Statistical comparison of spectral and biochemical measurements on an example of Norway spruce stands in the Ore Mountains, Czech Republic
DOI:
https://doi.org/10.14311/gi.15.1.6Keywords:
Laboratory spectroscopy, hyperspectral imagery, Ore Mountains, Norway spruce, Chlorophyll, Carotenoids, RWC.Abstract
The physiological status of vegetation and changes thereto can be monitored by means of biochemical analysis of collected samples as well as by means of spectroscopic measurements either on the leaf level, using field (or laboratory) spectroradiometers or on the canopy level, applying hyperspectral airborne or spaceborne image data. The presented study focuses on the statistical comparison and ascertainment of relations between three datasets collected from selected Norway spruce forest stands in the Ore Mountains, Czechia. The data sets comprise i) photosynthetic pigments (chlorophylls, carotenoids) and water content of 495 samples collected from 55 trees from three different vertical levels and the first three needle age classes, ii) the spectral reflectance of the same samples measured with an ASD Field Spec 4 Wide-Res spectroradiometer equipped with a plant contact probe, iii) an airborne hyperspecral image acquired with an Apex sensor. The datasets cover two localities in the Ore Mountains that were affected differently by acid deposits in the 1970s and 1980s. A one-way analysis of variance (ANOVA), Tukey’s honest significance test, hot spot analysis and linear regression were applied either on the original measurements (the content of leaf compounds and reflectance spectra) or derived values, i.e., selected spectral indices. The results revealed a generally low correlation between the photosynthetic pigments, water content and spectral measurement. The results of the ANOVA showed significant differences between sites (model areas) only in the case of the leaf compound dataset. Differences between the stands on various levels of significance exist in all three datasets and are explained in detail. The study also proved that the vertical gradient of the biochemical and biophysical parameters in the canopy play a role when the optical properties of the forest stands are modelled.References
Jonas Ardö et al. “Satellite Based Estimations of Coniferous Forest Cover Changes:
Krusne Hory, Czech Republic”. In: Ambio 26.3 (1997), pp. 158–166.
ASD Inc. Analytical Spectral Devices. 2013. url: http://www.asdi.com/products-
and-services (visited on 06/03/2016).
ASD Inc. Analytical spectral devices. Ed. by David C Hatchell. Technical Guide 3rd.
Ed. 1999. url: http://www.geo- informatie.nl/courses/grs60312/fieldwork/
New%20Folder%20%282%29/Fieldspec%20fieldguide%20TG_Rev4_web.pdf (visited
on 06/03/2016).
Richard J. Aspinall, W. Andrew Marcus, and Joseph W. Boardman. “Considerations
in collecting, processing, and analysing high spatial resolution hyperspectral data for
environmental investigations”. In: Journal of Geographical Systems 4.1 (2002), pp. 15–
doi: 10.1007/s101090100071.
P. K. Entcheva Campbell et al. “Detection of initial damage in Norway spruce canopies
using hyperspectral airborne data”. In: International Journal of Remote Sensing 25.24
(2004), pp. 5557–5584. doi: 10.1080/01431160410001726058.
Gregory A Carter and Alan K Knapp. “Leaf optical properties in higher plants: linking
spectral characteristics to stress and chlorophyll concentration”. In: American Journal
of Botany 88.4 (2001), pp. 677–684. doi: 10.2307/2657068.
Lucie Červená et al. “Models for estimating leaf pigments and relative water content
in three vertical canopy levels of norway spruce based on laboratory spectroscopy”. In:
EARSeL 34th Symposium Proceedings. Ed. by B. Zagajewski, M. Kycko, and R. Reuter.
EARSeL and University of Warsaw, 16–20 June 2014. doi: 10.12760/03-2014-11. url:
http://www.earsel.org/symposia/2014- symposium- Warsaw/pdf_proceedings/
EARSeL-Symposium-2014_6_1_cervena.pdf (visited on 06/03/2016).
Roshanak Darvishzadeh et al. “Mapping grassland leaf area index with airborne hyper-
spectral imagery: A comparison study of statistical approaches and inversion of radia-
tive transfer models”. In: ISPRS Journal of Photogrammetry and Remote Sensing 66.6
(2011), pp. 894–906. doi: 10.1016/j.isprsjprs.2011.09.013.
Jean-Baptiste Feret et al. “PROSPECT-4 and 5: Advances in the leaf optical properties
model separating photosynthetic pigments”. In: Remote Sensing of Environment 112.6
(2008), pp. 3030–3043. doi: 10.1016/j.rse.2008.02.012.
Arthur Getis and J Keith Ord. “The analysis of spatial association by use of distance
statistics”. In: Geographical analysis 24.3 (1992), pp. 189–206. doi: 10.1111/j.1538-
1992.tb00261.x.
