Remote sensing of nitrogen and lignin in Mediterranean vegetation from AVIRIS data: Decomposing biochemical from structural signals

By L. Serrano, Josep Peñuelas, Susan L. Ustin. 2002

502 citations recorded by the source corpus.

Subfields: Ecological Modeling, Ecology, Global and Planetary Change

View Paper: https://www.semanticscholar.org/paper/7a9077260be18ede18dce8613e6e0b85204fc543

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Citations in the corpus

Characterizing canopy biochemistry from imaging spectroscopy and its application to ecosystem studies (2009, background): “In a study of dryland ecosystems, Serrano et al. (2002) estimated leaf lignin concentrations in areas with a considerable fraction of dry, senescent or woody vegetation cover and found that lignin is correlated with spectral reflectance at 1.754 µm (r2=0.44–0.58).”
SWIR-based spectral indices for assessing nitrogen content in potato fields (2010, background): “The Normalized Difference Nitrogen Index (NDNI; Serrano et al. 2002) is a log10 transformed reflectance NI based on the absorption feature of N at 1510 nm and a reference band at 1680 nm: NDNI ¼ ½log10 ð1=r1510Þ log10 ð1=r1680Þ ½log10 ð1=r1510Þ þ log10 ð1=r1680Þ (3) Both bands are within the…”
Significant Remote Sensing Vegetation Indices: A Review of Developments and Applications (2017, unknown): “NDLI [log (1/ 1754) − log (1/ 1680)] [log (1/ 1754) + log (1/ 1680)] [111]”
Using canopy reflectance and partial least squares regression to calculate within-field statistical variation in crop growth and nitrogen status of rice (2006, methodology): “In contrast, the partial least squares (PLS) regression overcomes the collinearity and over-fitting problems found with MSLR while using as much information as possible (Galadi & Kowalski, 1986; Haaland & Thomas, 1988; Huang et al., 2004; Serrano et al., 2002).”
Hyperspectral remote sensing of plant biochemistry using Bayesian model averaging with variable and band selection (2013, background): “…an algorithmic basis for hyperspectral remote sensing of plant biochemicals (Knyazikhin et al., 2012), including water, carbon, nitrogen, cellulose, lignin, and foliage pigments such as chlorophyll, carotenoids, and anthocyanins (Asner & Martin, 2008; Gitelson et al., 2006; Serrano et al., 2002).”
Reflectance estimation of canopy nitrogen content in winter wheat using optimised hyperspectral spectral indices and partial least squares regression (2014, methodology): “Optimum multiple narrow band reflectance using step linear regression analysis has been commonly used to identify the characteristic bands related to the crop biophysical and biochemical parameters of interest (Thenkabail et al., 2000; Serrano et al., 2002).”
Estimating foliar biochemistry from hyperspectral data in mixed forest canopy (2008, result): “Our study confirms previous findings that partitioning data by functional groups yielded lower errors (Serrano et al., 2002; Mutanga et al., 2004).”
Review of optical-based remote sensing for plant trait mapping (2013, methodology): “…600 700 800 900 1000 1100 1200 1300 1400 1500 1600 1700 1800 1900 2000 2100 2200 2300 2400 Zagolski et al. (1996) Yoder and Pettigrew−Crosby (1995) Serrano et al. (2002) Schlerf et al. (2010) Martin and Aber (1997) Kokaly (2001) Kokaly and Clark (1999) Jongschaap and Booij (2004) Johnson and…”