Nelson, R, Ranson, KJ, Sun, G, Kimes, DS, Kharuk, V, Montesano, P (2009). Estimating Siberian timber volume using MODIS and ICESat/GLAS. REMOTE SENSING OF ENVIRONMENT, 113(3), 691-701.
Geosciences Laser Altimeter System (GLAS) space LiDAR data are used to attribute a MODerate resolution Imaging Spectrometer (MODIS) 500 m land cover classification of a 10 degrees latitude by 12 degrees longitude study area in south-central Siberia. Timber volume estimates are generated for 16 forest classes, i.e., four forest cover types x four canopy density classes, across this 811,414 km(2) area and compared with a ground-based regional volume estimate. Two regional GLAS/MODIS timber volume products, one considering only those pulses falling on slopes <= 10 degrees and one utilizing all GLAS pulses regardless of slope, are generated. Using a two-phase (GLAS-ground plot) sampling design, GLAS/MODIS volumes average 163.4 +/- 11.8 m(3)/ha across all 16 forest classes based on GLAS pulses on slopes <= 10 degrees and 171.9 +/- 12.4 m(3)/ha considering GLAS shots on all slopes. The increase in regional GLAS volume per-hectare estimates as a function of increasing slope most likely illustrate the effects of vertical waveform expansion due to the convolution of topography with the forest canopy response. A comparable, independent, ground-based estimate is 146 m(3)/ha [Shepashenko, D., Shvidenko, A., and Nilsson, S. (1998). Phytomass (live biomass) and carbon of Siberian forests. Biomass and Bioenergy, 14, 21-31], a difference of 11.9% and 17.7% for GLAS shots on slopes <= 10 degrees and all GLAS shots regardless of slope, respectively. A ground-based estimate of total volume for the entire study area, 7.46 x 109 m(3). is derived using Shepashenko et al.'s per-hectare volume estimate in conjunction with forest area derived from a 1990 forest map [Grasia, M.G. (ed.). (1990). Forest Map of USSR. Soyuzgiproleskhoz, Moscow, RU. Scale: 1:2,500,000]. The comparable GLAS/MODIS estimate is 7.38 x 10(9) m(3), a difference of less than 1.1 %. Results indicate that GLAS data can be used to attribute digital land cover maps to estimate forest resources over subcontinental areas encompassing hundreds of thousands of square kilometers. Published by Elsevier Inc.