Dept. of Geography, University of Lethbridge, Lethbridge, Alberta T1K 3M4, Canada.
Integral Ecology Group, Duncan, British Columbia V9L 6H1, Canada.
Sci Total Environ. 2018 Nov 15;642:436-446. doi: 10.1016/j.scitotenv.2018.06.039. Epub 2018 Jun 14.
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 = 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 = 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 × 20 m pixels (R = 0.44-0.50; p < 0.00). As expected, decreased sensitivity of NDVI is problematic for sites with LAI > 3 m m, making this index more appropriate for newly regenerating reclamation areas. For sites with LAI < 3 m m, 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.
利用 SPOT5 数据提取的时间序列遥感植被指数与加拿大阿尔伯塔省油砂区 15 个干湿开垦区和对照区的植被结构和涡度协方差通量数据进行了比较。这项综合分析考察了在斑块水平和像素内观测到的生态系统功能指标和变化轨迹之间的联系。利用 SPOT 图像，我们发现与插值（低分辨率）像素相比，较高空间分辨率数据集（例如 10m）可改善植被指数与结构测量之间的关系。与基于茎密度的指标相比，简单比值（SR）植被指数的表现最佳（R=0.65;p<0.00），而归一化差异植被指数（NDVI）和土壤调整植被指数（SAVI）与叶指标（叶面积指数（LAI）和冠层覆盖率（R=0.52-0.78;p>0.02）最可比。当将通量（净生态系统生产力（NEP）和总生态系统生产力（GEP））插值到较大的 20m×20m 像素时，与 NDVI 和 SAVI 最为相关（R=0.44-0.50;p<0.00）。正如预期的那样，NDVI 的灵敏度降低对于 LAI>3mm 的站点是有问题的，这使得该指数更适合新再生开垦区。对于 LAI<3mm 的站点，可以随时间映射植被变化的轨迹，并且与大多数站点观测到的年际测量 LAI 变化相差 2.7%和 3.3%。本研究证明了遥感与现场和涡度协方差数据相结合，可用于监测和扩展加拿大西部油砂区内外开垦区和对照区的生产力。
