CN111597692A - Surface net radiation estimation method, system, electronic equipment and storage medium - Google Patents
Surface net radiation estimation method, system, electronic equipment and storage medium Download PDFInfo
- Publication number
- CN111597692A CN111597692A CN202010340715.7A CN202010340715A CN111597692A CN 111597692 A CN111597692 A CN 111597692A CN 202010340715 A CN202010340715 A CN 202010340715A CN 111597692 A CN111597692 A CN 111597692A
- Authority
- CN
- China
- Prior art keywords
- data
- net radiation
- area
- surface net
- source data
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- 230000005855 radiation Effects 0.000 title claims abstract description 312
- 238000000034 method Methods 0.000 title claims abstract description 51
- 238000004458 analytical method Methods 0.000 claims abstract description 40
- 238000005259 measurement Methods 0.000 claims abstract description 27
- 238000012549 training Methods 0.000 claims abstract description 14
- 230000002159 abnormal effect Effects 0.000 claims description 15
- 238000004590 computer program Methods 0.000 claims description 7
- 238000012950 reanalysis Methods 0.000 abstract description 9
- 230000000875 corresponding effect Effects 0.000 description 33
- 238000012216 screening Methods 0.000 description 7
- 238000010586 diagram Methods 0.000 description 6
- 238000012360 testing method Methods 0.000 description 5
- 238000004891 communication Methods 0.000 description 4
- 238000004422 calculation algorithm Methods 0.000 description 2
- 230000008859 change Effects 0.000 description 2
- 238000004519 manufacturing process Methods 0.000 description 2
- 230000003287 optical effect Effects 0.000 description 2
- 238000007637 random forest analysis Methods 0.000 description 2
- 238000011160 research Methods 0.000 description 2
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 2
- 239000002028 Biomass Substances 0.000 description 1
- 238000009825 accumulation Methods 0.000 description 1
- 230000035508 accumulation Effects 0.000 description 1
- 230000005540 biological transmission Effects 0.000 description 1
- 230000015572 biosynthetic process Effects 0.000 description 1
- 230000002596 correlated effect Effects 0.000 description 1
- 230000001419 dependent effect Effects 0.000 description 1
- 238000001514 detection method Methods 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 230000004907 flux Effects 0.000 description 1
- 238000005755 formation reaction Methods 0.000 description 1
- 239000011521 glass Substances 0.000 description 1
- 230000012010 growth Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000008638 plant developmental process Effects 0.000 description 1
- 230000008635 plant growth Effects 0.000 description 1
- 239000011435 rock Substances 0.000 description 1
- 238000007619 statistical method Methods 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/20—Design optimisation, verification or simulation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/25—Fusion techniques
Landscapes
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Physics & Mathematics (AREA)
- Evolutionary Computation (AREA)
- General Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Data Mining & Analysis (AREA)
- Bioinformatics & Cheminformatics (AREA)
- Bioinformatics & Computational Biology (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Evolutionary Biology (AREA)
- Artificial Intelligence (AREA)
- Life Sciences & Earth Sciences (AREA)
- Computer Hardware Design (AREA)
- Geometry (AREA)
- Geophysics And Detection Of Objects (AREA)
Abstract
The embodiment of the invention provides a method, a system, electronic equipment and a storage medium for estimating surface net radiation, wherein the method comprises the following steps: determining multisource data of the area to be detected based on the first remote sensing data and the re-analysis meteorological data of the area to be detected, or the second remote sensing data, the re-analysis meteorological data and downlink short wave radiation from site actual measurement data; the first remote sensing data comprise downlink short wave radiation, and the second remote sensing data do not comprise downlink short wave radiation; inputting the multi-source data into a surface net radiation estimation model to obtain a surface net radiation estimation result of the region to be detected, which is output by the surface net radiation estimation model; the surface net radiation estimation model is obtained by training sample site measured data, a sample normalized vegetation index and sample reanalysis meteorological data based on the sample area, the sample site measured data comprise sample downlink short wave radiation, sample surface albedo and sample surface net radiation, and estimation of the surface net radiation with high precision and high resolution is achieved.
Description
Technical Field
The invention relates to the technical field of remote sensing, in particular to a method and a system for estimating surface net radiation, electronic equipment and a storage medium.
Background
The surface net radiation is the most important parameter in the surface energy balance and is also one of the important parameters for constructing various ecological modes. Under the background of global climate change, the high-quality long-time-sequence net radiation data has important significance for researches such as climate change prediction, evapotranspiration estimation, plant growth and development processes, and formation and accumulation of ecosystem biomass. Remote sensing technology provides an effective observation means from a global scale, and is always an important mode for inversion of radiation parameters. The existing remote sensing products containing net radiation are generally low in resolution (over kilometer grade) and difficult to meet the requirements of small-area radiation balance research.
At present, the net radiation estimation method based on remote sensing data mainly utilizes a parameterization mode to respectively estimate short wave radiation components and long wave radiation components related to net radiation, and then sums and calculates the net radiation. The other method is a net radiation direct estimation method, an empirical model for directly estimating net radiation from short wave radiation is established by using various statistical methods based on high correlation between the short wave radiation and the net radiation and with the help of other auxiliary information, and the method has the advantages of easy acquisition of required parameters, high operating efficiency, good universality and satisfactory estimation precision, so the method becomes a preferred method for producing the net radiation data product at present. However, this method is highly dependent on the accuracy of the input data and the sample quality and comprehensiveness for model generation, etc., and is not currently used for high resolution (tens and beyond) net radiation estimation production.
Therefore, how to realize the estimation of the surface net radiation with long time sequence, high resolution and high precision becomes a problem to be solved urgently.
Disclosure of Invention
The embodiment of the invention provides a method, a system, electronic equipment and a storage medium for estimating surface net radiation, which are used for solving the problems of low resolution and low precision of the existing method for estimating surface net radiation.
In a first aspect, an embodiment of the present invention provides a method for estimating surface net radiation, including:
determining multi-source data of the area to be detected based on first remote sensing data and re-analysis meteorological data of the area to be detected, or second remote sensing data, the re-analysis meteorological data and downlink short wave radiation from site actual measurement data; the first remote sensing data comprise downlink short wave radiation, and the second remote sensing data do not comprise downlink short wave radiation;
inputting the multi-source data into a surface net radiation estimation model to obtain a surface net radiation estimation result of the region to be detected, which is output by the surface net radiation estimation model;
the surface net radiation estimation model is obtained by training based on sample site measured data, a sample normalized vegetation index and sample re-analysis meteorological data of a sample area, wherein the sample site measured data comprises sample downlink short wave radiation, sample surface albedo and sample surface net radiation.
