CN111638195A - Drought monitoring method and device - Google Patents
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Abstract
The embodiment of the invention provides a drought monitoring method and a device, wherein the method comprises the following steps: acquiring hyperspectral resolution remote sensing data of a region to be monitored; processing the hyperspectral resolution remote sensing data to obtain atmospheric layer top entrance pupil radiance, and obtaining sunlight induced chlorophyll fluorescence according to the atmospheric layer top entrance pupil radiance; inducing chlorophyll fluorescence according to the sunlight to obtain a vegetation physiological drought index of the area to be monitored; and evaluating the vegetation drought stress condition of the area to be monitored according to the vegetation physiological drought index. Sunlight-induced chlorophyll fluorescence is obtained through inversion of the hyperspectral resolution remote sensing data, and the physiological drought index of the vegetation is further obtained, so that the drought stress condition of the vegetation in the area to be monitored can be directly evaluated, and the time delay defect of the existing drought stress monitoring is avoided.
Description
Technical Field
The invention relates to the technical field of remote sensing, in particular to a drought monitoring method and device.
Background
Drought has multiple definitions, defined by the american meteorological institute in 1997 as four categories: meteorological drought, agricultural drought, hydrological drought, and socioeconomic drought. The usual Parmer Drought Severity Index (PDSI) and Standardized Precipitation Index (SPI) are mostly calculated by meteorological factors. For example, PDSI is calculated based on temperature, precipitation and soil moisture balance models, and SPI is calculated only for precipitation anomalies.
These indices are very effective for monitoring weather drought, but for terrestrial vegetation, weather drought does not mean true drought, as the drought stress status of vegetation also depends on non-meteorological factors such as ground water storage, agricultural irrigation, and the like. Therefore, agricultural drought cannot be effectively monitored by the weather drought index alone. Remote sensing technology can provide long-time and wide-range observation information of terrestrial vegetation, and the information is helpful for monitoring the stressed state of the vegetation 'real'.
In the prior art, vegetation indexes based on remote sensing reflection are obtained mainly by monitoring the pigment content of leaves and the change of a canopy structure. Because the vegetation index based on the remote sensing reflection mainly depends on the pigment content of the leaves and the change of the canopy structure, and the changes are the accumulated effect of the physiological stress of the plants for a period of time, the rapid and accurate response of the vegetation to the photosynthetic physiological change caused by drought stress is difficult, and the vegetation index has certain time delay (for example, the response delay of the vegetation index NDVI to rainfall can reach 1-2 months).
Therefore, the vegetation drought monitoring method in the prior art has the defects of time delay and incapability of directly reflecting the drought stress condition of the vegetation. Therefore, how to design a new drought monitoring method to solve the problems of time delay and incapability of directly reflecting the drought stress condition of vegetation in vegetation drought monitoring becomes an urgent problem to be solved.
Disclosure of Invention
The embodiment of the invention provides a drought monitoring method and device, which are used for overcoming the defects of time delay and incapability of directly reflecting the drought stress condition of vegetation in the prior art.
In a first aspect, an embodiment of the present invention provides a drought monitoring method, including:
acquiring hyperspectral resolution remote sensing data of a region to be monitored;
processing the hyperspectral resolution remote sensing data to obtain atmospheric layer top entrance pupil radiance, and obtaining sunlight induced chlorophyll fluorescence according to the atmospheric layer top entrance pupil radiance;
inducing chlorophyll fluorescence according to the sunlight to obtain a vegetation physiological drought index of the area to be monitored;
and evaluating the vegetation drought stress condition of the area to be monitored according to the vegetation physiological drought index.
Optionally, the processing the hyperspectral resolution remote sensing data to obtain the radiance of the top entrance pupil of the atmospheric layer specifically includes:
and preprocessing the hyperspectral resolution remote sensing data, including but not limited to noise reduction, radiometric calibration and reflectivity inversion processing, and acquiring the radiance of the top entrance pupil of the atmospheric layer.
Optionally, the obtaining of sunlight-induced chlorophyll fluorescence according to the atmospheric layer top entrance pupil radiance specifically includes:
expressing the non-fluorescence spectrum of the hyperspectral resolution remote sensing data in the inversion window by using a principal component through a feature extraction algorithm, and determining each principal component by fitting the radiance of a non-fluorescence target through least square;
and acquiring a fluorescence spectrum according to an atmospheric layer top entrance pupil radiance equation, and acquiring sunlight induced chlorophyll fluorescence according to the fluorescence spectrum.
