Paper Info
Title
Area-Based Approach for Mapping and Monitoring Riverine Vegetation Using Mobile Laser Scanning
Abstract
Vegetation plays an important role in stabilizing the soil and decreasing fluvial erosion. In certain cases, vegetation increases the accumulation of fine sediments. Efficient and accurate methods are required for mapping and monitoring changes in the fluvial environment. Here, we develop an area-based approach for mapping and monitoring the vegetation structure along a river channel. First, a 2 x 2 m grid was placed over the study area. Metrics describing vegetation density and height were derived from mobile laser-scanning (MLS) data and used to predict the variables in the nearest-neighbor (NN) estimations. The training data were obtained from aerial images. The vegetation cover type was classified into the following four classes: bare ground, field layer, shrub layer, and canopy layer. Multi-temporal MLS data sets were applied to the change detection of riverine vegetation. This approach successfully classified vegetation cover with an overall classification accuracy of 72.6%; classification accuracies for bare ground, field layer, shrub layer, and canopy layer were 79.5%, 35.0%, 45.2% and 100.0%, respectively. Vegetation changes were detected primarily in outer river bends. These results proved that our approach was suitable for mapping riverine vegetation.
Year
DOI
Venue
2013
10.3390/rs5105285
REMOTE SENSING
Keywords
Field
DocType
LiDAR,mobile laser scanning (MLS),riverine environment,river bank,vegetation,change detection
Sediment,Vegetation,Hydrology,Remote sensing,Shrub,Channel (geography),Lidar,Bank,Geology,Fluvial,Canopy
Journal
Volume
Issue
Citations 
5
10
2
PageRank 
References 
Authors
0.42
11
10
Name
Order
Citations
PageRank
ninni saarinen163.53
Mikko Vastaranta229834.91
Matti Vaaja38410.00
eliisa lotsari420.42
Anttoni Jaakkola534430.30
Antero Kukko648347.44
Harri Kaartinen760863.10
Markus Holopainen835740.95
Hannu Hyyppa920223.16
Petteri Alho10969.09