Next Article in Journal
Identifying Flood Events over the Poyang Lake Basin Using Multiple Satellite Remote Sensing Observations, Hydrological Models and In Situ Data
Next Article in Special Issue
Monitoring Crop Evapotranspiration and Crop Coefficients over an Almond and Pistachio Orchard Throughout Remote Sensing
Previous Article in Journal
Remote Sensing Big Data: Theory, Methods and Applications
Previous Article in Special Issue
Effects of Heterogeneity within Tree Crowns on Airborne-Quantified SIF and the CWSI as Indicators of Water Stress in the Context of Precision Agriculture
Open AccessArticle

Improving the Accuracy of Remotely Sensed Irrigated Areas Using Post-Classification Enhancement Through UAV Capability

1
International Water Management Institute, Southern Africa Regional Office (IWMI-SA), 141 Cresswell St., Weavind Park, Silverton, Pretoria 0184, South Africa
2
University of Wageningen, Droevendaalsesteeg 2, 6708 PB Wageningen, The Netherlands
3
Geomatics Department, Tshwane University of Technology, Staatsartillerie Road, Pretoria 0001, South Africa
4
International Water Management Institute (IWMI), 127, Sunil Mawatha, Pelawatte, Battaramulla 10120, Sri Lanka
5
Limpopo Department of Agriculture & Rural Development, 69 Biccard Street, Polokwane 0700, South Africa
*
Author to whom correspondence should be addressed.
Remote Sens. 2018, 10(5), 712; https://doi.org/10.3390/rs10050712
Received: 3 April 2018 / Revised: 30 April 2018 / Accepted: 3 May 2018 / Published: 5 May 2018
(This article belongs to the Special Issue Remote Sensing for Crop Water Management)
Although advances in remote sensing have enhanced mapping and monitoring of irrigated areas, producing accurate cropping information through satellite image classification remains elusive due to the complexity of landscapes, changes in reflectance of different land-covers, the remote sensing data selected, and image processing methods used, among others. This study extracted agricultural fields in the former homelands of Venda and Gazankulu in Limpopo Province, South Africa. Landsat 8 imageries for 2015 were used, applying the maximum likelihood supervised classifier to delineate the agricultural fields. The normalized difference vegetation index (NDVI) applied on Landsat imageries on the mapped fields during the dry season (July to August) was used to identify irrigated areas, because years of satellite data analysis suggest that healthy crop conditions during dry seasons are only possible with irrigation. Ground truth points totaling 137 were collected during fieldwork for pre-processing and accuracy assessment. An accuracy of 96% was achieved on the mapped agricultural fields, yet the irrigated area map produced an initial accuracy of only 71%. This study explains and improves the 29% error margin from the irrigated areas. Accuracy was enhanced through post-classification correction (PCC) using 74 post-classification points randomly selected from the 2015 irrigated area map. High resolution aerial photographs of the 74 sample fields were acquired by an unmanned aerial vehicle (UAV) to give a clearer picture of the irrigated fields. The analysis shows that mapped irrigated fields that presented anomalies included abandoned croplands that had green invasive alien species or abandoned fruit plantations that had high NDVI values. The PCC analysis improved irrigated area mapping accuracy from 71% to 95%. View Full-Text
Keywords: remote sensing; accuracy assessment; unmanned aerial vehicle; irrigated areas; mapping; field verification remote sensing; accuracy assessment; unmanned aerial vehicle; irrigated areas; mapping; field verification
Show Figures

Graphical abstract

MDPI and ACS Style

Nhamo, L.; Van Dijk, R.; Magidi, J.; Wiberg, D.; Tshikolomo, K. Improving the Accuracy of Remotely Sensed Irrigated Areas Using Post-Classification Enhancement Through UAV Capability. Remote Sens. 2018, 10, 712.

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.

Article Access Map by Country/Region

1
Back to TopTop