干旱区生态环境知识资源中心(Arid): Crops monitoring and yield estimation using sentinel products in semi-arid smallholder irrigation schemes

Arid

DOI	10.1080/01431161.2020.1739355
	Crops monitoring and yield estimation using sentinel products in semi-arid smallholder irrigation schemes
	Ouattara, Boris; Forkuor, Gerald; Zoungrana, Benewinde J. B.; Dimobe, Kangbeni; Danumah, Jean; Saley, Bachir; Tondoh, Jerome E.
通讯作者	Ouattara, B
来源期刊	INTERNATIONAL JOURNAL OF REMOTE SENSING
ISSN	0143-1161
EISSN	1366-5901
出版年	2020
卷号	41 期号:17 页码:6527-6549
英文摘要	The use of earth observation data for crop mapping and monitoring in West Africa has concentrated on rainfed systems due to its pre-dominance in the sub-region. However, irrigated systems, though of limited extent, provide critical livelihood support to many. Accurate statistics on irrigated crops are, thus, needed for effective management and decision making. This study explored the use of Sentinel 1 (S-1) and Sentinel 2 (S-2) data to map the extent and yield of irrigated crops in an informal irrigation scheme in Burkina Faso. Random Forest classification and regression were used together with an extensive field data comprising 842 polygons. Four irrigated crops (tomoto, onion, green bean and other) were classified while the yield of tomatoes was modelled through regression analysis. Apart from spectral bands, derivatives (e.g. biophysical parameters and vegetation indices) from S-2 were used. Different data configuration of S-1, S-2 and their derivatives were tested to ascertain optimal temporal windows for accurate irrigated crop mapping and yield estimation. Results of the crop classification revealed a greater overall accuracy (76.3%) for S-2 compared to S-1 (69.4%), with S-2 biophysical parameters (especially the fraction of absorbed photosynthetic active radiation i.e fAPAR) being prominent. For yield prediction, however, S-1 VV polarization came up as the most prominent predictor in the regression analysis (R-adj(2) = 0.63), while the addition of S-2 fAPAR marginally improved the fit (R-adj(2) = 0.64). Tomato yield in the study area was found to range from 1 to 16 kg m(-2), although about 83% of the area have yields of less than 10 kg m(-2). Our study revealed that early season images (acquired in December) perform better in classifying irrigated crop compared to mid or late season. On the other hand, the use of early to mid-season (December to February) images for yield modelling produced reasonable prediction accuracy. This indicates the possibility of using S-1 and S-2 data to predict crop yield prior to harvest season for efficient planning and food security attainment.
类型	Article
语种	英语
收录类别	SCI-E
WOS记录号	WOS:000544461900001
WOS关键词	DIFFERENCE WATER INDEX ; VEGETATION INDEXES ; LAND-COVER ; CLASSIFICATION ; AREA ; NDWI ; PERFORMANCE ; ALGORITHM ; CHANNEL ; FAPAR
WOS类目	Remote Sensing ; Imaging Science & Photographic Technology
WOS研究方向	Remote Sensing ; Imaging Science & Photographic Technology
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/324880
作者单位	[Ouattara, Boris] Univ Wurzburg, Inst Geog & Geol, Wurzburg, Germany; [Forkuor, Gerald] United Nations Univ, Inst Nat Resources Africa UNU INRA, Accra, Ghana; [Zoungrana, Benewinde J. B.; Dimobe, Kangbeni] Ctr Climate Change & Adapted Land Use WASCAL, West African Sci Serv, Ouagadougou, Burkina Faso; [Danumah, Jean; Saley, Bachir] Univ Felix Houphouet Boigny, Ctr Univ Rech & Applicat Teledetect CURAT, Abidjan, Cote Ivoire; [Tondoh, Jerome E.] Univ Nangui Abrogoua, Ctr Rech Ecol, Abidjan, Cote Ivoire
推荐引用方式 GB/T 7714	Ouattara, Boris,Forkuor, Gerald,Zoungrana, Benewinde J. B.,et al. Crops monitoring and yield estimation using sentinel products in semi-arid smallholder irrigation schemes[J],2020,41(17):6527-6549.
APA	Ouattara, Boris.,Forkuor, Gerald.,Zoungrana, Benewinde J. B..,Dimobe, Kangbeni.,Danumah, Jean.,...&Tondoh, Jerome E..(2020).Crops monitoring and yield estimation using sentinel products in semi-arid smallholder irrigation schemes.INTERNATIONAL JOURNAL OF REMOTE SENSING,41(17),6527-6549.
MLA	Ouattara, Boris,et al."Crops monitoring and yield estimation using sentinel products in semi-arid smallholder irrigation schemes".INTERNATIONAL JOURNAL OF REMOTE SENSING 41.17(2020):6527-6549.