estimation of concentration and temperature of gas to be detected. The hardware portion is composed of a light source, a receiving system, an optical detection system and a computer, and the software portion is composed of a gas state space model and an extended Kalman filtering portion. Light wave emitted from the light source passes through the gas to be detected and enters the optical detection system through a receiving system, and the optical detection system acquires transmittance corresponding to each wavelength of the light wave and transmits corresponding light intensity spectral data to the computer. The computer constructs a measurement equation based on gas absorption intensity data by gas state analysis software to obtain a gas state equation, thus inversing the concentration and the temperature of the gas by using the extended Kalman filtering algorithm.

The invention discloses an improved water cloud model and a paddy parameter inversion method adopting the model. The canopy heterogeneity and phenological change thereof are considered in the construction of a planting area scene by the water cloud model; the secondary scattering between the plant and the underlying surface is considered in the scattering mechanism analysis process; a quantitative relation between the main scattering mechanism and the plant parameter is established. The model framework is more reasonable and is more suitable for the practical process of the growth and development of the crops, including paddy. The improved water cloud model is applied to the paddy parameter inversion method. On the basis of polarized SAR data, the contributions of different scattering mechanisms and the correlation thereof with different paddy parameters are fully considered. A polarized SAR paddy parameter inversion method considering the canopy heterogeneity and phenological change thereof is developed. According to the method, the inversion accuracy is high, the error is small, the parameters in the early phenological periods of the growth and development of the paddy can be accurately inversed and the monitoring for the growth of the paddy and the estimation for the yield are more true, accurate and reliable.

The embodiment of the invention provides a chlorophyll remote sensing inversion device and a chlorophyll remote sensing inversion method. Based on sensitivity analysis of a spectral characteristic of chlorophyll a, an improved chlorophyll a inversion model is formed, and influence of complex optical property of a nearshore water body on the chlorophyll a is integrally considered; meanwhile, an HICO high spectral image is pre-processed to obtain an image mean value spectrum of an experimental sample region. The constructed chlorophyll a inversion mode is applied to the pre-processed image for chlorophyll a inversion. According to the embodiment of the invention, the inversion precision of the chlorophyll a is hugely increased.

A method for detecting earth surface evapotranspiration based on remote sensing earth surface temperature and vegetation coverage two-stage space comprises the following steps: 1, acquiring earth surface temperature and vegetation coverage by utilizing a remote sensing data product; 2, establishing the earth surface temperature and vegetation coverage two-stage feature space; 3, extracting the temperature of vegetation component and bare soil component by utilizing the earth surface temperature and vegetation coverage two-stage feature space; 4, calculating the evaporation ratio of vegetation and bare soil by combining the earth surface temperature and vegetation coverage two-stage feature space and a Priestley-Taylor formula; 5, calculating the available energy of the vegetation component and the available energy of the bare soil component according to a radiation income and outcome balance equation; 6, calculating the output vegetation evapotranspiration, soil evaporation and earth surface evapotranspiration through a binary pattern of earth surface evapotranspiration.

The invention provides a method and device for establishing a full-waveform inversion model for geophysics parameters. The method comprises following steps: residual values of real wave-fields and initial model observation wave-fields are calculated; by use of the residual values, gradients of an objective function to model parameters are calculated through an adjoint state method; A Hessian matrix is calculated by use of variations of the model parameters and variations of the gradients By use of the gradients and the Hessian matrix, trust region sub-problems are established through performing second-order expansion calculation to the objective function according to Taylor's formula; the trust region sub-problems are solved through a conjugate gradient method to obtain solutions, namely the probe step length of the next iteration, of the trust region sub-problems; updates of the model parameters and trust region radii are performed on the basis of the trust region algorithm to obtain the full-waveform inversion model of geophysics parameters. By use of the method and device, a high fidelity velocity model is obtained.

The invention provides a pre-stack seismic wide angle retrieval method. The pre-stack seismic wide angle retrieval method comprises the following steps: inputting at least three angle stacking seismic data volumes, at least three corresponding wavelets, longitudinal wave speeds, a transverse wave speed and an initial density model; creating a pre-stack retrieval objective function; expanding the taylor series of the pre-stack retrieval objective function; deriving parameters through the matrix form of a Zoeppritz equation to obtain the partial derivatives of a reflection coefficient to the longitudinal wave speeds, the transverse wave speed and the density; according to actual data, decreasing computing amount through matrix partitioning; computing the perturbation of a retrieval parameter; and controlling the convergence of the retrieval objective function through the computed perturbation of the retrieval parameter to obtain a pre-stack retrieval parameter. The pre-stack seismic wide angle retrieval method solves the problems that the approximate conditions of the validity of the Zoeppritz equation are difficult to met and the error is great in the prior art, and has the advantages of wide application range, small error and high retrieval precision.

