CN106504210A - A kind of MODIS image datas lack restorative procedure - Google Patents
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- 238000000034 method Methods 0.000 title claims abstract description 52
- 241001269238 Data Species 0.000 title claims abstract description 16
- 238000012544 monitoring process Methods 0.000 claims abstract description 55
- 230000013011 mating Effects 0.000 claims abstract description 4
- 230000008034 disappearance Effects 0.000 claims description 9
- 239000000443 aerosol Substances 0.000 claims description 8
- 230000008878 coupling Effects 0.000 claims description 7
- 238000010168 coupling process Methods 0.000 claims description 7
- 238000005859 coupling reaction Methods 0.000 claims description 7
- 238000006243 chemical reaction Methods 0.000 claims description 5
- 230000009471 action Effects 0.000 claims description 2
- 230000008033 biological extinction Effects 0.000 claims description 2
- 238000013500 data storage Methods 0.000 claims description 2
- 230000007613 environmental effect Effects 0.000 claims description 2
- 238000012217 deletion Methods 0.000 abstract description 11
- 230000037430 deletion Effects 0.000 abstract description 11
- 230000000694 effects Effects 0.000 abstract description 8
- 238000005516 engineering process Methods 0.000 description 9
- 238000012986 modification Methods 0.000 description 5
- 230000004048 modification Effects 0.000 description 5
- 230000003287 optical effect Effects 0.000 description 5
- 230000008901 benefit Effects 0.000 description 3
- 238000003915 air pollution Methods 0.000 description 2
- 230000008859 change Effects 0.000 description 2
- 239000003344 environmental pollutant Substances 0.000 description 2
- 231100000719 pollutant Toxicity 0.000 description 2
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- 239000008186 active pharmaceutical agent Substances 0.000 description 1
- 238000002474 experimental method Methods 0.000 description 1
- 238000003780 insertion Methods 0.000 description 1
- 230000037431 insertion Effects 0.000 description 1
- 230000008569 process Effects 0.000 description 1
- 239000000047 product Substances 0.000 description 1
- 230000006641 stabilisation Effects 0.000 description 1
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T5/00—Image enhancement or restoration
- G06T5/77—Retouching; Inpainting; Scratch removal
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
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Abstract
The invention discloses a kind of MODIS image datas lack restorative procedure, methods described includes：S1：The shooting time t of MODIS images is obtained, according to the real-time AQI values that time t obtains the time point air ground monitoring station；S2：Latitude and longitude coordinates information using ground monitoring station website is added to ground monitoring data in remote sensing image mating remote sensing image picture element；S3：To having added the remote sensing image after ground monitoring data, the method of utilization space interpolation to remote sensing image in enter row interpolation reparation without value region, achieve when MODIS image deletions, image data can be repaired, can accurately carry out the technique effect of Air Quality Forecast.
Description
Technical field
A kind of the present invention relates to Remote Sensing Image Processing Technology field, in particular it relates to MODIS image datas disappearance reparation side
Method.
Background technology
IDEA-I is that international MODIS/AIRS satellite datas process bag project (International MODIS/AIRS
Processing Package, IMAPP) sub-project for undertaking Air Quality Forecast in project.The polluter of IDEA-I models
(Aerosol Optical Depth, AOD) data that data are obtained essentially from satellite remote sensing.
But the aerosol optical depth image data of MODIS is often lacked, affected by weather larger, in sleet, cloudy
Under etc. weather condition, where being covered by sleet, cloud etc., it is more likely that be without value region, substantial amounts of cause to enter without value area
Row Air Quality Forecast.
In sum, present inventor has found above-mentioned technology extremely during the present application technical scheme is realized
There is following technical problem less：
There is MODIS images and there is disappearance in Air Quality Forecast method of the prior art, occur, without value region, causing nothing
Method is normally carried out the technical problem of Air Quality Forecast.
Content of the invention
The invention provides a kind of MODIS image datas lack restorative procedure, air quality of the prior art is solved
There is MODIS images and there is disappearance in Forecasting Methodology, occur, without value region, leading to not the technology for being normally carried out Air Quality Forecast
Problem, it is achieved that when MODIS image deletions, image data can be repaired, can accurately carry out Air Quality Forecast
Technique effect.
In recent years, ground air monitoring station website is more and more, and the area of covering is also increasingly wider, its data stabilization,
Reliable, continuous, a secondary data can be obtained per hour, and the data type for including is abundant (including PM2.5, PM10, AQI etc.),
Can be very good the supplement as remote sensing image data.Therefore, using ground air monitoring station data write MODIS images come mould
Plan is a kind of method of MODIS image datas disappearance in feasible solution IDEA-I locus models.
