阅读说明：本技术 一种日光诱导叶绿素荧光数据的获取方法及系统 (Method and system for acquiring sunlight-induced chlorophyll fluorescence data ) 是由 杨健 杨淞晰 史硕 张阳阳 杜霖 于 2021-08-18 设计创作，主要内容包括：本发明公开了一种日光诱导叶绿素荧光数据的获取方法及系统。先获取蒸气压含量数据、地表反射率数据、叶面积指数、风速、空气温度、地表接收短波、长波辐射数据；再基于地表反射率数据和预设的查找表反演得到叶绿素含量数据；将蒸气压含量数据、叶面积指数、风速、空气温度、地表接收短波、长波辐射数据、叶绿素含量数据输入到预设的辐射传输模型中,输出得到叶绿素荧光数据。通过本发明获得的数据集的时空分辨率高,数据获取结果有较强的物理基础,可以适应于大中小尺度的荧光反演验证与荧光数据产品的深度应用。(The invention discloses a method and a system for acquiring sunlight-induced chlorophyll fluorescence data. Firstly, acquiring vapor pressure content data, surface reflectivity data, leaf area index, wind speed, air temperature and surface receiving short wave and long wave radiation data; performing inversion based on the surface reflectivity data and a preset lookup table to obtain chlorophyll content data; and inputting the vapor pressure content data, the leaf area index, the wind speed, the air temperature, the earth surface receiving short wave and long wave radiation data and the chlorophyll content data into a preset radiation transmission model, and outputting to obtain chlorophyll fluorescence data. The data set obtained by the method has high space-time resolution, and the data acquisition result has stronger physical basis, so that the method can be suitable for large, medium and small scale fluorescence inversion verification and deep application of fluorescence data products.)

1. A method for acquiring sunlight-induced chlorophyll fluorescence data is characterized by comprising the following steps:

acquiring vapor pressure content data and surface reflectivity data;

performing inversion based on the surface reflectivity data and a preset lookup table to obtain chlorophyll content data;

acquiring leaf area index, wind speed, air temperature and earth surface receiving short wave and long wave radiation data;

and inputting the vapor pressure content data, the leaf area index, the wind speed, the air temperature, the earth surface receiving short wave and long wave radiation data and the chlorophyll content data into a preset radiation transmission model, and outputting to obtain chlorophyll fluorescence data.

2. The method of claim 1, wherein said obtaining vapor pressure content data comprises:

acquiring relative humidity data and air temperature data;

by the formulaCalculating to obtain the vapor pressure content data e_a；

Wherein, e (T)_min) And e (T)_max) The saturated vapor pressure, RH, corresponding to the daily minimum and maximum temperatures, respectively_maxAnd RH_minHighest relative humidity and lowest relative humidity, respectively; and the saturated vapor pressure is calculated as follows:

wherein T is nullThe temperature of the gas.

3. The method of claim 1, wherein after said acquiring leaf area index, wind speed, air temperature, surface received short wave, long wave radiation data, further comprising:

and removing the points with the attribute values being null or extracting the points with the cloud pixel values.

4. The method of claim 1, further comprising:

acquiring point, line or surface element information containing geographic information;

constructing a geographical range according to geographical information in the point, line or surface element information;

and extracting the constructed fluorescence image in the geographical range from the chlorophyll fluorescence image to construct and obtain the cut chlorophyll fluorescence image.

5. The method of claim 1, further comprising:

obtaining at least 2 chlorophyll fluorescence images;

constructing a geographical information range covering all areas according to the geographical range information in the chlorophyll fluorescence image;

and extracting the fluorescence attribute value in the geographic information range covering all the areas to construct and obtain the mosaic chlorophyll fluorescence image.

6. A system for acquiring daylight-induced chlorophyll fluorescence data, comprising:

the first data acquisition module is used for acquiring vapor pressure content data and earth surface reflectivity data;

the data inversion module is used for performing inversion to obtain chlorophyll content data based on the earth surface reflectivity data and a preset lookup table;

the second data acquisition module is used for acquiring the leaf area index, the wind speed, the air temperature and the earth surface receiving short wave and long wave radiation data;

and the data processing module is used for inputting the vapor pressure content data, the leaf area index, the wind speed, the air temperature, the ground surface receiving short wave and long wave radiation data and the chlorophyll content data into a preset radiation transmission model and outputting to obtain chlorophyll fluorescence data.

