Developing Novel Rice Yield Index Using UAV Remote Sensing Imagery Fusion Technology
نویسندگان
چکیده
Efficient and quick yield prediction is of great significance for ensuring world food security crop breeding research. The rapid development unmanned aerial vehicle (UAV) technology makes it more timely accurate to monitor crops by remote sensing. objective this study was explore the method developing a novel index (YI) with wide adaptability fusing vegetation indices (VIs), color (CIs), texture (TIs) from UAV-based imagery. Six field experiments 24 varieties rice 21 fertilization methods were carried out in three experimental stations 2019 2020. multispectral RGB images canopy collected UAV platform used rebuild six new VIs TIs. performance VI-based YI (MAPE = 13.98%) developed quadratic nonlinear regression at maturity stage better than other stages, outperformed that CI-based 22.21%) TI-based 18.60%). Then VIs, CIs, TIs fused build multiple linear random forest models. Compared heading (R2 0.78, MAPE 9.72%) all 0.59, 22.21%), best + CIs 0.84, 7.86%). Our findings suggest proposed has potential monitoring.
منابع مشابه
Fusion of Multispectral Imagery and Spectrometer Data in UAV Remote Sensing
High spatial resolution hyperspectral data often used in precision farming applications are not available from current satellite sensors, and difficult or expensive to acquire from standard aircraft. Alternatively, in precision farming, unmanned aerial vehicles (UAVs) are emerging as lower cost and more flexible means to acquire very high resolution imagery. Miniaturized hyperspectral sensors h...
متن کاملDevelopment of a remote sensing-based rice yield forecasting model
This study aimed to develop a remote sensing-based method for forecasting rice yield by considering vegetation greenness conditions during initial and peak greenness stages of the crop; and implemented for “boro” rice in Bangladeshi context. In this research, we used Moderate Resolution Imaging Spectroradiometer (MODIS)-derived two 16-day composite of normalized difference vegetation index (NDV...
متن کاملLow Cost UAV-based Remote Sensing for Autonomous Wildlife Monitoring
In recent years, developments in unmanned aerial vehicles, lightweight on-board computers, and low-cost thermal imaging sensors offer a new opportunity for wildlife monitoring. In contrast with traditional methods now surveying endangered species to obtain population and location has become more cost-effective and least time-consuming. In this paper, a low-cost UAV-based remote sensing platform...
متن کاملA novel building change index for automatic building change detection from high-resolution remote sensing imagery
A novel building change index for automatic building change detection from high-resolution remote sensing imagery Xin Huang, Tingting Zhu, Liangpei Zhang & Yuqi Tang To cite this article: Xin Huang, Tingting Zhu, Liangpei Zhang & Yuqi Tang (2014) A novel building change index for automatic building change detection from high-resolution remote sensing imagery, Remote Sensing Letters, 5:8, 713-72...
متن کاملDetecting Surface Waters Using Data Fusion of Optical and Radar Remote Sensing Sensor
Identification and monitoring of surface water using remote sensing have become very important in recent decades due to its importance in human needs and political decisions. Therefore, surface water has been studied using remote sensing systems and Sentinel-1 and Sentinel-2 sensors in this study. In this paper, two data fusion approaches and decision fusion improve the accuracy of surface wate...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Drones
سال: 2022
ISSN: ['2504-446X']
DOI: https://doi.org/10.3390/drones6060151