Multimodal hyperspectral remote sensing: An overview and perspective

Y Gu, T Liu, G Gao, G Ren, Y Ma, J Chanussot… - Science China …, 2021 - Springer
Since the advent of hyperspectral remote sensing in the 1980s, it has made important
achievements in aerospace and aviation field and been applied in many fields. Conventional …

[HTML][HTML] A simple and effective spectral-spatial method for mapping large-scale coastal wetlands using China ZY1-02D satellite hyperspectral images

W Sun, K Liu, G Ren, W Liu, G Yang, X Meng… - International Journal of …, 2021 - Elsevier
This paper proposes a simple and effective spatial-spectral (SESS) method for mapping
large-scale coastal wetlands using China ZY1-02D satellite hyperspectral data. First, the …

Aboveground biomass of salt-marsh vegetation in coastal wetlands: Sample expansion of in situ hyperspectral and Sentinel-2 data using a generative adversarial …

C Chen, Y Ma, G Ren, J Wang - Remote Sensing of Environment, 2022 - Elsevier
Coastal wetlands are main components of the “blue carbon” ecosystems in coastal zones.
Salt-marsh biomass is especially important regarding climate-change mitigation. Generating …

[HTML][HTML] A hierarchical classification framework of satellite multispectral/hyperspectral images for mapping coastal wetlands

L Jiao, W Sun, G Yang, G Ren, Y Liu - Remote Sensing, 2019 - mdpi.com
Mapping different land cover types with satellite remote sensing data is significant for restoring
and protecting natural resources and ecological services in coastal wetlands. In this paper…

[HTML][HTML] Semi-supervised cross-domain feature fusion classification network for coastal wetland classification with hyperspectral and LiDAR data

F Guo, Z Li, Q Meng, G Ren, L Wang, J Wang… - International Journal of …, 2023 - Elsevier
Multi-source remote sensing monitoring plays a crucial part in the ecological protection and
restoration of coastal wetlands. However, due to the inaccessible of wetlands environment, …

Multisource feature embedding and interaction fusion network for coastal wetland classification with hyperspectral and LiDAR data

F Guo, Q Meng, Z Li, G Ren, L Wang… - … on Geoscience and …, 2024 - ieeexplore.ieee.org
With the development of Earth observation technology, hyperspectral image (HSI) and light
detection and ranging (LiDAR) data collaborative monitoring has shown great potential in the …

Hyperspectral coastal wetland classification based on a multiobject convolutional neural network model and decision fusion

Y Hu, J Zhang, Y Ma, J An, G Ren… - IEEE Geoscience and …, 2019 - ieeexplore.ieee.org
The phenomenon of spectral aliasing exists for coastal wetland object types, which leads to
class mixing. This letter proposes a multiobject convolutional neural network (CNN) decision …

Ecological effects analysis of Spartina alterniflora invasion within Yellow River delta using long time series remote sensing imagery

G Ren, Y Zhao, J Wang, P Wu, Y Ma - Estuarine, Coastal and Shelf Science, 2021 - Elsevier
Spartina alterniflora has caused serious ecological problems in the coastal zone of mainland
China. We used Landsat and HJ-1 satellite remote sensing images covering the Yellow …

Gradient guided multi-scale feature collaboration networks for few-shot class-incremental remote sensing scene classification

W Wang, L Zhang, S Fu, P Ren, G Ren… - … on Geoscience and …, 2024 - ieeexplore.ieee.org
Few-shot class-incremental learning has recently received significant research focus in
remote sensing scene classification (FSCIL-RSSC). The success of FSCIL-RSSC relies on the …

Hyperspectral classification using deep belief networks based on conjugate gradient update and pixel-centric spectral block features

C Chen, Y Ma, G Ren - IEEE Journal of Selected Topics in …, 2020 - ieeexplore.ieee.org
This article describes the use of deep belief networks (DBNs) based on the conjugate
gradient (CG) update algorithm for hyperspectral classification. DBNs perform two processes: …