CN106980765B - Method for calculating root mean square height of earth surface by utilizing fully polarized SAR data - Google Patents
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- 238000000034 method Methods 0.000 title claims abstract description 22
- 238000005388 cross polarization Methods 0.000 claims abstract description 7
- 230000010287 polarization Effects 0.000 claims description 15
- 238000007781 pre-processing Methods 0.000 claims description 2
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- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 11
- 230000003746 surface roughness Effects 0.000 description 7
- 238000012544 monitoring process Methods 0.000 description 6
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- 238000005070 sampling Methods 0.000 description 2
- 230000035945 sensitivity Effects 0.000 description 2
- 238000004162 soil erosion Methods 0.000 description 2
- 238000012795 verification Methods 0.000 description 2
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- G—PHYSICS
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- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
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- G01S13/90—Radar or analogous systems specially adapted for specific applications for mapping or imaging using synthetic aperture techniques, e.g. synthetic aperture radar [SAR] techniques
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- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
- G01S13/88—Radar or analogous systems specially adapted for specific applications
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Abstract
The invention provides a method for calculating the root mean square height of the earth surface by utilizing fully polarized SAR datavv、σhh、σhvAnd σvhAnd the co-polarization correlation coefficient ρvvhh(ii) a Secondly, according to the co-polarization correlation coefficient rhovvhhObtaining the height h of the vegetation according to the relation with the height h of the vegetation; and finally, calculating to obtain the root mean square height s of the earth surface according to the relation between the difference value dB of the cross polarization and the homopolarity and the root mean square height s of the earth surface.
Description
Technical Field
The invention relates to the field of microwave remote sensing, in particular to a method for calculating the root mean square height of the earth surface by utilizing fully polarized SAR data
Background
High resolution Synthetic Aperture Radar (SAR) data has important applications in crop monitoring, and can be used for monitoring crop growth, yield and soil humidity. Soil humidity is used as an indicator factor of climate and environment drought, and is an important monitoring content in global change research; meanwhile, the method is an important index in the aspects of drought monitoring, crop yield estimation and the like as a basic condition of plant growth. The traditional measuring method of soil humidity is based on point measurement, and the measuring result has space-time discontinuity, which is not beneficial to large-scale estimation and dynamic monitoring. By means of high sensitivity of the SAR to soil humidity, the SAR can make up for the defects of the traditional measuring method and becomes a new method and means for monitoring the soil humidity. Through which scholars at home and abroad develop an inversion algorithm based on a backscattering model and a polarization information algorithm based on target decomposition. The semi-empirical water cloud model is widely applied to modeling of the scattering model of the vegetation coverage area due to the simplicity of the semi-empirical water cloud model. The water cloud model simplifies the total backward scattering coefficient into two parts of a vegetation body scattering item and a soil scattering item attenuated by the vegetation two-way transmission effect, and the influence of multiple scattering is ignored. The scattering model applied to the bare earth surface at present mainly comprises a theoretical model, namely an Integral Equation Model (IEM), an improved integral equation model (AIEM), an empirical-semi-empirical model, namely an Oh model, a Dubois model, a Shi model and the like. When soil moisture inversion is carried out in a vegetation coverage area, the correction of the influence of earth surface vegetation on backscattering is very important, the predecessors propose vegetation coverage models such as MIMICS models and water cloud models, the vegetation canopy and the stem part are not obviously different in the actual crop coverage area, and the water cloud model is more suitable for application.
In the interaction process of the ground and radar incident waves, the ground scattering characteristics are related to the ground humidity and vegetation coverage, and the ground roughness parameter is also a main determining factor which influences the backscattering characteristics of radar waves. The surface roughness is one of important geophysical parameters reflecting the surface alteration condition, and is an important parameter for researching the land surface processes of surface runoff, soil erosion, soil water storage capacity, permeation rate and the like and the space change of the land surface processes. The slope runoff resistance is increased due to the existence of the surface roughness in the water flow moving direction, so that the water flow speed is reduced or the path is increased, the flow velocity gradient in the runoff advancing direction is reduced, and a series of influences are generated on surface runoff and soil erosion; meanwhile, after the surface roughness of the soil is increased, the surface runoff is blocked, and the infiltration time of soil moisture is prolonged, so that the water storage capacity of the soil is higher. Therefore, the surface roughness is not only an important parameter in the land surface process, but also an important influence factor of water and soil loss in the fields of disasters, agriculture and the like. The root mean square height of the earth surface is the most important parameter of the roughness of the earth surface, and in the prior art, the root mean square height of the earth surface is difficult to invert from microwave remote sensing data, so the invention provides a method for calculating the root mean square height of the earth surface by utilizing fully polarized SAR data.
