文章基本信息

标题：Analysis on the change of runoff curve number influence to surface flow debit using ALOS AVNIR-2 data imagery
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作者：Wenang Anurogo ; Kartika Pratiwi ; Muhammad Zainuddin Lubis 等
期刊名称：Jurnal Pendidikan Geografi
印刷版ISSN：0853-9251
电子版ISSN：2527-628X
出版年度：2022
卷号：27
期号：1
页码：15-25
DOI：10.17977/um017v27i12022p15-25
语种：English
出版社：Universitas Negeri Malang
摘要：One part of the hydrologic cycle which has a major influence in increasing the amount of river flow discharge is surface runoff. The higher surface runoff discharge, causing the possibility of surface flooding, therefore required an empirical model that can calculate the amount of surface runoff so as to produce updated data and quickly change according to their needs. One of the empirical methods that can be used to calculate the amount of surface runoff is by using the curve number method. This research is done by utilizing remote sensing image, that is, ALOS AVNIR-2. Data extraction from ALOS imagery includes land cover information using multispectral classification analysis, slope inclination information through visual interpretation, and land use interpretation. The runoff that occurred in Banjarnegara Regency tends to be high, that is, 61.24 percent of the total area of the research area. Large runoff with very high/extreme class spread on the form of hilly land to the old volcano complex at the study site. The runoff in the medium to low class only covers 3.56 percent of the total area and is distributed on the fluvial form with the flat-to-flat slopes. The result of analysis of runoff data is obtained from slope analysis and type of land use in the research location. Increasingly steep slope with little vegetation-land use, then the greater the runoff that occurs. Finally, the research result could be implemented into higher student class activity, especially in remote sensing classes, GIS, cloud computing, and big data analysis. By this process, the students will be improved their skills in analyzing imagery data as well as create new information derived from the remote sensing data.