Work

The Implications of Field Worker Characteristics and Landscape Heterogeneity for Classification Correctness and the Completeness of Topographical Mapping

Year: 2018

Type: article

Abstract: The quality of spatial data may vary spatially. If mapping (interpretation of orthophotos) is done during fieldwork, this variation in quality may occur as a result of differences in the complexity of the landscape, differences in the characteristics of individual field workers, and differences in their perception of the landscape. In this study, we explored the interaction between the characteristics of these workers, including their gender and years of experience (as a proxy for their mapping skills), and landscape heterogeneity. There was no significant difference between male and female workers. Although field workers with more years of experience generally had higher mapping quality, the relationship was not statistically significant. We found differences in the rates of misclassification, omission, and commission errors between workers in different landscape types. We conclude that the error rates due to misclassification, omission, and commission were the lowest in more diverse landscapes (high number of different land use types) with a relatively high amount of buildings, whereas the error rates were the highest in mainly forested landscapes with larger and more complex shaped patches.

Source: ISPRS International Journal of Geo-Information

DOI: 10.3390/ijgi7060205

Authors: Kiira Mõisja, Evelyn Uuemaa, Tõnu Oja

Institution: University of Tartu

Language: English

Topic: Automated Road and Building Extraction

Subfield: Computer Vision and Pattern Recognition

Field: Computer Science

Domain: Physical Sciences

Open Access status: gold

Estimated APC paid: $2,292

Funders: Tartu Ülikool, Research Executive Agency, H2020 Marie Skłodowska-Curie Actions