The invention discloses a backscatter-and-oblique-ionograms-based joint inversion method for ionospheric parameters. The method comprises the following steps of: determining an ionospheric model required by the backscatter detection and oblique detection joint inversion as a quasi-parabolic model; setting parameters of the ionospheric model, and calculating by using the set ionospheric parameters to obtain a simulated backscatter ionogram front edge and a simulated oblique ionogram; adding random errors into the simulated backscatter ionogram front edge and the simulated oblique ionogram, wherein the simulated backscatter ionogram front edge and the simulated oblique ionogram into which the random errors are added serve as the backscatter ionogram front edge and the oblique ionogram for the final inversion; and performing data sampling on the backscatter ionogram front edge and the oblique ionogram which are used for the final inversion and comparing the difference between the inversed result and the set parameters of the ionospheric model to judge the effectiveness of a retrieval algorithm, wherein the sampled data serves as the input of the inversion. By introducing the novel ionospheric joint detection technology and taking detection data, in different forms, of the same detection area as the input of the retrieval algorithm, the precision and stability of the inversion are effectively improved.

The invention relates to a time-domain single frequency waveform travel time inversion method independent of source wavelets. In view of the cycle skip phenomenon in full waveform inversion due to theloss of low-frequency components in seismic data, wave equation travel time inversion is carried out based on time-domain single frequency waveform, and a high-precision initial velocity model is constructed for conventional full waveform inversion, in order to solve the problem of cycle skip and obtain a high-precision full waveform inversion result. The invention aims to reduce the dependence of full waveform inversion on low-frequency components, avoid waveform mismatch caused by inaccurate source wavelets, and provide more technical support for full waveform inversion in practical application. The method greatly alleviates the cycle skip phenomenon in the full waveform inversion process, improves the inversion accuracy, and provides a high-precision initial velocity model for conventional full waveform inversion. The influence brought about by inaccurate source wavelets can be avoided while the problem of cycle skip in full waveform inversion is solved.

The invention relates to an approximation of a DCT and a quantization which are to be applied subsequently to digital data for compression of this digital data. In order to improve the transform, it is proposed to simplify a predetermined transform matrix to require less operations when applied to digital data. In addition, elements of the simplified transform matrix constituting irrational numbers are approximated by rational numbers. These measures are compensated by extending a predetermined quantization to include the operations which were removed in the simplification of the predetermined transform matrix. The included operations are further adjusted to compensate for the approximation of elements of the simplified transform matrix by rational numbers. If the simplified transform matrix and the extended quantization are used as basis for implementation, a fast transform with a good resulting quality can be achieved. An approximation of an IDCT employed in decompression of compressed digital data can be simplified correspondingly.

The invention discloses a CCD spectral image dark current correction method for an imaging spectrometer. The method comprises: an average CCD spectral-dimensional dark pixel response value is used as a corresponding spatial-dimensional average dark current to form an average dark current of an overall image plane; according to spectral images under different brightness, a dark pixel response non-uniformity correction matrix is calculated; the average dark current of the image plane adds to the dark pixel correction matrix to obtain an actual dark current of the image plane; and then deduction of the actual dark current is carried out to realize CCD spectral image dark current correction. According to the invention, spectral image dark current correction based on the CCD dark pixel is realized; and the dark signal response non-uniformity noises are eliminated. The method is reliable and is easy to implement; and the imaging quality of the imaging spectrometer is enhanced.

A shallow sea water depth multi-source remote sensing fusion inversion method comprises the steps of: 1, preprocessing a multispectral remote sensing image to obtain a sea surface reflectivity; 2, acquiring and processing a field test depth value; 3, conducting single-source water depth inversion and water depth segment identification; 4, conducting multi-source water depth inversion fusion; and 5, conducting water depth inversion accuracy verification; using the n types of single-source water depth results, corresponding water depth segment identification images and fusion parameters as input, and conducting multi-source water depth inversion fusion by pixel; verifying water depth inversion accuracy, and using a final depth value as the output data of the actual water depth value of the remote sensing image. Compared with the inversion method of the prior art, the method can comprehensively utilize different responses of a plurality of remote sensing data sources to water depth information, excavate the water depth data, improve inversion accuracy, and conduct decision-making fusion process, and is especially applicable to marine water depth measurement of shallow water region in complex situations.

The invention relates to a method for inverting atmospheric water vapor content from MODIS (Moderate Resolution Imaging Spectroradiometer) data, which can be applied to the remote sensing application departments, such as meteorology, environment monitoring, land management, crop condition monitoring, disaster monitoring and the like. The method comprises the following three steps of: (1) performing forward simulation to the second, fifth, seventeenth, eighteenth and nineteenth near-infrared bands of acquired remote sensing MODIS data in given areas and seasons and an atmospheric model by using atmospheric radiation transmission simulation software MODTRAN, and establishing a training and test database; (2) repeatedly training and testing the training and test data set by using a neural network; and (3) performing inversion calculation to the MODIS actual image data, and performing actual earth surface verification and application analysis. The atmospheric water vapor inversed product has high precision, strong practicability and relatively simple operation. The method can be applied to the departments of weather forecast, environment monitoring, crop condition monitoring, disaster monitoring and the like.