Method and device for obtaining pixel-scale ground truth for surface reflectance products

Abstract

The present invention provides a pixel-scale ground truth acquisition method and device for surface reflectance products, the method comprising: determining the sampling mode of the target site based on the site size of the target site, the sampling mode comprising a secondary sampling mode and an end-member measurement mode; when the sampling mode is determined to be the secondary sampling mode, performing ground object spectrum measurement on the basic sampling unit in the target site to generate the surface reflectance at the pixel scale corresponding to the target site; when the sampling mode is determined to be the end-member measurement mode, performing ground object spectrum measurement on various ground object areas in the target site respectively to generate the surface reflectance at the pixel scale corresponding to the target site; based on the surface reflectance at the pixel scale corresponding to the target site, generating the satellite pixel-scale surface reflectance corresponding to the target site. The pixel-scale ground truth acquisition method for surface reflectance products of the present invention can significantly improve the precision and accuracy of the truth value obtained.

Description

Technical Field

[0001] The present invention relates to the technical field of obtaining ground truth values ​​of surface reflectance, and in particular to a method and device for obtaining ground truth values ​​of surface reflectance products at a pixel scale. Background Art

[0002] Land surface reflectance represents the ability of the surface to reflect solar radiation in a certain direction in a certain band. It is the basis of remote sensing application analysis and is of great significance for studying surface energy balance, crop growth estimation, land feature identification and classification, resource development, water and climate models, etc. It is also an important variable for inverting many remote sensing application model parameters and a key input parameter for inverting many surface geophysical parameters (such as leaf area index, chlorophyll, biomass, soil moisture content, etc.). As the core quantitative remote sensing product, the accuracy of reflectance products will directly or indirectly determine the accuracy of other quantitative remote sensing products.

[0003] With the continuous development of remote sensing technology, remote sensing has gradually changed from traditional "point" measurement to "surface" measurement. The inconsistency of measurement scale will make it difficult to obtain the true value of remote sensing products. In practical applications, due to the non-uniformity of the surface and the fact that most medium and low resolution pixels are mixed pixels, large errors are easily generated during the scale conversion process, which affects the high-precision acquisition of the true value of the surface of remote sensing products and cannot meet the needs of decision-making in various industries for the accuracy of remote sensing inversion of surface parameters. Summary of the invention

[0004] The present invention provides a method and device for obtaining pixel-scale ground truth values ​​for surface reflectance products, so as to solve the defects of low precision and accuracy of surface reflectance data obtained in the prior art, and achieve the acquisition of high-precision and high-accuracy ground truth values ​​of surface reflectance.

[0005] The present invention provides a method for obtaining pixel-scale ground truth values ​​for surface reflectance products, comprising:

[0006] Determining a sampling method of the target site based on the site size of the target site, wherein the sampling method includes a secondary sampling method and an end member measurement method;

[0007] When it is determined that the sampling method is the secondary sampling method, performing ground object spectrum measurement on the basic sampling unit in the target site to generate the surface reflectance at the pixel scale corresponding to the target site;

[0008] When the sampling mode is determined to be the end member measurement mode, performing ground object spectrum measurement on various ground object areas in the target site respectively to generate the ground surface reflectance at the pixel scale corresponding to the target site;

[0009] Based on the surface reflectivity at the pixel scale corresponding to the target site, the satellite pixel scale surface reflectivity corresponding to the target site is generated.

[0010] According to a pixel-scale ground truth acquisition method for a surface reflectance product provided by the present invention, the surface reflectance at the pixel scale corresponding to the target site is generated by performing ground object spectral measurement on the basic sampling unit in the target site, including:

[0011] Acquire multiple sampling points in the target site;

[0012] Determine the basic sampling unit based on the multiple sampling points using a simulated annealing algorithm;

[0013] Conduct ground object spectrum measurement on the standard reference plate to obtain the standard DN value spectrum curve;

[0014] Performing ground object spectrum measurement on the basic sampling unit to obtain a spectrum curve of actual DN value;

[0015] Based on the actual DN value spectrum curve, the standard DN value spectrum curve and the absolute reflectivity of the standard reference plate observed vertically at the target solar irradiation angle, the surface reflectivity at the pixel scale corresponding to the target site is generated.

[0016] According to a pixel-scale ground truth acquisition method for a surface reflectance product provided by the present invention, the surface reflectance at the pixel scale corresponding to the target site is generated based on the actual DN value spectrum curve, the standard DN value spectrum curve and the absolute reflectance of the standard reference plate observed vertically at the target solar irradiation angle, including:

[0017] Generate the surface reflectance at the instrument scale corresponding to the target site based on the actual DN value spectrum curve, the standard DN value spectrum curve and the absolute reflectance of the standard reference plate observed vertically at the target solar irradiation angle;

[0018] Converting the surface reflectance at the instrument scale to the surface reflectance at the basic sampling unit scale;

[0019] The surface reflectance at the basic sampling unit scale is converted into the surface reflectance at the pixel scale.

[0020] According to a pixel-scale ground truth acquisition method for a surface reflectance product provided by the present invention, the surface reflectance at the pixel scale corresponding to the target site is generated by performing surface spectrum measurement on various surface feature areas in the target site respectively, and comprising:

[0021] Performing multiple ground object spectral measurements on the target ground object area to obtain multiple first ground surface reflectivities;

[0022] Taking an average value of the plurality of first surface reflectivities to generate an average spectrum corresponding to the target object area;

[0023] Based on the average spectrum corresponding to the target ground object region and the ratio of the area of ​​the target ground object region to the target site, the surface reflectance at the pixel scale corresponding to the target site is generated.

[0024] According to a pixel-scale ground truth acquisition method for a surface reflectance product provided by the present invention, the surface reflectance at the pixel scale corresponding to the target site is generated based on the surface reflectance at the pixel scale corresponding to the target site, comprising:

[0025] Construct a target model based on uniform scattering characteristics, geometric optical scattering characteristics, and volume scattering characteristics;

[0026] Direction correction is performed on the surface reflectivity at the pixel scale based on the target model to generate the satellite pixel scale surface reflectivity corresponding to the target site at the moment of satellite transit to be verified.

[0027] According to a method for obtaining pixel-scale ground truth of a surface reflectance product provided by the present invention, the sampling method of the target site is determined based on the site size of the target site, including:

[0028] Determining the site size of the target site based on the spatial resolution of the satellite to be verified;

[0029] When the site size is the first target size and the site includes a ground feature, determining that the sampling method of the target site is the secondary sampling method;

[0030] When the site size is the first target size and the site includes multiple ground objects, determining that the sampling method of the target site is the end member measurement method;

[0031] When the site size is the second target size, determining the sampling method of the target site to be the secondary sampling method;

[0032] The first target size is smaller than the second target size.

