CN107563594B - Method for evaluating effective data acquisition capacity of remote sensing satellite - Google Patents

Abstract

The invention discloses an effective data acquisition capability evaluation method of a remote sensing satellite, which fully considers the influence of three factors, including satellite receiving station resources, satellite usage constraints and regional climate characteristics, on the satellite data acquisition capability in addition to the capability of the satellite itself. Geospatial analysis is carried out on three factors: satellite receiving station resources, satellite usage constraints and regional climate characteristics to obtain a graded distribution map of the difficulty of satellite data acquisition on global land areas; based on the distribution map and regional scores corresponding to each factor, the satellite It improves the accuracy and objectivity of the evaluation of satellite data acquisition capabilities, and provides a reference for the mission planning of orbiting satellites.

Description

An Effective Data Acquisition Capability Evaluation Method for Remote Sensing Satellites

technical field

The invention belongs to the technical field of remote sensing satellites, and in particular relates to a method for evaluating the effective data acquisition capability of remote sensing satellites.

Background technique

With the continuous increase of the number of autonomous land observation satellites in my country, the continuous improvement of spatial resolution, and the continuous increase of sensor types, the ability to obtain remote sensing data has been greatly enhanced. At present, my country has launched 13 civil land observation remote sensing satellites, 10 of which are in orbit. The medium and low resolution data can be covered once every 2 days in my country, and the data better than 2.5 meters is covered once a month. Data acquisition capabilities have also been further improved. How to evaluate the effective data acquisition capability of remote sensing satellites is an important task.

At present, the data acquisition capability evaluation of remote sensing satellites commonly used at home and abroad is mainly based on satellite orbit and sensor coverage. ability. This kind of data acquisition capability assessment does not take into account the ground receiving capability of satellite data, weather and even climate and other constraints, and the final evaluation result cannot truly and accurately reflect the satellite data acquisition capability.

SUMMARY OF THE INVENTION

The technical solution of the present invention is to overcome the deficiencies of the prior art and provide a method for evaluating the effective data acquisition capability of a remote sensing satellite, which can more accurately and objectively evaluate the effective data acquisition capability of a remote sensing satellite.

In order to solve the above-mentioned technical problems, the present invention discloses a method for evaluating the effective data acquisition capability of remote sensing satellites, including:

Geospatial analysis is performed on three factors of satellite receiving station resources, satellite usage constraints and regional climate characteristics, and a graded distribution map of the difficulty of satellite data acquisition on global land areas is obtained; wherein, the graded distribution map includes: satellite receiving stations Resource level distribution map, satellite usage constraint level distribution map and regional climate characteristic distribution map; among them, the resource level distribution map of satellite receiving stations includes: three distribution areas with corresponding scores of A ₁ , A ₂ and A ₃ respectively; The distribution map of the satellite usage constraint level includes: three distribution areas with corresponding scores B ₁ , B ₂ and B ₃ respectively; the regional climate characteristic distribution map includes: the corresponding scores are C ₁ , C ₂ and _Three distribution areas of C3;

According to the latitude and longitude information of a single satellite, determine the distribution area of the single satellite in the satellite receiving station resource level distribution map, the satellite usage constraint level distribution map and the regional climate characteristic distribution map, and obtain the score of the corresponding area ;

A weighted summation is performed on the acquired scores for acquiring the corresponding area to obtain the data acquisition capability of the single satellite.

In the above-mentioned method for evaluating the effective data acquisition capability of remote sensing satellites, the resource level distribution map of the satellite receiving station is obtained through the following steps:

According to the receiving category of the ground station, the global land area is divided into the real transmission area, the alternate real transmission area and the recording imaging area;

_The actual transmission area is determined as the A1 score distribution area; wherein, the actual transmission area includes: the area within China, the receiving range area of Kashi Station and the receiving area area of Mudanjiang Station;

_The alternate actual transmission area is determined as the A2 score distribution area; wherein, the alternate actual transmission area includes: the receiving range area of Miyun station except China and the receiving area area of Sanya station except China ;

_The recording imaging area is determined as the A3 score distribution area; wherein, the recording imaging area includes: excluding the area within the territory of China, the receiving area of Kashi Station, the receiving area of Mudanjiang Station, and the area of Miyun Station except those within China outside the receiving area and other land areas outside the receiving area of Sanya Station outside of China.

