CN107563594B - Method for evaluating effective data acquisition capacity of remote sensing satellite - Google Patents
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Abstract
The invention discloses an effective data acquisition capacity evaluation method of a remote sensing satellite, which fully considers the influence of three factors such as satellite receiving station resources, satellite use constraint, regional climate characteristic and the like on the satellite data acquisition capacity except the self capacity of the satellite, and carries out geospatial analysis on the three factors such as the satellite receiving station resources, the satellite use constraint and the regional climate characteristic to obtain a grade distribution map of the satellite on the difficulty degree of acquiring global land regional data; and evaluating the data acquisition capacity of the satellite based on the distribution map and the regional score corresponding to each factor, so that the accuracy and the objectivity of evaluating the data acquisition capacity of the satellite are improved, and a reference basis is provided for task planning of the satellite in orbit.
Description
Technical Field
The invention belongs to the technical field of remote sensing satellites, and particularly relates to an effective data acquisition capacity evaluation method of a remote sensing satellite.
Background
With the increasing number of autonomous land observation satellites in China, the increasing of the spatial resolution and the increasing of the types of sensors, the remote sensing data acquisition capability is greatly enhanced. At present, 13 civil land observation remote sensing satellites are transmitted in China, 10 civil land observation remote sensing satellites are operated in orbit, the data of low and medium resolution can be covered once every 2 days and once every month better than the data of 2.5 meters in domestic areas, and meanwhile, the data acquisition capacity of the foreign areas is further improved. How to evaluate the effective data acquisition capacity of the remote sensing satellite is an important task.
At present, the evaluation of the data acquisition capacity of the remote sensing satellite commonly used at home and abroad is mainly based on the satellite orbit and the coverage of a sensor, the orbit prediction is carried out to obtain the satellite down-satellite point track, and the data acquisition capacity of the satellite is finally obtained according to the breadth and the sidesway capacity of the sensor. The evaluation of the data acquisition capability does not consider the ground reception capability of satellite data, weather, even climate and other constraint factors, and the finally obtained evaluation result cannot truly and accurately reflect the data acquisition capability of the satellite.
Disclosure of Invention
The technical problem of the invention is solved: the method for evaluating the effective data acquisition capacity of the remote sensing satellite overcomes the defects of the prior art, and more accurately and objectively evaluates the effective data acquisition capacity of the remote sensing satellite.
In order to solve the technical problem, the invention discloses an effective data acquisition capacity evaluation method of a remote sensing satellite, which comprises the following steps:
performing geospatial analysis on three factors including satellite receiving station resources, satellite use constraint and regional climate characteristics to obtain a grade distribution map of the satellite on the difficulty degree of acquiring global terrestrial region data; wherein the level distribution map comprises: the satellite receiving station resource level distribution map, the satellite use constraint level distribution map and the regional climate characteristic distribution map; the resource grade distribution diagram of the satellite receiving station comprises the following components: the corresponding scores are respectively A1、A2And A3Three distribution areas of (a); the satellite usage constraint level profile comprising: the corresponding scores are respectively B1、B2And B3Three distribution areas of (a); the regional climate characteristic profile comprising: the corresponding scores are respectively C1、C2And C3Three distribution areas of (a);
determining distribution areas of a single satellite in the satellite receiving station resource level distribution map, the satellite use constraint level distribution map and the area climate characteristic distribution map according to the dimensional information of the single satellite, and acquiring the scores of the corresponding areas;
and carrying out weighted summation on the obtained scores of the corresponding regions to obtain the data acquisition capacity of the single satellite.
In the method for evaluating the effective data acquisition capacity of the remote sensing satellite, the resource grade distribution map of the satellite receiving station is obtained through the following steps:
dividing a global land area into a real transmission area, an alternate real transmission area and a recording imaging area according to the receiving type of a ground station;
determining the real transmission area as A1A score distribution region; wherein, the real-time transmission area comprises: chinese domestic area, Kashi station receiving range area and peony river station receiving range area;
determining the alternate real transmission area as A2A score distribution region; wherein, the alternate real-time transmission area comprises: receiving range area of dense cloud station except in Chinese and receiving range area of three-station except in ChineseAn outer reception range region;
determining the recording imaging area as A3A score distribution region; wherein the recording imaging area includes: except for the regions within china, the karhshi station reception range region, the peony river station reception range region, the dense cloud station reception range region other than within the china border, and the other land regions other than the three-in station reception range region other than within the china border.