Optionally, the atmospheric layer top entrance pupil radiance equation is:
wherein L isTOAIs the top entrance pupil radiance of the atmosphere, IsolSolar irradiance at the top of the atmospheric layer, measured from satellite observations, μ0Is the cosine of the zenith angle of the sun, wherein lambda is the wavelength and PC is the main component of the atmosphere αiIs the coefficient of principal component, n is the number of principal components, βjIs a polynomial fitting coefficient, m is a polynomial degree, FsConstant of fluorescence, hfFor fluorescence spectroscopy, usually expressed as a Gaussian function, T↑The upward transmittance of the atmosphere can be obtained by utilizing the spectrum calculation of the normalization of the apparent reflectivity.
Optionally, the obtaining of sunlight-induced chlorophyll fluorescence according to the fluorescence spectrum specifically includes:
and performing Gaussian fitting on the fluorescence spectrum, and calculating the product of the fluorescence spectrum, the fluorescence constant and the atmospheric uplink transmittance to obtain the sunlight-induced chlorophyll fluorescence.
Optionally, the obtaining of the vegetation physiological drought index of the area to be monitored according to the sunlight-induced chlorophyll fluorescence specifically includes:
and carrying out normalization treatment on the sunlight-induced chlorophyll fluorescence to obtain the vegetation physiological drought index of the area to be monitored.
Optionally, the normalizing the sunlight-induced chlorophyll fluorescence specifically includes:
subjecting the daylight-induced chlorophyll fluorescence to cos (SZA) or PAR normalization; and/or
And carrying out BRF normalization treatment on the sunlight-induced chlorophyll fluorescence.
Optionally, the evaluating the vegetation drought stress condition of the region to be monitored according to the vegetation physiological drought index specifically includes:
and comparing and analyzing the vegetation physiological drought index and the vegetation physiological drought index in the historical period of the area to obtain the vegetation drought stress condition of the area to be monitored.
In a second aspect, an embodiment of the present invention provides a drought monitoring device, including:
a first obtaining module: the system is used for acquiring the hyperspectral resolution remote sensing data of a region to be monitored;
a processing module: the system is used for processing the hyperspectral resolution remote sensing data to obtain the top entrance pupil radiance of the atmospheric layer, and obtaining sunlight induced chlorophyll fluorescence according to the top entrance pupil radiance of the atmospheric layer;
a second obtaining module: the sunlight-induced chlorophyll fluorescence is used for obtaining the vegetation physiological drought index of the area to be monitored;
an evaluation module: and the method is used for evaluating the vegetation drought stress condition of the area to be monitored according to the vegetation physiological drought index.
In a third aspect, embodiments of the present invention provide a non-transitory computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements the steps of the drought monitoring method according to any one of the first aspect.
According to the drought monitoring method and device provided by the embodiment of the invention, sunlight-induced chlorophyll fluorescence is obtained by processing the remote sensing data with the ultra-spectral resolution, and the sunlight-induced chlorophyll fluorescence is inverted to further obtain the physiological drought index of the vegetation, so that the drought stress condition of the vegetation in the area to be monitored can be directly evaluated, and the time delay defect of the existing drought stress monitoring is avoided.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and those skilled in the art can also obtain other drawings according to the drawings without creative efforts.
FIG. 1 is a schematic flow chart of a drought monitoring method according to an embodiment of the present invention;
fig. 2 is a schematic structural diagram of a drought monitoring device provided by an embodiment of the invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
As shown in fig. 1, a drought monitoring method provided in an embodiment of the present invention includes:
acquiring hyperspectral resolution remote sensing data of a region to be monitored;
processing the hyperspectral resolution remote sensing data to obtain atmospheric layer top entrance pupil radiance, and obtaining sunlight induced chlorophyll fluorescence according to the atmospheric layer top entrance pupil radiance;
inducing chlorophyll fluorescence according to the sunlight to obtain a vegetation physiological drought index of the area to be monitored;
and evaluating the vegetation drought stress condition of the area to be monitored according to the vegetation physiological drought index.
