Land cover change detection with heterogeneous remote sensing images: Review, progress, and perspective

ZY Lv, HT Huang, X Li, MH Zhao… - Proceedings of the …, 2022 - ieeexplore.ieee.org
With the fast development of remote sensing platforms and sensors technology, change
detection with heterogeneous remote sensing images (Hete-CD) has become an attractive …

Change detection methods for remote sensing in the last decade: A comprehensive review

G Cheng, Y Huang, X Li, S Lyu, Z Xu, H Zhao, Q Zhao… - Remote Sensing, 2024 - mdpi.com
Change detection is an essential and widely utilized task in remote sensing that aims to
detect and analyze changes occurring in the same geographical area over time, which has …

A deep translation (GAN) based change detection network for optical and SAR remote sensing images

X Li, Z Du, Y Huang, Z Tan - ISPRS Journal of Photogrammetry and …, 2021 - Elsevier
With the development of space-based imaging technology, a larger and larger number of
images with different modalities and resolutions are available. The optical images reflect the …

Commonality autoencoder: Learning common features for change detection from heterogeneous images

Y Wu, J Li, Y Yuan, AK Qin, QG Miao… - IEEE transactions on …, 2021 - ieeexplore.ieee.org
Change detection based on heterogeneous images, such as optical images and synthetic
aperture radar images, is a challenging problem because of their huge appearance …

Iterative training sample augmentation for enhancing land cover change detection performance with deep learning neural network

Z Lv, H Huang, W Sun, M Jia… - … on Neural Networks …, 2023 - ieeexplore.ieee.org
Labeled samples are important in achieving land cover change detection (LCCD) tasks via
deep learning techniques with remote sensing images. However, labeling samples for …

ISNet: Towards improving separability for remote sensing image change detection

G Cheng, G Wang, J Han - IEEE Transactions on Geoscience …, 2022 - ieeexplore.ieee.org
Deep learning has substantially pushed forward remote sensing image change detection
through extracting discriminative hierarchical features. However, as the increasingly high …

Transition is a process: Pair-to-video change detection networks for very high resolution remote sensing images

M Lin, G Yang, H Zhang - IEEE Transactions on Image …, 2022 - ieeexplore.ieee.org
As an important yet challenging task in Earth observation, change detection (CD) is
undergoing a technological revolution, given the broadening application of deep learning …

[HTML][HTML] Fourier domain structural relationship analysis for unsupervised multimodal change detection

H Chen, N Yokoya, M Chini - ISPRS Journal of Photogrammetry and …, 2023 - Elsevier
Change detection on multimodal remote sensing images has become an increasingly
interesting and challenging topic in the remote sensing community, which can play an …

Hierarchical attention feature fusion-based network for land cover change detection with homogeneous and heterogeneous remote sensing images

Z Lv, J Liu, W Sun, T Lei… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Deep learning techniques have become popular in land cover change detection (LCCD)
with remote sensing images (RSIs). However, many existing networks mostly concentrate on …

[HTML][HTML] Global-aware siamese network for change detection on remote sensing images

R Zhang, H Zhang, X Ning, X Huang, J Wang… - ISPRS journal of …, 2023 - Elsevier
Change detection (CD) in remote sensing images is one of the most important technical
options to identify changes in observations in an efficient manner. CD has a wide range of …