Distinguishing between Hazardous Flooding and Non-Hazardous Agronomic Inundation in Irrigated Rice Fields: A Case Study from West Java']Java

被引:5
|
作者
Sianturi, Riswan [1 ]
Jetten, Victor G. [1 ]
Ettema, Janneke [1 ]
Sartohadi, Junun [2 ]
机构
[1] Univ Twente, Fac Geoinformat Sci & Earth Observat ITC, NL-7514 AE Enschede, Netherlands
[2] Univ Gadjah Mada, Fac Geog, Yogyakarta 55281, Indonesia
来源
REMOTE SENSING | 2018年 / 10卷 / 07期
关键词
MOD09A1; irrigated rice fields; flooding; agronomic inundation; West [!text type='Java']Java[!/text; DIFFERENCE WATER INDEX; MULTITEMPORAL MODIS IMAGES; VEGETATION INDEXES; ACCURACY ASSESSMENT; AGRICULTURE; MANAGEMENT; RISK; NDWI; CLASSIFICATION; HETEROGENEITY;
D O I
10.3390/rs10071003
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
An accurate flood detection method is essential for obtaining areas of irrigated rice fields affected by flooding. This paper aims to distinguish between rice fields with flooding and rice fields with agronomic inundation using MODerate resolution Imaging Spectroradiometer (MODIS) 8 day 500 m spatial resolution (MOD09A1) imageries over irrigated rice fields with complex cropping patterns in West Java. Over the past decade, Enhanced Vegetation Index (EVI) <= 0.1 derived from moderate resolution remote sensing imageries has been used for detecting flooding in irrigated rice fields. Without additional farming information, this paper argues that EVI <= 0.1 cannot estimate flood areas correctly, given the existence of both hazardous flooding and non-hazardous agronomic inundation in irrigated rice fields. Adding a threshold of 40-day duration representing land preparation and transplanting activities enables EVI <= 0.1 to distinguish between agronomic inundation and flooding in irrigated rice fields. The difference in the Start of Season (SOS) between the wet planting season 2013/2014 and long-term average (2000-2015) shows that the Overall Accuracy (OA) and F1 scores are 75.96% and 81.74%, respectively. The confusion matrix using the respondents' reports shows OA of 80.5% and Kappa of 60.16%. The quality of flood maps is partly influenced by environmental processes, human decisions, and mixed pixels.
引用
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页数:21
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