ResearchSpace

Field Sampling from a Segmented Image

Show simple item record

dc.contributor.author Debba, Pravesh
dc.contributor.author Stein, A
dc.contributor.author Van der Meer, FD
dc.contributor.author Carranza, EJM
dc.contributor.author Lucieer, A
dc.date.accessioned 2008-07-25T12:06:22Z
dc.date.available 2008-07-25T12:06:22Z
dc.date.issued 2008-06
dc.identifier.citation Debba P et al. 2008. Field Sampling from a Segmented Image. Computational science and its applications (ICCSA 2008) International Conference, Perugia, Italy, June 30 - July 3, 2008; Part I, pp 756-768 en
dc.identifier.isbn 978-3-540-69838-8
dc.identifier.uri http://www.springerlink.com/content/12185225j16k6129/?p=bf0a90f1833f409fa12d01e52e6a353e&pi=54
dc.identifier.uri http://hdl.handle.net/10204/2334
dc.description The original publication is available at www.springerlink.com en
dc.description.abstract This paper presents a statistical method for deriving the optimal prospective field sampling scheme on a remote sensing image to represent different categories in the field. The iterated conditional modes algorithm (ICM) is used for segmentation followed by simulated annealing within each category. Derived field sampling points are more intense in heterogeneous segments. This method is applied to airborne hyperspectral data from an agricultural field. The optimized sampling scheme shows superiority to simple random sampling and rectangular grid sampling in estimating common vegetation indices and is thus more representative of the whole study area. en
dc.language.iso en en
dc.publisher Springer-Verlag Berlin Heidelberg en
dc.subject Iterated conditional modes en
dc.subject Vegetational studies en
dc.title Field Sampling from a Segmented Image en
dc.type Article en
dc.identifier.apacitation Debba, P., Stein, A., Van der Meer, F., Carranza, E., & Lucieer, A. (2008). Field Sampling from a Segmented Image. http://hdl.handle.net/10204/2334 en_ZA
dc.identifier.chicagocitation Debba, Pravesh, A Stein, FD Van der Meer, EJM Carranza, and A Lucieer "Field Sampling from a Segmented Image." (2008) http://hdl.handle.net/10204/2334 en_ZA
dc.identifier.vancouvercitation Debba P, Stein A, Van der Meer F, Carranza E, Lucieer A. Field Sampling from a Segmented Image. 2008; http://hdl.handle.net/10204/2334. en_ZA
dc.identifier.ris TY - Article AU - Debba, Pravesh AU - Stein, A AU - Van der Meer, FD AU - Carranza, EJM AU - Lucieer, A AB - This paper presents a statistical method for deriving the optimal prospective field sampling scheme on a remote sensing image to represent different categories in the field. The iterated conditional modes algorithm (ICM) is used for segmentation followed by simulated annealing within each category. Derived field sampling points are more intense in heterogeneous segments. This method is applied to airborne hyperspectral data from an agricultural field. The optimized sampling scheme shows superiority to simple random sampling and rectangular grid sampling in estimating common vegetation indices and is thus more representative of the whole study area. DA - 2008-06 DB - ResearchSpace DP - CSIR KW - Iterated conditional modes KW - Vegetational studies LK - https://researchspace.csir.co.za PY - 2008 SM - 978-3-540-69838-8 T1 - Field Sampling from a Segmented Image TI - Field Sampling from a Segmented Image UR - http://hdl.handle.net/10204/2334 ER - en_ZA


Files in this item

Thumbnail
Name: Debba_2008.pdf
Size: 1.113Mb
Format: PDF
View/Open
Icon
Name: Debba2_2008.pdf
Size: 975.2Kb
Format: PDF
View/Open

This item appears in the following Collection(s)

Show simple item record