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Remote Sensing Technology

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Gross primary productivity estimation through remote sensing and machine learning techniques in the high Andean Region of Ecuador.

International journal of biometeorology
Accurately estimating gross primary productivity (GPP) is crucial for simulating the carbon cycle and addressing the challenges of climate change. However, estimating GPP is challenging due to the absence of direct measurements at scales larger than ...

Understanding ecosystem services of detailed forest and wetland types using remote sensing and deep learning techniques in Northern China.

Journal of environmental management
Spanning both temperate and sub-frigid zones, Northeast China boasts typical boreal forests and abundant wetland resources. Because of these attributes, the region is critically significant for global climate regulation, carbon sequestration, and bio...

Long-term water quality assessment in coastal and inland waters: An ensemble machine-learning approach using satellite data.

Marine pollution bulletin
Accurate estimation of coastal and in-land water quality parameters is important for managing water resources and meeting the demand of sustainable development goals. The water quality monitoring based on discrete water sample analysis is limited to ...

Forest Aboveground Biomass Estimation Based on Unmanned Aerial Vehicle-Light Detection and Ranging and Machine Learning.

Sensors (Basel, Switzerland)
is a widely planted species in plantation forests because of its outstanding characteristics, such as fast growth rate and high adaptability. Accurate and rapid prediction of biomass is important for plantation forest management and the prediction ...

Leveraging GIS-based AHP, remote sensing, and machine learning for susceptibility assessment of different flood types in peshawar, Pakistan.

Journal of environmental management
Due to its diverse topography, Pakistan faces different types of floods each year, which cause substantial physical, environmental, and socioeconomic damage. However, the susceptibility of specific regions to different flood types remains unexplored....

Assessing long-term water storage dynamics in Afghanistan: An integrated approach using machine learning, hydrological models, and remote sensing.

Journal of environmental management
Assessment of Terrestrial Water Storage (TWS) components is crucial for understanding regional climate and water resources, particularly in arid and semi-arid regions like Afghanistan. Given the scarcity of ground-based data, this study leverages rem...

Wastewater treatment plant site selection using advanced decision tree machine learning and remote sensing techniques.

Environmental science and pollution research international
Wastewater treatment plants in Coimbatore South are under pressure from rapid urbanization, inadequate infrastructure, and industrial pollution, leading to environmental and public health concerns. This study aimed to identify suitable locations for ...

Multitemporal monitoring of forest indicator species using UAV and machine learning image recognition.

Environmental monitoring and assessment
In natural restoration, it is important to improve the efficiency of monitoring. Remote sensing using unmanned aerial vehicle (UAV) platforms plays a major role in improving monitoring efficiency. UAV platforms are particularly suited for monitoring ...

Extraction of agricultural plastic greenhouses based on a U-Net convolutional neural network coupled with edge expansion and loss function improvement.

Journal of the Air & Waste Management Association (1995)
Agricultural plastic greenhouses (APGs) are crucial for sustainable agricultural planting, and accurate spatial distribution information acquisition is crucial. Deep learning network models can extract target features from remote sensing images more ...

Riverbed litter monitoring using consumer-grade aerial-aquatic speedy scanner (AASS) and deep learning based super-resolution reconstruction and detection network.

Marine pollution bulletin
Underwater litter is widely spread across aquatic environments such as lakes, rivers, and oceans, significantly impacting natural ecosystems. Current automated monitoring technologies for detecting this litter face limitations in survey efficiency, c...