CN108761034A - A kind of multi-source satellite soil moisture retrieval method - Google Patents
A kind of multi-source satellite soil moisture retrieval method Download PDFInfo
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Abstract
The invention discloses a kind of multi-source satellite soil moisture retrieval methods, which is characterized in that includes the following steps：The bright temperature data of multi-source satellite is collected, and obtains the same spatial resolution brightness temperature product serial of unification；Soil moisture microwave remote sensing inverse model is built, bright temperature is carried out and is converted with emissivity, the grid emissivity one by one of extraction microwave radiometer scanning track；Influence to vegetation and roughness of ground surface is rejected and is corrected；Soil dielectric constant is converted with emissivity, be associated with soil moisture using transformed dielectric constant it is counter push away, realize the remote-sensing inversion of soil moisture.The present invention is main input data using the quasi real time brightness temperature data of multiple satellite platforms observation, the bright temperature data for extracting different satellite sources carries out cutting splicing, the inverting and space-time for realizing surface soil water are rebuild, and the soil moisture product of continuous high-spatial and temporal resolution is obtained.
Description
Technical field
The invention belongs to hydrological remote sensing technical fields, and in particular to a kind of multi-source satellite soil moisture retrieval method.
Background technology
Soil moisture is weather, numerical weather forecast, hydrologic(al) prognosis, agricultural arid monitoring and prediction and Land data assimilation etc.
The important land surface parameters of research field.The measurement method for obtaining soil moisture classics at present mainly has：Weight method, tensometer method,
NEUTRON METHOD, electric-resistivity method etc., although the soil moisture precision of website artificial observation is high, the sparse or with a varied topography ground of website
Area can not lay website, and classical measurement method has the shortcomings of blocky scarce survey, data is discontinuous, it is difficult to show soil moisture
Spatial distribution.
The acquisition of the soil humidity information for developing into regional scale of satellite remote sensing technology provides effective means, but defends
The spatial resolution of star remote-sensing inversion surface soil humidity is low, and there are very large space heterogeneity, the soil of different spatial resolutions
Earth humidity characteristic is inconsistent；Due to the scanning track of satellite and coverage area, the shadow of the factors such as the veils such as vegetation, massif
It rings, there is part band, partial region data deficient phenomenas, and shortage of data region varies over, can not
For the soil moisture signature analysis of specific region and continuous time, need to rebuild missing data；Therefore, continuous high
The acquisition of spatial and temporal resolution soil moisture is also agricultural arid monitoring, Forecasting Flood etc. as the hot and difficult issue studied
Business department very relationship the problem of.
A series of domestic and international business satellites for carrying main passive microwave sensor succeed in sending up, such as：SMOS(Soil
Moisture and Ocean Salinity),SMAP(Soil Moisture Active Passive),FY3B(MWRI：
Microwave Radiation Imager),FY3C(MWRI：Microwave Radiation Imager),AMSR
(Advanced Microwave Scanning Radiometer 2) etc., utilizes the microwave remote sensor energy being mounted on satellite
A large amount of thin solum humidity informations are enough obtained, the joint inversion of multi-source satellite soil moisture is in basin-wide or regional soil moisture
There is irreplaceable advantage in monitoring.
Invention content
In order to obtain the soil moisture product of continuous high-spatial and temporal resolution, the present invention provides a kind of multi-source satellite soil
The method that the timely bare weight of humidity retrieval is built cuts, splicing by data, obtains using the satellite bright temperature data of domestic and international mainstream
The bright temperature data that format is consistent, resolution ratio is consistent builds soil moisture retrieval model, obtains soil moisture product；It will utilize
The information such as the soil water-containing information obtained for three days, antecedent precipitation are gone to carry out statistical regression interpolation, to obtain the land of space and time continuous
Table soil moisture product.
