Method for estimating field reflectance and its components of a film mulched farmland

Abstract

The application discloses a kind of estimation method of field reflectivity and its component of mulched farmland, and the MICA model of the application is constructed based on radiation balance theory, by considering the influence of farmland mulching on the process of surface radiation transmission, the total field surface reflectivity model of mulched farmland is constructed;It is the model that links the total reflectivity of mulched farmland surface, crown layer surface reflectivity, bare soil surface reflectivity and mulching soil surface reflectivity etc.Four components, it can accurately estimate the most complex crown layer surface reflectivity by knowing three solutions one;And the estimation method of the application has the characteristics of few parameters, simple principle, strong operability, therefore has good applicability, can provide theoretical basis for improving the applicability of existing land surface model in this typical complex surface of mulched farmland, so as to provide scientific basis for more accurately quantifying the influence of mulched farmland on regional climate.

Description

Technical Field

[0001] This invention relates to the field of micrometeorology and land surface process research, specifically to a method for estimating the field reflectance and its components in mulched farmland. Background Technology

[0002] Farmland mulching has been widely adopted in arid regions of my country due to its significant water-saving and entropy-preserving effects. However, farmland mulching also significantly alters surface reflectivity, affecting surface radiation transmission and energy balance, thus having a significant impact on regional climate. The shortwave radiation transmission process of mulched farmland is extremely complex. Its total surface reflectivity is comprehensively affected by the continuously developing surface reflectivity of vegetation canopy, mulched soil surface, and bare soil surface. Furthermore, the contributions of vegetation canopy, mulched soil surface, and bare soil surface to the total surface reflectivity differ at different stages of vegetation growth. Existing research indicates that: (1) Regarding the overall field reflectance of plastic-covered farmland, there is currently no physical-process-based mechanistic model that considers the influence of plastic mulch on the radiation transfer process (Sellers PJ Canopy Reflectance, Photosynthesis and Transpiration [J]. International Journal of Remote Sensing, 1985, 6(8): 1335-1372.). Although some empirical models exist, they require parameter calibration and are therefore difficult to apply to different regions (Yang Qidong, Zuo Hongchao, Xiao Xia, Wang Shujin, Chen Bolong, Chen Jiwei. Modelling the Effects of Plastic Mulch On Water, Heat and Co2 Fluxes Over Cropland in an Arid Region [J]. Journal of (2) For the components of field reflectance of mulched farmland, there is no model that can simultaneously simulate the components of field reflectance of mulched farmland (including canopy surface reflectance, mulched soil surface reflectance, and bare soil surface reflectance). This will have an adverse impact on the study of the mechanism of land surface processes in mulched farmland, the development of land surface models, and the regional rational allocation of agricultural water resources. Summary of the Invention

[0003] Therefore, based on the above background, this invention constructs a computational model for accurately estimating the total reflectance and its components in mulched farmland, based on the principle of radiation balance and farmland micrometeorology. This model links four components: total surface reflectance of mulched farmland, canopy surface reflectance, mulched soil surface reflectance, and bare soil surface reflectance. The fourth component can be solved by accurately solving any three of these four components. For example, the most complex canopy surface reflectance can be determined by accurately solving the total surface reflectance of mulched farmland, the mulched soil surface reflectance, and the bare soil surface reflectance. This method can accurately reflect the influence of the vegetation canopy surface, the mulched soil surface, and the bare soil surface on the total surface reflectance of mulched farmland with vegetation growth, as the canopy continues to develop, and can accurately assess the contribution of each component to the total surface reflectance.

[0004] The technical solution provided by this invention is as follows:

[0005] A method for estimating the field reflectance and its components in mulched farmland includes the following steps:

[0006] Step 1: Collect micro-meteorological data and crop growth data of the mulched farmland. The micro-meteorological data and crop growth data include:

[0007] Total field reflectance α and soil moisture content θ under the film during the growing season in mulched farmland m Soil moisture content θ of bare soil between membranes b Plant canopy height H c and leaf area index L T ;

[0008] Soil moisture content θ of bare soil during the non-growing season b and the surface reflectance α of bare soil b ;

[0009] Step 2: Based on the radiation balance theory and farmland micrometeorology theory, establish a link between the total field reflectance α and the canopy surface reflectance α. c α, the surface reflectance of the covered soil m and the surface reflectance α of bare soil b MICA, a comprehensive model of surface reflectance in four parts of mulched farmland;

[0010] Step 3: Using the data collected in Step 1, calibrate some parameters of the MICA model constructed in Step 2 to reduce the simulation error of the total surface reflectance and its components of mulched farmland.

