Options
Mapping litter decomposition by remote-detected indicators
Author(s)
Issued date
February 2006
Issue/vol(year)
1/49 (2006)
Language
English
Abstract
Leaf litter decomposition is a key process for the functioning of natural ecosystems. An important limiting factor
for this process is detritus availability, which we have estimated by remote sensed indices of canopy green
biomass (NDVI). Here, we describe the use of multivariate geostatistical analysis to couple in situ measures with
hyper-spectral and multi-spectral remote-sensed data for producing maps of litter decomposition. A direct relationship
between the decomposition rates in four different CORINE habitats and NDVI, calculated at different
scales from Landsat ETM+ multi-spectral data and MIVIS hyper-spectral data was found. Variogram analysis
was used to evaluate the spatial properties of each single variable and their common interaction. Co-variogram
and co-kriging analysis of the two variables turned out to be an effective approach for decomposition mapping
from remote-sensed spatial explicit data.
for this process is detritus availability, which we have estimated by remote sensed indices of canopy green
biomass (NDVI). Here, we describe the use of multivariate geostatistical analysis to couple in situ measures with
hyper-spectral and multi-spectral remote-sensed data for producing maps of litter decomposition. A direct relationship
between the decomposition rates in four different CORINE habitats and NDVI, calculated at different
scales from Landsat ETM+ multi-spectral data and MIVIS hyper-spectral data was found. Variogram analysis
was used to evaluate the spatial properties of each single variable and their common interaction. Co-variogram
and co-kriging analysis of the two variables turned out to be an effective approach for decomposition mapping
from remote-sensed spatial explicit data.
References
ABER, J.D. and J.M. MELILLO (1980): Litter decomposition:
measuring relative contribution of organic matter and
nitrogen to forest soil, Can. J. Bot., 58, 416-421.
ABER, J.D., J.M. MELILLO and C. MCCLAUGHERTY (1990):
Predicting long-term patterns of mass loss, nitrogen
dynamics, and soil organic matter formation from initial
fine litter chemistry in temperate forest ecosystems.
Can. J. Bot., 68, 2201-260.
AERTS, R. (1997): Climate, leaf litter chemistry and leaf litter
decomposition in terrestrial ecosystems: a triangular
relationship, Oikos, 79, 439-449.
CARD, D.H., D.J. PETERSON, P.A. MATSON and J.D. ABER
(1988): Prediction of leaf chemistry by the use of visible
and near-infrared reflectance spectroscopy, Remote
Sensing Environ., 26, 123-147.
CHAVEZ, P.S. JR. (1988): An improved dark-object subtraction
technique for atmospheric scattering correction of multispectral
data, Remote Sensing Environ., 24, 459-479.
CURRAN, P.J. (2001): Remote sensing: Using the spatial domain,
Environ. Ecol. Stat., 8, 331-344.
DUGAN, J.P., D.L. PETERSON and P.J. CURRAN (1994): Alternative
approaches for mapping vegetation quantities
using ground and image data, in Environmental Information
Management and Analysis: Ecosystem to Global
Scales, edited by W. MICHENER, J. BRUNT and S.
STAFFORD (Taylor and Francis, London), 237-261.
EUROPEAN UNION/DIRECTORATE GENERAL XI (1991): CORINE
Biotopes Manual, Habitats of the European
Community. A Method to Identify and Describe Consistently
Sites of Major Importance for Nature Conservation
(Bruxelles), EUR 12587/3.
GALLARDO, A. and J. MERINO (1993): Leaf decomposition – Influence of substrate quality, Ecology, 74 (1), 152-
161.
GILLON, D., R. JOFFRE and A. IBRAHIMA (1999): Can litter
decomposability be predicted by near infrared reflectance
spectroscopy?, Ecology, 80 (1), 175-186.
ISAAKS, E.H. and R.M. SRIVASTAVA (1989): Applied Geostatistics
(Oxford University Press, Oxford).
