Multi-source remote sensing data-based lunar surface multi-scene construction suitability evaluation method

Abstract

The invention discloses a lunar surface multi-scene construction suitability evaluation method based on multi-source remote sensing data. The method comprises the following steps: S1, determining key environmental factors required by construction suitability evaluation; s2, extracting a value domain range of each single-factor data according to regional distribution, respectively calculating 80 percents and 20 percents as construction suitability grading thresholds, establishing normalization according to the thresholds, constructing a single-factor construction suitability index, and drawing a single-factor construction suitability index map; s3, constructing an analytic hierarchy process (AHP) weight matrix corresponding to the typical lunar surface base application scene; and S4, generating a multi-factor comprehensive construction suitability evaluation index of each scene based on the weight obtained in the S3. According to the method, through construction of a standardized single-factor construction suitability index system and weight assignment of an analytic hierarchy process, differentiation and comprehensive evaluation and site selection planning of six typical application scenes including a scientific research station, a residential area, a photovoltaic power generation area, a water source supply area, a traffic corridor and an airship landing point are realized.

Description

Technical Field

[0001] The present invention relates to the technical fields of space information processing and lunar base planning, and specifically to a lunar surface multi-scenario buildability assessment method based on multi-source remote sensing data, which is suitable for long-term, modular lunar habitat site selection and overall layout planning. Background Art

[0002] With humanity's growing demand for deep space exploration, the Moon, with its proximity to Earth, abundant in-situ resources, and relatively stable geological environment, has become a prime target for establishing a long-term lunar habitat. Existing lunar base site selection research primarily focuses on the layout of landing sites and short-term scientific research stations. Most applied methods rely on single or limited factor-driven evaluations, such as local optimization based on terrain slope, lighting conditions, or polar water ice distribution. While these studies have achieved some success in their respective application scenarios, they often overlook the interplay of multiple environmental factors that influence the development of long-term lunar habitats and lack a systematic, multi-scenario, multi-factor comprehensive evaluation framework.

[0003] Currently, some studies have attempted to introduce multi-factor decision-making algorithms, such as TOPSIS or the analytic hierarchy process (AHP), to initially overlay factors such as illumination, topography, and resources. However, most of these approaches remain limited to quantitative assessments of a few factors, specifically for research stations or spacecraft landing sites. For example, in the patent for a genetically intelligent lunar exploration site selection method and equipment (CN117669868A) that considers the exploration value index, researchers used a genetically intelligent algorithm to screen high-value exploration areas. However, no research has considered multiple typical application requirements, such as research stations, residential areas, photovoltaic power generation, water hubs, transportation corridors, and landing sites. Furthermore, existing methods often rely on a single remote sensing product for both data source and processing depth, lacking the coordinated use of multiple, high-resolution data sources, such as high-precision topography (Lunar Reconnaissance Orbiter LOLA), temperature (Chang'e-2 microwave radiometer), and element abundance (Chang'e-2 gamma-ray spectrometer). This results in insufficient assessment accuracy and applicability, making it difficult to provide reliable decision support for the realization of a long-term, sustainable lunar base.

[0004] Therefore, a systematic, multi-source data-fusion, multi-scenario, and multi-factor comprehensive suitability assessment method is urgently needed to construct a standardized suitability index system. Using the analytic hierarchy process (AHP), weighted values ​​are assigned to typical application scenarios, ultimately generating a high-precision, multi-functional lunar base site selection and layout plan. This method not only fully utilizes existing high-resolution remote sensing data but also accounts for the differentiated requirements of various environmental factors in different scenarios, providing scientific and feasible technical support for the engineering implementation of future permanent lunar habitats. Summary of the Invention

[0005] Purpose of the Invention: To overcome the shortcomings of existing technologies in lunar base site selection, which rely heavily on single factors, single scenarios, insufficient data sources, and low assessment accuracy, the present invention aims to provide a lunar surface multi-scenario suitability assessment method based on multi-source remote sensing data. This method constructs a standardized single-factor suitability index system and uses the Analytic Hierarchy Process (AHP) weight assignment method to achieve differentiated and comprehensive assessment and site selection planning for six typical application scenarios: scientific research stations, residential areas, photovoltaic power generation areas, water supply areas, transportation corridors, and spacecraft landing sites.