In the method for evaluating the effective data acquisition capacity of the remote sensing satellite, the satellite use constraint level distribution map is obtained through the following steps:
dividing a global land area into a data acquisition easy area, a data acquisition difficulty general area and a data acquisition difficulty area according to at least one of imaging time length of each circle of a satellite, fixed storage capacity on the satellite, satellite data downloading rate and daily imaging requirements of the satellite;
determining the data acquisition easiness area as B1A score distribution region; wherein the data acquisition ease area includes: the imaging time of each circle reaches the limit specified by the satellite, the fixed storage capacity on the satellite is sufficient, the data downloading is not occupied, and the coverage area which can be received by a receiving station meeting daily requirements is met;
determining the general data acquisition difficulty area as B2A score distribution region; wherein, the general area of data acquisition difficulty includes: the coverage area which does not affect imaging in China and has surplus fixed storage capacity on the satellite is provided;
determining the data acquisition difficulty area as B3A score distribution region; wherein the data acquisition difficulty area comprises: other terrestrial regions than the easy-to-acquire region and the general difficult-to-acquire region.
In the method for evaluating the effective data acquisition capacity of the remote sensing satellite, a regional climate characteristic distribution map is obtained through the following steps:
according to the classification category of the Country climate, dividing the global land area into a dry climate area, a medium climate area and a wet climate area;
determining the climate dry zone as C1A score distribution region; wherein the climate drying zone comprises: tropical thinning grassland climate areas, tropical and subtropical desert climate areas, and tropical and subtropical grassland climate areas;
determining the climatically moderate dry zone as C2A score distribution region; wherein the climatically intermediate dry zone comprises: tropical and subtropical monsoon climate zones, tropical grassland climate zones, temperate zone climate zones of various types, cold climate zones, and snowforest climate zones;
determining the climatically humid area as C3A score distribution region; wherein the climatically wet area comprises: tropical rain forest climate zones, polar lichen zone and polar iceland climate zones.
In the above method for evaluating the effective data acquisition capability of a remote sensing satellite,
a is described1、A2And A3The corresponding scores were respectively: score 3, score 2 and score 1;
b is1、B2And B3The corresponding scores were respectively: score 3, score 2 and score 1;
said C is1、C2And C3The corresponding scores were respectively: 3 min, 2 min and 1 min.
In the method for evaluating the effective data acquisition capability of the remote sensing satellite, the determining distribution areas of the single satellite in the satellite receiving station resource level distribution map, the satellite use constraint level distribution map and the area climate characteristic distribution map according to the dimensional information of the single satellite, and acquiring the scores of the corresponding areas includes:
when the single satellite is determined to be positioned in A of the resource level distribution diagram of the satellite receiving station according to the dimension information of the single satelliteiWhen the distribution area of the score is located, taking the first score as Ai(ii) a Wherein i is 1, 2 or 3;
determining that the single satellite is located at the satellite usage restriction level according to the dimensional information of the single satelliteB in the distribution diagramjWhen the distribution area of the score is located, taking the second score as Bj(ii) a Wherein j is 1, 2 or 3;
determining that the single satellite is located at C in the regional climate characteristic distribution map according to the dimensional information of the single satellitemWhen the distribution area of the score is located, taking the third score as Cm(ii) a Wherein m is 1, 2 or 3.
In the method for evaluating the effective data acquisition capability of the remote sensing satellite, the obtaining of the data acquisition capability of the single satellite by performing weighted summation on the obtained scores of the corresponding areas comprises:
and the data acquisition capacity phi of the single satellite is equal to a first score + a second score + a third score.
In the method for evaluating the effective data acquisition capability of the remote sensing satellite, the method further comprises the following steps:
and evaluating the data acquisition capacity of the plurality of satellites according to the data acquisition capacity of the single satellite and the width of the single satellite.
