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Forests

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The Effect of Synergistic Approaches of Features and Ensemble Learning Algorith on Aboveground Biomass Estimation of Natural Secondary Forests Based on ALS and Landsat 8.

Sensors (Basel, Switzerland)
Although the combination of Airborne Laser Scanning (ALS) data and optical imagery and machine learning algorithms were proved to improve the estimation of aboveground biomass (AGB), the synergistic approaches of different data and ensemble learning ...

Identifying of Quercus vulcanica and Q. frainetto growing in different environments through deep learning analysis.

Environmental monitoring and assessment
Quercus is one of the important elements of forests worldwide. But the diagnosis of the species in this genus in particular using leaves is pretty challenging due to the presence of natural hybrids and phenotypically plastic trait expression. In this...

Deep diagnostic agent forest (DDAF): A deep learning pathogen recognition system for pneumonia based on CT.

Computers in biology and medicine
BACKGROUND: Even though antibiotics agents are widely used, pneumonia is still one of the most common causes of death around the world. Some severe, fast-spreading pneumonia can even cause huge influence on global economy and life security. In order ...

Forest fire detection system using wireless sensor networks and machine learning.

Scientific reports
Forest fires have become a major threat around the world, causing many negative impacts on human habitats and forest ecosystems. Climatic changes and the greenhouse effect are some of the consequences of such destruction. Interestingly, a higher perc...

Machine Learning Predicts Biogeochemistry from Microbial Community Structure in a Complex Model System.

Microbiology spectrum
Microbial community structure is influenced by the environment and in turn exerts control on many environmental parameters. We applied this concept in a bioreactor study to test whether microbial community structure contains information sufficient to...

Improving neural network classification of indigenous forest in New Zealand with phenological features.

Journal of environmental management
Accurate and up-to-date land cover maps inform and support effective management and policy decisions. Describing phenological changes in spectral response using time-series data may help to distinguish vegetation types, thereby allowing for more spec...

Digital Transformation in Smart Farm and Forest Operations Needs Human-Centered AI: Challenges and Future Directions.

Sensors (Basel, Switzerland)
The main impetus for the global efforts toward the current digital transformation in almost all areas of our daily lives is due to the great successes of artificial intelligence (AI), and in particular, the workhorse of AI, statistical machine learni...

Revealing the real-time diversity and abundance of small mammals by using an Intelligent Animal Monitoring System (IAMS).

Integrative zoology
It is challenging to reveal the real-time spatio-temporal change of diversity and abundance of animals in natural systems by using traditional methods. The rapid advancement of new technologies such as the Internet of Things, artificial intelligence,...

Evaluating the Forest Ecosystem through a Semi-Autonomous Quadruped Robot and a Hexacopter UAV.

Sensors (Basel, Switzerland)
Accurate and timely monitoring is imperative to the resilience of forests for economic growth and climate regulation. In the UK, forest management depends on citizen science to perform tedious and time-consuming data collection tasks. In this study, ...

Study on TLS Point Cloud Registration Algorithm for Large-Scale Outdoor Weak Geometric Features.

Sensors (Basel, Switzerland)
With the development of societies, the exploitation of mountains and forests is increasing to meet the needs of tourism, mineral resources, and environmental protection. The point cloud registration, 3D modeling, and deformation monitoring that are i...