AIMC Topic: Geographic Information Systems

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H3-MOSAIC: multimodal generative AI for semantic place detection from high-frequency GPS on H3 grids in mental health geomatics.

International journal of health geographics
BACKGROUND: Mental-health geomatics require reliable ways to convert high-frequency GPS trajectories into meaningful place types that support indicators such as homestay, location entropy, and spatial extent of daily activities. Raw coordinates are t...

Enhancing enviromics based predictions in common bean multi-environment trials.

Scientific reports
Enviromic approaches enhance predictive models by incorporating environmental data into selection frameworks. By integrating factor analytic (FA) models, enviromics, and Geographic Information Systems (GIS), the GIS-FA method was proposed to improve ...

Integrating machine learning and geospatial approaches for multi-hazard vulnerability mapping: implications for environmental health and contaminant risk in fragile ecosystems.

Environmental geochemistry and health
High-altitude ecosystems face growing threats from natural hazards and human activities, intensifying socio-economic and environmental risks. The Nilgiris District, Tamil Nadu, is a hotspot where steep terrain, fragile ecosystems, climate variability...

Assessment of climate change impacts on arsenic contamination in groundwater through machine learning, remote sensing, and GIS: a review.

Environmental geochemistry and health
More than 50% of the world's largest countries and cities depend on groundwater for their daily needs. In particular, 80% of the largest cities in the Middle East, South Asia, and Central Asia rely on groundwater for drinking, irrigation, and industr...

Harnessing Geospatial Artificial Intelligence (GeoAI) for Environmental Epidemiology: A Narrative Review.

Current environmental health reports
PURPOSE OF REVIEW: Geospatial analysis is an essential tool for research on the role of environmental exposures and health, and critical for understanding impacts of environmental risk factors on diseases with long latency (e.g. cardiovascular diseas...

GNN-RMNet: Leveraging graph neural networks and GPS analytics for driver behavior and route optimization in logistics.

PloS one
Logistics networks are becoming increasingly complex and rely more heavily on real-time vehicle data, necessitating intelligent systems to monitor driver behavior and identify route anomalies. Traditional techniques struggle to capture the dynamic sp...

Impact of Preseason Training Camps on Fitness, Fatigue, and Performance in Professional Football Players: Mildaltitude Camp Versus Sea-Level Camp.

International journal of sports physiology and performance
PURPOSE: Preseason in football is crucial for optimizing physical fitness, team cohesion, and tactical readiness. This study investigated the effects of 2 distinct preseason training environments-mild altitude with cooler conditions and sea level wit...

A novel framework integrating GeoAI and human perceptions to estimate walkability in Wuhan, China.

Scientific reports
Evidence shows enhanced walking environment promotes overall physical activities and further alleviates the risk of chronic diseases and mental disorders. Current walkability research is limited by traditional GIS methods that fail to capture micro-l...

GeoAI-based soil erosion risk assessment in the Brahmaputra River Basin: a synergistic approach using RUSLE and advanced machine learning.

Environmental monitoring and assessment
Soil erosion is a critical environmental issue in the Brahmaputra River Basin, threatening agricultural productivity, water resources, and ecological balance. This study employs the revised universal soil loss equation (RUSLE) alongside remote sensin...

GPS-based street-view greenspace exposure and wearable assessed physical activity in a prospective cohort of US women.

The international journal of behavioral nutrition and physical activity
BACKGROUND: Increasing evidence positively links greenspace and physical activity (PA). However, most studies use measures of greenspace, such as satellite-based vegetation indices around the residence, which fail to capture ground-level views and da...