Vegetation classification in a subtropical region with Sentinel-2 time series data and deep learning-Reference-Cited by-同舟云学术

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Vegetation classification in a subtropical region with Sentinel-2 time series data and deep learning

Published:2024-05 Issue: Volume: Page:1-19
ISSN:1009-5020
Container-title:Geo-spatial Information Science
language:en
Short-container-title:Geo-spatial Information Science

Author:

Zhang Ming¹²^ORCID,Li Dengqiu¹²^ORCID,Li Guiying¹²^ORCID,Lu Dengsheng¹²³^ORCID

Affiliation:

1. Institute of Geography, Fujian Normal University, Fuzhou, China

2. Key Laboratory for Humid Subtropical Eco-Geographical Processes of the Ministry of Education, Fujian Normal University, Fuzhou, China

3. Fujian Provincial Engineering Research Center for Forest Carbon Metering, Fujian Normal University, Fuzhou, China

Funder

National Key Research and Development Program of China

Natural Science Foundation of Fujian Province

Public Welfare Projects of Fujian Provincial Science and Technology Department

National Natural Science Foundation of China

China Scholarship Council

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/10095020.2024.2336604

Reference66 articles.

1. Fitting the Multitemporal Curve: A Fourier Series Approach to the Missing Data Problem in Remote Sensing Analysis

2. A high-performance and in-season classification system of field-level crop types using time-series Landsat data and a machine learning approach

3. Deep-STaR: Classification of image time series based on spatio-temporal representations

4. Identification of Short-Rotation Eucalyptus Plantation at Large Scale Using Multi-Satellite Imageries and Cloud Computing Platform

5. Image-Based Time Series Representations for Pixelwise Eucalyptus Region Classification: A Comparative Study

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