TY - JOUR
T1 - Camera derived vegetation greenness index as proxy for gross primary production in a low Arctic wetland area
AU - Westergaard-Nielsen, Andreas
AU - Lund, Magnus
AU - Hansen, Birger Ulf
AU - Tamstorf, Mikkel Peter
N1 - CENPERM[2013]
PY - 2013/12
Y1 - 2013/12
N2 - The Arctic is experiencing disproportionate warming relative to the global average, and the Arctic ecosystems are as a result undergoing considerable changes. Continued monitoring of ecosystem productivity and phenology across temporal and spatial scales is a central part of assessing the magnitude of these changes. This study investigates the ability to use automatic digital camera images (DCIs) as proxy data for gross primary production (GPP) in a complex low Arctic wetland site. Vegetation greenness computed from DCIs was found to correlate significantly (R2=0.62, p<0.001) with a normalized difference vegetation index (NDVI) product derived from the WorldView-2 satellite. An object-based classification based on a bi-temporal image composite was used to classify the study area into heath, copse, fen, and bedrock. Temporal evolution of vegetation greenness was evaluated and modeled with double sigmoid functions for each plant community. GPP at light saturation modeled from eddy covariance (EC) flux measurements were found to correlate significantly with vegetation greenness for all plant communities in the studied year (i.e., 2010), and the highest correlation was found between modeled fen greenness and GPP (R2=0.85, p<0.001). Finally, greenness computed within modeled EC footprints were used to evaluate the influence of individual plant communities on the flux measurements. The study concludes that digital cameras may be used as a cost-effective proxy for potential GPP in remote Arctic regions.
AB - The Arctic is experiencing disproportionate warming relative to the global average, and the Arctic ecosystems are as a result undergoing considerable changes. Continued monitoring of ecosystem productivity and phenology across temporal and spatial scales is a central part of assessing the magnitude of these changes. This study investigates the ability to use automatic digital camera images (DCIs) as proxy data for gross primary production (GPP) in a complex low Arctic wetland site. Vegetation greenness computed from DCIs was found to correlate significantly (R2=0.62, p<0.001) with a normalized difference vegetation index (NDVI) product derived from the WorldView-2 satellite. An object-based classification based on a bi-temporal image composite was used to classify the study area into heath, copse, fen, and bedrock. Temporal evolution of vegetation greenness was evaluated and modeled with double sigmoid functions for each plant community. GPP at light saturation modeled from eddy covariance (EC) flux measurements were found to correlate significantly with vegetation greenness for all plant communities in the studied year (i.e., 2010), and the highest correlation was found between modeled fen greenness and GPP (R2=0.85, p<0.001). Finally, greenness computed within modeled EC footprints were used to evaluate the influence of individual plant communities on the flux measurements. The study concludes that digital cameras may be used as a cost-effective proxy for potential GPP in remote Arctic regions.
KW - Low Arctic
KW - Digital camera
KW - Vegetation index
KW - Carbon
KW - Eddy covariance
KW - Gross primary production
U2 - 10.1016/j.isprsjprs.2013.09.006
DO - 10.1016/j.isprsjprs.2013.09.006
M3 - Journal article
SN - 0924-2716
VL - 86
SP - 89
EP - 99
JO - ISPRS Journal of Photogrammetry and Remote Sensing
JF - ISPRS Journal of Photogrammetry and Remote Sensing
ER -