DEVELOPMENT OF A DATABASE FOR BENCHMARK DATASETS IN PHOTOGRAMMETRY AND REMOTE SENSING

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 in...

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Bibliographic Details
Published inISPRS annals of the photogrammetry, remote sensing and spatial information sciences Vol. V-1-2022; pp. 187 - 193
Main Authors Budde, L. E., Schmidt, J., Javanmard-Ghareshiran, A., Hunger, S., Iwaszczuk, D.
Format Journal Article
LanguageEnglish
Published Gottingen Copernicus GmbH 17.05.2022
Copernicus Publications
Subjects
Benchmarks
Datasets
Domains
Metadata
Photogrammetry
Remote sensing
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Summary: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.
ISSN:2194-9050
2194-9042
2194-9050
DOI:10.5194/isprs-annals-V-1-2022-187-2022