期刊名称：ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
印刷版ISSN：2194-9042
电子版ISSN：2194-9050
出版年度：2022
卷号：V-1-2022
页码：187-193
DOI：10.5194/isprs-annals-V-1-2022-187-2022
语种：English
出版社：Copernicus Publications
摘要：Data are a key component for many applications and methods in the domain of photogrammetry and remote sensing. Especially data-driven approaches such as deep learning rely heavily on available annotated data. The amount of data is increasing significantly every day. However, reference data is not increasing at the same rate and finding relevant data for a specific domain is still difficult. Thus, it is necessary to make existing reference data more accessible to the scientific community as far as possible in order to make optimal use of it. In this paper we provide an overview of the development of our photogrammetry and remote sensing specific Benchmark Metadata Database (BeMeDa). BeMeDa is based on MongoDB, a NoSQL database system. In addition, the development of a user-oriented metadata schema serves for data structuring. BeMeDa enables easy searching of benchmark datasets in the field of photogrammetry and remote sensing.