In the method for evaluating the effective data acquisition capability of the remote sensing satellite, the evaluating the data acquisition capability of a plurality of satellites according to the data acquisition capability of a single satellite and the width of the single satellite includes:
obtaining the respective corresponding widths F of n satellitesnAnd, data acquisition capabilities Φ for each of the n satellitesn(ii) a Wherein, FnDenotes the width, phi, of the nth satellitenThe data acquisition capacity of the nth satellite is shown, and n is more than or equal to 2;
summing the widths of the n satellites to obtain the sum sigma F of the widths of the n satellites;
and according to the width corresponding to each satellite and the sum of the widths, distributing the weight of each satellite:
wherein Q isnRepresenting the weight of the nth satellite;
determining the data acquisition capacity psi of n satellites according to the data acquisition capacity of each satellite and the weight of each satellite:
Ψ＝∑Qn*Φn。
the invention has the following advantages:
according to the method for evaluating the effective data acquisition capacity of the remote sensing satellite, the influence of three factors such as satellite receiving station resources, satellite use constraints and regional climate characteristics on the satellite data acquisition capacity except the satellite self capacity is fully considered, the geospatial analysis is carried out on the three factors such as the satellite receiving station resources, the satellite use constraints and the regional climate characteristics, and a grade distribution diagram of the satellite on the difficulty degree of acquiring global land regional data is obtained; and evaluating the data acquisition capacity of the satellite based on the distribution map and the regional score corresponding to each factor, so that the accuracy and the objectivity of evaluating the data acquisition capacity of the satellite are improved, and a reference basis is provided for task planning of the satellite in orbit.
And secondly, on the basis of evaluating the data acquisition capacity of a single satellite, the invention also realizes the evaluation of the data acquisition capacity of a plurality of satellites based on the corresponding breadth of the satellite, improves the efficiency of the satellite, particularly the global effective coverage data of a plurality of satellites in a combined manner, and provides reference for users to know the difficulty of global data acquisition.
Drawings
Fig. 1 is a flowchart illustrating steps of a method for evaluating an effective data acquisition capability of a remote sensing satellite according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, common embodiments of the present invention will be described in further detail below with reference to the accompanying drawings.
Referring to fig. 1, a flowchart illustrating steps of a method for evaluating an effective data acquisition capability of a remote sensing satellite according to an embodiment of the present invention is shown. In this embodiment, the method for evaluating the effective data acquisition capability of the remote sensing satellite includes:
In this embodiment, the level distribution map includes: a satellite receiving station resource level profile, a satellite usage constraint level profile, and a regional climate characteristic profile.
Further, the resource level distribution diagram of the satellite receiving station comprises: the corresponding scores are respectively A1、A2And A3Three distribution areas. The satellite usage constraint level profile comprising: the corresponding scores are respectively B1、B2And B3Three distribution areas. The regional climate characteristic profile comprising: the corresponding scores are respectively C1、C2And C3Three distribution areas.
Wherein, A is1、A2And A3、B1、B2And B3And C1、C2And C3The specific value of (2) can be determined according to actual conditions. In other words, the resource level distribution map of the satellite receiving station may specifically include three regions, each corresponding to a different value; similarly, the satellite use constraint level distribution map specifically comprises three regions, wherein each region corresponds to a different score; the regional climate characteristic profile may specifically include three regions, each region corresponding to a different score.
Preferably, A is1、A2And A3The corresponding scores may be: score 3, score 2 and score 1; b is1、B2And B3The corresponding scores may be: score 3, score 2 and score 1; said C is1、C2And C3The corresponding scores may be: 3 min, 2 min and 1 min.
In a preferred embodiment of the present invention, since the orbit height, the type of data transmission antenna (broadcast or spot beam), and the ground receiving resource of each satellite are different, the influence factor of the satellite receiving station resource can be specifically divided according to the satellite characteristicsAnalyzing, dividing into three grades according to the easy to obtain, and respectively assigning A1、A2And A3。
Preferably, in this embodiment, the resource level distribution map of the satellite receiving station may be obtained by: dividing a global land area into a real transmission area, an alternate real transmission area and a recording imaging area according to the receiving type of a ground station; determining the real transmission area as A1A score distribution region; determining the alternate real transmission area as A2A score distribution region; the recording imaging area is determined as an a3 score distribution area.
Taking the high-score first satellite and the high-score second satellite as examples, the orbit heights of the high-score first satellite and the high-score second satellite are 645 kilometers, data are received by four receiving stations such as a dense cloud station, a karsh station, a third-generation station and a peony river station, and each receiving station corresponds to a different receiving range. Furthermore, because the data transmission antennas of the high-resolution one-number and high-resolution two-number satellites are in a spot beam type, that is, only one receiving station can receive data at the same time, and the working time of a single satellite circle cannot exceed 12 minutes, in order to ensure complete coverage in China during actual operation of the satellites, a dense cloud station and three-substation alternate real transmission and reception mode is usually adopted. In china, even if the system is located in the alternate reception range, the system usually uses a recording method to ensure timely coverage of the system.