Optionally, the inputting the multi-source data into a surface net radiation estimation model to obtain a surface net radiation estimation result of the region to be measured output by the surface net radiation estimation model specifically includes:
judging the surface attribute of the area to be detected based on the multi-source data;
and inputting the multi-source data into a surface net radiation estimation model corresponding to the surface attribute of the region to be detected, and obtaining a surface net radiation estimation result of the region to be detected output by the surface net radiation estimation model.
Optionally, the determining, based on the multi-source data, the surface attribute of the region to be measured specifically includes:
and determining the earth surface attribute of the area to be measured based on the normalized vegetation index and the earth surface albedo in the multi-source data.
Optionally, the determining the surface attribute of the region to be measured based on the normalized vegetation index and the surface albedo in the multi-source data specifically includes:
if the normalized vegetation index in the multi-source data is larger than a preset first threshold value and the earth surface albedo in the multi-source data is smaller than or equal to a preset second threshold value, determining the earth surface attribute of the area to be measured as a vegetation coverage class;
if the normalized vegetation index in the multi-source data is less than or equal to the preset first threshold value, or the earth surface albedo in the multi-source data is greater than the preset second threshold value, and the sunshine duration in the multi-source data is within a preset time range, determining that the earth surface attribute of the area to be measured is a normal sunshine duration non-vegetation coverage type;
otherwise, determining the earth surface attribute of the area to be detected as the non-vegetation coverage class with the abnormal sunshine duration.
Optionally, the inputting the multi-source data into the surface net radiation estimation model corresponding to the surface attribute of the region to be measured to obtain the surface net radiation estimation result of the region to be measured output by the surface net radiation estimation model specifically includes:
if the earth surface attribute of the area to be measured is a vegetation coverage type, inputting multi-source data including the normalized vegetation index into an earth surface net radiation estimation model corresponding to the vegetation coverage type to obtain an earth surface net radiation estimation result of the area to be measured output by the earth surface net radiation estimation model;
if the earth surface attribute of the area to be measured is normal sunshine duration non-vegetation coverage, inputting multi-source data except the normalized vegetation index into an earth surface net radiation estimation model corresponding to the normal sunshine duration non-vegetation coverage, and obtaining an earth surface net radiation estimation result of the area to be measured output by the earth surface net radiation estimation model;
and if the earth surface attribute of the area to be measured is an abnormal sunshine duration non-vegetation coverage type, inputting multi-source data except the normalized vegetation index into an earth surface net radiation estimation model corresponding to the abnormal sunshine duration non-vegetation coverage type to obtain an earth surface net radiation estimation result of the area to be measured output by the earth surface net radiation estimation model.
Optionally, the determining the multi-source data of the region to be measured based on the first remote sensing data and the re-analysis meteorological data of the region to be measured, or the second remote sensing data, the re-analysis meteorological data and the downlink short wave radiation from the site measured data specifically includes:
and adding data with the acquisition time within the preset time length before and after the site observation time in the first remote sensing data or the second remote sensing data of the area to be detected to the multi-source data of the area to be detected.
Optionally, the multi-source data further comprises a ground albedo, a normalized vegetation index, a meteorological parameter, and a geographic parameter.
In a second aspect, an embodiment of the present invention provides a surface net radiation estimation system, including:
the multi-source data determining module is used for determining the multi-source data of the area to be detected based on the first remote sensing data and the re-analysis meteorological data of the area to be detected, or the second remote sensing data, the re-analysis meteorological data and the downlink short wave radiation from the station actual measurement data; the first remote sensing data comprise downlink short wave radiation, and the second remote sensing data do not comprise downlink short wave radiation;
the surface net radiation estimation module is used for inputting the multi-source data to a surface net radiation estimation model to obtain a surface net radiation estimation result of the area to be detected, which is output by the surface net radiation estimation model;
the surface net radiation estimation model is obtained by training based on sample site measured data, a sample normalized vegetation index and sample re-analysis meteorological data of a sample area, wherein the sample site measured data comprises sample downlink short wave radiation, sample surface albedo and sample surface net radiation.
In a third aspect, an embodiment of the present invention provides an electronic device, including: a memory, a processor and a computer program stored on the memory and executable on the processor, the processor when executing the program implementing a surface net radiation estimation method as described in the first aspect.
In a fourth aspect, an embodiment of the present invention provides a non-transitory computer-readable storage medium, on which a computer program is stored, which, when executed by a processor, implements the surface net radiation estimation method according to the first aspect.
According to the method, the system, the electronic device and the storage medium for estimating the surface net radiation, the multi-source data containing the downlink short-wave radiation is determined based on the first remote sensing data and the re-analysis meteorological data of the region to be measured, or the second remote sensing data, the re-analysis meteorological data and the downlink short-wave radiation from the site measured data, the information amount of the input data is increased, the multi-source data is input into the surface net radiation estimation model, the resolution and the precision of the surface net radiation estimation are improved by exerting the advantages of different data sources, and the estimation of the surface net radiation with long time sequence, high precision and high resolution can be achieved.
Drawings
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 method for estimating net surface radiance according to an embodiment of the present invention;
fig. 2 is a schematic diagram of determining a surface property of a region to be measured according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of a system for estimating net surface radiation according to an embodiment of the present invention;
fig. 4 is a schematic structural diagram of an electronic device according to an embodiment of the present 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.
Fig. 1 is a schematic flow chart of a method for estimating net surface radiation according to an embodiment of the present invention, and as shown in fig. 1, the method for estimating net surface radiation according to an embodiment of the present invention includes:
Specifically, the multi-source data of the region to be measured is a data set formed by data of multiple sources obtained by observing the surface net radiation region to be estimated based on multiple technical means. The determination mode of the multi-source data comprises two modes: the first method is that multi-source data is determined based on first remote sensing data and re-analysis meteorological data of a region to be measured; and the second method is to determine multi-source data based on second remote sensing data of the region to be measured, re-analysis meteorological data and downlink short wave radiation from site measured data.
The first remote sensing data and the second remote sensing data are remote sensing data products of an area to be measured, which are acquired based on a remote sensing satellite, the first remote sensing data can comprise downlink short wave radiation, a ground surface albedo, a normalized vegetation index and the like, and the second remote sensing data can comprise the ground surface albedo, the normalized vegetation index and the like. Preferably, the downlink short wave radiation contained in the first remote sensing data can be a GLASS data product, and the earth surface albedo and the normalized vegetation index can be Landsat data products.
