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Convolutional neural network-based deep learning approach for automatic flood map** using NovaSAR-1 and Sentinel-1 data
The accuracy of most SAR-based flood classification and segmentation derived from semi-
automated algorithms is often limited due to complicated radar backscatter. However, deep …
automated algorithms is often limited due to complicated radar backscatter. However, deep …
GS-DeepLabV3+: A mountain tea disease segmentation network based on improved shuffle attention and gated multidimensional feature extraction
H Zhou, Y Peng, R Zhang, Y He, L Li, W **
Existing lightweight flood extent map** (FEM) methods, leveraging satellite imagery, offer
respite from the burden of extensive data processing. However, these methods often grapple …
respite from the burden of extensive data processing. However, these methods often grapple …
Kuro Siwo: 33 billion under the water. A global multi-temporal satellite dataset for rapid flood map**
Global floods, exacerbated by climate change, pose severe threats to human life,
infrastructure, and the environment. Recent catastrophic events in Pakistan and New …
infrastructure, and the environment. Recent catastrophic events in Pakistan and New …
Investigating the seasonal dynamics of surface water over the Qinghai–Tibet Plateau using Sentinel-1 imagery and a novel gated multiscale ConvNet
The surface water in the Qinghai–Tibet Plateau (QTP) region has undergone dramatic
changes in recent decades. To capture dynamic surface water information, many satellite …
changes in recent decades. To capture dynamic surface water information, many satellite …
Solving flood problems with deep learning technology: Research status, strategies, and future directions
H Li, M Zhu, F Li, M Skitmore - Sustainable Development, 2024 - Wiley Online Library
As a frequent and devastating natural disaster worldwide, floods are influenced by complex
factors. Building flood models for simulating, monitoring, and forecasting floods is crucial to …
factors. Building flood models for simulating, monitoring, and forecasting floods is crucial to …
The effect of negative samples on the accuracy of water body extraction using deep learning networks
J Song, X Yan - Remote Sensing, 2023 - mdpi.com
Water resources are important strategic resources related to human survival and
development. Water body extraction from remote sensing images is a very important …
development. Water body extraction from remote sensing images is a very important …
IMAFD: An interpretable multi-stage approach to flood detection from time series multispectral data
In this paper, we address two critical challenges in the domain of flood detection: the
computational expense of large-scale time series change detection and the lack of …
computational expense of large-scale time series change detection and the lack of …
TRSANet: A Remote Sensing Deep Learning Model for Water Body Change Detection Based on Time-Reversal Semantic Asymmetry
J Li, C **, Y Shen, W Ye - IEEE Transactions on Geoscience …, 2024 - ieeexplore.ieee.org
The goal of change detection is to identify modifications in dual-temporal remote sensing
(RS) images, which reveal dynamic changes in specific areas of interest. Specifically, the …
(RS) images, which reveal dynamic changes in specific areas of interest. Specifically, the …