The Effect of Environmental Conditions on the Quality of UAS Orthophoto-Maps in the Coastal Environment
Bibliographic Data
| ID | 22033663 |
|---|---|
| Authors | Michaela Doukari (0000-0002-9864-8790, University of the Aegean, corresponding author), Stelios Katsanevaki (0000-0002-5137-7540, University of the Aegean), Stelios Katsanevakis (University of the Aegean), Nikolaos Soulakellis (0000-0002-5328-2342, University of the Aegean), Konstantinos Topouzelis (0000-0002-1916-1600, University of the Aegean) |
| Year | 2021 |
| Volume | 10 |
| Issue | 1 |
| Pages | 18 |
| Publication date | 2021-01-06 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | ISPRS International Journal of Geo-Information (JOURNAL) |
| Journal identifiers | ISSN: 2220-9964 • E-ISSN: 2220-9964 |
| Publisher | MDPI AG (PUBLISHER • IT) |
| DOI | 10.3390/ijgi10010018 |
| OpenAlex | W3120917745 |
| Language | EN |
| References cited | 28 |
Marine conservation and management require detailed and accurate habitat mapping, which is usually produced by collecting data using remote sensing methods. In recent years, unmanned aerial systems (UAS) are used for marine data acquisition, as they provide detailed and reliable information through very high-resolution orthophoto-maps. However, as for all remotely sensed data, it is important to study and understand the accuracy and reliability of the produced maps. In this study, the effect of different environmental conditions on the quality of UAS orthophoto-maps was examined through a positional and thematic accuracy assessment. Selected objects on the orthophoto-maps were also assessed as to their position, shape, and extent. The accuracy assessment results showed significant errors in the different maps and objects. The accuracy of the classified images varied between 2.1% and 27%. Seagrasses were under-classified, while the mixed substrate class was overclassified when environmental conditions were not optimal. The highest misclassifications were caused due to sunglint presence in combination with a rough sea-surface. A change detection workflow resulted in detecting misclassifications of up to 45%, on orthophoto-maps that had been generated under non-optimal environmental conditions. The results confirmed the importance of optimal conditions for the acquisition of reliable marine information using UAS
Cartography · Geography · Orthophoto · Photogrammetry · Remote sensing · Thematic map · Coastal and Marine Management · Computer Science · Coral and Marine Ecosystems Studies · Environmental Science · Marine and coastal plant biology · Mathematics
| Highly cited | No |
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