7. The system of claim 6, wherein the first data acquisition module comprises: a vapor pressure content acquisition unit and a surface reflectivity acquisition unit;

the vapor pressure content acquiring unit includes:

the data acquisition subunit is used for acquiring relative humidity data and air temperature data;

a first calculating subunit for calculatingCalculating to obtain the vapor pressure content data e_a(ii) a Wherein, e (T)_min) And e (T)_max) The saturated vapor pressure, RH, corresponding to the daily minimum and maximum temperatures, respectively_maxAnd RH_minHighest relative humidity and lowest relative humidity, respectively;

a second calculation subunit for passing the formulaCalculating to obtain the saturated vapor pressure; wherein T is the air temperature;

the earth surface reflectivity acquiring unit is used for acquiring earth surface reflectivity data.

8. The system of claim 6, further comprising:

and the inspection module is used for removing the points with the attribute values being null or extracting the cloud pixel values.

9. The system of claim 6, further comprising:

the third data acquisition module is used for acquiring point, line or surface element information containing geographic information;

the first geographic range building module is used for building a geographic range according to geographic information in the point, line or surface element information;

and the cutting module is used for extracting the constructed fluorescence image in the geographical range from the chlorophyll fluorescence image so as to construct and obtain the cut chlorophyll fluorescence image.

10. The system of claim 6, further comprising:

the fourth data acquisition module is used for acquiring at least 2 chlorophyll fluorescence images;

the second geographical range construction module is used for constructing a geographical information range covering all areas according to the geographical range information in the chlorophyll fluorescence image;

and the mosaic module is used for extracting the fluorescence attribute values in the geographic information range covering all the areas, so that the mosaic chlorophyll fluorescence image can be constructed.

Technical Field

The invention relates to the technical field of agricultural energy, in particular to a method and a system for acquiring sunlight-induced chlorophyll fluorescence data.

Background

The sunlight-induced chlorophyll fluorescence (hereinafter referred to as chlorophyll fluorescence, SIF) is an optical signal between 650-800nm, which is actively released when plants are subjected to photosynthesis under natural light conditions. Chlorophyll fluorescence, one of the byproducts of photosynthesis, is closely related to photosynthetically active radiation, total primary productivity of vegetation, and various stress factors. Therefore, accurate measurement and calculation of chlorophyll fluorescence have wide prospects and important meanings for monitoring vegetation growth conditions, regional ecosystem stability, global carbon source carbon sink distribution and land carbon circulation conditions.

In order to improve the time-space resolution of chlorophyll fluorescence so as to be suitable for quantitative analysis, high-precision and small-scale scientific research, the existing production method is based on a machine learning algorithm and is limited by the inherent time-space resolution of a sensor.

Disclosure of Invention

The invention provides a method and a system for acquiring sunlight-induced chlorophyll fluorescence data, and solves the technical problem that the prior art is based on a machine learning algorithm and is limited by inherent space-time resolution of a sensor.

The invention provides a method for acquiring sunlight-induced chlorophyll fluorescence data, which comprises the following steps:

acquiring vapor pressure content data and surface reflectivity data;

performing inversion based on the surface reflectivity data and a preset lookup table to obtain chlorophyll content data;

acquiring leaf area index, wind speed, air temperature and earth surface receiving short wave and long wave radiation data;

and inputting the vapor pressure content data, the leaf area index, the wind speed, the air temperature, the earth surface receiving short wave and long wave radiation data and the chlorophyll content data into a preset radiation transmission model, and outputting to obtain chlorophyll fluorescence data.

Further, the acquiring vapor pressure content data comprises:

acquiring relative humidity data and air temperature data;

by the formulaCalculating to obtain the vapor pressure content data e_a；

Wherein, e (T)_min) And e (T)_max) The saturated vapor pressure, RH, corresponding to the daily minimum and maximum temperatures, respectively_maxAnd RH_minHighest relative humidity and lowest relative humidity, respectively; and the saturated vapor pressure is calculated as follows:

wherein T is the air temperature.

