Predicting Water Stress in Wild Blueberry Fields Using Airborne Visible and Near Infrared Imaging Spectroscopy

Remote Sensing

Bruce Hall¹  PeterR. Nelson²  Yong-Jiang Zhang³  Catherine Chan⁴  DanielJ. Hayes⁴ 

[1] Jasper Wyman & Son, PO Box 100, Milbridge, ME 04658, USA;Schoodic Institute, 9 Atterbury Circle, PO Box 277, Winter Harbor, ME 04693, USA;School of Biology and Ecology, University of Maine, Orono, ME 04469, USA;School of Forest Resources, University of Maine, Orono, ME 04469, USA;

关键词: hyperspectral;    agriculture;    vegetation indices;    irrigation;    machine learning;    water potential;   

DOI  :  10.3390/rs13081425

来源: DOAJ

【 摘 要 】

Water management and irrigation practices are persistent challenges for many agricultural systems, exacerbated by changing seasonal and weather patterns. The wild blueberry industry is at heightened susceptibility due to its unique growing conditions and uncultivated nature. Stress detection in agricultural fields can prompt management responses to mitigate detrimental conditions, including drought and disease. We assessed airborne spectral data accompanied by ground sampled water potential over three developmental stages of wild blueberries collected throughout the 2019 summer on two adjacent fields, one irrigated and one non-irrigated. Ground sampled leaves were collected in tandem to the hyperspectral image collection with an unoccupied aerial vehicle (UAV) and then measured for leaf water potential. Using methods in machine learning and statistical analysis, we developed models to determine irrigation status and water potential. Seven models were assessed in this study, with four used to process six hyperspectral cube images for analysis. These images were classified as irrigated or non-irrigated and estimated for water potential levels, resulting in an R² of 0.62 and verified with a validation dataset. Further investigation relating imaging spectroscopy and water potential will be beneficial in understanding the dynamics between the two for future studies.

【 授权许可】

Unknown