[0006] Technical solution: The lunar surface multi-scene suitability assessment method based on multi-source remote sensing data includes the following steps:

[0007] S1: Determine the key environmental factors required for buildability assessment, including temperature, topography, sunlight, building minerals, photovoltaic minerals, lunar dust activity, water resources, and radiation;

[0008] S2: Construction of single-factor buildability index: Extract the value range of each single-factor data according to regional distribution, calculate the threshold according to the standard classification, or calculate the 80th percentile and 20th percentile as the buildability classification threshold, and after normalization based on the threshold, construct the single-factor buildability index and draw the single-factor buildability index map;

[0009] S3: Construct an analytic hierarchy process (AHP) weight matrix corresponding to typical lunar base application scenarios and assign weights to each factor in different scenarios;

[0010] S4: Generate a multi-factor comprehensive suitability assessment index for each scenario based on the weights obtained in S3, identify highly suitable areas for a variety of typical scenarios, and conduct site selection planning for a multi-functional lunar base.

[0011] Furthermore, the temperature factor is considered: after correcting the brightness temperature data for time angle, a seventh-order polynomial fitting model is used to reconstruct the surface temperature at 48 equal parts of a lunar day. The proportion of time periods at each point within the human-tolerable temperature range (233K-313K) is calculated using the following formula:

[0012]

[0013] The temperature suitability index map for the whole month is generated according to the following formula: "≥24 period → TSI = 1; ≤16 period → TSI = 0; other periods are linearly interpolated". Figure 2 As shown, the calculation formula is as follows:

[0014]

[0015] Furthermore, terrain factors, including surface slope and roughness, were calculated using the median slope and the standard deviation of the slope within a ±0.1° window width of the LOLA laser ranging data under a 560m baseline. The suitability index was graded according to the standards of the International Geographical Union's Commission for Geomorphological Surveys and Cartography: when the slope is ≤5°, it is a highly suitable area and the SSI is assigned to 1; when the slope is between 5° and 15°, the SSI is calculated by linear interpolation; when the slope is >15°, the SSI is assigned to 0. When the roughness is ≤0.5, the RSI is assigned to 1; when it is between 0.5 and 1.5, the RSI is calculated by linear interpolation; when it exceeds 1.5, the RSI is assigned to 0.

[0016] The calculation formula is as follows:

[0017]

[0018] Among them, SSI is the slope suitability index, which takes values ​​from [0, 1]; S is the slope size at different points on the moon; RSI is the roughness suitability index, which takes values ​​from [0, 1]; R is the roughness size at different points on the moon.

[0019] Furthermore, before analyzing other factors such as illumination, construction minerals, photovoltaic minerals, lunar dust activity, water resources, radiation, and water resources, areas that simultaneously meet TSI=1, SSI=1, and RSI=1 are preferentially selected as basic habitable sites, and then these sites are subjected to a three-factor superposition analysis and base site optimization.

[0020] Furthermore, the illumination factor: Based on the terrain occlusion correction model, the maximum terrain elevation angle method is used to determine whether a point on the lunar surface can receive light radiation. The illumination model compares the sun vector with the terrain elevation angle to determine whether a point on the lunar surface is in shadow, and calculates the proportion of acceptable illumination frequency throughout the year. The high suitability threshold of the suitability index is defined as the corresponding index value being at or above the 80th percentile of its sample population, and the low suitability threshold is defined as the corresponding index value being at or below the 20th percentile.

[0021] The annual sunlight frequency ratio is calculated as follows:

[0022]

[0023] Where n is the total number of time periods calculated with a 3-hour resolution within the nutation cycle, I is the illumination rate, and α i The illumination ratio at each time resolution,

[0024] Calculate the extreme difference in illumination The 80% percentile and 20% values ​​are used as the appropriate standards for light distribution, and the range is calculated as follows:

[0025]

[0026] Generate a light suitability map using “≥80% percentile → ISI = 1; ≤20% percentile → ISI = 0”, as shown in the attached figure. Figure 6 As shown in (a), the calculation formula is as follows:

[0027] Furthermore, mineral factors: calculated by inverting the abundance of FeO and TiO2, where the high suitability threshold of the suitability index is defined as the corresponding index value being at the 80th percentile and above of its sample population, and the low suitability threshold is defined as the corresponding index value being at the 20th percentile and below.

