Leveraging Aqua and Terra satellite data for improved diurnal land surface temperature prediction: a comparative LSTM-based approach-Reference-Cited by-同舟云学术

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Leveraging Aqua and Terra satellite data for improved diurnal land surface temperature prediction: a comparative LSTM-based approach

Published:2023-07-03 Issue:7 Volume:14 Page:733-742
ISSN:2150-704X
Container-title:Remote Sensing Letters
language:en
Short-container-title:Remote Sensing Letters

Author:

Chauhan Shivam¹²^ORCID,Jethoo Ajay Singh²^ORCID,Varshney Vaibhav³^ORCID

Affiliation:

1. Department of Civil Engineering, University of Engineering and Management, Jaipur, India

2. Department of Civil Engineering, Malaviya National Institute of Technology, Jaipur, India

3. Department of Physics, Dyal Singh College, University of Delhi, New Delhi, India

Publisher

Informa UK Limited

Subject

Electrical and Electronic Engineering,Earth and Planetary Sciences (miscellaneous)

Link

https://www.tandfonline.com/doi/pdf/10.1080/2150704X.2023.2234553

Reference12 articles.

1. Limitations of integrated assessment models of climate change

2. Earth observation in service of the 2030 Agenda for Sustainable Development

3. Land skin temperature’s mathematical analysis of Ajmer city in remote sensing way

4. Statistical analysis of diurnal variations in land surface temperature and the UHI effect using aqua and terra MODIS data

5. Duo Satellite Based Surface Temperature Comparative Study of Jaipur City Using Soft Computing

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1. Prediction of land surface temperature using spectral indices, air pollutants, and urbanization parameters for Hyderabad city of India using six machine learning approaches;Remote Sensing Applications: Society and Environment;2024-08

2. Incremental–decremental data transformation based ensemble deep learning model (IDT-eDL) for temperature prediction;Modeling Earth Systems and Environment;2024-02-26

3. Land surface temperature prediction with dual satellites and BPNN: a comparative transfer function analysis;Remote Sensing Letters;2024-02-19

4. Duo satellite-based remotely sensed land surface temperature prediction by various methods of machine learning;International Journal of Data Science and Analytics;2023-09-30

5. Thermal characterization of Ajmer City: Insights into urban heat dynamics;Materials Today: Proceedings;2023-08

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