The critical role of geographic information system (GIS) and remote sensing (RS) in forest site classification and mapping


Günlü A., Kadioʇullari A. I., Başkent E. Z., GÜNEY D., Buyuksalih G.

7th International Symposium on Spatial Accuracy Assessment in Natural Resources and Environmental Sciences, ACCURACY 2006, Lisbon, Portekiz, 5 - 07 Temmuz 2006, ss.595-602 identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Basıldığı Şehir: Lisbon
  • Basıldığı Ülke: Portekiz
  • Sayfa Sayıları: ss.595-602
  • Anahtar Kelimeler: Forest site classification, Geographic information system, Remote sensing
  • İstanbul Üniversitesi Adresli: Hayır

Özet

It is essential that forest sites be characterized and classified to realize effective planning and implementation of sustainable forest management activities or regulations. Developing as well as conducting harvesting activities on the ground in the absence of forest site information is highly ineffective or insufficient, calling for recognizing the potential production capacity and conditions of forest sites. Forest site classification has been of a major problem in Turkish forestry. In Turkey, the productivity of forest sites has been determined with solo wood production objective in forest management using the dominant height at a reference age. However, forests sites have to be determined based on various factors such as landscape structure, climatic profile, biotic features and soil characteristics, as typical site parameters. This direct process is highly time demanding, expensive and hard to conduct, necessitating the use of information technologies such as Geographic Information System (GIS) and Remote Sensing (RS). This research was therefore designed to demonstrate the integrated use of GIS and RS in characterizing, classifying and mapping forest sites in Genya Mountain, located in central Management District in Artvin State Forest Enterprise of Turkey. The ground measurement data, used as ground truth data, was correlated with the supervised classification of the Landsat ETM (2001) image.