CN113012276B - Surface high-resolution spectral information remote sensing inversion method based on radiometric degree - Google Patents
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Abstract
The invention discloses a surface high-resolution spectral information remote sensing inversion method based on radiometry, which comprises the following steps: s1, reconstructing a three-dimensional scene; s2, angle normalization; s3, setting a sensor and a light source; s4, calculating a shape factor; s5, setting initial values of temperature and reflectivity; s6, outputting a simulation image through a GPU fast radiance method; s7, judging a threshold value; s8, optimizing the temperature and the reflectivity of the surface element; s9, the flow ends and the result is output. According to the method, the influence of multiple scattering on the earth surface is fully considered, so that the inverted temperature and reflectivity results have stability and accuracy; the method has inversion practicability due to the strategy based on the GPU instead of the CPU, and is expected to become an effective tool for producing the earth surface temperature and reflectivity from the high-resolution of the unmanned plane or the man-machine.
Description
Technical Field
The invention relates to an iterative inversion algorithm, in particular to an optimized inversion method of complex earth surface high-resolution optical band remote sensing signals (temperature and reflectivity).
Background
With the rapid development of high spatial resolution satellites and unmanned aerial vehicle technologies, the application of high spatial resolution remote sensing images is more and more extensive. Compared with the existing low spatial resolution data, the high spatial resolution data can provide more precise spatial information of the earth surface and corresponding spectrum or temperature information thereof, and the high spatial resolution remote sensing means gradually becomes an important data source for research and application in the fields of agricultural assessment, urban planning, urban heat island, environmental protection, drought and fire monitoring and the like.
The prior remote sensing inversion algorithm and remote sensing products are mostly based on polar orbit satellites and meteorological satellites low spatial resolution data. At present, most of the existing remote sensing product inversion algorithms based on high spatial resolution are directly migrated from low resolution. In addition to providing more information than the low spatial resolution data, the high spatial resolution data is more susceptible to the influence of the three-dimensional structure of the earth's surface, i.e., the proximity pixel effect, which is usually ignored by the inversion algorithms for low spatial resolution. For low spatial resolution pixels, the spatial resolution is usually greater than 500 meters, the effect of adjacent pixels on a flat ground surface can be ignored, the resolution of high spatial resolution pixels acquired by a high-resolution satellite and an unmanned aerial vehicle can reach 0.1 meter to 10 meters, and the influence of adjacent buildings or vegetation canopies on target pixels is difficult to ignore. Therefore, multiple scattering effects generated by adjacent pixels need to be considered in the remote sensing inversion process.
In summary, the existing high spatial resolution inversion algorithm and product do not consider the multiple scattering influence generated by the three-dimensional structure of the earth surface, so that the inverted earth surface temperature and reflectivity result has uncertainty, and therefore, based on the three-dimensional radiometry theory, the inversion method of the high spatial resolution earth surface temperature and reflectivity considering the multiple scattering influence is provided by taking radiation balance and remote sensing observation as constraints.
Disclosure of Invention
In order to solve the defects of the technology, the invention provides an inversion method of high spatial resolution temperature and reflectivity, which can eliminate multiple scattering terms of the earth surface, based on the three-dimensional radiation transmission technology of the radiometric degree. The patent states that the optimal inversion is carried out by the radiometric method based on the GPU, and compared with the existing CPU method such as a radiometric model RGM based on graphics and a RAPID radiometric model RAPID utilizing a porous medium, the radiometric method based on the GPU is higher in speed and has more practical value.