Anatoly A Gitelson et al. “Assessing carotenoid content in plant leaves with reflectance
spectroscopy”. In: Photochemistry and Photobiology 75.3 (2002), pp. 272–281. doi: 10.
/0031-8655(2002)0750272accipl2.0.co2.
Driss Haboudane et al. “Integrated narrow-band vegetation indices for prediction of
crop chlorophyll content for application to precision agriculture”. In: Remote sensing of
environment 81.2 (2002), pp. 416–426. doi: 10.1016/s0034-4257(02)00018-4.
E Raymond Hunt and Barrett N Rock. “Detection of changes in leaf water content using
near-and middle-infrared reflectances”. In: Remote sensing of environment 30.1 (1989),
pp. 43–54. doi: 10.1016/0034-4257(89)90046-1.
Stéphane Jacquemoud et al. “PROSPECT+ SAIL models: A review of use for vegetation
characterization”. In: Remote Sensing of Environment 113 (2009), S56–S66. doi: 10.
/j.rse.2008.01.026.
Raymond F Kokaly and Roger N Clark. “Spectroscopic determination of leaf biochem-
istry using band-depth analysis of absorption features and stepwise multiple linear re-
gression”. In: Remote sensing of environment 67.3 (1999), pp. 267–287. doi: 10.1016/
s0034-4257(98)00084-4.
Raymond F Kokaly et al. “Characterizing canopy biochemistry from imaging spec-
troscopy and its application to ecosystem studies”. In: Remote Sensing of Environment
(2009), S78–S91. doi: 10.1016/j.rse.2008.10.018.
Lucie Kupková et al. “Chlorophyll determination in silver birch and scots pine foliage
from heavy metal polluted regions using spectral reflectance data”. In: EARSeL e-
Proceedings. Vol. 11. 1. 2012, pp. 64–73. url: http://eproceedings.org/static/
vol11_1/11_1_kupkova1.pdf (visited on 06/03/2016).
Zuzana Lhotáková et al. “Detection of multiple stresses in Scots pine growing at post-
mining sites using visible to near-infrared spectroscopy”. In: Environmental Science:
Processes & Impacts 15.11 (2013), pp. 2004–2015. doi: 10.1039/c3em00388d.
Zuzana Lhotáková et al. “Does the azimuth orientation of Norway spruce (Picea abies/L.
/Karst.) branches within sunlit crown part influence the heterogeneity of biochemical,
structural and spectral characteristics of needles?” In: Environmental and experimental
botany 59.3 (2007), pp. 283–292. doi: 10.1016/j.envexpbot.2006.02.003.
Z Malenovský et al. “Applicability of the PROSPECT model for Norway spruce nee-
dles”. In: International Journal of Remote Sensing 27.24 (2006), pp. 5315–5340. doi:
1080/01431160600762990.
Jan Mišurec et al. “Detection of Spatio-Temporal Changes of Norway Spruce Forest
Stands in Ore Mountains Using Landsat Time Series and Airborne Hyperspectral Im-
agery”. In: Remote Sensing 8.2 (2016), p. 92. doi: 10.3390/rs8020092.
J Peñuelas et al. “Estimation of plant water concentration by the reflectance water
index WI (R900/R970)”. In: International Journal of Remote Sensing 18.13 (1997),
pp. 2869–2875. doi: 10.1080/014311697217396.
RJ Porra, WA Thompson, and PE Kriedemann. “Determination of accurate extinc-
tion coefficients and simultaneous equations for assaying chlorophylls a and b extracted
with four different solvents: verification of the concentration of chlorophyll standards by
atomic absorption spectroscopy”. In: Biochimica et Biophysica Acta (BBA)-Bioenergetics
3 (1989), pp. 384–394. doi: 0.1016/s0005-2728(89)80347-0.
Michael E Schaepman et al. “Advanced radiometry measurements and Earth science
applications with the Airborne Prism Experiment (APEX)”. In: Remote Sensing of
Environment 158 (2015), pp. 207–219. doi: 10.1016/j.rse.2014.11.014.
Daniel A Sims and John A Gamon. “Relationships between leaf pigment content and
spectral reflectance across a wide range of species, leaf structures and developmental
stages”. In: Remote sensing of environment 81.2 (2002), pp. 337–354. doi: 10.1016/
s0034-4257(02)00010-x.
Quan Wang and Pingheng Li. “Canopy vertical heterogeneity plays a critical role in
reflectance simulation”. In: Agricultural and forest meteorology 169 (2013), pp. 111–
doi: 10.1016/j.agrformet.2012.10.004.
Alan R Wellburn. “The spectral determination of chlorophylls a and b, as well as total
carotenoids, using various solvents with spectrophotometers of different resolution”. In:
Journal of plant physiology 144.3 (1994), pp. 307–313. doi: 10.1016/s0176-1617(11)
-2.
Downloads
Published
Issue
Section
License
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).