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Measuring biomass and carbon in delaware using an airborne profiling LIDAR

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A portable, inexpensive profiling light detection and ranging (LIDAR) system was used to inventory forests in Delaware, a small state (5205 km 2 ) on the mid-Atlantic seaboard of the USA. Ground and airborne sampling procedures are described, and large-area inventory results are reported and compared to independent estimates. Systematic airborne LIDAR profiling measurements were used (1) to estimate forest merchantable volume, biomass and above-ground carbon statewide; and (2) to estimate impervious surface and open water area. Over 1300 km of laser profiling data acquired along parallel flight lines 4 km apart were analysed. Four explicitly linear models were considered to predict merchantable volume and total above-ground dry biomass. Merchantable volume estimates were within 21% of US Forest Service estimates at the county level and within 1% statewide. Total above-ground dry biomass estimates were within 22% of USFS estimates at the county level and within 16% statewide. LIDAR estimates of percentage impervious area surface for the three counties (Newcastle, Kent and Sussex) were 10.9, 3.4 and 2.8%, respectively, and 4.7% statewide. Comparable estimates developed using 30 m Enhanced Thematic Mapper digital data and mixture modelling were 8.8, 3.5 and 3.9%, respectively, and 4.9% statewide. Laser estimates of open water at the county and state level were comparable to 1997 Geographical Information System (GIS) estimates. Open water estimates based on laser transect data showed the three counties to have 3.0, 2.0 and 4.6% of their county area covered by water, and 3.5% of the state to be covered by open water. Comparable 1997 GIS estimates were 2.6, 2.1 and 4.8% (county), and 3.5% (state), respectively. The results of the study indicate that line intercept sampling techniques can be used in conjunction with a relatively inexpensive, portable airborne laser system to assess multiple resources regionally.
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Keywords: Airborne laser profiling; forest biomass; regional forest inventory

Document Type: Research Article

Publication date: 2004-12-01

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