[0011] Step 4: Input the farmland micro-meteorological and crop growth data collected in Step 1 into the integrated surface reflectance model MICA for mulched farmland established in Steps 2 and 3 to simulate and calculate the total surface reflectance α and canopy surface reflectance α during the growing season of mulched farmland.c α, the surface reflectance of the covered soil m and the surface reflectance α of bare soil b Four parts.

[0012] Furthermore, in step 1, the micro-meteorological data and crop growth data of the mulched farmland during the growing season are categorized according to different stages, as follows:

[0013] Phase 1: No plastic film mulch and no plant growth:

[0014] At this point, the total reflectance in the field consists only of the reflectance of the bare soil surface:

[0015] α=α b ;

[0016] Second stage: There is mulch film coverage, but no plant growth; or the canopy is very small in the early stages of vegetation growth, with canopy coverage close to 0.

[0017] At this point, the total reflectance in the field consists of the reflectance of the covered soil surface and the reflectance of the bare soil surface:

[0018] α=f m ·α m +(1-f m )·α b ;

[0019] Where f m The proportion of farmland covered with plastic film;

[0020] Stage 3: There is mulch film coverage, and the canopy is continuously developing but has not yet completely covered the ground surface; or the canopy coverage is greater than 0 and less than 1.

[0021] At this time, the total field reflectance consists of the reflectance of the covered soil surface, the reflectance of the bare soil surface, and the reflectance of the canopy surface;

[0022] Stage 4: Covered with plastic film, with the canopy completely covering the ground surface; or the canopy coverage is approximately equal to 1.

[0023] At this point, the total reflectance in the field consists only of the reflectance of the vegetation canopy surface:

[0024] α=α c .

[0025] Furthermore, the specific steps for step 2 are as follows:

[0026] Step 2.1, the theoretical assumptions underlying the establishment of the MICA (Micro-Morphological Analysis) model for the surface reflectance of mulched farmland are as follows:

[0027] (1) There are only three reflective surfaces in the mulched farmland: the canopy surface, the mulched soil surface, and the bare soil surface;

[0028] (2) When multiple interactive reflections can be ignored, the reflectivities of the three reflecting surfaces are independent of each other;

[0029] Step 2.2: Under the given assumptions, construct the MICA model based on the radiation balance theory.

[0030] Solar shortwave radiation (DSR) reaching the height of the canopy in mulched farmland is reflected by the canopy (USR). c Absorb DSR a and transmission DSR τ The total shortwave radiation (USR) reflected from the surface of mulched farmland is composed of canopy reflections (USR). c USR (Ultra-Reflective Surface) m and bare soil reflection USR b Based on the shortwave radiation balance equation, we can obtain the following:

[0031] DSR = USR c +DSR a +DSR τ (1)

[0032] USR = USR c +USR m +USR b (2)

[0033] Among them, solar shortwave radiation (DSR) that penetrates from the canopy to the Earth's surface. τ With film ratio f m Distribution on covered surfaces and bare soil surfaces, namely:

[0034] DSR τm =DSR τ ·f m (3)

[0035] DSR τb =DSR τ ·(1-f m (4)

[0036] Therefore, the total surface reflectance of mulched farmland can be expressed as:

[0037]

[0038] Wherein, α is the total surface reflectance of the covered farmland; The reflectivity of the canopy surface; The reflectivity of the covered surface; The reflectance of bare soil surface; Let be the surface transmittance; E be the extinction coefficient; and L be the leaf area index. After substitution, the above formula can be expressed as:

[0039] α=α c +α m ·f m ·τ+α b ·(1-f m )·τ (6)

[0040] Therefore, a model was constructed to represent the relationship between the total field reflectance and its components in mulched farmland, namely the MICA model.

[0041] Step 2.3: Transform formula (6) to determine the expression forms of total field reflectance, mulched soil surface reflectance, and bare soil surface reflectance to calculate canopy surface reflectance;

[0042] The deformed expression of canopy surface reflectance calculated by the MICA model is as follows:

[0043] α c =α-α m ·τ·f m -α b ·τ·(1-f m (7)

[0044] Furthermore, the expression of the total field reflectance can be determined using the modified two-stream transport model (MTS), as follows:

[0045] To account for the impact of the film covering on the total surface reflectance, the boundary conditions for the MTS model are set as follows:

[0046] α g '=f m ·α m +(1-f m )·α b (8)

[0047] α g 'Total reflectance of farmland surface taking into account the mulching effect;'

[0048] The analytical expression for calculating the total field reflectance of mulched farmland using the MTS model is as follows:

[0049] α=f b (h1' / σ'+h2'+h3')+f d (h7'+h8') (9)

[0050] Where f b and f d This represents the ratio of direct to scattered incident sunlight, where σ', h2', h3', h7', and h8' are all values ​​that need to be expressed using α. g The calculated parameters are expressed in the following form:

[0051]

[0052]

[0053]

[0054]

[0055] u1'=bc / α g (14)

[0056] Furthermore, the reflectivity of the bare soil surface can be expressed in a linear form, as follows:

[0057] α b =a1θ b +b1 (15)

[0058] Where a1 and b1 are the parameters to be calibrated.

