CN113138431A - Smart city meteorological observation method and system - Google Patents
Smart city meteorological observation method and system Download PDFInfo
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Abstract
The invention relates to a smart city meteorological observation method, which comprises a plurality of detection stations distributed in scattered points, and the implementation method comprises the following steps: acquiring meteorological data of all detection stations in the selected target area at the current moment; calculating the current comfort level of each corresponding detection station by adopting a comfort level algorithm according to the acquired meteorological data; interpolating scattered point data in a target area into raster data by adopting a Kriging space interpolation method, and interpolating the generated raster data by adopting a bilinear difference algorithm; coloring each point after interpolation according to a set color corresponding to the comfort degree value to generate a color spot graph reflecting the comfort degree grade distribution in the target area; by the method, accuracy of data in the area between scattered points can be greatly improved, and meanwhile, the data are converted into the speckle patterns rendered according to comfort levels and are easier to observe.
Description
Technical Field
The invention relates to the technical field of smart city meteorological observation, in particular to a smart city meteorological observation method and a smart city meteorological observation system.
Background
The smart city meteorological observation is related to all members in city life, and is an important ring in smart city construction; the intelligent city meteorological observation mode that adopts at present, mostly all unreasonable, accuracy and the bandwagon effect of meteorological observation data all await promoting urgently.
Disclosure of Invention
The technical problem to be solved by the present invention is to provide a smart city weather observation method and a smart city weather observation system, aiming at the above-mentioned defects of the prior art.
The technical scheme adopted by the invention for solving the technical problems is as follows:
a smart city meteorological observation method is constructed, and comprises a plurality of detection stations distributed in scattered points, and the implementation method comprises the following steps:
the first step is as follows: acquiring meteorological data of all the detection stations in the selected target area at the current moment;
the second step is that: calculating the current comfort level of each corresponding detection station by adopting a comfort level algorithm according to the acquired meteorological data;
the third step: interpolating scattered point data in a target area into raster data by adopting a Kriging space interpolation method, and interpolating the generated raster data by adopting a bilinear difference algorithm;
the fourth step: and coloring each point after interpolation according to a set color corresponding to the comfort degree value to generate a color spot diagram reflecting the comfort degree grade distribution in the target area.
In the third step, a kriging spatial interpolation method and an inverse distance weighting algorithm are adopted to calculate interpolation result data of each position in a target area at a set interval distance, and grid data are formed.
In the fourth step, a front-end canvas technology is adopted, and the color representing the comfort level of the position is selected for coloring according to the data size of each point after interpolation, so that a color spot diagram reflecting the comfort level distribution in the target area is generated.
The invention relates to a smart city meteorological observation method, which further comprises the fifth step of: and fitting the generated color spot map with the comfort level distribution in the target area to the corresponding position on the map.
In the fifth step, a canvas layer technology of the high-grade map is adopted to realize the intelligent city meteorological observation method based on the developer function of the high-grade map.
The invention relates to a smart city meteorological observation method, wherein meteorological data comprise one or more of site ID, site position, wind speed, wind direction, temperature and humidity.
The invention discloses a smart city meteorological observation method, wherein in the second step, a comfort degree algorithm calculation formula is as follows:
ssd＝(1.818t+18.18)*(0.88+0.002f)+(t-32)/(45-t)-3.2v+18.2；
wherein ssd is the comfort level of the detection station, t is the average air temperature of all the temperatures of the detection station, f is the relative humidity of the detection station, and v is the wind speed of the detection station.
A smart city meteorological observation system is used for realizing the smart city meteorological observation method, and comprises a server and a plurality of detection stations distributed in scattered points; the server comprises a meteorological data collecting module, a computing processing module and an image rendering module;
the meteorological data collecting module is used for collecting meteorological data of all the detection sites in the selected target area at the current moment;
the calculation processing module is used for calculating the current comfort level of each corresponding detection station by adopting a comfort level algorithm according to the acquired meteorological data, interpolating scattered data in a target area into raster data by adopting a Kriging space interpolation method, and interpolating the generated raster data by adopting a bilinear difference algorithm;
and the image rendering module is used for coloring each point after interpolation of the calculation processing module according to the set color corresponding to the comfort value to generate a color spot diagram reflecting the comfort level distribution in the target area.
