CN106645037A - Method for detecting heavy metal content of coal gangue filling reclamation reconstruction soil based on high spectrum technology - Google Patents
Method for detecting heavy metal content of coal gangue filling reclamation reconstruction soil based on high spectrum technology Download PDFInfo
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- CN106645037A CN106645037A CN201611010453.8A CN201611010453A CN106645037A CN 106645037 A CN106645037 A CN 106645037A CN 201611010453 A CN201611010453 A CN 201611010453A CN 106645037 A CN106645037 A CN 106645037A
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- G—PHYSICS
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- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
- G01N21/55—Specular reflectivity
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
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Abstract
The invention discloses a method for detecting a heavy metal content of coal gangue filling reclamation reconstruction soil based on a high spectrum technology. The method comprises the steps of performing sampling on site; collecting a sample spectrum curve; performing data processing; constructing a high spectrum estimation model for inverting soil heavy metal content; constructing a partial least squares regression model; and finally utilizing the partial least squares regression model to detect the heavy metal content of the coal gangue filling reclamation reconstruction soil. Compared with a conventional multiple linear regression analysis method, according to the method, the problem of multicollinearity faced by the multiple linear regression analysis method is solved, spectral information can be summarized and extracted, system information and noise are identified more easily, and thus the content of heavy metal elements can be quantitatively inverted accurately. The simple and quick detection method is provided for large-area low-cost investigation and monitoring of heavy metal pollution of mine lot reclamation land soil, technical means are provided for guaranteeing mine lot reclamation land crop safety, and development and application of a high spectrum remote sensing technology are promoted.
Description
Technical field
The present invention relates to the detection method of heavy metal content in soil, more particularly to it is a kind of based on hyperspectral technique
The method that detection gangue Reclamation by filling reconstructs heavy metal content in soil.
Background technology
The gangue produced in progress of coal mining can fill subsidence area, but the heavy metal element entrained by it as matrix
The security of soil can be affected.On the one hand, pollution of the heavy metal to soil is that short-term is irreversible, and may pass through food
Chain enters human body；On the other hand, the complicated space heterogeneity of soil causes the spatial distribution to heavy metal-polluted soil and space correlation
Property carries out quantification detection difficulty increase.
With the development of high spectrum resolution remote sensing technique, it is with spectral resolution height, wave band is more and continuity is fixed the features such as strong
Amount forecast analysis heavy metal pollution of soil provides strong instrument, is the big face of land reclamation in mining area ground heavy metal pollution of soil
Product, the investigation of low cost and monitoring provide a kind of simple, quick assay method, to ensure that land reclamation in mining area ground crop safety is provided
Technological means, and promote the development and application of high spectrum resolution remote sensing technique.
The content of the invention
It is an object of the invention to overcome the deficiencies in the prior art, there is provided one kind detects gangue based on hyperspectral technique
The method that Reclamation by filling reconstructs heavy metal content in soil, so as to realize the indirect determination of heavy metal content in soil.
The present invention is achieved by the following technical solutions：
It is a kind of that the method that gangue Reclamation by filling reconstructs heavy metal content in soil is detected based on hyperspectral technique including following
Step：
(1) spot sampling：In gangue Reclamation Land by Filling, sampled point is randomly selected, according to the depth that fetches earth of setting, with plum
Flower stake formula gathers multiple samples in each sampled point, by multiple sample random division forecast set samples and calibration set sample；
(2) sample spectra curve is gathered：The curve of spectrum figure of sample is gathered using field spectroradiometer；
