[HTML][HTML] Modeling carbon storage in urban vegetation: Progress, challenges, and opportunities
Urban vegetation (UV) and its carbon storage capacity are critical for terrestrial carbon
cycling and global sustainable development goals (SDGs). With complex spatial distribution …
cycling and global sustainable development goals (SDGs). With complex spatial distribution …
Monitoring house vacancy dynamics in the pearl river delta region: a method based on NPP-viirs night-time light remote sensing images
Urban spatial interaction integrates cities into closely related urban network systems in
continuous urban regions. However, it also brings differentiation and has mutual negative …
continuous urban regions. However, it also brings differentiation and has mutual negative …
Generating annual high resolution land cover products for 28 metropolises in China based on a deep super-resolution mapping network using Landsat imagery
High resolution of global land cover dynamic is indicative for understanding the influence of
anthropogenic activity on environmental change. However, most of the land cover products …
anthropogenic activity on environmental change. However, most of the land cover products …
HANet: A hierarchical attention network for change detection with bitemporal very-high-resolution remote sensing images
Benefiting from the developments in deep learning technology, deep-learning-based
algorithms employing automatic feature extraction have achieved remarkable performance …
algorithms employing automatic feature extraction have achieved remarkable performance …
[HTML][HTML] Nationwide urban tree canopy mapping and coverage assessment in Brazil from high-resolution remote sensing images using deep learning
Urban tree canopy maps are essential for providing urban ecosystem services. The
relationship between urban trees and urban climate change, air pollution, urban noise …
relationship between urban trees and urban climate change, air pollution, urban noise …
Very fine spatial resolution urban land cover mapping using an explicable sub-pixel mapping network based on learnable spatial correlation
Sub-pixel mapping is the prevailing approach for dealing with the mixed pixel effect in urban
land use/land cover classification, by reconstructing the sub-pixel-scale distribution inside …
land use/land cover classification, by reconstructing the sub-pixel-scale distribution inside …
A self-supervised remote sensing image fusion framework with dual-stage self-learning and spectral super-resolution injection
Pan-sharpening is a very productive technique to enhance the spatial details of multispectral
images with the aid of panchromatic images. Nowadays, deep learning-based pan …
images with the aid of panchromatic images. Nowadays, deep learning-based pan …
Multiscale attention network guided with change gradient image for land cover change detection using remote sensing images
Learning performance is unsatisfactory when training deep-learning networks without prior-
knowledge guidance. In this letter, a multiscale change detection neural network guided by …
knowledge guidance. In this letter, a multiscale change detection neural network guided by …
[HTML][HTML] Multi-scale Feature Fusion and Transformer Network for urban green space segmentation from high-resolution remote sensing images
Accurate extraction of urban green space is critical for preserving urban ecological balance
and enhancing urban life quality. However, due to the complex urban green space …
and enhancing urban life quality. However, due to the complex urban green space …
CSANet: Cross-temporal interaction symmetric attention network for hyperspectral image change detection
R Song, W Ni, W Cheng, X Wang - IEEE Geoscience and …, 2022 - ieeexplore.ieee.org
Deep learning methods have been extensively applied to hyperspectral (HS) image change
detection (CD) tasks and achieved promising performance. However, the beneficial joint …
detection (CD) tasks and achieved promising performance. However, the beneficial joint …