Characterizing Canopy Gap Structure in Forests Using Wavelet Analysis

Bradshaw, G. A.; Spies, Thomas A.

doi:10.2307/2261007

Cited by 214 publications

(164 citation statements)

References 12 publications

Supporting

Mentioning

160

Contrasting

Unclassified

Order By: Relevance

“…Wavelet analysis has spread into many fields of research, such as signal processing, geophysics and climatology, and is becoming more and more popular within ecology (e.g. Bradshaw & Spies 1992, Grenfell et al 2001, Klvana et al 2004, Keitt & Urban 2005, Keitt & Fischer 2006, Ménard et al 2007. Nonetheless, wavelet analysis still displays 2 shortcomings with respect to its use in ecology.…”

Section: Resale or Republication Not Permitted Without Written Consenmentioning

confidence: 99%

Analysing multiple time series and extending significance testing in wavelet analysis

Rouyer¹,

Fromentin²,

Stenseth³

et al. 2008

Mar. Ecol. Prog. Ser.

101

105

View full text Add to dashboard Cite

Section: Resale or Republication Not Permitted Without Written Consenmentioning

confidence: 99%

Analysing multiple time series and extending significance testing in wavelet analysis

Rouyer¹,

Fromentin²,

Stenseth³

et al. 2008

Mar. Ecol. Prog. Ser.

101

105

View full text Add to dashboard Cite

“…The discrete wavelet transform (DWT) has been increasingly used in recent years in the processing of hyperspectral images for a variety of purposes [33][34][35][36][37][38][39]. These studies have shown its importance as an effective tool for reducing the dimensionality of hyperspectral data while maintaining information content for a variety of applications.…”

Section: Introductionmentioning

confidence: 99%

Investigating the Utility of Wavelet Transforms for Inverting a 3-D Radiative Transfer Model Using Hyperspectral Data to Retrieve Forest LAI

et al. 2013

View full text Add to dashboard Cite

Abstract:The need for an efficient and standard technique for optimal spectral sampling of hyperspectral data during the inversion of canopy reflectance models has been the subject of many studies. The objective of this study was to investigate the utility of the discrete wavelet transform (DWT) for extracting useful features from hyperspectral data with which forest LAI can be estimated through inversion of a three dimensional radiative transfer model, the Discrete Anisotropy Radiative Transfer (DART) model. DART, coupled with the leaf optical properties model PROSPECT, was inverted with AVIRIS data using a look-up-table (LUT)-based inversion approach. We used AVIRIS data and in situ LAI measurements from two different hardwood forested sites in Wisconsin, USA. Prior to inversion, model-simulated and AVIRIS hyperspectral data were transformed into discrete wavelet coefficients using Haar wavelets. The LUT inversion was performed with three different datasets, the original reflectance bands, the full set of wavelet extracted features, and two wavelet subsets containing 99.99% and 99.0% of the cumulative energy The results indicate that the discrete wavelet transform can increase the accuracy of LAI estimates by improving the LUT-based inversion of DART (and, potentially, by implication, other terrestrial radiative transfer models) using hyperspectral data. The improvement in accuracy of LAI estimates is potentially due to different properties of wavelet analysis such as multi-scale representation, dimensionality reduction, and noise removal.

show abstract

“…Wavelets have been heavily studied in mathematics and engineering for signal analysis and data compression, but have had limited use in biology [27] [28] [29] [30].…”

Section: Quantitative Measurementsmentioning

confidence: 99%

Structural Patterns of Immunoreactivity to Cytokeratin 18 in Normal Prostate and Benign Prostate Hyperplasia: Global and Local Differences

Santamarı́a¹,

Ingelmo²,

Teba³

2017

OJPathology

View full text Add to dashboard Cite

Background: Benign prostate hyperplasia (BPH) is the most common benign disease of the human prostate. The comparison between global versus local changes in spatial patterns of pathological lesions provoked a growing interest in some fields such as neuropathology. To date, there is little data on this subject in prostatic pathology. Given the interest of local parameters to distinguish between normal and pathological structures, the present study will apply first and second order stereological tools to find out if the cytokeratin18 (ck18) immunoexpression shows relevant local changes in BPH compared to normal prostate, independently if global estimates were similar in both groups. Methods: To verify if the global and local changes in immunoexpression of ck18 are relevant to ascertain differences between normal (CTR) and BPH cases, the following parameters will be applied: Volume fraction of epithelium immunostained for ck18 (V V ck18), both in global and local estimates; dispersion indices of V V ck18; estimates of local variance of V V ck18 (positional and of scale) using wavelet analysis; and lacunarity analysis to measure the tissue heterogeneity. Then, the set of values from the parameters studied that show significant differences between CTR and BPH will be employed to perform stepwise linear discriminant analyses to determine if locally estimated parameters were able to classify accurately the cases in CTR and BPH groups. Results and Conclusions: The findings of the present study indicate that changes in the expression of ck18 by the hyperplastic prostatic epithelium are not homogeneous. This limits the use of a single biopsy based markers to predict biological behavior in BPH. On the other hand, the local changes in the expression of ck18 are more evident in terms of V V ck18 and its 26local variability, whereas other parameters that are useful in other pathologies, such as lacunarity, are less relevant In prostatic hyperplasia.

show abstract

Characterizing Canopy Gap Structure in Forests Using Wavelet Analysis

Cited by 214 publications

References 12 publications

Analysing multiple time series and extending significance testing in wavelet analysis

Analysing multiple time series and extending significance testing in wavelet analysis

Investigating the Utility of Wavelet Transforms for Inverting a 3-D Radiative Transfer Model Using Hyperspectral Data to Retrieve Forest LAI

Structural Patterns of Immunoreactivity to Cytokeratin 18 in Normal Prostate and Benign Prostate Hyperplasia: Global and Local Differences

Contact Info

Product

Resources

About