(3) data processing：Curve of spectrum figure is converted into spectral reflectance data, and is derived；
(4) model：
A, the spectral reflectance data of forecast set sample is averaged respectively, logarithm reciprocal, first differential, second order it is micro-
Point conversion, then using the computing formula of Pearson correlation coefficients, by conversion after each band spectrum reflectivity data and soil
The concentration of sample heavy metal element carries out Bivariate analysis, and the concentration of the pedotheque heavy metal element can be using conventional
Method is determined, such as atomic absorption spectrophotometry, Pearson correlation coefficients computing formula is as follows：
ri--- the coefficient correlation of spectral reflectivity or other versions and heavy metal content in soil；
I --- band number；
cov(Xi, Y) --- refer between i-th wave band soil spectrum reflectivity and heavy metal content in soil the two variables
Covariance；
--- refer to the variance of i-th band spectrum reflectivity；
--- refer to the variance of heavy metal content in soil；
The selection of B, sensitive band：With correlation coefficient riCorresponding transform method is optimal transformation when maximum, meanwhile, take
Correlation coefficient riCorresponding wave band is sensitive band when maximum, with the spectral reflectance data institute of the sensitive band after optimal transformation
Corresponding averaged spectrum reflectivity, reflectivity inverse logarithm, First derivative reflectance, reflectivity second-order differential are independent variable, are adopted
The heavy metal content in soil of calibration set sample and the PLS mould of soil spectrum reflectivity are set up with MATLAB softwares
Type, while the coefficient of determination R of computation model2With standard error RMSE, with coefficient of determination R2Maximum, standard error RMSE is minimum
Principle is tested to the predictive ability and stability of model；
(5) detection of the content of beary metal of pedotheque to be measured：
Collection gangue Reclamation by filling to be measured reconstructs the curve of spectrum figure of soil sample, and curve of spectrum figure is turned
Spectral reflectance data is changed to, spectral reflectance data is carried out after data conversion in optimal transformation method, calculate sensitive band
Under spectral reflectance data, finally calculate soil to be detected using the EO-1 hyperion appraising model of inverting heavy metal content in soil
Content of beary metal.
Preferably, in the step (2), (3) and (5), gathered using ASD FieldSpec4 portable field spectroradiometers
Sample spectra curve, and the curve of spectrum is converted into spectral reflectance data.
Preferably, in the step (5), the acquisition method of pedotheque to be measured is：In gangue Reclamation Land by Filling, first
Sampled point is randomly selected, then according to the depth that fetches earth of setting, gathers multiple samples, by sample with quincuncial pile formula in each sampled point
This mixing, obtains representative combined sample, finally, combined sample is carried out into drying grinding, obtains pedotheque to be measured.
The present invention has compared to existing technology advantages below：The invention provides a kind of detect bastard coal based on hyperspectral technique
The method that stone Reclamation by filling reconstructs heavy metal content in soil, the method establishes Partial Least-Squares Regression Model, many with traditional
First linear regression analysis method is compared, and solves the Problems of Multiple Synteny that multiple linear regression analysis method is faced, and can be summarized and be carried
Take spectral information, and Partial Least-Squares Regression Model is easier to discrimination system information and noise (or even some nonrandomnesses is made an uproar
Sound), so as to relatively accurately quantitative inversion contents of heavy metal elements.The present invention is big for land reclamation in mining area ground heavy metal pollution of soil
Area, the investigation of low cost and monitoring provide a kind of simple, quick assay method, are to ensure that land reclamation in mining area ground crop safety is carried
For technological means, and promote the development and application of high spectrum resolution remote sensing technique.
Specific embodiment
Embodiments of the invention are elaborated below, the present embodiment is carried out under premised on technical solution of the present invention
Implement, give detailed embodiment and specific operating process, but protection scope of the present invention is not limited to following enforcements
Example.
