Estimating structural properties of riparian forests with airborne lidar data

Abstract

Riparian forest zones adjacent to surface water such as streams, lakes, reservoirs and wetlands maintain significant forest ecosystem functions including nutrient cycling, vegetative communities, water quality, fish and wildlife habitat and landscape aesthetics. In order to support the sustainable management of riparian forests, riparian zones should first be carefully delineated and then structural properties of riparian vegetation, especially forest trees, should be accurately measured. Geographical information system (GIS) techniques have been previously implemented to determine riparian zones quickly and reliably. However, basic measurements of forest structures in riparian areas have relied heavily on field-based surveys, which can be extremely time consuming in large areas. In this study, riparian forest zones were initially located using GIS techniques and then airborne lidar (light detection and ranging) data were used to determine and analyse structural properties (i.e. tree height, crown diameter, canopy closure and vegetation density) of a sample riparian forest. Lidar-derived tree height and crown diameter measurements of sample trees were compared with field-based measurements. Results indicated that 77.92% of the riparian area in the study area was covered by forest. Based on lidar-derived data, the average tree height, total crown width, canopy closure (above 3 m) and vegetation density (3–15 m) were found to be 74.72 m, 16.82 m, 71.15% and 26.05%, respectively. Although we found differences between measurement methods, lidar-derived riparian tree measurements were highly correlated with field measurements for tree height (R ² = 88%) and crown width (R ² = 92%). Differences between measurement methods were likely a result of difficulties associated with field measurements in the dense vegetation that is often associated with forested riparian areas.

Acknowledgements

This study was funded by the Scientific and Technological Research Council of Turkey (TUBITAK) under the International Postdoctoral Research Fellowship Programme-2219.