In the field of microwave remote sensing, the surface roughness is generally characterized by two main parameters, namely root-mean-square height s and surface correlation length 1, which respectively depict the surface roughness condition from the vertical direction and the horizontal direction.
Physical significance of root mean square height s
Assuming that the height of a point (x, y) in the plane x-y is z (x, y), taking a statistically representative block on the surface, the dimensions Lx and Ly, respectively, and placing the origin at the center of the plane, the average height of the surface is:
the mathematical expectation of the squared variable is:
then the root mean square height s is defined as:
for discrete data, the root mean square height s is:
in the formulaAnd N is the number of samples.
In the field, because the traditional scattering models of the bare earth surface are mainly an Integral Equation Model (IEM), an improved integral equation model (AIEM), an experience-semi-experience model-an Oh model, a Dubois model, a Shi model and the like, which have good results when the earth surface is bare, the traditional scattering models of the bare earth surface cannot be directly used for calculating the root mean square height of the earth surface because the influence of earth surface vegetation on backscattering needs to be corrected in a vegetation coverage area. In the vegetation model, because unknown parameters are numerous, most of the previous works only concern vegetation coverage related parameters, soil moisture and the like, and a method for effectively calculating the roughness of the vegetation coverage ground surface by using remote sensing data does not exist. The invention provides a method for calculating the root mean square height of the earth surface by utilizing fully polarized SAR data.
Disclosure of Invention
The invention provides a method for calculating the root-mean-square height of the earth surface by utilizing fully polarized SAR data, which comprises the following steps:
(1) preprocessing the satellite data of the complete polarization C wave band, extracting four channels and different polarization backscattering scattering coefficients sigmavv、σhh、σhvAnd σvhAnd the co-polarization correlation coefficient ρvvhh;
(2) According to the co-polarization correlation coefficient rhovvhhObtaining the height h of the vegetation according to the relation with the height h of the vegetation;
(3) and calculating to obtain the root mean square height s of the earth surface according to the relation between the difference value dB of the cross polarization and the homopolarity and the root mean square height s of the earth surface and h.
The co-polarization correlation coefficient p in the step (2)vvhhThe relationship with the vegetation height h is:
ρvvhh=-0.01702log(h)+0.824
wherein the correlation coefficient R satisfies: r2=0.88。
In the step (3), the relation between the dB difference value of cross polarization and homopolarity and h and the root-mean-square height s of the earth surface is as follows:
wherein a is-12.44, b is-2.42, and c is 4.62.
The method has the beneficial effects that the method for calculating the root mean square height of the vegetation covered ground surface by utilizing the fully polarized SAR data is obtained, so that the method becomes one of the other ground surface parameters which can be effectively calculated by utilizing the remote sensing data.
Drawings
Fig. 1 shows the complete polarization SAR data and the ground sampling points for performing the algorithm verification.
Fig. 2 is a relationship between the co-polarization correlation coefficient and the vegetation height.
Fig. 3 is a relationship between the measured value of the vegetation height h and the simulated value of the vegetation height.
Fig. 4 is a relationship between the measured root mean square height s and the simulated root mean square height s.
Detailed Description
Study area and data
The research area of the invention is located in the Itani farm of the inner Mongolia autonomous region, the forehead Golgi city and the periphery thereof (figure 1), is located in the west slope of the north section of Daxingan mountain, and has the coverage range of 120 degrees to 122 degrees 55 degrees at the east longitude and 50 degrees to 20 degrees to 52 degrees 30 degrees at the north latitude. The natural geography of the method is characterized by high latitude and high cold, and the planted crops mainly comprise dry field crops such as wheat, rape and the like; meanwhile, the region range of the research region is greatly higher than the image resolution, the number of mixed pixels is reduced, the aliasing of types is reduced, and favorable conditions are provided for the development of experiments. In the experiment, RADARSAT-2 full polarization data acquired in 2016, 6, 24 and actually measured sampling data acquired in the same period during transit are adopted to carry out the research of extracting the surface soil humidity based on the RADARSAT-2 data.
