A spatial-temporal attention-based method and a new dataset for remote sensing image change detection
Remote sensing image change detection (CD) is done to identify desired significant
changes between bitemporal images. Given two co-registered images taken at different …
changes between bitemporal images. Given two co-registered images taken at different …
Asymmetric cross-attention hierarchical network based on CNN and transformer for bitemporal remote sensing images change detection
X Zhang, S Cheng, L Wang, H Li - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
As an important task in the field of remote sensing (RS) image processing, RS image
change detection (CD) has made significant advances through the use of convolutional …
change detection (CD) has made significant advances through the use of convolutional …
[HTML][HTML] Flood susceptibility mapping using multi-temporal SAR imagery and novel integration of nature-inspired algorithms into support vector regression
Flood has long been known as one of the most catastrophic natural hazards worldwide.
Mapping flood-prone areas is an important part of flood disaster management. In this study …
Mapping flood-prone areas is an important part of flood disaster management. In this study …
Change is everywhere: Single-temporal supervised object change detection in remote sensing imagery
For high spatial resolution (HSR) remote sensing images, bitemporal supervised learning
always dominates change detection using many pairwise labeled bitemporal images …
always dominates change detection using many pairwise labeled bitemporal images …
Comparison of machine learning algorithms for flood susceptibility mapping
Floods are one of the most destructive natural disasters, causing financial and human losses
every year. As a result, reliable Flood Susceptibility Mapping (FSM) is required for effective …
every year. As a result, reliable Flood Susceptibility Mapping (FSM) is required for effective …
Flood susceptibility mapping using machine learning boosting algorithms techniques in Idukki district of Kerala India
Kerala experiences a high rate of annual rainfall and flooding resulting in a frequent natural
disaster. The objective of this study is to develop flood susceptibility maps for the Idukki …
disaster. The objective of this study is to develop flood susceptibility maps for the Idukki …
Flood hazard mapping using fuzzy logic, analytical hierarchy process, and multi-source geospatial datasets
Iran is among the driest countries in the world, where many natural hazards, such as floods,
frequently occur. This study introduces a straightforward flood hazard assessment approach …
frequently occur. This study introduces a straightforward flood hazard assessment approach …
D2ANet: Difference-aware attention network for multi-level change detection from satellite imagery
Recognizing dynamic variations on the ground, especially changes caused by various
natural disasters, is critical for assessing the severity of the damage and directing the …
natural disasters, is critical for assessing the severity of the damage and directing the …
A new end-to-end multi-dimensional CNN framework for land cover/land use change detection in multi-source remote sensing datasets
ST Seydi, M Hasanlou, M Amani - Remote Sensing, 2020 - mdpi.com
The diversity of change detection (CD) methods and the limitations in generalizing these
techniques using different types of remote sensing datasets over various study areas have …
techniques using different types of remote sensing datasets over various study areas have …
The use of artificial intelligence and satellite remote sensing in land cover change detection: review and perspectives
Z Gu, M Zeng - Sustainability, 2023 - mdpi.com
The integration of Artificial Intelligence (AI) and Satellite Remote Sensing in Land Cover
Change Detection (LCCD) has gained increasing significance in scientific discovery and …
Change Detection (LCCD) has gained increasing significance in scientific discovery and …