Specifically, the spectral resolution of the acquired remote sensing data with the hyper-spectral resolution is better than 0.3nm (generally not more than 1nm), and the spectral coverage range is 670-780nm (required to cover several typical sun and earth atmospheric absorption dark lines, such as O2Band a, etc.), the signal-to-noise ratio is better than 200: 1 (case of input radiance 10mWm-2sr-1 nm-1); the hyperspectral resolution remote sensing data meeting the requirements comprise: japanese GOSAT, American OCO-2, European and air Bureau GOME-2, European and air Bureau TROPOMI, European and air Bureau SCIAMACHY, European and air Bureau FLEX, China TanSat, China GF-5 and China will launch the remote sensing data obtained by the carbon monitoring satellite of the terrestrial ecosystem.
The acquired hyperspectral resolution remote sensing data also needs to be preprocessed according to conditions, wherein the preprocessing comprises noise reduction, radiometric calibration, reflectivity inversion and the like, and preprocessing steps related to different sunlight-induced chlorophyll fluorescence remote sensing inversion methods are different. The remote sensing data for inverting the sunlight-induced chlorophyll fluorescence based on the radiation transmission equation needs to be subjected to accurate atmospheric correction, and the remote sensing data for inverting the sunlight-induced chlorophyll fluorescence based on the data driving algorithm does not need to be subjected to atmospheric correction. In order to accurately invert sunlight-induced chlorophyll fluorescence, original spectral data needs to be calibrated into radiance data or a satellite radiance data product needs to be selected by using the latest radiance calibration coefficient of a remote sensing sensor.
Before SIF inversion, an inversion algorithm needs to be determined, and the inversion algorithm mainly comprises two data-driven algorithms of SVD (singular vector analysis) and PCA (principal Component analysis), and the principles of the two data-driven algorithms are consistent. Factors affecting the algorithm mainly include: selecting a training set, determining an inversion window, extracting main components of the atmosphere, and fitting a fluorescence spectrum. The selection of the training set needs to contain high-frequency information of sun dark lines and earth dark lines which are not filled with fluorescence, when SIF inversion is carried out by only using the sun dark lines, the selected training set needs to avoid large sun zenith angles (generally <70 ℃), influence caused by inelastic scattering is reduced, the acquisition time of the training set needs to be short of the acquisition time of a fluorescence target spectrum, and influence caused by sensor decay and solar radiation spectrum change is reduced; when the inversion window contains the earth dark line, the training set should contain non-fluorescence target spectra obtained under different atmospheric states and observation geometric conditions, so that the atmospheric principal components obtained by training can express atmospheric features under any observation conditions.
The selection of the inversion window needs to be determined according to the type of hyperspectral resolution remote sensing data, the inversion window determines the number of Fraunhofer line characteristics in the window, and the higher the spectral resolution and the signal-to-noise ratio of the sensor are, the narrower the required inversion window is.
Extracting the atmospheric principal components requires using a feature extraction algorithm (such as PCA), expressing the non-fluorescence spectrum of the remote sensing data with the hyperspectral resolution in a specific window by using a small amount of principal components, and determining the number of the principal components according to the least square fitting of the radiance of a non-fluorescence target.
Fitting the fluorescence spectrum requires selecting a gaussian function to fit the fluorescence spectrum. Solving the forward model adopts a linear least square method or a backward elimination algorithm to solve the forward model.
Further, acquiring a vegetation physiological drought index of the area to be monitored by normalizing the acquired sunlight-induced chlorophyll fluorescence (SIF), and judging the vegetation drought risk probability in advance according to the vegetation physiological drought index by combining data such as weather, soil moisture, irrigation conditions, vegetation phenology and the like of the area to be monitored; and analyzing the physiological drought stress condition of the vegetation by utilizing the SIF abnormal change space-time distribution diagram in combination with the drought risk, and realizing early monitoring, early warning and accurate evaluation of the drought of the vegetation in the area to be monitored.
As an embodiment of the present invention, the processing the hyperspectral resolution remote sensing data to obtain the radiance of the top entrance pupil of the atmospheric layer specifically includes:
and preprocessing the hyperspectral resolution remote sensing data, including but not limited to noise reduction, radiometric calibration and reflectivity inversion processing, and acquiring the radiance of the top entrance pupil of the atmospheric layer.
Specifically, in order to enable the obtained hyperspectral resolution remote sensing data to be suitable for obtaining sunlight-induced chlorophyll fluorescence, the hyperspectral resolution remote sensing data needs to be preprocessed; wherein the types of preprocessing include, but are not limited to, noise reduction, radiometric scaling, and reflectivity inversion processing.