[0033] The present invention also provides a device for obtaining pixel-scale ground truth values ​​for surface reflectance products, comprising:

[0034] A first processing module, configured to determine a sampling method of the target site based on the site size of the target site, wherein the sampling method includes a secondary sampling method and an end member measurement method;

[0035] A second processing module is used to perform ground object spectrum measurement on the basic sampling unit in the target site under the secondary sampling mode to generate the surface reflectance at the pixel scale corresponding to the target site;

[0036] In the case of the end member measurement method, the spectrum of various ground objects in the target site is measured respectively to generate the surface reflectance at the pixel scale corresponding to the target site;

[0037] The third processing module is used to generate the satellite pixel-scale surface reflectance corresponding to the target site based on the surface reflectance at the pixel scale corresponding to the target site.

[0038] The present invention also provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, a pixel-scale ground truth acquisition method for a surface reflectance product as described in any one of the above methods is implemented.

[0039] The present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements a pixel-scale ground truth acquisition method for a surface reflectance product as described in any one of the above.

[0040] The present invention also provides a computer program product, comprising a computer program, which, when executed by a processor, implements any of the above-mentioned methods for obtaining pixel-scale ground truth values ​​for surface reflectance products.

[0041] The pixel-scale ground truth acquisition method and device for surface reflectance products provided by the present invention can generate satellite pixel-scale surface reflectance true values ​​of different precisions based on different site sizes by adopting different sampling methods for sites of different site sizes, thereby significantly improving the precision and accuracy of the obtained true values. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0043] Figure 1 It is one of the flow charts of the method for obtaining the pixel-scale ground truth value of the surface reflectance product provided by the present invention;

[0044] Figure 2This is the second flow chart of the method for obtaining pixel-scale ground truth values ​​of surface reflectance products provided by the present invention;

[0045] Figure 3 This is the third flow chart of the method for obtaining pixel-scale ground truth values ​​of surface reflectance products provided by the present invention;

[0046] Figure 4 It is one of the principle schematic diagrams of the method for obtaining the pixel-scale ground truth value of the surface reflectance product provided by the present invention;

[0047] Figure 5 This is the second principle schematic diagram of the method for obtaining pixel-scale ground truth values ​​of surface reflectance products provided by the present invention;

[0048] Figure 6 This is the third principle schematic diagram of the method for obtaining pixel-scale ground truth values ​​of surface reflectance products provided by the present invention;

[0049] Figure 7 This is the fourth principle schematic diagram of the method for obtaining pixel-scale ground truth values ​​for surface reflectance products provided by the present invention;

[0050] Figure 8 It is a schematic diagram of the structure of a device for obtaining ground truth at a pixel scale for a surface reflectance product provided by the present invention;

[0051] Fig. 9 It is a structural schematic diagram of the electronic device provided by the present invention. DETAILED DESCRIPTION

[0052] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the drawings of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0053] Combine the following Figures 1 to 8 The present invention describes a pixel-scale ground truth acquisition method for surface reflectance products.

[0054] like Figure 1 As shown, the method for obtaining pixel-scale ground truth values ​​for surface reflectance products includes: step 110, step 120 and step 130.

[0055] Step 110: Determine a sampling method of the target site based on the site size of the target site, where the sampling method includes a secondary sampling method and an end member measurement method;

[0056] In this step, the target site is a site for performing spectrum measurement of ground objects when verifying the satellite to be verified.

[0057] Different target sites correspond to different areas, and the area of ​​the target site is determined based on the spatial resolution of the satellite to be verified.

[0058] It is understandable that the higher the spatial resolution of the satellite to be verified (ie, the smaller the minimum distance between two adjacent objects that can be identified), the smaller the area of ​​the corresponding target site.

[0059] The sampling methods corresponding to different target sites may be the same or different.

[0060] Among them, the sampling methods include two-level sampling method and end-member measurement method.

[0061] The secondary sampling method is to conduct a unified spectrum measurement of the ground objects in the target site area;

[0062] The end-member measurement method is to perform spectrum measurement on various types of ground objects in the target site.

[0063] For the end-member measurement method, the corresponding target site should include at least two types of ground objects.

[0064] Step 120: When the sampling mode is determined to be the secondary sampling mode, the spectrum of the ground object is measured for the basic sampling unit in the target site to generate the surface reflectance at the pixel scale corresponding to the target site;

[0065] When the sampling method is determined to be the end-member measurement method, the spectrum of various ground objects in the target site is measured respectively to generate the surface reflectance at the pixel scale corresponding to the target site;

[0066] In this step, the picture element is also called pixel point or pixel point, that is, the image unit (picture element), which is the smallest unit that constitutes the digital image. In remote sensing data acquisition, such as scanning imaging, it is the smallest unit for the sensor to scan and sample the ground scene; in digital image processing, it is the sampling point when scanning and digitizing the analog image, and is the basic unit that constitutes the remote sensing digital image.

[0067] Land features refer to fixed objects on the earth's surface, including those formed naturally and artificially. They generally refer to relatively fixed objects on the earth's surface. For example, land features in farmland can include but are not limited to bare soil and various crops.

[0068] The surface reflectance at the pixel scale corresponding to the target site is the measured reflectance of the ground corresponding to the target site.

[0069] The implementation process of step 120 is described below from two perspectives.

[0070] Primary and secondary sampling methods

[0071] In some embodiments, performing ground object spectral measurement on basic sampling units in a target site to generate surface reflectance at a pixel scale corresponding to the target site includes:

[0072] Acquire multiple sampling points in the target site;

[0073] The simulated annealing algorithm is used to determine the basic sampling unit based on multiple sampling points;

[0074] Conduct ground object spectrum measurement on the standard reference plate to obtain the standard DN value spectrum curve;

[0075] Conduct spectrum measurement of ground objects on basic sampling units to obtain spectrum curve of actual DN value;

[0076] Based on the actual DN value spectral curve, the standard DN value spectral curve and the absolute reflectivity of the standard reference plate observed vertically at the target solar irradiation angle, the surface reflectivity at the pixel scale corresponding to the target site is generated.

[0077] In this embodiment, the sampling point is an initial sampling point, and the number of the initial sampling points is multiple. By adjusting the position of one or more of the multiple initial sampling points, a new layout position is generated to determine the basic sampling unit.

[0078] It can be understood that there may be one or more basic sampling units.

[0079] The number of initial sampling points can be any number, such as 5, 9 or 10.

[0080] The initial sampling point can be determined by the systematic 3×3 or 5-point cross sampling method.

[0081] After obtaining a plurality of initial sampling points, a basic sampling unit can be determined based on the plurality of sampling points by using a simulated annealing algorithm, so that the determined basic sampling unit is an optimal sampling point.

[0082] Simulated annealing sampling uses multi-view high-resolution satellite images as reference data and uses the simulated annealing algorithm to determine the location of the basic sampling unit through the reference images. When the number of sampling points is N, the sum of the relative errors of the sampling points on the multi-view reference images is used as the objective function;

[0083]

[0084] Where, sumRE is the objective function, n is the number of reference images (i.e., the number of sampling days); μ iis the mean value of all pixels in the i-th reference image; μSample i is the mean value of the sampling points of the i-th reference image.

