Site index is the most commonly used measure of potential site productivity. This simple metric relates the expected height at a given base age (usually 50 years). Knowing site index helps you manage the given stocking of a forest site, estimating growth, and forcasting timber yields. Depending on various factors, site index may vary between sites. Tools such as Web Soil Survey or SoilWeb provide access to estimated site index based on soil type interpretations developed by the Natural Resources Conservation Service.
Site index can be observed in the field by coring or cutting down a tree of known height, counting tree rings to estimate the age, and plotting the results on a site index chart, finding the value on a table, or calculating using an equation. The height to age relationship that forms the site index concept are developed from published observational dendrochronological studies, usually based on tens or hundreds of field-measured samples. As forestry studies have matured, long-term growth and yield studies with repeated measurements and other continuous inventory data have provided a further source of site index information.
Careers have been made of relating site index to various soil characteristics, landforms, or other geological, geomorphic variables, in an attempt to explain the observations of varied site-species performance and expression of potential site productivity.
Recently, new remote-sensing based methods have been developed that benefit from the vast archive of aerial and satellite-based imagery to identify and construct stands by their origin year. These use either structure-from motion to develop digital surface models at a previous point in time (Véga and St-Onge 2009), and thereby estimate the height growth to current conditions as estimated by LiDAR-based canopy height derviatives, or estimate the stand age and relate to its current height using change-detection methodology to determine origin year (Gopalakrishnan et al 2019). These remote-sensing based methods previously would never have been able to be performed at the spatial extents as reported, except for the introduction of high-performance and distributed, cloud-based computing that facilitates such analyses. Indeed, these studies led insights into the accuracy of established guides to site index (i.e. soil interpretations) and the potential improvements in growth and yield that have been realized from genetic improvement programs, site preparation and competing vegetation techniques over stands of natural origin or earlier studies of forest plantation performance. Expressed site index and yields on a given site may have significantly increased with improved genetics and cultural methods. Or perhaps we are seeing recovery of eroded lands combined with the effects of a changing climate making growing conditions more ideal for the site index species? As with any forestry problem, there are many factors to consider and explore.
Below are the citations and links to the studies mentioned in this article:
Using historical aerial imagery to map landscape-level site index values
Landsat Satellite-based change detection to estimate stand origin year and relate to LiDAR estimated height