In order to obtain the soil moisture of continuous high-spatial and temporal resolution, the present invention specifically uses following technical scheme：
A kind of multi-source satellite soil moisture retrieval method, which is characterized in that include the following steps：
Step 1, the bright temperature data of multi-source satellite is collected, and obtains same spatial resolution (0.25 °) brightness of unification
Temperature product serial；
Step 2, soil moisture microwave remote sensing inverse model is built, bright temperature is carried out and is converted with emissivity, extract microwave radiation
The grid emissivity one by one of meter scanning track；
Including：
Step 21, soil moisture microwave remote sensing inverse model is built：
TBp=Tu+exp(-τa)×[{TdrSpexp(-2τc)}+{eSpTsexp(-τc)+Tc(1-ωp)[1-exp(-τc)][1
+rSpexp(-τc)] (1)
Wherein：TBpFor brightness temperature, TuFor the uplink radiation of air, TdThe downlink radiation for being air at the top of canopy, τaFor
The optical thickness of air, that subscript p is indicated is polarization mode, TcFor the temperature of vegetation, τcFor the optical thickness factor of vegetation, rSp
=1-eSpFor the reflectivity of soil surface；TsIt is effective physical temperature of earth's surface, ωpFor the single scattering albedo of vegetation；
Step 22, the quasi real time surface temperature and microwave radiometer of satellite remote sensing and the acquisition of real-time weather forecasting model are utilized
The bright temperature of observation, the grid emissivity one by one of extraction microwave radiometer scanning track：
γp=e(-τsecθ) (3)
In formula：TBpFor brightness temperature；T is physical temperature；E is emissivity；Subscript p represents polarization direction, including horizontal pole
Change (H) and vertical polarization (V), τ vegetation opacities, ω single scattering albedos, γ canopy transmissivities,The ground of polarization direction p
Table emissivity, θ are radiometer view angle or incident；
Step 3, the influence to vegetation and roughness of ground surface is rejected and is corrected；
Step 4, soil dielectric constant is converted with emissivity, is closed using transformed dielectric constant and soil moisture
Connection is counter to be pushed away, and realizes the remote-sensing inversion of soil moisture.
The bright temperature data of domestic and international high-spatial and temporal resolution is collected in the step 1, and according to the feature of the bright temperature of different satellites
The format conversion of progress data, resampling, space splicing, same spatial resolution (0.25 °) the brightness temperature for generating unification
Product serial is spent, following steps are specifically included：
Step 11, domestic and international bright temperature data is collected；
Step 12, the format of different satellite bright temperature datas is different, carries out Data Format Transform, is uniformly converted to HDF5；
Step 13, the spatial resolution of different satellite bright temperature datas is different, carries out resampling so that spatial resolution one
It causes；
Step 14, the track of the inswept earth of different satellites is different, needs to carry out space splicing to bright temperature data；
Step 15, the bright temperature temperature product that format is consistent, spatial resolution is consistent is generated；
Soil moisture microwave remote sensing inverse model is built in the step 2, is carried out bright temperature and is converted with emissivity, extracts microwave
Radiometer scans the grid emissivity one by one of track, and specific steps include：
Step 21, on the basis of classical τ-ω models, the brightness temperature observed using microwave radiometer is wet with soil
The relationship of degree builds soil moisture microwave remote sensing inverse model；
TBp=Tu+exp(-τa)×[{TdrSpexp(-2τc)}+{eSpTsexp(-τc)+Tc(1-ωp)[1-exp(-τc)][1
+rSpexp(-τc)] (1)
Wherein：TBpFor brightness temperature, TuFor the uplink radiation of air, TdThe downlink radiation for being air at the top of canopy, τaFor
The optical thickness of air, that subscript p is indicated is polarization mode, TcFor the temperature of vegetation, τcFor the optical thickness factor of vegetation, rSp
=1-eSpFor the reflectivity of soil surface；TsIt is effective physical temperature of earth's surface, ωpFor the single scattering albedo of vegetation.
