Abstract

Leaf area index (LAI) is an important essential biodiversity variable due to its role in many terrestrial ecosystem processes such as evapotranspiration, energy balance, and gas exchanges as well as plant growth potential. A novel approach presented here is the retrieval of LAI using thermal infrared (8–14 μm, TIR) measurements. Here, we evaluate LAI retrieval using TIR hyperspectral data. Canopy emissivity spectral measurements were recorded under controlled laboratory conditions using a MIDAC (M4401-F) illuminator Fourier Transform Infrared spectrometer for two plant species during which LAI was destructively measured. The accuracy of retrieval for LAI was then assessed using partial least square regression (PLSR) and narrow band index calculated in the form of normalized difference index from all possible combinations of wavebands. The obtained accuracy from the PLSR for LAI retrieval was relatively higher than narrow-band vegetation index (0.54 < R<sup>2</sup> < 0.74). The results demonstrated that LAI may successfully be estimated from hyperspectral thermal data. The study highlights the potential of hyperspectral thermal data for retrieval of vegetation biophysical variables at the canopy level for the first time.

Highlights

  • Leaf area index (LAI) is a principal component of biogeochemical cycles in ecosystems (Bréda 2003)

  • Our results demonstrate that biophysical properties of vegetation at the canopy level, such as LAI, can be retrieved using canopy emissivity spectra in the TIR region

  • The results of our experiments demonstrate that vegetation indices enable to accurately predict LAI for single species in the TIR domain rather than pooled data including two plant species

Read more

Summary

Introduction

Leaf area index (LAI) is a principal component of biogeochemical cycles in ecosystems (Bréda 2003). Previous studies have shown the importance of LAI in ecological and remote sensing studies. LAI is a key input for climate and large-scale ecosystem models and is a key structural characteristic of forest ecosystems (Chen et al 1997; Myneni et al 1997; Wang et al 2004; Zheng and Moskal 2009). LAI has been successfully retrieved using hyperspectral data in the visible/near–infrared (0.35-1.0 μm, VNIR) and short-wave infrared (1.0-2.5 μm, SWIR) regions (Zheng and Moskal 2009). Despite the broadly recognized importance of LAI across ecological research, to our knowledge, LAI has not estimated from thermal infrared (8-14 μm, TIR) hyperspectral data. TIR hyperspectral data deserves the same exploration and development of methods, as hyperspectral data in the VNIR and SWIR regions

Objectives
Methods
Results
Conclusion
Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call