###### Abstract
Remote sensing data, such as Sentinel-2, Landsat-8, and MODIS, with their differentiated spatial, temporal, and spectral resolutions, can more comprehensively reflect vegetation dynamics and provide a range of information for ecological environment monitoring [34]. In recent years, escalating global ecological challenges have driven the widespread adoption of air-space-ground integrated monitoring technology in ecological conservation and restoration research [35]. This comprehensive approach synergizes multi-source data from satellite remote sensing (space), unmanned aerial vehicles (UAVs), aerial platforms (air), and ground-based surveys (ground), enabling multi-scale and holistic ecosystem monitoring [36; 37]. While such technology has been increasingly applied to wetland ecological assessments, significant bottlenecks persist in multi-modal data fusion and dynamic evaluation mechanisms. Empirical studies reveal that although satellite systems (e.g., GF-5 and Sentinel series) provide large-scale monitoring capabilities, optical image quality in cloudy or rainy regions (e.g., the Guangdong-Hong Kong-Macao Greater Bay Area) suffers from temporal discontinuity, necessitating UAVs and ground sensors for high-frequency data supplementation [38]. However, inherent heterogeneity in multi-source data--spanning spatial resolution (e.g., Landsat's 30 m vs. Sentinel-2's 10 m), temporal alignment, and spectral characteristics--severely compromises fusion efficacy, with reported 28% error rates in wetland inundation boundary delineation [39; 40]. Furthermore, current inversion algorithms for critical wetland parameters (e.g., soil moisture and vegetation biomass) predominantly rely on empirical models. Sensitivity variations among parameters (e.g., leaf area index and chlorophyll content) and error accumulation mechanisms substantially degrade accuracy, as evidenced by the PROSAIL model's limited performance in coastal wetland biomass estimation (R\({}^{2}\) = 0.55-0.71) [41]. Building on previous studies, this paper contributes to the field by integrating multiple approaches and indices, including water environment, soil environment, carbon sequestration capacity, biodiversity, and ecological remote sensing interpretation, and proposes a regional ecological restoration effect. A comprehensive \"sky-ground-space\" three-dimensional monitoring and evaluation system is proposed to determine whether the pre-restoration goals have been achieved. Specifically, remote sensing evaluation indices are calculated using remote sensing imagery and land cover data, enabling the assessment of ecological restoration projects from three key perspectives: water resources, water environment, and ecological functions. The remainder of this paper is structured as follows: The Section 2 introduces the general situation of Liaohe Estuary wetland and the collection of monitoring data. In Section 3, experimental data processing and the selection and calculation of evaluation indexes are introduced. The Section 4 verifies the feasibility and superiority of the target method through the discussion of the evaluation results of the study area. The Section 5 makes a horizontal comparison with other similar studies, and clarifies the scientific significance and shortcomings of this paper. Finally, Section 6 concludes this study with a summary of the main findings.