Step 22, the quasi real time surface temperature and microwave radiometer of satellite remote sensing and the acquisition of real-time weather forecasting model are utilized
The bright temperature of (such as SMAP, SMOS and AMSR2) observation, the grid emissivity one by one of extraction microwave radiometer scanning track；It is bright
Spend temperature (TB), physical temperature (T), emissivity (e) by following physical equation establish contact：
γp=e(-τsecθ) (3)
In formula：TBpFor brightness temperature；T is physical temperature；E is emissivity；Subscript p represents polarization direction, including horizontal pole
Change (H) and vertical polarization (V), τ vegetation opacities, ω single scattering albedos, γ canopy transmissivities,The ground of polarization direction p
Table emissivity, θ are radiometer view angle or incident.
The extraction to soil moisture is improved in the step 3, the influence to vegetation and roughness of ground surface is kicked out of
And correction, including：
τ=bVWC (4)
In formula：τ vegetation opacities, VWC vegetation water content,The soil emissivity of polarization direction p, b depend on planting
By type, the parameter of microwave frequency, θ is radiometer view angle or incident.
Soil dielectric constant is converted with emissivity in the step 4, utilizes transformed dielectric constant and soil
Humidity association is counter to be pushed away, and realizes that the remote-sensing inversion step of soil moisture includes：
Step 41, soil dielectric constant be associated with emissivity it is counter push away, soil dielectric constant passes through famous with emissivity relationship
Fresnel formula state, dielectric constant same polarization emissivity can be converted.
In formula, εrUpper soll layer dielectric constant,Horizontal polarization emissivity,Vertical polarization emissivity, θ are radiation
Count view angle or incident.
Step 42, right using transformed dielectric constant and existing soil water-containing and soil dielectric constant relational model
Soil water-containing is counter to be pushed away, to realize the inverting extraction of soil moisture.
In formula：ρbSoil block volume density；ρsSoil solid particle proportion；mvSoil volumetric water content；εfwFree water dielectric
Constant；εsSoil particle dielectric constant, α, β are empirical index number.
Beneficial effects of the present invention：A kind of side that the timely bare weight of multi-source satellite soil moisture retrieval is built provided by the invention
Method downloads the brightness temperature data of mainstream satellite, and uniform format processing, Design Based on Spatial Resampling, data splicing are carried out to bright temperature data
Etc. obtaining, format is consistent, the bright temperature product of the consistent Time Continuous of spatial resolution；On the basis of classical τ-ω models, soil is established
Earth humidity passive microwave remote sensing inversion algorithm, i.e.,：The surface temperature that is obtained using satellite remote sensing and real-time weather forecasting model and
The bright temperature of microwave radiometer observation, extracts grid emissivity one by one；Emissivity is established by fresnel formula with soil to be situated between
The relationship of electric constant, emissivity and dielectric constant are converted；The relational model of soil moisture and dielectric constant is established, is realized
The remote-sensing inversion of soil moisture.This method fully considers the advantages of each satellite, is basic data, data source with brightness temperature
It is reliable and stable；Soil moisture passive microwave remote sensing inversion algorithm is established, based on classical Remote Sensing Model, ensure that the objective of result
Reasonability realizes the soil moisture retrieval of multi-source satellite, obtains the soil of the consistent high-spatial and temporal resolution of Time Continuous spatial distribution
Earth humidity product.
Description of the drawings
Fig. 1 is bright temperature data processing schematic diagram of the present invention.
Fig. 2 is inversion algorithm schematic diagram in the present invention.
Fig. 3 is bright temperature data amount schematic diagram in the present invention.
Fig. 4 is original bright temperature data schematic diagram in the present invention.
Fig. 5 is to splice bright temperature data schematic diagram in the present invention.
Fig. 6 is soil moisture product schematic diagram in the present invention.
Specific implementation mode
The invention will be further described in the following with reference to the drawings and specific embodiments.
