Land use and land cover mapping in the era of big data
C Zhang, X Li - Land, 2022 - mdpi.com
We are currently living in the era of big data. The volume of collected or archived geospatial
data for land use and land cover (LULC) mapping including remotely sensed satellite …
data for land use and land cover (LULC) mapping including remotely sensed satellite …
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 …
BOMSC-Net: Boundary optimization and multi-scale context awareness based building extraction from high-resolution remote sensing imagery
Automatic building extraction from high-resolution remote sensing imagery has various
applications, such as urban planning and land use management. However, the existing …
applications, such as urban planning and land use management. However, the existing …
Multiscale feature learning by transformer for building extraction from satellite images
X Chen, C Qiu, W Guo, A Yu, X Tong… - IEEE Geoscience and …, 2022 - ieeexplore.ieee.org
Extracting buildings from very high-resolution satellite images is a challenging yet important
task for applications such as urban monitoring. Multiscale feature learning proves to be a …
task for applications such as urban monitoring. Multiscale feature learning proves to be a …
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 …
Low-degree term first in ResNet, its variants and the whole neural network family
T Sun, S Ding, L Guo - Neural Networks, 2022 - Elsevier
To explain the working mechanism of ResNet and its variants, this paper proposes a novel
argument of shallow subnetwork first (SSF), essentially low-degree term first (LDTF), which …
argument of shallow subnetwork first (SSF), essentially low-degree term first (LDTF), which …
Model-guided coarse-to-fine fusion network for unsupervised hyperspectral image super-resolution
Fusing a low-resolution hyperspectral image (LrHSI) with an auxiliary high-resolution
multispectral image (HrMSI) is a burgeoning technique to realize hyperspectral image super …
multispectral image (HrMSI) is a burgeoning technique to realize hyperspectral image super …
Hybrid Conv-ViT network for hyperspectral image classification
H Yan, E Zhang, J Wang, C Leng… - IEEE Geoscience and …, 2023 - ieeexplore.ieee.org
With the success of Vision Transformer (ViT), Transformer is being increasingly used for
hyperspectral image (HSI) classification given its ability to extract global context …
hyperspectral image (HSI) classification given its ability to extract global context …
A lightweight network for building extraction from remote sensing images
H Huang, Y Chen, R Wang - IEEE Transactions on Geoscience …, 2021 - ieeexplore.ieee.org
Building extraction is a fundamental research topic in remote sensing image interpretation.
Convolutional neural network (CNN)-based building extraction algorithms have achieved …
Convolutional neural network (CNN)-based building extraction algorithms have achieved …