[0059] Furthermore, the method for determining the parameters to be calibrated, a1 and b1, is as follows:

[0060] Using the observed data of bare soil moisture content and bare soil surface reflectance collected in step 1 during the first stage of the growing season, the bare soil surface reflectance estimated by the bare soil surface reflectance parameterization scheme is fitted with the observed values ​​using the least squares method, and the parameters a1 and b1 in the bare soil surface reflectance parameterization scheme are calibrated.

[0061] Furthermore, the reflectance of the covered soil surface is expressed as follows:

[0062] α m =a2θ m +b2 (16)

[0063] Where a2 and b2 are the parameters to be calibrated.

[0064] Furthermore, the method for determining the parameters to be calibrated, a2 and b2, is as follows:

[0065] The soil moisture content and total ground reflectance of the covered soil and the bare soil between the film and the film were collected in step 1 during the second stage of the growing season. The surface reflectance of the covered soil was calculated as the true value of the surface reflectance of the covered soil using the formula for calculating the surface reflectance of the partially covered soil.

[0066] Using the true value and the corresponding time series of the covered soil moisture content, the least squares method is used to fit the estimated surface reflectance of the covered soil surface reflectance parameterization scheme with the true value, and the parameters a2 and b2 in the covered soil surface reflectance parameterization scheme are calibrated.

[0067] Furthermore, the specific calculation process for step 4 is as follows:

[0068] Step 4.1: Input the farmland micro-meteorological and crop growth data collected in Step 1 into the calculation model of the total field reflectance of the mulched farmland established in Step 2, and simulate and calculate the total surface reflectance α of the mulched farmland during the growing season.

[0069] Step 4.2: Using the expressions for the reflectance of the covered soil surface and the reflectance of the bare soil surface, respectively, and combined with the total reflectance α of the farmland surface, the MICA model is used to calculate the reflectance of the canopy surface.

[0070] The beneficial effects of adopting the above technical solution are as follows:

[0071] The MICA model of this invention is based on the radiation balance theory. By considering the influence of farmland mulching on the surface radiation transmission process, a field total surface reflectance model for mulched farmland is constructed. It is a model that links four components: total surface reflectance of mulched farmland, canopy surface reflectance, bare soil surface reflectance, and mulched soil surface reflectance. By knowing three components and solving one, the most complex canopy surface reflectance can be accurately estimated.

[0072] Furthermore, the estimation method of this invention has the characteristics of few parameters, simple principle, and strong operability, thus having good applicability. It can help improve the simulation ability of surface reflectance models with vegetation cover under surface mulching conditions, enhance the understanding of the radiation transfer process of mulched farmland as a typical underlying surface, provide a theoretical basis for improving the applicability of existing land surface models to mulched farmland as a typical complex surface, and thus provide a scientific basis for more accurately quantifying the impact of mulched farmland on regional climate. Attached Figure Description

[0073] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0074] Figure 1 This is a schematic diagram of the MICA model of the present invention;

[0075] Figure 2 The difference in surface reflectance of mulched farmland is shown between the improved dual-stream transport model (MTS) and the traditional dual-stream transport model (TS) in Embodiment 2 of the present invention.

[0076] Figure 3This refers to the changes in the surface reflectance components of the mulched farmland (i.e., canopy surface reflectance, mulched soil surface reflectance, and bare soil surface reflectance) during the growing season in Example 2 of the present invention. Detailed Implementation

[0077] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0078] The invention will now be further described with reference to the accompanying drawings.

[0079] The technical solution of this invention is as follows:

[0080] A method for estimating the field reflectance and its components in mulched farmland includes the following steps:

[0081] Step 1: Collect micro-meteorological data and crop growth data of the mulched farmland. The micro-meteorological data and crop growth data include:

[0082] Total field reflectance α and soil moisture content θ under the film during the growing season in mulched farmland m Soil moisture content θ of bare soil between membranes b Plant canopy height H c and leaf area index L T ;

[0083] Soil moisture content θ of bare soil during the non-growing season b (and the surface reflectance α of bare soil) b ;

[0084] In this embodiment, the non-growing season refers to the period without mulch, where the surface is bare soil, and it is the other stage outside the growing season; the growing season refers to the period with partial mulch covering the ground, and the surface is a strip of alternating mulch and bare soil; there is a crop growth stage: from sowing to harvest.

[0085] It should be noted that the soil moisture content of the bare soil between the films during the growing season and the bare soil during the non-growing season in the above-mentioned mulched farmland is essentially the same, therefore the same label is used for them.