As an embodiment of the present invention, the acquiring sunlight-induced chlorophyll fluorescence according to the atmospheric layer top entrance pupil radiance specifically includes:
expressing the non-fluorescence spectrum of the hyperspectral resolution remote sensing data in the inversion window by using a principal component through a feature extraction algorithm, and determining each principal component by fitting the radiance of a non-fluorescence target through least square;
and acquiring a fluorescence spectrum according to an atmospheric layer top entrance pupil radiance equation, and acquiring sunlight induced chlorophyll fluorescence according to the fluorescence spectrum.
Specifically, principal component expression is carried out on the non-fluorescence spectrum of the inversion window through a feature extraction algorithm such as PCA or SVD, and each principal component is obtained through least square fitting of non-fluorescence target radiance; and further acquiring a fluorescence spectrum through an atmospheric layer top entrance pupil radiance equation, and acquiring sunlight-induced chlorophyll fluorescence according to the main components and the fluorescence spectrum.
As an embodiment of the present invention, the atmospheric layer top entrance pupil radiance equation is:
wherein L isTOAIs the top entrance pupil radiance of the atmosphere, IsolSolar irradiance at the top of the atmospheric layer, measured from satellite observations, μ0Is the cosine of the zenith angle of the sun, wherein lambda is the wavelength and PC is the main component of the atmosphere αiIs the coefficient of principal component, n is the number of principal components, βjIs a polynomial fitting coefficient, m is a polynomial degree, FsConstant of fluorescence, hfFor fluorescence spectroscopy, usually expressed as a Gaussian function, T↑The upward transmittance of the atmosphere can be obtained by utilizing the spectrum calculation of the normalization of the apparent reflectivity.
Specifically, the function of the atmospheric layer top entrance pupil radiance equation is to solve and obtain the fluorescence spectrum h according to the equation and various acquired data such as the atmospheric layer top entrance pupil radiance, the atmospheric layer top solar irradiance, the atmospheric principal component, the principal component coefficient and the likef。
As an embodiment of the present invention, the acquiring of sunlight-induced chlorophyll fluorescence according to the fluorescence spectrum specifically includes:
and performing Gaussian fitting on the fluorescence spectrum, and calculating the product of the fluorescence spectrum, the fluorescence constant and the atmospheric uplink transmittance to obtain the sunlight-induced chlorophyll fluorescence.
Specifically, fitting the fluorescence spectrum through a Gaussian function, obtaining the fluorescence spectrum after Gaussian fitting, and calculating the fluorescence spectrum hfConstant of fluorescence FsAnd upward atmospheric transmittance T↑The product of (a) and (b) is obtained for sunlight-induced chlorophyll fluorescence.
The fluorescence spectrum after gaussian fitting was:
wherein λ is the wavelength, μhIs the central wavelength, σ, of the fluorescence spectrumhWidth of the fluorescence spectrum.
As an embodiment of the present invention, the acquiring of the vegetation physiological drought index of the region to be monitored by inducing chlorophyll fluorescence according to the sunlight specifically includes:
and carrying out normalization treatment on the sunlight-induced chlorophyll fluorescence to obtain the vegetation physiological drought index of the area to be monitored.
Specifically, the sensitive index reflecting vegetation physiological drought stress is calculated based on the instant SIF obtained by inversion, namely the original SIF is an instant SIF value, the response of SIF to vegetation photosynthesis physiology is interfered by the influence of illumination conditions, clouds, algorithm inversion random errors, vegetation canopy structure and the like when a sensor passes through the environment, and the response is required to be subjected to time-space averaging, illumination normalization, canopy structure effect correction and the like for further application. The method comprises the following steps: and eliminating the influence of the illumination condition when the sensor passes the border and correcting the SIF canopy structure effect by utilizing the reflectivity BRF normalization.
The relationship between SIF and photosynthetically active radiation is SIF PAR × fPAR ×F×fesc；
Wherein PAR is photosynthetically active radiation, fPAR is photosynthetically active radiation absorption ratio,Ffor fluorescence quantum yield, fescThe canopy escape rate of fluorescence, SIF is sunlight-induced chlorophyll fluorescence
As an embodiment of the present invention, the normalizing the sunlight-induced chlorophyll fluorescence specifically includes:
subjecting the daylight-induced chlorophyll fluorescence to cos (SZA) or PAR normalization; and/or
And carrying out BRF normalization treatment on the sunlight-induced chlorophyll fluorescence.
