气候变化领域集成服务门户(CCPortal): Mapping irrigated agriculture in complex landscapes using SPOT6 imagery and object-based image analysis – A case study in the Central Rift Valley, Ethiopia

CCPortal

DOI	10.1016/j.jag.2018.07.019
	Mapping irrigated agriculture in complex landscapes using SPOT6 imagery and object-based image analysis – A case study in the Central Rift Valley, Ethiopia –
	Vogels M.F.A.; de Jong S.M.; Sterk G.; Addink E.A.
发表日期	2019
ISSN	15698432
起始页码	118
结束页码	129
卷号	75
英文摘要	Irrigation infrastructure development for smallholder farmers in developing countries increasingly gains attention in the light of domestic food security and poverty alleviation. However, these complex landscapes with small cultivated plots pose a challenge with regard to mapping and monitoring irrigated agriculture. This study presents an object-based approach to map irrigated agriculture in an area in the Central Rift Valley in Ethiopia using SPOT6 imagery. The study is a proof-of-concept that the use of shape, texture, neighbour and location information next to spectral information is beneficial for the classification of irrigated agriculture. The underlying assumption is that the application of irrigation has a positive effect on crop growth throughout the field, following the field's borders, which is detectable in an object-based approach. The type of agricultural system was also mapped, distinguishing smallholder farming and modern large-scale agriculture. Irrigated agriculture was mapped with an overall accuracy of 94% and a kappa coefficient of 0.85. Producer's and user's accuracies were on average 90.6% and 84.2% respectively. The distinction between smallholder farming and large-scale agriculture was identified with an overall accuracy of 95% and a kappa coefficient of 0.88. The classifications were performed at the field level, since the segmentation was able to adequately delineate individual fields. The additional use of object features proved essential for the identification of cropland plots, irrigation period and type of agricultural system. This method is independent of expert knowledge on crop phenology and absolute spectral values. The proposed method is useful for the assessment of spatio-temporal dynamics of irrigated (smallholder) agriculture in complex landscapes and yields a basis for land and water managers on agricultural water use. © 2018 Elsevier B.V.
英文关键词	Agriculture; Central Rift Valley; Data-poor regions; Ethiopia; Field-level analysis; GEOBIA; Smallholder irrigation
语种	英语
scopus关键词	agricultural land; farming system; food security; image analysis; irrigation; mapping; poverty alleviation; smallholder; East African Rift; Ethiopian Rift
来源期刊	International Journal of Applied Earth Observation and Geoinformation
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/156542
作者单位	Utrecht University, Department of Physical Geography, PO box 80115, TC Utrecht, 3508, Netherlands
推荐引用方式 GB/T 7714	Vogels M.F.A.,de Jong S.M.,Sterk G.,等. Mapping irrigated agriculture in complex landscapes using SPOT6 imagery and object-based image analysis – A case study in the Central Rift Valley, Ethiopia –[J],2019,75.
APA	Vogels M.F.A.,de Jong S.M.,Sterk G.,&Addink E.A..(2019).Mapping irrigated agriculture in complex landscapes using SPOT6 imagery and object-based image analysis – A case study in the Central Rift Valley, Ethiopia –.International Journal of Applied Earth Observation and Geoinformation,75.
MLA	Vogels M.F.A.,et al."Mapping irrigated agriculture in complex landscapes using SPOT6 imagery and object-based image analysis – A case study in the Central Rift Valley, Ethiopia –".International Journal of Applied Earth Observation and Geoinformation 75(2019).