In order to solve the technical problems, the invention adopts the technical scheme that: a surface high-resolution spectral information remote sensing inversion method based on radiometry comprises the following steps:
s1, reconstructing a three-dimensional scene;
s2, angle normalization;
s3, setting a sensor and a light source;
s4, calculating a shape factor;
s5, setting initial values of temperature and reflectivity;
s6, outputting a simulation image through a GPU fast radiance method;
s7, judging a threshold value;
s8, optimizing the temperature and the reflectivity of the surface element: for pixels which do not meet the threshold, the corresponding surface element temperature needs to be corrected, the comparison result of the simulated and actually measured images is used as constraint, the correction is carried out by a Gaussian-Seidel iteration method, and the optimization formula is as follows:
wherein, Bi，stepF is an optimized proportion for the optimized radiometric result; b isi，iniAnd Bj，iniRadiance of bin i and bin j in the initial state, Ei，iniSelf-emission terms representing initial state bins; in circulation ofIn the ring process, Bi，iniAnd Bj，ini，Ei，iniThe state corresponding to the previous cycle of the current cycle step length can also be considered; x is the number ofiThe transmittance or the reflectivity of the surface element is represented, and the transmittance or the reflectivity is judged according to the geometrical relationship between the light and the surface element; fi，jIs a form factor;
s9, the flow ends and the result is output.
Further, in step S1, the three-dimensional unmanned aerial vehicle/manned observation platform obtains a series of remote sensing images, and then performs surface three-dimensional reconstruction by using a two-dimensional moving image three-dimensional reconstruction method to obtain surface three-dimensional structure information and corresponding spectrum or temperature information; the SFM method comprises the following processing steps: image alignment, sparse point cloud construction, dense point cloud construction, grid construction, digital elevation construction and orthorectification.
Further, in step S2, the remote sensing signals observed at different angles are homogenized to eliminate the influence of the angle effect, and the method is implemented by a kernel driving method, where the kernel driving method is as follows:
wherein T is a remote sensing observation signal; theta5Observing the zenith angle for the sun; thetavObserving a zenith angle for the sensor;
is the relative azimuth angle between the sensor and the sun; kLSFIs a Li-Strahler-Friedl radiation transmission nucleus; kLIIs a Li-Strahler geometric optical nucleus; kjumpIs a neighboring pixel core; f. ofLSF、fLI、fjumpThe nuclear coefficients of the radiation transmission nucleus, the geometric optical nucleus and the adjacent pixel nucleus are respectively; f. ofisoThe kernel coefficient for isotropic kernel "1".
Further, in step S3, an observation matrix of the three-dimensional scene is given according to the position, the observation field and the field angle of the sensor; the light source vector is set according to the position of the sun.
Further, in step S4, a shape factor between bins is calculated by bin, which is related to the shapes and angles of bin i and bin j, according to the principle of computer graphics, and the calculation formula is as follows:
wherein, Fi，jIs a form factor; a. theiAnd AjArea of bin i and bin j, respectively, then dAiAnd dAjRespectively, the differential results; thetaiIs the angle of bin i; thetajIs the angle of bin j; r is the distance between the bins.
Further, in step S5, setting the initial temperature of the vegetation surface element in the three-dimensional scene to be air temperature +1 ℃, and setting the initial temperature of the soil and the building surface element to be air temperature +10 ℃; and setting initial spectrum information of vegetation, soil and buildings according to the spectrum library.
Further, in step S6, the bin radiance refers to the radiant flux density leaving the surface of the bin, and the formula of the bin radiance is as follows:
wherein, BiIs the radiance of bin i; eiSelf-emission items representing bins; x is the number ofiThe transmittance or the reflectivity of the surface element is represented, and the transmittance or the reflectivity is judged according to the geometrical relationship between the light and the surface element; fi，jIs a form factor; b isjIs the radiance of bin j; n isfIs the total number of bins;
the formula indicates that the radiance of a bin includes the emission term of the bin and the multiple scattering term with neighboring pixels.
Further, in step S7, comparing the actual measurement image with the simulated image pixel by pixel, and determining whether the difference satisfies a threshold condition; under normal conditions, a temperature threshold of less than 0.1 ℃ is considered to satisfy the condition skipping optimization, and a reflectance threshold of less than 0.001 is considered to satisfy the condition skipping optimization.
Further, in step S9, repeating steps S6-S8 until all the pixels satisfy the threshold condition; the surface element temperature and the reflectivity are the real temperature and the reflectivity of the ground object, and the result image is output and stored in the TIF format.