[0028] Furthermore, the water resources: suitability index (WSI) is composed of three factors: ilmenite content distribution, silicon oxide content distribution and sunlight duration. The three sub-indices are averaged to obtain the WRSI.

[0029] Furthermore, the lunar dust activity factor is composed of two sub-indices: solar wind flux and lunar soil thickness. The solar wind suitability index and lunar soil thickness suitability index are established respectively. The high suitability threshold of the suitability index is defined as the corresponding index value is at or below the 20th percentile of its sample population, and the low suitability threshold is defined as the corresponding index value is at or above the 80th percentile. The two sub-indices are averaged to obtain the lunar dust activity suitability index DASI.

[0030] The calculation method is as follows:

[0031]

[0032]

[0033] Among them, SWSI is the solar wind flux distribution suitability index, DTSI is the lunar soil thickness distribution suitability index, SW is the solar wind flux, is the extreme difference of solar wind flux in this region, DT is the thickness of lunar soil, This is the extreme difference in lunar soil thickness in this area.

[0034] Furthermore, radiation factors, including neutron dose and gamma ray dose, are used to establish the Neutron Suitability Index and the Gamma Suitability Index. The high suitability threshold of the suitability index is defined as the corresponding index value being at the 20th percentile or below of its sample population, and the low suitability threshold is defined as the corresponding index value being at the 80th percentile or above. The radiation suitability index (RSI) is obtained by averaging the two sub-indices.

[0035] Furthermore, the AHP weight matrix was constructed and the comprehensive index was calculated: the Saaty 1-7 scaling method was used to construct an 8×8 pairwise comparison matrix, and the obtained weight vector was applied to the eight single-factor indices of each basic habitable point, and the multi-scenario comprehensive habitability index (MSI) was calculated by weighted superposition.

[0036] First, construct a multi-source remote sensing single factor suitability index system

[0037] S1. Identify eight key environmental factors: temperature, topography (slope and roughness), sunlight, architectural minerals (FeO, TiO2), photovoltaic minerals (SiO2), lunar dust activity (solar wind flux, lunar soil thickness), water resources (ilmenite abundance), and radiation (neutron dose, gamma-ray dose).

[0038] S2. Quantitatively invert or estimate the above factors based on multi-source remote sensing data, including LOLA laser altimetry, Chang'e-2 microwave radiometer, and gamma-ray spectrometer, to obtain single-factor original datasets.

[0039] S3. Extract the regional value range for each factor, define high / low suitability thresholds based on the 80% and 20% quantiles of the sample population, and construct a single-factor suitability index map based on normalization;

[0040] A multi-scenario comprehensive suitability index calculation method based on AHP is proposed.

[0041] S4. For the six application scenarios (research stations, residential areas, photovoltaic areas, water supply areas, and transportation routes and landing points), we constructed an 8×8 pairwise comparison judgment matrix using the Saaty 1-7 scale based on the degree of impact of each environmental factor on engineering and daily life in each scenario. We then performed a consistency test to determine the weights of each factor.

[0042] S5. Calculate the multi-scenario comprehensive suitability index (MSI) by weighting the eight single-factor suitability indices for each location with the corresponding scenario weights. Then, on the same lunar map, select the cluster of locations with the highest suitability for each scenario and identify optimal areas covering five to six scenarios.

[0043] S6. Based on the above-mentioned preferred areas and combined with factors such as terrain, resources, and transportation, a general layout plan for a multifunctional lunar base is proposed with the flat area in the central part of the Sea of ​​Knowledge as the core, to achieve the organic coupling and safe isolation of functional areas such as scientific research, residence, energy, water resources, and transportation.