In the above-mentioned method for evaluating the effective data acquisition capability of remote sensing satellites, the satellite usage constraint level distribution map is obtained through the following steps:

According to at least one of the imaging duration of each lap of the satellite, the fixed storage capacity on the satellite, the data download rate of the satellite and the daily imaging requirements of the satellite, the global land area is divided into areas with easy data acquisition, areas with general difficulty in data acquisition, and areas with difficult data acquisition. ;

_The easy area for data acquisition is determined as the B1 score distribution area; wherein, the easy area for data acquisition includes: the imaging duration of each circle reaches the limit specified by the satellite, the fixed storage capacity on the satellite is sufficient, and the data download is not occupied , The coverage area that can be received by the receiving station that meets the daily needs;

Determining the general area of data acquisition difficulty as the B2 score distribution area _; wherein, the general data acquisition difficulty area includes: coverage areas that do not affect imaging within China and have a margin of fixed storage capacity on the satellite;

The data acquisition difficulty area is determined as a _B3 score distribution area; wherein the data acquisition difficulty area includes: other land areas except the data acquisition easy area and the data acquisition difficulty area.

In the above-mentioned method for evaluating the effective data acquisition capability of remote sensing satellites, the distribution map of regional climate characteristics is obtained through the following steps:

According to the Köppen climate classification category, the global land areas are divided into dry climate regions, moderately dry climate regions, and humid climate regions;

The dry climate area is determined as a C ₁ score distribution area; wherein, the dry climate area includes: a tropical sparse forest grassland climate area, a tropical and subtropical desert climate area, and a tropical and subtropical grassland climate area;

The moderately dry climate area is determined as a _C2 score distribution area; wherein, the moderately dry climate area includes: tropical and subtropical monsoon climate areas, savanna climate areas, temperate climate areas of various types, cold climate areas, and snow forest climate zone;

_The humid climate region is determined as a C3 score distribution region; wherein, the climate humid region includes: a tropical rain forest climate region, a polar tundra climate region and a polar ice sheet climate region.

In the above-mentioned methods for evaluating the effective data acquisition capability of remote sensing satellites,

The corresponding points of A ₁ , A ₂ and A ₃ are respectively: 3 points, 2 points and 1 point;

The corresponding scores of B ₁ , B ₂ and B ₃ are respectively: 3 points, 2 points and 1 point;

The corresponding scores of C ₁ , C ₂ and C ₃ are: 3 points, 2 points and 1 point, respectively.

In the above method for evaluating the effective data acquisition capability of remote sensing satellites, according to the longitude and dimensional information of a single satellite, the resource level distribution map, the satellite usage constraint level distribution map and the regional climate of the single satellite at the satellite receiving station are determined. The distribution area in the characteristic distribution map, and obtain the score of the corresponding area, including:

When it is determined according to the latitude and longitude information of the single satellite that the single satellite is located in the distribution area where the A _i score in the satellite receiving station resource level distribution diagram is located, the first score is A _i ; wherein , i=1, 2 or 3;

When it is determined according to the latitude and longitude information of the single satellite that the single satellite is located in the distribution area where the B _j score in the satellite usage constraint level distribution map is located, the second score is taken as B _j ; wherein, j=1, 2 or 3;

When it is determined according to the latitude and longitude information of the single satellite that the single satellite is located in the distribution area where the _Cm score in the regional climate characteristic distribution map is located, the third score is taken as _Cm ; wherein, m =1, 2 or 3.

In the above-mentioned method for evaluating the effective data acquisition capability of a remote sensing satellite, the weighted summation is performed on the acquired scores of the corresponding regions to obtain the data acquisition capability of the single satellite, including:

The data acquisition capability Φ of the single satellite is equal to the first score + the second score + the third score.

The above-mentioned methods for evaluating the effective data acquisition capability of remote sensing satellites also include:

According to the data acquisition capability of a single satellite and the width of a single satellite, the data acquisition capability of multiple satellites is evaluated.

