A survey of machine learning and deep learning in remote sensing of geological environment: Challenges, advances, and opportunities

W Han, X Zhang, Y Wang, L Wang, X Huang… - ISPRS Journal of …, 2023‏ - Elsevier
Due to limited resources and environmental pollution, monitoring the geological
environment has become essential for many countries' sustainable development. As various …

Deep learning for change detection in remote sensing: a review

T Bai, L Wang, D Yin, K Sun, Y Chen… - Geo-spatial Information …, 2023‏ - Taylor & Francis
ABSTRACT A large number of publications have incorporated deep learning in the process
of remote sensing change detection. In these Deep Learning Change Detection (DLCD) …

Machine learning in modelling land-use and land cover-change (LULCC): Current status, challenges and prospects

J Wang, M Bretz, MAA Dewan, MA Delavar - Science of the Total …, 2022‏ - Elsevier
Land-use and land-cover change (LULCC) are of importance in natural resource
management, environmental modelling and assessment, and agricultural production …

[HTML][HTML] A survey on deep learning-based change detection from high-resolution remote sensing images

H Jiang, M Peng, Y Zhong, H **e, Z Hao, J Lin, X Ma… - Remote Sensing, 2022‏ - mdpi.com
Change detection based on remote sensing images plays an important role in the field of
remote sensing analysis, and it has been widely used in many areas, such as resources …

[HTML][HTML] A spatial-temporal attention-based method and a new dataset for remote sensing image change detection

H Chen, Z Shi - Remote sensing, 2020‏ - mdpi.com
Remote sensing image change detection (CD) is done to identify desired significant
changes between bitemporal images. Given two co-registered images taken at different …

Change detection based on artificial intelligence: State-of-the-art and challenges

W Shi, M Zhang, R Zhang, S Chen, Z Zhan - Remote Sensing, 2020‏ - mdpi.com
Change detection based on remote sensing (RS) data is an important method of detecting
changes on the Earth's surface and has a wide range of applications in urban planning …

[HTML][HTML] Deep learning classifiers for hyperspectral imaging: A review

ME Paoletti, JM Haut, J Plaza, A Plaza - ISPRS Journal of Photogrammetry …, 2019‏ - Elsevier
Advances in computing technology have fostered the development of new and powerful
deep learning (DL) techniques, which have demonstrated promising results in a wide range …

STADE-CDNet: Spatial–temporal attention with difference enhancement-based network for remote sensing image change detection

Z Li, S Cao, J Deng, F Wu, R Wang… - IEEE Transactions on …, 2024‏ - ieeexplore.ieee.org
High-resolution remote sensing (RS) image change detection (CD) focuses on ground
surface changes. It has wide applications, including territorial spatial planning, urban region …

[HTML][HTML] Deep learning in remote sensing applications: A meta-analysis and review

L Ma, Y Liu, X Zhang, Y Ye, G Yin… - ISPRS journal of …, 2019‏ - Elsevier
Deep learning (DL) algorithms have seen a massive rise in popularity for remote-sensing
image analysis over the past few years. In this study, the major DL concepts pertinent to …

[HTML][HTML] End-to-end change detection for high resolution satellite images using improved UNet++

D Peng, Y Zhang, H Guan - Remote Sensing, 2019‏ - mdpi.com
Change detection (CD) is essential to the accurate understanding of land surface changes
using available Earth observation data. Due to the great advantages in deep feature …