[0044] The present invention's lunar surface multi-scenario suitability assessment method, based on multi-source remote sensing data, includes two core elements: the first is the construction and standardization of a "multi-factor suitability assessment index system." This includes: Based on the requirements for lunar base construction, eight key suitability factors are proposed: temperature, topography, illumination, building minerals, photovoltaic minerals, lunar dust activity, water resources, and radiation. Suitability indices are constructed for each individual factor using data sources such as LOLA and the Chang'e-2 microwave radiometer and gamma-ray spectrometer. The index system is normalized by setting 80th and 20th percentile thresholds, and spatial distribution maps of each factor are plotted. The second element is the proposed calculation method for a "multi-scenario comprehensive suitability index based on the analytic hierarchy process." It includes: combining six typical application scenarios on the moon (scientific research stations, residential areas, photovoltaic areas, water supply areas, transportation routes and spacecraft landing points) to construct an 8×8 comparative judgment matrix; weighting each factor according to its importance level to different scenarios to construct a comprehensive suitability index distribution map; identifying high-suitability areas, and proposing a layout suggestion for a multi-functional lunar base with the central part of the Sea of ​​Knowledge as the core, to achieve systematic planning for future sustainable lunar habitation space.

[0045] Compared with the prior art, the present invention has the following beneficial effects:

[0046] 1. Multi-source high-resolution data fusion: Utilizing multi-source remote sensing products such as LOLA, the Chang'e-2 microwave radiometer, and the gamma-ray spectrometer, the data achieves quantification of the suitability of eight environmental factors.

[0047] 2. Standardized indicator system: A unified normalization technique is used to construct a single-factor suitability index, which makes different indices highly comparable and scalable;

[0048] 3. Multi-scenario differentiated assessment: Combining six typical application scenarios, the AHP weight assignment enables accurate assessment of scientific research stations, residential areas, photovoltaic areas, water source areas, transportation routes, and landing points;

[0049] 4. Systematic Site Selection and Planning: Based on the preferred areas identified by the multi-scenario comprehensive buildability index, a systematic, modular, and scalable lunar base spatial layout plan was proposed, providing reliable decision-making support for the engineering implementation of future permanent lunar habitats. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] Figure 1 It is a schematic diagram of the process of this method;

[0051] Figure 2 It is a global temperature suitability map of the Moon;

[0052] Figure 3 (a) Global distribution map of slope suitability index, (b) Global distribution map of roughness suitability index, (c) Distribution map of terrain suitability index;

[0053] Figure 4 This is a distribution map of 3001 suitable construction sites based on terrain suitability and temperature suitability;

[0054] Figure 5 It is a schematic diagram for calculating whether a certain point on the lunar surface can receive sunlight;

[0055] Figure 6 These are single-factor suitability maps: (a) is the light suitability distribution map, (b) is the construction mineral suitability distribution map, (c) is the photovoltaic mineral suitability distribution map, (d) is the lunar dust activity suitability distribution map, (e) is the water resource suitability distribution map, and (f) is the radiation suitability distribution map.

[0056] Figure 7 This is a multi-factor suitability map, (a) is the residential area scenario suitability distribution map, (b) is the scientific research station scenario suitability distribution map, (c) is the landing scenario suitability distribution map, (d) is the photovoltaic power generation area scenario suitability distribution map, (e) is the core water supply scenario suitability distribution map, and (f) is the transportation scenario suitability distribution map.

[0057] Figure 8 It is a comprehensive adaptability map covering multiple scenarios and multiple factors. DETAILED DESCRIPTION

[0058] The following is a clear and complete description of the technical solutions in the embodiments of the present invention, in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0059] In order to more clearly and easily demonstrate the embodiments of the present invention, the present invention selects the lunar environment as an example to describe the embodiments. This celestial body is relatively close to the earth, rich in mineral resources, and has multiple sets of mature remote sensing monitoring data. The following is combined with the data processing and site selection process of the lunar environment, as shown in the attached figure. Figure 1 , step by step, the various technical steps of this embodiment are explained:

[0060] S1. Key Environmental Factor Screening and Data Acquisition: Based on the needs of lunar base construction and long-term human life, eight key suitability factors were identified: temperature, topography (slope and roughness), illumination, construction minerals (FeO and TiO2), photovoltaic minerals (SiO2), lunar dust activity (water and soil thickness and solar wind flux), water resources (ilmenite volume fraction and light exposure), and radiation (annual neutron and gamma-ray dose). Multi-source remote sensing and simulation data, including LRO / LOLA laser altimetry data, Chang'e-2 microwave radiometer brightness temperature data, Chang'e-2 gamma-ray spectrometer data, terrain shadow models, and mineral inversion models, were used to prepare for subsequent index construction.