Further, after the acquiring of the leaf area index, the wind speed, the air temperature, and the earth surface receiving short wave and long wave radiation data, the method further comprises the following steps:

and removing the points with the attribute values being null or extracting the points with the cloud pixel values.

Further, still include:

acquiring point, line or surface element information containing geographic information;

constructing a geographical range according to geographical information in the point, line or surface element information;

and extracting the constructed fluorescence image in the geographical range from the chlorophyll fluorescence image to construct and obtain the cut chlorophyll fluorescence image.

Further, still include:

obtaining at least 2 chlorophyll fluorescence images;

constructing a geographical information range covering all areas according to the geographical range information in the chlorophyll fluorescence image;

and extracting the fluorescence attribute value in the geographic information range covering all the areas to construct and obtain the mosaic chlorophyll fluorescence image.

The invention also provides a system for acquiring the sunlight-induced chlorophyll fluorescence data, which comprises:

the first data acquisition module is used for acquiring vapor pressure content data and earth surface reflectivity data;

the data inversion module is used for performing inversion to obtain chlorophyll content data based on the earth surface reflectivity data and a preset lookup table;

the second data acquisition module is used for acquiring the leaf area index, the wind speed, the air temperature and the earth surface receiving short wave and long wave radiation data;

and the data processing module is used for inputting the vapor pressure content data, the leaf area index, the wind speed, the air temperature, the ground surface receiving short wave and long wave radiation data and the chlorophyll content data into a preset radiation transmission model and outputting to obtain chlorophyll fluorescence data.

Further, the first data obtaining module includes: a vapor pressure content acquisition unit and a surface reflectivity acquisition unit;

the vapor pressure content acquiring unit includes:

the data acquisition subunit is used for acquiring relative humidity data and air temperature data;

a first calculating subunit for calculatingCalculating to obtain the vapor pressure content data e_a(ii) a Wherein, e (T)_min) And e (T)_max) The saturated vapor pressure, RH, corresponding to the daily minimum and maximum temperatures, respectively_maxAnd RH_minHighest relative humidity and lowest relative humidity, respectively;

a second calculation subunit for passing the formulaCalculating to obtain the saturated vapor pressure; wherein T is the air temperature;

the earth surface reflectivity acquiring unit is used for acquiring earth surface reflectivity data.

Further, still include:

and the inspection module is used for removing the points with the attribute values being null or extracting the cloud pixel values.

Further, still include:

the third data acquisition module is used for acquiring point, line or surface element information containing geographic information;

the first geographic range building module is used for building a geographic range according to geographic information in the point, line or surface element information;

and the cutting module is used for extracting the constructed fluorescence image in the geographical range from the chlorophyll fluorescence image so as to construct and obtain the cut chlorophyll fluorescence image.

Further, still include:

the fourth data acquisition module is used for acquiring at least 2 chlorophyll fluorescence images;

the second geographical range construction module is used for constructing a geographical information range covering all areas according to the geographical range information in the chlorophyll fluorescence image;

and the mosaic module is used for extracting the fluorescence attribute values in the geographic information range covering all the areas, so that the mosaic chlorophyll fluorescence image can be constructed.

One or more technical schemes provided by the invention at least have the following technical effects or advantages:

firstly, acquiring vapor pressure content data, surface reflectivity data, leaf area index, wind speed, air temperature and surface receiving short wave and long wave radiation data; performing inversion based on the surface reflectivity data and a preset lookup table to obtain chlorophyll content data; and inputting the vapor pressure content data, the leaf area index, the wind speed, the air temperature, the earth surface receiving short wave and long wave radiation data and the chlorophyll content data into a preset radiation transmission model, and outputting to obtain chlorophyll fluorescence data. The data set obtained by the method has high space-time resolution, and the data acquisition result has stronger physical basis, so that the method can be suitable for large, medium and small scale fluorescence inversion verification and deep application of fluorescence data products.

