Abstract:
The purpose of this study is to use the Unmanned Aerial Systems (UAS) images for mapping
wetland vegetation using object-based classification methods and to compare its performance
with cropland data layers. The UAS imagery (~0.1-m resolution) and National Agriculture
Imagery Program (~0.6-m) data were used to extract wetland vegetation using object-based
classification methods in ArcGIS Pro. Spectral indices, such as green chromatic coordinate
(GCC) and normalized difference vegetation index (NDVI) coupled with unsupervised
classification have been used for vegetation classification. UAS imagery performed slightly
better than NAIP for classification yielding 49% vegetation in 2019, while it was 45% in 2018
and 35% in 2016 for NAIP classification. According to cropland data classification, open
water land cover class also covered a large portion of the study area. In conclusion, object based classification using high-resolution imagery has good potential to integrate with
ground survey to implement best management practices for restoring wetlands.