As shown in table 1, the present invention is a comparison table between each region of a distribution diagram of resource grades of a satellite receiving station and the grade of the score.
TABLE 1
As can be seen, the real-time transfer area may include: chinese domestic area, Kashi station receiving range area and peony river station receiving range area; the alternate real transfer region may include: a receiving range area of the dense cloud station except the Chinese border and a receiving range area of the three-substation except the Chinese border; the recording imaging area may include: except for the regions within china, the karhshi station reception range region, the peony river station reception range region, the dense cloud station reception range region other than within the china border, and the other land regions other than the three-in station reception range region other than within the china border.
In a preferred embodiment of the present invention, the satellite usage constraints must be strictly followed when scheduling and scheduling the satellites. In this embodiment, the satellite usage constraints primarily considered include: (1) imaging time of each circle of the satellite; (2) fixed storage capacity on the satellite; (3) a satellite data download rate; (4) satellite daily imaging needs. Dividing the obtained data into three grades according to the easy to be difficult to be obtained, and respectively assigning values B1、B2And B3. The daily imaging requirement of the satellite is non-mandatory constraint and can not be considered in an emergency situation. For a Chinese terrestrial observation satellite, the daily imaging requirement is to meet the coverage of an area in a Chinese environment, and generally, the satellite needs to be imaged as long as the satellite passes through the Chinese environment.
Preferably, in this embodiment, the satellite usage constraint level distribution map may be obtained by: dividing a global land area into a data acquisition easy area, a data acquisition difficulty general area and a data acquisition difficulty area according to at least one of imaging time length of each circle of a satellite, fixed storage capacity on the satellite, satellite data downloading rate and daily imaging requirements of the satellite; determining the data acquisition easiness area as B1A score distribution region; determining the general data acquisition difficulty area as B2A score distribution region; determining the data acquisition difficulty area as B3A score distribution region.
As shown in table 2, a comparison table of each region of the constraint level distribution map and the score level is used for a satellite according to an embodiment of the present invention.
TABLE 2
As can be seen, the data acquisition ease area may include: the imaging time of each circle reaches the limit specified by the satellite, the fixed storage capacity on the satellite is sufficient, the data downloading is not occupied, and the coverage area which can be received by a receiving station meeting daily requirements is met; the general data acquisition difficulty area may include: the coverage area which does not affect imaging in China and has surplus fixed storage capacity on the satellite is provided; the data acquisition difficulty area may include: other terrestrial regions than the easy-to-acquire region and the general difficult-to-acquire region.
Take high-grade first satellite as an example
The imaging time length of each circle of the high-grade first satellite is limited to 12 minutes; the fixed storage capacity on the satellite is 1 Tb; the data downloading adopts two channels, and the rate of each channel is 450Mbps, namely the total downloading rate is 900 Mbps. And combining the objective use constraint of the high-grade first satellite and the satellite imaging requirement, and obtaining the grade distribution condition of the satellite use constraint influence factor of the high-grade first satellite.
B3Score, data acquisition difficulty area: the data downloading capability of the satellite cannot meet the real-time transmission of all cameras when being started at the same time, so that a 2 m/8 m data real-time transmission and 16 m data recording mode is usually adopted when imaging in China. However, due to the capacity limit of satellite solid storage (16 m data is stored for 18 minutes at most), other passing non-real-transmission areas cannot be imaged before the total solid storage data is not downloaded (unless 16 m imaging in China is lost); meanwhile, the north and south areas adjacent to China are difficult to acquire data in consideration of the imaging time limit of each circle of the satellite.
B2Score, general area of data acquisition difficulty: the imaging requirement in China is not influenced, and meanwhile, the on-satellite storage space is enough to record the imaging area. When the night satellite passes through the ground receiving station, 16 m data recorded in the daytime in China are transmitted back, and then the data can be recorded in other areas in a space.
B1Score, data acquisition ease area: china and the areas that the receiving station can receive.
In a preferred embodiment of the invention, on the basis of the Caben climate classification method, the global land is divided into three grades according to the climate dryness degree and the cloud and snow coverage degree, and the three grades are respectively assigned with valuesC1、C2And C3。
Preferably, in this embodiment, the regional climate characteristic distribution map may be obtained by: according to the category of the Caben climate classification, the global land area is divided into a dry climate area, a medium climate area and a wet climate area. Determining the climate dry zone as C1A score distribution region; determining the climatically moderate dry zone as C2A score distribution region; determining the climatically humid area as C3A score distribution region.
