SwePub
Sök i LIBRIS databas

  Utökad sökning

WFRF:(Ban Yifang)
 

Sökning: WFRF:(Ban Yifang) > Fusion of multitemp...

Fusion of multitemporal spaceborne SAR and optical data for urban mapping and urbanization monitoring

Ban, Yifang (författare)
KTH,Geoinformatik
Jacob, Alexander (författare)
KTH,Geodesi och geoinformatik,Geoinformatik
 (creator_code:org_t)
2016-11-30
2016
Engelska.
Ingår i: Remote Sensing and Digital Image Processing. - Cham : Springer. - 1567-3200 .- 2215-1842. ; , s. 107-123
  • Tidskriftsartikel (refereegranskat)
Abstract Ämnesord
Stäng  
  • The overall objective of this research is to evaluate multitemporal spaceborne SAR and optical data for urban land cover mapping and urbanization monitoring. Multitemporal Sentinel-1A SAR and historical ERS SAR and ENVISAT ASAR data as well as HJ-1B multispectral data were acquired in Beijing, Chendgdu and Nanchang, China where rapid urbanization has taken place. KTHSEG, a novel object-based classification method is adopted for urban land cover mapping while KTH-Pavia Urban Extractor, a robust algorithm is improved for urban extent extraction and urbanization monitoring. The research demonstrates that, for urban land cover classification, the fusion of multitemporal SAR and optical data is superior to SAR or optical data alone. The second best classification result is achieved using fusion of 4-date SAR and one HJ-1B image. The results indicate that carefully selected multitemporal SAR dataset and its fusion with optical data could produce nearly as good classification accuracy as the whole multitemporal dataset. The results also show that KTH-SEG, the edge-aware region growing and merging segmentation algorithm, is effective for classification of SAR, optical and their fusion. KTH-SEG outperforms eCognition, the commonly used commercial software, for image segmentation and classification of linear features. For Urban extent extraction, single-date and multitemporal SAR data including ERS SAR, ENVISAT ASAR and Sentinel-1A SAR achieved very promising results in all study areas using the improved KTH-Pavia Urban Extractor. The results showed that urban areas as well as small towns and villages could be well extracted using multitemporal Sentinel-1A SAR data while major urban areas could be well extracted using a single-date single-polarization SAR image. The results clearly demonstrate that multitemporal SAR data are cost- and time-effective way for monitoring spatiotemporal patterns of urbanization.

Ämnesord

NATURVETENSKAP  -- Geovetenskap och miljövetenskap -- Multidisciplinär geovetenskap (hsv//swe)
NATURAL SCIENCES  -- Earth and Related Environmental Sciences -- Geosciences, Multidisciplinary (hsv//eng)

Publikations- och innehållstyp

ref (ämneskategori)
art (ämneskategori)

Hitta via bibliotek

Till lärosätets databas

Hitta mer i SwePub

Av författaren/redakt...
Ban, Yifang
Jacob, Alexander
Om ämnet
NATURVETENSKAP
NATURVETENSKAP
och Geovetenskap och ...
och Multidisciplinär ...
Artiklar i publikationen
Remote Sensing a ...
Av lärosätet
Kungliga Tekniska Högskolan

Sök utanför SwePub

Kungliga biblioteket hanterar dina personuppgifter i enlighet med EU:s dataskyddsförordning (2018), GDPR. Läs mer om hur det funkar här.
Så här hanterar KB dina uppgifter vid användning av denna tjänst.

 
pil uppåt Stäng

Kopiera och spara länken för att återkomma till aktuell vy