Exploring vegetation indices adequate in detecting twister disease of onion using Sentinel-2 imagery
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Exploring vegetation indices adequate in detecting twister disease of onion using Sentinel-2 imagery M. F. Isip2
•
R. T. Alberto1 • A. R. Biagtan2
Received: 12 June 2019 / Revised: 30 September 2019 / Accepted: 5 October 2019 Korean Spatial Information Society 2019
Abstract Traditional plant disease detection is time consuming and costly, thus an inexpensive and faster alternative method of detection is needed to send early warning to farmers to prevent pests and disease infestation and for proper intervention. To provide timely and accurate detection in twister disease of onion, remote sensing was exploited using Sentinel 2 imageries. Vegetation indices (VIs) derived from the VIS–NIR region of the image were evaluated for their capability to detect twister disease. VIs were subjected to regression analysis to evaluate the relationship between vegetation indices and severity index of onion twister disease. Vegetation indices with strong relationship to twister disease were selected and further used in unsupervised ISODATA classification. Overall accuracy of classification generated from vegetation indices were calculated based on confusion matrix using ground truth points collected from field work to identify the most suitable index based on highest overall accuracy. It was found out that NDVI and GNDVI has the highest coefficient of determination (R2) indicating a strong relationship to the disease severity. Results of the classification shows that GNDVI, PSSRa and NDVI obtained the highest overall accuracy of 83.33%, 80.95% and 78.57% respectively. This indicates that these 3 VIs can be used for detection of twister disease in the field since it gives better discrimination and high accuracies. Hence, VI’s generated
& M. F. Isip [email protected] 1
College of Agriculture, Central Luzon State University, Mun˜oz 3120, Nueva Ecija, Philippines
2
Institute for Climate Change and Environmental Management, Central Luzon State University, Mun˜oz 3120, Nueva Ecija, Philippines
from Sentinel 2 imagery has the potential in detection, monitoring and management of twister disease of onion in the field. Keywords Sentinel-2 imagery Vegetation Indices Detection ISODATA Twister disease
1 Introduction Twister disease of onion is caused by a facultative endophyte (living inside the plant) Gibberella moniliformis. It is a major onion pathogen in Central Luzon Region, Philippines, mainly in the Province of Nueva Ecija because it is the biggest onion producer in the country [1]. In the recent years, twister disease has become epidemic on onion crop in coastal tract and other major onion growing districts in Karnataka, India. This disease vernacularly in Sri Lanka called as disco, in Indonesia as seven whorl and in Karnataka as octopus disease and creeping disease of onion [2]. The pathogen is present on many crops in the United States; it was the first report of causing agent for twister disease of onion in the United States. In Nigeria and Brazil, yield losses as much as 100% were observed in fields with i
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