The site actual measurement data of the area to be measured is actually observed data of the foundation sites arranged in the area to be measured, and can include downlink short wave radiation, earth surface albedo and the like. The re-analyzed meteorological data for the area under test may provide meteorological parameters for the area under test. Preferably, the re-analysis meteorological data for the area under test may be MERRA2 data product.
The downlink short wave radiation in the first multi-source data determining mode is from first remote sensing data, and the downlink short wave radiation in the second multi-source data determining mode is from site actual measurement data. In a second multi-source data determining manner, the earth surface albedo may be from the second remote sensing data or from site measured data, which is not specifically limited in this embodiment of the present invention.
the surface net radiation estimation model is obtained by training sample site actual measurement data, a sample normalized vegetation index and sample reanalysis meteorological data based on the sample area, and the sample site actual measurement data comprise sample downlink short wave radiation, sample surface albedo and sample surface net radiation.
Specifically, the multi-source data must include downlink short-wave radiation, and the surface net radiation model is used for calculating and outputting a surface net radiation estimation result of the region to be measured according to the input downlink short-wave radiation of the multi-source data based on the high correlation between the downlink short-wave radiation and the surface net radiation. Because the normalized vegetation index and the earth surface albedo in the input multi-source data are high in spatial resolution (up to 30 meters) and high in time resolution (up to 1 day), the output earth surface net radiation estimation result of the area to be detected has high space-time resolution.
When downlink short wave radiation in the multi-source data is determined through station actual measurement data of the region to be measured, the resolution of the downlink short wave radiation can be further improved, and high-precision surface net radiation estimation of a small region can be achieved. When downlink short wave radiation in the multi-source data is determined through the second remote sensing data of the region to be measured, surface net radiation estimation of a long time sequence and a global coverage can be obtained based on the characteristics of long time sequence and large coverage of the remote sensing data.
Before step 120 is executed, the surface net radiation estimation model may also be trained in advance, and may specifically be trained as follows: firstly, collecting multi-source data of a global area, and screening sample site actual measurement data, a sample normalized vegetation index and sample reanalysis meteorological data of a sample area according to preset screening conditions, wherein the sample site actual measurement data comprise sample downlink short wave radiation, sample earth surface albedo and sample earth surface net radiation. And inputting the sample site actual measurement data, the sample normalized vegetation index and the sample re-analysis meteorological data of the sample area into the initial model for training so as to obtain the surface net radiation estimation model. The initial model here may be constructed based on a random forest algorithm.
The preset screening condition is that the measured data of the sample site in the sample area comprises downlink short wave radiation and surface net radiation, the continuous observation time of the site is more than one year, and the site is located at a conventional geographic position. By screening the multi-source data of the global area, the data quality of the model training data is improved, and the precision of the surface net radiation estimation model is further improved.
According to the surface net radiation estimation method provided by the embodiment of the invention, the multi-source data containing the downlink short wave radiation is determined based on the first remote sensing data and the re-analysis meteorological data of the region to be measured, or the second remote sensing data, the re-analysis meteorological data and the downlink short wave radiation from the site measured data, the information content of the input data is increased, the multi-source data is input into the surface net radiation estimation model, the resolution and the precision of the surface net radiation estimation are improved by exerting the advantages of different data sources, and the estimation of the surface net radiation with long time sequence, high precision and high resolution can be realized.
Based on the above embodiment, step 120 specifically includes:
step 121, judging the surface attribute of the area to be detected based on the multi-source data;
and step 122, inputting the multi-source data into the surface net radiation estimation model corresponding to the surface attribute of the region to be measured, and obtaining a surface net radiation estimation result of the region to be measured output by the surface net radiation estimation model.
In particular, different ground surface types result in different radiation transmission processes, for example the net radiation of snow-covered ground surfaces is not determined by short-wave downlink radiation, whereas the net radiation of vegetation-covered ground surfaces is highly correlated with short-wave radiation. Based on the influence of different surface properties on the relationship between the short wave radiation and the net radiation, the surface net radiation estimation method provided by the embodiment of the invention adopts different surface net radiation estimation models to estimate according to different surface properties of the region to be measured.
Correspondingly, different surface attributes correspond to different surface net radiation estimation models, and the model corresponding to any surface attribute is obtained by training based on sample site measured data, a sample normalized vegetation index and sample reanalysis meteorological data of a sample area belonging to the surface attribute, wherein the sample site measured data comprises sample downlink short wave radiation, sample surface albedo and sample surface net radiation.
Firstly, the surface attribute of the area to be measured is judged based on multi-source data. The multi-source data may further include a normalized vegetation index, a surface albedo and a sunshine duration, and accordingly, the surface attribute of the area to be measured may be determined based on one parameter in the multi-source data or based on a combination of multiple parameters in the multi-source data. The surface attribute of the area to be measured can be a plant-covered type, a non-plant-covered type with normal sunshine duration and a non-plant-covered type with abnormal sunshine duration.
After the earth surface attribute of the region to be detected is judged, the multi-source data are input into an earth surface net radiation estimation model corresponding to the earth surface, and the earth surface net radiation estimation model calculates and outputs an earth surface net radiation estimation result of the region to be detected based on downlink short wave radiation in the multi-source data.
According to the method for estimating the surface net radiation, provided by the embodiment of the invention, the surface attribute of the area to be measured is judged based on the multi-source data, and the multi-source data is input into the surface net radiation estimation model corresponding to the surface attribute of the area to be measured, so that different surface attributes of the area to be measured are estimated by adopting different surface net radiation estimation models, and the precision of surface net radiation estimation is further improved.
Based on any of the above embodiments, step 121 specifically includes:
and judging the earth surface attribute of the area to be detected based on the normalized vegetation index and the earth surface albedo in the multi-source data.
Specifically, the multi-source data includes a Normalized Vegetation Index (NDVI), which is a ratio of a difference between reflectances of a near-infrared band and a red-light band to a sum of reflectances of the near-infrared band and the red-light band, and may represent a growth state of Vegetation and a coverage of the Vegetation. The value of the normalized vegetation index is between-1 and 1, and the surface of the ground is represented as water surface or snow cover when the normalized vegetation index is a negative value; when the normalized vegetation index is close to zero, representing that the earth surface is rock or bare earth; when the normalized vegetation index is a positive value, the representation earth surface has vegetation coverage, and the larger the numerical value is, the larger the vegetation coverage range is. The ground surface Albedo (ABD) is the ratio of the reflection radiant flux of the ground surface to the incident solar radiation, and the ground surface Albedo of the snow covered ground surface is generally more than 0.7, and the ground surface Albedo of the vegetation covered ground surface is generally smaller. It follows that the normalized vegetation index and the ground albedo can be used to distinguish between different ground attributes.