KRUSE, F.A., K.S. KIEREN-YOUNG and J.W BOARDMAN
(1990): Mineral Mapping at Cuprite, Nevada with a 63
channel imaging spectrometer, Photogramm. Eng. Remote
Sensing Environ., 56 (1), 83-92.
LEGENDRE, P. and M.-J. FORTIN (1989): Spatial pattern and
ecological analysis, Vegetatio, 80, 107-138.
MARTIN, M.E. and J.D. ABER (1994): Analysis of forest foliage,
III. Determining nitrogen, lignin and cellulose in
fresh leaves using near infrared reflectance data, J.
Near Infrared Spectrosc., 2, 25-32.
OLSON, J.S. (1963): Energy storage and the balance of producers
and decomposers in ecological systems, Ecology,
44, 322-331.
PEBESMA, E.J. and C.G. WESSELING (1998): GSTAT: a program
for geostatistical modelling, prediction and simulation,
Comput. Geosci., 24 (1), 17-31.
PEREZ-HARGUINDEGUY, N., S. DIAZ, J.H.C. CORNELISSEN, F.
VERDRAMINI, M. CABIDO and A. CASTELLANOS (2000): decomposition
rates over a wide spectrum of functional types in
Central Argentina, Plant Soil, 218, 212-30.
RICHARDS, J.A. (1994): Remote Sensing Digital Image Analysis
(Springer-Verlag, Berlin), p. 340.
ROSSI, R.E., D.J. MULLA, A.G. JOURNEL and E.H. FRANZ
(1992): Geostatistical tools for modeling and interpreting
ecological spatial dependence, Ecol. Monogr., 62,
277-314.
ROUSE, J.W., R.H. HAAS, J.A. SHELL, D.W. DEERING and
J.C. HARLAN (1974): Monitoring the vernal advancement
of retrogradation of natural vegetation, NASA/
GSFC, Greenbelt, MD, Final Rep.
SAUNDERS, G.W. (1976): Decomposition in freshwater, in
The Role of Terrestrial and Aquatic Organism in Decomposition
Processes, edited by J.M. ANDERSON and
A. MACFADYEN (Blackwell Scientific), 341-374.
SWIFT, M.J., O.W. HEAL and J.M. ANDERSON (1979): Decomposition
in Terrestrial Ecosystems (Univ. Calif.
Press, Berkeley), pp. 509.
USGS (2004): Revised Landsat 5 TM Radiometric Calibration
Procedures and Post-Calibration Dynamic Ranges,
edited by J. CHANDER and B. MARKHAM (USGS, Landsat
Project; on line http://landsat7.usgs.gov/resource.html).
WACKERNAGEL, H. (1995): Multivariate Geostatistics. An Introduction
with Applications (Springer-Verlag, Berlin).
measuring relative contribution of organic matter and
nitrogen to forest soil, Can. J. Bot., 58, 416-421.
ABER, J.D., J.M. MELILLO and C. MCCLAUGHERTY (1990):
Predicting long-term patterns of mass loss, nitrogen
dynamics, and soil organic matter formation from initial
fine litter chemistry in temperate forest ecosystems.
Can. J. Bot., 68, 2201-260.
AERTS, R. (1997): Climate, leaf litter chemistry and leaf litter
decomposition in terrestrial ecosystems: a triangular
relationship, Oikos, 79, 439-449.
CARD, D.H., D.J. PETERSON, P.A. MATSON and J.D. ABER
(1988): Prediction of leaf chemistry by the use of visible
and near-infrared reflectance spectroscopy, Remote
Sensing Environ., 26, 123-147.
CHAVEZ, P.S. JR. (1988): An improved dark-object subtraction
technique for atmospheric scattering correction of multispectral
data, Remote Sensing Environ., 24, 459-479.
CURRAN, P.J. (2001): Remote sensing: Using the spatial domain,
Environ. Ecol. Stat., 8, 331-344.
