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 (...

Полное описание

Библиографические подробности

Главные авторы:	Andrea Tassi, Daniela Gigante, Giuseppe Modica, Luciano Di Martino, Marco Vizzari
Формат:	Artigo
Язык:	Inglês
Опубликовано:	MDPI AG 2021-06-01
Серии:	Remote Sensing
Предметы:	Google Earth Engine (GEE) land use land cover (LULC) Landsat 8 object-oriented classification machine learning (ML) Random Forest (RF)
Online-ссылка:	https://www.mdpi.com/2072-4292/13/12/2299
Метки:	Добавить метку Нет меток, Требуется 1-ая метка записи!