Spatial Estimation of Daily Growth Biomass in Paddy Rice Field Using Canopy Photosynthesis Model Based on Ground and UAV Observations

Precision farming, a labor-saving and highly productive form of management, is gaining popularity as the number of farmers declines in comparison to the increasing global food demand. However, it requires more efficient crop phenology observation and growth monitoring. One measure is the leaf area i...

Full description

Saved in:
Bibliographic Details
Published in:Remote sensing (Basel, Switzerland) Switzerland), 2024-01, Vol.16 (1), p.125
Main Authors: Yamashita, Megumi, Kaieda, Tomoya, Toyoda, Hiro, Yamaguchi, Tomoaki, Katsura, Keisuke
Format: Article
Language:English
Subjects:
Agricultural production
Airborne observation
Analysis
Biomass
Bouguer law
Canopies
canopy photosynthesis model
daily biomass
Estimation
Farmers
field observation
Ground-based observation
Growth models
Image acquisition
Leaf area
Leaf area index
Leaves
Light
Light intensity
Luminous intensity
Mathematical models
Numerical models
Phenology
Photosynthesis
Plants (botany)
Precision farming
Production processes
relative light intensity
Remote sensing
Rice
Rice fields
Spatial variations
UAV
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:Precision farming, a labor-saving and highly productive form of management, is gaining popularity as the number of farmers declines in comparison to the increasing global food demand. However, it requires more efficient crop phenology observation and growth monitoring. One measure is the leaf area index (LAI), which is essential for estimating biomass and yield, but its validation requires destructive field measurements. Thus, using ground and UAV observation data, this study developed a method for indirect LAI estimation based on relative light intensity under a rice canopy. Daily relative light intensity was observed under the canopy at several points in paddy fields, and a weekly plant survey was conducted to measure the plant length, above-ground biomass, and LAI. Furthermore, images from ground-based and UAV-based cameras were acquired to generate NDVI and the canopy height (CH), respectively. Using the canopy photosynthetic model derived from the Beer–Lambert law, the daily biomass was estimated by applying the weekly estimated LAI using CH and the observed light intensity data as input. The results demonstrate the possibility of quantitatively estimating the daily growth biomass of rice plants, including spatial variation. The near-real-time estimation method for rice biomass by integrating observation data at fields with numerical models can be applied to the management of major crops.
ISSN:2072-4292
2072-4292
DOI:10.3390/rs16010125