Drawings

Fig. 1 is a flowchart of a method for acquiring sunlight-induced chlorophyll fluorescence data according to an embodiment of the present invention;

FIG. 2 is a schematic diagram of a method for obtaining sunlight-induced chlorophyll fluorescence data according to an embodiment of the present invention;

fig. 3 is a distribution diagram of chlorophyll fluorescence data of the first 8 days of 8 months in 2018 in south america, which is obtained by the method for acquiring sunlight-induced chlorophyll fluorescence data according to the embodiment of the present invention;

fig. 4 is a block diagram of a system for acquiring sunlight-induced chlorophyll fluorescence data according to an embodiment of the present invention.

Detailed Description

The embodiment of the invention provides a method and a system for acquiring sunlight-induced chlorophyll fluorescence data, and solves the technical problem that the prior art is based on a machine learning algorithm and is limited by inherent space-time resolution of a sensor.

In order to solve the above problems, the technical solution in the embodiments of the present invention has the following general idea:

firstly, acquiring vapor pressure content data, surface reflectivity data, leaf area index, wind speed, air temperature and surface receiving short wave and long wave radiation data; performing inversion based on the surface reflectivity data and a preset lookup table to obtain chlorophyll content data; and inputting the vapor pressure content data, the leaf area index, the wind speed, the air temperature, the earth surface receiving short wave and long wave radiation data and the chlorophyll content data into a preset radiation transmission model, and outputting to obtain chlorophyll fluorescence data. The data set obtained by the method has high space-time resolution, and the data acquisition result has stronger physical basis, so that the method can be suitable for large, medium and small scale fluorescence inversion verification and deep application of fluorescence data products.

For better understanding of the above technical solutions, the following detailed descriptions will be provided in conjunction with the drawings and the detailed description of the embodiments.

Referring to fig. 1, the method for acquiring sunlight-induced chlorophyll fluorescence data provided by the embodiment of the present invention includes:

step S110: acquiring vapor pressure content data and surface reflectivity data;

specifically, vapor pressure content data is obtained, including:

acquiring relative humidity data and air temperature data;

by the formulaVapor pressure content data e is obtained by calculation_a；

Wherein, e (T)_min) And e (T)_maxThe saturated vapor pressure, RH, corresponding to the daily minimum and maximum temperatures, respectively_maxAnd RH_minHighest relative humidity and lowest relative humidity, respectively; and the saturated vapor pressure is calculated as follows:

wherein T is the air temperature.

Step S120: performing inversion based on the surface reflectivity data and a preset lookup table to obtain chlorophyll content data;

step S130: acquiring leaf area index, wind speed, air temperature and earth surface receiving short wave and long wave radiation data;

in order to remove the illegal and low-quality points and improve the acquisition precision of the sunlight-induced chlorophyll fluorescence data of the embodiment of the invention, after acquiring the leaf area index, the wind speed, the air temperature and the ground surface receiving short-wave and long-wave radiation data, the method further comprises the following steps:

and removing the points with the attribute values being null or extracting the points with the cloud pixel values.

It should be noted that, in the embodiment of the present invention, data acquisition is not in sequence, that is, data of steam pressure content, data of surface reflectivity, leaf area index, wind speed, air temperature, and data of surface receiving short-wave and long-wave radiation are actually not in sequence.

Step S140: inputting the vapor pressure content data, the leaf area index, the wind speed, the air temperature, the earth surface receiving short wave and long wave radiation data and the chlorophyll content data into a preset radiation transmission model, and outputting to obtain chlorophyll fluorescence data;

in order to complement the fluorescence signal value of the vacant pixel, after chlorophyll fluorescence data is obtained through output, a certain number of pixels are searched in the neighborhood of the vacant pixel to form a linear weight combination, and the fluorescence signal value of the vacant pixel is complemented. The number of the neighborhoods is determined by the effective points: if the number of the effective points is less, selecting a search neighborhood as 12, thereby ensuring that the number of surrounding points is sampled as much as possible; if the number of the effective points is more, the search neighborhood is selected to be 8, so that the sampling point is not influenced by the numerical value of too many remote points. That is to say, in the embodiment of the present invention, the search neighborhood is set to be 8 or 12 to complement the blank pixel, that is, 8 or 12 pixels are searched around the blank pixel to form a linear weight combination, and the fluorescence value of the blank pixel is calculated.

