气候变化领域集成服务门户(CCPortal): A Machine Learning Approach to Estimating Land Use Change and Scenario Influence in Soil Infiltration at the Sub-Watershed Level

CCPortal

DOI	10.13044/j.sdewes.d11.0477
	A Machine Learning Approach to Estimating Land Use Change and Scenario Influence in Soil Infiltration at the Sub-Watershed Level
	Putra, Aditya Nugraha; Paimin, Saskia Karyna; Alfaani, Salsabila Fitri; Nita, Istika; Arifin, Syamsul; Munir, Mochammad
发表日期	2024
ISSN	1848-9257
起始页码	12
结束页码	1
卷号	12 期号:1
英文摘要	This research uses random forest machine learning to develop infiltration-friendly land-use scenarios, addressing the global 32% change in land use over the past six decades. The study used Sentinel-2A satellite imagery data for 2017, 2019, 2021, and 2022 as a land use baseline, predicting business as usual using cellular automata and comparing it with regional spatial planning and land capability scenarios. One hundred points of infiltration data were distributed using a random forest. Results showed that deforestation and its change into orchards, rice fields, and settlements over five years affected the infiltration. Business as usual reduces the high infiltration class to approximately 1,545 ha, while regional spatial planning and land capability cover 1,390 ha and 1,316 ha, respectively. The most infiltration-friendly land-use scenario is applicable at the sub-watershed level, with an accuracy of about 97%. The limitations of this research include not comparing extreme dry seasons and using 2022 infiltration values for all other years.
英文关键词	Machine learning; Remote sensing; Geostatistics; Hydrology; Disaster.
语种	英语
WOS研究方向	Environmental Sciences & Ecology
WOS类目	Environmental Sciences
WOS记录号	WOS:001112231100001
来源期刊	JOURNAL OF SUSTAINABLE DEVELOPMENT OF ENERGY WATER AND ENVIRONMENT SYSTEMS-JSDEWES
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/292611
作者单位	Brawijaya University
推荐引用方式 GB/T 7714	Putra, Aditya Nugraha,Paimin, Saskia Karyna,Alfaani, Salsabila Fitri,et al. A Machine Learning Approach to Estimating Land Use Change and Scenario Influence in Soil Infiltration at the Sub-Watershed Level[J],2024,12(1).
APA	Putra, Aditya Nugraha,Paimin, Saskia Karyna,Alfaani, Salsabila Fitri,Nita, Istika,Arifin, Syamsul,&Munir, Mochammad.(2024).A Machine Learning Approach to Estimating Land Use Change and Scenario Influence in Soil Infiltration at the Sub-Watershed Level.JOURNAL OF SUSTAINABLE DEVELOPMENT OF ENERGY WATER AND ENVIRONMENT SYSTEMS-JSDEWES,12(1).
MLA	Putra, Aditya Nugraha,et al."A Machine Learning Approach to Estimating Land Use Change and Scenario Influence in Soil Infiltration at the Sub-Watershed Level".JOURNAL OF SUSTAINABLE DEVELOPMENT OF ENERGY WATER AND ENVIRONMENT SYSTEMS-JSDEWES 12.1(2024).