PMID- 29906733
OWN - NLM
STAT- PubMed-not-MEDLINE
DCOM- 20180724
LR  - 20180724
IS  - 1879-1026 (Electronic)
IS  - 0048-9697 (Linking)
VI  - 642
DP  - 2018 Nov 15
TI  - Monitoring ecosystem reclamation recovery using optical remote sensing: 
      Comparison with field measurements and eddy covariance.
PG  - 436-446
LID - S0048-9697(18)32101-6 [pii]
LID - 10.1016/j.scitotenv.2018.06.039 [doi]
AB  - Time series remote sensing vegetation indices derived from SPOT 5 data are 
      compared with vegetation structure and eddy covariance flux data at 15 dry to wet 
      reclamation and reference sites within the Oil Sands region of Alberta, Canada. 
      This comprehensive analysis examines the linkages between indicators of ecosystem 
      function and change trajectories observed both at the plot level and within 
      pixels. Using SPOT imagery, we find that higher spatial resolution datasets (e.g. 
      10 m) improves the relationship between vegetation indices and structural 
      measurements compared with interpolated (lower resolution) pixels. The simple 
      ratio (SR) vegetation index performs best when compared with stem density-based 
      indicators (R(2) = 0.65; p < 0.00), while the normalised difference vegetation 
      index (NDVI) and soil adjusted vegetation index (SAVI) are most comparable to 
      foliage indicators (leaf area index (LAI) and canopy cover (R(2) = 0.52-0.78; 
      p > 0.02). Fluxes (net ecosystem production (NEP) and gross ecosystem production 
      (GEP)) are most related to NDVI and SAVI when these are interpolated to larger 
      20 m x 20 m pixels (R(2) = 0.44-0.50; p < 0.00). As expected, decreased 
      sensitivity of NDVI is problematic for sites with LAI > 3 m(2) m(-2), making this 
      index more appropriate for newly regenerating reclamation areas. For sites with 
      LAI < 3 m(2) m(-2), trajectories of vegetation change can be mapped over time and 
      are within 2.7% and 3.3% of annual measured LAI changes observed at most sites. 
      This study demonstrates the utility of remote sensing in combination with field 
      and eddy covariance data for monitoring and scaling of reclaimed and reference 
      site productivity within and beyond the Oil Sands Region of western Canada.
CI  - Copyright (c) 2018 Elsevier B.V. All rights reserved.
FAU - Chasmer, L
AU  - Chasmer L
AD  - Dept. of Geography, University of Lethbridge, Lethbridge, Alberta T1K 3M4, 
      Canada. Electronic address: laura.chasmer@uleth.ca.
FAU - Baker, T
AU  - Baker T
AD  - Integral Ecology Group, Duncan, British Columbia V9L 6H1, Canada.
FAU - Carey, S K
AU  - Carey SK
AD  - School of Geography and Earth Sciences, McMaster University, Hamilton, Ontario 
      L8S 4K1, Canada.
FAU - Straker, J
AU  - Straker J
AD  - Integral Ecology Group, Duncan, British Columbia V9L 6H1, Canada.
FAU - Strilesky, S
AU  - Strilesky S
AD  - Dept. of Geography, Carleton University, Ottawa, Ontario K1S 5B6, Canada.
FAU - Petrone, R
AU  - Petrone R
AD  - Dept. of Geography & Environmental Management, University of Waterloo, Waterloo, 
      Ontario N2L 3G1, Canada.
LA  - eng
PT  - Journal Article
DEP - 20180614
PL  - Netherlands
TA  - Sci Total Environ
JT  - The Science of the total environment
JID - 0330500
OTO - NOTNLM
OT  - Biomass
OT  - LAI
OT  - Net ecosystem exchange
OT  - Oil sands reclamation
OT  - Remote sensing
OT  - Trajectory
EDAT- 2018/06/16 06:00
MHDA- 2018/06/16 06:01
CRDT- 2018/06/16 06:00
PHST- 2018/03/13 00:00 [received]
PHST- 2018/06/04 00:00 [revised]
PHST- 2018/06/04 00:00 [accepted]
PHST- 2018/06/16 06:00 [pubmed]
PHST- 2018/06/16 06:01 [medline]
PHST- 2018/06/16 06:00 [entrez]
AID - S0048-9697(18)32101-6 [pii]
AID - 10.1016/j.scitotenv.2018.06.039 [doi]
PST - ppublish
SO  - Sci Total Environ. 2018 Nov 15;642:436-446. doi: 10.1016/j.scitotenv.2018.06.039. 
      Epub 2018 Jun 14.