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- Holmgren, Helén, 1970-
(författare)
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Case i bokföring
- 2013
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Bok (övrigt vetenskapligt/konstnärligt)
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| 2. |
- Nordkvist, Karin, et al.
(författare)
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Classification of EBONE General Habitat Categories in a Swedish forest area by using LiDAR in combination with SPOT satellite data
- 2010
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Rapport (övrigt vetenskapligt/konstnärligt)abstract
- We have investigated to which degree a combination of optical satellite data and LiDAR data can improve classification accuracy of the General Habitat Categories (GHC) used by the FP7 project European Biodiversity Observation Network (EBONE), compared to using satellite data alone. The study was carried out in Remningstorp, a forest dominated area in southern Sweden. Remote sensing data used in the study were a SPOT 5 image from August 2009 and a laser scanning (26 points/m2) from September 2008. Ground truth samples were collected by interpretation of color infrared digital air photos from September 2009. Maximum likelihood and Random Forests classifications were made with satellite data and with a combination of satellite and LiDAR data. The classification scheme consisted of six forest classes, arable land and pasture land. The use of LiDAR data improved over-all accuracy with 6% for maximum likelihood classification and 7% for Random Forests. The highest over-all accuracy was obtained with Random Forests, but on the expense of the smaller classes.
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| 3. |
- Nordkvist, Karin, et al.
(författare)
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Combining optical satellite data and airborne laser scanner data for vegetation classification
- 2012
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Ingår i: Remote Sensing Letters. - : Informa UK Limited. - 2150-704X .- 2150-7058. ; 3, s. 393-401
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Tidskriftsartikel (refereegranskat)abstract
- The aim of this study was to investigate to which degree the accuracy of vegetation classification could be improved by combining optical satellite data and airborne laser scanner (ALS) data, compared with using satellite data only. A Satellite Pour l'Observation de la Terre (SPOT) 5 scene and Leica ALS 50-II data from 2009, covering a test area in the mid-Sweden (latitude 60 degrees 43' N, longitude 16 degrees 43' E), were used in maximum likelihood and decision tree classifications. Training and validation data were obtained from the interpretation of digital aerial photo stereo models. Combination of SPOT and ALS data gave classification accuracies up to 72%, compared with 56% using only SPOT data. This indicates that integrating features from large area laser scanning may lead to significant improvements in satellite data-based vegetation classifications.
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