As illustrated in fig. 1 and 2, a kind of method that the timely bare weight of multi-source satellite soil moisture retrieval is built provided by the invention, packet
Include following steps：Step 1, the bright temperature data of domestic and international high-spatial and temporal resolution is collected, and according to the feature of the bright temperature of different satellites, into
The format conversion of row data, resampling, space splicing, same spatial resolution (0.25 °) brightness temperature for generating unification
Product serial, specially：
Step 11, domestic and international bright temperature data is collected；
Step 12, the format of different satellite bright temperature datas is different, carries out Data Format Transform, is uniformly converted to HDF5；
Step 13, the spatial resolution of different satellite bright temperature datas is different, carries out resampling so that spatial resolution one
It causes；
Step 14, the track of the inswept earth of different satellites is different, needs to carry out space splicing to bright temperature data；
Step 15, the bright temperature temperature product that format is consistent, spatial resolution is consistent is generated；
Step 2, soil moisture microwave remote sensing inverse model is built, bright temperature is carried out and is converted with emissivity, extract microwave radiation
The grid emissivity one by one of meter scanning track, specially：
Step 21, using the brightness temperature of microwave radiometer observation soil moisture microwave is built with the relationship of soil moisture
Remote sensing estimation model；TBp=Tu+exp(-τa)×[{TdrSpexp(-2τc)}+{eSpTsexp(-τc)+Tc(1-ωp)[1-exp(-
τc)][1+rSpexp(-τc)] (1)
Wherein：TBpFor brightness temperature, TuFor the uplink radiation of air, TdThe downlink radiation for being air at the top of canopy, τaFor
The optical thickness of air, that subscript p is indicated is polarization mode, TcFor the temperature of vegetation, τcFor the optical thickness factor of vegetation, rSp
=1-eSpFor the reflectivity of soil surface；TsIt is effective physical temperature of earth's surface, ωpFor the single scattering albedo of vegetation.
Step 22, the quasi real time surface temperature and microwave radiometer of satellite remote sensing and the acquisition of real-time weather forecasting model are utilized
The bright temperature of (such as SMAP, SMOS and AMSR2) observation, the grid emissivity one by one of extraction microwave radiometer scanning track, builds
Relational expression under Liru：
γp=e(-τsecθ) (3)
Wherein, TBpFor brightness temperature；T is physical temperature；E is emissivity；Subscript p represents polarization direction, including horizontal pole
Change (H) and vertical polarization (V), τ vegetation opacities, ω single scattering albedos, γ canopy transmissivities,The ground of polarization direction p
Table emissivity, θ are radiometer view angle or incident.
Step 3, in order to improve the extraction to soil moisture, the influence to vegetation and roughness of ground surface is kicked out of and school
Just, specially：
τ=bVWC (4)
In formula：τ is vegetation opacity, and VWC is vegetation water content,For the soil emissivity of polarization direction p, b is
Depending on vegetation pattern, the parameter of microwave frequency, θ is radiometer view angle or incident.
Step 4, using transformed dielectric constant and existing soil water-containing and soil dielectric constant relational model, to soil
Earth it is aqueous it is counter pushed away, to realize soil moisture inverting extraction, specially：
Step 41, soil dielectric constant be associated with emissivity it is counter push away, dielectric constant same polarization emissivity is converted：
In formula, εrUpper soll layer dielectric constant；Horizontal polarization emissivity；Vertical polarization emissivity, θ are radiation
Count view angle or incident.
Step 42, right using transformed dielectric constant and existing soil water-containing and soil dielectric constant relational model
Soil water-containing is counter to be pushed away, and realizes the inverting extraction of soil moisture：
In formula：ρbSoil block volume density；ρsSoil solid particle proportion；mvSoil volumetric water content；εfwFree water dielectric
Constant；εsSoil particle dielectric constant, α, β are empirical index number.
