JW Roberts
Council for Scientific and Industrial Research, Natural Resources and the Environment, Ecosystems, Forestry and Forest Products Research Centre, PO Box 17001, Congella 4013, South Africa
S Tesfamichael
Council for Scientific and Industrial Research, Natural Resources and the Environment, Ecosystems, Forestry and Forest Products Research Centre, PO Box 17001, Congella 4013, South Africa
M Gebreslasie
Council for Scientific and Industrial Research, Natural Resources and the Environment, Ecosystems, Forestry and Forest Products Research Centre, PO Box 17001, Congella 4013, South Africa
J van Aardt
Council for Scientific and Industrial Research, Natural Resources and the Environment, Ecosystems, Earth Observation, PO Box 395, Pretoria 0001, South Africa
FB Ahmed
School of Environmental Sciences, University of KwaZulu-Natal, King George V Avenue, Glenwood, Durban 4041, South Africa
Abstract
The Forestry and Forest Products Research Centre (CSIR), University of KwaZulu-Natal and MONDI Business Paper have recently embarked on a remote sensing cooperative. The primary focus of this cooperative is to explore the potential benefits associated with using remote sensing for forestry-related activities. A subproject within the cooperative is exploring the utility of various remote sensing technologies for forest structural assessment. This paper reports on the primary findings of a state-of-the-art review conducted by members of the cooperative and seeks to inform and contribute to the development of focused research projects. Both active and passive sensors are reviewed at varying spatial scales focusing primarily on accuracies attained. Medium-resolution studies focus on contextual forest attributes while high-resolution studies focused on location-based forest variables. Results from research consulted indicate that while remote sensing has a strong theoretical background, there are several limiting factors that need to be explored within a South African context. These include the saturation of satellite signals in mature forests, underestimation of tree heights using LiDAR data and the cost of LiDAR surveys. The review ends with recommendations for future research activities.
Keywords: forest assessment, LiDAR, multispectral, remote sensing, Synthetic Aperture Radar
Southern Hemisphere Forestry Journal 2007, 69(3): 183–203