During field data acquisition in the field (23-24 days 6 months in 2016), Radarsat-2 data of a scene is acquired, the transit time is 18:27 days, the data is C-band full polarization data, and the coverage range is 25 multiplied by 25 km. The incident angle was 38 deg., and the incident frequency was about 5.4 GHz. And calibration and geometric correction are carried out by utilizing SNAP software of the European space agency, and meanwhile, a backscattering coefficient corresponding to each polarization and a ground measured point is extracted from the SAR image.
The ground data measured synchronously with the transit time of the satellite includes: surface roughness, soil moisture, vegetation related parameters (vegetation height, vegetation water content).
Detailed description of the invention
The method of the invention is mainly divided into three parts: firstly, an empirical relation is established by utilizing SAR complete polarization data to estimate the vegetation height (h); establishing a relation between a difference value dB of cross polarization and homopolarity and h and the root-mean-square height s of the earth surface; third is the inverse surface root mean square height s.
Co-polarization correlation coefficient rhovvhhRelation with h
Co-polarization correlation coefficient (p)vvhh) Reflecting the correlation between HH polarization and VV polarization.
FIG. 2 shows the relationship between the co-polarization correlation coefficient and the vegetation height, and it can be seen from the graph that rhovvhhHas higher sensitivity to the vegetation height. Fitting the data by using the least square principle and using the same polarization correlation coefficient rhovvhhThe relation with the vegetation height h is rhovvhh-0.01702log (h) +0.824, where the correlation coefficient R is R2=0.88。
The results show that: the co-polarization correlation coefficient is highly dependent on vegetation, and is independent of vegetation type.
Calculating the root mean square height of the earth surface according to the relation between h and the root mean square height s of the earth surface according to the difference between the cross polarization and the homopolarity dB, (a is-12.44, b is-2.42, c is 4.62)
Verification of experimental results
Comparison of the simulated value of the backscattering coefficient with the actual value
The vegetation height h and the ground root mean square height s are inverted, and the relation between the measured value and the simulated value of the vegetation height h and the ground root mean square height s is respectively shown in fig. 3 and 4. The inversion accuracy is high as can be seen from the relationship between the vegetation height and the root mean square height of the earth surface and the measured value in the graph.
In the invention, the root mean square height of the earth surface is finally established by calculating the vegetation height h by utilizing Radarsat-2 full polarization data and field data measured in the field at the same time. The advantage of the invention is that the values of h and s can be inverted using only one scene of the fully polarized radar data, without the aid of optical data. The model parameterization is good for the scattering information expression; the inversion model has a good effect of acquiring vegetation height and surface root mean square height information.
Claims (1)
1. A method for calculating the root mean square height of the earth surface in high latitude and high cold areas by utilizing full polarization SAR data comprises the following steps:
(1) preprocessing the satellite data of the complete polarization C wave band, extracting four channels and different polarization backscattering scattering coefficients sigmavv、σhh、σhvAnd σvhAnd the co-polarization correlation coefficient ρvvhh;
(2) According to the co-polarization correlation coefficient rhovvhhObtaining the height h of the vegetation according to the relation with the height h of the vegetation;
(3) calculating to obtain the root mean square height s of the earth surface according to the relation between the difference value dB of the cross polarization and the homopolarity and the root mean square height s of the earth surface and h;
the co-polarization correlation coefficient rho in the step (2)vvhhThe relationship with the vegetation height h is:
ρvvhh-0.01702log (h) +0.824, wherein the correlation coefficient R satisfies: r2=0.88;
The relation between the difference value dB of cross polarization and homopolarity in the step (3) and the root-mean-square height h and the ground surface s is as follows:
wherein a is-12.44, b is-2.42, and c is 4.62.
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"Soil moisture retrieval over agricultural fields from multi-polarized and multi-angular RADARSAT-2 SAR data";Imen Gherboudj等;《Remote Sensing of Environment》;20110117;第115卷(第1期);第33-43页 * |
"基于Radarsat-2 SAR数据反演定西裸露地表土壤水分";胡蝶等;《干旱气象》;20140831;第32卷(第4期);第553-559页 * |
"基于极化分解的极化特征参数提取与应用";王庆等;《国土资源遥感》;20120915(第3期);第103-110页 * |
"林分平均高度卫星遥感新进展";董立新;《遥感技术与应用》;20161031;第31卷(第5期);第833-845页 * |
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