Multi-spectral remote sensing driven site style and appearance evaluation system adopting unmanned aerial vehicle

Abstract

The invention relates to the field of site style and appearance evaluation systems driven by multi-spectral remote sensing adopting unmanned aerial vehicles, in particular to a site style and appearance evaluation system driven by multi-spectral remote sensing adopting unmanned aerial vehicles, which comprises a multi-spectral data acquisition module, a site feature extraction module, a style and appearance evaluation module and an evaluation result visualization module, the multispectral data acquisition module is used for carrying out multispectral data acquisition on a site according to a preset flight path and parameters by utilizing an unmanned aerial vehicle to carry a multispectral sensor, acquiring multispectral image data of the site, and deepening the fusion of the multispectral data and site style and appearance evaluation; the site feature extraction module is used for extracting the vegetation coverage and the land utilization type of the site from the multispectral image data by utilizing a linkage mode of an image processing algorithm and a machine learning algorithm; according to the system, the site style and appearance evaluation efficiency is remarkably improved through automatic feature extraction and analysis processes. The flexibility and rapid deployment capability of the unmanned aerial vehicle enable data acquisition to be more flexible.

Description

Technical Field

[0001] The present invention relates to the field of site landscape evaluation systems driven by multispectral remote sensing using unmanned aerial vehicles (UAVs), and in particular to a site landscape evaluation system driven by multispectral remote sensing using unmanned aerial vehicles (UAVs). Background Art

[0002] The Site Landscape Assessment System utilizes advanced technology and scientific methods to comprehensively evaluate a site's vegetation cover, land use type, topography, and other characteristics. Its purpose is to provide decision-making support for site planning, ecological protection, and landscape design through scientific evaluation methods.

[0003] Traditional site assessment often relies on ground surveys and satellite remote sensing data for data collection. However, ground surveys are time-consuming and labor-intensive, and they struggle to cover large areas. Satellite remote sensing data, while offering wide coverage, has limited resolution and a long acquisition cycle. Furthermore, traditional assessment methods often rely on empirical judgment and lack systematic real-time monitoring and scientific evaluation methods. In recent years, the rapid development of drone technology has opened up new possibilities for site assessment. Drones equipped with multispectral sensors can efficiently acquire multispectral image data of a site, offering advantages such as high resolution, real-time performance, and flexibility. Multispectral remote sensing technology can capture spectral information across different wavelengths, thereby more accurately reflecting site characteristics such as vegetation health, land use type, and topography.

[0004] Therefore, to address the above problems, a site landscape evaluation system driven by multispectral remote sensing using UAVs is proposed. Summary of the Invention

[0005] To address the shortcomings of existing technologies, this paper proposes a site landscape assessment system driven by multispectral remote sensing using drones. This system uses drones equipped with multispectral sensors to collect high-resolution, real-time multispectral data on sites. It then uses advanced image processing and machine learning algorithms to extract site features. This system then combines an ecological aesthetics index system with a comprehensive evaluation model to scientifically assess site landscape. Finally, the evaluation results are intuitively displayed using a geographic information system (GIS) and three-dimensional visualization technology, providing strong support for site planning and ecological protection.

[0006] The present invention solves the technical problem by adopting the following technical solution: a site landscape evaluation system driven by multispectral remote sensing using an unmanned aerial vehicle (UAV) comprises a multispectral data acquisition module, a site feature extraction module, a landscape evaluation module, and an evaluation result visualization module. The multispectral data acquisition module utilizes a multispectral sensor mounted on an UAV to collect multispectral data of a site according to a preset flight path and parameters, obtains multispectral image data of the site, and deepens the integration of multispectral data with site landscape evaluation. The site feature extraction module utilizes an "image processing algorithm + machine learning algorithm" linkage mode to extract site features such as vegetation coverage, land use type, and topography from the multispectral image data, and deepens the integration of site feature extraction and multispectral data analysis. The landscape evaluation module utilizes an "ecological aesthetics index system + comprehensive evaluation model" linkage mode to comprehensively evaluate the site landscape based on the extracted site features, and deepens the integration of landscape evaluation and site feature analysis. The evaluation result visualization module utilizes a "geographic information system (GIS) + three-dimensional visualization technology" linkage mode to display the evaluation results in an intuitive visual form, and deepens the integration of evaluation result presentation and user decision support.

[0007] Preferably, the multispectral data acquisition module includes a UAV flight control submodule and a multispectral sensor data acquisition submodule.

[0008] Preferably, the UAV flight control submodule includes flight path planning, flight attitude control and flight status monitoring.

