Impact of Various Atmospheric Corrections on Sentinel-2 Land Cover Classification Accuracy Using Machine Learning Classifiers
Atmospheric correction is one of the key parts of remote sensing preprocessing because it can influence and change the final classification result. This research examines the impact of five different atmospheric correction processing on land cover classification accuracy using Sentinel-2 satellite i...
Main Authors: | Luka Rumora, Mario Miler, Damir Medak |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2020-04-01
|
Series: | ISPRS International Journal of Geo-Information |
Subjects: | |
Online Access: | https://www.mdpi.com/2220-9964/9/4/277 |
Similar Items
-
Multispectral LiDAR Data for Land Cover Classification of Urban Areas
by: Salem Morsy, et al.
Published: (2017-04-01) -
Angular-Based Radiometric Slope Correction for Sentinel-1 on Google Earth Engine
by: Andreas Vollrath, et al.
Published: (2020-06-01) -
iCOR Atmospheric Correction on Sentinel-3/OLCI over Land: Intercomparison with AERONET, RadCalNet, and SYN Level-2
by: Erwin Wolters, et al.
Published: (2021-02-01) -
Synergistic Use of Sentinel-1 and Sentinel-2 Based on Different Preprocessing for Predicting Forest Aboveground Biomass
by: Gengsheng Fang, et al.
Published: (2023-08-01) -
Evaluating Atmospheric Correction Methods for Sentinel−2 in Low−to−High−Turbidity Chinese Coastal Waters
by: Shuyi Zhang, et al.
Published: (2023-04-01)