This application provides a kind of MODIS image datas lack restorative procedure, methods described includes：
S1：The shooting time t of MODIS images is obtained, the real-time of the time point air ground monitoring station is obtained according to time t
AQI values；
S2：Latitude and longitude coordinates information using ground monitoring station website mating remote sensing image picture element, by ground monitoring number
According to being added in remote sensing image；
S3：To having added the remote sensing image after ground monitoring data, during the method for utilization space interpolation is to remote sensing image
Enter row interpolation reparation without value region.
Without value accuracy of the regional effect IDWA-I locus models to Air Quality Forecast, and according to remote sensing image number itself
According to and the ground monitoring station data that adds do space interpolation, can finally obtain that a width is smooth and there is the distant of value in all regions
Sense image.
Wherein, air quality index (Air Quality Index, abbreviation AQI).
Further, step S2 is specifically included：
Based on the coordinate information of each pixel in remote sensing image, judge ground monitoring station website latitude and longitude coordinates (lon,
Lat) whether the value of corresponding pixel lacks；If the corresponding pixel of the latitude and longitude coordinates (lon, lat) has value, then execute S201；If should
The value disappearance of the corresponding pixel of latitude and longitude coordinates (lon, lat), then execute S202；
Wherein, S201：Do not deal with, continue the next monitoring station of coupling, until having mated all of ground monitoring station
Point；
S202：AQI values are converted to AOD values and write remote sensing image.
Air quality index is changed with aerosol optical depth (AQI and AOD), through existing numerous studies and experiment,
There is dependency between AQI and AOD, research on utilization achievement, by conversion formula, the AQI that will can be obtained from ground monitoring station
Value is converted into AOD values.After by conversion AOD values write remote sensing image in, then proceed to mate next monitoring station, until
All of ground monitoring website is matched somebody with somebody.
Further, enter row interpolation reparation without value region during the method for the utilization space interpolation is to remote sensing image, have
Body includes：Use anti-distance weighting interpolation method (IDW), its basic thought is two object similaritys with the distance between them
Increase and reduce.Distance between interpolation point and sample point for weight be weighted averagely, from interpolation point more close to sample give
Weight is bigger.By anti-distance weighting interpolation method (IDW) with the ground monitoring station data of remote sensing image data itself and interpolation
To enter row interpolation to remaining without value region, the complete remote sensing image of a width can have finally been obtained.
Further, described AQI values are converted to AOD values and write remote sensing image, specifically include：AQI data are high, represent
Atmospheric turbidity is higher, directly influences the value of AOD.AQI data and AOD data from physical significance for general keep positive
The relation of closing property.Method more common at present is, in the same area, under conditions of weather conditions are approximate, individually set up and returns
One changes equation：
AQI=η × AOD (1)
η is to affect moonscope environment AOD factor action functions, relevant with humiture and aerosol vertical extinction degree.
Further, the real-time AQI values for obtaining the time point air ground monitoring station according to time t, specially：In
Data center of magnificent Chinese Ministry of Environmental Protection of people's republic (http://datacenter.mep.gov.cn/) can in real time update the whole nation each
The pollutant monitoring data of monitoring station, and primary pollutant is announced, provide air pollution index.By the data reptile of webpage
Technology by these data storages to data base, by the anti-function of looking into of Baidu map API geographical coordinate, you can obtain band longitude and latitude
The AQI data of coordinate.
In IDEA-I locus models in the application, the method for MODIS image deletion reparations is specially：Insertion air ground
Monitoring station data, add the method for space interpolation to simulate MODIS images, so that when MODIS image deletions
Air Quality Forecast can be done.
One or more technical schemes that the application is provided, at least have the following technical effect that or advantage：
The method that MODIS image deletions are repaired in the IDEA-I locus models of the present invention, according to during the shooting of remote sensing image
Between t, using latitude and longitude coordinates (lon, lat) the information matches remote sensing image corresponding coordinate point of ground monitoring website, judge remote sensing
In image, whether same coordinate points have value, then do not deal with if there are value, continue the next ground monitoring website of coupling；If nothing
Value, then air quality index (AQI) data for monitoring ground monitoring website are converted to aerosol optical according to conversion formula
Then AOD values are write remote sensing images, then mate next ground monitoring website, until all of website by thickness value (AOD)
With completing, after the completion of all ground monitoring station data couplings, then carried out without value region to remaining with the method for space interpolation
Interpolation, finally obtaining all regions of a width has the remote sensing image of value, so, efficiently solve air quality of the prior art
There is MODIS images and there is disappearance in Forecasting Methodology, occur, without value region, leading to not the technology for being normally carried out Air Quality Forecast
Problem, and then achieve when MODIS image deletions, image data can be repaired, can accurately carry out air quality
The technique effect of prediction.