[0009] Preferably, the multispectral sensor data acquisition submodule includes spectral band selection, image resolution setting and data storage management.

[0010] Preferably, the site feature extraction module includes vegetation coverage extraction, land use type identification and topography analysis.

[0011] Preferably, the style evaluation module includes the construction of an ecological aesthetic index system and the application of a comprehensive evaluation model.

[0012] Preferably, the evaluation result visualization module includes geographic information system display and three-dimensional visualization rendering.

[0013] Preferably, the ecological aesthetic index system is constructed including vegetation health index, landscape diversity index and site overall coordination index.

[0014] Preferably, the application of the comprehensive evaluation model includes weight distribution optimization and evaluation result calibration.

[0015] Preferably, the evaluation result visualization module also includes an evaluation report generation and export module, which is used to generate a detailed evaluation report based on the evaluation results and support export in multiple formats to facilitate users to further analyze and make decisions.

[0016] The present invention is beneficial in that:

[0017] 1. A site landscape assessment system powered by multispectral remote sensing using drones demonstrates significant benefits in multiple areas, thanks to its unique technical advantages and application value. First, the system utilizes drone-mounted multispectral sensors to acquire real-time, high-resolution multispectral imagery of sites. This data not only includes key information such as vegetation cover, land use type, and topography, but is also highly accurate and comprehensive, providing a solid foundation for site landscape assessment. Second, the system significantly improves the efficiency of site landscape assessment through automated feature extraction and analysis processes. The flexibility and rapid deployment of drones enhance data collection flexibility, enabling rapid response to site changes and timely data updates, thereby reducing the need for manual operations and costs while improving the speed and cost-effectiveness of the assessment process. Furthermore, the system, incorporating an ecological aesthetic indicator system and a comprehensive evaluation model, provides scientific evaluation results, providing strong decision-making support for site planning, ecological protection, and landscape design. Leveraging GIS and 3D visualization technologies, the evaluation results can be intuitively presented to decision makers and stakeholders, facilitating understanding and communication, and enhancing transparency and participation in decision-making. To enhance emergency response capabilities, the system can issue timely alerts before risks occur, giving managers ample time to take action and mitigate losses. Through precise analysis of vegetation cover and land use types, the system helps monitor and assess ecosystem health, providing a scientific basis for ecological protection. The system also uses expert systems and dynamic simulation technology to scientifically assess construction safety and provide optimization recommendations, providing strong support for construction safety management. By establishing a safety indicator system, it comprehensively assesses construction safety and, based on the assessment results, proposes reasonable optimization recommendations for construction plans, improving construction safety and efficiency. The emergency plan development and drill module develops targeted emergency plans based on risk assessment results and conducts drills, further enhancing construction safety management. Through drills, construction personnel familiarize themselves with emergency response procedures, improving their response speed and coordination, and ensuring a swift and effective response when emergencies occur. Another significant advantage of the system is its strong environmental adaptability. The drone can operate in a variety of complex environments, including hard-to-reach areas, enhancing the system's adaptability and enabling landscape assessments under diverse site conditions. At the same time, the application of this system has promoted the development of drone-based multispectral remote sensing technology, providing new tools and methods for research in related fields and promoting scientific progress. Finally, compared to traditional ground-based survey methods, drone-based remote sensing technology has a lower environmental impact and is a more environmentally friendly method for data collection. This not only helps reduce environmental impact but also aligns with the concept of sustainable development, providing an innovative solution for environmental protection and resource management.In summary, the site landscape evaluation system driven by multispectral remote sensing using drones has significant advantages in improving evaluation accuracy, efficiency, and scientificity. It also provides strong technical support for ecological protection and environmental management, and is an important innovation in the field of site landscape evaluation. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0019] Figure 1 This is a schematic diagram of the framework structure of the site landscape evaluation system driven by multispectral remote sensing using an unmanned aerial vehicle (UAV).

[0020] 1. Multispectral data acquisition module; 101. UAV flight control submodule; 102. Multispectral sensor data acquisition submodule; 2. Site feature extraction module; 201. Vegetation coverage extraction; 202. Land use type identification; 203. Topography and landform analysis; 3. Landscape evaluation module; 301. Construction of ecological aesthetics indicator system; 302. Application of comprehensive evaluation model; 4. Evaluation result visualization module; 401. Geographic information system display; 402. Three-dimensional visualization rendering. DETAILED DESCRIPTION

[0021] The following will clearly and completely describe 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.

