Classification of Landscape Affected by Deforestation Using High-Resolution Remote Sensing Data and Deep-Learning Techniques
Human-induced deforestation has a major impact on forest ecosystems and therefore its detection and analysis methods should be improved. This study classified landscape affected by human-induced deforestation efficiently using high-resolution remote sensing and deep-learning. The SegNet and U-Net al...
Main Authors: | Seong-Hyeok Lee, Kuk-Jin Han, Kwon Lee, Kwang-Jae Lee, Kwan-Young Oh, Moung-Jin Lee |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2020-10-01
|
Series: | Remote Sensing |
Subjects: | |
Online Access: | https://www.mdpi.com/2072-4292/12/20/3372 |
Similar Items
-
Oil Spill Mapping from Kompsat-2 High-Resolution Image Using Directional Median Filtering and Artificial Neural Network
by: Sung-Hwan Park, et al.
Published: (2020-01-01) -
Analysis of Orbital Lifetime Prediction Parameters in Preparation for Post-Mission Disposal
by: Ha–Yeon Choi, et al.
Published: (2015-12-01) -
Feasibility Study of Synthetic Aperture Radar - Adaptability of the Payload to KOMPSAT Platform
by: Young-Soo Kim, et al.
Published: (2002-09-01) -
Updating Absolute Radiometric Characteristics for KOMPSAT-3 and KOMPSAT-3A Multispectral Imaging Sensors Using Well-Characterized Pseudo-Invariant Tarps and Microtops II
by: Jong-Min Yeom, et al.
Published: (2018-05-01) -
Automated Geo/Co-Registration of Multi-Temporal Very-High-Resolution Imagery
by: Youkyung Han, et al.
Published: (2018-05-01)