The intelligent urban meteorological observation system comprises a server and a network map module, wherein the network map module is used for attaching a color spot map with comfort level distribution in a target area generated by the image rendering module to a corresponding position on a map.
The smart city meteorological observation system comprises a server side and a display module, wherein the display module is used for displaying the collected detection site data and the generated chart.
The invention has the beneficial effects that: by the method, scattered point data in the target area are interpolated into raster data through a kriging space interpolation method for scattered point meteorological data, the generated raster data are interpolated by a bilinear difference algorithm, each point after interpolation is colored according to a set color corresponding to a comfort value, a color spot graph reflecting the comfort level distribution in the target area is generated, the accuracy of data in the area between the scattered points can be greatly improved, and meanwhile, the scattered point data are converted into the color spot graph rendered according to the comfort level and are easier to observe.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the present invention will be further described with reference to the accompanying drawings and embodiments, wherein the drawings in the following description are only part of the embodiments of the present invention, and for those skilled in the art, other drawings can be obtained without inventive efforts according to the accompanying drawings:
FIG. 1 is a flow chart of a smart city weather observation method according to a preferred embodiment of the present invention;
FIG. 2 is a schematic diagram of the comfort level of the bamboo forest of Shenzhen in the smart city meteorological observation method in accordance with the preferred embodiment of the present invention;
FIG. 3 is a schematic block diagram of a smart city weather observation system according to a preferred 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 following will clearly and completely describe the technical solutions in the embodiments of the present invention, and it is obvious that the described embodiments are some embodiments of the present invention, but not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments of the present invention without inventive step, are within the scope of the present invention.
The smart city weather observation method according to the preferred embodiment of the present invention is shown in fig. 1 and also shown in fig. 2, and includes a plurality of detection sites distributed in scattered points, and the implementation method thereof is as follows:
s01: acquiring meteorological data of all detection stations in the selected target area at the current moment;
s02: calculating the current comfort level of each corresponding detection station by adopting a comfort level algorithm according to the acquired meteorological data;
s03: interpolating scattered point data in a target area into raster data by adopting a Kriging space interpolation method, and interpolating the generated raster data by adopting a bilinear difference algorithm;
s04: coloring each point after interpolation according to a set color corresponding to the comfort degree value to generate a color spot graph reflecting the comfort degree grade distribution in the target area;
by applying the method, scattered point data in the target area are interpolated into raster data by a kriging space interpolation method for scattered point meteorological data, the generated raster data are interpolated by a bilinear difference algorithm, each point after interpolation is colored according to a set color corresponding to a comfort degree value, and a color spot diagram reflecting the comfort degree grade distribution in the target area is generated, so that the accuracy of the data in the area between the scattered points can be greatly improved, and meanwhile, the data are converted into the color spot diagram rendered according to the comfort degree and are easier to observe;
preferably, in the third step, interpolation result data of each position in the target area at a set interval distance is calculated by using a kriging spatial interpolation method and an inverse distance weighting algorithm, so as to form raster data.
Explanation of the kriging interpolation processing algorithm:
kriging interpolation assumes that the distance and direction between sample points can reflect the spatial correlation that can be used to account for surface variations.
Kriging interpolation may fit a mathematical function to a specified number of points or all points within a specified radius to determine an output value for each location. The kriging process is a multi-step process; it includes exploratory statistical analysis of data, modeling of variogram, and creation of surface, and also includes study variance surface.