Embodiment 1
One kind that the present embodiment is provided is based on hyperspectral technique detection gangue Reclamation by filling reconstruct heavy metal content in soil
Method, comprise the following steps：
(1) spot sampling：In gangue Reclamation Land by Filling, sampled point is randomly selected first, then according to what is set fetches earth
Depth, gathers multiple samples, by multiple sample random division forecast set samples and calibration set with quincuncial pile formula in each sampled point
Sample；
(2) sample spectra curve is gathered：Measured using indoor darkroom, geometrical arrangements light path is made using black Swan flannelette
For background, using ASD FieldSpec4 portable field spectroradiometers the curve of spectrum figure of sample is gathered；In the present embodiment, light
Source for 1000W Halogen lamp LED, 5 ° of angles of visual field, light source direction of illumination and vertical direction angle are 15 °, and light source distance is 30cm, are visited
Head distance is 15cm, is placed in the oblique upper of soil surface.Before test, blank is carried out after spectrometer is preheated into half an hour excellent
Change, into albedo measurement pattern, spectrometer arranges 10 times averagely, and each pedotheque measures 4 directions (will light path turn
It is dynamic 3 times, every time 90 °), 5 curves of spectrum of preservation on each direction, totally 20, as the reality of the pedotheque after arithmetic average
Border spectroscopic data；During the collection curve of spectrum, to ensure that blank is completely covered visual field simultaneously, temperature in laboratory, humidity,
Electromagnetic interference, vibration and Power Supplies Condition should meet that " test site, laboratory and wave spectrum measuring instrument set in instrument stabilizer job requirement
The requirement of standby specification "；
(3) data processing：The software carried using ASD FieldSpec4 is converted in curve of spectrum figure can be derived
Data type, obtains the spectral reflectance data of each pedotheque；
(4) model：
A, the spectral reflectance data of forecast set sample is averaged respectively, logarithm reciprocal, first differential, second order it is micro-
Point conversion, then using the computing formula of Pearson correlation coefficients, by conversion after each band spectrum reflectivity data and atom
The concentration of the pedotheque heavy metal element that absorptiometry is measured carries out Bivariate analysis, Pearson correlation coefficients
Computing formula is as follows：
ri--- the coefficient correlation of spectral reflectivity or other versions and heavy metal content in soil；
I --- band number；
cov(Xi, Y) --- refer between i-th wave band soil spectrum reflectivity and heavy metal content in soil the two variables
Covariance；
--- refer to the variance of i-th band spectrum reflectivity；
--- refer to the variance of heavy metal content in soil；
The selection of B, sensitive band：With correlation coefficient riCorresponding transform method is optimal transformation when maximum, meanwhile, take
Correlation coefficient riCorresponding wave band is sensitive band when maximum, with the spectral reflectance data institute of the sensitive band after optimal transformation
Corresponding averaged spectrum reflectivity, reflectivity inverse logarithm, First derivative reflectance, reflectivity second-order differential are independent variable, are adopted
The heavy metal content in soil of calibration set sample and the PLS mould of soil spectrum reflectivity are set up with MATLAB softwares
Type, while the coefficient of determination R of computation model2With standard error RMSE, with coefficient of determination R2Maximum, standard error RMSE is minimum
Principle is tested to the predictive ability and stability of model, obtains the EO-1 hyperion appraising model of inverting heavy metal content in soil.
In the present embodiment, spectrum analysis is carried out according to the gangue reclaimed land soil of known heavy metal Cu content, as a result sent out
Existing, Cu is extremely low with original spectrum, Druy screen correlation reciprocal, therefore the only coefficient correlation to selecting in the spectrum of differential transform
High wave band carries out the Partial Least-Squares Regression Model of Cu contents, sets up Cu contents respectively to different selected wave band numbers in order
Forecast model.
Table 1：The PLSR models of the heavy metal Cu content of differential smoothing
Note：In formula, Y for heavy metal-polluted soil Cu predicted value, XiRepresent spectral reflectivity at each differential smoothing wavelength i
Value is multiplied by 106。
As shown in Table 1, in the first derivative spectra, with the increase of selected wave band, RMSE constantly reduces, R2Increase
Greatly, when wave band number is 8, R2Increase to 0.9927, work as R2Bigger, RMSE gets over hour, and model is better, so determining selected wave band
For 8 when for PLSR regression models be predict heavy metal Cu content best model, prediction expression now is as shown in Table.
In second-order differential spectrum, with being continuously increased for selected wave band number, the RMSE of PLSR regression models is not to reduce always, is gone out
Show first to increase and reduced situation about being further added by, R afterwards2Nor increasing always, 4 ripples in selected wave band is stepwise regression analysis
Duan Shi, R2It is 2.406 to reach 0.991, RMSE, and precision when being at this moment 5～11 than wave band number will be good.When selected wave band number is
When 15, R2Maximum is reached, is that 0.994, RMSE reaches minimum, be 1.919, be now prediction heavy metal for PLSR regression models
The best model of Cu contents, prediction expression now is as shown in table 1.