[0086] In this embodiment, the relevant reflectance is collected, which can be done using a radiometer observation method, such as a four-component radiometer (CNR4, USA).

[0087] In this step, the micro-meteorological data and crop growth data of mulched farmland during the growing season are categorized according to different stages, as follows:

[0088] Phase 1: No plastic film mulch and no plant growth:

[0089] At this point, the total reflectance in the field consists only of the reflectance of the bare soil surface:

[0090] α=α b ;

[0091] Second stage: There is mulch film coverage, but no plant growth; or the canopy is very small in the early stages of vegetation growth, with canopy coverage close to 0.

[0092] At this point, the total reflectance in the field consists of the reflectance of the covered soil surface and the reflectance of the bare soil surface:

[0093] α=f m ·α m +(1-f m )·α b ;

[0094] Where f m The proportion of farmland covered with plastic film;

[0095] Stage 3: There is mulch film coverage, and the canopy is continuously developing but has not yet completely covered the ground surface; or the canopy coverage is greater than 0 and less than 1.

[0096] At this time, the total field reflectance consists of the reflectance of the covered soil surface, the reflectance of the bare soil surface, and the reflectance of the canopy surface;

[0097] Stage 4: Covered with plastic film, with the canopy completely covering the ground surface; or the canopy coverage is approximately equal to 1.

[0098] At this point, the total reflectance in the field consists only of the reflectance of the vegetation canopy surface:

[0099] α=α c .

[0100] Step 2: Based on the radiation balance theory and farmland micrometeorology theory, establish a link between the total field reflectance α and the canopy surface reflectance α. c α, the surface reflectance of the covered soil m and the surface reflectance α of bare soil b MICA, a comprehensive model of surface reflectance in four parts of mulched farmland;

[0101] The specific steps in this process are as follows:

[0102] Step 2.1, the theoretical assumptions underlying the establishment of the MICA (Micro-Morphological Analysis) model for the surface reflectance of mulched farmland are as follows:

[0103] (1) There are only three reflective surfaces in the mulched farmland: the canopy surface, the mulched soil surface, and the bare soil surface;

[0104] (2) When multiple interactive reflections can be ignored, the reflectivities of the three reflecting surfaces are independent of each other;

[0105] Step 2.2: Under the given assumptions, construct the MICA model based on the radiation balance theory.

[0106] Solar shortwave radiation (DSR) reaching the height of the canopy in mulched farmland is reflected by the canopy (USR). c Absorb DSR a and transmission DSR τ The total shortwave radiation (USR) reflected from the surface of mulched farmland is composed of canopy reflections (USR). c USR (Ultra-Reflective Surface) m and bare soil reflection USR b Based on the shortwave radiation balance equation, we can obtain the following:

[0107] DSR = USR c +DSR a +DSR τ (1)

[0108] USR = USR c +USR m +USR b (2)

[0109] Among them, solar shortwave radiation (DSR) that penetrates from the canopy to the Earth's surface. τ With film ratio f m Distribution on covered surfaces and bare soil surfaces, namely:

[0110] DSR τm =DSR τ ·f m (3)

[0111] DSR τb =DSR τ ·(1-f m (4)

[0112] Therefore, the total surface reflectance of mulched farmland can be expressed as:

[0113]

[0114] Wherein, α is the total surface reflectance of the covered farmland; The reflectivity of the canopy surface; The reflectivity of the covered surface; The reflectance of bare soil surface; Let be the surface transmittance; E be the extinction coefficient; and L be the leaf area index. After substitution, the above formula can be expressed as:

[0115] α=α c +α m ·f m ·τ+α b ·(1-f m )·τ (6)

[0116] Therefore, a model was constructed to represent the relationship between the total field reflectance and its components in mulched farmland, namely the MICA model.

[0117] Step 2.3: Transform formula (6) to determine the expression forms of total field reflectance, mulched soil surface reflectance, and bare soil surface reflectance to calculate canopy surface reflectance;

[0118] The deformed expression of canopy surface reflectance calculated by the MICA model is as follows:

[0119] α c =α-α m ·τ·f m -α b ·τ·(1-f m (7)

[0120] 1) The expression of the total field reflectance can be determined using the modified two-stream transport model (MTS), as follows:

[0121] In practice, canopy surface reflectance is generally difficult to calculate because the canopy morphology continuously evolves during vegetation growth, and no model can accurately describe the canopy surface reflectance throughout the entire growth process.

[0122] Therefore, according to the MICA model, the total surface reflectance of the mulched farmland, the surface reflectance of bare soil, and the surface reflectance of the mulched soil can be determined first, and then the surface reflectance of the canopy can be estimated by the model transformation formula. In this way, the surface reflectance of the mulched farmland throughout its entire growth period and the changes of its components can be determined.

