AIMC Topic: Forests

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Explainable few-shot learning workflow for detecting invasive and exotic tree species.

Scientific reports Jul 2, 2025
Deep Learning methods are notorious for relying on extensive labeled datasets to train and assess their performance. This can cause difficulties in practical situations where models should be trained for new applications for which very little data is...
Algorithms Brazil Deep Learning Neural Networks, Computer Trees Introduced Species Unmanned Aerial Devices Workflow Forests
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Exploring the spatiotemporal influence of climate on American avian migration with random forests.

Scientific reports Jul 1, 2025
Birds have adapted to climatic and ecological cycles to inform their Spring and Fall migration timings, but anthropogenic global warming has affected these long-establish cycles. Understanding these dynamics is critical for conservation during a chan...
Animal Migration Animals Random Forest Machine Learning Birds Forests Climate Change Spatio-Temporal Analysis Seasons Climate
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Monitoring temporal changes in large urban street trees using remote sensing and deep learning.

PloS one Jun 26, 2025
In the rapidly changing dynamics of urbanization, urban forests offer numerous benefits to city dwellers. However, the information available on these resources is often outdated or non-existent, leading in part to inequitable access to these benefits...
Humans Ecosystem Deep Learning Forests Trees San Francisco Cities Remote Sensing Technology Urbanization
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Deforestation driven by illegal and informal gold mining in the southern Peruvian Amazon: a predictive land use analysis over the next 50 years.

Environmental monitoring and assessment Jun 23, 2025
The Amazon is recognized not only for its vast biodiversity and territorial extent but also for the significant mineral riches it harbors. This potential has intensified small-scale illegal and informal gold mining, a practice often employed without ...
Conservation of Natural Resources Mining Environmental Monitoring Forests Peru Gold
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Machine learning techniques for continuous genetic assignment of geographic origin of forest trees.

PloS one Jun 6, 2025
Origin tracking is important to ensure use of the right seed source and trade with legally harvested timber. Additionally, it can help to reconstruct human-caused historical long-distance seed transfer and to spot mislabelling in forest field trials....
Europe Forests Quercus Fagus Trees Humans Machine Learning Polymorphism, Single Nucleotide
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Remote sensing-based detection of brown spot needle blight: a comprehensive review, and future directions.

PeerJ May 22, 2025
Pine forests are increasingly threatened by needle diseases, including Brown Spot Needle Blight (BSNB), caused by . BSNB leads to needle loss, reduced growth, significant tree mortality, and disruptions in global timber production. Due to its severit...
Pinus Forests Plant Diseases Ascomycota Plant Leaves Remote Sensing Technology
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Modeling climate change impacts and predicting future vulnerability in the Mount Kenya forest ecosystem using remote sensing and machine learning.

Environmental monitoring and assessment May 6, 2025
The Mount Kenya forest ecosystem (MKFE), a crucial biodiversity hotspot and one of Kenya's key water towers, is increasingly threatened by climate change, putting its ecological integrity and vital ecosystem services at risk. Understanding the intera...
Ecosystem Environmental Monitoring Forests Climate Change Remote Sensing Technology Machine Learning Conservation of Natural Resources Kenya
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Modeling land use and land cover dynamics of Bale Mountains National Park using Google Earth Engine and cellular automata-artificial neural network (CA-ANN) model.

PloS one Apr 30, 2025
This research aimed to assess the observed land use and land cover (LULC) changes of Bale Mountains National Park (BMNP) from 1993 to 2023 and its future projections for the years (2033 and 2053). The study utilized multi-date Landsat imagery from 19...
Parks, Recreational Algorithms Humans Satellite Imagery Conservation of Natural Resources Neural Networks, Computer Forests
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Spatial and temporal classification and prediction of aspen probability in boreal forests using machine learning algorithms.

Environmental monitoring and assessment Apr 9, 2025
Mapping and classifying the probability of occurrence of Populus tremula L. (aspen) in boreal forests is a complex task for sustainable forest management and biodiversity conservation. As a key broadleaved species in the taiga region, aspen supports ...
Populus Algorithms Environmental Monitoring Taiga Biodiversity Forests Machine Learning Forestry
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Forest fire susceptibility mapping using multi-criteria decision making and machine learning models in the Western Ghats of India.

Journal of environmental management Mar 9, 2025
Forest fires have significantly increased over the last decade due to shifts in rainfall patterns, warmer summers, and long spells of dry weather events in the coastal regions. Assessment of susceptibility to forest fires has become an important mana...
Remote Sensing Technology Fires Forests India Decision Making Machine Learning Geographic Information Systems Wildfires
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