[0061] S2. Construction of single-factor suitability index

[0062] S21. Temperature factors:

[0063] Based on brightness temperature data obtained by the Chang'e-2 microwave radiometer at multiple frequency channels (3.0, 7.8, 19.35, and 37.0 GHz), the brightness temperature distribution at each moment of a lunar day was obtained through time-angle conversion and seventh-order polynomial fitting. The proportion of time within a lunar day at a temperature suitable for human habitation was determined. The temperature factor classification standard is based on the proportion of temperature periods that are tolerable to humans in the lunar diurnal cycle: if a region has a suitable temperature period for more than half of the lunar day (i.e., no less than 24 out of 48 equal time points), the region is assigned a Temperature Suitability Index (TSI) of 1; if the suitable temperature period accounts for less than 16 out of 48 periods (equivalent to 8 hours in a day on Earth), the region is assigned a TSI of 0; in other cases, the TSI is calculated by linear interpolation.

[0064] After correcting the brightness temperature for the time angle, a seventh-order polynomial fitting model was used to reconstruct the surface temperature at 48 equal parts of a lunar day. The proportion of time periods at each point within the human-tolerable temperature range (233K-313K) was calculated using the following formula:

[0065]

[0066] The temperature suitability index map for the whole month is generated according to the following formula: "≥24 period → TSI = 1; ≤16 period → TSI = 0; other periods are linearly interpolated". Figure 2 As shown, the calculation formula is as follows:

[0067]

[0068] S22. For terrain factors: Calculate the slope (median slope of the 560m baseline) and roughness (±0.1° window slope standard deviation) using LOLA data. Generate SSI and RSI maps according to the following rules: "slope ≤ 5° → SSI = 1; > 15° → SSI = 0, and other linear interpolation" and "roughness ≤ 0.5 → RSI = 1; > 1.5 → RSI = 0, and other linear interpolation." Figure 3 (a), 3(b) are calculated as follows:

[0069]

[0070] Among them, SSI is the slope suitability index, which takes values ​​from [0, 1]; S is the slope size at different points on the moon; RSI is the roughness suitability index, which takes values ​​from [0, 1]; R is the roughness size at different points on the moon.

[0071] The comprehensive terrain suitability analysis is based on the slope suitability index and the roughness suitability index. Since the latitude and longitude corresponding to the two are different in accuracy, the results of aligning the longitude and longitude are averaged to obtain TrSI, and a terrain suitability map is drawn, as shown in the attached figure. Figure 3 (c) is shown in the figure, and the calculation formula is as follows:

[0072]

[0073] S23. Pre-screening of basic suitable construction points: Screen the grid cells that meet TSI=1, SSI=1, and RSI=1 on the example celestial body to obtain the basic suitable construction candidate point set, and draw the distribution map of the 3001 selected suitable construction points, as shown in the attached figure. Figure 4 As shown, it serves as the input subset for subsequent multi-factor superposition and AHP calculation.

[0074] S24. Regarding illumination factors: Based on the terrain occlusion correction model, the maximum terrain elevation angle method is used to determine whether a lunar point can receive illumination radiation. The illumination model compares the sun vector with the terrain elevation angle to determine whether a point on the lunar surface is in shadow, and calculates the proportion of acceptable illumination frequency throughout the year. The high suitability threshold of the suitability index is defined as the corresponding index value being at the 80th percentile or above of its sample population, and the low suitability threshold is defined as the corresponding index value being at the 20th percentile or below.

[0075] This case study integrates the SPICE (Spacecraft Planet Instrument Camera-matrix Events) celestial positioning framework with a terrain shading analysis algorithm to establish a high-precision spatiotemporal distribution model of illumination in the J2000 inertial coordinate system. The calculation covers one complete nutation cycle (2015 / 01 / 01-2033 / 08 / 08) with a time resolution of 3 hours. Points with a solar incidence angle of less than or equal to 0 are initially screened out and no longer participate in the comparison calculation. When the solar incidence angle is greater than 0, the maximum terrain altitude angle method is used to determine whether there is direct sunlight every 3 hours, as shown in the attached figure. Figure 5 Taking point M as an example, calculate whether the angle between the vector of the line connecting point M and points with an accuracy of 0.1° within a 5° range with point M as the center point and the vector of the line connecting point M and the sun is 0. If the angle is 0, calculate the terrain elevation angle of point M and the 49 points in the direction of the line. If the solar incidence azimuth of point M is greater than the maximum obstruction elevation angle in the terrain elevation angle, then point M can receive sunlight. Otherwise, there is no sunlight. The annual sunlight frequency ratio is calculated as follows:

[0076]

[0077] Where n is the total number of time periods calculated with a 3-hour resolution within the nutation cycle, I is the illumination rate, and α i Illumination ratio at each temporal resolution.

