A MACHINE LEARNING APPROACH FOR IMAGE CLASSIFICATION FOR MAPPING AND MONITORING LAND-COVER AND LAND-USE IN THE USA/MEXICO BORDER

A MACHINE LEARNING APPROACH FOR IMAGE CLASSIFICATION FOR MAPPING AND MONITORING LAND-COVER AND LAND-USE IN THE USA/MEXICO BORDER

PI: Jorge Munoz

Sponsor: CONSEJO NACIONAL DE CIENCIA Y TECNOLOGIA THROUGH THE UNIVERSITY OF TEXAS AT SAN ANTONIO

Physics

Amount awarded: $60,241

This project proposes a new method for urban land use mapping, which integrates machine learning, GIS, spatial metrics, and texture analysis in an object-based image analysis classification.

Posting date: Wed, 06/24/2020

Award start date: Thu, 10/01/2020

Award end date: Thu, 09/30/2021