[0123] Furthermore, this invention considers the impact of mulching on the lower boundary conditions of radiation transmission, and therefore improves the existing surface reflectance model to more accurately estimate the total field reflectance of mulched farmland. The Two Stream (TS) model is commonly used in land surface models to simulate the total reflectance of vegetated surfaces, and its expression is as follows:

[0124]

[0125]

[0126] Among them, I u and I dα and β are the normalized shortwavelength radiation flux densities of the reflected and incident rays, respectively; μ is the incident photon tilt angle; E = G(μ) / μ is the optical path depth of the incident beam per unit leaf area; G(μ) is the relative projected area of ​​the blade unit in the μ direction; ω = α leaf +τ leaf It is the scattering coefficient of the blade, where α leaf It is the leaf surface reflectance, τ leaf is leaf surface transmittance; L is the cumulative leaf area index; B and B0 are the reflectance coefficients of scattered radiation and direct radiation, respectively. The relevant constants are obtained through experimental observation, such as using a spectrophotometer; or from references, such as Dickinson, RE, P.S. Sellers and D.S. Kimes, Albedos of homogeneous semi-infinite canopies: Comparison of two-stream analytic and numerical solutions. Journal of Geophysical Research-Atmospheres, 1987, 92(D4): p.4282-4286.

[0127]

[0128]

[0129] χ is the average blade tilt angle; L The deviation index is the deviation of the leaf tilt angle from the spherical distribution. The average diffuse optical depth per unit leaf area; α s (μ) represents the scattering rate of a single blade.

[0130] For the direct radiative transmission process in the two-stream transmission model (TS), the upper boundary condition of the model is assumed to be: I d =0, L=0; the lower boundary condition of the model is: I u =α g [I d +exp(-EL T )],L=L T For the scattering and radiative transport process in the two-stream transport model (TS), the upper boundary condition of the model is assumed to be: I d =1, L=0; the lower boundary condition of the model is: I u =α g I d L = L T Among them, αg It is the surface reflectance. In the traditional two-stream transmission model, the surface reflectance is often assumed to be the reflectance of the bare soil surface, without considering the impact of the surface being covered with plastic film on the lower boundary conditions of radiation transmission. This is not true for actual covered farmland.

[0131] Therefore, this invention, by changing the lower boundary condition of radiative transfer and providing an analytical solution for the surface reflectivity of mulched farmland, can take into account the influence of mulching on surface reflectivity. That is, for the direct radiative transfer process of the improved dual-stream transport model (MTS), the upper boundary condition of the model is considered to be: I d =0, L=0; the lower boundary condition of the model is: I u =α g '[I d +exp(-EL T )],L=L T For the MTS scattering radiative transfer process, the upper boundary condition of the model is assumed to be: I d =1, L=0; the lower boundary condition of the model is: I u =α g 'I d L = L T Among them, α g 'It is the total reflectance of farmland surface that takes into account the mulch effect (the surface is a strip distribution of mulched and bare soil).

[0132] Considering the impact of the film covering on the total surface reflectance, the boundary conditions for the MTS model are set as follows:

[0133] α g '=f m ·α m +(1-f m )·α b (8)

[0134] α g Total reflectance of farmland surface considering the mulching effect;

[0135] The analytical expression for calculating the total field reflectance of mulched farmland using the MTS model is as follows:

[0136] α=f b (h1' / σ'+h2'+h3')+f d (h7'+h8') (9)

[0137] Where f b and f d This represents the ratio of direct to scattered incident sunlight, where σ', h2', h3', h7', and h8' are all values ​​that need to be expressed using α. g The calculated parameters are expressed in the following form:

[0138]

[0139]

[0140]

[0141]

[0142] u1'=bc / α g (14)

[0143] In specific implementation, the other parameters involved in equations (10) to (14) and their solutions can be found in the following references: ①Sellers, PJ, 1985: Canopy Reflectance, Photosynthesis and Transpiration, Int. J. Remote Sens., 6(8), 1335-1372;

[0144] ②https / / doi.org / 10.1080 / 01431168508948283;

[0145] ③Sellers, PJ, Los, SO, Tucker, CJ, Justice, CO, Dazlich, DA, Collatz, GJ, Randall, DA, 1996: ARevised Land Surface Parameterization (Sib2) for Atmospheric Gcms, Part ⅱ: The Generation of Global Fields of TerrestrialBiophysical Parameters From Satellite Data,J.Climate,9(4),706-737;

[0146] ④https / / doi.org / 10.1175 / 1520-0442(1996)009<0706:ARLSPF>2.0.CO; 2.

[0147] In the traditional two-stream transport model MTS, the boundary conditions for the radiative transport process only consider bare soil. The original lower boundary condition is:

[0148] α g =α b

[0149] Where, α gThis refers to the ground reflectivity.

