Volume XL-1/W3
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-1/W3, 159-164, 2013
https://doi.org/10.5194/isprsarchives-XL-1-W3-159-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-1/W3, 159-164, 2013
https://doi.org/10.5194/isprsarchives-XL-1-W3-159-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.

  24 Sep 2013

24 Sep 2013

CANOPY DENSITY MAPPING ON ULTRACAM-D AERIAL IMAGERY IN ZAGROS WOODLANDS, IRAN

Y. Erfanifard and Z. Khodaee Y. Erfanifard and Z. Khodaee
  • Dept. of Desert Management, College of Agriculture, Shiraz University, Shiraz, Iran

Keywords: Canopy density map, kNN, UltraCam-D imagery, Woodland, Zagros

Abstract. Canopy density maps express different characteristics of forest stands, especially in woodlands. Obtaining such maps by field measurements is so expensive and time-consuming. It seems necessary to find suitable techniques to produce these maps to be used in sustainable management of woodland ecosystems. In this research, a robust procedure was suggested to obtain these maps by very high spatial resolution aerial imagery. It was aimed to produce canopy density maps by UltraCam-D aerial imagery, newly taken in Zagros woodlands by Iran National Geographic Organization (NGO), in this study. A 30 ha plot of Persian oak (Quercus persica) coppice trees was selected in Zagros woodlands, Iran. The very high spatial resolution aerial imagery of the plot purchased from NGO, was classified by kNN technique and the tree crowns were extracted precisely. The canopy density was determined in each cell of different meshes with different sizes overlaid on the study area map. The accuracy of the final maps was investigated by the ground truth obtained by complete field measurements. The results showed that the proposed method of obtaining canopy density maps was efficient enough in the study area. The final canopy density map obtained by a mesh with 30 Ar (3000 m2) cell size had 80% overall accuracy and 0.61 KHAT coefficient of agreement which shows a great agreement with the observed samples. This method can also be tested in other case studies to reveal its capability in canopy density map production in woodlands.