EFFICIENT APPLICATION OF DRONE WITH SATELLITE DATA FOR EARLY-STAGE WHEAT DETECTION: FOR PRECISION AGRICULTURE MONITORING

被引:5
作者
Kukunuri, Anjana N. J. [1 ]
Singh, Dharmendra [1 ]
机构
[1] Indian Inst Technol Roorkee, Dept Elect & Commun Engn, Roorkee 247667, Uttar Pradesh, India
来源
2022 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS 2022) | 2022年
关键词
Early-stage wheat; satellite data; drone; precision agriculture; machine learning; SAR;
D O I
10.1109/IGARSS46834.2022.9883266
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
Early-stage wheat detection is quite useful and important for monitoring national food security and crop management systems. However, it is difficult to differentiate early-stage wheat among the ploughed and bare lands using medium to low-resolution satellite data at a large scale. Further, the estimated wheat sowing area would be erroneous due to misclassifications of one class to the other class. On the other hand, drones provide high-resolution data at the field level. Hence, there is a need to fuse drone and satellite data for precision agriculture information at a large scale. Therefore, in this paper, we have explored the application of machine-learning classifiers for early-stage wheat detection using drone and sentinel 1A SAR data. Further, the area is estimated for each class and is compared with the area estimated from the high-resolution drone image. Both qualitative and quantitative analysis of the obtained classification results is carried out with the help of field survey data.
引用
收藏
页码:4388 / 4391
页数:4
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