Publications

Yuan, Lin; Zhang, Jingcheng; Shi, Yeyin; Nie, Chenwei; Wei, Liguang; Wang, Jihua (2014). Damage Mapping of Powdery Mildew in Winter Wheat with High-Resolution Satellite Image. REMOTE SENSING, 6(5), 3611-3623.

Abstract
Powdery mildew, caused by the fungus Blumeria graminis, is a major winter wheat disease in China. Accurate delineation of powdery mildew infestations is necessary for site-specific disease management. In this study, high-resolution multispectral imagery of a 25 km(2) typical outbreak site in Shaanxi, China, taken by a newly-launched satellite, SPOT-6, was analyzed for mapping powdery mildew disease. Two regions with high representation were selected for conducting a field survey of powdery mildew. Three supervised classification methods-artificial neural network, mahalanobis distance, and maximum likelihood classifier-were implemented and compared for their performance on disease detection. The accuracy assessment showed that the ANN has the highest overall accuracy of 89%, following by MD and MLC with overall accuracies of 84% and 79%, respectively. These results indicated that the high-resolution multispectral imagery with proper classification techniques incorporated with the field investigation can be a useful tool for mapping powdery mildew in winter wheat.

DOI:
10.3390/rs6053611

ISSN:
2072-4292