More Reliable Crop Water Stress Quantification Using Small Unmanned Aerial Systems (sUAS)*. Issue 16 (2016)

• Record Type: Journal Article
• Authors: Zhao, Tiebiao; Stark, Brandon; Chen, YangQuan; Ray, Andrew; Doll, David
• Is Part Of: IFAC-PapersOnLine. Volume 49:Issue 16(2016)
• Page Start: 409
• Page End: 414
• Publication Date: 2016
• Subjects: small unmanned aerial system (sUAS) -- canopy normalized difference vegetation index (NDVI) -- canopy non-normalized difference vegetation index (NNDVI) -- water stress detection -- stem water potential (SWP); Automatic control -- Periodicals; 629.805
• DOI: 10.1016/j.ifacol.2016.10.075
• Languages: English
• ISSNs: 2405-8963

Abstract

Abstract: The remarkable development of small unmanned aerial systems (sUAS) and imaging payloads have made it easier to monitor the crops with higher spatial resolution and temporal resolution images. As a crop based water status index, stem water potential (SWP) has been widely accepted in field practice to monitor the water status of almond trees. This study aims to research the relationship between SWP and vegetation index extracted from the high spatial resolution images. A circle mission was conducted to evaluate the effects of bidirectional reflectance distribution function (BRDF) on canopy NDVI mean. It indicated that the importance of BRDF calibration to infer SWP from canopy normalized difference vegetation index (NDVI) mean. In addition, it was demonstrated that a strong linear relationship exists between canopy NDVI mean and canopy NDVI variance under different view angles. Further analysis of images identified a non-normalized difference vegetation index (NNDVI) based on ground-truthed measurements of three weeks showed a more significant relationship with SWP than canopy NDVI mean.