As shown in table 3, it is a comparison table of each region of the regional climate characteristic distribution map and the score level according to the embodiment of the present invention.
TABLE 3
As can be seen, the climate drying zone may comprise: tropical thinning grassland climate areas, tropical and subtropical desert climate areas, and tropical and subtropical grassland climate areas; the climatically intermediate dry zone may include: tropical and subtropical monsoon climate zones, tropical grassland climate zones, temperate zone climate zones of various types, cold climate zones, and snowforest climate zones; the climatically humid region may include: tropical rain forest climate zones, polar lichen zone and polar iceland climate zones.
And 102, determining distribution areas of the single satellite in the satellite receiving station resource level distribution map, the satellite use constraint level distribution map and the area climate characteristic distribution map according to the dimensional information of the single satellite, and acquiring the scores of the corresponding areas.
In the present embodiment, it is preferred that,
when the single satellite is determined to be positioned in A of the resource level distribution diagram of the satellite receiving station according to the dimension information of the single satelliteiWhen the distribution area of the score is located, taking the first score as Ai(ii) a Wherein i is 1, 2 or 3.
When according to the single toiletDetermining that the single satellite is located in B of the satellite usage constraint level distribution map through dimension information of the satellitejWhen the distribution area of the score is located, taking the second score as Bj(ii) a Wherein j is 1, 2 or 3.
Determining that the single satellite is located at C in the regional climate characteristic distribution map according to the dimensional information of the single satellitemWhen the distribution area of the score is located, taking the third score as Cm(ii) a Wherein m is 1, 2 or 3.
For example, assuming that the dimensional coordinates of a single satellite are determined to be (x, y) according to the dimensional information of the single satellite, the specific scores of three factors corresponding to the satellite can be determined according to the longitude and latitude coordinates (x, y): if the satellite is determined to be located in an actual transmission area (satellite receiving station resource factor), a data acquisition easy area (satellite use constraint factor) and a climate dry area (area climate characteristic factor) according to the longitude and latitude coordinates (x, y), the corresponding factor scores of the satellite can be determined as follows: a. the1、B1And C1。
And 103, carrying out weighted summation on the obtained scores of the corresponding regions to obtain the data acquisition capacity of the single satellite.
In this embodiment, the data acquisition capability Φ of the single satellite is equal to the first score + the second score + the third score. For the satellite with the longitude and latitude coordinates (x, y), the data acquisition capability of the satellite is A1、B1And C1The sum of the three.
In a preferred embodiment of the present invention, a method for evaluating data acquisition capabilities of a plurality of satellites is also disclosed. Preferably, the method for evaluating the effective data acquisition capability of the remote sensing satellite may further include:
and 104, evaluating the data acquisition capacity of the multiple satellites according to the data acquisition capacity of the single satellite and the width of the single satellite.
In this embodiment, the specific steps for evaluating the data acquisition capability of multiple (n) satellites may be as follows:
a substep S1 of obtaining the widths F corresponding to the n satellites respectivelynAnd, data acquisition capabilities Φ for each of the n satellitesn。
In this embodiment, the data obtaining capability Φ of each satellite can be obtained according to the foregoing steps 101-103nAnd based on the characteristics of each satellite, obtaining the width F corresponding to each satelliten. Wherein, FnDenotes the width, phi, of the nth satellitenThe data acquisition capability of the nth satellite is shown, and n is more than or equal to 2.
In the sub-step S2, the widths of the n satellites are summed to obtain a sum Σ F of the widths of the n satellites.
And a substep S3 of assigning a weight to each satellite according to the width corresponding to each satellite and the sum of the widths.
In this embodiment, the weight of each satellite is calculated as follows:
wherein Q isnRepresenting the weight of the nth satellite.
And a sub-step S4 of determining the data acquisition capacities Ψ of the n satellites according to the data acquisition capacities of the satellites and the weights of the satellites.
