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[HTML][HTML] Map** and classification of Liao River Delta coastal wetland based on time series and multi-source GaoFen images using stacking ensemble model
H Qian, N Bao, D Meng, B Zhou, H Lei, H Li - Ecological Informatics, 2024 - Elsevier
The precise map** of coastal wetlands holds great significance for monitoring carbon
sequestration and storage within coastal ecosystems, particularly in light of climate change …
sequestration and storage within coastal ecosystems, particularly in light of climate change …
[HTML][HTML] Enhancing Land Cover/Land Use (LCLU) classification through a comparative analysis of hyperparameters optimization approaches for deep neural network …
Sustainable natural resources management relies on effective and timely assessment of
conservation and land management practices. Using satellite imagery for Earth observation …
conservation and land management practices. Using satellite imagery for Earth observation …
Vegetation classification and evaluation of Yancheng Coastal Wetlands based on random forest algorithm from Sentinel-2 images
The identification of wetland vegetation is essential for environmental protection and
management as well as for monitoring wetlands' health and assessing ecosystem services …
management as well as for monitoring wetlands' health and assessing ecosystem services …
Quantifying effects of climate change and farmers' information demand on wheat yield in India: a deep learning approach with regional clustering
Introduction With increasing demand for food and changing environmental conditions, a
better understanding of the factors impacting wheat yield is essential for ensuring food …
better understanding of the factors impacting wheat yield is essential for ensuring food …
[HTML][HTML] Integration of multi-temporal SAR data and robust machine learning models for improvement of flood susceptibility assessment in the southwest coast of India
The flood hazards in the southwest coastal region of India in 2018 and 2020 resulted in
numerous casualties and the displacement of over a million people from their homes. In …
numerous casualties and the displacement of over a million people from their homes. In …
Threshold-based inventory for flood susceptibility assessment of the world's largest river island using multi-temporal SAR data and ensemble machine learning …
P Prasad, D Gogoi, D Gogoi, T Kumar… - … Research and Risk …, 2024 - Springer
Majuli is the world's largest inhabited river island and is highly prone to flood hazards,
resulting in significant damage to houses and agriculturally based livelihoods. Considering …
resulting in significant damage to houses and agriculturally based livelihoods. Considering …
Integration Sentinel-1 SAR data and machine learning for land subsidence in-depth analysis in the North Coast of Central Java, Indonesia
The escalating issue of land subsidence poses a critical threat to the economic prosperity of
Indonesia's North Coast in Central Java. This recurring phenomenon intensifies annual tidal …
Indonesia's North Coast in Central Java. This recurring phenomenon intensifies annual tidal …
A hybrid machine learning modelling for optimization of flood susceptibility map** in the eastern Mediterranean
Floods are considered one of the most destructive natural disasters due to the human and
economic losses caused. The Eastern Mediterranean region is subject to devastating …
economic losses caused. The Eastern Mediterranean region is subject to devastating …
[HTML][HTML] Map** high-resolution XCO2 concentrations in China from 2015 to 2020 based on spatiotemporal ensemble learning model
W Liu, R Li, J Cao, C Huang, F Zhang, M Zhang - Ecological Informatics, 2024 - Elsevier
High-resolution column-averaged dry air mole fraction of CO 2 (XCO 2) data is crucial for
understanding the spatiotemporal patterns of XCO 2 and for mitigating carbon emissions …
understanding the spatiotemporal patterns of XCO 2 and for mitigating carbon emissions …