Incorporating crop phenological trajectory and texture for paddy rice detection with time series MODIS, HJ-1A and ALOS PALSAR imagery

doi:10.1080/22797254.2018.1556568

	Incorporating crop phenological trajectory and texture for paddy rice detection with time series MODIS, HJ-1A and ALOS PALSAR imagery
	Singha, Mrinal 1; Sarmah, Sangeeta 2
刊名	EUROPEAN JOURNAL OF REMOTE SENSING
	2019
卷号	52 期号:1 页码:73-87
关键词	Paddy rice phenology texture MODIS NDVI HJ-1A PALSAR object-based image analysis
DOI	10.1080/22797254.2018.1556568
通讯作者	Singha, Mrinal(mrn3306@gmail.com)
英文摘要	Repeated monitoring of paddy rice is essential for government agencies and policy makers to maintain the balance of supply and demand for rice. Recent studies have mostly concentrated on the mapping of paddy rice with temporal satellite imagery during growing seasons. Given the phenological variation within paddy rice fields and spectral confusion between paddies and other vegetation classes, our ability to identify paddy rice fields with temporal imagery remains limited. The objective of this study is to develop new phenology and textural-based strategies to detect paddies with HJ-1A, MODIS and PALSAR FNF imagery. Two phenology-based strategies that track the seasonal trajectory of crops and one textural-based strategy that contains image surface characteristics are presented. With the proposed strategies, temporal, spectral and textural features were investigated for paddy rice detection. The results indicate that the phenology-based strategies could reveal the phenological variation within paddy rice and significantly improved the detection accuracy. Seasonal amplitude, grey level co-occurrence matrix entropy and spectral features of the heading stage were proven to be important in identifying paddy rice. It was concluded that the combination of HJ-1A, MODIS and PALSAR FNF imagery are promising in facilitating the rapid mapping of paddy rice at a regional scale.
资助项目	China Scholarship Council
WOS关键词	SURFACE REFLECTANCE ; LANDSAT ; CLASSIFICATION ; COVER ; AREAS
WOS研究方向	Remote Sensing
语种	英语
出版者	TAYLOR & FRANCIS LTD
WOS记录号	WOS:000475926300005
资助机构	China Scholarship Council
内容类型	期刊论文
源URL	[http://ir.igsnrr.ac.cn/handle/311030/58237]
专题	中国科学院地理科学与资源研究所
通讯作者	Singha, Mrinal
作者单位	1.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Beijing 100100, Peoples R China 2.Univ Chinese Acad Sci, Inst Atmospher Phys, Beijing, Peoples R China
推荐引用方式 GB/T 7714	Singha, Mrinal,Sarmah, Sangeeta. Incorporating crop phenological trajectory and texture for paddy rice detection with time series MODIS, HJ-1A and ALOS PALSAR imagery[J]. EUROPEAN JOURNAL OF REMOTE SENSING,2019,52(1):73-87.
APA	Singha, Mrinal,&Sarmah, Sangeeta.(2019).Incorporating crop phenological trajectory and texture for paddy rice detection with time series MODIS, HJ-1A and ALOS PALSAR imagery.EUROPEAN JOURNAL OF REMOTE SENSING,52(1),73-87.
MLA	Singha, Mrinal,et al."Incorporating crop phenological trajectory and texture for paddy rice detection with time series MODIS, HJ-1A and ALOS PALSAR imagery".EUROPEAN JOURNAL OF REMOTE SENSING 52.1(2019):73-87.