AIMC Topic: Forests

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Demi-decadal land use land cover change analysis of Mizoram, India, with topographic correction using machine learning algorithm.

Environmental science and pollution research international Apr 12, 2024
Mizoram (India) is part of UNESCO's biodiversity hotspots in India that is primarily populated by tribes who engage in shifting agriculture. Hence, the land use land cover (LULC) pattern of the state is frequently changing. We have used Landsat 5 and...
Algorithms India Machine Learning Forests Conservation of Natural Resources Agriculture Support Vector Machine
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Wood identification based on macroscopic images using deep and transfer learning approaches.

PeerJ Feb 28, 2024
Identifying forest types is vital for evaluating the ecological, economic, and social benefits provided by forests, and for protecting, managing, and sustaining them. Although traditionally based on expert observation, recent developments have increa...
Machine Learning Forests Artificial Intelligence Wood Mental Recall
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Sensors for Digital Transformation in Smart Forestry.

Sensors (Basel, Switzerland) Jan 25, 2024
Smart forestry, an innovative approach leveraging artificial intelligence (AI), aims to enhance forest management while minimizing the environmental impact. The efficacy of AI in this domain is contingent upon the availability of extensive, high-qual...
Artificial Intelligence Forestry Technology Forests Conservation of Natural Resources Humans
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Robotic monitoring of forests: a dataset from the EU habitat 9210* in the Tuscan Apennines (central Italy).

Scientific data Dec 1, 2023
Effective monitoring of habitats is crucial for their preservation. As the impact of anthropic activities on natural habitats increases, accurate and up-to-date information on the state of ecosystems has become imperative. This paper presents a new d...
Italy Forests Ecosystem Robotics Conservation of Natural Resources
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Soundscapes and deep learning enable tracking biodiversity recovery in tropical forests.

Nature communications Oct 17, 2023
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...
Tropical Climate Biodiversity Forests Trees Conservation of Natural Resources Ecosystem Animals Deep Learning
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Three-dimensional forest foodscape in large herbivores' habitat based on UAV with LiDAR detection.

Integrative zoology Oct 8, 2023
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...
Ecosystem Forests Ecology Herbivory Artificial Intelligence Animals
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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 Jan 16, 2023
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...
Trees Wood Conservation of Natural Resources Deep Learning Industry Forestry Forests
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Modelling flood susceptibility based on deep learning coupling with ensemble learning models.

Journal of environmental management Oct 11, 2022
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...
Floods Forests Deep Learning Disasters ROC Curve
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Validation, analysis, and comparison of MISR V23 aerosol optical depth products with MODIS and AERONET observations.

The Science of the total environment Sep 29, 2022
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...
Humans Forests Reproducibility of Results Aerosols Robotics
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Forest Environmental Carrying Capacity Based on Deep Learning.

Computational intelligence and neuroscience Sep 27, 2022
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...
Forests China Deep Learning Conservation of Natural Resources Rivers Cities
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