Author:
Wu Jingan,Lin Liupeng,Li Tongwen,Cheng Qing,Zhang Chi,Shen Huanfeng
Funder
National Key Research and Development Program of China
Ministry of Science and Technology of the People's Republic of China
Subject
Management, Monitoring, Policy and Law,Computers in Earth Sciences,Earth-Surface Processes,Global and Planetary Change
Reference39 articles.
1. Evaluation of Landsat 8 OLI/TIRS Level-2 and Sentinel 2 Level-1C Fusion Techniques Intended for Image Segmentation of Archaeological Landscapes and Proxies;Agapiou;Remote Sens.,2020
2. Constructing 10-m NDVI Time Series From Landsat 8 and Sentinel 2 Images Using Convolutional Neural Networks;Ao;IEEE Geosci. Remote Sens. Lett.,2021
3. Deep learning-based framework for spatiotemporal data fusion: an instance of Landsat 8 and Sentinel 2 NDVI;Bhogendra;J. Appl. Remote Sens.,2021
4. Deep Learning for Feature-Level Data Fusion: Higher Resolution Reconstruction of Historical Landsat Archive;Chen;Remote Sensing,2021
5. Chen, N., Tsendbazar, N.-E., Hamunyela, E., Verbesselt, J. and Herold, M., 2021b. Sub-annual tropical forest disturbance monitoring using harmonized Landsat and Sentinel-2 data. International Journal of Applied Earth Observation and Geoinformation, 102: 102386.
Cited by
22 articles.
订阅此论文施引文献
订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献