In this embodiment, the calculation formula of the data acquisition capability Ψ for n satellites is as follows:
Ψ＝∑Qn*Φn
taking four satellites of GF-1, GF-2, ZY-3 and ZY-102C with the resolution better than 2.5 m as an example, as shown in Table 4, the weight value distribution table of the satellite with the resolution better than 2.5 m in the embodiment of the invention is provided.
| Satellite | Breadth (kilometer) | Weighted value |
| GF-1 | 70 | 0.30 |
| GF-2 | 45 | 0.20 |
| ZY-3 | 51 | 0.25 |
| ZY-1 02C | 54 | 0.25 |
TABLE 4
The data acquisition capabilities of the four satellites above a resolution of 2.5 meters are then:
Ψfourthly＝0.30*ΦGF-1+0.20*ΦGF-2+0.25*ΦZY-3+0.25*ΦZY-1 02C
In conclusion, the method for evaluating the effective data acquisition capacity of the remote sensing satellite fully considers the influence of three factors such as satellite receiving station resources, satellite use constraint and regional climate characteristic on the satellite data acquisition capacity except the capacity of the satellite, and carries out geospatial analysis on the three factors such as the satellite receiving station resources, the satellite use constraint and the regional climate characteristic to obtain a grade distribution map of the satellite on the difficulty degree of acquiring global land regional data; and evaluating the data acquisition capacity of the satellite based on the distribution map and the regional score corresponding to each factor, so that the accuracy and the objectivity of evaluating the data acquisition capacity of the satellite are improved, and a reference basis is provided for task planning of the satellite in orbit.
And secondly, on the basis of evaluating the data acquisition capacity of a single satellite, the invention also realizes the evaluation of the data acquisition capacity of a plurality of satellites based on the corresponding breadth of the satellite, improves the efficiency of the satellite, particularly the global effective coverage data of a plurality of satellites in a combined manner, and provides reference for users to know the difficulty of global data acquisition.
The embodiments in the present description are all described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other.
The above description is only for the best mode of the present invention, but the scope of the present invention is not limited thereto, and any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope of the present invention are included in the scope of the present invention.
Those skilled in the art will appreciate that the invention may be practiced without these specific details.
Claims (2)
1. A method for evaluating the effective data acquisition capacity of a remote sensing satellite is characterized by comprising the following steps:
performing geospatial analysis on three factors including satellite receiving station resources, satellite use constraint and regional climate characteristics to obtain a grade distribution map of the satellite on the difficulty degree of acquiring global terrestrial region data; wherein the level distribution map comprises: the satellite receiving station resource level distribution map, the satellite use constraint level distribution map and the regional climate characteristic distribution map;
obtaining the resource grade distribution map of the satellite receiving station by the following steps: dividing a global land area into a real transmission area, an alternate real transmission area and a recording imaging area according to the receiving type of a ground station; determining the real transmission area as A1A value distribution region, the alternate real transmission region is determined as A2A distribution region of the component values, the recording imaging region being determined as A3A score distribution region; wherein, the real-time transmission area comprises: internal region of ChineseThe receiving range area of the region, the Kashi station and the peony river station; the alternate real transmission area comprises: a receiving range area of the dense cloud station except the Chinese border and a receiving range area of the three-substation except the Chinese border; the recording imaging area includes: excluding the region in China, the karhshi station receiving range region, the peony river station receiving range region, the receiving range region of the dense cloud station except the region in China and other land regions except the receiving range region of the three-in station except the region in China;
obtaining the satellite use constraint level distribution map by the following steps: dividing a global land area into a data acquisition easy area, a data acquisition difficulty general area and a data acquisition difficulty area according to at least one of imaging time length of each circle of a satellite, fixed storage capacity on the satellite, satellite data downloading rate and daily imaging requirements of the satellite; determining the data acquisition easiness area as B1A value distribution area, wherein the general area of data acquisition difficulty is determined as B2A distribution region of the scores, the region of data acquisition difficulty being determined as B3A score distribution region; wherein the data acquisition ease area includes: the imaging time of each circle reaches the limit specified by the satellite, the fixed storage capacity on the satellite is sufficient, the data downloading is not occupied, and the coverage area which can be received by a receiving station meeting daily requirements is met; the general data acquisition difficulty area comprises: the coverage area which does not affect imaging in China and has surplus fixed storage capacity on the satellite is provided; the data acquisition difficulty area comprises: other land areas except the data acquisition easy area and the data acquisition difficulty general area;
