Hyperspectral remote sensing analysis of short rotation woody crops grown with controlled nutrient and irrigation treatments

Journal Article · Sat Aug 01 04:00:00 EDT 2009 · Geocarto International (Hong Kong)

DOI:https://doi.org/10.1080/10106040802556207· OSTI ID:953637

Im, Jungho ^[1]; Jensen, John R.; Coleman, Mark; Nelson, Eric

---

1. USDA Forest Service, Savannah River

Abstract - Hyperspectral remote sensing research was conducted to document the biophysical and biochemical characteristics of controlled forest plots subjected to various nutrient and irrigation treatments. The experimental plots were located on the Savannah River Site near Aiken, SC. AISA hyperspectral imagery were analysed using three approaches, including: (1) normalized difference vegetation index based simple linear regression (NSLR), (2) partial least squares regression (PLSR) and (3) machine-learning regression trees (MLRT) to predict the biophysical and biochemical characteristics of the crops (leaf area index, stem biomass and five leaf nutrients concentrations). The calibration and cross-validation results were compared between the three techniques. The PLSR approach generally resulted in good predictive performance. The MLRT approach appeared to be a useful method to predict characteristics in a complex environment (i.e. many tree species and numerous fertilization and/or irrigation treatments) due to its powerful adaptability.

• Research Organization: USDA Forest Service, Savannah River, New Ellenton, SC
• Sponsoring Organization: USDOE Office of Environment, Safety and Health (EH)
• DOE Contract Number: AI09-00SR22188
• OSTI ID: 953637
• Report Number(s): na; 09-02-P
• Journal Information: Geocarto International (Hong Kong), Journal Name: Geocarto International (Hong Kong) Journal Issue: 4 Vol. 24; ISSN 1010-6049
• Country of Publication: United States
• Language: English

Related Subjects

machine-learning regression trees
60 APPLIED LIFE SCIENCES
BIOMASS
CALIBRATION
CROPS
FERTILIZATION
FORESTS
IRRIGATION
NDVI
NUTRIENTS
PERFORMANCE
PLANTS
REMOTE SENSING
ROTATION
SAVANNAH RIVER PLANT
TREES
biomass
hyperspectral analysis
leaf area index
leaf nutrients
partial least squares regression
remote sensing