With the development of hardware techniques and the decrease in equipment costs, unmanned aerial vehicle (UAV) has been widely applied in various socio-economic fields. However, there have been relatively few studies on low-altitude airspace resources as the operational carrier of UAVs. In this study, from the perspective of geography, the key issues related to the research of low-altitude airspace resources for UAV applications are discussed. Firstly, it is theoretically defined that low-altitude airspace is an important kind of natural resources with natural, social, and economic attributes, which should be included in the national natural resource development and utilization system; Secondly, we review the latest UAV applications based on the low-altitude airspace resources, categorize their constraints to utilize resources from natural and social aspects, and point out that the intervention of geography will speed up the development and utilization process of low-altitude airspace resources. Finally, this paper constructs the low-altitude airspace resource measurement index composed of three categories and nine sub-categories, and proposes four basic principles of low-altitude airspace resource measurement of "non-conflict utilization of resources, safety guarantee, benefit priority, and fairness", and thus forming a theoretical model of low-altitude airspace resource measurement with the three basic elements of national scope (S), true height (H) and time (t). This paper explores and discusses the low-altitude airspace resources from the perspective of geography, which will promote the interdisciplinarity of geography and aviation to some extent and the sustainable utilization of low-altitude airspace resources.

Aiming at the requirement to use unmanned aerial vehicle (UAV) data to verify common products from China High-resolution Earth Observation System (CHEOS), this research examines the distribution of UAV airports using the existing ecological observation stations. Firstly, to comprehensively consider the factors affecting the satellite products, a physical model of the geographical background coverage was proposed. Secondly, a maximal geographic background model is designed based on the improved the coverage model with geographic backgrounds, and the number of UAV airports was determined using the sample size determination method of random sampling. Then, the maximal geographic background covering model and a maximal area covering model were used to study the distribution of UAV airports. Finally, the results of the airport layout under the two models were compared, and MODIS EVI (Enhanced Vegetation Index) data products were used to verify the results. The results showed that for a limited number of airports (n = 60), the geographical background coverage of the service areas of the airports selected by the maximal area coverage model was 26.66%, which represents 70.37% of China's land area. The geographical background coverage of the service areas of the airports selected by the maximal geographical background covering model was 38.32%, which represents 73.36% of China's land area. The layout of the UAV airports selected by the maximal geographic covering model is better than that selected by the maximal area covering model. The results can lay a foundation for the design of an unmanned aerial vehicle observation network for the verification of common products from CHEOS.