[0150] In other words, the traditional dual-flow transport model MTS does not take into account the impact of mulching on the total reflectance in the field, and is not suitable for calculating the reflectance related to mulched fields.

[0151] 2) The reflectance of the bare soil surface can be expressed in a linear form, as follows:

[0152] α b =a1θ b +b1 (15)

[0153] Where a1 and b1 are the parameters to be calibrated.

[0154] The method for determining the parameters a1 and b1 to be calibrated is as follows:

[0155] Using the observation data of bare soil moisture content and bare soil surface reflectance collected in step 1 during the first stage of the growing season, the bare soil surface reflectance estimated by the bare soil surface reflectance parameterization scheme (see formula (15)) is fitted with the observed value using the least squares method, and the parameters a1 and b1 in the bare soil surface reflectance parameterization scheme are calibrated.

[0156] In this embodiment, the surface reflectance of bare soil can be observed using a radiometer (e.g., CNR4, Kipp & Zonen, The Netherlands), while the soil moisture content can be observed using a soil volumetric moisture content monitor (e.g., model CS616, Campbell Scientific, Inc., USA).

[0157] 3) The expression form of the reflectance of the covered soil surface is as follows:

[0158] α m =a2θ m +b2 (16)

[0159] Where a2 and b2 are the parameters to be calibrated.

[0160] The method for determining the parameters to be calibrated, a2 and b2, is as follows:

[0161] The soil moisture content and total ground reflectance of the covered soil and the bare soil between the film in the second stage of the growing season were collected in step 1. The surface reflectance of the covered soil was calculated using the formula for calculating the surface reflectance of the partially covered soil (see formula (16)) as the true value of the surface reflectance of the covered soil.

[0162] Using the true value and the corresponding time series of the covered soil moisture content, the least squares method is used to fit the estimated surface reflectance of the covered soil surface reflectance parameterization scheme with the true value, and the parameters a2 and b2 in the covered soil surface reflectance parameterization scheme are calibrated.

[0163] In this embodiment, the surface reflectance of the covered soil can be observed using a radiometer (e.g., CNR4, Kipp & Zonen, The Netherlands), while the soil moisture content can be observed using a soil volumetric moisture content monitor (e.g., model CS616, Campbell Scientific, Inc., USA).

[0164] Step 3: Using the data collected in Step 1, calibrate some parameters of the MICA model constructed in Step 2 to reduce the simulation error of the total surface reflectance and its components of mulched farmland.

[0165] Step 4: Input the farmland micro-meteorological and crop growth data collected in Step 1 into the integrated surface reflectance model MICA for mulched farmland established in Steps 2 and 3 to simulate and calculate the total surface reflectance α and canopy surface reflectance α during the growing season of mulched farmland. c α, the surface reflectance of the covered soil m and the surface reflectance α of bare soil b Four parts.

[0166] The specific calculation process in this step is as follows:

[0167] Step 4.1: Input the farmland micro-meteorological and crop growth data collected in Step 1 into the calculation model of the total field reflectance of the mulched farmland established in Step 2, and simulate and calculate the total surface reflectance α of the mulched farmland during the growing season.

[0168] Step 4.2: Using the expressions for the reflectance of the covered soil surface and the reflectance of the bare soil surface, respectively, and combined with the total reflectance α of the farmland surface, the MICA model is used to calculate the reflectance of the canopy surface.

[0169] Example 2: This example uses surface reflectance and soil moisture data from mulched maize fields at the Shiyang River Experimental Station of China Agricultural University in the arid Northwest region as validation data. Data were collected throughout the maize growing season from 2014 to 2016. Results are shown below. Figures 1 to 3 ,in Figure 2 The results show the difference in surface reflectance of mulched farmland using the dual-stream transport model (MTS) and dual-stream transport model (TS) employed in this invention.

[0170] The constants and their reference values ​​involved in the calculation process of this invention are as follows: Based on experimental observations, a1 and b1 are -1.27 and 0.48 respectively; a2 and b2 are 0.13 and 0.23 respectively; according to literature searches, τ leaf and α leaf The values ​​were 0.2 and 0.3 respectively (Ross, J., 1975: Radiative Transfer in Plant Communities, Vegetation and the Atmosphere, Academic Press, New York); f b and f d They are 0.2 and 0.8 respectively (Wang, Y., 2003: A Comparison of Three Different Canopy Radiation Models Commonly Used in PlantModelling, Funct. Plant Biol., 30(2), 143-152. https / / doi.org / 10.1071 / FP02117).