[0078] Calculate the extreme difference in illumination The 80% percentile and 20% values ​​are used as the appropriate standards for light distribution, and the range is calculated as follows:

[0079]

[0080] Generate a light suitability map using “≥80% percentile → ISI = 1; ≤20% percentile → ISI = 0”, as shown in the attached figure. Figure 6 As shown in (a), the calculation formula is as follows:

[0081]

[0082] S25. For mineral factors: calculate the abundance through the FeO and TiO2 inversion models respectively, set the IASI and TASI high and low thresholds according to the 80% and 20% quantiles of their respective sample ranges, and use the calculation method similar to S24 to synthesize IASI and TASI into MDSI by averaging, and use the calculation method similar to S22 to generate the mineral suitability map, as shown in the attached figure. Figure 6 (b) shown.

[0083] S26. Photovoltaic mineral factors: This case is based on the abundance distribution data of silicon dioxide obtained by inversion of existing studies. The SOSI high and low thresholds are set according to the 80% and 20% quantiles of the sample range. The calculation method is similar to S24 to generate a photovoltaic mineral suitability map, as shown in the attached figure. Figure 6 (c) shown.

[0084] S27. Lunar dust activity factor: It is composed of two sub-indices, solar wind flux and lunar soil thickness. The solar wind suitability index and lunar soil thickness suitability index are established respectively. The high suitability threshold of the suitability index is defined as the corresponding index value is at the 20th percentile or below of its sample population, and the low suitability threshold is defined as the corresponding index value is at the 80th percentile or above. The two sub-indices are averaged to obtain the lunar dust activity suitability index DASI.

[0085] The solar wind flux and regolith thickness in the region are calculated. The solar wind flux distribution suitability index and lunar regolith thickness distribution suitability index are constructed according to the principle of "≤20% percentile → SWSI / DTSI = 1; ≥80% percentile → = 0". The calculation method is as follows:

[0086]

[0087] Among them, SWSI is the solar wind flux distribution suitability index, DTSI is the lunar soil thickness distribution suitability index, SW is the solar wind flux, is the extreme difference of solar wind flux in this region, DT is the thickness of lunar soil, This is the extreme difference in lunar soil thickness in this area.

[0088] Based on the above analysis, this case developed the Dust Activity Suitability Index (DASI), averaged the SWSI and DTSI, and calculated the DASI map similar to S22. Figure 6 (d) shown.

[0089] S28. Water resource factors: This case is based on the volume percentage distribution of ilmenite on the lunar surface obtained by inversion of existing research. The ilmenite suitability index (ILMSI) is obtained by the calculation method of S24. The WRSI is generated by averaging the ISI obtained by S24 and the SOSI obtained by S26. The calculation method is similar to S22, and a water resource suitability map is drawn, as shown in the attached figure. Figure 6 (e) shown.

[0090] S29. For radiation factors, including neutron dose and gamma ray dose, a Neutron Suitability Index and a Gamma Suitability Index are established. The high suitability threshold of the suitability index is defined as the corresponding index value being at or below the 20th percentile of the sample population, and the low suitability threshold is defined as the corresponding index value being at or above the 80th percentile. The two sub-indices are averaged to obtain the Radiation Suitability Index (RSI). Using the annual neutron and gamma ray doses obtained from existing studies, the NSI and GSI are generated according to the principle of "≤20% percentile → NSI / GSI = 1; ≥80% percentile → = 0", and the RSI is obtained by averaging. The calculation method is similar to S22, and a radiation suitability map is drawn, as shown in the attached figure. Figure 6 (f) shown.

[0091] S3. Construction of AHP weight matrix and calculation of comprehensive index:

[0092] S31. For the six typical application scenarios (scientific research stations, residential areas, photovoltaic areas, water supply areas, transportation route planning areas, and landing points), the factor importance levels (level 1 to level 4) were set respectively, and the Saaty 1-7 scaling method was used to construct an 8×8 pairwise comparison matrix, which was then tested for consistency.