Description of the drawings
Accompanying drawing described herein is used for providing further understanding the embodiment of the present invention, constitutes of the application
Point, do not constitute the restriction to the embodiment of the present invention；
Fig. 1 is the schematic flow sheet that ODIS image datas lack restorative procedure in the application.
Specific embodiment
The invention provides a kind of MODIS image datas lack restorative procedure, air quality of the prior art is solved
There is MODIS images and there is disappearance in Forecasting Methodology, occur, without value region, leading to not the technology for being normally carried out Air Quality Forecast
Problem, it is achieved that when MODIS image deletions, image data can be repaired, can accurately carry out Air Quality Forecast
Technique effect.
In order to be more clearly understood that the above objects, features and advantages of the present invention, below in conjunction with the accompanying drawings and concrete real
Apply mode to be further described in detail the present invention.It should be noted that in the case where mutually not conflicting, the application's
Feature in embodiment and embodiment can be mutually combined.
A lot of details are elaborated in the following description in order to fully understand the present invention, but, the present invention may be used also
With the other modes in the range of being different from being described herein using other implementing, therefore, protection scope of the present invention is not received down
The restriction of specific embodiment disclosed in face.
Fig. 1 is refer to, the technical scheme in the application is specially：
A kind of MODIS image datas lack restorative procedure, it is characterised in that methods described includes：
S1：The shooting time t of MODIS images is obtained, the real-time of the time point air ground monitoring station is obtained according to time t
AQI values；
S2：Latitude and longitude coordinates information using ground monitoring station website mating remote sensing image picture element, by ground monitoring number
According to being added in remote sensing image；
S3：To having added the remote sensing image after ground monitoring data, during the method for utilization space interpolation is to remote sensing image
Enter row interpolation reparation without value region.
Fig. 1 is the flow chart of MODIS image deletions restorative procedure in IDEA-I locus models in the present invention.As shown in figure 1,
In IDEA-I locus models of the present invention, MODIS image deletion restorative procedures are comprised the following steps：
S101：The shooting time t that remote sensing image is recognized by filename or header file, used in the present embodiment be
3 points of MODIS04 product MOD04_ of 05 minute of the 280th day 2014 UTC time
L2.A2014280.0305.006.2015077193207.hdf, has most of region not have aerosol data (AOD values), then
According to air pollution index (AQI) data that time t obtains the time point whole nation ground monitoring station real-time monitoring.
S102：Research on utilization result, sets up the relational expression of AOD and AQI, then monitors ground monitoring station
AQI values are converted to AOD values, then mate remote sensing with latitude and longitude coordinates (lon, the lat) information of national ground monitoring station website
The coordinate information of image picture element, judges that whether the AOD values of the corresponding pixel of the latitude and longitude coordinates (lon, lat) are 9999 (default
Value).If the AOD values of the corresponding pixel of the latitude and longitude coordinates (lon, lat) are default, then will be by corresponding ground monitoring station AQI data
In the AOD data write remote sensing image being converted to；If the corresponding pixel of the latitude and longitude coordinates (lon, lat) has AOD values, then not
Deal with, continue the next monitoring station of coupling, until having mated all of ground monitoring website.
S103:To having added the remote sensing image after ground monitoring data, with the method for space interpolation to remaining without value area
Enter row interpolation in domain.Use in this example anti-distance weighting interpolation method (IDW), its basic thought is two object similaritys
Reduce with the distance increase between them.Distance between interpolation point and sample point is weighted averagely for weight, is got over from interpolation point
The weight that near sample gives is bigger.By anti-distance weighting interpolation method (IDW) with remote sensing image data itself and the ground of interpolation
Monitoring station data in face can finally obtain the complete remote sensing image of a width entering row interpolation to remaining without value region.
Technical scheme in above-mentioned the embodiment of the present application, at least has the following technical effect that or advantage：
The method that MODIS image deletions are repaired in the IDEA-I locus models of the present invention, according to during the shooting of remote sensing image
Between t, using latitude and longitude coordinates (lon, lat) the information matches remote sensing image corresponding coordinate point of ground monitoring website, judge remote sensing
In image, whether same coordinate points have value, then do not deal with if there are value, continue the next ground monitoring website of coupling；If nothing
Value, then air quality index (AQI) data for monitoring ground monitoring website are converted to aerosol optical according to conversion formula
Then AOD values are write remote sensing images, then mate next ground monitoring website, until all of website by thickness value (AOD)
With completing, after the completion of all ground monitoring station data couplings, then carried out without value region to remaining with the method for space interpolation
Interpolation, finally obtaining all regions of a width has the remote sensing image of value, so, efficiently solve air quality of the prior art
There is MODIS images and there is disappearance in Forecasting Methodology, occur, without value region, leading to not the technology for being normally carried out Air Quality Forecast
Problem, and then achieve when MODIS image deletions, image data can be repaired, can accurately carry out air quality
The technique effect of prediction.
