AIMC Topic: Environmental Monitoring

Clear Filters Showing 191 to 200 of 1335 articles

Modeling Soil pH at regional scale using environmental covariates and machine learning algorithm.

Environmental monitoring and assessment
Soil pH serves as a critical indicator of soil chemistry and fertility, and mapping its spatial distribution holds significant importance for effective crop management. Digital soil mapping (DSM) is a commonly employed method for making rapid and cos...

An integrated IKOA-CNN-BiGRU-Attention framework with SHAP explainability for high-precision debris flow hazard prediction in the Nujiang river basin, China.

PloS one
Debris flows represent a persistent challenge for disaster prediction in mountainous regions due to their highly nonlinear and multivariate triggering mechanisms. This study proposes an explainable deep learning framework, the Improved Kepler Optimiz...

Climate change influences on algal bloom intensity in lakes in the Yangtze River Basin, China from 1985 to 2022.

Journal of hazardous materials
This study investigates the long-term influence of climate change on the spatiotemporal dynamics of harmful algal blooms in lakes larger than 10 km² across the Yangtze River Basin from 1985 to 2022. Using Landsat satellite imagery, we quantified bloo...

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
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 ...

Use of Artificial Neural Networks (ANNs) to assess xenobiotics in a river catchment using macroinvertebrates as bioindicators.

Aquatic toxicology (Amsterdam, Netherlands)
The Danube flows through various European regions, exposing its aquatic ecosystem to multiple stressors, including dams, canalization, and agricultural activities. Fertilizers, manures, pesticides, animal husbandry activities, irrigation practices, d...

Ecological risk assessment of oilfield soil through the use of machine learning combining with spatial interaction effects.

Ecotoxicology and environmental safety
With the intensification of oil extraction activities, total petroleum hydrocarbons (TPHs) and toxic elements contamination in soil around oil wells have become severe environmental problems. This paper proposed a novel method based on machine learni...

Decoding nutrient dynamics in coastal aquifers: Machine learning insights into submarine groundwater discharge and seawater intrusion in south India.

Chemosphere
Coastal aquifers are vulnerable to natural and human-induced processes that impact their resilience and ecosystems. Submarine Groundwater Discharge (SGD) and Seawater Intrusion (SWI) play crucial roles in transporting nutrients and contaminants into ...

Data-driven prediction of daily Cryptosporidium river concentrations for water resource management: Use of catchment-averaged vs spatially distributed features in a Bagging-XGBoost model.

The Science of the total environment
Cryptosporidium is a waterborne pathogen which poses a major challenge to water utilities because of its resistance to chlorination and its infectivity at very low concentrations. The ability to make predictions of Cryptosporidium concentrations in r...

Enhanced hermit crabs detection using super-resolution reconstruction and improved YOLOv8 on UAV-captured imagery.

Marine environmental research
Hermit crabs are vital to coastal ecosystems, serving as environmental health indicators and contributing to seed dispersal, debris cleanup, and soil disturbance. Traditional hermit crabs survey methods, like quadrat sampling, are labor-intensive and...

Tracking the spatial and temporal evolution of salt marsh vegetation based on UAV sampling and seasonal phenology from Landsat data.

Journal of environmental management
Salt marshes, valued for their ecological importance, have been increasingly degraded in recent decades. Preserving salt marshes necessitates a critical approach that involves monitoring vegetation distribution and species composition. This study pre...