AIMC Topic: Forests

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Mapping spatiotemporal distribution of forest carbon density in Xizang, China.

PloS one
Climate warming is a major global challenge, and forests, essential carbon sinks, are critical in mitigating its effects. Forest carbon density is a key parameter in assessing the carbon sinks. Traditional estimating methods of forest carbon density ...

Multi-branch and multi-label tree species classification using deep learning for UAV aerial photography and Sentinel remote sensing images.

Scientific reports
The classification and identification of forest tree species is of great value in the study of species diversity and forest monitoring. With the development of emerging technologies, the combination of remote sensing images and deep learning methods ...

A meta-analysis of predictive accuracies and errors of biomass estimation models in Sub-Saharan Africa.

The Science of the total environment
Accurate biomass estimation is essential for forest monitoring, energy planning and carbon accounting in Sub-Saharan Africa (SSA), where destructive sampling is often impractical. Biomass estimation models (BEMs) offer scalable alternatives, but thei...

Causal inference unveils how forest coverage mitigates excess snakebite cases during rainfall seasons in Colombia.

Scientific reports
Snakebite envenoming is a neglected tropical disease that affects mainly rural populations, where antivenom is scarce. Understanding environmental drivers of snakebite incidence is critical for public health preparedness. This study employs causal in...

Artificial vision models for the identification of Mediterranean flora: An analysis in four ecosystems.

PloS one
Object identification has been widely used in several applications, utilising the annotated data with bounding boxes to specify each object's exact location and category in images and videos. However, relatively little research has been conducted on ...

Aboveground biomass estimation using multimodal remote sensing observations and machine learning in mixed temperate forest.

Scientific reports
Plants sequester carbon in their aboveground components, making aboveground tree biomass a key metric for assessing forest carbon storage. Traditional methods of aboveground biomass (AGB) estimation via Forest Inventory and Analysis (FIA) plots lack ...

Indigenous wood species classification using a multi-stage deep learning with grad-CAM explainability and an ensemble technique for Northern Bangladesh.

PloS one
Wood species recognition has recently emerged as a vital field in the realm of forestry and ecological conservation. Early studies in this domain have offered various methods for classifying distinct wood species found worldwide using data collected ...

Inversion and validation of soil water-holding capacity in a wild fruit forest, using hyperspectral technology combined with machine learning.

Scientific reports
Soil water retention is a critical aspect of water conservation. To quantitatively assess the Soil Water-Holding Capacity (SWHC), this study focused on a typical wild fruit forest in Xinjiang, China. The spectral characteristics of the forest canopy ...

Predictive modelling of land use land cover dynamics for a coastal urban city in Brazil.

Journal of environmental management
Better urban planning depends on assessing how land use and land cover (LULC) have evolved in recent decades and what the prospects are for change in the future. Cities are the result of various factors interacting, and land configuration directly in...

A data-driven approach to forest health assessment through multivariate analysis and machine learning techniques.

BMC plant biology
BACKGROUND: Himalayan forests are fragile, rich in biodiversity, and face increasing threats from anthropogenic pressures and climate change. Assessing their health is critical for sustainable forest management. This study integrated ecological indic...