The method extracts the three-dimensional structure of the earth surface from the unmanned aerial vehicle or high-fraction data through the existing software and technology, determines the influence of the adjacent pixels by the shape factors among the surface elements in the inversion process, continuously optimizes the earth surface radiation transmission by using the radiation balance and high spatial resolution observation as constraints through a Gauss-Seidel iteration method, finally eliminates the multiple scattering influence to obtain the real temperature and reflectivity result of the earth surface,
the invention provides a method for obtaining the real temperature and reflectivity of the earth surface by removing the influence of multiple scattering items based on a three-dimensional radiometric theory aiming at the influence of the multiple scattering items of the high-resolution unmanned aerial vehicle/human-computer observation on the complex earth surface, particularly considers the influence caused by the complex three-dimensional structure of the earth surface, and eliminates or reduces the uncertainty of remote sensing signals caused by adjacent ground objects to target ground objects.
According to the method, the influence of multiple scattering on the earth surface is fully considered, so that the inverted temperature and reflectivity results have stability and accuracy; the method has inversion practicability due to the strategy based on the GPU instead of the CPU, and is expected to become an effective tool for producing the earth surface temperature and reflectivity from the high-resolution of the unmanned plane or the man-machine.
Drawings
FIG. 1 is an overall flow chart of the present invention.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings and specific embodiments.
The radiometric-based surface high-resolution spectral information remote sensing inversion method shown in fig. 1 comprises the following steps:
s1, reconstructing a three-dimensional scene;
the three-dimensional unmanned aerial vehicle/manned observation platform obtains a series of remote sensing images, and then carries out surface three-dimensional reconstruction by a method of three-dimensional reconstruction (Structure from motion) of a two-dimensional motion image to obtain surface three-dimensional Structure information and corresponding spectrum or temperature information; the step is a preposed step for eliminating multiple scattering items of an observation result, and the SFM method comprises the following processing steps: image alignment, sparse point cloud construction, dense point cloud construction, grid construction, Digital Elevation (DEM) construction and orthorectification. A bin is a basic unit, usually a triangle or a quadrilateral, that makes up a complex scene.
S2, angle normalization;
the method comprises the following steps of homogenizing colors of remote sensing signals observed at different angles to eliminate angle effect influence, and realizing the method through a nuclear driving method, wherein the nuclear driving method comprises the following steps:
wherein T is a remote sensing observation signal; thetasObserving the zenith angle for the sun; thetavObserving a zenith angle for the sensor;
is the relative azimuth angle between the sensor and the sun; k'LSFIs a Li-Strahler-Friedl radiation transmission nucleus; kLIIs a Li-Strahler geometric optical nucleus; kjumpIs a neighboring pixel core; f. ofLSF、fLI、fjumpThe nuclear coefficients of the radiation transmission nucleus, the geometric optical nucleus and the adjacent pixel nucleus are respectively; f. ofisoThe kernel coefficient for isotropic kernel "1".
S3, setting a sensor and a light source;
an observation matrix of the three-dimensional scene is given according to the position, the observation field and the field angle of the sensor; the light source vector is set according to the position of the sun.
S4, calculating a shape factor;
calculating shape factors among the surface elements by surface elements according to the principle of computer graphics, wherein the shape factors are related to the shapes and angles of the surface elements i and j, and the calculation formula is as follows:
wherein, Fi，jIs a form factor; a. theiAnd AjArea of bin i and bin j, respectively, then dAiAnd dAjRespectively, the differential results; thetaiIs the angle of bin i; thetajIs the angle of bin j; r is the distance between the bins.
S5, setting initial values of temperature and reflectivity;
setting the initial temperature of a vegetation surface element in a three-dimensional scene as the air temperature plus 1 ℃, and setting the initial temperature of soil and a building surface element as the air temperature plus 10 ℃; and setting initial spectrum information of vegetation, soil and buildings according to the spectrum library.
