Estimating Biomass of Barley Using Crop Surface Models (CSMs) Derived from UAV-Based RGB Imaging

Remote Sensing

Juliane Bendig¹  Andreas Bolten¹  Simon Bennertz¹  Janis Broscheit¹  Silas Eichfuss¹  Georg Bareth¹  Clement Atzberger² 

[1] Institute of Geography, GIS & RS, University of Cologne, 50923 Cologne, Germany; E-Mails:Institute of Geography, GIS & RS, University of Cologne, 50923 Cologne, Germany;

关键词: UAV;    optical;    remote sensing;    RGB;    3D;    biomass estimation;    crop surface model;    plant height;    summer barley;    precision agriculture;   

DOI  :  10.3390/rs61110395

来源: mdpi

【 摘 要 】

Crop monitoring is important in precision agriculture. Estimating above-ground biomass helps to monitor crop vitality and to predict yield. In this study, we estimated fresh and dry biomass on a summer barley test site with 18 cultivars and two nitrogen (N)-treatments using the plant height (PH) from crop surface models (CSMs). The super-high resolution, multi-temporal (1 cm/pixel) CSMs were derived from red, green, blue (RGB) images captured from a small unmanned aerial vehicle (UAV). Comparison with PH reference measurements yielded an R² of 0.92. The test site with different cultivars and treatments was monitored during “Biologische Bundesanstalt, Bundessortenamt und CHemische Industrie” (BBCH) Stages 24–89. A high correlation was found between PH from CSMs and fresh biomass (R² = 0.81) and dry biomass (R² = 0.82). Five models for above-ground fresh and dry biomass estimation were tested by cross-validation. Modelling biomass between different N-treatments for fresh biomass produced the best results (R² = 0.71). The main limitation was the influence of lodging cultivars in the later growth stages, producing irregular plant heights. The method has potential for future application by non-professionals, i.e., farmers.

【 授权许可】

CC BY   
© 2014 by the authors; licensee MDPI, Basel, Switzerland.