[0085] The initial solution is set as N random sampling points, and a point is randomly selected from the N sampling points to change its position to generate a new solution; the loop is iterated until the conditions are met to obtain the sampling point layout with the smallest sampling error (that is, the sum of the relative errors of the new sampling points on the multi-view reference images), which is the optimized basic sampling unit position.

[0086] like Figure 3 As shown, the specific steps of determining the basic sampling unit using the simulated annealing algorithm are as follows:

[0087] 1. Determine the number of sampling points N in the experimental site, and set the cooling schedule of the simulated annealing algorithm: the initial control parameter T = 10 × N, the number of inner loop iterations iter = 200, the control parameter attenuation function is f = 0.99 × T, and the algorithm termination condition is T ≤ 0.001.

[0088] Assume that the objective function of simulated annealing optimization is F(X)=sumRE, where X is a sample point set, and the initial solution of the sample point set is X0; the function that generates a new solution is perturb(X).

[0089] 2. Calculate the mean values ​​μ1…μ of n images respectively n ; Among them, n is used to represent the number of sampling days, μ n is the mean value of the image on day n;

[0090] 3. Generate new solution X new =perturb(X0) where X0 is the initial solution of the sample point set;

[0091] 4. Calculate F1 = F(X0), F2 = F(X new ) and ΔF=F2-F1, where F1 is the objective function value corresponding to the initial solution and F2 is the objective function value corresponding to the new solution.

[0092] If ΔF<0, accept the new solution X new , that is, X0=X new ;

[0093] If ΔF>0, generate a random number r. If r <e (-ΔF / kT) =200, accept the new solution, that is, X0 = X new ;

[0094] Otherwise keep X0 unchanged.

[0095] 5. Determine whether the number of new solutions generated at temperature T is 200 or more. If not, repeat steps 3 and 4. If so, set T = 0.99 × T.

[0096] 6. Determine whether T satisfies the condition T≤0.001. If not, repeat steps 3, 4, and 5. If so, terminate the algorithm and output X0 and F(X0).

[0097] The position of the sampling point corresponding to the output X0 is the position corresponding to the basic sampling unit, such as Figure 4-Figure 6 shown.

[0098] After the basic sampling unit is determined, the spectral sampling points can be further determined from the basic sampling unit to perform spectrum measurement of ground objects.

[0099] The spectrum sampling point is the specific location used to measure the spectrum of an object.

[0100] The spectrum sampling points can be generated randomly or determined by the cross sampling method.

[0101] Continue to refer Figure 4-Figure 6 , taking the cross sampling method as an example, the process of determining the spectrum sampling points is explained.

[0102] The cross sampling method is commonly used with the five-point sampling method, which first determines the midpoint of the diagonal as the central sampling point, and then selects four points on the diagonal that are equidistant from the central sampling point as spectral sampling points.

[0103] After determining the spectrum sampling points in the basic sampling unit, the spectrometer can be used to perform multiple spectrum measurements on the spectrum sampling points, and the measured results are used as the actual DN value spectrum curve.

[0104] Among them, DN is the brightness value (Digital Number) of the remote sensing image pixel.

[0105] It should be noted that before the actual measurement, a spectrometer is required to perform a spectrum measurement on a standard reference plate (such as a reference white plate), and the measured result is used as a standard DN value spectrum curve.

[0106] The standard DN value spectrum curve is used to characterize the reflectivity when there is no interference from ground objects and other measurement parameters are the same.

[0107] like Figure 2 As shown, in some embodiments, based on the actual DN value spectrum curve, the standard DN value spectrum curve and the absolute reflectivity of the standard reference plate observed vertically at the target solar irradiation angle, generating the surface reflectivity at the pixel scale corresponding to the target site may include:

[0108] Based on the actual DN value spectrum curve, the standard DN value spectrum curve and the absolute reflectance of the standard reference plate observed vertically at the target solar irradiation angle, the surface reflectance at the instrument scale corresponding to the target site is generated;

[0109] Convert the surface reflectance at the instrument scale to the surface reflectance at the basic sampling unit scale;

[0110] Convert the surface reflectance at the basic sampling unit scale to the surface reflectance at the pixel scale.

[0111] For example, the formula:

[0112]

[0113] Generate the surface reflectance at the instrument scale corresponding to the target site, where ρ g is the surface reflectivity at the instrument scale corresponding to the target site, V g (λ) is the actual DN value spectrum curve, V p (λ) is the standard DN value spectrum curve, ρ p (θ) is the absolute reflectivity of the standard reference plate observed vertically when the solar irradiation angle is θ.

[0114] The surface reflectivity ρ at the instrument scale corresponding to the target site is obtained g After that, the surface reflectivity ρ at the instrument scale corresponding to the target site can be calculated. g By performing scale conversion, the surface reflectance at the pixel scale corresponding to the target site can be generated.

[0115] In some embodiments, scaling the surface reflectance at the instrument scale corresponding to the target site may include:

[0116] Convert the surface reflectance at the instrument scale to the surface reflectance at the basic sampling unit scale;

[0117] Convert the surface reflectance at the basic sampling unit scale to the surface reflectance at the pixel scale.

[0118] In this embodiment, the surface reflectance at the instrument scale is converted to the surface reflectance at the basic sampling unit scale by averaging the five spectra measured in the basic sampling unit, using the formula:

[0119]

[0120] To generate the surface reflectance at the basic sampling unit scale, where ρ gi is the i-th reflectance measurement result in the basic sampling unit (i.e., the surface reflectance at the instrument scale corresponding to the i-th spectrum).

[0121] Continue to refer Figure 2 When converting the surface reflectance at the basic sampling unit scale to the surface reflectance at the pixel scale, it can be done in any of the following ways.

[0122] First, conversion by arithmetic mean method

[0123] In this embodiment, the surface reflectance at the basic sampling unit scale corresponding to all basic sampling units in the target site may be arithmetic averaged, such as by the formula:

[0124]

[0125] Converted to surface reflectance at the pixel scale, where ρ pixel is the surface reflectance at the pixel scale corresponding to the target site, and n is the number of corresponding basic sampling units in the target site, which is determined by the sampling method; is the surface reflectance at the basic sampling unit scale corresponding to the i-th basic sampling unit.

[0126] Second, conversion by weighted average method

[0127] In this embodiment, the surface reflectance at the basic sampling unit scale corresponding to all basic sampling units in the target site can be weighted averaged according to certain mathematical rules to obtain the pixel-scale surface reflectance, for example, by the formula:

[0128]

[0129] Converted to surface reflectance at the pixel scale, where k i is the weight value corresponding to the i-th basic sampling unit, ρ pixel is the surface reflectance at the pixel scale corresponding to the target site, N is the total number of basic sampling units in the target site, is the surface reflectance at the basic sampling unit scale corresponding to the i-th basic sampling unit; is the gray value corresponding to the i-th basic sampling unit in the reference image; It is the gray value corresponding to all pixels in the reference image, which can be represented by the mean value of all pixels of the target site corresponding to the reference image.

