Spatio-Temporal Wildfire Prediction using Multi-Modal Data

Spatio-temporal Estimation of Wildfire Growth

This work presents a methodology for real-time estimation of wildland fire growth, utilizing a fire growth model based on a set of partial differential equations for prediction, and harnessing concepts of space-time Kalman filtering and Proper Orthogonal Decomposition techniques towards low dimensional estimation of potentially large spatio-temporal states. The estimation framework is discussed...

Multi - Dimensional Modal Logi as a Framework for Spatio - Temporal

A Spatio-temporal Multi-modal Data Management and Analysis Environment for Tracking MS Lesions

We describe the development of a system that automates data collection, metadata extraction and analysis of spatio-temporal multi-modal data, combining data management and data analysis to provide an efficient resource for clinicians. Though the system is extensible to many applications, the current focus is on managing Multiple Sclerosis (MS) lesion data, which are disparate streams of image, ...

Integrated Spatio-temporal Data Mining for Forest Fire Prediction

Forests play a critical role in sustaining the human environment. Most forest fires not only destroy the natural environment and ecological balance, but also seriously threaten the security of life and property. The early discovery and forecasting of forest fires are both urgent and necessary for forest fire control. This article explores the possible applications of Spatio-temporal Data Mining...

Multi-modal Target Prediction

Users with severe motor impairment often depends on alternative input devices like eye-gaze or head movement trackers to access computers. However these devices are not as fast as computer mouse and often turn difficult to use. We have proposed a Neural-network based model that can predict pointing target by analyzing pointing trajectory. We have validated the model for standard computer mouse,...