[0022] Example 1

[0023] See also Figure 1 As shown, a site landscape evaluation system driven by multispectral remote sensing using an unmanned aerial vehicle comprises a multispectral data acquisition module 1, a site feature extraction module 2, a landscape evaluation module 3, and an evaluation result visualization module 4;

[0024] Multispectral data acquisition module 1 uses a multispectral sensor equipped with an unmanned aerial vehicle to collect multispectral data of the site according to the preset flight path and parameters, obtains multispectral image data of the site, and deepens the integration of multispectral data and site style evaluation; site feature extraction module 2 uses the "image processing algorithm + machine learning algorithm" linkage mode to extract the site's vegetation coverage, land use type, topography and other features from the multispectral image data, and deepens the integration of site feature extraction and multispectral data analysis; style evaluation module 3 uses the "ecological aesthetic index system + comprehensive evaluation model" linkage mode to conduct a comprehensive evaluation of the site style based on the extracted site features, and deepens the integration of style evaluation and site feature analysis; evaluation result visualization module 4 uses the "geographic information system GIS + three-dimensional visualization technology" linkage mode to display the evaluation results in an intuitive visual form, and deepens the integration of evaluation result presentation and user decision support.

[0025] Furthermore, the multispectral data acquisition module 1 includes a UAV flight control submodule 101 and a multispectral sensor data acquisition submodule 102 .

[0026] Furthermore, the UAV flight control submodule 101 includes flight path planning, flight attitude control and flight status monitoring.

[0027] Furthermore, the multispectral sensor data acquisition submodule 102 includes spectral band selection, image resolution setting, and data storage management. The multispectral data acquisition module 1 utilizes a drone equipped with a multispectral sensor to collect multispectral data of the site according to a preset flight path and parameters, obtaining multispectral image data of the site and deepening the integration of multispectral data with site landscape assessment. This process involves the drone flight control submodule 101 and the multispectral sensor data acquisition submodule 102. The drone flight control submodule 101 includes flight path planning, flight attitude control, and flight status monitoring, ensuring that the drone flies along the predetermined trajectory while maintaining a stable attitude and timely status feedback, thereby ensuring accurate and reliable data collection. The multispectral sensor data acquisition submodule 102 includes spectral band selection, image resolution setting, and data storage management. These functions ensure that the collected data meets various analysis requirements and can be efficiently stored and processed.

[0028] Furthermore, site feature extraction module 2 includes vegetation coverage extraction 201, land use type identification 202, and topography analysis 203. Using a combination of image processing and machine learning algorithms, site feature extraction module 2 extracts site features such as vegetation coverage, land use type, and topography from multispectral image data, further integrating site feature extraction with multispectral data analysis. This module includes vegetation coverage extraction 201, land use type identification 202, and topography analysis 203. Vegetation coverage extraction 201 assesses vegetation health and coverage by analyzing vegetation indices, such as the Normalized Difference Vegetation Index (NDVI), in multispectral images. Land use type identification 202 utilizes machine learning algorithms to classify images and identify different land use types, such as farmland, forest, and urban areas. Topography analysis 203 assesses the impact of terrain on site appearance by analyzing topographic features in the images, such as slope, aspect, and elevation changes.

[0029] Furthermore, the landscape evaluation module 3 includes the construction of an ecological aesthetic index system 301 and the application of a comprehensive evaluation model 302. This module utilizes the "ecological aesthetic index system + comprehensive evaluation model" linkage model to comprehensively evaluate the site's landscape based on extracted site characteristics, further integrating landscape evaluation with site characteristic analysis. This module includes the construction of an ecological aesthetic index system 301 and the application of a comprehensive evaluation model 302. The construction of the ecological aesthetic index system 301 involves vegetation health indicators, landscape diversity indicators, and overall site coordination indicators. These indicators comprehensively consider ecological and aesthetic factors to comprehensively assess the site's landscape quality. The application of the comprehensive evaluation model 302 includes weight allocation optimization and evaluation result calibration. By rationally allocating weights to each indicator and calibrating the evaluation results, the fairness and accuracy of the evaluation are ensured.

[0030] Furthermore, the evaluation result visualization module 4 includes a geographic information system display 401 and a three-dimensional visualization rendering 402 .

[0031] Furthermore, the ecological aesthetic index system is constructed 301 to include vegetation health index, landscape diversity index and overall coordination index of the site.

[0032] Furthermore, the comprehensive evaluation model application 302 includes weight distribution optimization and evaluation result calibration.