(5) detection of unknown pedotheque：
A, collecting soil sample to be measured：In gangue Reclamation Land by Filling, sampled point is randomly selected first, then according to setting
The depth that fetches earth, multiple samples are gathered in each sampled point with quincuncial pile formula, sample is mixed, obtain representative combination
Sample, finally, by combined sample drying grinding is carried out, and obtains pedotheque to be measured, and pedotheque to be measured is encapsulated with hermetic bag,
And label is posted, and what a sample is often processed, the instrument for being used must be scrubbed, in order to avoid cause cross pollution；
B, the curve of spectrum that unknown pedotheque is gathered using the method as described in step (2)；
The curve of spectrum of step B is carried out data processing by C, method of the utilization as described in step (3), obtains unknown soil-like
The spectral reflectance data of product；
D, spectral reflectance data is carried out into data variation in the optimum variation method of step (4), and calculate sensitive band
Under spectral reflectance data, spectral reflectance data is finally brought into the inverting heavy metal content in soil of step (4) foundation
EO-1 hyperion appraising model, directly calculates the content of beary metal for obtaining pedotheque to be measured.
It is above a kind of detailed embodiment of the invention and specific operating process, is with technical solution of the present invention as front
Put and implemented, but protection scope of the present invention is not limited to the above embodiments.
Claims (3)
1. a kind of to detect the method that gangue Reclamation by filling reconstructs heavy metal content in soil based on hyperspectral technique, its feature exists
In comprising the following steps：
(1) spot sampling：In gangue Reclamation Land by Filling, sampled point is randomly selected, the depth collection of fetching earth according to setting is multiple
Sample, by multiple sample random division forecast set samples and calibration set sample；
(2) sample spectra curve is gathered：The curve of spectrum figure of sample is gathered using field spectroradiometer；
(3) data processing：Curve of spectrum figure is converted into spectral reflectance data, and is derived；
(4) model：
A, the spectral reflectance data of forecast set sample is averaged respectively, logarithm reciprocal, first differential, second-order differential become
Change, then using the computing formula of Pearson correlation coefficients, by conversion after each band spectrum reflectivity data and pedotheque
The concentration of heavy metal element carries out Bivariate analysis, and the concentration of the pedotheque heavy metal element is surveyed using conventional method
Fixed, Pearson correlation coefficients computing formula is as follows：
ri--- the coefficient correlation of spectral reflectivity or other versions and heavy metal content in soil；
I --- band number；
cov(Xi, Y) --- refer to the association side between i-th wave band soil spectrum reflectivity and heavy metal content in soil the two variables
Difference；
--- refer to the variance of i-th band spectrum reflectivity；
--- refer to the variance of heavy metal content in soil；
The selection of B, sensitive band：With correlation coefficient riCorresponding transform method is optimal transformation when maximum, meanwhile, take correlation
Coefficient riCorresponding wave band is sensitive band when maximum, with corresponding to the spectral reflectance data of the sensitive band after optimal transformation
Averaged spectrum reflectivity, reflectivity inverse logarithm, First derivative reflectance, reflectivity second-order differential be independent variable, set up school
Just collecting the heavy metal content in soil of sample and the Partial Least-Squares Regression Model of soil spectrum reflectivity；
(5) detection of the content of beary metal of pedotheque to be measured：
Collection gangue Reclamation by filling to be measured reconstructs the curve of spectrum figure of soil sample, and curve of spectrum figure is converted to
Spectral reflectance data, spectral reflectance data is carried out after data conversion in optimal transformation method, under calculating sensitive band
Spectral reflectance data, finally calculates the content of beary metal of soil to be detected using Partial Least-Squares Regression Model.
2. a kind of hyperspectral technique detection gangue Reclamation by filling reconstruct heavy metal-polluted soil that is based on according to claim 1 contains
The method of amount, it is characterised in that in the step (2), (3) and (5), using ASD FieldSpec4 portable field spectroradiometers
Collection sample spectra curve, and the curve of spectrum is converted into spectral reflectance data.
3. a kind of hyperspectral technique detection gangue Reclamation by filling reconstruct heavy metal-polluted soil that is based on according to claim 1 contains
The method of amount, it is characterised in that in the step (5), the acquisition method of pedotheque to be measured is：In gangue Reclamation by filling
Area, randomly selects first sampled point, then according to the depth that fetches earth of setting, multiple samples are gathered with quincuncial pile formula in each sampled point
This, sample is mixed, and obtains representative combined sample, finally, combined sample is carried out into drying grinding, obtains soil to be measured
Earth sample.