The kriging method is similar to the inverse distance weighting method in that it weights surrounding measurements to derive a prediction of the unmeasured positions. The common formulas for both interpolators consist of a weighted sum of data:
wherein:
z (si) is a measurement at the ith position;
λ i — the unknown weight of the measurement at the ith position;
s0 — predicted position;
n is the number of measured values;
in the inverse distance weight method, the weight λ i depends only on the distance of the predicted position. However, when the kriging method is used, the weight depends not only on the distance between the measurement points and the predicted position but also on the overall spatial arrangement based on the measurement points. To use spatial arrangement in the weights, the spatial autocorrelation must be quantized. Therefore, in the ordinary kriging method, the weight λ i depends on a fitting model of the spatial relationship between the measurement points, the distance of the predicted position, and the measurement values around the predicted position.
Preferably, in the fourth step, a front-end canvas technology is adopted, and a color representing the comfort level of the position is selected for coloring according to the data size of each point after interpolation, so that a color spot diagram reflecting the comfort level distribution in the target area is generated.
Preferably, the method further comprises the step of S05: and fitting the generated color spot map with the comfort level distribution in the target area to the corresponding position on the map.
By combining the comfort rendering map with the map, the comfort distribution condition of each area can be observed more clearly;
preferably, in the fifth step, based on the developer function of the high-grade map, the method is realized by adopting a canvas layer technology of the high-grade map;
it is understood that other mapping software may be used, and that simple transformation according to the situation is also within the scope of the present application.
Preferably, the meteorological data includes one or more of site ID, site location, wind speed, wind direction, temperature, humidity.
Preferably, in the second step, the comfort algorithm is calculated by the following formula:
ssd＝(1.818t+18.18)*(0.88+0.002f)+(t-32)/(45-t)-3.2v+18.2；
wherein ssd is the comfort level of the detection station, t is the average air temperature of all the temperatures of the detection station, f is the relative humidity of the detection station, and v is the wind speed of the detection station.
A smart city meteorological observation system is used for realizing the smart city meteorological observation method, as shown in figure 3, and comprises a server 1 and a plurality of detection stations 2 distributed in scattered points; the server 1 comprises a meteorological data collecting module 10, a calculation processing module 11 and an image rendering module 12;
a meteorological data collecting module 10, configured to collect meteorological data of all detection sites in a selected target area at the current time;
the calculation processing module 11 is configured to calculate the current comfort level of each corresponding detection station by using a comfort level algorithm according to the acquired meteorological data, interpolate scattered point data in a target area into raster data by using a kriging space interpolation method, and interpolate the generated raster data by using a bilinear difference algorithm;
the image rendering module 12 is configured to color each point interpolated by the calculation processing module according to a set color corresponding to the comfort value, and generate a color spot map reflecting comfort level distribution in the target area;
by the method, scattered point data in the target area are interpolated into raster data through a kriging space interpolation method for scattered point meteorological data, the generated raster data are interpolated by a bilinear difference algorithm, each point after interpolation is colored according to a set color corresponding to a comfort value, a color spot graph reflecting the comfort level distribution in the target area is generated, the accuracy of data in the area between the scattered points can be greatly improved, and meanwhile, the scattered point data are converted into the color spot graph rendered according to the comfort level and are easier to observe.
Preferably, the server 1 further includes a network map module 13, where the network map module is configured to attach the mottled map with the comfort level distribution in the target area generated by the image rendering module to a corresponding position on the map;
by combining the comfort rendering map with the map, the comfort distribution condition of each area can be observed more clearly.
Preferably, the server 1 further includes a display module 14, and the display module is configured to display the collected detection site data and the generated graph; the display and the visual operation are convenient.
It will be understood that modifications and variations can be made by persons skilled in the art in light of the above teachings and all such modifications and variations are intended to be included within the scope of the invention as defined in the appended claims.
Claims (10)
1. A smart city meteorological observation method comprises a plurality of detection stations distributed in scattered points, and is characterized in that the implementation method comprises the following steps:
the first step is as follows: acquiring meteorological data of all the detection stations in the selected target area at the current moment;
the second step is that: calculating the current comfort level of each corresponding detection station by adopting a comfort level algorithm according to the acquired meteorological data;
the third step: interpolating scattered point data in a target area into raster data by adopting a Kriging space interpolation method, and interpolating the generated raster data by adopting a bilinear difference algorithm;
the fourth step: and coloring each point after interpolation according to a set color corresponding to the comfort degree value to generate a color spot diagram reflecting the comfort degree grade distribution in the target area.
