Detailed and automated classification of land use/land cover using machine learning algorithms in Google Earth Engine-Reference-Cited by-同舟云学术

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Detailed and automated classification of land use/land cover using machine learning algorithms in Google Earth Engine

Published:2021-05-14 Issue: Volume: Page:1-18
ISSN:1010-6049
Container-title:Geocarto International
language:en
Short-container-title:Geocarto International

Author:

Pan Xia¹,Wang Zhenyi¹,Gao Yong¹²,Dang Xiaohong¹³,Han Yanlong¹

Affiliation:

1. College of Desert Control Science and Engineering, Inner Mongolia Agricultural University, Hohhot, China

2. Wind Erosion Key Laboratory of Central and Government, Hohhot, China

3. National Positioning Observation Research Station of Hangjin Desert Ecosystem, Ordos, China

Publisher

Informa UK Limited

Subject

Water Science and Technology,Geography, Planning and Development

Link

https://www.tandfonline.com/doi/pdf/10.1080/10106049.2021.1917005

Reference48 articles.

1. Google Earth Engine Cloud Computing Platform for Remote Sensing Big Data Applications: A Comprehensive Review

2. A land use and land cover classification system for use with remote sensor data

3. Classifying Complex Mountainous Forests with L-Band SAR and Landsat Data Integration: A Comparison among Different Machine Learning Methods in the Hyrcanian Forest

4. A training algorithm for optimal margin classifiers

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