S6, outputting a simulation image through a GPU fast radiance method;
bin radiance refers to the radiant flux density leaving the surface of the bin, and the formula for the radiance of the bin is as follows:
wherein, BiIs the radiance of bin i; eiSelf-emission items representing bins; x is the number ofiThe transmittance or the reflectivity of the surface element is represented, and the transmittance or the reflectivity is judged according to the geometrical relationship between the light and the surface element; fi，jIs a form factor; b isjIs the radiance of bin j; n isfIs the total number of bins;
the formula indicates that the radiance of a bin includes the emission term of the bin and the multiple scattering term with neighboring pixels. The multiple scattering term is calculated taking into account the contributions of this bin to all bins in the neighborhood. The platform can realize cross-platform application of Windows, Linux and Andron operating systems based on a Vulkan API framework, and NVIDIA display card equipment is used as an operation unit. And then, simultaneously setting up the radiance equations of all the surface elements to calculate the radiance result.
S7, judging a threshold value;
comparing the actual measurement image with the simulation image pixel by pixel, and judging whether the difference meets a threshold condition; under normal conditions, a temperature threshold of less than 0.1 ℃ is considered to satisfy the condition skipping optimization, and a reflectance threshold of less than 0.001 is considered to satisfy the condition skipping optimization.
S8, optimizing the temperature and the reflectivity of the surface element;
for pixels which do not meet the threshold, the corresponding surface element temperature needs to be corrected, the comparison result of the simulated and actually measured images is used as constraint, the correction is carried out by a Gaussian-Seidel iteration method, and the optimization formula is as follows:
wherein, Bi，stepF is an optimized proportion for the optimized radiometric result; b isi，iniAnd Bj，iniRadiance of bin i and bin j in the initial state, Ei，iniSelf-emission terms representing initial state bins; in the cyclic process, Bi，iniAnd Bj，ini，Ei，iniThe state corresponding to the previous cycle of the current cycle step length can also be considered; x is the number ofiThe transmittance or the reflectivity of the surface element is represented, and the transmittance or the reflectivity is judged according to the geometrical relationship between the light and the surface element; fi，jIs a form factor.
S9, the flow ends and the result is output.
Repeating steps S6-S8 until all pixels satisfy the threshold condition; the surface element temperature and the reflectivity are the real temperature and the reflectivity of the ground object, and the result image is output and stored in the TIF format.
The above embodiments are not intended to limit the present invention, and the present invention is not limited to the above examples, and those skilled in the art may make variations, modifications, additions or substitutions within the technical scope of the present invention.
Claims (9)
1. A surface high-resolution spectral information remote sensing inversion method based on radiometry is characterized by comprising the following steps: the method comprises the following steps:
s1, reconstructing a three-dimensional scene;
s2, angle normalization;
s3, setting a sensor and a light source;
s4, calculating a shape factor;
s5, setting initial values of temperature and reflectivity;
s6, outputting a simulation image through a GPU fast radiance method;
s7, judging a threshold value;
s8, optimizing the temperature and the reflectivity of the surface element: for pixels which do not meet the threshold, the corresponding surface element temperature needs to be corrected, the comparison result of the simulated and actually measured images is used as constraint, the correction is carried out by a Gaussian-Seidel iteration method, and the optimization formula is as follows:
wherein, Bi，stepF is an optimized proportion for the optimized radiometric result; b isi，iniAnd Bj，iniRadiance of bin i and bin j in the initial state, Ei，iniSelf-emission terms representing initial state bins; in the cyclic process, Bi，iniAnd Bj，ini，Ei，iniThe state corresponding to the previous cycle of the current cycle step length can also be considered; x is the number ofiThe transmittance or the reflectivity of the surface element is represented, and the transmittance or the reflectivity is judged according to the geometrical relationship between the light and the surface element; fi，jIs a form factor;
s9, the flow ends and the result is output.
