Remote sensing image scene classification meets deep learning: Challenges, methods, benchmarks, and opportunities
Remote sensing image scene classification, which aims at labeling remote sensing images
with a set of semantic categories based on their contents, has broad applications in a range …
with a set of semantic categories based on their contents, has broad applications in a range …
Deep learning-based change detection in remote sensing images: A review
Images gathered from different satellites are vastly available these days due to the fast
development of remote sensing (RS) technology. These images significantly enhance the …
development of remote sensing (RS) technology. These images significantly enhance the …
Deep building footprint update network: A semi-supervised method for updating existing building footprint from bi-temporal remote sensing images
Building footprint information is one foundation for understanding urban processes and
hence a program for environmentally sustainable urbanization. For most cities, municipal …
hence a program for environmentally sustainable urbanization. For most cities, municipal …
SCViT: A spatial-channel feature preserving vision transformer for remote sensing image scene classification
P Lv, W Wu, Y Zhong, F Du… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Convolutional neural network (CNN)-based methods are widely used in remote sensing
image scene classification and can obtain excellent performances. However, the stacked …
image scene classification and can obtain excellent performances. However, the stacked …
Investigating the effects of 3D urban morphology on the surface urban heat island effect in urban functional zones by using high-resolution remote sensing data: A …
The Urban heat island (UHI) effect is an increasingly serious problem in urban areas.
Information on the driving forces of intra-urban temperature variation is crucial for …
Information on the driving forces of intra-urban temperature variation is crucial for …
A review of building detection from very high resolution optical remote sensing images
Building detection from very high resolution (VHR) optical remote sensing images, which is
an essential but challenging task in remote sensing, has attracted increased attention in …
an essential but challenging task in remote sensing, has attracted increased attention in …
Change detection from very-high-spatial-resolution optical remote sensing images: Methods, applications, and future directions
Change detection is a vibrant area of research in remote sensing. Thanks to increases in the
spatial resolution of remote sensing images, subtle changes at a finer geometrical scale can …
spatial resolution of remote sensing images, subtle changes at a finer geometrical scale can …
Understanding spatio-temporal patterns of land use/land cover change under urbanization in Wuhan, China, 2000–2019
Exploring land use structure and dynamics is critical for urban planning and management.
This study attempts to understand the Wuhan development mode since the beginning of the …
This study attempts to understand the Wuhan development mode since the beginning of the …
A review of change detection in multitemporal hyperspectral images: Current techniques, applications, and challenges
We review both widely used methods and new techniques proposed in the recent literature.
The basic concepts, categories, open issues, and challenges related to CD in HS images …
The basic concepts, categories, open issues, and challenges related to CD in HS images …
Large-scale deep learning based binary and semantic change detection in ultra high resolution remote sensing imagery: From benchmark datasets to urban …
With the acceleration of urban expansion, urban change detection (UCD), as a significant
and effective approach, can provide the change information with respect to geospatial …
and effective approach, can provide the change information with respect to geospatial …