By taking regional as an example, study the bright temperature data of the bright temperature data in area from the whole world, under be downloaded from the official of each satellite
Square website, specially：
Step 1, the bright temperature data of domestic and international high-spatial and temporal resolution is downloaded, and according to the feature of the bright temperature of different satellites, is carried out
The format conversion of data, resampling, space splicing, same spatial resolution (0.25 °) brightness temperature production for generating unification
Product sequence, specially：
Step 11, domestic and international bright temperature data is collected, as shown in Figure 3；
Step 12, the format of different satellite bright temperature datas is different, carries out Data Format Transform, is uniformly converted to HDF5, such as
Shown in Fig. 4；
Step 13, the spatial resolution of different satellite bright temperature datas is different, carries out resampling so that spatial resolution one
It causes；
Step 14, the track of the inswept earth of different satellites is different, needs to carry out space splicing to bright temperature data；
Step 15, the bright temperature temperature product that format is consistent, spatial resolution is consistent is generated, as shown in Figure 5；
Step 2, soil moisture microwave remote sensing inverse model is built, bright temperature is carried out and is converted with emissivity, extract microwave radiation
The grid emissivity one by one of meter scanning track, specially：
Step 21, on the basis of classical τ-ω models, the brightness temperature observed using microwave radiometer is wet with soil
The relationship of degree builds soil moisture microwave remote sensing inverse model；
TBp=Tu+exp(-τa)×[{TdrSpexp(-2τc)}+{eSpTsexp(-τc)+Tc(1-ωp)[1-exp(-τc)][1
+rspexp(-τc)] (1)
Wherein：TBpFor brightness temperature, TuFor the uplink radiation of air, TdThe downlink radiation for being air at the top of canopy, τaFor
The optical thickness of air, that subscript p is indicated is polarization mode, TcFor the temperature of vegetation, τcFor the optical thickness factor of vegetation, rSp
=1-eSpFor the reflectivity of soil surface；TsIt is effective physical temperature of earth's surface, ωpFor the single scattering albedo of vegetation.
Step 22, the quasi real time surface temperature and microwave radiometer of satellite remote sensing and the acquisition of real-time weather forecasting model are utilized
The bright temperature of (such as SMAP, SMOS and AMSR2) observation, the grid emissivity one by one of extraction microwave radiometer scanning track；It is bright
Spend temperature (TB), physical temperature (T), emissivity (e) by following physical equation establish contact：
γp=e(-τsecθ) (3)
In formula：TBpFor brightness temperature；T is physical temperature；E is emissivity；Subscript p represents polarization direction, including horizontal pole
Change (H) and vertical polarization (V), τ vegetation opacities, ω single scattering albedos, γ canopy transmissivities,The ground of polarization direction p
Table emissivity, θ are radiometer view angle or incident.
Step 3, in order to improve the extraction to soil moisture, the influence to vegetation and roughness of ground surface is kicked out of and school
Just, specially：
τ=bVWC (4)
In formula：τ vegetation opacities, VWC vegetation water content,The soil emissivity of polarization direction p, b depend on planting
By type, the parameter of microwave frequency, the view angle of θ radiometers or incident.
Step 4, soil dielectric constant be associated with emissivity it is counter push away, soil dielectric constant and emissivity relationship pass through famous
Fresnel formula is stated, and can be converted to dielectric constant same polarization emissivity, is realized inverting (such as Fig. 6 of soil moisture
It is shown), specially：
Step 41, soil dielectric constant be associated with emissivity it is counter push away, soil dielectric constant passes through famous with emissivity relationship
Fresnel formula state, dielectric constant same polarization emissivity can be converted.
In formula, εrUpper soll layer dielectric constant,Horizontal polarization emissivity,Vertical polarization emissivity, θ radiometers
View angle or incident.
Step 42, right using transformed dielectric constant and existing soil water-containing and soil dielectric constant relational model
Soil water-containing is counter to be pushed away, to realize the inverting extraction of soil moisture.
