However, according to direct method, forest site classification process is highly time-demanding, 1|]# expensive and hard to conduct for large areas. Thus, it necessitates the use of powerful information technologies such as GIS and Remote Sensing (RS) to help develop forest site maps, such information technologies should be utilized effectively.This study focuses on identifying forest sites using direct, indirect and remote sensing methods in a research area of Sinop-Ayanc?k-Goldag Inhibitors,Modulators,Libraries Forest District located in northern part of Turkey. Part of the research relate to classifying and mapping the forest sites with the spatial analysis functions of GIS. Additionally, forest site productivity values determined by direct method, indirect method and RSM were compared and contrasted to evaluate the potential use of the methods.
2.?Study Inhibitors,Modulators,Libraries AreaThe study area was the Goldag forest Inhibitors,Modulators,Libraries planning unit with 600 ha, a part of Sinop-Ayanc?k province Inhibitors,Modulators,Libraries located in the central Black Sea Region, Turkey (647000-650000 E. 4629000-4632000 N. UTM ED 50 datum Zone 36 N, Figure 1). Elevation ranges from 500 m to 970 m with an average of 775 m. The study area is situated on a steep terrain, topographic surface with a slope ranging from 10% to 60%, with an average of 26%. Average annual temperature reaches a maximum of 27.6��C in the summer and a minimum of 13.8��C in the winter with an average annual temperature of 17.6��C. Average annual precipitation in the study area is 677.3 mm [11]. Generally, soils tend to be heavy clay type.
The study area is covered with unmanaged, even-aged, pure stands of oriental beech (Fagus orientalis Lipsky.
).Figure 1.The geographic location of the study area surrounded with solid red lines.3.?DatasetThe research accommodates both the satellite data and Inhibitors,Modulators,Libraries forest inventory data obtained Inhibitors,Modulators,Libraries from ground measurements for classifying and interpreting forest sites with respect to the degree of site productivity. The topographic features such as elevation-climate zone, aspect, slope and landform were used to delineate the sites. Forest site classification was performed based on edaphic (soil properties), topographic (altitude, Inhibitors,Modulators,Libraries slope, aspect and landform) and climate (precipitation and temperature) factors.
As for the ground measurements, a total of 70 sample Inhibitors,Modulators,Libraries plots were established with 300 �� 300 m grids and the necessary measurements were taken in each sample plot.
In each sample plot, a soil pit was dug up to bedrock or to a minimum depth Cilengitide of 1 m. All soil profiles were described and classified. Approximately, 1 quart of rock-free soil was collected from each horizon in each soil pit. Soil samples were air-dried, ground and sieved through a 2 mm-mesh-sized nothing sieve before further Brefeldin_A selleck chemical analysis. Also noted were some soil characteristics such as stone content, thickness of the horizons and physiological soil depth.