Cost-effective disaster-induced land cover analysis: a semi-automatic methodology Using machine learning and satellite imagery-Reference-Cited by-同舟云学术

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Cost-effective disaster-induced land cover analysis: a semi-automatic methodology Using machine learning and satellite imagery

Published:2024-01-08 Issue:2 Volume:45 Page:279-305
ISSN:0143-1161
Container-title:International Journal of Remote Sensing
language:en
Short-container-title:International Journal of Remote Sensing

Author:

I. Volke Matias¹,Abarca-Del-Rio Rodrigo²,A. Warner Timothy³^ORCID

Affiliation:

1. Energy Doctoral Program, Faculty of Engineering, Universidad de Concepción, Concepción, Chile

2. Department of Geophysics, Faculty of Physical and Mathematical Sciences, University of Concepcion, Concepcion, Chile

3. Department of Geology and Geography, West Virginia University, Morgantown, WV, USA

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/01431161.2023.2292015

Reference105 articles.

1. Land cover and land use classification performance of machine learning algorithms in a boreal landscape using Sentinel-2 data

2. Analysis of Maximum Likelihood Classification on Multispectral Data;Ahmad A.;Applied Mathematical Sciences,2012

3. NS-k-NN: Neutrosophic Set-Based k-Nearest Neighbors Classifier

4. Efectos geomorfológicos del tsunami de Chile de 2010 frente a la zona de máximo slip, revelados por imágenes satelitales y observaciones de campo: El caso del litoral arenoso La Trinchera, Región del Maule

5. Assessing nighttime lights for mapping the urban areas of 50 cities across the globe

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1. Assessment of Semi-Automated Techniques for Crop Mapping in Chile Based on Global Land Cover Satellite Data;Remote Sensing;2024-08-12

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