Specifically, the cos (sza) processing formula is: SIFnSIF/cos (sza); the PAR normalization process formula is: SIFn＝SIF/PAR；
Wherein, SIFnIs SIF normalized by cos (SZA) or PAR, and cos (SZA) is the cosine value of the zenith angle of the sun;
the BRF normalization processing formula is as follows:
wherein, SIFcnFor the normalized correction of the canopy structure effect by the reflectivity BRF, SIF, omega isObservation direction solid angle.
As an embodiment of the present invention, the evaluating the vegetation drought stress condition of the region to be monitored according to the vegetation physiological drought index specifically includes:
and comparing and analyzing the vegetation physiological drought index and the vegetation physiological drought index in the historical period of the area to obtain the vegetation drought stress condition of the area to be monitored.
Specifically, the vegetation drought risk probability is judged in advance by using data such as weather, soil moisture, irrigation conditions, vegetation phenology and the like of the area to be monitored according to the obtained vegetation physiological drought index and the vegetation physiological drought index in the historical period of the area. And further combining drought risk, analyzing the physiological drought stress condition of the vegetation by utilizing a SIF abnormal change space-time distribution diagram, and realizing early monitoring, early warning and accurate evaluation of the drought of the vegetation.
As shown in fig. 2, a drought monitoring device provided in an embodiment of the present invention includes:
the first obtaining module 201: the system is used for acquiring the hyperspectral resolution remote sensing data of a region to be monitored;
the processing module 202: the system is used for processing the hyperspectral resolution remote sensing data to obtain the top entrance pupil radiance of the atmospheric layer, and obtaining sunlight induced chlorophyll fluorescence according to the top entrance pupil radiance of the atmospheric layer;
the second obtaining module 203: the sunlight-induced chlorophyll fluorescence is used for obtaining the vegetation physiological drought index of the area to be monitored;
the evaluation module 204: and the method is used for evaluating the vegetation drought stress condition of the area to be monitored according to the vegetation physiological drought index.
Specifically, the first obtaining module 201 is configured to obtain hyperspectral resolution remote sensing data of an area to be monitored, where the hyperspectral resolution remote sensing data meeting requirements includes: japanese GOSAT, American OCO-2, European and air Bureau GOME-2, European and air Bureau TROPOMI, European and air Bureau SCIAMACHY, European and air Bureau FLEX, China TanSat, China GF-5 and China will launch the remote sensing data obtained by the carbon monitoring satellite of the terrestrial ecosystem.
The second obtaining module 203 is configured to obtain a vegetation physiological drought index of the area to be monitored through normalization processing on the obtained sunlight-induced chlorophyll fluorescence (SIF).
The evaluation module 204 is configured to pre-determine a vegetation drought risk probability according to the vegetation physiological drought index and the vegetation physiological drought indexes in different historical periods in combination with data of weather, soil moisture, irrigation conditions, vegetation phenology and the like of the area to be monitored; and analyzing the physiological drought stress condition of the vegetation by utilizing the SIF abnormal change space-time distribution diagram in combination with the drought risk, and realizing early monitoring, early warning and accurate evaluation of the drought of the vegetation in the area to be monitored.
In another aspect, an embodiment of the present invention further provides a non-transitory computer-readable storage medium, on which a computer program is stored, where the computer program is implemented to perform the transmission method provided in the foregoing embodiments when executed by a processor, and for example, the method includes: acquiring hyperspectral resolution remote sensing data of a region to be monitored; processing the hyperspectral resolution remote sensing data to obtain atmospheric layer top entrance pupil radiance, and obtaining sunlight induced chlorophyll fluorescence according to the atmospheric layer top entrance pupil radiance; inducing chlorophyll fluorescence according to the sunlight to obtain a vegetation physiological drought index of the area to be monitored; and evaluating the vegetation drought stress condition of the area to be monitored according to the vegetation physiological drought index.
The above-described embodiments of the apparatus are merely illustrative, and the units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment. One of ordinary skill in the art can understand and implement it without inventive effort.
Through the above description of the embodiments, those skilled in the art will clearly understand that each embodiment can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware. With this understanding in mind, the above-described technical solutions may be embodied in the form of a software product, which can be stored in a computer-readable storage medium such as ROM/RAM, magnetic disk, optical disk, etc., and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the methods described in the embodiments or some parts of the embodiments.