The embodiment of the invention does not specifically limit the method for judging the earth surface attribute of the area to be detected based on the normalized vegetation index and the earth surface albedo in the multi-source data, and the method comprises the following steps: if the normalized vegetation index in the multi-source data is larger than a preset first threshold value and the earth surface albedo in the multi-source data is smaller than or equal to a preset second threshold value, determining the earth surface attribute of the area to be measured as a vegetation coverage class; otherwise, determining the surface attribute of the area to be detected as a non-vegetation coverage type. Preferably, the preset first threshold may be 0.05, and the preset second threshold may be 0.7.
Correspondingly, if the earth surface attribute of the area to be measured is a vegetation coverage class, inputting multi-source data including the normalized vegetation index into an earth surface net radiation estimation model corresponding to the vegetation coverage class; and if the earth surface attribute of the area to be detected is a non-vegetation coverage type, inputting the multi-source data except the normalized vegetation index into an earth surface net radiation estimation model corresponding to the non-vegetation coverage type.
According to the method for estimating the net surface radiation, provided by the embodiment of the invention, the surface attribute of the area to be measured is judged based on the normalized vegetation index and the surface albedo in the multi-source data so as to estimate different surface attributes of the area to be measured by adopting different surface net radiation estimation models, and the precision of estimating the net surface radiation is further improved.
Based on any one of the embodiments, in the method for estimating net surface radiation, the surface attribute of the region to be measured is judged based on the normalized vegetation index and the surface albedo in the multi-source data, and the method specifically includes:
if the normalized vegetation index in the multi-source data is larger than a preset first threshold value and the earth surface albedo in the multi-source data is smaller than or equal to a preset second threshold value, determining the earth surface attribute of the area to be measured as a vegetation coverage class;
if the normalized vegetation index in the multi-source data is less than or equal to a preset first threshold value, or the earth surface albedo in the multi-source data is greater than a preset second threshold value, and the sunshine duration in the multi-source data is within a preset time range, determining that the earth surface attribute of the area to be measured is a normal sunshine duration non-vegetation coverage type;
otherwise, determining the earth surface attribute of the area to be detected as the non-vegetation coverage class with the abnormal sunshine duration.
Specifically, the multi-source data includes a normalized vegetation index, a ground albedo, and a duration of sunshine. Because the normalized vegetation index corresponding to the vegetation-covered land surface is generally high, the vegetation-covered land surface can absorb most of incident solar radiation, and the corresponding land surface albedo is generally low, if the normalized vegetation index in the multi-source data is greater than a preset first threshold value and the land surface albedo in the multi-source data is less than or equal to a preset second threshold value, the land surface attribute of the area to be measured can be determined to be the vegetation coverage type.
Because the sunshine duration (dt) can be used for distinguishing different seasons, further, if the normalized vegetation index in the multi-source data is less than or equal to a preset first threshold, or the earth surface albedo in the multi-source data is greater than a preset second threshold, and the sunshine duration in the multi-source data is within a preset time range, the earth surface attribute of the area to be measured can be determined to be a normal sunshine duration non-vegetation coverage type. Otherwise, determining the earth surface attribute of the area to be detected as the non-vegetation coverage class with the abnormal sunshine duration.
Preferably, the preset first threshold may be 0.05, the preset second threshold may be 0.7, and the preset time range may be 9 to 16 hours. On this basis, fig. 2 is a schematic diagram of the determination of the surface attribute of the area to be measured according to the embodiment of the present invention, and as shown in fig. 2, the surface attribute can be divided into a vegetation coverage class, a normal sunshine duration non-vegetation coverage class, and a non-normal sunshine duration non-vegetation coverage class based on the normalized vegetation index, the surface albedo, and the sunshine duration in the multi-source data.
According to the method for estimating the net surface radiation, provided by the embodiment of the invention, the surface attributes of the area to be measured are divided into the vegetation cover type, the normal sunshine duration non-vegetation cover type and the abnormal sunshine duration non-vegetation cover type based on the normalized vegetation index, the surface albedo and the sunshine duration in the multi-source data, so that different surface attributes of the area to be measured can be estimated by adopting different surface net radiation estimation models, and the estimation precision of the net surface radiation is further improved.
Based on any of the above embodiments, step 122 specifically includes:
if the earth surface attribute of the area to be measured is a vegetation coverage class, inputting multi-source data including the normalized vegetation index into an earth surface net radiation estimation model corresponding to the vegetation coverage class to obtain an earth surface net radiation estimation result of the area to be measured output by the earth surface net radiation estimation model;
if the earth surface attribute of the area to be measured is normal sunshine duration non-vegetation coverage, inputting the multi-source data except the normalized vegetation index into an earth surface net radiation estimation model corresponding to the normal sunshine duration non-vegetation coverage, and obtaining an earth surface net radiation estimation result of the area to be measured output by the earth surface net radiation estimation model;
and if the earth surface attribute of the area to be measured is the non-vegetation coverage class with the abnormal sunshine duration, inputting the multi-source data except the normalized vegetation index into an earth surface net radiation estimation model corresponding to the non-vegetation coverage class with the abnormal sunshine duration to obtain an earth surface net radiation estimation result of the area to be measured output by the earth surface net radiation estimation model.
Specifically, if the earth surface attribute of the area to be measured is a vegetation cover type, the normalized vegetation index in the multi-source data is used for being input to a corresponding earth surface net radiation estimation model for estimation; and if the earth surface attribute of the area to be measured is a normal sunshine duration non-vegetation coverage type or a non-vegetation coverage type, the normalized vegetation index in the multi-source data is not used for being input to a corresponding earth surface net radiation estimation model for estimation.
According to the method for estimating the surface net radiation, provided by the embodiment of the invention, different surface attributes of the region to be measured are estimated by adopting different surface net radiation estimation models, so that the accuracy of surface net radiation estimation is further improved.
Based on any of the above embodiments, step 110 specifically includes:
and adding data with the acquisition time within the preset time length before and after the site observation time in the first remote sensing data or the second remote sensing data of the region to be detected to the multi-source data of the region to be detected.
