Abstract: Objective The landscape character assessment system is an effective tool to help people understand the history and current situation of landscapes. Its results are widely used in land decision-making and spatial planning control. Landscape Character Assessment (LCA) and Landscape Personality Assessment are two different perspectives and systems. LCA has a certain research and practical foundation, forming a relatively mature methodology system, emphasizing the characterization of the current landscape situation. There is relatively little research and practice related to LPA, and attention is paid to the trend of landscape changes. There is a nested relationship in terms of value connotation, landscape spatial carrier, evaluation index system, and practical application of results, and there is a certain degree of complementarity between the two. Integrating LCA and LPA and constructing a multi-level nested framework for landscape character assessment can sort out the multi-level relationships of landscape character representation, better meet practical needs at different scales, and help people comprehensively understand the past, present, and future of landscapes. Methods Taking the landscape character assessment system as the research object, this paper analyzes the concepts and connotations related to landscape character, and evaluates the shortcomings of existing LCA and LPA research and practice from the aspects of value dimension, indicator system, process characteristics, classification methods, et al. There is considerable research and practical experience in LCA research field, and scholars have also explored LPA. This study analyzes, evaluates, and horizontally compares relevant typical research and practical projects both domestically and internationally. The overall landscape carries the overall humanistic ecosystem, and the structural and deconstructive nature of the overall humanistic ecosystem determines that the landscape space is a complex composed of multiple relatively independent spaces; The concatenation and nesting determine the multi-level nesting of the overall landscape space; Perception and symbolism determine that identifying the characteristics of a landscape is a way to recognize the unique value of the landscape. Based on existing research content, summarize the overall characteristics and future development trends of the two assessment methods, analyze the differences and underlying connections between the two, and explore possible integration methods for the two methods. Results LCA can describe what a landscape is, while LPA can explore why it is. Comparing the methodology of LCA with that of LPA, LPA and LCA have certain complementarity in research perspectives, indicator systems, classification methods, and other aspects. LCA focuses on the objective description of elements and their combination level features, which can depict the local differences in the landscape and is supported by quantitative analysis techniques; LPA focuses on the comprehensive effects in the dynamic process of resource combination, which can characterize the value and personalized characteristics of the overall landscape, but lacks quantitative classification techniques. LP is formed by highly condensed LC with inherent attributes that are perceived by humans, and LCA is the foundation of LPA formation. How to comprehensively characterize the unique value of landscape and better integrate the assessment results with practice is the current challenge facing landscape character assessment. The two have certain complementarity in different stages of landscape character assessment, and are two sets of local character representation ideas suitable for different scenes in the landscape character assessment system. The integration of the two helps to optimize and improve the landscape character assessment system in both theory and practice. Based on the overall characteristics of the landscape and the nested characteristics of landscape spatial units, integrating the perspectives and systems of LCA and LPA, a multi-level nested assessment framework for landscape character is proposed, providing reference for understanding multi-scale landscape local characteristics and spatial systems. By combining multi-scale segmentation and spatial clustering techniques of deep learning, a technical path for multi-level nested assessment of landscape character is constructed, providing ideas for characterizing landscape local characteristics at multiple scales. Conclusion In the process of developing landscape character assessment systems, there have been numerous methodological systems. The multi-level nested evaluation framework and technical path integrating LCA and LPA can accurately grasp the local characteristics of the landscape through quantitative assessment and spatial mapping using artificial intelligence technology at different scales of practical needs. This framework serves as a comprehensive framework in the landscape character assessment system, providing a holistic perspective for exploring the unique value of the landscape. In addition, combining the integration framework with digital technology analysis, a landscape character assessment approach that adapts to different scale practical needs is proposed, providing a technical path for analyzing the local characteristics of landscapes based on different levels of landscape space. The landscape spatial unit system can be used as a carrier to characterize the characteristics of different levels of landscape places, and the assessment results can be integrated with applications at different scales, assisting in the practice of landscape planning and design, zoning control, resource protection and utilization in different fields. The integrated framework and technical path of LCA and LPA can help future landscape character assessment research comprehensively understand the past, present, and future of landscapes; Systematically understand the local characteristics of the landscape from the local to the overall; Combine practical needs at different scales of results.