Tree Density and Forest Productivity in a Heterogeneous Alpine Environment: Insights from Airborne Laser Scanning and Imaging Spectroscopy  
[PERSON]  
1 Remote Sensing Laboratories (RSL), University of Zurich, Winterthurerstrasse 190, 8057 Zurich, Switzerland; [EMAIL_ADDRESS] (A.D.); [EMAIL_ADDRESS] (R.L. ); [EMAIL_ADDRESS] (M.E.S. ); [EMAIL_ADDRESS] (M.K.) 2 Center for Research and Development of Northern Zagros Forests, Faculty of Natural Resources, University of Kurdistan, 66177-15175 Sanandaj, Iran; [EMAIL_ADDRESS]
3 Correspondence: [EMAIL_ADDRESS]; Tel. : +41-44-635-6508  
concentrations [10]) and other natural disturbances such as insect and pathogen attacks [11]. Further, FP information facilitates the design of optimal silivcultural guidelines [12], and multi-temporal assessments of FP have shown a great potential to assess growth patterns of different forest types including virgin, natural or managed forests [13]. TD and FP balance each other since both are determined by the availability of resources, are complementary information variables to characterize forest ecosystems, and are valuable input for broad-scale modeling of biological and biogeochemical processes [14]. Understanding the relationship between FP and TD is important for ecologists and forest managers [15]. However, few studies have exploited inter-dependencies at larger ecosystem scales so far [16]. Further, ecologists are interested in abiotic components such as topography that often has a strong influence on structure, composition, and function of forest ecosystems [17]. Topography (i.e., elevation) has been identified as an easy proxy for resource availability and spatial patterns of ecosystem properties [18]. Changes in elevation, particularly across large gradients, can introduce major changes in community-averaged leaf traits [19], which in turn may affect FP. [PERSON] et al. [20] emphasized the lack of knowledge about the contribution of elevation on plant functional traits at different scales. Such information would allow modeling and prediction of spatial variation in ecosystem processes at any given point along elevation gradients. In addition, the interrelation between FP and TD with elevation can also provide crucial information to determine tree-line elevation [21]. Nevertheless, the assessment of such relations between forest functional and structural attributes remains largely underrepresented at ecosystem scale. Field surveys are still the most accurate approach to collect structural forest attributes [22; 23]. The advantage of the high accuracy achievable is often counterbalanced by substantial costs and difficulties in obtaining information for large, remote, and structurally complex forest areas [3]. Further, providing continuous information of forest attributes typically requires additional interpolation approaches that are prone to error [23]. With the launch of the first Earth observation (EO) satellites in the 1970s, substantial efforts have been conducted to find alternatives to traditional field surveys. Nowadays, the use of EO data and information extraction approaches are an important alternative to complement mapping of forest attributes, particularly for large areas [24; 25; 26]. Estimates of TD from both active and passive EO systems have been widely performed [25; 26; 27; 28; 29]. In particular, airborne laser scanning (ALS) holds a large potential to accurately measure the three-dimensional distribution of forest structural components [30; 31; 32], and has become an essential component for operationalizing forest inventories in various countries [33; 34]. Estimates of TD from ALS data can be obtained either from area-based approaches (ABAs) or from individual tree detection approaches (ITD) [35]. ABAs are often based on empirical relationships between measured TD at plot or stand level and corresponding ALS-derived metrics (e.g., canopy height, height percentiles, canopy closure, and crown diameter) [36; 37].