AIMC Topic: Forests

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

Environmental monitoring and assessment Nov 4, 2021
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...
Forests Trees Quercus Deep Learning Environmental Monitoring
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Extreme fire weather is the major driver of severe bushfires in southeast Australia.

Science bulletin Oct 5, 2021
In Australia, the proportion of forest area that burns in a typical fire season is less than for other vegetation types. However, the 2019-2020 austral spring-summer was an exception, with over four times the previous maximum area burnt in southeast ...
Forests Fires Wildfires Humans Weather Australia
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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) Sep 6, 2021
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 ...
Forests Lasers Biomass China Machine Learning
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Characterizing and forecasting the responses of tropical forest leaf phenology to El Nino by machine learning algorithms.

PloS one Aug 26, 2021
Climate change and global warming have serious adverse impacts on tropical forests. In particular, climate change may induce changes in leaf phenology. However, in tropical dry forests where tree diversity is high, species responses to climate change...
El Nino-Southern Oscillation Tropical Climate Plant Leaves Forests Machine Learning Trees Seasons Algorithms Plant Physiological Phenomena
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Prediction of soil-bearing capacity on forest roads by statistical approaches.

Environmental monitoring and assessment Jul 28, 2021
The soil-bearing capacity is one of the important criteria in dimensioning the superstructure. In Turkey, predictability of California Bearing Ratio values, which may be used in the planning and dimensioning of forest roads, of which about 26% lacks ...
Environmental Monitoring Fuzzy Logic Turkey Forests Soil
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Hyperspectral band selection and modeling of soil organic matter content in a forest using the Ranger algorithm.

PloS one Jun 28, 2021
Effective soil spectral band selection and modeling methods can improve modeling accuracy. To establish a hyperspectral prediction model of soil organic matter (SOM) content, this study investigated a forested Eucalyptus plantation in Huangmian Fores...
Forests China Support Vector Machine Models, Biological Eucalyptus Neural Networks, Computer Farms
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Predicting direct and indirect non-target impacts of biocontrol agents using machine-learning approaches.

PloS one Jun 1, 2021
Biological pest control (i.e. 'biocontrol') agents can have direct and indirect non-target impacts, and predicting these effects (especially indirect impacts) remains a central challenge in biocontrol risk assessment. The analysis of ecological netwo...
Animals Phylogeny Machine Learning Lepidoptera Food Chain Introduced Species Forests Diptera Hymenoptera Pest Control, Biological Host-Parasite Interactions
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Identifying the vegetation type in Google Earth images using a convolutional neural network: a case study for Japanese bamboo forests.

BMC ecology Nov 27, 2020
BACKGROUND: Classifying and mapping vegetation are crucial tasks in environmental science and natural resource management. However, these tasks are difficult because conventional methods such as field surveys are highly labor-intensive. Identificatio...
Neural Networks, Computer Machine Learning Forests Japan
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A Machine Learning Ensemble Approach Based on Random Forest and Radial Basis Function Neural Network for Risk Evaluation of Regional Flood Disaster: A Case Study of the Yangtze River Delta, China.

International journal of environmental research and public health Dec 19, 2019
The Yangtze River Delta (YRD) is one of the most developed regions in China. This is also a flood-prone area where flood disasters are frequently experienced; the situations between the people-land nexus and the people-water nexus are very complicate...
Rivers Floods Cities Forests Geographic Information Systems China Machine Learning Ecosystem Neural Networks, Computer Risk Assessment
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Artificial neural networks: Modeling tree survival and mortality in the Atlantic Forest biome in Brazil.

The Science of the total environment Jul 18, 2018
Models to predict tree survival and mortality can help to understand vegetation dynamics and to predict effects of climate change on native forests. The objective of the present study was to use Artificial Neural Networks, based on the competition in...
Neural Networks, Computer Ecosystem Forests Climate Change Brazil Trees Environmental Monitoring
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