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Ecosystem

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Deep learning-based image classification of sea turtles using object detection and instance segmentation models.

PloS one
Sea turtles exhibit high migratory rates and occupy a broad range of habitats, which in turn makes monitoring these taxa challenging. Applying deep learning (DL) models to vast image datasets collected from citizen science programs can offer promisin...

Towards efficient IoT communication for smart agriculture: A deep learning framework.

PloS one
The integration of IoT (Internet of Things) devices has emerged as a technical cornerstone in the landscape of modern agriculture, revolutionising the way farming practises are viewed and managed. Smart farming, enabled by interconnected sensors and ...

Uncovering global risk to human and ecosystem health from pesticides in agricultural surface water using a machine learning approach.

Environment international
Pesticides typically co-occur in agricultural surface waters and pose a potential threat to human and ecosystem health. As pesticide screening in global agricultural surface waters is an immense analytical challenge, a detailed risk picture of pestic...

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 ...

Habitat selection ecology of the aquatic beetle community using explainable machine learning.

Scientific reports
The aim of our work is to determine the importance of habitat features for the selection of the aquatic beetle community. Insects are represented by their general ecological traits such as body size, ecological element and trophic type, which are cat...

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...

A spatial machine learning approach to exploring the impacts of coal mining and ecological restoration on regional ecosystem health.

Environmental research
Ecosystem health is an important approach to measuring urban and regional sustainability. In previous studies, the spatiotemporal changes of ecosystem health have been addressed using comprehensive assessment index system. However, the quantitative c...

Robots and animals teaming up in the wild to tackle ecosystem challenges.

Science robotics
Interactively teaming up animals and robots could facilitate basic scientific research and address environmental and ecological crises.

Water environment risk prediction method based on convolutional neural network-random forest.

Marine pollution bulletin
The accelerated processes of urbanization and industrialization globally have resulted in an increased risk to aquatic environments, posing a significant threat to the sustainable management of water resources and the health of ecosystems. Accurate p...

Multi-temporal image analysis of wetland dynamics using machine learning algorithms.

Journal of environmental management
Wetlands play a crucial role in enhancing groundwater quality, mitigating natural hazards, controlling erosion, and providing essential habitats for unique flora and wildlife. Despite their significance, wetlands are facing decline in various global ...