Using multispectral ground sensors to improve crop phenology monitoring

Keywords: ground sensors, remote sensing, SAR, maize, phenology
Session Type: Virtual Paper Abstract
Day: Friday
Session Start / End Time: 2/25/2022 11:20 AM (Eastern Time (US & Canada)) - 2/25/2022 12:40 PM (Eastern Time (US & Canada))
Room: Virtual 38

Abstract

Cloud cover remains a fundamental obstacle to satellite-based remote sensing, especially in tropical and sub-tropical areas with prolonged rainy seasons. Ground-based multispectral sensors allow for monitoring of crop phenology at daily and hourly intervals, regardless of cloud cover, but can only sense within a limited radius. This paper examines how crop phenology curves from time-dense ground sensors can potentially fill gaps in satellite-based time-series. A key question is how well satellite imagery, including multi-spectral and radar, can model ground-measured surface reflectance at locations where pods are not present. This estimation model can take both parametric and non-parametric forms, and this paper will discuss the data needs and advantages of each type of model.