Specifically, the time resolution of the first remote sensing data or the second remote sensing data of the region to be measured is affected by the observation period of the corresponding remote sensing satellite, so that multi-source data continuously observed for a long time cannot be acquired. The normalized vegetation index and the earth surface albedo are parameters reflecting the characteristics of the underlying surface, obvious fluctuation can not occur in a short time generally, and corresponding data of time in the first remote sensing data or the second remote sensing data within a preset time length before and after the observation time of the station can be added to the multi-source data to obtain the multi-source data continuously observed for a long time. The preset duration may be set according to different remote sensing detection satellites, which is not specifically limited in the embodiment of the present invention.
For example, if the observation period of the Landsat satellite is 16 days, the time resolution of the normalized vegetation index and the ground surface albedo in the Landsat data product is 16 days, and if the time resolution of the actually measured data of the site is 1 day, in order to make the time resolution of the multi-source data be 1 day, the normalized vegetation index and the ground surface albedo in clear sky before and after 4 days of the observation time of the site in the Landsat data product can be used as the normalized vegetation index and the ground surface albedo of the observation time of the site and added to the multi-source data. And if the normalized vegetation index and the ground surface albedo of clear sky within 4 days before and after the observation time of the station do not exist in the Landsat data product, setting the corresponding data of the observation time of the station as null.
According to the method for estimating the surface net radiation, provided by the embodiment of the invention, data with the acquisition time within the preset duration before and after the station observation time in the first remote sensing data or the second remote sensing data of the region to be measured are added to the multi-source data of the region to be measured so as to obtain the multi-source data continuously observed for a long time, and the estimation of the surface net radiation with long time sequence, high resolution and high precision can be realized.
Based on any embodiment, in the surface net radiation estimation method, the multi-source data further comprises a surface albedo, a normalized vegetation index, a meteorological parameter and a geographic parameter.
Specifically, the meteorological parameters may include an average air temperature, a minimum air temperature, a maximum air temperature, an average surface atmospheric pressure, an average relative humidity, an average wind speed, an average water vapor pressure, a sunshine duration, a sunny index, and the like; the geographic parameter may include a distance of day and earth. The average temperature of the air, the lowest temperature of the air, the highest temperature of the air, the surface atmospheric pressure, the average relative humidity and the average wind speed can be determined based on the re-analysis meteorological data of the area to be measured, and the average vapor pressure, the sunshine duration, the clear index and the distance between the day and the ground can be directly calculated based on the multi-source data of the area to be measured.
Based on any of the above embodiments, fig. 3 is a schematic structural diagram of a surface net radiation estimation system according to an embodiment of the present invention, and as shown in fig. 3, the surface net radiation estimation system according to the embodiment of the present invention includes:
the multi-source data determining module 310 is used for determining the multi-source data of the region to be detected based on the first remote sensing data and the re-analysis meteorological data of the region to be detected, or the second remote sensing data, the re-analysis meteorological data and the downlink short wave radiation from the station actual measurement data; the first remote sensing data comprise downlink short wave radiation, and the second remote sensing data do not comprise downlink short wave radiation.
The multi-source data of the region to be measured is a data set formed by data of multiple sources obtained by observing the surface net radiation region to be estimated based on multiple technical means. The determination mode of the multi-source data comprises two modes: the first method is that multi-source data is determined based on first remote sensing data and re-analysis meteorological data of a region to be measured; and the second method is to determine multi-source data based on second remote sensing data of the region to be measured, re-analysis meteorological data and downlink short wave radiation from site measured data.
The first remote sensing data and the second remote sensing data are remote sensing data products of an area to be measured, which are acquired based on a remote sensing satellite, the first remote sensing data can comprise downlink short wave radiation, a ground surface albedo, a normalized vegetation index and the like, and the second remote sensing data can comprise the ground surface albedo, the normalized vegetation index and the like. The site actual measurement data of the area to be measured is actually observed data of the foundation sites arranged in the area to be measured, and can include downlink short wave radiation, earth surface albedo and the like. The re-analyzed meteorological data for the area under test may provide meteorological parameters for the area under test.
The surface net radiation estimation module 320 is used for inputting the multi-source data into the surface net radiation estimation model to obtain a surface net radiation estimation result of the region to be detected, which is output by the surface net radiation estimation model; the surface net radiation estimation model is obtained by training sample site actual measurement data, a sample normalized vegetation index and sample reanalysis meteorological data based on the sample area, and the sample site actual measurement data comprise sample downlink short wave radiation, sample surface albedo and sample surface net radiation.
Specifically, the multi-source data must include downlink short-wave radiation, and the surface net radiation estimation module 320 inputs the multi-source data to the surface net radiation estimation model based on the high correlation between the downlink short-wave radiation and the surface net radiation, and outputs a surface net radiation estimation result of the region to be measured.
The determination method of the surface net radiation estimation model comprises the following steps: firstly, collecting multi-source data of a global area, and screening sample site actual measurement data, a sample normalized vegetation index and sample reanalysis meteorological data of a sample area according to preset screening conditions, wherein the sample site actual measurement data comprise sample downlink short wave radiation, sample earth surface albedo and sample earth surface net radiation. And then inputting the sample site actual measurement data, the sample normalized vegetation index and the sample re-analysis meteorological data of the sample area into the initial model and training to obtain the surface net radiation estimation model. The initial model here may be constructed based on a random forest algorithm. The preset screening condition is that the measured data of the sample site in the sample area comprises downlink short wave radiation and surface net radiation, the continuous observation time of the site is more than one year, and the site is located at a conventional geographic position.
According to the surface net radiation estimation system provided by the embodiment of the invention, the multi-source data including the downlink short wave radiation is determined through the multi-source data determination module based on the first remote sensing data and the re-analysis meteorological data of the region to be measured, or the second remote sensing data, the re-analysis meteorological data and the downlink short wave radiation from the site measured data, the information amount of the input data is increased, the multi-source data is input to the surface net radiation estimation model through the surface net radiation estimation module, the resolution and the precision of surface net radiation estimation are improved through exerting the respective advantages of different data sources, and the estimation of the surface net radiation with long time sequence, high precision and high resolution can be realized.
Based on any of the above embodiments, the surface net radiation estimation module 320 specifically includes:
the surface attribute judging submodule 321 is configured to judge a surface attribute of the region to be detected based on the multi-source data;
and the surface net radiation estimation submodule 322 is configured to input the multi-source data to a surface net radiation estimation model corresponding to the surface attribute of the region to be measured, and obtain a surface net radiation estimation result of the region to be measured, which is output by the surface net radiation estimation model.
