Pixel- vs. Object-Based Landsat 8 Data Classification in Google Earth Engine Using Random Forest: The Case Study of Maiella National Park

Pixel- vs. Object-Based Landsat 8 Data Classification in Google Earth Engine Using Random Forest: The Case Study of Maiella National Park

With the general objective of producing a 2018–2020 Land Use/Land Cover (LULC) map of the Maiella National Park (central Italy), useful for a future long-term LULC change analysis, this research aimed to develop a Landsat 8 (L8) data composition and classification process using Google Earth Engine (...

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Bibliographic Details
Main Authors: Andrea Tassi, Daniela Gigante, Giuseppe Modica, Luciano Di Martino, Marco Vizzari
Format: Article
Language:English
Published: MDPI AG 2021-06-01
Series:Remote Sensing
Subjects:
Google Earth Engine (GEE)
land use land cover (LULC)
Landsat 8
object-oriented classification
machine learning (ML)
Random Forest (RF)
Online Access:https://www.mdpi.com/2072-4292/13/12/2299

Internet

https://www.mdpi.com/2072-4292/13/12/2299

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