Finally, it should be noted that: the above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (10)
1. A drought monitoring method, comprising:
acquiring hyperspectral resolution remote sensing data of a region to be monitored;
processing the hyperspectral resolution remote sensing data to obtain atmospheric layer top entrance pupil radiance, and obtaining sunlight induced chlorophyll fluorescence according to the atmospheric layer top entrance pupil radiance;
inducing chlorophyll fluorescence according to the sunlight to obtain a vegetation physiological drought index of the area to be monitored;
and evaluating the vegetation drought stress condition of the area to be monitored according to the vegetation physiological drought index.
2. The method according to claim 1, wherein the processing the hyperspectral resolution remote sensing data to obtain the radiance at the top entrance pupil of the atmospheric layer specifically comprises:
and preprocessing the hyperspectral resolution remote sensing data, including but not limited to noise reduction, radiometric calibration and reflectivity inversion processing, and acquiring the radiance of the top entrance pupil of the atmospheric layer.
3. The method according to claim 2, wherein the obtaining of the sunlight-induced chlorophyll fluorescence according to the atmospheric layer top entrance pupil radiance specifically comprises:
expressing the non-fluorescence spectrum of the hyperspectral resolution remote sensing data in the inversion window by using a principal component through a feature extraction algorithm, and determining each principal component by fitting the radiance of a non-fluorescence target through least square;
and acquiring a fluorescence spectrum according to an atmospheric layer top entrance pupil radiance equation, and acquiring sunlight induced chlorophyll fluorescence according to the fluorescence spectrum.
4. The method of claim 3, wherein the atmospheric layer top entrance pupil radiance equation is:
wherein L isTOAIs the top entrance pupil radiance of the atmosphere, IsolSolar irradiance at the top of the atmospheric layer, measured from satellite observations, μ0Is the cosine of the zenith angle of the sun, wherein lambda is the wavelength and PC is the main component of the atmosphere αiIs the coefficient of principal component, n is the number of principal components, βjIs a polynomial fitting coefficient, m is a polynomial degree, FsConstant of fluorescence, hfFor fluorescence spectroscopy, usually expressed as a Gaussian function, T↑The upward transmittance of the atmosphere can be obtained by utilizing the spectrum calculation of the normalization of the apparent reflectivity.
5. The method according to claim 4, wherein the obtaining of the sunlight-induced chlorophyll fluorescence from the fluorescence spectrum specifically comprises:
and performing Gaussian fitting on the fluorescence spectrum, and calculating the product of the fluorescence spectrum, the fluorescence constant and the atmospheric uplink transmittance to obtain the sunlight-induced chlorophyll fluorescence.
6. The method according to claim 5, wherein the step of obtaining the physiological drought index of the vegetation in the area to be monitored by inducing chlorophyll fluorescence according to the sunlight specifically comprises the following steps:
and carrying out normalization treatment on the sunlight-induced chlorophyll fluorescence to obtain the vegetation physiological drought index of the area to be monitored.
7. The method according to claim 6, wherein the normalizing the sunlight-induced chlorophyll fluorescence specifically comprises:
subjecting the daylight-induced chlorophyll fluorescence to cos (SZA) or PAR normalization; and/or
And carrying out BRF normalization treatment on the sunlight-induced chlorophyll fluorescence.
8. The method of claim 7, wherein the evaluating the vegetation drought stress condition of the area to be monitored according to the vegetation physiological drought index specifically comprises:
and comparing and analyzing the vegetation physiological drought index and the vegetation physiological drought index in the historical period of the area to obtain the vegetation drought stress condition of the area to be monitored.
9. A drought monitoring device, comprising:
a first obtaining module: the system is used for acquiring the hyperspectral resolution remote sensing data of a region to be monitored;
a processing module: the system is used for processing the hyperspectral resolution remote sensing data to obtain the top entrance pupil radiance of the atmospheric layer, and obtaining sunlight induced chlorophyll fluorescence according to the top entrance pupil radiance of the atmospheric layer;
a second obtaining module: the sunlight-induced chlorophyll fluorescence is used for obtaining the vegetation physiological drought index of the area to be monitored;
an evaluation module: and the method is used for evaluating the vegetation drought stress condition of the area to be monitored according to the vegetation physiological drought index.
10. A non-transitory computer readable storage medium, on which a computer program is stored, wherein the computer program, when executed by a processor, implements the steps of the drought monitoring method according to any one of claims 1 to 8.
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