Monitoring Land-Cover Changes: A Machine-Learning Perspective

By Anuj Karpatne, Zhe Jiang, Ranga Raju Vatsavai, Shashi Shekhar, Vipin Kumar. 2016

85 citations recorded by the source corpus.

Subfields: Ecology, Global and Planetary Change, Media Technology

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Ecology

1. Anuj Karpatne
2. James Gerber
3. Paul C. West
4. Patrick Meyfroidt

In Global and Planetary Change

1. Anuj Karpatne
2. Vipin Kumar
3. Gowtham Atluri
4. Michael S. Steinbach
5. Shashi Shekhar
6. James H. Faghmous
7. Arindam Banerjee
8. Auroop Ratan Ganguly

In Media Technology

1. Anuj Karpatne
2. Vipin Kumar

Citations in the corpus

• Theory-Guided Data Science: A New Paradigm for Scientific Discovery from Data (2016, background): “signals, and the inherent variability of water and land classes over space and time [58], [59].”
• Predict Land Covers with Transition Modeling and Incremental Learning (2017, background): “In addition, the prediction of these land covers become even more challenging due to the temporal variation [11].”
• Spatio-Temporal Data Mining (2017, methodology): “Other techniques for time-series change detection have been explored in remote sensing applications (Karpatne et al. 2016a), e.”