Uncovering the rapid expansion of photovoltaic power plants in China from 2010 to 2022 using satellite data and deep learning-Reference-Cited by-同舟云学术

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Uncovering the rapid expansion of photovoltaic power plants in China from 2010 to 2022 using satellite data and deep learning

Published:2024-05 Issue: Volume:305 Page:114100
ISSN:0034-4257
Container-title:Remote Sensing of Environment
language:en
Short-container-title:Remote Sensing of Environment

Author:

Chen Yuehong,Zhou Jiayue,Ge Yong,Dong Jinwei

Funder

National Natural Science Foundation of China

National Key Research and Development Program of China

National Key Research and Development Program of China Stem Cell and Translational Research

Publisher

Elsevier BV

Reference38 articles.

1. Local indicators of spatial association—LISA;Anselin;Geogr. Anal.,1995

2. Spatiotemporal image fusion using multiscale attention-aware two-stream convolutional neural networks;Chen;Sci. Remote Sens.,2022

3. Object-based superresolution land cover mapping from remotely sensed imagery;Chen;IEEE Trans. Geosci. Remote Sens.,2018

4. TransUNet: transformers make strong encoders for medical image segmentation;Chen,2021

5. Spatiotemporal remote sensing image fusion using multiscale two-stream convolutional neural networks;Chen;IEEE Trans. Geosci. Remote Sens.,2022

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1. Mapping national-scale photovoltaic power stations using a novel enhanced photovoltaic index and evaluating carbon reduction benefits;Energy Conversion and Management;2024-10

2. Enhancing low voltage ride-through capability of grid-connected photovoltaic plants using superconducting fault current limiters;Renewable Energy;2024-09

3. Space cannot substitute for time in the study of the ecosystem services-human wellbeing relationship;Geography and Sustainability;2024-09

4. A 100 m gridded population dataset of China's seventh census using ensemble learning and big geospatial data;Earth System Science Data;2024-08-16

5. Digital Surface Model Super-Resolution by Integrating High-Resolution Remote Sensing Imagery Using Generative Adversarial Networks;IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing;2024

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