Analyzing Impact of Types of UAV-Derived Images on the Object-Based Classification of Land Cover in an Urban Area
The development of UAV sensors has made it possible to obtain a diverse array of spectral images in a single flight. In this study, high-resolution UAV-derived images of urban areas were employed to create land cover maps, including car-road, sidewalk, and street vegetation. A total of nine orthoima...
Main Authors: | Geonung Park, Kyunghun Park, Bonggeun Song, Hungkyu Lee |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2022-03-01
|
Series: | Drones |
Subjects: | |
Online Access: | https://www.mdpi.com/2504-446X/6/3/71 |
Similar Items
-
Integrating a UAV-Derived DEM in Object-Based Image Analysis Increases Habitat Classification Accuracy on Coral Reefs
by: Brian O. Nieuwenhuis, et al.
Published: (2022-10-01) -
Coastal Wetland Vegetation Classification Using Pixel-Based, Object-Based and Deep Learning Methods Based on RGB-UAV
by: Jun-Yi Zheng, et al.
Published: (2022-11-01) -
Uncertainty Analysis of Object-Based Land-Cover Classification Using Sentinel-2 Time-Series Data
by: Lei Ma, et al.
Published: (2020-11-01) -
UAV, a Farm Map, and Machine Learning Technology Convergence Classification Method of a Corn Cultivation Area
by: Dong-Ho Lee, et al.
Published: (2021-08-01) -
Evaluation of Above-Ground Carbon Sequestration of Forest in Mahasarakham University Using Remote Sensing Data
by: Jaturong Som-ard
Published: (2020-12-01)