AIMC Topic: Forests

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Flash droughts threaten global managed forests.

Nature communications
Flash droughts, characterized by rapid onset and increasing frequency, pose significant threats to ecosystem stability and function. However, there remains no global consensus regarding forest responses to flash droughts. Here, using a reconstructed ...

Ecology-informed symbolic machine learning: a methodological framework for classification of forest succession.

Environmental monitoring and assessment
Accurately classifying forest successional stages remains a major challenge in applied ecology due to the continuum of succession, ecological heterogeneity, and limited interpretability of many machine learning (ML) approaches. Prevailing models typi...

Deep learning-based forest fire detection using an improved SSD algorithm with CBAM.

PloS one
Fires are characterized by their sudden onset, rapid spread, and destructive nature, often causing irreversible damage to ecosystems. To address the challenges in forest fire detection, including the varying scales and complex features of flame and s...

Real-time deforestation anomaly detection using YOLO and LangChain agents for sustainable environmental monitoring.

Scientific reports
Deforestation continues to pose a major threat to global ecosystems, biodiversity, and climate resilience, demanding intelligent and timely monitoring solutions. This study introduces a novel framework that integrates YOLOv8 (You Only Look Once) obje...

Automated forest land division using deep learning and drone imagery.

PloS one
This paper proposes an automated solution for tree enumeration in areas designated for forest land division using drone image processing. Traditional tree counting methods are time-consuming and error-prone. Our approach leverages drone imagery and a...

Fires enhanced productivity in fire-adapted subtropical pinelands of the Florida Everglades.

The Science of the total environment
Some ecosystems require regular disturbances to maintain their biological and structural diversity. However, shifts in climate and changes in land management practices have altered global fire regimes, making it challenging to determine the most effe...

Prediction of changes in suitable habitats for tea plants in China's four major tea-producing regions based on machine learning models.

PloS one
Under the background of ongoing global climate warming, clarifying the spatiotemporal dynamics of suitable habitats for tea plants and their potential impact on forest ecosystems is essential for promoting sustainable tea industry development and eco...

Estimation of woody vegetation biomass in Australia based on multi-source remote sensing data and stacking models.

Scientific reports
Vegetation serves as the most critical carbon reservoir within terrestrial ecosystems and plays a vital role in mitigating global climate change. Australia features a vast and diverse landscape, ranging from dense eucalyptus forests to sparse woodlan...

Evaluating the effectiveness of the forest pests and diseases control methods on the industrial wood production using deep learning.

Scientific reports
Industrial wood production plays a vital role in the economies of many countries by supplying raw materials for a wide range of sectors, including construction, paper, and pulp industries. However, the industry is increasingly challenged by the detri...

When crops fail, forests follow: Agricultural shocks and deforestation in Zambia.

Proceedings of the National Academy of Sciences of the United States of America
As climate change makes agricultural production shocks more frequent and severe, it is vital to understand their effect on farmer welfare, land use, and deforestation. Theoretically, a change in agricultural productivity could increase or decrease de...