Specifically, firstly, the surface attribute of the region to be measured is judged based on multi-source data. The multi-source data may include at least one of a normalized vegetation index, a ground surface albedo and a sunshine duration, and correspondingly, the ground surface attribute of the region to be measured may be determined based on one parameter in the multi-source data or based on a combination of multiple parameters in the multi-source data, which is not specifically limited in the embodiment of the present invention. The surface attribute of the area to be measured can be vegetation or non-vegetation.
After the surface attribute of the region to be measured is judged, the multi-source data are input into a surface net radiation estimation model corresponding to the surface attribute, and the surface net radiation estimation model calculates and outputs a surface net radiation estimation result of the region to be measured based on downlink short wave radiation in the multi-source data. The model corresponding to any earth surface attribute is obtained by training based on sample site measured data, a sample normalized vegetation index and sample reanalysis meteorological data of a sample area belonging to the earth surface attribute, wherein the sample site measured data comprises sample downlink short wave radiation, sample earth surface albedo and sample earth surface net radiation.
According to the surface net radiation estimation system provided by the embodiment of the invention, the surface attribute of the area to be measured is judged based on the multi-source data, and the multi-source data is input into the surface net radiation estimation model corresponding to the surface attribute of the area to be measured, so that different surface net radiation estimation models are adopted for estimation aiming at different surface attributes of the area to be measured, and the precision of surface net radiation estimation is further improved.
Based on any of the above embodiments, in the system for estimating surface net radiation, the surface property determination submodule 321 is specifically configured to:
and judging the earth surface attribute of the area to be detected based on the normalized vegetation index and the earth surface albedo in the multi-source data.
Specifically, the multi-source data includes a normalized vegetation index and a ground surface albedo, and the method for judging the ground surface attribute of the region to be detected based on the normalized vegetation index and the ground surface albedo in the multi-source data is not specifically limited in the embodiment of the invention, and includes but is not limited to: if the normalized vegetation index in the multi-source data is larger than a preset first threshold value and the earth surface albedo in the multi-source data is smaller than or equal to a preset second threshold value, determining the earth surface attribute of the area to be measured as a vegetation coverage class; otherwise, judging the surface attribute of the area to be detected as a non-vegetation coverage type.
Correspondingly, if the earth surface attribute of the area to be measured is a vegetation coverage class, inputting multi-source data including the normalized vegetation index into an earth surface net radiation estimation model corresponding to the vegetation coverage class; and if the earth surface attribute of the area to be detected is a non-vegetation coverage type, inputting the multi-source data except the normalized vegetation index into an earth surface net radiation estimation model corresponding to the non-vegetation coverage type.
The system for estimating the net surface radiation provided by the embodiment of the invention determines the surface attribute of the area to be measured based on the normalized vegetation index and the surface albedo in the multi-source data so as to estimate different surface attributes of the area to be measured by adopting different surface net radiation estimation models, thereby further improving the precision of estimating the net surface radiation.
Based on any one of the embodiments, in the system for estimating net surface radiation, the determining the surface property of the area to be measured based on the normalized vegetation index and the surface albedo in the multi-source data specifically includes:
if the normalized vegetation index in the multi-source data is larger than a preset first threshold value and the earth surface albedo in the multi-source data is smaller than or equal to a preset second threshold value, judging that the earth surface attribute of the area to be measured is a vegetation coverage class;
if the normalized vegetation index in the multi-source data is less than or equal to a preset first threshold value, or the earth surface albedo in the multi-source data is greater than a preset second threshold value, and the sunshine duration in the multi-source data is within a preset time range, judging that the earth surface attribute of the area to be measured is a normal sunshine duration non-vegetation coverage type;
otherwise, determining the earth surface attribute of the area to be detected as the non-vegetation coverage class with the abnormal sunshine duration.
According to the land surface net radiation estimation system provided by the embodiment of the invention, the land surface attributes of the area to be measured are judged to be plant cover type, normal sunshine duration non-plant cover type and non-normal sunshine duration non-plant cover type based on the normalized vegetation index, the land surface albedo and the sunshine duration in the multi-source data, so that different land surface attributes of the area to be measured can be estimated by adopting different land surface net radiation estimation models, and the accuracy of land surface net radiation estimation is further improved.
Based on any of the above embodiments, the surface net radiation estimation sub-module 322 has a processor for:
if the earth surface attribute of the area to be measured is a vegetation coverage class, inputting multi-source data including the normalized vegetation index into an earth surface net radiation estimation model corresponding to the vegetation coverage class to obtain an earth surface net radiation estimation result of the area to be measured output by the earth surface net radiation estimation model;
if the earth surface attribute of the area to be measured is normal sunshine duration non-vegetation coverage, inputting the multi-source data except the normalized vegetation index into an earth surface net radiation estimation model corresponding to the normal sunshine duration non-vegetation coverage, and obtaining an earth surface net radiation estimation result of the area to be measured output by the earth surface net radiation estimation model;
and if the earth surface attribute of the area to be measured is the non-vegetation coverage class with the abnormal sunshine duration, inputting the multi-source data except the normalized vegetation index into an earth surface net radiation estimation model corresponding to the non-vegetation coverage class with the abnormal sunshine duration to obtain an earth surface net radiation estimation result of the area to be measured output by the earth surface net radiation estimation model.
According to the surface net radiation estimation system provided by the embodiment of the invention, different surface attributes of the region to be measured are estimated by adopting different surface net radiation estimation models, so that the surface net radiation estimation precision is further improved.
Based on any of the embodiments above, the multi-source data determining module 310 is specifically configured to:
and adding data with the acquisition time within the preset time length before and after the site observation time in the first remote sensing data or the second remote sensing data of the region to be detected to the multi-source data of the region to be detected.
Specifically, the time resolution of the first remote sensing data or the second remote sensing data of the region to be measured is affected by the observation period of the corresponding remote sensing satellite, so that multi-source data continuously observed for a long time cannot be acquired. The normalized vegetation index and the earth surface albedo are parameters reflecting the characteristics of the underlying surface, obvious fluctuation can not occur in a short time generally, and corresponding data of time in the first remote sensing data or the second remote sensing data within a preset time length before and after the observation time of the station can be added to the multi-source data to obtain the multi-source data continuously observed for a long time. The preset duration may be set according to different remote sensing satellites, which is not specifically limited in the embodiment of the present invention.