[0033] Furthermore, the evaluation result visualization module 4 also includes an evaluation report generation and export module, which is used to generate a detailed evaluation report based on the evaluation results and supports export in multiple formats, so as to facilitate further analysis and decision-making by users. The evaluation result visualization module 4 uses the "geographic information system GIS + three-dimensional visualization technology" linkage mode to display the evaluation results in an intuitive visual form, deepening the integration of evaluation result presentation and user decision support. This module includes a geographic information system display 401 and a three-dimensional visualization rendering 402. The geographic information system display 401 uses GIS technology to combine the evaluation results with geographic information, providing spatial distribution and statistical analysis functions. The three-dimensional visualization rendering 402 uses three-dimensional models and animations to intuitively display the site style and evaluation results, enhancing the user's understanding and decision-making ability. Furthermore, the evaluation result visualization module 4 also includes an evaluation report generation and export module, which is used to generate a detailed evaluation report based on the evaluation results and supports export in multiple formats, so as to facilitate further analysis and decision-making by users.

[0034] The basic principles, main features, and advantages of the present invention are shown and described above. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The above embodiments and descriptions are merely illustrative of the principles of the present invention. Various changes and modifications may be made to the present invention without departing from the spirit and scope of the present invention, and such changes and modifications fall within the scope of the invention as claimed.

Claims

1. A site landscape assessment system driven by multispectral remote sensing using an unmanned aerial vehicle, characterized by: It includes a multispectral data acquisition module (1), a site feature extraction module (2), a landscape evaluation module (3) and an evaluation result visualization module (4); The multispectral data acquisition module (1) utilizes a multispectral sensor mounted on an unmanned aerial vehicle to collect multispectral data of a site according to a preset flight path and parameters, obtains multispectral image data of the site, and deepens the integration of multispectral data with site style evaluation; the site feature extraction module (2) utilizes an "image processing algorithm + machine learning algorithm" linkage mode to extract features such as vegetation coverage, land use type, topography, and landforms of the site from the multispectral image data, and deepens the integration of site feature extraction and multispectral data analysis; the style evaluation module (3) utilizes an "ecological aesthetics index system + comprehensive evaluation model" linkage mode to conduct a comprehensive evaluation of the site style based on the extracted site features, and deepens the integration of style evaluation and site feature analysis; the evaluation result visualization module (4) utilizes a "geographic information system (GIS) + three-dimensional visualization technology" linkage mode to display the evaluation results in an intuitive visual form, and deepens the integration of evaluation result presentation and user decision support.

2. The multispectral remote sensing-driven site landscape assessment system using an unmanned aerial vehicle according to claim 1, characterized in that: The multispectral data acquisition module (1) comprises a UAV flight control submodule (101) and a multispectral sensor data acquisition submodule (102).

3. The multispectral remote sensing-driven site landscape assessment system using an unmanned aerial vehicle according to claim 1, characterized in that: The UAV flight control submodule (101) includes flight path planning, flight attitude control and flight status monitoring.

4. The multispectral remote sensing-driven site landscape assessment system using an unmanned aerial vehicle according to claim 1, characterized in that: The multispectral sensor data acquisition submodule (102) includes spectral band selection, image resolution setting and data storage management.

5. The multispectral remote sensing-driven site landscape assessment system using an unmanned aerial vehicle according to claim 1, characterized in that: The site feature extraction module (2) includes vegetation coverage extraction (201), land use type identification (202) and topography analysis (203).

6. The multispectral remote sensing-driven site landscape assessment system using an unmanned aerial vehicle according to claim 1, characterized in that: The style evaluation module (3) includes the construction of an ecological aesthetics index system (301) and the application of a comprehensive evaluation model (302).

7. The multispectral remote sensing-driven site landscape assessment system using an unmanned aerial vehicle according to claim 1, characterized in that: The evaluation result visualization module (4) includes a geographic information system display (401) and a three-dimensional visualization rendering (402).

8. The multispectral remote sensing-driven site landscape assessment system using an unmanned aerial vehicle according to claim 6, characterized in that: The ecological aesthetic index system (301) includes vegetation health index, landscape diversity index and site overall coordination index.

9. The multispectral remote sensing-driven site landscape assessment system using an unmanned aerial vehicle according to claim 6, characterized in that: The comprehensive evaluation model application (302) includes weight distribution optimization and evaluation result calibration.

10. The multispectral remote sensing driven site landscape assessment system using an unmanned aerial vehicle according to claim 7, characterized in that: The evaluation result visualization module (4) also includes an evaluation report generation and export module, which is used to generate a detailed evaluation report based on the evaluation results and supports exporting in multiple formats to facilitate further analysis and decision-making by users.

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