## 1 Introduction  
Unmanned Aerial Vehicle Remote Sensing (UAV-RS) has evolved from a niche technology into a mainstream scientific tool for high-resolution Earth observation using UAV platforms [1, 2]. Compared to traditional satellite and manned aerial remote sensing, UAV-RS offers significant advantages in spatiotemporal resolution, acquisition efficiency, and cost-effectiveness, making it particularly suitable for geographic scenarios requiring high-frequency observation, fine-scale monitoring, and rapid response.  
In recent years, with the advancement of key technologies such as flight control, navigation and positioning, and remote sensing sensors, the application domains of UAV-RS have continuously expanded. UAV-RS now shows tremendous potential in areas such as precision agriculture [3, 4], ecological and environmental monitoring [5], disaster emergency response [6], urban planning [7], marine surveillance [8], and infrastructure management [9]. For example, in agriculture, UAV-RS can be used for crop health monitoring [10], soil nutrient assessment [11], and pest and disease warning [12], facilitating the digital and precision transformation of agriculture. In the ecological domain, UAV-RS enables dynamic monitoring of forests [13], wetlands [14], and water bodies [15], providing vital technical support for resource conservation and environmental governance. In disaster management, UAV-RS allows rapid acquisition of high-resolution imagery to support emergency assessment and decision-making [16]. In urban management, it can be applied to land use monitoring [17], urban expansion analysis [18], and traffic control [19].  
Although multiple review articles on UAV-RS have emerged in recent years [1, 20, 21, 22, 23, 24], most focus on specific technologies or application fields [25], and there is still a lack of systematic review and quantitative analysis of the overall development trajectory of UAV-RS. For instance, many studies emphasize sector-specific applications such as agriculture [26, 27], forestry [28, 29], fisheries [8], archaeology [30], natural disasters [31], and ecological monitoring--including grasslands [32], wildlife [33], and biodiversity [34]--yet cross-disciplinary integrations are rarely discussed. Moreover, most reviews tend to emphasize technical aspects like sensor design and image processing [35], with limited attention to global research landscapes, collaborative networks, and technological convergence trends in UAV-RS.  
Despite the exponential growth of the UAV-RS literature, a critical tension has become increasingly evident: has the rapid expansion on the application side masked stagnation on the technological front? In other words, while a large body of research focuses on how to efficiently apply UAVs to address practical problems in agriculture, ecology, and related fields, have the foundational technologies that support these applications--such as platform endurance, sensor coordination, data standardization, and global collaboration mechanisms--quietly become bottlenecks limiting the field's long-term development?  
To address this, the present study proposes three interrelated core questions that serve as the analytical framework for this paper:  
1. Does quantitative evidence indicate that UAV-RS research has become predominantly driven by application demands, at the expense of investment in foundational research?
2. Within the global landscape of knowledge production, is there evidence of \"technological silos\" that hinder deep collaboration across institutions and across national or regional boundaries?
3. Behind the current enthusiasm for multi-source data fusion, is the lack of unified data standards and interoperability frameworks posing hidden risks to data integration?  
Answering these questions not only helps to clarify the internal tension between the rapid development of application-level UAV-RS and the relative stagnation of its technical foundations, but also provides forward-looking strategic insights for researchers, funding agencies, and policy makers.