obtaining a regional climate characteristic distribution map by the following steps: according to the category of the Corbook climate classification, dividing the global land area into a climate dry area, a climate moderate dry area and a climate wet area; determining the climate dry zone as C1A distribution region of the scores, the dry region in the climate is determined as C2A distribution region of the scores, the climate-wetted region being determined as C3A score distribution region; wherein the climate drying zone comprises: grass land for tropical sparse forestClimate zones, tropical, subtropical desert climate zones, and tropical, subtropical grassland climate zones; the climatically intermediate dry zone comprising: tropical and subtropical monsoon climate zones, tropical grassland climate zones, temperate zone climate zones of various types, cold climate zones, and snowforest climate zones; the climatically-humid region comprising: tropical rain forest climate zones, polar lichen zone and polar ice zone;
when determining that the single satellite is positioned in A in the resource level distribution map of the satellite receiving station according to the longitude and latitude information of the single satelliteiWhen the distribution area of the score is located, taking the first score as Ai(ii) a When the single satellite is determined to be positioned in B in the satellite use constraint level distribution diagram according to the longitude and latitude information of the single satellitejWhen the distribution area of the score is located, taking the second score as Bj(ii) a When the single satellite is determined to be positioned in C in the regional climate characteristic distribution map according to the longitude and latitude information of the single satellitemWhen the distribution area of the score is located, taking the third score as Cm(ii) a Wherein i is 1, 2 or 3, j is 1, 2 or 3, and m is 1, 2 or 3;
carrying out weighted summation on the obtained values of the obtained corresponding regions to obtain the data obtaining capacity of the single satellite; wherein, the data acquisition capacity phi of a single satellite is Ai+Bj+Cm；
Obtaining the respective corresponding widths F of n satellitesnAnd, data acquisition capabilities Φ for each of the n satellitesn(ii) a Wherein, FnDenotes the width, phi, of the nth satellitenThe data acquisition capacity of the nth satellite is shown, and n is more than or equal to 2;
summing the widths of the n satellites to obtain the sum sigma F of the widths of the n satellites;
and according to the width corresponding to each satellite and the sum sigma F of the widths of the n satellites, distributing the weight of each satellite:
wherein Q isnRepresenting the weight of the nth satellite;
determining the data acquisition capacity psi of n satellites according to the data acquisition capacity of each satellite and the weight of each satellite:
Ψ＝∑Qn*Φn。
2. the method of claim 1,
a is described1、A2And A3The corresponding scores were respectively: score 3, score 2 and score 1;
b is1、B2And B3The corresponding scores were respectively: score 3, score 2 and score 1;
said C is1、C2And C3The corresponding scores were respectively: 3 min, 2 min and 1 min.
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| CN102982392A (en) * | 2012-11-07 | 2013-03-20 | 中国科学院亚热带农业生态研究所 | Index of agricultural rodent pest outbreak risk estimation method based on geographical information system |
| CN104406698A (en) * | 2014-11-24 | 2015-03-11 | 武汉理工大学 | Urban thermal island space distribution evaluation method |
| CN105005649A (en) * | 2015-07-07 | 2015-10-28 | 兰州交通大学 | Potential underground water distribution mapping method |
| CN105787652A (en) * | 2016-02-23 | 2016-07-20 | 北京师范大学 | Area integrated environment risk evaluation and portioning method |
| CN106570337A (en) * | 2016-11-14 | 2017-04-19 | 中国西安卫星测控中心 | Method for evaluating comprehensive capability of spacecraft |
| CN106651211A (en) * | 2016-12-30 | 2017-05-10 | 吉林师范大学 | Different-scale regional flood damage risk evaluation method |
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| CN102982392A (en) * | 2012-11-07 | 2013-03-20 | 中国科学院亚热带农业生态研究所 | Index of agricultural rodent pest outbreak risk estimation method based on geographical information system |
| CN104406698A (en) * | 2014-11-24 | 2015-03-11 | 武汉理工大学 | Urban thermal island space distribution evaluation method |
| CN105005649A (en) * | 2015-07-07 | 2015-10-28 | 兰州交通大学 | Potential underground water distribution mapping method |
| CN105787652A (en) * | 2016-02-23 | 2016-07-20 | 北京师范大学 | Area integrated environment risk evaluation and portioning method |
| CN106570337A (en) * | 2016-11-14 | 2017-04-19 | 中国西安卫星测控中心 | Method for evaluating comprehensive capability of spacecraft |
| CN106651211A (en) * | 2016-12-30 | 2017-05-10 | 吉林师范大学 | Different-scale regional flood damage risk evaluation method |
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