[0171] Based on actual observations of basic data from mulched farmland, including bare soil moisture content, mulched soil moisture content, and crop leaf area index, the original two-stream transport model (TS) and the improved two-stream transport model (MTS) were used to simulate the surface reflectance (e.g., ...) of mulched farmland throughout its entire growth period. Figure 2 The results were compared with the surface reflectance of mulched farmland observed in experiments. The results show that one of the methods in this invention, the MTS model, can accurately simulate the surface reflectance of mulched farmland, and compared with TS, it significantly improves the simulation results, especially significantly improving the simulation of surface reflectance when crops do not completely cover the ground. Its root mean square error (RMSE, the closer to 0, the higher) decreased from 0.036 to 0.011, and the correlation coefficient (R²) decreased. 2 (The closer to 1 the better) The value was increased from 0.12 to 0.76, resulting in an overall improvement of 80% in simulation accuracy.

[0172] Based on actual observations of basic data from mulched farmland, including the moisture content of bare soil and mulched soil, the surface reflectance of bare soil and mulched soil in mulched farmland throughout the entire growth period is estimated using the parameterized formulas for surface reflectance of bare soil and mulched soil proposed in this invention, along with calibrated parameters. Based on the second aspect of this invention, namely the established correlation formula for surface reflectance and its components in mulched farmland, and combined with the previously calculated surface reflectance of bare soil and mulched soil, the canopy surface reflectance throughout the entire growth period is derived. The changes in surface reflectance of bare soil, mulched soil, and canopy surface reflectance throughout the entire growth period are as follows: Figure 3 As shown, its trend and range of change are consistent with reality, demonstrating the rationality of this method.

[0173] The present invention and its embodiments have been described above. This description is not restrictive, and the accompanying drawings are only one embodiment of the present invention; the actual structure is not limited thereto. In conclusion, if those skilled in the art are inspired by this description and design similar structures and embodiments without departing from the spirit of the invention, such designs should fall within the protection scope of the present invention.

Claims

1. A method for estimating the field reflectance and its components in mulched farmland, characterized in that, It includes the following steps: Step 1: Collect micro-meteorological data and crop growth data of the mulched farmland. The micro-meteorological data and crop growth data include: Total field reflectance during the growing season of mulched farmland α Soil moisture content under the film θ m Soil moisture content of bare soil between membranes θ b Plant canopy height H c Leaf area index L T ; Soil moisture content of bare soil during the non-growing season θ b and the reflectivity of bare soil surface α b ; Step 2: Based on the radiation balance theory and farmland micrometeorology theory, establish a system that can link the total reflectance in the field. α and canopy surface reflectivity α c Surface reflectivity of covered soil α m and the reflectivity of bare soil surface α b MICA, a comprehensive model of surface reflectance in four parts of mulched farmland; Step 3: Using the data collected in Step 1, calibrate some parameters of the MICA model constructed in Step 2 to reduce the simulation error of the total surface reflectance and its components of mulched farmland. Step 4: Input the farmland micro-meteorological and crop growth data collected in Step 1 into the MICA (Made in China) model for surface reflectance of mulched farmland established in Steps 2 and 3 to simulate and calculate the total surface reflectance of mulched farmland during the growing season. α and canopy surface reflectivity α c Surface reflectivity of covered soil α m and the reflectivity of bare soil surface α b Four parts; The specific steps for step 2 are as follows: Step 2.1, the theoretical assumptions underlying the establishment of the MICA (Micro-Morphological Analysis) model for the surface reflectance of mulched farmland are as follows: (1) There are only three reflective surfaces in the mulched farmland: the canopy surface, the mulched soil surface, and the bare soil surface; (2) When multiple interactive reflections can be ignored, the reflectivities of the three reflecting surfaces are independent of each other; Step 2.2: Under the given assumptions, construct the MICA model based on the radiation balance theory. The solar shortwave radiation DSR reaching the mulched farmland canopy height is reflected by the canopy USR c , absorbed DSR a and transmitted DSR τ , and the total shortwave radiation reflected by the mulched farmland surface USR is composed of the canopy reflected USR c , the mulched surface reflected USR m and the bare soil reflected USR b , so according to the shortwave radiation balance equation, the following equation can be obtained: DSR=USR c +DSR a +DSR τ (1) （2） Among them, solar shortwave radiation (DSR) that penetrates from the canopy to the Earth's surface. τ With film ratio f m Distribution on covered surfaces and bare soil surfaces, namely: DSR τm =DSR τ ·f m (3) DSR τb =DSR τ ·(1-f m )(4) Therefore, the total surface reflectance of mulched farmland can be expressed as: in, α The total reflectance of the farmland surface covered with plastic film; The reflectivity of the canopy surface; The reflectivity of the covered surface; The reflectance of bare soil surface; Where E is the surface transmittance, E is the extinction coefficient, and L is the leaf area index. After substitution, the above formula can be expressed as: a = a c +a m ·f m ·t+a b ·(1-f m )·t (6) Therefore, a model was constructed to represent the relationship between the total field reflectance and its components in mulched farmland, namely the MICA model. Step 2.3, transform formula (6) to determine the expression forms of total field reflectance, mulched soil surface reflectance and bare soil surface reflectance to calculate canopy surface reflectance; The deformed expression of canopy surface reflectance calculated by the MICA model is as follows: a c =a-a m ·t·f m -a b ·τ·(1-f m ) (7).

