Surface water mapping by deep learning
F Isikdogan, AC Bovik… - IEEE journal of selected …, 2017 - ieeexplore.ieee.org
Mapping of surface water is useful in a variety of remote sensing applications, such as
estimating the availability of water, measuring its change in time, and predicting droughts …
estimating the availability of water, measuring its change in time, and predicting droughts …
[HTML][HTML] An applicable and automatic method for earth surface water mapping based on multispectral images
Earth's surface water plays an important role in the global water cycle, environmental
processes, and human society, and it is necessary to dynamically capture the distribution …
processes, and human society, and it is necessary to dynamically capture the distribution …
[HTML][HTML] DeepAqua: Semantic segmentation of wetland water surfaces with SAR imagery using deep neural networks without manually annotated data
Deep learning and remote sensing techniques have significantly advanced water surface
monitoring; however, the need for annotated data remains a challenge. This is particularly …
monitoring; however, the need for annotated data remains a challenge. This is particularly …
Seeing through the clouds with deepwatermap
LF Isikdogan, A Bovik… - IEEE Geoscience and …, 2019 - ieeexplore.ieee.org
We present our next-generation surface water mapping model, DeepWaterMapV2, which
uses improved model architecture, data set, and a training setup to create surface water …
uses improved model architecture, data set, and a training setup to create surface water …
Deep learning approach for Sentinel-1 surface water mapping leveraging Google Earth Engine
Satellite remote sensing plays an important role in mapping the location and extent of
surface water. A variety of approaches are available for mapping surface water, but deep …
surface water. A variety of approaches are available for mapping surface water, but deep …
Accurate water extraction using remote sensing imagery based on normalized difference water index and unsupervised deep learning
Large-scale monitoring of surface water bodies is of great significance to the sustainable
development of regional ecosystems. Remote sensing is currently the main method of global …
development of regional ecosystems. Remote sensing is currently the main method of global …
NFANet: A novel method for weakly supervised water extraction from high-resolution remote-sensing imagery
The use of deep learning for water extraction requires precise pixel-level labels. However, it
is very difficult to label high-resolution remote-sensing images at the pixel level. Therefore …
is very difficult to label high-resolution remote-sensing images at the pixel level. Therefore …
Multilayer perceptron neural network for surface water extraction in Landsat 8 OLI satellite images
W Jiang, G He, T Long, Y Ni, H Liu, Y Peng, K Lv… - Remote Sensing, 2018 - mdpi.com
Surface water mapping is essential for monitoring climate change, water resources,
ecosystem services and the hydrological cycle. In this study, we adopt a multilayer …
ecosystem services and the hydrological cycle. In this study, we adopt a multilayer …
Convolutional neural networks for water body extraction from Landsat imagery
L Yu, Z Wang, S Tian, F Ye, J Ding… - International Journal of …, 2017 - World Scientific
Traditional machine learning methods for water body extraction need complex spectral
analysis and feature selection which rely on wealth of prior knowledge. They are time …
analysis and feature selection which rely on wealth of prior knowledge. They are time …
Combining pixel-and object-based machine learning for identification of water-body types from urban high-resolution remote-sensing imagery
Water is one of the vital components for the ecological environment, which plays an
important role in human survival and socioeconomic development. Water resources in urban …
important role in human survival and socioeconomic development. Water resources in urban …