According to the surface net radiation estimation system provided by the embodiment of the invention, data with the collection time within the preset duration before and after the station observation time in the first remote sensing data or the second remote sensing data of the region to be measured are added to the multi-source data of the region to be measured so as to obtain the multi-source data continuously observed for a long time, and the estimation of surface net radiation with long time sequence, high precision and high resolution can be realized.
Fig. 4 is a schematic entity structure diagram of an electronic device according to an embodiment of the present invention, and as shown in fig. 4, the electronic device may include: the system comprises a processor 401, a communication interface 402, a memory 403 and a communication bus 404, wherein the processor 401, the communication interface 402 and the memory 403 are communicated with each other through the communication bus 404. Processor 401 may call logic instructions in memory 403 to perform the following method: determining multisource data of the area to be detected based on the first remote sensing data and the re-analysis meteorological data of the area to be detected, or the second remote sensing data, the re-analysis meteorological data and downlink short wave radiation from site actual measurement data; the first remote sensing data comprise downlink short wave radiation, and the second remote sensing data do not comprise downlink short wave radiation; inputting the multi-source data into a surface net radiation estimation model to obtain a surface net radiation estimation result of the region to be detected, which is output by the surface net radiation estimation model; the surface net radiation estimation model is obtained by training sample site actual measurement data, a sample normalized vegetation index and sample reanalysis meteorological data based on the sample area, and the sample site actual measurement data comprise sample downlink short wave radiation, sample surface albedo and sample surface net radiation.
In addition, the logic instructions in the memory 403 may be implemented in the form of software functional units and stored in a computer readable storage medium when the software functional units are sold or used as independent products. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
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 by a processor to perform the method provided by the foregoing embodiments, for example, including: determining multisource data of the area to be detected based on the first remote sensing data and the re-analysis meteorological data of the area to be detected, or the second remote sensing data, the re-analysis meteorological data and downlink short wave radiation from site actual measurement data; the first remote sensing data comprise downlink short wave radiation, and the second remote sensing data do not comprise downlink short wave radiation; inputting the multi-source data into a surface net radiation estimation model to obtain a surface net radiation estimation result of the region to be detected, which is output by the surface net radiation estimation model; the surface net radiation estimation model is obtained by training sample site actual measurement data, a sample normalized vegetation index and sample reanalysis meteorological data based on the sample area, and the sample site actual measurement data comprise sample downlink short wave radiation, sample surface albedo and sample surface net radiation.
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 method of estimating net surface radiance, comprising:
determining multi-source data of the area to be detected based on first remote sensing data and re-analysis meteorological data of the area to be detected, or second remote sensing data, the re-analysis meteorological data and downlink short wave radiation from site actual measurement data; the first remote sensing data comprise downlink short wave radiation, and the second remote sensing data do not comprise downlink short wave radiation;
inputting the multi-source data into a surface net radiation estimation model to obtain a surface net radiation estimation result of the region to be detected, which is output by the surface net radiation estimation model;
the surface net radiation estimation model is obtained by training based on sample site measured data, a sample normalized vegetation index and sample re-analysis meteorological data of a sample area, wherein the sample site measured data comprises sample downlink short wave radiation, sample surface albedo and sample surface net radiation.
2. The method according to claim 1, wherein the inputting the multi-source data into a surface net radiation estimation model to obtain a surface net radiation estimation result of the region to be measured output by the surface net radiation estimation model specifically comprises:
judging the surface attribute of the area to be detected based on the multi-source data;
and inputting the multi-source data into a surface net radiation estimation model corresponding to the surface attribute of the region to be detected, and obtaining a surface net radiation estimation result of the region to be detected output by the surface net radiation estimation model.
3. The method according to claim 2, wherein the determining the surface property of the region to be measured based on the multi-source data specifically comprises:
and determining the earth surface attribute of the area to be measured based on the normalized vegetation index and the earth surface albedo in the multi-source data.
4. The method according to claim 3, wherein the determining the surface property of the area to be measured based on the normalized vegetation index and the surface albedo in the multi-source data specifically comprises:
if the normalized vegetation index in the multi-source data is larger than a preset first threshold value and the earth surface albedo in the multi-source data is smaller than or equal to a preset second threshold value, determining the earth surface attribute of the area to be measured as a vegetation coverage class;
if the normalized vegetation index in the multi-source data is less than or equal to the preset first threshold value, or the earth surface albedo in the multi-source data is greater than the preset second threshold value, and the sunshine duration in the multi-source data is within a preset time range, determining that the earth surface attribute of the area to be measured is a normal sunshine duration non-vegetation coverage type;
otherwise, determining the earth surface attribute of the area to be detected as the non-vegetation coverage class with the abnormal sunshine duration.
5. The method according to claim 4, wherein the inputting the multi-source data into the surface net radiation estimation model corresponding to the surface property of the region to be measured to obtain the surface net radiation estimation result of the region to be measured output by the surface net radiation estimation model specifically comprises:
if the earth surface attribute of the area to be measured is a vegetation coverage type, inputting multi-source data including the normalized vegetation index into an earth surface net radiation estimation model corresponding to the vegetation coverage type to obtain an earth surface net radiation estimation result of the area to be measured output by the earth surface net radiation estimation model;
if the earth surface attribute of the area to be measured is normal sunshine duration non-vegetation coverage, inputting multi-source data except the normalized vegetation index into an earth surface net radiation estimation model corresponding to the normal sunshine duration non-vegetation coverage, and obtaining an earth surface net radiation estimation result of the area to be measured output by the earth surface net radiation estimation model;
and if the earth surface attribute of the area to be measured is an abnormal sunshine duration non-vegetation coverage type, inputting multi-source data except the normalized vegetation index into an earth surface net radiation estimation model corresponding to the abnormal sunshine duration non-vegetation coverage type to obtain an earth surface net radiation estimation result of the area to be measured output by the earth surface net radiation estimation model.
6. The method for estimating surface net radiation according to any one of claims 1 to 5, wherein the determining the multi-source data of the area to be measured based on the first remote sensing data and the re-analysis meteorological data of the area to be measured, or the second remote sensing data, the re-analysis meteorological data and the downlink short wave radiation from the site measured data specifically comprises:
and adding data with the acquisition time within the preset time length before and after the site observation time in the first remote sensing data or the second remote sensing data of the area to be detected to the multi-source data of the area to be detected.
7. The method of surface net radiance estimation of any of claims 1 to 5, where the multi-source data further includes surface albedo, normalized vegetation index, meteorological parameters, and geographical parameters.
