the field of forestry has evolved to meet several objectives, including timber and other forest product production, tourism and recreation, habitat and wildlife management and climate change monitoring. as the field encompasses and affects several values, both public and private, the management of the forest and its properties needs to be efficient, timely, and accurate. as a result, there has been a lot of investment put into forest monitoring strategies, particularly with remote sensing. several researchers have investigated the use of spectral indices to acquire certain forest attributes, such as biomass and characteristics of forest structure (age, basal area, species composition, etc.). though spectral indices employed on multispectral images have been proven beneficial, other techniques such as texture analysis, hyperspectral remote sensing, radar, and lidar may be more useful in discriminating quantitative features of the forest and be favourable in certain applications, such as understory characterization. studies of various spectral indices and other remote sensing techniques have been explored to determine their relatability and accuracy, to determine their usefulness in acquiring measurable properties in the forest. as technology and information advances, hopefully their capabilities will too.