[0093] S32. Apply the obtained weight vector to the eight single-factor indices of each basic habitable point, calculate the multi-scenario comprehensive suitability index (MSI) by weighted superposition, and draw the comprehensive suitability distribution on the example celestial body, as shown in the attached figure. Figure 7 shown.

[0094] S4. Identification and planning layout of high-rise construction areas:

[0095] S41. Sort by MSI from high to low, extract the top 100 candidate points for each scene, and overlay the six scene hot spots, as shown in the attached figure. Figure 8 As shown, an area that meets the needs of multiple scenarios is identified, with the central part of Zhihai (approximately -27°E~-21°E, -13°N~-7°N) as the core.

[0096] S42. Based on the identification results and combined with transportation routes, functional zones such as scientific research, housing, energy, water resources, transportation, and landing are planned to form a multifunctional lunar base spatial layout to meet sustainable living needs.

[0097] In this specification, the terms "embodiment", "case" or "taking ... as an example" are only used to illustrate specific features, structures, materials or functions, and the examples are not necessarily the same. The features can be flexibly combined in one or more embodiments. The above content only illustrates the basic principles and advantages of the present invention and is not limited to the illustrated embodiments. Technicians can make various equivalent changes and improvements to the embodiments without departing from the spirit and scope of the present invention, and these changes should fall within the scope of protection of the present invention.

[0098] The above description is merely a preferred embodiment of the present invention and does not limit the present invention in any way. Any person skilled in the art who, without departing from the scope of the present invention, makes any equivalent substitution, modification, or other changes to the technical solution and technical content disclosed in the present invention shall be deemed to be within the scope of the present invention and still fall within the scope of protection of the present invention.

Claims

1. A lunar surface multi-scene suitability assessment method based on multi-source remote sensing data, characterized by: The steps include: S1: Determine the key environmental factors required for buildability assessment, including temperature, topography, sunlight, building minerals, photovoltaic minerals, lunar dust activity, water resources, and radiation; S2: Construction of single-factor buildability index: For data without specific regulations, the threshold values ​​of each single-factor data are classified according to the standard, or the range of the value range is extracted according to the regional distribution. The 80th and 20th percentiles are calculated as the buildability classification thresholds, and after normalization based on the threshold values, the single-factor buildability index is constructed and a single-factor buildability index map is drawn. S3: Construct an analytic hierarchy process (AHP) weight matrix corresponding to typical lunar base application scenarios, and assign weights based on the impact of various factors on production and life in different scenarios; S4: Generate a multi-factor comprehensive suitability assessment index for each scenario based on the weights obtained in S3, identify highly suitable areas for a variety of typical scenarios, and conduct site selection planning for a multi-functional lunar base.

2. The lunar surface multi-scene suitability assessment method based on multi-source remote sensing data according to claim 1 is characterized in that: Temperature factor: After correcting the brightness temperature data for time angle, a seventh-order polynomial fitting model is used to reconstruct the surface temperature at 48 equal parts of a lunar day. The proportion of time at each point within the human-tolerable temperature range (233K-313K) is calculated using the following formula: The temperature suitability index map for the entire month is generated according to the following formula: "≥24 period → TSI = 1; ≤16 period → TSI = 0; other periods are linearly interpolated", as shown in Figure 2. The calculation formula is as follows:

3. The lunar surface multi-scene suitability assessment method based on multi-source remote sensing data according to claim 1 is characterized in that: Topographic factors: including surface slope and roughness, which are calculated by the median slope of LOLA laser ranging data under a 560m baseline and the standard deviation of the slope within a ±0.1° window width. The suitability index is graded according to the standards of the International Geographical Union's Commission for Geomorphological Survey and Cartography: when the slope is ≤5°, it is a highly suitable area and the SSI is assigned to 1; when the slope is between 5° and 15°, the SSI is calculated by linear interpolation; when the slope is >15°, the SSI is assigned to 0. When the roughness is ≤0.5, the RSI is assigned to 1; when it is between 0.5 and 1.5, the RSI is calculated by linear interpolation; when it exceeds 1.5, the RSI is assigned to 0. The calculation formula is as follows: Among them, SSI is the slope suitability index, which takes values ​​from [0, 1]; S is the slope size at different points on the moon; RSI is the roughness suitability index, which takes values ​​from [0, 1]; R is the roughness size at different points on the moon.