[0130] In the actual implementation process, the gray value and All can be obtained from high-resolution (2-meter) satellite images.

[0131] Third, conversion by transferring truth value

[0132] In this embodiment, the surface reflectance at the pixel scale can be obtained by constructing a linear relationship between the grayscale value of the high-resolution reference image and the surface reflectance at the basic sampling unit scale corresponding to the basic sampling unit.

[0133] The specific steps are as follows:

[0134] First, the surface reflectance at the basic sampling unit scale corresponding to multiple basic sampling units and the corresponding grayscale value in the high-resolution image are obtained. The grayscale value is used as the independent variable and the surface reflectance is used as the dependent variable. The linear regression relationship between the two is established by the least squares method, such as through the formula:

[0135]

[0136] Construct a linear regression relationship between the two, where is the surface reflectance at the basic sampling unit scale corresponding to the i-th basic sampling unit in the target site; is the gray value corresponding to the i-th basic sampling unit in the target site in the high-resolution (2-meter) satellite image; a and b are the calibration coefficients to be inverted, which can be obtained using the least squares method.

[0137] Then, the linear relationship of "gray value-reflectivity" is calculated to convert the pixel grayscale mean of the target site corresponding to the high-resolution image into the surface reflectivity at the pixel scale, such as through the formula:

[0138]

[0139] Among them, ρ pixel is the surface reflectance at the pixel scale corresponding to the target site, is the mean value of all pixels of the high-resolution (2 m) satellite image of the target site, and a and b are the calibration coefficients to be inverted.

[0140] 2. End member measurement method

[0141] In some embodiments, the ground object spectrum measurement is performed on various ground object areas in the target site to generate the ground surface reflectance at the pixel scale corresponding to the target site, including:

[0142] Performing multiple ground object spectral measurements on the target ground object area to obtain multiple first ground surface reflectivities;

[0143] Taking an average value of a plurality of first surface reflectivities to generate an average spectrum corresponding to the target object area;

[0144] Based on the average spectrum corresponding to the target object area and the proportion of the target object area to the target site, the surface reflectance at the pixel scale corresponding to the target site is generated.

[0145] In this embodiment, the target feature area is an area where any type of features in the target site are located.

[0146] There may be two or more types of features in the target site.

[0147] In some embodiments, a site including two types of features may be selected as a target site to improve the precision and accuracy of subsequent measurement results.

[0148] For example, in the process of determining the target site, by judging and classifying the types of land features in the site, sites containing two types of land features are retained, and sites containing three or more types of land features are excluded.

[0149] It should be noted that different types of land features must be clearly distinguished.

[0150] For example, when the target site is a corn planting site, the two land feature types of the target site may be corn and bare soil; for another example, when the target site is a Gobi desert, the two land feature types of the target site may be Gobi desert and camel thorn.

[0151] The target object region may include one or more spectral sampling points.

[0152] The first surface reflectance is the surface reflectance corresponding to any spectral sampling point in the target object area.

[0153] like Figure 7 As shown, this embodiment is described by taking the target site as a corn planting site as an example.

[0154] During the actual implementation process, multiple spectral sampling points in the corn area are measured for multiple spectral measurements to obtain multiple first surface reflectances corresponding to the corn (ground feature 1) area; multiple spectral sampling points in the bare soil area are measured for multiple spectral measurements to obtain multiple first surface reflectances corresponding to the bare soil (ground feature 2) area.

[0155] An average value is taken for a plurality of first surface reflectances corresponding to the corn region to generate an average spectrum corresponding to the corn region; an average value is taken for a plurality of first surface reflectances corresponding to the bare soil region to generate an average spectrum corresponding to the bare soil region.

[0156] Based on the average spectrum corresponding to the corn area and the ratio of the area of ​​the corn area to the total area of ​​the target site, the surface reflectance at the pixel scale corresponding to the corn area is generated; based on the average spectrum corresponding to the bare soil area and the ratio of the area of ​​the bare soil area to the total area of ​​the target site, the surface reflectance at the pixel scale corresponding to the bare soil area is generated.

[0157] In the actual implementation process, the ratio of the area of ​​the target object region to the total area of ​​the target site can be obtained by the UAV.

[0158] The surface reflectance at the pixel scale corresponding to the corn area and the surface reflectance at the pixel scale corresponding to the bare soil area are summed up to generate the surface reflectance at the pixel scale corresponding to the target site.

[0159] In some embodiments, the formula:

[0160]

[0161] Determine the average spectrum corresponding to the target area, where ρ i is the average spectrum corresponding to the i-th ground feature area (i.e., the target ground feature area); ρ gp is the result of the p-th reflectivity measurement corresponding to the ith type of ground object (i.e., the first surface reflectivity generated by the p-th reflectivity measurement); n is the number of spectral measurements of each ground object (i.e., the number of spectral sampling points).

[0162] In some embodiments, the number of spectral measurements for each ground object should be no less than 25 times.

[0163] According to the area ratio of each object in the drone reference image, the surface reflectance at the pixel scale corresponding to the target area is obtained. For example, the formula can be used:

[0164] ρ pixel =k1ρ1+k2ρ2

[0165] Determine, where ρ pixel is the surface reflectance at the pixel scale corresponding to the target site, ρ i is the average spectrum corresponding to the i-th ground feature area (i.e., the target ground feature area); k i is the area ratio of the i-th type of landform in the target site, and k1+k2=1.

[0166] In this step, by adopting different sampling methods for sites of different site sizes to measure reflectance, surface reflectance at pixel scales of different precisions can be generated based on different site sizes, thereby significantly improving the accuracy of the true value obtained.

[0167] Step 130: Generate satellite pixel-scale surface reflectance corresponding to the target site based on the surface reflectance at the pixel scale corresponding to the target site.

[0168] In this step, the satellite pixel-scale surface reflectivity is the surface reflectivity at the pixel scale under the satellite observation angle at the time of the satellite passing by to be verified.

[0169] The surface reflectivity at the satellite pixel scale is the true value, that is, the actual value reflected by the measurement under certain time and space (position or state) conditions.

[0170] It can be understood that the satellite pixel-scale surface reflectivity corresponding to the target site includes satellite pixel-scale surface reflectivity at different measurement angles.

[0171] In the actual implementation process, the surface reflectance at the pixel scale generated by step 120 can be directional corrected to generate the satellite pixel scale surface reflectance at the required angle.

[0172] The implementation of this step is described below through a specific embodiment.

[0173] In some embodiments, step 130 may include:

[0174] Construct a target model based on uniform scattering characteristics, geometric optical scattering characteristics, and volume scattering characteristics;

[0175] Based on the target model, the surface reflectivity at the pixel scale is directionally corrected to generate the satellite pixel-scale surface reflectivity corresponding to the target site at the time of satellite transit to be verified.

[0176] In this embodiment, the target model is used to perform directional correction on the measured surface reflectivity at the pixel scale to obtain a simulated value of the surface reflectivity at the moment of satellite transit, that is, the satellite pixel scale surface reflectivity.