In order to obtain the remote sensing image format data of any region in the global scope at fixed time, the method further comprises the following steps:

acquiring point, line or surface element information containing geographic information;

and constructing a geographical range according to the geographical information in the point, line or surface element information, namely the geographical coordinates of a certain point, the coordinates along a certain line or the geographical coordinate range of a certain surface element.

And extracting the constructed fluorescence image in the geographical range from the chlorophyll fluorescence image to construct and obtain the cut chlorophyll fluorescence image.

And/or the presence of a gas in the gas,

obtaining at least 2 chlorophyll fluorescence images;

constructing a geographical information range covering all areas according to the geographical range information in the chlorophyll fluorescence image;

and (4) extracting fluorescence attribute values in the geographic information range covering all the areas, and constructing and obtaining the mosaic chlorophyll fluorescence image.

If multiple-valued coincidence of fluorescence values occurs at a certain geographic location, an average is taken.

Referring to fig. 2, the method for acquiring sunlight-induced chlorophyll fluorescence data provided by the embodiment of the present invention is specifically described below with reference to specific examples (taking the production process of chlorophyll fluorescence data in 8/2018 in south america as an example):

1. grid making

Grids with 1km by 1km resolution are fabricated from the desired geographic region (500m by 500m grids may also be collected here to improve spatial resolution), and the grids are tailored to the land distribution on the earth's surface using the face vector data from seven continents. And simultaneously, collecting geographic longitude and latitude data of the grid. In this example, 615,733 grid points in south america were collected.

2. Vapor pressure content calculation

The vapor pressure content was calculated using the daily average relative humidity data and the daily average temperature data of the MERRA-2 satellite. In this example, data was collected and calculated for the first 8 days of 8 months in 2018. The vapor pressure content can be calculated from the relative humidity and air temperature:

wherein e is_aIs the vapor pressure, e (T)_min) And e (T)_max) The saturated vapor pressure, RH, corresponding to the daily minimum temperature and the maximum temperature, respectively_maxAnd RH_minRespectively, the highest relative humidity and the lowest relative humidity. The saturated vapor pressure is calculated as follows:

wherein T is the air temperature.

3. Chlorophyll content inversion

And establishing a lookup table based on the blade radiation transmission model. The lookup table consists of different biochemical parameters of the leaf (including leaf structure parameters, chlorophyll, carotenoid, water, dry matter and anthocyanin content) and reflectance and transmittance curves obtained by forward calculation in the range of 400-2500 nm. From previous studies it is known that: leaf reflectance curve of four parameters of chlorophyll, carotenoid, water and dry matter content on leaf scaleThe influence of the line accounts for more than 90%, so that the chlorophyll content value range is 1, 100]ug/cm²Step length is 0.1; the dry matter content value range is [0.002, 0.05 ]]ug/cm²The step length is 0.005; the water content value range is [0.01, 0.09 ]]cm, the step length is 0.005; the carotenoid content is 1/4 of chlorophyll content. A total of 9911 pieces of data are combined into a lookup table (here, the data capacity of the lookup table can be increased by changing the step size and the parameter value field to further improve the chlorophyll inversion accuracy).

And (3) extracting MODIS surface reflectivity data at the grid by using a Google Earth Engine platform (hereinafter referred to as GEE) for seven wave bands in total, and inverting the surface chlorophyll content by using a lookup table. And the inversion process is to compare the difference value between the MODIS reflectivity data of a certain grid and the reflectivity data in the lookup table, and to take the chlorophyll content corresponding to the lookup table data with the closest reflectivity as the chlorophyll content of the grid. In this example, MODIS surface reflectivity data was collected in the first 8 days of 8 months in 2018 and subjected to look-up table inversion.

4. And respectively resampling the leaf area index, the wind speed, the vapor pressure content, the air temperature, the earth surface receiving short wave and long wave radiation data to 0.01 ℃ through a GEE platform, extracting to a grid, removing the point with an empty attribute value or extracting a cloud pixel value, and then exporting a shape file. In the example, data in the first 8 days of 8 months in 2018 are collected to a grid file, 503,729 points in total can be used for calculating fluorescence after data quality screening, and the legal effective point proportion of the data is as high as 81.8%.

