AIMC Topic: Geographic Information Systems

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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...

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...

Cognition-enhanced geospatial decision framework integrating fuzzy FCA, surprisingly popular method, and a large language model.

Scientific reports
This study introduces a cognition-enhanced framework for geospatial decision-making by integrating Fuzzy Formal Concept Analysis (FCA), the Surprisingly Popular (SP) method, and a Large Language Model (GPT-4o). Our approach captures cognitive influen...

A comparative study of fully automatic and semi-automatic methods for oil spill detection using Sentinel-1 data.

Environmental monitoring and assessment
The oil spill detection and assessment study conducted in the Banten Province of Indonesia involves the application of Sentinel-1 satellite data and machine learning tools in the year 2024. Synthetic Aperture Radar (SAR) data were used with VV polari...

High-precision deformation monitoring and intelligent early warning for wellbore based on BDS/GNSS.

PloS one
To address the complex deformation of wellbores influenced by surrounding coal mining operations, this study employed an improved modified least-squares ambiguity decorrelation (MLAMBDA) algorithm based on the double-difference model for high-frequen...

Spatiotemporal patterns and climate-induced macroeconomic burden of malaria in sub-Saharan Africa.

BMC public health
BACKGROUND: The global malaria burden is characterized by economic, geographical, and climatic disparities, especially in sub-Saharan Africa (SSA). Moreover, meteorological factors have become increasingly important to understand the malaria burden i...

Management of sustainable urban green spaces through machine learning-supported MCDM and GIS integration.

Environmental science and pollution research international
This study evaluates green space suitability in İzmir's Konak district using the analytic hierarchy process, machine learning, weighted linear combination, and the technique for order preference by similarity to ideal solution methods, integrated wit...

The generative revolution: AI foundation models in geospatial health-applications, challenges and future research.

International journal of health geographics
In an era of rapid technological advancements, generative artificial intelligence and foundation models are reshaping industries and offering new advanced solutions in a wide range of scientific areas, particularly in public and environmental health....