Savanna woody vegetation classification – now in 3‐D. Issue 1 (21st May 2013)
- Record Type:
- Journal Article
- Title:
- Savanna woody vegetation classification – now in 3‐D. Issue 1 (21st May 2013)
- Main Title:
- Savanna woody vegetation classification – now in 3‐D
- Authors:
- Fisher, Jolene T.
Erasmus, Barend F.N.
Witkowski, Ed T.F.
van, Jan
Wessels, Konrad J.
Asner, Gregory P.
Schmidtlein, Sebastian - Abstract:
- <abstract abstract-type="main" id="avsc12048-abs-0001"> <title>Abstract</title> <sec id="avsc12048-sec-0001" sec-type="section"> <title>Question</title> <p>The co‐existence of woody plants and grasses characterize savannas, with the horizontal and vertical spatial arrangement of trees creating a heterogeneous biotic environment. To understand the influence of biogeophysical drivers on the spatial patterns of 3‐D structure of woody vegetation, these patterns need to be explained over large areas to capture the context. Is there a spatially explicit, ecologically meaningful way to capture the patterns and context of 3‐D woody vegetation structure?</p> </sec> <sec id="avsc12048-sec-0002" sec-type="section"> <title>Location</title> <p>Classification development and testing sites: landscapes in Bushbuckridge Municipality, Sabi Sand Wildtuin and Kruger National Park, Mpumalanga province, north‐east South Africa.</p> </sec> <sec id="avsc12048-sec-0003" sec-type="section"> <title>Methods</title> <p>The aforementioned structural classification approach requires appropriate 3‐D and spatially explicit remote sensing data. A LiDAR‐based canopy height model (CHM) and volumetric pixel (voxel) data from the Carnegie Airborne Observatory Alpha system were used to create the structural classification. First, we segmented the CHM images using multi‐threshold and multi‐resolution image segmentation techniques, and classified the image segments into four height classes, namely shrub (1–3 m),<abstract abstract-type="main" id="avsc12048-abs-0001"> <title>Abstract</title> <sec id="avsc12048-sec-0001" sec-type="section"> <title>Question</title> <p>The co‐existence of woody plants and grasses characterize savannas, with the horizontal and vertical spatial arrangement of trees creating a heterogeneous biotic environment. To understand the influence of biogeophysical drivers on the spatial patterns of 3‐D structure of woody vegetation, these patterns need to be explained over large areas to capture the context. Is there a spatially explicit, ecologically meaningful way to capture the patterns and context of 3‐D woody vegetation structure?</p> </sec> <sec id="avsc12048-sec-0002" sec-type="section"> <title>Location</title> <p>Classification development and testing sites: landscapes in Bushbuckridge Municipality, Sabi Sand Wildtuin and Kruger National Park, Mpumalanga province, north‐east South Africa.</p> </sec> <sec id="avsc12048-sec-0003" sec-type="section"> <title>Methods</title> <p>The aforementioned structural classification approach requires appropriate 3‐D and spatially explicit remote sensing data. A LiDAR‐based canopy height model (CHM) and volumetric pixel (voxel) data from the Carnegie Airborne Observatory Alpha system were used to create the structural classification. First, we segmented the CHM images using multi‐threshold and multi‐resolution image segmentation techniques, and classified the image segments into four height classes, namely shrub (1–3 m), low tree (3–6 m), high tree (6–10 m) or tall tree (&gt;10 m). A hierarchical <italic>a priori</italic> approach was used to develop classification criteria. The following metrics were calculated for 0.25‐ha grid cells based on the cover and spatial arrangement of the four height classes: canopy cover, sub‐canopy cover, canopy layers, Simpson's diversity index and cohesion. Top of canopy vegetation was classified using each metric at the 0.25‐ha scale, with canopy cover being the primary classification metric. Subsequently, individual layers identified within the canopy were classified using the voxel data. We use a code system for describing classes to ensure standardization between different regions; a more traditional naming system may be used in addition for interpretation.</p> </sec> <sec id="avsc12048-sec-0004" sec-type="section"> <title>Conclusion</title> <p>This system provides a more comprehensive classification of the horizontal and vertical structural diversity of savannas compared to the traditional vegetation classification systems. The description of multi‐layers within the canopy should allow for a sensitive change detection method. The classification can be used in many current focus areas, including habitat suitability mapping for biodiversity conservation, strategic adaptive management and monitoring land‐cover change.</p> </sec> </abstract> … (more)
- Is Part Of:
- Applied vegetation science. Volume 17:Issue 1(2014:Jan.)
- Journal:
- Applied vegetation science
- Issue:
- Volume 17:Issue 1(2014:Jan.)
- Issue Display:
- Volume 17, Issue 1 (2014)
- Year:
- 2014
- Volume:
- 17
- Issue:
- 1
- Issue Sort Value:
- 2014-0017-0001-0000
- Page Start:
- 172
- Page End:
- 184
- Publication Date:
- 2013-05-21
- Subjects:
- Plant ecology -- Periodicals
Plant communities -- Periodicals
Plant populations -- Periodicals
Nature -- Effect of human beings on -- Periodicals
581.705 - Journal URLs:
- http://onlinelibrary.wiley.com/journal/10.1111/(ISSN)1654-109X ↗
http://www.bioone.org/bioone/?request=get-journals-list&issn=1402-2001 ↗
http://www.jstor.org/journals/14022001.html ↗
http://onlinelibrary.wiley.com/ ↗ - DOI:
- 10.1111/avsc.12048 ↗
- Languages:
- English
- ISSNs:
- 1402-2001
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 1580.113100
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 3589.xml