2. The radiometry-based remote sensing inversion method for surface high-resolution spectral information according to claim 1, characterized in that: in the step S1, the three-dimensional unmanned aerial vehicle/manned observation platform obtains a series of remote sensing images, and then performs surface three-dimensional reconstruction by using a two-dimensional moving image three-dimensional reconstruction method to obtain surface three-dimensional structure information and corresponding spectrum or temperature information; the SFM method comprises the following processing steps: image alignment, sparse point cloud construction, dense point cloud construction, grid construction, digital elevation construction and orthorectification.
3. The radiometry-based remote sensing inversion method for surface high-resolution spectral information according to claim 2, characterized in that: in step S2, the remote sensing signals observed at different angles are homogenized to eliminate the influence of the angle effect, and the method is implemented by a kernel driving method, where the kernel driving method is as follows:
wherein T is a remote sensing observation signal; thetasObserving the zenith angle for the sun; thetavObserving a zenith angle for the sensor;
is the relative azimuth angle between the sensor and the sun; kLSFIs a Li-Strahler-Friedl radiation transmission nucleus; kLIIs a Li-Strahler geometric optical nucleus; kjumpIs a neighboring pixel core; f. ofLSF、fLI、fjumpThe nuclear coefficients of the radiation transmission nucleus, the geometric optical nucleus and the adjacent pixel nucleus are respectively; f. ofisoThe kernel coefficient for isotropic kernel "1".
4. The radiometry-based remote sensing inversion method for surface high-resolution spectral information according to claim 3, characterized in that: in the step S3, an observation matrix of the three-dimensional scene is given according to the position, the observation field and the field angle of the sensor; the light source vector is set according to the position of the sun.
5. The radiometry-based remote sensing inversion method for surface high-resolution spectral information according to claim 4, characterized in that: in step S4, a shape factor between bins is calculated by bin according to the principle of computer graphics, where the shape factor is related to the shapes and angles of bin i and bin j, and the calculation formula is as follows:
wherein, Fi，jIs a form factor; a. theiAnd AjArea of bin i and bin j, respectively, then dAiAnd dAjRespectively, the differential results; thetaiIs the angle of bin i; thetajIs the angle of bin j; r is the distance between the bins.
6. The radiometry-based remote sensing inversion method for surface high-resolution spectral information according to claim 5, characterized in that: in the step S5, setting the initial temperature of a vegetation surface element in the three-dimensional scene to be air temperature +1 ℃, and setting the initial temperature of soil and a building surface element to be air temperature +10 ℃; and setting initial spectrum information of vegetation, soil and buildings according to the spectrum library.
7. The radiometry-based remote sensing inversion method for surface high-resolution spectral information according to claim 6, characterized in that: in step S6, the bin radiance refers to the radiant flux density leaving the surface of the bin, and the formula of the bin radiance is as follows:
wherein, BiIs the radiance of bin i; eiSelf-emission items representing bins; x is the number ofiThe transmittance or the reflectivity of the surface element is represented, and the transmittance or the reflectivity is judged according to the geometrical relationship between the light and the surface element; fi，jIs a form factor; b isjIs the radiance of bin j; n isfIs the total number of bins;
the formula indicates that the radiance of a bin includes the emission term of the bin and the multiple scattering term with neighboring pixels.
8. The radiometry-based remote sensing inversion method for surface high-resolution spectral information according to claim 7, characterized in that: in step S7, comparing the actual measurement image with the simulation image pixel by pixel, and determining whether the difference satisfies a threshold condition; under normal conditions, a temperature threshold of less than 0.1 ℃ is considered to satisfy the condition skipping optimization, and a reflectance threshold of less than 0.001 is considered to satisfy the condition skipping optimization.
9. The radiometry-based remote sensing inversion method for surface high-resolution spectral information according to claim 8, characterized in that: in the step S9, the steps S6-S8 are repeated until all the pixels meet the threshold condition; the surface element temperature and the reflectivity are the real temperature and the reflectivity of the ground object, and the result image is output and stored in the TIF format.
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