## 1 Introduction  
Protected areas (PAs), as delineated in scholarly literature, are unique geographical zones that are not only legally recognized and managed, but are also committed to the enduring preservation of nature, inclusive of the associated ecosystem services and cultural values [1]. At present, the establishment of PAs is a pivotal global strategy for biodiversity conservation, climate change mitigation, and the reduction of human impact [2, 3, 4, 5, 6, 7]. It also serves as a significant policy instrument for the protection of natural resources and the promotion of sustainable development [1, 8, 9]. China, being one of the countrieswith the most diverse ecosystems globally, has instituted more than ten categories of PAs, which encompass 18% of its terrestrial area and 4.1% of its marine area [10; 11; 12]. However, numerous PAs are still under considerable pressure, confronting challenges such as the exploitation of agricultural and forestry products, illegal hunting, and infrastructure development [13]. In essence, merely augmenting the quantity and size of PAs is no longer adequate to cater to the present and future requirements of biodiversity conservation [14; 12]. The most pressing concern at this juncture is to amplify the effectiveness of existing PAs to ensure their preservation [15]. The effectiveness of PAs is contingent on a multitude of political, economic, and local environmental factors. There are authoritative domestic and international assessment standards for PAs, such as the Standard for Conservation Effectiveness Assessment of Ecology and Environment in Nature Reserves, promulgated by the Ministry of Ecology and Environment of China, and Evaluating Effectiveness: A Framework for Assessing Management Effectiveness of Protected Areas, published by the International Union for Conservation of Nature (IUCN), Gland, Switzerland. In practice, the assessment criteria are relatively sophisticated, necessitating specialized technical expertise, rendering implementation challenging. Furthermore, numerous studies have utilized multi-temporal historical land use data to appraise the land use/land cover changes and landscape pattern dynamics within PAs [16; 17; 18]. Indexes such as the landscape development intensity index and landscape pressure index have been employed by academics to assess the effectiveness of safeguarding marine PAs [19]. In addition, alterations in ecosystems, as well as the distribution and abundance of key species, also serve as indicators of conservation effectiveness [20; 21; 22]. Nevertheless, these existing evaluation techniques are often labor-intensive and time-consuming [23; 24], or necessitate plenty of field investigations [21]. Remote Sensing (RS) is an advanced data acquisition technology that can swiftly, comprehensively, and accurately generate thematic data. It facilitates repeated observations of large territories and inaccessible areas, proving to be more cost-effective than field observations [25; 26]. In recent years, research using satellite imagery to predict sustainable development outcomes has achieved rapid growth, especially studies employing machine learning methods. Satellite data with greatly improved spatial, temporal, and spectral resolutions have provided richer information on the Earth's surface. RS meets the needs for monitoring sustainable development outcomes, with the advantages of mature technology, rapid data updates, and extensive coverage, which can satisfy the requirements of large-scale, high-precision effectiveness monitoring in PAs [27]. The Geographic Information System (GIS), with its robust information extraction technology and spatial analysis capabilities, can accurately and efficiently address geographic issues related to resources and the environment [28]. The significance of this technology continues to escalate, with ongoing enhancements to its role and functionality. Consequently, the integration of RS and GIS has emerged as the preferred methodology for evaluating the conservation effectiveness of PAs.