dc.contributor.author
Joshi, Neha
dc.contributor.author
Baumann, Matthias
dc.contributor.author
Ehammer, Andrea
dc.contributor.author
Fensholt, Rasmus
dc.contributor.author
Grogan, Kenneth
dc.contributor.author
Hostert, Patrick
dc.contributor.author
Rudbeck Jepsen, Martin
dc.contributor.author
Kuemmerle, Tobias
dc.contributor.author
Meyfroidt, Patrick
dc.contributor.author
Mitchard, Edward T. A.
dc.contributor.author
Reiche, Johannes
dc.contributor.author
Ryan, Casey M.
dc.contributor.author
Waske, Björn
dc.date.accessioned
2018-06-08T10:33:10Z
dc.date.available
2018-02-28T12:18:13.423Z
dc.identifier.uri
https://refubium.fu-berlin.de/handle/fub188/20637
dc.identifier.uri
http://dx.doi.org/10.17169/refubium-23938
dc.description.abstract
The wealth of complementary data available from remote sensing missions can
hugely aid efforts towards accurately determining land use and quantifying
subtle changes in land use management or intensity. This study reviewed 112
studies on fusing optical and radar data, which offer unique spectral and
structural information, for land cover and use assessments. Contrary to our
expectations, only 50 studies specifically addressed land use, and five
assessed land use changes, while the majority addressed land cover. The
advantages of fusion for land use analysis were assessed in 32 studies, and a
large majority (28 studies) concluded that fusion improved results compared to
using single data sources. Study sites were small, frequently 300–3000 km 2 or
individual plots, with a lack of comparison of results and accuracies across
sites. Although a variety of fusion techniques were used, pre-classification
fusion followed by pixel-level inputs in traditional classification algorithms
(e.g., Gaussian maximum likelihood classification) was common, but often
without a concrete rationale on the applicability of the method to the land
use theme being studied. Progress in this field of research requires the
development of robust techniques of fusion to map the intricacies of land uses
and changes therein and systematic procedures to assess the benefits of fusion
over larger spatial scales. View Full-Text
en
dc.rights.uri
http://creativecommons.org/licenses/by/4.0/
dc.subject
synthetic aperture radar
dc.subject
machine learning
dc.subject
pixel- and segment-level analyses
dc.subject.ddc
500 Naturwissenschaften und Mathematik::550 Geowissenschaften, Geologie
dc.title
A Review of the Application of Optical and Radar Remote Sensing Data Fusion to
Land Use Mapping and Monitoring
dc.type
Wissenschaftlicher Artikel
dcterms.bibliographicCitation
Remote Sens. - 8 (2016), 1, Artikel Nr. 70
dcterms.bibliographicCitation.doi
10.3390/rs8010070
dcterms.bibliographicCitation.url
http://www.mdpi.com/2072-4292/8/1/70
refubium.affiliation
Geowissenschaften
de
refubium.mycore.fudocsId
FUDOCS_document_000000029140
refubium.note.author
Der Artikel wurde in einer reinen Open-Access-Zeitschrift publiziert.
refubium.resourceType.isindependentpub
no
refubium.mycore.derivateId
FUDOCS_derivate_000000009481
dcterms.accessRights.openaire
open access