2. The method for estimating the field reflectance and its components of mulched farmland according to claim 1, characterized in that, Step 1 involves classifying the micro-meteorological data and crop growth data of mulched farmland during the growing season according to different stages; these stages are as follows: Phase 1: No plastic film mulch and no plant growth: At this point, the total reflectance in the field consists only of the reflectance of the bare soil surface: α=α b ； Second stage: There is mulch film coverage, but no plant growth; or the canopy is very small in the early stages of vegetation growth, with canopy coverage close to 0. At this point, the total reflectance in the field consists of the reflectance of the covered soil surface and the reflectance of the bare soil surface: α=f m · α m +（ 1-f m ）· α b ； in f m The proportion of farmland covered with plastic film; Stage 3: There is mulch film coverage, and the canopy is continuously developing but has not yet completely covered the ground surface; or the canopy coverage is greater than 0 and less than 1. At this time, the total field reflectance consists of the reflectance of the covered soil surface, the reflectance of the bare soil surface, and the reflectance of the canopy surface; Stage 4: Covered with plastic film, with the canopy completely covering the ground surface; or the canopy coverage is approximately equal to 1. At this point, the total reflectance in the field consists only of the reflectance of the vegetation canopy surface: α=α c 。 3. The method for estimating the field reflectance and its components of mulched farmland according to claim 1, characterized in that, The expression for the total field reflectance can be determined using the modified two-stream transport model (MTS), as follows: To account for the impact of the film covering on the total surface reflectance, the boundary conditions for the MTS model are set as follows: α g ’=f m · α m +（ 1-f m ）· α b （8） α g ’ The total reflectance of farmland surface taking into account the mulching effect; The analytical expression for calculating the total field reflectance of mulched farmland using the MTS model is as follows: α=f b (h1' / s'+h2'+h3')+f d (h7'+h8') (9) Where f b and f d This refers to the ratio of direct to scattered incident sunlight, where σ', h2', h3', h7', and h8' are all values ​​that need to be used. α g The calculated parameters are expressed in the following form: （10） （11） （12） （13） （14）。 4. The method for estimating the field reflectance and its components of mulched farmland according to claim 1, characterized in that, The reflectivity of the bare soil surface can be expressed in a linear form, as follows: （15） Where a1 and b1 are the parameters to be calibrated.

5. The method for estimating the field reflectance and its components of mulched farmland according to claim 4, characterized in that, The method for determining the parameters a1 and b1 to be calibrated is as follows: Using the observed data on bare soil moisture content and surface reflectance collected in step 1 during the first stage of the growing season, the least squares method was used to fit the estimated bare soil surface reflectance of the parameterization scheme with the observed values, thus calibrating the parameters in the bare soil surface reflectance parameterization scheme. a 1 and b 1 .

6. The method for estimating the field reflectance and its components of mulched farmland according to claim 1, characterized in that, The expression of the reflectivity of the covered soil surface is as follows: （16） in, a 2 and b 2 The parameters to be calibrated.

7. The method for estimating the field reflectance and its components of mulched farmland according to claim 6, characterized in that, The method for determining the parameters to be calibrated, a2 and b2, is as follows: The soil moisture content and total ground reflectance of the covered soil and the bare soil between the film and the film were collected in step 1 during the second stage of the growing season. The surface reflectance of the covered soil was calculated as the true value of the surface reflectance of the covered soil using the formula for calculating the surface reflectance of the partially covered soil. Using the true value and the corresponding time series of soil moisture content under film mulch, the least squares method is used to fit the estimated surface reflectance of the film mulch surface reflectance parameterization scheme with the true value, thereby calibrating the parameters in the parameterization scheme. a 2 and b 2 .

8. The method for estimating the field reflectance and its components of mulched farmland according to claim 6, characterized in that, The specific calculation process for step 4 is as follows: Step 4.1: Input the farmland micro-meteorological and crop growth data collected in Step 1 into the calculation model for the total field reflectance of the mulched farmland established in Step 2, and simulate and calculate the total surface reflectance of the mulched farmland during the growing season. α ; Step 4.2: Express the reflectance of the covered soil surface and the reflectance of the bare soil surface separately, and combine them with the total reflectance of the farmland surface. α， The MICA model was used to calculate the reflectivity of the canopy surface.

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