In the above-mentioned method for evaluating the effective data acquisition capability of remote sensing satellites, the data acquisition capability of multiple satellites is evaluated according to the data acquisition capability of a single satellite and the width of a single satellite, including:

Obtain the width F _n corresponding to each of the n satellites, and the data acquisition capability Φ _n corresponding to each of the n satellites; wherein, F _n represents the width of the nth satellite, and Φ _n represents the data acquisition capability of the nth satellite , n≥2;

Sum the widths of n satellites to get the sum of the widths of n satellites ∑F;

The weight of each satellite is allocated according to the corresponding width of each satellite and the sum of the width:

Among them, Q _n represents the weight of the nth satellite;

According to the data acquisition ability of each satellite and the weight of each satellite, determine the data acquisition ability Ψ of n satellites:

Ψ= _{∑Qn *} Φn.

The present invention has the following advantages:

The method for evaluating the effective data acquisition capability of a remote sensing satellite according to the present invention fully considers the influence of three factors, such as satellite receiving station resources, satellite usage constraints and regional climate characteristics, on the satellite data acquisition capability in addition to the capability of the satellite itself. Geospatial analysis was carried out on three factors: receiving station resources, satellite usage constraints and regional climate characteristics to obtain a graded distribution map of the difficulty of satellite data acquisition on global land areas; The evaluation of data acquisition ability improves the accuracy and objectivity of the evaluation of satellite data acquisition ability, and provides a reference for the mission planning of orbiting satellites.

Secondly, on the basis of evaluating the data acquisition ability of a single satellite, the present invention also realizes the evaluation of the data acquisition ability of multiple satellites based on the width corresponding to the satellite, which improves the ability of satellites, especially the joint globalization of multiple satellites. Effectively cover the efficiency of data, and provide a reference for users to understand the difficulty of global data acquisition.

Description of drawings

FIG. 1 is a flow chart of steps of a method for evaluating the effective data acquisition capability of a remote sensing satellite in an embodiment of the present invention.

Detailed ways

In order to make the objectives, technical solutions and advantages of the present invention clearer, the 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 of steps of a method for evaluating the effective data acquisition capability of a remote sensing satellite in an embodiment of the present invention is shown. In this embodiment, the effective data acquisition capability evaluation method of the remote sensing satellite includes:

In step 101, geospatial analysis is performed on three factors of satellite receiving station resources, satellite usage constraints and regional climate characteristics, to obtain a grade distribution map of the difficulty in acquiring global land area data by satellites.

In this embodiment, the level distribution map includes: a satellite receiving station resource level distribution map, a satellite usage constraint level distribution map, and a regional climate characteristic distribution map.

Further, the resource level distribution map of the satellite receiving station includes: three distribution areas with corresponding scores of A ₁ , A ₂ and A ₃ respectively. The satellite usage constraint level distribution map includes: three distribution areas with corresponding scores of B ₁ , B ₂ and B ₃ respectively. The regional climate characteristic distribution map includes: three distribution regions with corresponding scores of C ₁ , C ₂ and C ₃ respectively.

It should be noted that the specific values of A ₁ , A ₂ and A ₃ , B ₁ , B ₂ and B ₃ , and C ₁ , C ₂ and C ₃ can be determined according to actual conditions. In other words, the resource level distribution map of satellite receiving stations may specifically include three regions, each of which corresponds to a different score; similarly, the satellite usage constraint level distribution map may specifically include three regions, each of which corresponds to a Different scores; the regional climate characteristic distribution map can specifically include three regions, and each region corresponds to a different score.

Preferably, the points corresponding to A ₁ , A ₂ and A ₃ may be respectively: 3 points, 2 points and 1 point; the points corresponding to the B ₁ , B ₂ and B ₃ may be respectively: 3 points , 2 points and 1 point; the corresponding points of C ₁ , C ₂ and C ₃ may be: 3 points, 2 points and 1 point respectively.

In a preferred embodiment of the present invention, since the orbit height, data transmission antenna type (broadcast or spot beam type) and ground receiving resources of each satellite are different, the influence factor of satellite receiving station resources can be The specific analysis is carried out according to the characteristics of the satellite, and it is divided into three grades according to the acquisition from easy to difficult, and assigns A ₁ , A ₂ and A ₃ respectively.