[0177] For example, the target model may be a bidirectional reflectance distribution function (BRDF) model.

[0178] In the actual implementation process, a drone equipped with a spectrometer can be used to obtain multi-angle reflectance data at different measurement times, and the reflectance data can be converted into surface reflectance at the pixel scale.

[0179] Then by constructing the BRDF model, the BRDF model can be expressed as:

[0180]

[0181] Where R is the bidirectional reflectivity, K geo is the geometric optics kernel, K vol is the volume scattering core, and all three are solar zenith angles θ s , observation zenith angle θ v and relative azimuth Function of iso Indicates the proportion (weight) of isotropic uniform scattering, f geo represents the proportion (weight) of uniform scattering in all-directional geometric optical scattering, f vol Indicates the proportion (weight) of isotropic scattering.

[0182] Based on the BRDF model established above, the simulated value of the surface reflectivity ρ under the satellite observation angle at the time of satellite transit can be obtained: transit-sate , and its calculation formula is:

[0183]

[0184] Among them, ρ transit-satel is the satellite pixel-scale surface reflectivity corresponding to the target site, θ s is the solar zenith angle corresponding to the time t0 when the satellite to be verified passes by, θ v is the satellite observation zenith angle corresponding to the time t0 when the satellite to be verified passes by. is the relative azimuth corresponding to the time t0 when the satellite to be verified passes.

[0185] It can be understood that through the formula ρ transit-satellite The satellite pixel-scale surface reflectivity corresponding to the target site at any angle can be determined.

[0186] According to the pixel-scale ground truth acquisition method for surface reflectance products provided by an embodiment of the present invention, by adopting different sampling methods for sites of different site sizes, satellite pixel-scale surface reflectance true values ​​of different precisions can be generated based on different site sizes, thereby significantly improving the precision and accuracy of the obtained true values.

[0187] It is understandable that before the actual measurement, the measurement site needs to be screened and determined first.

[0188] The implementation process of step 110 is described below through a specific embodiment.

[0189] In some embodiments, step 110 may include:

[0190] Determine the site size of the target site based on the spatial resolution of the satellite to be verified;

[0191] When the site size is the first target size and includes a type of ground feature, determining the sampling method of the target site as the secondary sampling method;

[0192] When the site size is the first target size and includes multiple ground objects, determining that the sampling method of the target site is an end-member measurement method;

[0193] When the site size is the second target size, the sampling method of the target site is determined to be the secondary sampling method;

[0194] The first target size is smaller than the second target size.

[0195] In this embodiment, the site size of the target site can be represented by the site area or side length.

[0196] A combination of image reference and field investigation can be used to select a suitable experimental site.

[0197] Generally speaking, the lower the spatial resolution of the satellite to be verified (that is, the larger the minimum distance between two adjacent objects that can be identified), the larger the size of the corresponding measurement site.

[0198] In this embodiment, the first target size is a field smaller than 100 meters, and the second target size is a field not smaller than 100 meters, including fields of 100 meters and kilometers.

[0199] For venues that are not less than 100 meters, the sampling method corresponding to the venue will be directly determined as the secondary sampling method.

[0200] For sites smaller than 100 meters, the sampling method corresponding to the site can be further determined based on the heterogeneity of the site.

[0201] Among them, the heterogeneity size is used to characterize the types of land features included in the site. The more types of land features there are, the greater the heterogeneity size.

[0202] When the site includes a single land feature, the sampling method corresponding to the site is determined as the secondary sampling method; when the site includes two or more land features, the sampling method corresponding to the site is determined as the end member measurement method.

[0203] In some embodiments, sites that are smaller than 100 meters and include three or more types of landforms are excluded.

[0204] For example, the site sizes can be divided into four levels based on the spatial resolution of the satellite to be verified:

[0205] (1) High-resolution site: Applicable to satellites to be verified with a spatial resolution of less than 16 m. The site size of the high-resolution site can be a site with a side length of 30-59 m, for example, it can be set to 48 m.

[0206] (2) Medium-resolution site: Applicable to satellites to be verified with a spatial resolution between 16m and 30m. The site size of the medium-resolution site can be a site with a side length of 60-99m, for example, it can be set to 90m;

[0207] (3) Medium and low resolution sites: Applicable to satellites to be verified with a spatial resolution between 30m and 100m. The site size of a medium and low resolution site can be a site with a side length of 100-999m, for example, it can be set to 300m;

[0208] (4) Low-resolution site: Applicable to satellites to be verified with a spatial resolution greater than 100 m. The site size of a low-resolution site can be a site with a side length of 1 km to 5 km, for example, it can be set to 3 km.

[0209] The high-resolution site and the medium-resolution site both correspond to the first target size, and the medium-low resolution site and the low-resolution site both correspond to the second target size.

[0210] For sites less than 100 meters, the size of the site heterogeneity needs to be considered. If the site heterogeneity is small (the site consists of a single feature), a two-level sampling strategy based on the basic sampling unit is adopted, that is, the position of the basic sampling unit is determined by the system 3×3 or 5-point cross sampling method, and then the 5-point cross sampling method is used in the basic sampling unit to measure the feature spectrum;

[0211] If the site heterogeneity is large (the site is composed of multiple land features), the endmember measurement method is used, that is, the spectrum of each land feature is measured, and the drone image of the site is obtained at the same time to calculate the area ratio of each land feature component in the site.

[0212] For sites at the hundred-meter and kilometer levels, a two-level sampling strategy based on basic sampling units is adopted, that is, the position of the basic sampling unit is determined by a simulated annealing algorithm, and then a five-point cross sampling method is used within the basic sampling unit to measure the spectrum of the ground objects.

[0213] Of course, in other embodiments, the size of the venue may be set to other sizes based on actual needs, and the present invention is not limited thereto.

[0214] According to the pixel-scale ground truth acquisition method for surface reflectance products provided by an embodiment of the present invention, the site size of the target site is determined based on the spatial resolution of the satellite to be verified, and on this basis, the sampling method corresponding to the target site is determined in combination with the site size of the target site and the site heterogeneity of the target site; on the one hand, for sites of 100 meters and kilometers, a secondary sampling strategy based on basic sampling units is adopted, thereby simplifying the sampling steps, reducing the sampling difficulty, and making the sampling process easier to implement; on the other hand, for sites less than 100 meters, further based on site heterogeneity, a secondary sampling strategy is adopted for sites composed of a single land object, and a more sophisticated end-member measurement method is adopted for sites composed of multiple land objects, thereby helping to improve the accuracy of the acquired truth value.

[0215] In some embodiments, the method may further include: generating an uncertainty corresponding to the sampling method based on the sampling method.

[0216] In this embodiment, the uncertainty is used to characterize the accuracy of the values ​​generated at each stage under various sampling modes.

[0217] The uncertainty corresponding to the sampling method may include one or more of the following: uncertainty generated in the reflectivity measurement process, uncertainty generated in the scale conversion process, uncertainty generated in the directionality correction process, and total uncertainty in the true value acquisition process.

