AN OPENSTREETMAP-BASED DATASET OF BUILDING FOOTPRINTS FOR ANALYSING DIFFERENT TYPES OF LABEL NOISE

Jonas Gütter; Anna Kruspe; Xiao Xiang Zhu

doi:10.1109/IGARSS47720.2021.9553583

AN OPENSTREETMAP-BASED DATASET OF BUILDING FOOTPRINTS FOR ANALYSING DIFFERENT TYPES OF LABEL NOISE

Jonas Gütter, Anna Kruspe, Xiao Xiang Zhu

Chair of Data Science in Earth Observation

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Scopus citations

Abstract

We present a dataset consisting of OpenStreetMap imagery and corresponding building footprint labels. Multiple label sets are provided, each containing a different type of label noise. The purpose of the dataset is to enable a systematic analysis of different label noise types in the earth observation domain and to provide a benchmark dataset for noise removal techniques. We also present some preliminary results from experiments on the effect of different label noise types on model performance.

Original language	English
Title of host publication	IGARSS 2021 - 2021 IEEE International Geoscience and Remote Sensing Symposium, Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	2321-2324
Number of pages	4
ISBN (Electronic)	9781665403696
DOIs	https://doi.org/10.1109/IGARSS47720.2021.9553583
State	Published - 2021
Event	2021 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2021 - Brussels, Belgium Duration: 12 Jul 2021 → 16 Jul 2021

Publication series

Name	International Geoscience and Remote Sensing Symposium (IGARSS)
Volume	2021-July

Conference

Conference	2021 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2021
Country/Territory	Belgium
City	Brussels
Period	12/07/21 → 16/07/21

Keywords

Building footprints
Dataset
Deep learning
Label noise
OpenStreetMap

Access to Document

10.1109/IGARSS47720.2021.9553583

Cite this

Gütter, J., Kruspe, A., & Zhu, X. X. (2021). AN OPENSTREETMAP-BASED DATASET OF BUILDING FOOTPRINTS FOR ANALYSING DIFFERENT TYPES OF LABEL NOISE. In IGARSS 2021 - 2021 IEEE International Geoscience and Remote Sensing Symposium, Proceedings (pp. 2321-2324). (International Geoscience and Remote Sensing Symposium (IGARSS); Vol. 2021-July). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IGARSS47720.2021.9553583

Gütter, Jonas ; Kruspe, Anna ; Zhu, Xiao Xiang. / AN OPENSTREETMAP-BASED DATASET OF BUILDING FOOTPRINTS FOR ANALYSING DIFFERENT TYPES OF LABEL NOISE. IGARSS 2021 - 2021 IEEE International Geoscience and Remote Sensing Symposium, Proceedings. Institute of Electrical and Electronics Engineers Inc., 2021. pp. 2321-2324 (International Geoscience and Remote Sensing Symposium (IGARSS)).

@inproceedings{3dc6e56e96da42568e08e57f721111ae,

title = "AN OPENSTREETMAP-BASED DATASET OF BUILDING FOOTPRINTS FOR ANALYSING DIFFERENT TYPES OF LABEL NOISE",

abstract = "We present a dataset consisting of OpenStreetMap imagery and corresponding building footprint labels. Multiple label sets are provided, each containing a different type of label noise. The purpose of the dataset is to enable a systematic analysis of different label noise types in the earth observation domain and to provide a benchmark dataset for noise removal techniques. We also present some preliminary results from experiments on the effect of different label noise types on model performance.",

keywords = "Building footprints, Dataset, Deep learning, Label noise, OpenStreetMap",

author = "Jonas G{\"u}tter and Anna Kruspe and Zhu, {Xiao Xiang}",

note = "Publisher Copyright: {\textcopyright} 2021 IEEE.; 2021 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2021 ; Conference date: 12-07-2021 Through 16-07-2021",

year = "2021",

doi = "10.1109/IGARSS47720.2021.9553583",

language = "English",

series = "International Geoscience and Remote Sensing Symposium (IGARSS)",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "2321--2324",

booktitle = "IGARSS 2021 - 2021 IEEE International Geoscience and Remote Sensing Symposium, Proceedings",

