Comparison of machine learning and parametric methods for the discrimination of urban land cover types-Reference-Cited by-同舟云学术

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Comparison of machine learning and parametric methods for the discrimination of urban land cover types

Published:2024-01 Issue:1 Volume:39 Page:
ISSN:1010-6049
Container-title:Geocarto International
language:en
Short-container-title:Geocarto International

Author:

Amarsaikhan Enkhmanlai¹,Enkhjargal Damdin²³,Jargaldalai Enkhtuya³,Amarsaikhan Damdinsuren³

Affiliation:

1. National Technical University, Ulaanbaatar, Mongolia

2. Oyuny tsomorlig impex LLC, Ulaanbaatar, Mongolia

3. Institute of Geography and Geoecology, Mongolian Academy of Sciences, Ulaanbaatar, Mongolia

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/10106049.2024.2380372

Reference84 articles.

1. Land-use/cover classification in a heterogeneous coastal landscape using RapidEye imagery: evaluating the performance of random forest and support vector machines classifiers

2. Classification of land use/land cover using artificial intelligence (ANN-RF)

3. Data fusion and multisource image classification

4. Applications of remote sensing and geographic information systems for urban land-cover change studies in Mongolia

5. Fusing high-resolution SAR and optical imagery for improved urban land cover study and classification

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