At the landscape-level, remote sensing can support many aspects of fire sellekchem management. Fuel and fire studies utilizing remotely sensed data such as Landsat, MODIS, SPOT and AVHRR can read this provide valuable information on fuel moisture [21], fuel characteristics [22, 23, 24], fire risk and danger, and fire frequency [15, 25, 26]. On the Inhibitors,Modulators,Libraries local scale, the use of Lidar [27, 28] and airborne hyperspectral sensors, such as multispectral infrared and visible imaging spectrometer (MIVIS) [18] and airborne visible/infrared imaging spectrometer (AVIRIS) data [2] allow the measurement of the three-dimensional structure of the canopy. These have been widely used to analyze vertical forest structure and to estimate critical parameters for fire behavior such as crown Inhibitors,Modulators,Libraries bulk density, tree height and basal area, [28-32].
In addition, using such airborne hyperspectral sensors, remote sensing techniques can provide new information concerning the canopy layer and vegetation Inhibitors,Modulators,Libraries Inhibitors,Modulators,Libraries parameters such as height, crown dimensions, volume and biomass [32-36] and detailed spatial information on forest attributes that may be relevant to spatial fire behavior models Inhibitors,Modulators,Libraries [32, 37].The objective of this study is to determine forest stand parameters using remotely sensed data in a case study area Inhibitors,Modulators,Libraries in northwestern Turkey. The research focuses on classifying and mapping the stand parameters such as stages of stand development, crown closure, stand types, and land cover using the spatial analysis functions of GIS.2.
?Study AreaKorudag Forest District, an area particularly vulnerable to forest fires due to its ecological characteristics and prevailing wind patterns, is a sub-temperate forest zone covering an area of 18,506 ha along the coast of the Saros Gulf in Inhibitors,Modulators,Libraries the north of Eagan Sea, northwestern Turkey (470600�C492500 Inhibitors,Modulators,Libraries E, 4499750-4515600 N, UTM ED 50 datum Zone 35N) (Figure 1). The altitude varies between 0 and 700 m above sea level with an average slope of 12%. The vegetation is composed of calabrian pine (Pinus brutia Ten.), Anatolian black pine (P. nigra J.F. Arnold subsp.), Quercus spp. and shrubs.Figure AV-951 1.The geographic location of the study area.The data used in this research are forest cover type maps of 1/25 000 scale for the years 1980, 1995 and 2004, a Landsat TM satellite image of 11.
05.1987 and a Landsat ETM image of 25.07.2000.
BAY 73-4506 The forest cover types, used as ground truthing, were originally generated from both the stereo interpretation of black and white aerial photos with an average 1/25 000 scale and ground measurements with 300��300 sampling points. The Landsat images were interpreted with ERDAS image analysis program.3.?Materials and Methods3.1. Geometric Correction of Landsat Carfilzomib such information Images and Digitizing Stand Type MapsSubsets of satellite images were rectified using 1/25,000 scale Topographical Maps with UTM projection (ED 50 datum) using first order nearest neighbour rules.