Utilising land use scenario modeling and machine learning for mitigating drought risks in degraded landscapes
Authors
Aditya Nugraha Putra
Department of Land and Water Resources Management, Faculty of Civil Engineering, Slovak University of Technology in Bratislava, Bratislava, Slovakia
Soil Science Department, Faculty of Agriculture, Brawijaya University, Indonesia
Sephia Dewi Meila Chrisaputri
Agroecotechnology Study Program, Faculty of Agriculture, Brawijaya University, Indonesia
Cindy Monica Manurung
Agroecotechnology Study Program, Faculty of Agriculture, Brawijaya University, Indonesia
Michelle Talisia Sugiarto
Soil and Water Management Study Program, Faculty of Agriculture, Brawijaya University, Indonesia
Novandi Rizky Prasetya
Soil and Water Management Study Program, Faculty of Agriculture, Brawijaya University, Indonesia
Irma Ardi Kusumawati
Yayasan Bumi Hijau Lestari, Indonesia
Istika Nita
Soil Science Department, Faculty of Agriculture, Brawijaya University, Indonesia
Mohd Hasmadi Ismail
Faculty of Forestry and Environment, Universiti Putra Malaysia, Malaysia
Silvia Kohnová
Department of Land and Water Resources Management, Faculty of Civil Engineering, Slovak University of Technology in Bratislava, Bratislava, Slovakia
Kamila Hlavčová
Department of Land and Water Resources Management, Faculty of Civil Engineering, Slovak University of Technology in Bratislava, Bratislava, Slovakia
Language: English
Page range: 260 - 272
Submitted on: Apr 16, 2025
Accepted on: Jul 19, 2025
Published on: Sep 27, 2025
Published by: Slovak Academy of Sciences, Institute of Hydrology
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year
Keywords:
Related subjects:
© 2025 Aditya Nugraha Putra, Sephia Dewi Meila Chrisaputri, Cindy Monica Manurung, Michelle Talisia Sugiarto, Novandi Rizky Prasetya, Irma Ardi Kusumawati, Istika Nita, Mohd Hasmadi Ismail, Silvia Kohnová, Kamila Hlavčová, published by Slovak Academy of Sciences, Institute of Hydrology
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.