In formula：ρbSoil block volume density；ρsSoil solid particle proportion；mvSoil volumetric water content；εfwFree water dielectric
Constant；εsSoil particle dielectric constant, α, β are empirical index number.
Claims (4)
1. a kind of multi-source satellite soil moisture retrieval method, which is characterized in that include the following steps：
Step 1, the bright temperature data of multi-source satellite is collected, and obtains the same spatial resolution brightness temperature product sequence of unification
Row；
Step 2, soil moisture microwave remote sensing inverse model is built, bright temperature is carried out and is converted with emissivity, extraction microwave radiometer is swept
Retouch the grid emissivity one by one of track；
Including：
Step 21, soil moisture microwave remote sensing inverse model is built：
TBp=Tu+exp(-τa)×[{TdrSpexp(-2τc)}+{eSpTsexp(-τc)+Tc(1-ωp)[1-exp(-τc)][1+
rSpexp(-τc)] (1)
Wherein：TBpFor brightness temperature, TuFor the uplink radiation of air, TdThe downlink radiation for being air at the top of canopy, τaFor air
Optical thickness, that subscript p is indicated is polarization mode, TcFor the temperature of vegetation, τcFor the optical thickness factor of vegetation, rSp=1-
eSpFor the reflectivity of soil surface；TsIt is effective physical temperature of earth's surface, ωpFor the single scattering albedo of vegetation；
Step 22, the quasi real time surface temperature and microwave radiometer obtained using satellite remote sensing and real-time weather forecasting model is observed
Bright temperature, extraction microwave radiometer scanning track grid emissivity one by one：
γp=e(-τsecθ) (3)
In formula：TBpFor brightness temperature；T is physical temperature；E is emissivity；Subscript p represents polarization direction, including horizontal polarization (H)
With vertical polarization (V), τ vegetation opacities, ω single scattering albedos, γ canopy transmissivities,The earth's surface of polarization direction p emits
Rate, θ are radiometer view angle or incident；
Step 3, the influence to vegetation and roughness of ground surface is rejected and is corrected；
Step 4, soil dielectric constant is converted with emissivity, is associated with instead with soil moisture using transformed dielectric constant
It pushes away, realizes the remote-sensing inversion of soil moisture.
2. a kind of method that the timely bare weight of multi-source satellite soil moisture retrieval is built according to claim 1, which is characterized in that
The step 3 includes：
τ=bVWC (4)
In formula：τ vegetation opacities, VWC vegetation water content,The soil emissivity of polarization direction p, b depend on vegetation class
Type, the parameter of microwave frequency, θ are radiometer view angle or incident.
3. according to a kind of method that the timely bare weight of multi-source satellite soil moisture retrieval is built described in claim 2, feature exists
In the step 4 includes：
Step 41, soil dielectric constant is converted with emissivity：
In formula, εrUpper soll layer dielectric constant,Horizontal polarization emissivity,Vertical polarization emissivity, θ see for radiometer
Angle measurement or incident；
Step 42, using transformed dielectric constant and existing soil water-containing and soil dielectric constant relational model, to soil
It is aqueous it is counter pushed away, to realize soil moisture inverting extraction：
In formula：ρbSoil block volume density；ρsSoil solid particle proportion；mvSoil volumetric water content；εfwFree water dielectric is normal
Number；εsSoil particle dielectric constant, α, β are empirical index number.
4. a kind of method that the timely bare weight of multi-source satellite soil moisture retrieval is built according to claim 3, which is characterized in that
The step 1 includes the following steps：
Step 11, domestic and international bright temperature data is collected；
Step 12, the format of different satellite bright temperature datas is different, carries out Data Format Transform, is uniformly converted to HDF5；
Step 13, the spatial resolution of different satellite bright temperature datas is different, carries out resampling so that spatial resolution is consistent；
Step 14, the track of the inswept earth of different satellites is different, needs to carry out space splicing to bright temperature data；
Step 15, the bright temperature temperature product that format is consistent, spatial resolution is consistent is generated.
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