Land Cover Mapping in Limited Labels Scenario: A Survey [preprint]
Preprint date
March 3, 2021
Authors
Rahul Ghosh (Ph.D. student), Xiaowei Jia (Ph.D. 2020), Vipin Kumar (professor)
Abstract
Land cover mapping is essential for monitoring global environmental change and managing natural resources. Unfortunately, traditional classification models are plagued by limited training data available in existing land cover products and data heterogeneity over space and time. In this survey, we provide a structured and comprehensive overview of challenges in land cover mapping and machine learning methods used to address these problems. We also discuss the gaps and opportunities that exist for advancing research in this promising direction.
Link to full paper
Land Cover Mapping in Limited Labels Scenario: A Survey
Keywords
data mining, machine learning, environmental data science