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| CN107167446A (en) * | 2017-05-16 | 2017-09-15 | 武汉大学 | A kind of heavy metal-polluted soil is visible and near-infrared spectral reflectance feature diagnostic method |
| CN107421894A (en) * | 2017-09-28 | 2017-12-01 | 威海五洲卫星导航科技有限公司 | Based on unmanned plane EO-1 hyperion inverting heavy metal in soil pollution monitoring method |
| CN107748140A (en) * | 2017-10-19 | 2018-03-02 | 中国矿业大学(北京) | A kind of field EO-1 hyperion Fast measurement system |
| CN107945162A (en) * | 2017-11-23 | 2018-04-20 | 华南农业大学 | Detection recognition method based on computer vision technique to flourishing ant nest |
| CN108982756A (en) * | 2018-04-26 | 2018-12-11 | 贵州省烟草公司遵义市公司 | A kind of crop heavy metal pollution prediction method and device |
| CN108982380A (en) * | 2018-05-30 | 2018-12-11 | 贵州省山地资源研究所 | A kind of cultivated soil heavy metal monitoring system |
| CN109508512A (en) * | 2018-12-28 | 2019-03-22 | 中南大学 | Change the earth's surface constituent content visited and combined with remote sensing and quantifies projectional technique and device |
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| CN109902406A (en) * | 2019-03-06 | 2019-06-18 | 苏州市环境科学研究所 | A kind of method and application of the detection heavy metal content in soil based on deep learning |
| CN110174359A (en) * | 2019-05-27 | 2019-08-27 | 生态环境部南京环境科学研究所 | A kind of Airborne Hyperspectral image heavy metal-polluted soil concentration evaluation method returned based on Gaussian process |
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| CN107421894A (en) * | 2017-09-28 | 2017-12-01 | 威海五洲卫星导航科技有限公司 | Based on unmanned plane EO-1 hyperion inverting heavy metal in soil pollution monitoring method |
| CN107748140A (en) * | 2017-10-19 | 2018-03-02 | 中国矿业大学(北京) | A kind of field EO-1 hyperion Fast measurement system |
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| CN108982380A (en) * | 2018-05-30 | 2018-12-11 | 贵州省山地资源研究所 | A kind of cultivated soil heavy metal monitoring system |
| CN109508512A (en) * | 2018-12-28 | 2019-03-22 | 中南大学 | Change the earth's surface constituent content visited and combined with remote sensing and quantifies projectional technique and device |
| CN109902406A (en) * | 2019-03-06 | 2019-06-18 | 苏州市环境科学研究所 | A kind of method and application of the detection heavy metal content in soil based on deep learning |
| CN109902406B (en) * | 2019-03-06 | 2022-11-18 | 苏州市环境科学研究所 | Method for detecting heavy metal content in soil based on deep learning and application |
| CN110174359A (en) * | 2019-05-27 | 2019-08-27 | 生态环境部南京环境科学研究所 | A kind of Airborne Hyperspectral image heavy metal-polluted soil concentration evaluation method returned based on Gaussian process |
| CN110907367A (en) * | 2019-11-09 | 2020-03-24 | 华东师范大学 | Soil moisture content detection method based on hyperspectral remote sensing |
| CN110907367B (en) * | 2019-11-09 | 2022-10-04 | 华东师范大学 | Soil moisture content detection method based on hyperspectral remote sensing |
| CN111337447A (en) * | 2020-03-20 | 2020-06-26 | 中国矿业大学 | Coal and gangue bionic identification system and method |
| CN111337447B (en) * | 2020-03-20 | 2021-09-24 | 中国矿业大学 | Coal and gangue bionic identification system and method |
| CN111398199A (en) * | 2020-04-29 | 2020-07-10 | 中国农业大学 | Hyperspectral imaging-based wheat flour trace element rapid detection method |
| CN112149827A (en) * | 2020-09-27 | 2020-12-29 | 哈尔滨航天恒星数据系统科技有限公司 | System and method for constructing soil quick-acting potassium analysis model based on satellite images |
| CN112683813A (en) * | 2020-12-31 | 2021-04-20 | 核工业北京地质研究院 | Hyperspectral extraction method for soil pollution information of hard rock type uranium mine |
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