8. A surface net radiation estimation system, comprising:
the multi-source data determining module is used for determining the multi-source data of the area to be detected based on the first remote sensing data and the re-analysis meteorological data of the area to be detected, or the second remote sensing data, the re-analysis meteorological data and the downlink short wave radiation from the station actual measurement data; the first remote sensing data comprise downlink short wave radiation, and the second remote sensing data do not comprise downlink short wave radiation;
the surface net radiation estimation module is used for inputting the multi-source data to a surface net radiation estimation model to obtain a surface net radiation estimation result of the area to be detected, which is output by the surface net radiation estimation model;
the surface net radiation estimation model is obtained by training based on sample site measured data, a sample normalized vegetation index and sample re-analysis meteorological data of a sample area, wherein the sample site measured data comprises sample downlink short wave radiation, sample surface albedo and sample surface net radiation.
9. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor when executing the program performs the steps of the surface net radiation estimation method of any of claims 1 to 7.
10. A non-transitory computer readable storage medium having stored thereon a computer program, wherein the computer program when executed by a processor implements the steps of the surface net radiation estimation method of any of claims 1 to 7.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010340715.7A CN111597692B (en) | 2020-04-26 | 2020-04-26 | Method, system, electronic equipment and storage medium for estimating surface net radiation |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010340715.7A CN111597692B (en) | 2020-04-26 | 2020-04-26 | Method, system, electronic equipment and storage medium for estimating surface net radiation |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN111597692A true CN111597692A (en) | 2020-08-28 |
| CN111597692B CN111597692B (en) | 2024-02-27 |
Family
ID=72185115
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010340715.7A Active CN111597692B (en) | 2020-04-26 | 2020-04-26 | Method, system, electronic equipment and storage medium for estimating surface net radiation |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN111597692B (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112861355A (en) * | 2021-02-09 | 2021-05-28 | 北京师范大学 | Sea surface net radiation estimation method and system |
| CN117131313A (en) * | 2023-10-23 | 2023-11-28 | 沈阳仪表科学研究院有限公司 | Method for calculating soil moisture content parameters of traditional Chinese medicinal materials, computer equipment and medium |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2006162447A (en) * | 2004-12-07 | 2006-06-22 | Japan Weather Association | Calculator, method and program for calculating ground surface heat balance, and road surface freezing possibility index calculator |
| CN106169014A (en) * | 2016-06-15 | 2016-11-30 | 中国水利水电科学研究院 | Region based on remotely-sensed data Surface sensible heat/latent heat flux inversion method and system |
| US20160363696A1 (en) * | 2015-06-10 | 2016-12-15 | Tung X. Dao | Observer-based meteorology and image identification |
-
2020
- 2020-04-26 CN CN202010340715.7A patent/CN111597692B/en active Active
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2006162447A (en) * | 2004-12-07 | 2006-06-22 | Japan Weather Association | Calculator, method and program for calculating ground surface heat balance, and road surface freezing possibility index calculator |
| US20160363696A1 (en) * | 2015-06-10 | 2016-12-15 | Tung X. Dao | Observer-based meteorology and image identification |
| CN106169014A (en) * | 2016-06-15 | 2016-11-30 | 中国水利水电科学研究院 | Region based on remotely-sensed data Surface sensible heat/latent heat flux inversion method and system |
Non-Patent Citations (2)
| Title |
|---|
| STEVEN D. MILLER 等: "Short-term solar irradiance forecasting via satellite/model coupling" * |
| 温松楠 等: "基于随机森林和MODIS 产品的逐日太阳辐射估算" * |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112861355A (en) * | 2021-02-09 | 2021-05-28 | 北京师范大学 | Sea surface net radiation estimation method and system |
| CN112861355B (en) * | 2021-02-09 | 2022-02-11 | 北京师范大学 | Sea surface net radiation estimation method and system |
| CN117131313A (en) * | 2023-10-23 | 2023-11-28 | 沈阳仪表科学研究院有限公司 | Method for calculating soil moisture content parameters of traditional Chinese medicinal materials, computer equipment and medium |
Also Published As
| Publication number | Publication date |
|---|---|
| CN111597692B (en) | 2024-02-27 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Perez et al. | GOW2: A global wave hindcast for coastal applications | |
| Li et al. | Assessing the performance of satellite-based precipitation products and its dependence on topography over Poyang Lake basin | |
| Chen et al. | A statistical method based on remote sensing for the estimation of air temperature in China. | |
| Kundu et al. | The value of remotely sensed surface soil moisture for model calibration using SWAT | |
| CN111666656A (en) | Rainfall estimation method and rainfall monitoring system based on microwave rainfall attenuation | |
| CN104142142A (en) | Method for estimating global vegetation coverage | |
| CN113673765B (en) | Small drainage basin flood forecasting and early warning method and terminal | |
| CN113222283A (en) | Mountain torrent forecasting and early warning method and system based on digital twin | |
| CN112585505A (en) | Determining location-specific weather information for agronomic decision support | |
| CN111597692A (en) | Surface net radiation estimation method, system, electronic equipment and storage medium | |
| Zhang et al. | Spatial and temporal downscaling of TRMM precipitation with novel algorithms | |
| Fan et al. | A comparative study of four merging approaches for regional precipitation estimation | |
| CN113534083B (en) | SAR-based corn stubble mode identification method, device and medium | |
| Medeiros et al. | A Random Forest model based on lidar and field measurements for parameterizing surface roughness in coastal modeling | |
| CN116823579B (en) | Method and system for predicting water quantity change of mountain glacier lake | |
| Haddjeri et al. | Exploring the sensitivity to precipitation, blowing snow, and horizontal resolution of the spatial distribution of simulated snow cover | |
| CN111488553B (en) | Solar irradiance calculating method and device | |
| Xu et al. | A validation of passive microwave rain-rate retrievals from the Chinese FengYun-3B satellite | |
| CN116029162B (en) | Flood disaster inundation range monitoring method and system by using satellite-borne GNSS-R data | |
| CN113297904A (en) | Alpine grassland biomass estimation method and system based on satellite driving model | |
| CN114926040B (en) | Comprehensive evaluation method and system for natural capital of drainage basin and electronic equipment | |
| CN115855272A (en) | Method for generating near-real-time hourly all-weather surface temperature | |
| CN114611699A (en) | Soil moisture downscaling method and device, electronic equipment and storage medium | |
| CN114898138A (en) | Method for predicting forest fire based on landform and remote sensing data | |
| CN115688955A (en) | Vegetation growth prediction method, vegetation growth prediction device and storage medium |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |