Landsat 8Bands’ 1 to 7 spectral vectors plus machine learning to improve land use/cover classification using Google Earth Engine-Reference-Cited by-同舟云学术

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Landsat 8Bands’ 1 to 7 spectral vectors plus machine learning to improve land use/cover classification using Google Earth Engine

Published:2022-02-14 Issue:3 Volume:28 Page:401-424
ISSN:1947-5683
Container-title:Annals of GIS
language:en
Short-container-title:Annals of GIS

Author:

Ngandam Mfondoum Alfred Homère¹²^ORCID,Hakdaoui Sofia³^ORCID,Batcha Roseline²

Affiliation:

1. Statsn’maps, Consulting Firm, Dallas, Texas, USA

2. Natural Resources Management Laboratory, Department of Geography, University of Yaoundé, Yaoundé, Cameroon

3. Geoscience, Water and Environment Laboratory, Faculty of Sciences, Mohammed V University in Rabat, Rabat, Morocco

Publisher

Informa UK Limited

Subject

General Earth and Planetary Sciences,Computer Science Applications

Link

https://www.tandfonline.com/doi/pdf/10.1080/19475683.2022.2026475

Reference58 articles.

1. Integrating multiple texture methods and NDVI to the Random Forest classification algorithm to detect tea and hazelnut plantation areas in northeast Turkey

2. Urban Mapping in Landsat Images Based on Normalized Difference Spectral Vector

3. Urban sprawl measurement from remote sensing data

4. Classification And Regression Trees

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Variation of groundwater level due to land use, precipitation, and earthquake in Yogyakarta City from 2005 to 2020;Groundwater for Sustainable Development;2024-08

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