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 …
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 full-level fused cross-task transfer learning method for building change detection using noise-robust pretrained networks on crowdsourced labels
Accurate building change detection is crucial for understanding urban development.
Although fully supervised deep learning-based methods for building change detection have …
Although fully supervised deep learning-based methods for building change detection have …
SiamHYPER: Learning a hyperspectral object tracker from an RGB-based tracker
Hyperspectral videos can provide the spatial, spectral, and motion information of targets,
which makes it possible to track camouflaged targets that are similar to the background …
which makes it possible to track camouflaged targets that are similar to the background …
[HTML][HTML] Generating 2m fine-scale urban tree cover product over 34 metropolises in China based on deep context-aware sub-pixel mapping network
Contrast to the global forest, few trees live in cities but contribute significantly to urban
environment and human health. However, the classical satellite-derived land cover/forest …
environment and human health. However, the classical satellite-derived land cover/forest …
Deep subpixel mapping based on semantic information modulated network for urban land use mapping
Mixed pixel problem is omnipresent in remote sensing images for urban land use
interpretation due to the hardware limitations. Subpixel mapping (SPM) is a usual way to …
interpretation due to the hardware limitations. Subpixel mapping (SPM) is a usual way to …
Landslide detection mapping employing CNN, ResNet, and DenseNet in the three gorges reservoir, China
Landslide detection mapping (LDM) is the basis of the field of landslide disaster prevention;
however, it has faced certain difficulties. The Three Gorges Reservoir area of the Yangtze …
however, it has faced certain difficulties. The Three Gorges Reservoir area of the Yangtze …
Road extraction from satellite imagery by road context and full-stage feature
Road extraction from satellite imagery is vital in a broad range of applications. However,
extracting complete roads is challenging due to road occlusions caused by the …
extracting complete roads is challenging due to road occlusions caused by the …
Spatial validation of spectral unmixing results: A systematic review
RM Cavalli - Remote Sensing, 2023 - mdpi.com
The pixels of remote images often contain more than one distinct material (mixed pixels),
and so their spectra are characterized by a mixture of spectral signals. Since 1971, a shared …
and so their spectra are characterized by a mixture of spectral signals. Since 1971, a shared …
TransRoadNet: A novel road extraction method for remote sensing images via combining high-level semantic feature and context
Road extraction is a significant research hotspot in the area of remote sensing images.
Extracting an accurate road network from remote sensing images is still challenging …
Extracting an accurate road network from remote sensing images is still challenging …