Field Crops Research 120 (2011) 299–310 Contents lists available at ScienceDirect Field Crops Research journal homepage: www.elsevier.com/locate/fcr Assessing newly developed and published vegetation indices for estimating rice leaf nitrogen concentration with ground- and space-based hyperspectral reflectance Y.C. Tian a , X. Yao a , J. Yang a , W.X. Cao a , D.B. Hannaway b , Y. Zhu a,∗ a Jiangsu Key Laboratory for Information Agriculture, MOA Key Laboratory of Crop Growth Regulation, Nanjing Agricultural University, 1 Weigang Road, Nanjing, Jiangsu 210095, PR China b Department of Crop and Soil Science, College of Agricultural Sciences, Oregon State University, Corvallis, OR 97331-3002, USA article info Article history: Received 22 August 2010 Received in revised form 7 November 2010 Accepted 7 November 2010 Keywords: Rice canopy Leaf nitrogen concentration LNC Hyperspectral parameter Three-band index Growth monitoring abstract Non-destructive and quick assessment of leaf nitrogen (N) status is important for dynamic management of nitrogen nutrition and productivity forecast in crop production. This research was undertaken to make a systematic analysis on the quantitative relationship of leaf nitrogen concentrations (LNCs) to different hyperspectral vegetation indices with multiple field experiments under varied nitrogen rates and varied types in rice (Oryza sativa L.). The results showed that some published indices had good relations with LNC such as two-band indices, R 750 /R 710 (ZM), Gitelson and Merzlyak index two (GM-2), R 735 /R 720 (RI-1dB), R 738 /R 720 (RI-2dB) and the normalized difference red edge index (NDRE), three-band indices, adjusted normalized index 705 (mND705), physiological reflectance index c (PRI c ), terrestrial chlorophyll index (MTCI), and red edge position derived with four point linear interpolation (REP LI). Three-band indices performed better than two-band indices, with MTCI exhibiting the best logarithmic relation to LNC in rice. Then, hyper-spectral vegetation indices computed with random two bands ( 1 and  2 ) from 400 to 2500 nm range were related to LNC of rice. The results indicated that two-band indices combined with bands of 550–600 nm and 500–550 nm in green region had good relationships with LNC, and simple ratio index SR(533,565) performed the best in all two-band indices, similar to the published three-band indices (mND705, PRI c and MTCI). New three-band indices R 434 /(R 496 + R 401 ) and R 705 /(R 717 + R 491 ) were proposed for prediction of LNC with improved ability over the SR(533,565) and published spectral indices. Moreover, R 705 /(R 717 + R 491 ) performed well in all the data from ground spectra, modeled AVIRIS and Hyperion spectra, and acquired Hyperion image hyperspectra. The R 434 /(R 496 + R 401 ) also exhibited well in both ground and modeled AVIRIS and Hyperion image spectra, but could not be tested with the acquired Hyperion image because of the absence in radiometric calibration of the bands less than 416 nm. Overall, the newly developed three-band spectral index R 705 /(R 717 + R 491 ) should be a good indicator of LNC at ground and space scales in rice. Yet, these new indices still need to be tested with more remote sensors based on ground, airborne and spaceborne, and verified widely in other ecological locations involving different cultivars and production systems. © 2010 Elsevier B.V. All rights reserved. 1. Introduction The contribution of N to photosynthesis and grain yield through Rubisco content was greater than through chlorophyll (Woodard and Bly, 1998). Excess N supply which induces fertilizer nitrate (NO 3 -N) losses in crop production, however, is considered to be one of the major sources for surface and groundwater pollution (Ferguson et al., 2002). Thus, it is important to develop technologies that ensure high grain yield and quality while minimizing envi- ∗ Corresponding author. Tel.: +86 25 84396565; fax: +86 25 84396672. E-mail address: yanzhu@njau.edu.cn (Y. Zhu). ronmental damage caused by improper N management. Accurate, real-time and rapid monitoring and diagnosis of crop N status can assist with achieving both of these often conflicting objectives (high yield and low environmental impact). Spectral remote sensing is a useful tool for non-destructive estimation of plant growth and biophysical parameters (Takebe et al., 1990). Spectral wavebands in the red edge (700–750 nm), red (630–690 nm) and green band (500–580 nm) regions are con- sidered to be the three useful ranges for estimating chlorophyll concentration (Blackburn, 1998; Gitelson et al., 1999, 2003; Zarco- Tejada et al., 2001). Based on red edge bands, several simple ratio and normalized difference indices were developed for estimat- ing chlorophyll a concentration in plant leaves, e.g. red edge ratio 0378-4290/$ – see front matter © 2010 Elsevier B.V. All rights reserved. doi:10.1016/j.fcr.2010.11.002