Unbiased Area Estimation Using Copernicus High Resolution Layers and Reference Data

Kleinewillinghöfer, L; Olofsson, P; Pebesma, E; Meyer, H; Buck, O; Haub, C; Eiselt, B

Forschungsartikel (Zeitschrift) | Peer reviewed

Zusammenfassung

Land cover area estimates can be derived via design-based approaches using a probability (random) reference sample. The collection of samples is usually costly and requires an effective sampling design. Earth-Observation-based mapping approaches do not have this requirement but can be biased in providing area estimates. Combining reference samples with remote sensing products can reduce sampling efforts and provide a more effective method to estimate land cover. The Copernicus High-Resolution Layer (HRL) provides remote-sensing-based data across Europe to support area estimation. Different methods are tested to estimate areas of imperviousness in four selected countries in Europe to demonstrate the use and shortcomings of existing reference information from the LUCAS survey program and the HRL Imperviousness products from 2015 and 2018.

Details zur Publikation

FachzeitschriftRemote Sensing (Remote Sens.)
Jahrgang / Bandnr. / Volume14
Ausgabe / Heftnr. / Issue19
Seitenbereich4903null
StatusVeröffentlicht
Veröffentlichungsjahr2022
Sprache, in der die Publikation verfasst istEnglisch
DOI10.3390/rs14194903
Link zum Volltexthttps://www.mdpi.com/2072-4292/14/19/4903
Stichwörterarea estimation; Copernicus; LUCAS; regression estimator

Autor*innen der Universität Münster

Meyer, Hanna
Professur für Remote Sensing und Spatial Modelling (Prof. Meyer)
Pebesma, Edzer
Professur für Geoinformatik (Prof. Pebesma)