2. The smart city weather observation method as claimed in claim 1, wherein in the third step, interpolation result data for each position at a set distance interval in the target area is calculated by using a kriging space interpolation method and an inverse distance weighting algorithm to form raster data.
3. The smart city weather observation method as claimed in claim 1, wherein in the fourth step, a front-end canvas technique is adopted, and a color representing the comfort level of the location is selected and colored according to the data size of each point after interpolation, so as to generate a color spot diagram reflecting the comfort level distribution in the target area.
4. The smart city weather observation method according to any one of claims 1 to 3, further comprising a fifth step of: and fitting the generated color spot map with the comfort level distribution in the target area to the corresponding position on the map.
5. The smart city weather observation method as claimed in claim 4, wherein in the fifth step, the function of a developer based on a Gade map is implemented by using a canvas layer technology of the Gade map.
6. The smart city weather observation method according to any one of claims 1 to 3, wherein the weather data includes one or more of a site ID, a site location, a wind speed, a wind direction, a temperature, and a humidity.
7. The smart city weather observation method according to any one of claims 1 to 3, wherein in the second step, the comfort level algorithm is calculated as:
ssd＝(1.818t+18.18)*(0.88+0.002f)+(t-32)/(45-t)-3.2v+18.2；
wherein ssd is the comfort level of the detection station, t is the average air temperature of all the temperatures of the detection station, f is the relative humidity of the detection station, and v is the wind speed of the detection station.
8. A smart city weather-meteorological observation system for implementing the smart city weather-meteorological observation method according to any one of claims 1 to 7, comprising a server and a plurality of detection stations distributed in a scattered manner; the server comprises a meteorological data collecting module, a computing processing module and an image rendering module;
the meteorological data collecting module is used for collecting meteorological data of all the detection sites in the selected target area at the current moment;
the calculation processing module is used for calculating the current comfort level of each corresponding detection station by adopting a comfort level algorithm according to the acquired meteorological data, interpolating scattered data in a target area into raster data by adopting a Kriging space interpolation method, and interpolating the generated raster data by adopting a bilinear difference algorithm;
and the image rendering module is used for coloring each point after interpolation of the calculation processing module according to the set color corresponding to the comfort value to generate a color spot diagram reflecting the comfort level distribution in the target area.
9. The smart city weather observation system according to claim 8, wherein the server further includes a network map module, and the network map module is configured to attach a mottled map of comfort level distribution in the target area generated by the image rendering module to a corresponding position on a map.
10. The smart city weather observation system according to claim 9, wherein the server further comprises a display module for displaying the collected inspection site data and the generated chart.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN114442198A (en) * | 2022-01-21 | 2022-05-06 | 广西壮族自治区气象科学研究所 | Forest fire weather grade forecasting method based on weighting algorithm |
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| CN109239811A (en) * | 2018-09-26 | 2019-01-18 | 东莞绿邦智能科技有限公司 | Compartmentalization weather comfort level intelligence real-time broadcasting system |
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Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN102521403A (en) * | 2011-12-26 | 2012-06-27 | 南京成风大气信息技术有限公司 | Refined meteorological information service system |
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| CN109239811A (en) * | 2018-09-26 | 2019-01-18 | 东莞绿邦智能科技有限公司 | Compartmentalization weather comfort level intelligence real-time broadcasting system |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN114442198A (en) * | 2022-01-21 | 2022-05-06 | 广西壮族自治区气象科学研究所 | Forest fire weather grade forecasting method based on weighting algorithm |
| CN114442198B (en) * | 2022-01-21 | 2024-03-15 | 广西壮族自治区气象科学研究所 | Forest fire weather grade forecasting method based on weighting algorithm |
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