Forest inventory, which is the first step of forest management planning, is the most difficult stage that requires much time and a lot of efforts. To reduce fieldworks that are considered time consuming and expensive methods of ground measurements, remote sensing data are widely used. Aerial photographs have been an integral part of forest inventory data in Turkey since 1963. Panchromatic and RGBI (Red, Green, Blue, Infrared) aerial photographs acquired by digital aerial cameras proved to be

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... y important in forest inventory. They have maintained their importance for forest management planning process. The aim of this study is to construct a fast and practical inventory model that requires least fieldwork for forest management planning process. Pixel values and vegetation indices (NDVI, DVI, IPVI, RVI and PCA), obtained from remote sensing data, and stand parameters (stand volume, volume increment and number of trees) have been compared statistically. Black pine Pinus nigra J. F. Arnold plantations located in the south-east region of Turkey, Çelikhan Forest Planning Unit, was chosen as a research area. 0.5 meter spacing and 8 bit radiometric resolution Ultracam-X Digital Aerial Photos were used as remote sensing data. According to statistical analysis, IPVI and Green Band values provided the highest evaluation coefficient compared to the models developed for the estimation of stand parameters. Adjusted R square of stand volume, volume increment and the number of tree in the models were found to yield 0.74, 0.73 and 0.50 respectively. It was concluded that stand characteristics estimated by statistical models can be used for forest areas managed for conservation and service purposes.