Preferably, in this embodiment, the resource level distribution map of the satellite receiving station can be obtained through the following steps: dividing the global land area into a real transmission area, an alternate real transmission area and a recording imaging area according to the reception type of the ground station; _The real transmission area is determined as the A1 score distribution area; the alternate real transmission area is determined as the A2 score distribution area _; the recorded imaging area is determined as the A3 score distribution area.

Taking the Gaofen-1 and Gaofen-2 satellites as examples, the orbital altitudes of the Gaofen-1 and Gaofen-2 satellites are both 645 kilometers, and the data are received by four stations including Miyun Station, Kashi Station, Sanya Station and Mudanjiang Station Station receiving, each receiving station corresponds to a different receiving range. Further, since the data transmission antennas of the Gaofen-1 and Gaofen-2 satellites are of the spot beam type, that is, only one receiving station can receive data at the same time, and the single lap of the satellites cannot exceed 12 minutes. In actual operation, in order to ensure complete coverage in China, the mode of alternate real transmission and reception between Miyun Station and Sanya Station is usually adopted. For the territory of China, even if it is within the alternate reception range, the recording method is usually used to ensure timely coverage of the domestic area.

As shown in Table 1, it is a comparison table of each region and score level of a resource level distribution map of a satellite receiving station in an embodiment of the present invention.

Table 1

It can be seen that the actual transmission area may include: the area within China, the reception area of Kashi Station and the reception area of Mudanjiang Station; the alternate actual transmission area may include: the reception area of Miyun Station excluding China and the receiving area of Sanya Station The receiving range area outside the territory of China; the recording and imaging area may include: excluding the area within the territory of China, the receiving range area of the Kashi Station, the receiving range area of the Mudanjiang Station, the receiving range area of the Miyun Station except the territory of China, and the Sanya Station Other land areas other than the receiving area outside China.

In a preferred embodiment of the present invention, when scheduling and tasking the satellites, the usage constraints of the satellites must be strictly followed. In this embodiment, the satellite usage constraints that are mainly considered include: (1) the imaging duration of each lap of the satellite; (2) the fixed storage capacity on the satellite; (3) the satellite data download rate; (4) the daily imaging requirements of the satellite. It is divided into three grades from easy to difficult, and assigned B ₁ , B ₂ and B ₃ respectively. Among them, "daily imaging requirements of satellites" are non-mandatory constraints, which can be ignored in emergency situations. For China's land observation satellites, the daily imaging requirement is to meet the coverage of the area within China. Usually, the satellite needs to be imaged as long as it passes through the territory of China.

Preferably, in this embodiment, the satellite usage constraint level distribution map can be obtained through the following steps: according to at least one of the imaging duration of each lap of the satellite, the fixed storage capacity on the satellite, the download rate of the satellite data, and the daily imaging requirements of the satellite The global land area is divided into an easy area for data acquisition, a general area for data acquisition difficulty, and a difficult area for data acquisition _; the easy data acquisition area is determined as the B1 score distribution area; the data acquisition difficulty area is determined as B2 score distribution area _; the data acquisition difficulty area is determined as _B3 score distribution area.

As shown in Table 2, it is a comparison table of each area and score level of a distribution map of satellite usage constraint levels in an embodiment of the present invention.

Table 2

It can be seen that the easy data acquisition area may include: the imaging duration of each circle reaches the limit specified by the satellite, the fixed storage capacity on the satellite is sufficient, the data download is not occupied, and the coverage area that can be received by the receiving station that meets daily needs; the The areas with general difficulty in data acquisition may include: coverage areas that do not affect imaging in China and have a margin for fixed storage capacity onboard; the areas with difficulty in data acquisition may include: in addition to the areas with easy data acquisition and areas with general difficulty in data acquisition other land areas.

Take the Gaofen-1 satellite as an example

The imaging time of each round of the Gaofen-1 satellite is limited to 12 minutes; the fixed storage capacity on the satellite is 1Tb; the data download adopts dual channels, and the rate of each channel is 450Mbps, that is, the total download rate is 900Mbps. Combined with the objective usage constraints of the Gaofen-1 satellite and the satellite imaging requirements, the distribution of the influence factors of the satellite usage constraints of the Gaofen-1 satellite can be obtained.