DUGAN, J.P., D.L. PETERSON and P.J. CURRAN (1994): Alternative
approaches for mapping vegetation quantities
using ground and image data, in Environmental Information
Management and Analysis: Ecosystem to Global
Scales, edited by W. MICHENER, J. BRUNT and S.
STAFFORD (Taylor and Francis, London), 237-261.
EUROPEAN UNION/DIRECTORATE GENERAL XI (1991): CORINE
Biotopes Manual, Habitats of the European
Community. A Method to Identify and Describe Consistently
Sites of Major Importance for Nature Conservation
(Bruxelles), EUR 12587/3.
GALLARDO, A. and J. MERINO (1993): Leaf decomposition – Influence of substrate quality, Ecology, 74 (1), 152-
161.
GILLON, D., R. JOFFRE and A. IBRAHIMA (1999): Can litter
decomposability be predicted by near infrared reflectance
spectroscopy?, Ecology, 80 (1), 175-186.
ISAAKS, E.H. and R.M. SRIVASTAVA (1989): Applied Geostatistics
(Oxford University Press, Oxford).
KRUSE, F.A., K.S. KIEREN-YOUNG and J.W BOARDMAN
(1990): Mineral Mapping at Cuprite, Nevada with a 63
channel imaging spectrometer, Photogramm. Eng. Remote
Sensing Environ., 56 (1), 83-92.
LEGENDRE, P. and M.-J. FORTIN (1989): Spatial pattern and
ecological analysis, Vegetatio, 80, 107-138.
MARTIN, M.E. and J.D. ABER (1994): Analysis of forest foliage,
III. Determining nitrogen, lignin and cellulose in
fresh leaves using near infrared reflectance data, J.
Near Infrared Spectrosc., 2, 25-32.
OLSON, J.S. (1963): Energy storage and the balance of producers
and decomposers in ecological systems, Ecology,
44, 322-331.
PEBESMA, E.J. and C.G. WESSELING (1998): GSTAT: a program
for geostatistical modelling, prediction and simulation,
Comput. Geosci., 24 (1), 17-31.
PEREZ-HARGUINDEGUY, N., S. DIAZ, J.H.C. CORNELISSEN, F.
VERDRAMINI, M. CABIDO and A. CASTELLANOS (2000): decomposition
rates over a wide spectrum of functional types in
Central Argentina, Plant Soil, 218, 212-30.
RICHARDS, J.A. (1994): Remote Sensing Digital Image Analysis
(Springer-Verlag, Berlin), p. 340.
ROSSI, R.E., D.J. MULLA, A.G. JOURNEL and E.H. FRANZ
(1992): Geostatistical tools for modeling and interpreting
ecological spatial dependence, Ecol. Monogr., 62,
277-314.
ROUSE, J.W., R.H. HAAS, J.A. SHELL, D.W. DEERING and
J.C. HARLAN (1974): Monitoring the vernal advancement
of retrogradation of natural vegetation, NASA/
GSFC, Greenbelt, MD, Final Rep.
SAUNDERS, G.W. (1976): Decomposition in freshwater, in
The Role of Terrestrial and Aquatic Organism in Decomposition
Processes, edited by J.M. ANDERSON and
A. MACFADYEN (Blackwell Scientific), 341-374.
SWIFT, M.J., O.W. HEAL and J.M. ANDERSON (1979): Decomposition
in Terrestrial Ecosystems (Univ. Calif.
Press, Berkeley), pp. 509.
USGS (2004): Revised Landsat 5 TM Radiometric Calibration
Procedures and Post-Calibration Dynamic Ranges,
edited by J. CHANDER and B. MARKHAM (USGS, Landsat
Project; on line http://landsat7.usgs.gov/resource.html).
WACKERNAGEL, H. (1995): Multivariate Geostatistics. An Introduction
with Applications (Springer-Verlag, Berlin).
Type
article
File(s)
Loading...
Name
24 Sabetta.pdf
Size
1.65 MB
Format
Adobe PDF
Checksum (MD5)
c155fed9898d0458df0f319ff2bc7302