||With diversification of societal demand on forest resources, forest inventory programs have evolved to a multiresource basis. This significantly increases financial burden on current programs. Implementing efficient sampling designs and innovating measurement equipment are ways to meet this challenge. Growing stock of a forest is a statistics that serves as a proxy for many forest ecosystem services such as carbon sequestration and biodiversity. Critical Height Sampling (CHS), an extension of Horizontal Point Sampling (HPS), is a sampling design with selection probabilities proportional to growing stock. Thus, CHS would be efficient in collecting information on non-timber forest products, but it is understudied probably due to equipment cost. Diameter at breast height (DBH), upper-stem diameters, height and spatial location increases accuracy in estimating and projecting growing stock, but measuring them are time consuming. As the saying goes, “a picture is worth a thousand words”, implying that a photograph contains a large amount of information. Spherical photogrammetry is a process that extracts measurements from a spherical panorama, which has 180° vertical by 360° horizontal full view of forest environment at a location. It has many advantages: inexpensive camera equipment, no requirement of specialized skills, and simultaneous extraction of multiple tree attributes. It is widely applied in other natural sciences but is underexplored in forest mensuration. Thus, the overarching goal of this project is application of spherical photogrammetry to forest sampling and tree measurement. This project has four specific objectives. The first objective to be completed in the first year is assessing accuracy in measuring tree attributes with spherical photogrammetry. Distance scale, which is actual length represented by a pixel, needs to be first determined for every pixel in a panorama prior to measurement. Three methods in calculating distance scale are compared. Furthermore, forest structures affects light availability under canopy, which in turns could affect quality of panoramas and accuracy of measurement. The second objective to be completed in the second year is studying efficiency of applying spherical photogrammetry to HPS and CHS. A time study comparing traditional field methods to spherical photogrammetry is carried out. Trees hidden in panoramas are a major issue that could cause bias in growing stock estimation. A double sampling approach to derive a correction factor is tested. The third year focuses on software development and biodiversity assessment, which are the third and fourth objectives, respectively. An open source software that automates selection of sample trees by CHS or HPS and tree measurement in panoramas will facilitate applications of spherical photogrammetry in the field. Furthermore, potential of using spherical panoramas in plant species identification is explored. Field assessment is planned for the first two year research in plantation and naturally regenerated forests of single and multispecies, and of coniferous and deciduous composition.