# Historical Eco-Environmental Quality Mapping in China with Multi-Source Data Fusion
## 1 Introduction  
Since the beginning of the twenty-first century, global society has undergone progress and technological advancements, while China has made significant strides in urbanization and industrialization [1; 2], However, this development has resulted in a progressive degradation of the eco-environmental quality (EEQ) [3; 4]. It is essential to recognize that social progress and human development are intrinsically linked to the ecological environment [5]. In the 1990s, the United Nations organized conferences such as the \"Conference on Environment and Development\" and the \"Habitat Conference\" [6], marking the gradual emergence of ecological environment research as a significant area of focus for scholars. Additionally, with societal progress, residents' economic income and living standards haveimproved, leading to an inevitable pursuit of a high quality of life, which necessitates a sound ecological environment as a fundamental prerequisite [7]. Given the growing global awareness of the ecological environment, the evaluation and protection of the ecological environment have become crucial tasks in China's modernization endeavors. Since the reform and opening up, China has witnessed unprecedented development across all fields [8]. However, simultaneously, the ecological environment in China has suffered more severe damage compared to other countries worldwide [9]. The rapid economic development has come at the expense of ecological degradation, highlighting a disconnect between urbanization development and ecological protection in China, thereby hindering the achievement of sustainable development goals [10; 11]. This low-coupling phenomenon is a growing concern for both the state and society, particularly as the extent of ecological damage increasingly affects people's lives. In 2000, China introduced the National Outline of Ecological Environmental Protection [12], which emphasized the crucial environmental policy of \"equal emphasis on pollution prevention and ecological protection,\" thereby urging nationwide ecological. When it comes to assessing EEG, the OECD (Organization for Economic Cooperation and Development) introduced the \"pressure-state-response\" (PSR) model in 1990, which was the world's first recognized EEG assessment index system [13]. As scientific progress continues, cross-disciplinary applications are becoming increasingly common. For instance, [PERSON] et al. [14] utilized GIS and RS to examine the interplay between ecological factors, EEG, and urbanization in the Nile Delta, revealing that rapid urbanization poses significant threats to both ecology and EEG. [PERSON] et al. [15] employed 3S technology to analyze the reciprocal relationship between EEG and urbanization. [PERSON] [16] employed principal component analysis (PCA) and cluster analysis to investigate the impact of urbanization development on EEG in Helsinki. [PERSON] et al. [17] devised a novel modeling approach for evaluating and monitoring urban ecological safety. In the twenty-first century, studies focusing on EEG evaluation have become increasingly rigorous and comprehensive [18]. Some scholars have analyzed EEG from social, economic, and natural perspectives [19]. For instance, [PERSON] et al. [20] constructed an urban ecological suitability index model based on three dimensions (living, production, and environment) and applied it to analyze the EEG of Changsha city, providing scientific and empirical support for environmental protection policies. Additionally, ecological niche theory has been employed by scholars [21] to assess EEG. [PERSON] [22] conducted a quantitative analysis of the ecological niche in 14 cities in Gansu Province in 2009, employing dynamic cluster analysis. Existing studies on EEG evaluation have primarily focused on the comprehensive evaluation process, including indicator selection, evaluation principles, and models [23]. However, there is a notable lack of an internationally accepted standard with high precision for EEG evaluation [24].