5. Radiation transport model calculation

The radiation transmission model is a chlorophyll fluorescence radiation transmission model, and chlorophyll fluorescence signals are inverted by inputting parameters such as soil, leaves, canopy, weather, observation orientation and the like. After reading the grid shape file, fluorescence values (typical fluorescence data wavelengths are 740nm, 757nm and 771nm) at each grid point are calculated and stored into attribute values of the grid points.

6. Data post-processing and export

The data post-processing part is mainly used for complementing the fluorescence signal value of the vacant pixel in south America and defining a projection mode. The individual projection parameters (e.g., reference planes and ellipsoids) are added to a projection definition file (PRJ) and associated with a fluorescent mesh file for use on any geographic information processing platform. Because the available points in the area are more, the search neighborhood is set to be 8 to complement the vacant pixels. And cutting the complemented result by the surface elements to obtain a final fluorescence image.

Before data export, the data in the format of the remote sensing image with fixed time in any region in the global scope can be obtained by cutting or inlaying according to the actual application requirements. When cutting is carried out, the south America face element vector file is input, and then the geographic coordinate range is constructed according to geographic information in the face element file. And then extracting a fluorescence image in the geographical range of south America from the chlorophyll fluorescence image obtained in the last step to obtain the cut chlorophyll fluorescence image. When embedding is carried out, if the boundaries are not overlapped, the boundaries can be directly merged; if the boundaries overlap, the average of the stacked cells may be used. Both cropping and tessellation may make the final output geographical range satisfactory.

Referring to fig. 3, the final picture file in this example is in GeoTIFF format, the geographic information of the data is chlorophyll fluorescence signals at 757nm in the first 8 days of 8 months in 2018 in south america, and the spatial resolution reaches 1 km.

Referring to fig. 4, the system for acquiring sunlight-induced chlorophyll fluorescence data provided by the embodiment of the present invention includes:

the first data acquisition module 100 is used for acquiring vapor pressure content data and earth surface reflectivity data;

specifically, the first data acquisition module 100 includes: a vapor pressure content acquisition unit and a surface reflectivity acquisition unit;

a vapor pressure content acquiring unit including:

the data acquisition subunit is used for acquiring relative humidity data and air temperature data;

a first calculating subunit for calculatingCalculating to obtain vaporPressure content data e_a(ii) a Wherein, e (T)_min) And e (T)_max) The saturated vapor pressure, RH, corresponding to the daily minimum and maximum temperatures, respectively_maxAnd RH_minHighest relative humidity and lowest relative humidity, respectively;

a second calculation subunit for passing the formulaCalculating to obtain saturated vapor pressure; wherein T is the air temperature;

and the earth surface reflectivity acquiring unit is used for acquiring earth surface reflectivity data.

The data inversion module 200 is used for performing inversion to obtain chlorophyll content data based on the earth surface reflectivity data and a preset lookup table;

the second data acquisition module 300 is used for acquiring the leaf area index, the wind speed, the air temperature and the earth surface receiving short wave and long wave radiation data;

in order to remove the illegal and low-quality points and improve the acquisition precision of the sunlight-induced chlorophyll fluorescence data of the embodiment of the invention, the method further comprises the following steps:

and the inspection module is used for removing the points with the attribute values being null or extracting the cloud pixel values.

It should be noted that, in the embodiment of the present invention, data acquisition is not in sequence, that is, data of steam pressure content, data of surface reflectivity, leaf area index, wind speed, air temperature, and data of surface receiving short-wave and long-wave radiation are actually not in sequence.