[0218] Among them, the uncertainty generated in the reflectivity measurement process is the surface reflectivity at the instrument scale corresponding to the target site.

[0219] The uncertainty generated in the scale conversion process includes: the uncertainty generated in the instrument-basic sampling unit scale conversion process, the uncertainty generated in the basic sampling unit-pixel scale conversion process, and the total uncertainty generated in the scale conversion process.

[0220] The uncertainty generated in the directional correction process is the uncertainty corresponding to the satellite pixel-scale surface reflectance corresponding to the reference site.

[0221] The total uncertainty in the true value acquisition process is the overall uncertainty of all steps involved in generating the satellite pixel-scale surface reflectance corresponding to the final target site.

[0222] The calculation methods of various uncertainties are explained below.

[0223] (1) Calculate the uncertainty ε generated during reflectivity measurement meas .

[0224] The uncertainty of reflectivity measurement is related to the whiteboard itself (which can be accurately estimated through laboratory whiteboard calibration) and the degree of standardization of the operator's operating methods during the measurement process.

[0225] Among them, the uncertainty caused by the whiteboard can be expressed by the formula:

[0226] ε refer =1-DN refer / DN stand

[0227] Determine, where ε refer To measure the uncertainty of the white plate, DN refer It is the gray value corresponding to the white plate measured by the spectrometer, DN stand It is the gray value measured by the spectrometer on the standard reference plate.

[0228] The uncertainty of the measurement operation can be expressed as:

[0229]

[0230] Determine, where ε oper is the uncertainty caused by the measurement operation, ρ1 and ρ2 are the reflectances measured continuously by the measurer at the same spectral sampling point.

[0231] The uncertainty generated in the reflectivity measurement process of this method can be expressed by the formula:

[0232] εmeas 2 =ε refer 2 +ε oper 2

[0233] Determine, where ε meas is the uncertainty in the reflectivity measurement process, ε refer is the uncertainty of measuring the white plate, ε oper The uncertainty introduced by the measurement operation.

[0234] (2) Calculate the uncertainty ε generated during the scale conversion process scale .

[0235] For sampling methods based on basic sampling units:

[0236] 1) Calculate the uncertainty ε generated during the instrument-basic sampling unit scale conversion process inst-EsU , using the mean gray value corresponding to each reflectivity in the basic sampling unit The gray value of the basic sampling unit The relative error is expressed as .

[0237] in, The formula can be:

[0238]

[0239] Determine, among which, Respectively, the reflectivity in the basic sampling unit The corresponding grayscale value in the reference image.

[0240] The formula can be:

[0241]

[0242] Determine, where m and n are the number of rows and columns corresponding to the reference image respectively; DN ij is the gray value of the i-th row and j-th column in the reference image; It is the true value of the gray value of the basic sampling unit, which is represented by the mean value of all pixels of the reference image corresponding to the basic sampling unit.

[0243] Then by the formula:

[0244]

[0245] Determine the uncertainty ε generated during the instrument-basic sampling unit scale conversion process inst-ESU ,in, and The grayscale values ​​in the figure are obtained from high-resolution airborne images.

[0246] 2) Calculate the uncertainty ε generated during the basic sampling unit-pixel scale conversion process ESU-pixel :

[0247] The uncertainty generated by the arithmetic mean method in this process can be calculated by taking the mean grayscale value of multiple sampling units in the reference image as The mean gray value of all pixels in the site The relative error can be expressed by the formula:

[0248]

[0249] Determine, among which, is the gray value corresponding to the i-th basic sampling unit in the reference image; is the mean value of pixels covering all sites in the reference image; and The grayscale values ​​in the figure are obtained from high-resolution satellite images.

[0250] The uncertainty generated by the weighted average method in this process comes from the mismatch between the image and the ground measurement point position, which can be specifically expressed by the formula:

[0251]

[0252] Determine, where ρ pixel is the simulated value of the surface reflectance at the pixel scale; ρT pixel is the relative true value of the surface reflectance at the pixel scale;

[0253] Among them, the relative true value of the surface reflectance at the pixel scale can be obtained by the formula:

[0254]

[0255] Determine, among which, is the gray value of the adjacent pixel corresponding to the ith basic sampling unit in the high-resolution satellite image, and N is the number of basic sampling units.

[0256] The uncertainty generated by the transfer truth method in this process also comes from the mismatch between the image and the ground measurement point position, which can be specifically described by the formula:

[0257]

[0258] Determine, where ρ pixel is the simulated value of the surface reflectance at the pixel scale; ρT pixel is the relative true value of the surface reflectance at the pixel scale;

[0259] Among them, the relative true value of the surface reflectance at the pixel scale can be obtained by the formula:

[0260]

[0261] Determine, where a T and b T The surface reflectance of the basic sampling unit and the gray value of the adjacent pixel of the reference image corresponding to the basic sampling unit are obtained by the least square method; is the mean value of all pixels of the high-resolution (2-meter) satellite image corresponding to the site, It is the mean value of all pixels in the high-resolution (2-meter) satellite image corresponding to the site.

[0262] 3) Calculate the total uncertainty ε generated during the scale conversion process scale .

[0263] The specific formula can be:

[0264] ε scale 2 =ε inst-ESU 2 +ε ESU-pixel 2

[0265] Determine, where ε scale is the total uncertainty generated in the scale conversion process, ε inst-ESU is the uncertainty in the instrument-basic sampling unit scale conversion process, ε ESU-pixel It is the uncertainty generated in the process of basic sampling unit-pixel scale conversion.

[0266] For the sampling method based on endmember measurement, the uncertainty generated in the scale conversion process comes from two parts: inside the endmember and between the endmembers.

[0267] The uncertainty within the endmember is represented by the standard deviation of multiple spectra of each endmember, which can be specifically expressed by the formula:

[0268]

[0269] Determine, where n is the number of endmember spectrum measurements; ρ i is the surface reflectivity measured by the end member for the i-th time; ρ i is the average reflectivity of n measurements of the end member.

[0270] The uncertainty between end members comes from the misclassification of end members by airborne reference images, which leads to different area proportions of each end member in the site. The specific formula can be:

[0271]

[0272] Determine, among which, and The pixel-scale surface reflectance is calculated using different airborne reference images (usually a drone image containing the site is taken before and after the reflectance measurement).

[0273] The total uncertainty ε generated during the scale conversion process scale The formula can be:

[0274] ε scal 2 =ε scale-inte 2 +ε scale-exte 2

[0275] Determine, where ε scale is the total uncertainty generated in the scale conversion process, ε scale-inte is the uncertainty within the end member, ε scale-ext is the uncertainty between end members.

[0276] (3) Calculate the uncertainty ε generated during the directional correction process model .

[0277] The specific steps are as follows:

[0278] The errors in the directional correction process mainly come from two sources: sun angle correction error and observation angle correction error, which are caused by changes in the sun angle and inconsistent observation angles, respectively.

