Modeling maize above-ground biomass based on machine learning approaches using UAV remote-sensing data.

ABSTRACT:

Background

Above-ground biomass (AGB) is a basic agronomic parameter for field investigation and is frequently used to indicate crop growth status, the effects of agricultural management practices, and the ability to sequester carbon above and below ground. The conventional way to obtain AGB is to use destructive sampling methods that require manual harvesting of crops, weighing, and recording, which makes large-area, long-term measurements challenging and time consuming. However, with the diversity of platforms and sensors and the improvements in spatial and spectral resolution, remote sensing is now regarded as the best technical means for monitoring and estimating AGB over large areas.

Results

In this study, we used structural and spectral information provided by remote s

SUBMITTER: Han L 

PROVIDER: S-EPMC6360736 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature