Generation of monthly VIIRS nighttime lights time-series (1992–2013) images using deep learning (cGAN) technique-Reference-Cited by-同舟云学术

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Generation of monthly VIIRS nighttime lights time-series (1992–2013) images using deep learning (cGAN) technique

Published:2024-08 Issue: Volume:35 Page:101263
ISSN:2352-9385
Container-title:Remote Sensing Applications: Society and Environment
language:en
Short-container-title:Remote Sensing Applications: Society and Environment

Author:

Jindal Mehak^ORCID,Gupta Prasun Kumar^ORCID,Srivastav S.K.^ORCID

Publisher

Elsevier BV

Reference46 articles.

1. Indian economy and nighttime lights;Agnihotri,2021

2. A deep journey into super-resolution;Anwar;ACM Comput. Surv.,2020

3. Nighttime lights compositing using the VIIRS day-night band: preliminary results;Baugh;Proceedings of the Asia-Pacific Advanced Network,2013

4. Advances in using multitemporal night-time lights satellite imagery to detect, estimate, and monitor socioeconomic dynamics;Bennett;Rem. Sens. Environ.,2017

5. Quantitative analysis of VIIRS DNB nightlight point source for light power estimation and stability monitoring;Cao;Rem. Sens.,2014

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