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Forests

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Extreme fire weather is the major driver of severe bushfires in southeast Australia.

Science bulletin
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 ...

Forest Environmental Carrying Capacity Based on Deep Learning.

Computational intelligence and neuroscience
In this paper, we proposed an assessment system of forest environmental carrying capacity from many aspects and comprehensively evaluated and predicted the forest environmental carrying capacity of 40 cities in the Yangtze River Delta of China by usi...

Validation, analysis, and comparison of MISR V23 aerosol optical depth products with MODIS and AERONET observations.

The Science of the total environment
The latest Multi-angle Imaging Spectro Radiometer (MISR) Version (V) 23 aerosol optical depth (AOD) products were released, with an improved spatial resolution of 4.4 km, providing an unprecedented opportunity for the refined regional application. To...

Evaluation of deep learning and transform domain feature extraction techniques for land cover classification: balancing through augmentation.

Environmental science and pollution research international
The identification of features that can improve classification accuracy is a major concern in land cover classification research. This paper compares deep learning and transform domain feature extraction techniques for land cover classification of SA...

Automatic Segmentation of Standing Trees from Forest Images Based on Deep Learning.

Sensors (Basel, Switzerland)
Semantic segmentation of standing trees is important to obtain factors of standing trees from images automatically and effectively. Aiming at the accurate segmentation of multiple standing trees in complex backgrounds, some traditional methods have s...

Modelling flood susceptibility based on deep learning coupling with ensemble learning models.

Journal of environmental management
Modelling flood susceptibility is an indirect way to reduce the loss from flood disaster. Now, flood susceptibility modelling based on data driven model is state-of-the-art method such as ensemble learning and deep learning. However, the effect of de...

Assessment of the effects of the biotic and abiotic harmful factors on the amount of industrial wood production with deep learning.

Environmental science and pollution research international
The protection and sustainability of forest assets is possible with planned production of forest products to lead to minimum loss. One of the products obtained from forests is the industrial wood, which is the most important raw material for many sec...

Practical Guide to Honest Causal Forests for Identifying Heterogeneous Treatment Effects.

American journal of epidemiology
"Heterogeneous treatment effects" is a term which refers to conditional average treatment effects (i.e., CATEs) that vary across population subgroups. Epidemiologists are often interested in estimating such effects because they can help detect popula...

Soundscapes and deep learning enable tracking biodiversity recovery in tropical forests.

Nature communications
Tropical forest recovery is fundamental to addressing the intertwined climate and biodiversity loss crises. While regenerating trees sequester carbon relatively quickly, the pace of biodiversity recovery remains contentious. Here, we use bioacoustics...

Three-dimensional forest foodscape in large herbivores' habitat based on UAV with LiDAR detection.

Integrative zoology
With the development of artificial intelligence, the integration of LiDAR technologies and foodscape theories to study wildlife habitat, nutritional ecology, species coexistence, and other existing hot and difficult issues would become an internation...