B ₃ points, data acquisition difficulty area: the data download capability of the satellite cannot meet the real-time transmission of all cameras turned on at the same time, so when imaging in China, the method of 2m/8m data transmission and 16m data recording is usually adopted. . However, due to the limited storage capacity on the satellite (16-meter data can be stored for up to 18 minutes), other non-real transmission areas cannot be imaged before the total stored data is downloaded (unless the domestic 16-meter imaging is lost); At the same time, taking into account the imaging time limit of each lap of the satellite, it is also difficult to obtain data in the northern and southern regions adjacent to China.

B ₂ points, areas with general difficulty in data acquisition: areas that do not affect the needs of imaging in China, but also have sufficient on-board storage space for recording and imaging. When the satellite passes through the ground receiving station at night, after the 16-meter data recorded during the day in China is transmitted back, there is room to record other areas.

B ₁ point, easy data acquisition area: the area within China and the area that can be received by the receiving station.

In a preferred embodiment of the present invention, based on the Köppen climate classification method, the global land is divided into three grades according to the degree of climate dryness and the degree of cloud and snow coverage, and assigned values C ₁ , C ₂ and C ₃ respectively.

Preferably, in this embodiment, the regional climate characteristic distribution map can be obtained by the following steps: according to the Köppen climate classification, the global land area is divided into dry climate regions, moderately dry climate regions, and humid climate regions. The dry climate area is determined as a _C1 score distribution area; the moderately dry climate area is determined as a _C2 score distribution area _; the climate humid area is determined as a C3 score distribution area.

As shown in Table 3, it is a comparison table of each region and score level of a regional climate characteristic distribution map in an embodiment of the present invention.

table 3

It can be seen that the dry climate area can include: tropical savannah climate area, tropical and subtropical desert climate area, and tropical and subtropical grassland climate area; the climate medium dry area can include: tropical and subtropical monsoon climate area, tropical grassland climate area regions, various types of temperate climate regions, cold climate regions, and snow forest climate regions; the humid climate regions may include: tropical rain forest climate regions, polar tundra climate regions and polar ice sheet climate regions.

Step 102: Determine the distribution area of the single satellite in the satellite receiving station resource level distribution map, the satellite usage constraint level distribution map, and the regional climate characteristic distribution map according to the longitude and dimensional information of the single satellite, and obtain the corresponding area. 's score.

In this embodiment,

When it is determined according to the latitude and longitude information of the single satellite that the single satellite is located in the distribution area where the A _i score in the satellite receiving station resource level distribution diagram is located, the first score is A _i ; wherein , i=1, 2 or 3.

When it is determined according to the latitude and longitude information of the single satellite that the single satellite is located in the distribution area where the B _j score in the satellite usage constraint level distribution map is located, the second score is taken as B _j ; wherein, j=1, 2 or 3.

When it is determined according to the latitude and longitude information of the single satellite that the single satellite is located in the distribution area where the _Cm score in the regional climate characteristic distribution map is located, the third score is taken as _Cm ; wherein, m =1, 2 or 3.

For example, assuming that the longitude and latitude coordinates of a single satellite are determined to be (x, y) according to the longitude and latitude information of a single satellite, three factors corresponding to the satellite can be determined according to the longitude and latitude coordinates (x, y). What are the specific scores: if according to the latitude and longitude coordinates (x, y), it is determined that the satellite is located in the actual transmission area (satellite receiving station resource factor), the easy data acquisition area (satellite use constraint factor), and the dry climate area (regional climate characteristic factor), the factor scores corresponding to the satellite can be determined as: A ₁ , B ₁ and C ₁ respectively.

Step 103 , weighting and summing the acquired scores of the corresponding area to obtain the data acquisition capability of the single satellite.

In this embodiment, the data acquisition capability Φ of the single satellite = the first score + the second score + the third score. Taking the above-mentioned satellite with latitude and longitude coordinates (x, y), the data acquisition capability of the satellite is the sum of A ₁ , B ₁ and C ₁ .