4. The lunar surface multi-scene suitability assessment method based on multi-source remote sensing data according to claim 1 is characterized in that: Before analyzing illumination, construction minerals, photovoltaic minerals, lunar dust activity, water resources, radiation, and water resources, areas that simultaneously meet TSI=1, SSI=1, and RSI=1 are prioritized as basic habitable sites, and then these sites are subjected to a three-factor superposition analysis and base site optimization.

5. The lunar surface multi-scene suitability assessment method based on multi-source remote sensing data according to claim 4 is characterized in that: Lighting factors: Based on the terrain occlusion correction model, the maximum terrain elevation angle method is used to determine whether a lunar point can receive light radiation. The lighting model compares the sun vector with the terrain elevation angle to determine whether a point on the lunar surface is in shadow and calculates the proportion of acceptable light frequency throughout the year. The high suitability threshold of the suitability index is defined as the corresponding index value being at or above the 80th percentile of its sample population, and the low suitability threshold is defined as the corresponding index value being at or below the 20th percentile. The annual sunlight frequency ratio is calculated as follows: Where n is the total number of time periods calculated with a 3-hour resolution within the nutation cycle, I is the illumination rate, and α i The illumination ratio at each time resolution, Calculate the extreme difference in illumination The 80% percentile and 20% values ​​are used as the appropriate standards for light distribution, and the range is calculated as follows: Generate a light suitability map using "≥80% percentile → ISI = 1; ≤20% percentile → ISI = 0" as shown in the attached figure.

6. The lunar surface multi-scene suitability assessment method based on multi-source remote sensing data according to claim 4 is characterized in that: Mineral factors: calculated by inverting the abundance of FeO and TiO2, where the high suitability threshold of the suitability index is defined as the corresponding index value being at the 80th percentile or above of its sample population, and the low suitability threshold is defined as the corresponding index value being at the 20th percentile or below.

7. The lunar surface multi-scene suitability assessment method based on multi-source remote sensing data according to claim 4 is characterized in that: Water resources: The Buildability Index (WSI) is composed of three factors: ilmenite content distribution, silicon oxide content distribution, and sunlight duration. The WRSI is obtained by averaging the three sub-indices.

8. The lunar surface multi-scene suitability assessment method based on multi-source remote sensing data according to claim 4 is characterized in that: Lunar dust activity factor: It is composed of two sub-indices, solar wind flux and lunar soil thickness. The solar wind suitability index and lunar soil thickness suitability index are established respectively. The high suitability threshold of the suitability index is defined as the corresponding index value is at or below the 20th percentile of its sample population, and the low suitability threshold is defined as the corresponding index value is at or above the 80th percentile. The two sub-indices are averaged to obtain the lunar dust activity suitability index DASI. The calculation method is as follows: Among them, SWSI is the solar wind flux distribution suitability index, DTSI is the lunar soil thickness distribution suitability index, SW is the solar wind flux, is the extreme difference of solar wind flux in this region, DT is the thickness of lunar soil, This is the extreme difference in lunar soil thickness in this area.

9. The lunar surface multi-scene suitability assessment method based on multi-source remote sensing data according to claim 4 is characterized in that: Radiation factors: including neutron dose and gamma ray dose, the Neutron Suitability Index and Gamma Suitability Index were established. The high suitability threshold of the suitability index is defined as the corresponding index value being at the 20th percentile or below of its sample population, and the low suitability threshold is defined as the corresponding index value being at the 80th percentile or above. The radiation suitability index (RSI) is obtained by averaging the two sub-indices.

10. The lunar surface multi-scene suitability assessment method based on multi-source remote sensing data according to claim 1 is characterized in that: Construction of AHP weight matrix and calculation of comprehensive index: The Saaty 1-7 scaling method was used to construct an 8×8 pairwise comparison matrix. The obtained weight vector was applied to the eight single-factor indices of each basic habitable point, and the multi-scenario comprehensive suitability index (MSI) was calculated by weighted superposition.

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