Jie Wang
Orcid: 0000-0002-9663-3165Affiliations:
- Chinese Academy of Sciences, Institute of Remote Sensing and Digital Earth, State Key Laboratory of Remote Sensing Science, Beijing, China
According to our database1,
Jie Wang
authored at least 17 papers
between 2011 and 2025.
Collaborative distances:
Collaborative distances:
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Bibliography
2025
MGMNet: Mutual-Guidance Mechanism for Joint Classification of Multisource Remote Sensing Data.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2025
2024
Municipal and Urban Renewal Development Index System: A Data-Driven Digital Analysis Framework.
Remote. Sens., February, 2024
2022
Grid-Based Essential Urban Land Use Classification: A Data and Model Driven Mapping Framework in Xiamen City.
Remote. Sens., December, 2022
IEEE Trans. Geosci. Remote. Sens., 2022
Enhanced Resolution of FY4 Remote Sensing Visible Spectrum Images Utilizing Super-Resolution and Transfer Learning Techniques.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2022
MUSTFN: A spatiotemporal fusion method for multi-scale and multi-sensor remote sensing images based on a convolutional neural network.
Int. J. Appl. Earth Obs. Geoinformation, 2022
2020
Improving 3-m Resolution Land Cover Mapping through Efficient Learning from an Imperfect 10-m Resolution Map.
Remote. Sens., 2020
2018
Long-Term Annual Mapping of Four Cities on Different Continents by Applying a Deep Information Learning Method to Landsat Data.
Remote. Sens., 2018
2016
A probabilistic graphical model approach in 30 m land cover mapping with multiple data sources.
CoRR, 2016
Probabilistic graphical model based approach for water mapping using GaoFen-2 (GF-2) high resolution imagery and Landsat 8 time series.
CoRR, 2016
2015
Joint Use of ICESat/GLAS and Landsat Data in Land Cover Classification: A Case Study in Henan Province, China.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2015
Seasonal Land Cover Dynamics in Beijing Derived from Landsat 8 Data Using a Spatio-Temporal Contextual Approach.
Remote. Sens., 2015
2014
Comparison of Classification Algorithms and Training Sample Sizes in Urban Land Classification with Landsat Thematic Mapper Imagery.
Remote. Sens., 2014
2013
Int. J. Digit. Earth, 2013
2011
Residential area extraction by integrating supervised/unsupervised/contextual/object-based methods with moderate resolution remotely sensed data.
Proceedings of the Joint Urban Remote Sensing Event, 2011