Machine learning data-driven approaches for land use/cover mapping and trend analysis using Google Earth Engine-Reference-Cited by-同舟云学术

Machine learning data-driven approaches for land use/cover mapping and trend analysis using Google Earth Engine

Published:2021-11-23 Issue: Volume: Page:1-33
ISSN:0964-0568
Container-title:Journal of Environmental Planning and Management
language:en
Short-container-title:Journal of Environmental Planning and Management

Author:

Feizizadeh Bakhtiar¹²^ORCID,Omarzadeh Davoud¹^ORCID,Kazemi Garajeh Mohammad¹^ORCID,Lakes Tobia²^ORCID,Blaschke Thomas³^ORCID

Affiliation:

1. Faculty of Planning and Environmental Sciences, Department of Remote Sensing and GIS, University of Tabriz, Tabriz, Iran

2. Department of Geography, Humboldt-Universitaet zu Berlin, Berlin, Germany

3. Department of Geoinformatics, University of Salzburg, Salzburg, Austria

Funder

Alexander von Humboldt Foundation

Publisher

Informa UK Limited

Subject

Management, Monitoring, Policy and Law,Fluid Flow and Transfer Processes,General Environmental Science,Water Science and Technology,Geography, Planning and Development

Link

https://www.tandfonline.com/doi/pdf/10.1080/09640568.2021.2001317

Reference121 articles.

1. GIS-based forest fire risk mapping using the analytical network process and fuzzy logic

2. Methodology for identifying urban growth potential using land use and population data: A case study of Islamabad Zone IV

3. Optimizing land cover classification accuracy for change detection, a combined pixel-based and object-based approach in a mountainous area in Mexico

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