[0279] During the ground spectral measurement, the solar zenith angle will change, and the solar radiation will also change accordingly. Therefore, it is necessary to construct a kernel-driven model using the multi-angle reflectance data taken by drones at different times to correct the solar incidence angle of the measured data, and simulate the surface reflectance simulation value ρ under vertical observation conditions at the start measurement time t1, satellite transit time t2, and end measurement time t3. t1 , t2 , t3 .

[0280] The calculation formula for the sun angle correction error is:

[0281]

[0282] Under the same solar radiation conditions, changes in satellite observation angles will also produce different surface reflectivity, so the observation angle needs to be corrected. For satellites with a smaller field of view, the observation angle correction error can be ignored; for satellites with a larger field of view, the error caused by the observation angle correction needs to be considered.

[0283] The calculation formula for the observation angle correction error is:

[0284]

[0285] Among them, ρ vertical is the simulated value of the surface reflectivity at the vertical observation angle at the moment of satellite transit; ρ direcional It is the simulated value of the surface reflectivity under the satellite observation angle at the moment of satellite transit.

[0286] Then, the uncertainty ε corresponding to the target model is model (i.e. the uncertainty generated during the directional correction process) can be expressed as:

[0287] ε model 2 =ε model-sun 2 +ε model-satellit 2

[0288] Among them, ε model-su is the sun angle correction error, ε model-satellit Corrects for observation angle errors.

[0289] (4) ε in the process of calculating the true value total .

[0290] The specific steps are as follows:

[0291] According to the error transfer formula, the total uncertainty can be expressed by the root sum of the squares of the uncertainties generated in each process. The calculation formula is:

[0292] ε total 2 =ε meas 2 +ε scale 2 +ε model 2

[0293] Among them, ε meas is the measurement uncertainty; ε scale is the scale conversion uncertainty, ε model is the uncertainty corresponding to the target model.

[0294] After obtaining the uncertainty, the uncertainty corresponding to the reflectivity data can be outputted at the same time as the reflectivity data corresponding to each step, so as to provide the user with the accuracy corresponding to each data, thereby improving the accuracy of subsequent measurement results.

[0295] The pixel-scale ground truth acquisition method for surface reflectance products provided in an embodiment of the present invention outputs the uncertainty corresponding to the true value while acquiring the true value, and uses the uncertainty to characterize the accuracy and credibility of the true value, thereby helping to improve the precision of the acquired true value.

[0296] The following is a description of a pixel-scale ground truth acquisition device for a surface reflectance product provided by the present invention. The pixel-scale ground truth acquisition device for a surface reflectance product described below and the pixel-scale ground truth acquisition method for a surface reflectance product described above can be referenced to each other.

[0297] like Figure 8 As shown, the pixel-scale ground truth acquisition device for surface reflectance products includes: a first processing module 810, a second processing module 820, a third processing module 830 and a fourth processing module 840.

[0298] A first processing module 810 is used to determine a sampling method of the target site based on the site size of the target site, where the sampling method includes a secondary sampling method and an end member measurement method;

[0299] The second processing module 820 is used to perform ground object spectrum measurement on the basic sampling unit in the target site to generate the surface reflectance at the pixel scale corresponding to the target site when the sampling mode is determined to be the secondary sampling mode;

[0300] The third processing module 830 is used to perform ground object spectrum measurement on various ground object areas in the target site respectively when the sampling method is determined to be the end member measurement method, and generate the ground surface reflectance at the pixel scale corresponding to the target site;

[0301] The fourth processing module 840 is used to generate the satellite pixel-scale surface reflectance corresponding to the target site based on the surface reflectance at the pixel-scale corresponding to the target site.

[0302] According to the pixel-scale ground truth acquisition device for surface reflectance products provided by an embodiment of the present invention, by adopting different sampling methods for sites of different site sizes, satellite pixel-scale surface reflectance true values ​​of different precisions can be generated based on different site sizes, thereby significantly improving the precision and accuracy of the obtained true values.

[0303] In some embodiments, the second processing module 820 may also be used to:

[0304] Acquire multiple sampling points in the target site;

[0305] The simulated annealing algorithm is used to determine the basic sampling unit based on multiple sampling points;

[0306] Conduct ground object spectrum measurement on the standard reference plate to obtain the standard DN value spectrum curve;

[0307] Conduct spectrum measurement of ground objects on basic sampling units to obtain spectrum curve of actual DN value;

[0308] Based on the actual DN value spectral curve, the standard DN value spectral curve and the absolute reflectivity of the standard reference plate observed vertically at the target solar irradiation angle, the surface reflectivity at the pixel scale corresponding to the target site is generated.

[0309] In some embodiments, the second processing module 820 may also be used to:

[0310] Based on the actual DN value spectrum curve, the standard DN value spectrum curve and the absolute reflectance of the standard reference plate observed vertically at the target solar irradiation angle, the surface reflectance at the instrument scale corresponding to the target site is generated;

[0311] Convert the surface reflectance at the instrument scale to the surface reflectance at the basic sampling unit scale;

[0312] Convert the surface reflectance at the basic sampling unit scale to the surface reflectance at the pixel scale.

[0313] In some embodiments, the third processing module 830 may also be used to:

[0314] Performing multiple ground object spectral measurements on the target ground object area to obtain multiple first ground surface reflectivities;

[0315] Taking an average value of a plurality of first surface reflectivities to generate an average spectrum corresponding to the target object area;

[0316] Based on the average spectrum corresponding to the target object area and the proportion of the target object area to the target site, the surface reflectance at the pixel scale corresponding to the target site is generated.

[0317] In some embodiments, the fourth processing module 840 may also be used to:

[0318] Construct a target model based on uniform scattering characteristics, geometric optical scattering characteristics, and volume scattering characteristics;

[0319] Based on the target model, the surface reflectivity at the pixel scale is directionally corrected to generate the satellite pixel-scale surface reflectivity corresponding to the target site at the time of satellite transit to be verified.

[0320] In some embodiments, the first processing module 810 may also be used to:

[0321] Determine the site size of the target site based on the spatial resolution of the satellite to be verified;

[0322] When the site size is the first target size and the site includes a type of feature, determining the sampling method of the target site as the secondary sampling method;

[0323] When the site size is the first target size and the site includes multiple ground objects, determining that the sampling method of the target site is an end-member measurement method;

[0324] When the site size is the second target size, the sampling method of the target site is determined to be the secondary sampling method;

[0325] The first target size is smaller than the second target size.

[0326] Fig. 9 An example of a physical structure diagram of an electronic device is shown in FIG. Fig. 9 As shown, the electronic device may include: a processor 910, a communication interface 920, a memory 930 and a communication bus 940, wherein the processor 910, the communication interface 920 and the memory 930 communicate with each other through the communication bus 940. The processor 910 may call the logic instructions in the memory 930 to execute a pixel-scale ground truth acquisition method for a surface reflectance product, the method comprising: determining a sampling method of the target site based on the site size of the target site, the sampling method including a secondary sampling method and an end-member measurement method; when the sampling method is determined to be the secondary sampling method, performing ground object spectrum measurement on the basic sampling unit in the target site to generate the surface reflectance at the pixel scale corresponding to the target site; when the sampling method is determined to be the end-member measurement method, performing ground object spectrum measurement on various ground object areas in the target site respectively to generate the surface reflectance at the pixel scale corresponding to the target site; based on the surface reflectance at the pixel scale corresponding to the target site, generating the satellite pixel-scale surface reflectance corresponding to the target site.