}

Gütter, J, Kruspe, A & Zhu, XX 2021, AN OPENSTREETMAP-BASED DATASET OF BUILDING FOOTPRINTS FOR ANALYSING DIFFERENT TYPES OF LABEL NOISE. in IGARSS 2021 - 2021 IEEE International Geoscience and Remote Sensing Symposium, Proceedings. International Geoscience and Remote Sensing Symposium (IGARSS), vol. 2021-July, Institute of Electrical and Electronics Engineers Inc., pp. 2321-2324, 2021 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2021, Brussels, Belgium, 12/07/21. https://doi.org/10.1109/IGARSS47720.2021.9553583

AN OPENSTREETMAP-BASED DATASET OF BUILDING FOOTPRINTS FOR ANALYSING DIFFERENT TYPES OF LABEL NOISE. / Gütter, Jonas; Kruspe, Anna; Zhu, Xiao Xiang.
IGARSS 2021 - 2021 IEEE International Geoscience and Remote Sensing Symposium, Proceedings. Institute of Electrical and Electronics Engineers Inc., 2021. p. 2321-2324 (International Geoscience and Remote Sensing Symposium (IGARSS); Vol. 2021-July).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - AN OPENSTREETMAP-BASED DATASET OF BUILDING FOOTPRINTS FOR ANALYSING DIFFERENT TYPES OF LABEL NOISE

AU - Gütter, Jonas

AU - Kruspe, Anna

AU - Zhu, Xiao Xiang

PY - 2021

Y1 - 2021

N2 - We present a dataset consisting of OpenStreetMap imagery and corresponding building footprint labels. Multiple label sets are provided, each containing a different type of label noise. The purpose of the dataset is to enable a systematic analysis of different label noise types in the earth observation domain and to provide a benchmark dataset for noise removal techniques. We also present some preliminary results from experiments on the effect of different label noise types on model performance.

AB - We present a dataset consisting of OpenStreetMap imagery and corresponding building footprint labels. Multiple label sets are provided, each containing a different type of label noise. The purpose of the dataset is to enable a systematic analysis of different label noise types in the earth observation domain and to provide a benchmark dataset for noise removal techniques. We also present some preliminary results from experiments on the effect of different label noise types on model performance.

KW - Building footprints

KW - Dataset

KW - Deep learning

KW - Label noise

KW - OpenStreetMap

UR - http://www.scopus.com/inward/record.url?scp=85126014216&partnerID=8YFLogxK

U2 - 10.1109/IGARSS47720.2021.9553583

DO - 10.1109/IGARSS47720.2021.9553583

M3 - Conference contribution

AN - SCOPUS:85126014216

T3 - International Geoscience and Remote Sensing Symposium (IGARSS)

SP - 2321

EP - 2324

BT - IGARSS 2021 - 2021 IEEE International Geoscience and Remote Sensing Symposium, Proceedings

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2021 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2021

Y2 - 12 July 2021 through 16 July 2021

ER -

Gütter J, Kruspe A, Zhu XX. AN OPENSTREETMAP-BASED DATASET OF BUILDING FOOTPRINTS FOR ANALYSING DIFFERENT TYPES OF LABEL NOISE. In IGARSS 2021 - 2021 IEEE International Geoscience and Remote Sensing Symposium, Proceedings. Institute of Electrical and Electronics Engineers Inc. 2021. p. 2321-2324. (International Geoscience and Remote Sensing Symposium (IGARSS)). doi: 10.1109/IGARSS47720.2021.9553583

AN OPENSTREETMAP-BASED DATASET OF BUILDING FOOTPRINTS FOR ANALYSING DIFFERENT TYPES OF LABEL NOISE

Abstract

Publication series

Conference

Keywords

Access to Document

Other files and links

Fingerprint

Cite this