Bottomland Hardwood Restoration Monitoring

Submitted by atripp on

Vegetation growth is important to monitor in areas undergoing restoration. Color imagery collected using an unmanned aircraft system (UAS) at a bottomland hardwood restoration site in northeast Indiana was used to derive a vegetation height model using Structure from Motion (SfM) image processing. Data from that model were then compared to vegetation height data collected in field plots. UAS data were equally as effective as field data in detecting age-related height trends and classifying vegetation into standardized height classes. UAS-based data collection has the added advantage of sampling larger areas in less time, providing a more comprehensive assessment of vegetation development on the site. The relative biases of field and UAS-based data are being identified and explored.

Vegetation height model derived from UAS-collected color imagery for a bottomland restoration site in northeast Indiana. Yellow circles indicate UAS sample areas co-located with field plot locations, but analyses of UAS data were also performed at the treatment (restoration year) level.


Author Name
Matthew Struckhoff
Author Email