The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Publications Copernicus
Articles | Volume XL-7/W3
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-7/W3, 521–524, 2015
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-7/W3, 521–524, 2015

  29 Apr 2015

29 Apr 2015

Tree number estimation with the use of VHR natural colour orthophotos over a heterogeneous landscape in northern Greece

P. Stournara1, M. Tsakiri-Strati1, S. Siachalou1, G. Doxani1, G. Mallinis2, and V. Tsioukas1 P. Stournara et al.
  • 1Aristotle University of Thessaloniki (AUTH), School of Rural and Surveying Engineering, Thessaloniki, Greece
  • 2Democritus University of Thrace (DUTH), Department of Forestry and Management of the Environment and Natural Resources, Orestiada, Thrace, Greece

Keywords: VHR orthophotos, Forest management, Tree number, Tree crown detection, Local Maxima

Abstract. Spatial explicit knowledge regarding the quantity and the spatial distribution of forest parameters is crucial for sustainable forest management, as well as in fulfilling national reporting needs in the framework of international treaties (i.e. Kyoto Protocol, FAO, EFFIS etc). Especially, tree number which can be used for assessing forest tree density (tree number/ha), is among the most important and laboursome parameters to be measured in the field. The aim of this study is to estimate tree number based on the use of nationwide, freely available, very high spatial resolution orthophotos acquired from Greek National Cadastre and Mapping Agency during the 2007-2009 period. The study area is the University Forest of Taxiarchis, which is located in central Halkidiki, Northern Greece. The dominant species of the forest includes both broadleaves (oak, beech) and coniferous species (Black pine, Calabrian pine), which are found in both pure and mixed stands. Tree crown detection was tested on natural color orthophoto bands in several plots. The principal components and intensity-hue-saturation transformations were also applied in order to enhance tree detection accuracy. Local maxima technique was utilized for tree crown detection. Accuracy results were evaluated based on field plot data available from the official forest management plan of the area completed in 2011. Overall, the detection accuracy exceeded 50% which is deemed satisfactory considering also the heterogeneity of the Mediterranean landscape and the limited spectral resolution of the remote sensing data available.