The data processing module 400 is used for inputting the vapor pressure content data, the leaf area index, the wind speed, the air temperature, the ground surface receiving short wave and long wave radiation data and the chlorophyll content data into a preset radiation transmission model and outputting to obtain chlorophyll fluorescence data;

in order to complement the fluorescence signal value of the vacant pixel, the method further comprises the following steps:

and the signal complementing module is used for searching a certain number of pixels from the vacant pixel neighborhood to form a linear weight combination and complementing the fluorescent signal value of the vacant pixels. The number of the neighborhoods is determined by the effective points: if the number of the effective points is less, selecting a search neighborhood as 12, thereby ensuring that the number of surrounding points is sampled as much as possible; if the number of the effective points is more, the search neighborhood is selected to be 8, so that the sampling point is not influenced by the numerical value of too many remote points. That is to say, in the embodiment of the present invention, the search neighborhood is set to be 8 or 12 to complement the blank pixel, that is, 8 or 12 pixels are searched around the blank pixel to form a linear weight combination, and the fluorescence value of the blank pixel is calculated.

In order to obtain the remote sensing image format data of any region in the global scope at fixed time, the method further comprises the following steps:

the third data acquisition module is used for acquiring point, line or surface element information containing geographic information;

and the first geographic range building module is used for building a geographic range according to the geographic information in the point, line or surface element information, namely the geographic coordinate of a certain point, the coordinate along a certain line or the geographic coordinate range of a certain surface element.

And the cutting module is used for extracting the constructed fluorescence image in the geographical range from the chlorophyll fluorescence image so as to construct and obtain the cut chlorophyll fluorescence image.

And/or the presence of a gas in the gas,

the fourth data acquisition module is used for acquiring at least 2 chlorophyll fluorescence images;

the second geographical range construction module is used for constructing a geographical information range covering all the areas according to the geographical range information in the chlorophyll fluorescence image;

and the mosaic module is used for extracting fluorescence attribute values in a geographic information range covering all the areas, so that a mosaic chlorophyll fluorescence image can be constructed. If multiple-valued coincidence of fluorescence values occurs at a certain geographic location, an average is taken.

Technical effects

1. Firstly, acquiring vapor pressure content data, surface reflectivity data, leaf area index, wind speed, air temperature and surface receiving short wave and long wave radiation data; performing inversion based on the surface reflectivity data and a preset lookup table to obtain chlorophyll content data; and inputting the vapor pressure content data, the leaf area index, the wind speed, the air temperature, the earth surface receiving short wave and long wave radiation data and the chlorophyll content data into a preset radiation transmission model, and outputting to obtain chlorophyll fluorescence data. The data set obtained by the embodiment of the invention has high space-time resolution, and the data acquisition result has stronger physical basis, so that the method can be suitable for large, medium and small scale fluorescence inversion verification and deep application of fluorescence data products.

2. After the short-wave and long-wave radiation data received by the leaf area index, the wind speed, the air temperature and the earth surface are obtained, the points with the attribute values being null or the cloud pixel-containing values are extracted, so that the illegal and low-quality points are removed, and the obtaining precision of the sunlight-induced chlorophyll fluorescence data is improved.

3. After chlorophyll fluorescence data are obtained through output, a certain number of pixels are searched in the neighborhood of the vacant pixels to form a linear weight combination, so that the fluorescence signal value of the vacant pixels can be complemented.

4. By cutting and inlaying, the remote sensing image format data of any region in the global scope at fixed time can be obtained.

Aiming at the current state of the prior art, the embodiment of the invention calculates the global chlorophyll fluorescence signals of the earth surface by using MODIS reflectivity, Leaf Area Index (LAI), MERRA-2 wind speed, air temperature, air humidity and atmospheric short-wave and long-wave radiation data sets based on the chlorophyll fluorescence radiation transmission physical mechanism, wherein the spatial resolution can reach 0.005-0.01 degrees (500m-1km) and the time resolution can reach 8 days. The embodiment of the invention can be used as a ground surface chlorophyll fluorescence inversion verification data set, and can also be suitable for the deep fusion application of fluorescence and other remote sensing products in various scales.

As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.

The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

While preferred embodiments of the present invention have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. Therefore, it is intended that the appended claims be interpreted as including preferred embodiments and all such alterations and modifications as fall within the scope of the invention.

It will be apparent to those skilled in the art that various changes and modifications may be made in the present invention without departing from the spirit and scope of the invention. Thus, if such modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include such modifications and variations.