Toward Precision Agriculture in Outdoor Vertical Greenery Systems (VGS): Monitoring and Early Detection of Stress Events

Vertical greenery systems (VGS) have been proposed as a nature-based solution to mitigate the adverse effects of urban heat islands and climate change in cities. However, large-scale VGS are costly and require ongoing maintenance, typically carried out manually through trial and error based on profe...

Full description

Saved in:
Bibliographic Details
Published in:Remote sensing (Basel, Switzerland) Switzerland), 2024-01, Vol.16 (2), p.302
Main Authors: Zuckerman, Noa, Cohen, Yafit, Alchanatis, Victor, Lensky, Itamar M.
Format: Article
Language:English
Subjects:
Agriculture
Automation
Cameras
Case studies
Chlorophyll
Climate change
Decision support systems
Energy consumption
Flowers & plants
Global temperature changes
green wall
Internet of Things
Irrigation
Maintenance
Microclimate
Monitoring
monitoring VGS
nature-based solution
Precision farming
Remote sensing
Spatial distribution
Temperature
Urban heat islands
Vegetation
Vegetation index
vertical greenery systems (VGS)
VGS health
VGS maintenance
Water management
Yellowing
Citations: Items that this one cites
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Vertical greenery systems (VGS) have been proposed as a nature-based solution to mitigate the adverse effects of urban heat islands and climate change in cities. However, large-scale VGS are costly and require ongoing maintenance, typically carried out manually through trial and error based on professional experience. Advanced management is essential for the sustainability of VGS due to its limited accessibility and associated costs. To address these challenges, we examined the use of remote sensing methods for outdoor VGS monitoring as a basis for a precision agriculture approach for VGS management and maintenance. This study presents the first ongoing monitoring of real-scale VGS using thermal, hyperspectral, and RGB vegetation indices. These indices were employed for the early detection of vegetation stress, focusing on two case studies exhibiting visible yellowing symptoms. Through the application of unsupervised classification techniques, stressed pixels were successfully detected 14–35 days before visual yellowing, achieving an accuracy of 0.85–0.91. Additionally, the thermal index provided valuable information regarding the spatial distribution of watering along the VGS. Stress maps based on noninvasive methods were demonstrated, forming the basis of a spatial decision support system capable of detecting issues related to plant vitality and VGS irrigation management.
ISSN:2072-4292
2072-4292
DOI:10.3390/rs16020302