Predictive Analytics for Identifying Land Cover Change Hotspots in the Mekong Region

Predictive Analytics for Identifying Land Cover Change Hotspots in the Mekong Region

Understanding land cover change dynamics and potential pathways of change is of critical importance for sustainable resource management, to promote food security and resilience on a range of spatial scales. Data scarcity is a key concern, however, with the availability of free Earth Observation (EO)...

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Bibliographic Details
Main Authors: Ate Poortinga, Aekkapol Aekakkararungroj, Kritsana Kityuttachai, Quyen Nguyen, Biplov Bhandari, Nyein Soe Thwal, Hannah Priestley, Jiwon Kim, Karis Tenneson, Farrukh Chishtie, Peeranan Towashiraporn, David Saah
Format: Article
Language:English
Published: MDPI AG 2020-05-01
Series:Remote Sensing
Subjects:
land cover change
land use planning
Mekong
remote sensing
machine learning
Online Access:https://www.mdpi.com/2072-4292/12/9/1472

Internet

https://www.mdpi.com/2072-4292/12/9/1472

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