Next Article in Journal
Automatic Annotation of Airborne Images by Label Propagation Based on a Bayesian-CRF Model
Previous Article in Journal
Change Detection Based on Multi-Grained Cascade Forest and Multi-Scale Fusion for SAR Images
Article Menu

Export Article

Open AccessTechnical Note
Remote Sens. 2019, 11(2), 143; https://doi.org/10.3390/rs11020143

Spatio-Temporal Patterns of Smallholder Irrigated Agriculture in the Horn of Africa Using GEOBIA and Sentinel-2 Imagery

Department of Physical Geography, Utrecht University, P.O. box 80115, 3508 TC Utrecht, The Netherlands
*
Author to whom correspondence should be addressed.
Received: 31 October 2018 / Revised: 7 December 2018 / Accepted: 29 December 2018 / Published: 13 January 2019
(This article belongs to the Section Remote Sensing in Agriculture and Vegetation)
Full-Text   |   PDF [13038 KB, uploaded 13 January 2019]   |  

Abstract

Irrigated agriculture practiced by smallholders is essential for food security in East Africa. Insight in the spatio-temporal distribution of irrigated agriculture is required to optimize irrigation water use. Irrigation-mapping efforts in the complex smallholder-dominated agricultural landscape in the Horn of Africa so far are generally too coarse and often the extent of smallholder irrigated agriculture is underestimated. The arrival of Sentinel-2 (10-m resolution) considerably enhanced the prospect of analyzing agriculture at field level. The objective of this study is to demonstrate the feasibility to map spatio-temporal patterns of smallholder irrigated agriculture in the Horn of Africa using a novel method based on object-based image analysis and Sentinel-2 imagery. The method includes segmentation at field level and smart process-based rules on neighbouring objects and NDVI time series to distinguish irrigated agriculture from rainfed agriculture. The assumption is that irrigation is applied at field level, while a rainfall event is not restricted to field borders and that this information on the local context of irrigated agriculture can be exploited in an object-based approach. Monthly land-use maps on irrigated agriculture were produced for September 2016 to August 2017 at 10-m resolution field level (objects). Three different spatial-heterogeneity thresholds were used to describe the vegetation development of neighbouring objects and to assign crop growth to either rainfall or irrigation. This method is unique as it can discriminate irrigation- and rainfall-induced crop growth, even in the rainy season. The estimates of irrigated agriculture in the Horn of Africa range from 27.96 Mha to 37.13 Mha. This is 2.8 to 3.7 times higher than the current highest estimate, the Global Irrigated Area Map at 1000 m resolution, and 1.2 to 1.7 times higher than the Irrigated Area Map Asia (2000–2010) and Africa (2010) when including water-managed non-irrigated croplands. For the dry season (October–March), the estimates of irrigated agriculture range from 17.67 Mha to 23.72 Mha. The irrigation frequency, the number of time steps (months) with irrigation events in the studied year, varies strongly. Irrigated area with an irrigation frequency of 1 to 2 events has a mapped surface area of 22.57 Mha to 23.13 Mha. Irrigated area with an irrigation frequency of 3 or more events has a mapped surface area of 4.83 Mha to 14.56 Mha. The produced maps will provide valuable information for the development of irrigated agriculture and optimization of irrigation water use in the Horn of Africa. In addition, the portability of this method to other (semi-)arid regions seems feasible as the local context of irrigated agriculture, used in this study for irrigation classification, describes universal characteristics regarding irrigated agriculture. This is especially valuable in the context of food security and water availability for other large data-poor regions in low- and middle-income countries. View Full-Text
Keywords: smallholder irrigation; Google Earth Engine; GEOBIA; field-level analysis; agriculture; data-poor regions; Horn of Africa smallholder irrigation; Google Earth Engine; GEOBIA; field-level analysis; agriculture; data-poor regions; Horn of Africa
Figures

Graphical abstract

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

Supplementary material

SciFeed

Share & Cite This Article

MDPI and ACS Style

Vogels, M.F.; de Jong, S.M.; Sterk, G.; Douma, H.; Addink, E.A. Spatio-Temporal Patterns of Smallholder Irrigated Agriculture in the Horn of Africa Using GEOBIA and Sentinel-2 Imagery. Remote Sens. 2019, 11, 143.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Remote Sens. EISSN 2072-4292 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top