, but those skilled in the art once know basic creation although preferred embodiments of the present invention have been described
Property concept, then can make other change and modification to these embodiments.So, claims are intended to be construed to include excellent
Select embodiment and fall into the had altered of the scope of the invention and change.
Obviously, those skilled in the art can carry out the essence of various changes and modification without deviating from the present invention to the present invention
God and scope.So, if these modifications of the present invention and modification belong to the scope of the claims in the present invention and its equivalent technologies
Within, then the present invention is also intended to comprising these changes and modification.
Claims (5)
1. a kind of MODIS image datas lack restorative procedure, it is characterised in that methods described includes：
S1：The shooting time t of MODIS images is obtained, according to the real-time AQI that time t obtains the time point air ground monitoring station
Value；
S2：Ground monitoring data are added mating remote sensing image picture element by the latitude and longitude coordinates information using ground monitoring station website
It is added in remote sensing image；
S3：To having added the remote sensing image after ground monitoring data, the method for utilization space interpolation to remote sensing image in without value
Enter row interpolation reparation in region.
2. MODIS image datas according to claim 1 lack restorative procedure, it is characterised in that step S2 is concrete
Including：
Based on the coordinate information of each pixel in remote sensing image, the latitude and longitude coordinates (lon, lat) of ground monitoring station website are judged
Whether the value of corresponding pixel lacks；If the corresponding pixel of the latitude and longitude coordinates (lon, lat) has value, then execute S201；If the longitude and latitude
The value disappearance of the corresponding pixel of degree coordinate (lon, lat), then execute S202；
Wherein, S201：Do not deal with, continue the next monitoring station of coupling, until having mated all of ground monitoring website；
S202：AQI values are converted to AOD values and write remote sensing image.
3. MODIS image datas according to claim 1 lack restorative procedure, it is characterised in that the utilization space is inserted
The method of value to remote sensing image in enter row interpolation reparation without value region, row interpolation is entered using anti-distance weighting interpolation method specially
Repair.
4. MODIS image datas according to claim 2 lack restorative procedure, it is characterised in that described by the conversion of AQI values
For AOD values and remote sensing image is write, AQI values are converted to by AOD values using formula 1 specially, formula 1 is：
AQI=η × AOD (1)
Wherein, η is for affecting moonscope environment AOD factor action functions, relevant with humiture and aerosol vertical extinction degree.
5. MODIS image datas according to claim 1 lack restorative procedure, it is characterised in that described obtained according to time t
The real-time AQI values of the time point air ground monitoring station are taken, specially：Will be real-time for data center of Chinese Ministry of Environmental Protection of the People's Republic of China (PRC)
Data storage obtains the AQI data with latitude and longitude coordinates to data base by the anti-function of looking into of map API geographical coordinates.
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN107507152A (en) * | 2017-09-13 | 2017-12-22 | 鲁东大学 | A kind of remote sensing images missing data restorative procedure based on more image local interpolation |
| CN110334651A (en) * | 2019-07-05 | 2019-10-15 | 云南电网有限责任公司电力科学研究院 | A kind of power transformation station coordinates method of calibration based on transfer learning |
| CN113935956A (en) * | 2021-09-23 | 2022-01-14 | 中国矿业大学(北京) | Two-way mixed modeling mining area soil water content data missing repairing method |
| CN116008481A (en) * | 2023-01-05 | 2023-04-25 | 山东理工大学 | Air pollutant monitoring method and device based on large-range ground monitoring station |
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Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107507152A (en) * | 2017-09-13 | 2017-12-22 | 鲁东大学 | A kind of remote sensing images missing data restorative procedure based on more image local interpolation |
| CN110334651A (en) * | 2019-07-05 | 2019-10-15 | 云南电网有限责任公司电力科学研究院 | A kind of power transformation station coordinates method of calibration based on transfer learning |
| CN110334651B (en) * | 2019-07-05 | 2023-06-23 | 云南电网有限责任公司电力科学研究院 | Substation coordinate verification method based on transfer learning |
| CN113935956A (en) * | 2021-09-23 | 2022-01-14 | 中国矿业大学(北京) | Two-way mixed modeling mining area soil water content data missing repairing method |
| CN113935956B (en) * | 2021-09-23 | 2022-03-25 | 中国矿业大学(北京) | Two-way mixed modeling mining area soil water content data missing repairing method |
| CN116008481A (en) * | 2023-01-05 | 2023-04-25 | 山东理工大学 | Air pollutant monitoring method and device based on large-range ground monitoring station |
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