Key technology for selecting depressions as sites of FAST-type radio telescopes

The Five-hundred-meter Aperture Spherical radio Telescope (FAST), also known as Tianyan (meaning the Eye of the Sky), has attracted worldwide attention and is the largest single-dish radio telescope in the world. The joint observations of FAST and several more FAST-type radio telescopes allow detection sensitivity and resolution to be further improved and the research fields to be expanded. Therefore, Chinese radio astronomy scientists have the expectation of building more FAST-type radio telescopes in China, which should be achieved based on the preceding research on depressions as the sites of FAST-type radio telescopes. Presently, the shared digital elevation model (DEM) data enjoy intercontinental coverage and different ground resolutions. The development of computer processing technology has greatly enhanced the processing and analysis capacities of DEM data and continuously innovated the processing technologies. Moreover, relevant analyses and expressions can be simulated. Therefore, based on a comparative analysis of the structural scales of the projects of the Arecibo radio telescope and the FAST, as well as the morphological characteristics of karst depressions, this study proposed the conditions of ideal depressions as the sites of FAST-type radio telescopes. Moreover, by analyzing the resolution and data quality of shared DEM data on the Internet, it is concluded that areas with ASTER_GDEMV3 data with a resolution of 30 m are suitable as sites of large radio telescopes in provincial-level regions. In search of large-scale depressions in Guizhou Province, this study developed special modules for quantitative analyses, such as extracting the characteristic parameters of depressions and the fitting of filling, excavation, and superimposed sections, based on the ArcGIS platform and summarized the key steps to organize and apply the major tools of ArcGIS in the special modules. The results of this study determined key technology in search of large Karst depressions in provincial-level regions. Furthermore, this study proposed several issues that are noteworthy in the application.