[0327] In addition, the logic instructions in the above-mentioned memory 930 can be implemented in the form of a software functional unit and can be stored in a computer-readable storage medium when it is sold or used as an independent product. Based on such an understanding, the technical solution of the present invention can be essentially or partly embodied in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc. Various media that can store program codes.

[0328] On the other hand, the present invention also provides a computer program product, which includes a computer program stored on a non-transitory computer-readable storage medium, and the computer program includes program instructions. When the program instructions are executed by a computer, the computer can execute the pixel-scale ground truth acquisition method for the surface reflectance product provided by the above-mentioned methods, and the method includes: based on the site size of the target site, determining the sampling method of the target site, the sampling method includes a secondary sampling method and an end-member measurement method; when the sampling method is determined to be the secondary sampling method, performing ground object spectral measurement on the basic sampling unit in the target site to generate the surface reflectance at the pixel scale corresponding to the target site; when the sampling method is determined to be the end-member measurement method, performing ground object spectral measurement on various ground object areas in the target site respectively to generate the surface reflectance at the pixel scale corresponding to the target site; based on the surface reflectance at the pixel scale corresponding to the target site, generating the satellite pixel-scale surface reflectance corresponding to the target site.

[0329] On the other hand, the present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, is implemented to execute the above-mentioned pixel-scale ground truth acquisition method for surface reflectance products, the method comprising: determining a sampling method for the target site based on the site size of the target site, the sampling method comprising a secondary sampling method and an end-member measurement method; when the sampling method is determined to be the secondary sampling method, performing ground object spectral measurement on the basic sampling units in the target site to generate a surface reflectance at a pixel scale corresponding to the target site; when the sampling method is determined to be the end-member measurement method, performing ground object spectral measurement on various ground object areas in the target site respectively to generate a surface reflectance at a pixel scale corresponding to the target site; based on the surface reflectance at the pixel scale corresponding to the target site, generating a satellite pixel-scale surface reflectance corresponding to the target site.

[0330] The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without paying creative labor.

[0331] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0332] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for obtaining pixel-scale ground truth for surface reflectance products, characterized in that: include: Determining a sampling method of the target site based on the site size of the target site, wherein the sampling method includes a secondary sampling method and an end member measurement method; When it is determined that the sampling method is the secondary sampling method, performing ground object spectrum measurement on the basic sampling unit in the target site to generate the surface reflectance at the pixel scale corresponding to the target site; When the sampling mode is determined to be the end member measurement mode, performing ground object spectrum measurement on various ground object areas in the target site respectively to generate the ground surface reflectance at the pixel scale corresponding to the target site; Based on the surface reflectance at the pixel scale corresponding to the target site, generating the surface reflectance at the satellite pixel scale corresponding to the target site; The step of measuring the ground object spectrum of the basic sampling unit in the target site to generate the ground surface reflectance at the pixel scale corresponding to the target site includes: Acquire multiple sampling points in the target site; Determine the basic sampling unit based on the multiple sampling points using a simulated annealing algorithm; Conduct ground object spectrum measurement on the standard reference plate to obtain the standard DN value spectrum curve; Performing ground object spectrum measurement on the basic sampling unit to obtain a spectrum curve of actual DN value; Generate the surface reflectance at the pixel scale corresponding to the target site based on the actual DN value spectrum curve, the standard DN value spectrum curve and the absolute reflectance of the standard reference plate observed vertically at the target solar irradiation angle; or, Performing multiple ground object spectral measurements on the target ground object area to obtain multiple first ground surface reflectivities; Taking an average value of the plurality of first surface reflectivities to generate an average spectrum corresponding to the target object area; Generate the surface reflectance at the pixel scale corresponding to the target site based on the average spectrum corresponding to the target object area and the ratio of the area of ​​the target object area to the target site; Wherein, determining the sampling method of the target site based on the site size of the target site includes: Determining the site size of the target site based on the spatial resolution of the satellite to be verified; When the site size is the first target size and the site includes a ground feature, determining that the sampling method of the target site is the secondary sampling method; When the site size is the first target size and the site includes multiple ground objects, determining that the sampling method of the target site is the end member measurement method; When the site size is the second target size, determining the sampling method of the target site to be the secondary sampling method; The first target size is smaller than the second target size.

2. The method for obtaining pixel-scale ground truth for surface reflectance products according to claim 1, characterized in that: The generating of the surface reflectance at the pixel scale corresponding to the target site based on the actual DN value spectrum curve, the standard DN value spectrum curve and the absolute reflectance of the standard reference plate observed vertically at the target solar irradiation angle includes: Generate the surface reflectance at the instrument scale corresponding to the target site based on the actual DN value spectrum curve, the standard DN value spectrum curve and the absolute reflectance of the standard reference plate observed vertically at the target solar irradiation angle; Converting the surface reflectance at the instrument scale to the surface reflectance at the basic sampling unit scale; The surface reflectance at the basic sampling unit scale is converted into the surface reflectance at the pixel scale.

3. The method for obtaining pixel-scale ground truth for surface reflectance products according to any one of claims 1 to 2, characterized in that: The step of generating a satellite pixel-scale surface reflectance corresponding to the target site based on the surface reflectance at the pixel-scale corresponding to the target site comprises: Construct a target model based on uniform scattering characteristics, geometric optical scattering characteristics, and volume scattering characteristics; Direction correction is performed on the surface reflectivity at the pixel scale based on the target model to generate the satellite pixel scale surface reflectivity corresponding to the target site at the moment of satellite transit to be verified.

4. A device for executing the pixel-scale ground truth acquisition method for a surface reflectance product according to any one of claims 1 to 3, characterized in that: include: A first processing module, configured to determine a sampling method of the target site based on the site size of the target site, wherein the sampling method includes a secondary sampling method and an end member measurement method; A second processing module is used to perform ground object spectrum measurement on the basic sampling unit in the target site under the secondary sampling mode to generate the surface reflectance at the pixel scale corresponding to the target site; In the case of the end member measurement method, the spectrum of various ground objects in the target site is measured respectively to generate the surface reflectance at the pixel scale corresponding to the target site; The third processing module is used to generate the satellite pixel-scale surface reflectance corresponding to the target site based on the surface reflectance at the pixel scale corresponding to the target site.

5. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the program, the method for obtaining pixel-scale ground truth for a surface reflectance product as described in any one of claims 1 to 3 is implemented.

6. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method for obtaining pixel-scale ground truth for a surface reflectance product as described in any one of claims 1 to 3 is implemented.

7. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the method for obtaining pixel-scale ground truth for a surface reflectance product as described in any one of claims 1 to 3 is implemented.

Images