In a preferred embodiment of the present invention, a method for evaluating the data acquisition capability of multiple satellites is also disclosed. Preferably, the method for evaluating the effective data acquisition capability of the remote sensing satellite may also include:

Step 104 , according to the data acquisition capability of the single satellite and the width of the single satellite, evaluate the data acquisition capability of multiple satellites.

In this embodiment, the specific steps for evaluating the data acquisition capability of multiple (n) satellites may be as follows:

In sub-step S1, the respective widths F _n corresponding to the n satellites are acquired, and the respective data acquisition capabilities Φ _n corresponding to the n satellites are obtained.

In this embodiment, according to the foregoing steps 101-103, the data acquisition capability Φ _n of each satellite can be obtained respectively, and the corresponding width F _n of each satellite can be obtained based on the characteristics of each satellite. Among them, F _n represents the width of the nth satellite, Φ _n represents the data acquisition capability of the nth satellite, and n≥2.

Sub-step S2, summing the widths of the n satellites to obtain the sum ΣF of the widths of the n satellites.

In sub-step S3, the weight of each satellite is allocated according to the respective widths of the satellites and the sum of the widths.

In this embodiment, the weight calculation method of each satellite is as follows:

Among them, Q _n represents the weight of the nth satellite.

In sub-step S4, the data acquisition capability Ψ of the n satellites is determined according to the data acquisition capability of each satellite and the weight of each satellite.

In this embodiment, the calculation formula of the data acquisition capability Ψ of n satellites is as follows:

Ψ=∑Q _n *Φ _n

Taking four satellites GF-1, GF-2, ZY-3 and ZY-1 02C with a resolution better than 2.5 meters as examples, as shown in Table 4, it is a satellite with a resolution better than 2.5 meters in the embodiment of the present invention Weight value assignment table.

satellite Width (km) Weights GF-1 70 0.30 GF-2 45 0.20 ZY-3 51 0.25 ZY-1 02C 54 0.25

Table 4

Then, the data acquisition capabilities of the above four satellites with a resolution better than 2.5 meters are:

_Ψ4 =0.30*Φ _GF-1 +0.20*Φ _GF-2 +0.25*Φ _ZY-3 +0.25*Φ _{ZY-1 02C}

To sum up, the method for evaluating the effective data acquisition capability of remote sensing satellites according to the present invention fully considers the satellite data acquisition capability by three factors, including satellite receiving station resources, satellite usage constraints, and regional climate characteristics, in addition to the capabilities of the satellite itself. Based on the influence of satellite receiving station resources, satellite usage constraints and regional climate characteristics, geospatial analysis was carried out to obtain a graded distribution map of the difficulty of satellite data acquisition on global land areas; The evaluation of satellite data acquisition ability improves the accuracy and objectivity of satellite data acquisition ability evaluation, and provides a reference for the mission planning of orbiting satellites.

Secondly, on the basis of evaluating the data acquisition ability of a single satellite, the present invention also realizes the evaluation of the data acquisition ability of multiple satellites based on the width corresponding to the satellite, which improves the ability of satellites, especially the joint globalization of multiple satellites. Effectively cover the efficiency of data, and provide a reference for users to understand the difficulty of global data acquisition.

The various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments, and the same and similar parts between the various embodiments may be referred to each other.

The above is only the best specific embodiment of the present invention, but the protection scope of the present invention is not limited to this. Substitutions should be covered within the protection scope of the present invention.

Contents that are not described in detail in the specification of the present invention belong to the well-known technology of those skilled in the art.

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 satellite_iWhen the distribution area of the score is located, taking the first score as A_i(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 satellite_jWhen the distribution area of the score is located, taking the second score as B_j(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 satellite_mWhen the distribution area of the score is located, taking the third score as C_m(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 A_i+B_j+C_m；

Obtaining the respective corresponding widths F of n satellites_nAnd, data acquisition capabilities Φ for each of the n satellites_n(ii) a Wherein, F_nDenotes the width, phi, of the nth satellite_nThe 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 is_nRepresenting 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＝∑Q_n*Φ_n。

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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