Satellite radar remote sensing of seasonal growing seasons for boreal and subalpine evergreen forests

详细信息	查看全文 | 推荐本文 |

• 作者：Kimball ; John S. ; McDonald ; Kyle C. ; Running ; Steven W. ; Frolking ; Steve E.
• 关键词：Radar remote sensing ; Growing season ; Evergreen forest ; Phenology ; NPP ; SeaWinds ; Boreal forest ; Freeze-thaw ; BIOME-BGC
• 刊名：Remote Sensing of Environment
• 出版年：2004
• 期刊代码：79_00344257
• 类别：ear
• 出版时间：March 30, 2004
• 卷：90
• 期：2
• 页码：243-258
• 文件大小：1.21 M

摘要

We evaluated whether satellite radar remote sensing of landscape seasonal freeze–thaw cycles provides an effective measure of active growing season timing and duration for boreal and subalpine evergreen forests. Landscape daily radar backscatter measurements from the SeaWinds scatterometer on-board the QuikSCAT satellite were evaluated across a regional network of North American coniferous forest sites for 2000 and 2001. Radar remote sensing measurements of the initiation and length of the growing season corresponded closely with both site measurements and ecosystem process model (BIOME-BGC) simulations of these parameters because of the sensitivity of the K_u-band scatterometer to snow cover freeze–thaw dynamics and associated linkages between growing season initiation and the timing of seasonal snowmelt. In contrast, remote sensing estimates of the timing of growing season termination were either weakly or not significantly associated with site measurements and model simulation results, due to the relative importance of light availability and other environmental controls on stand phenology in the fall. Regional patterns of estimated annual net primary production (NPP) and component photosynthetic and autotrophic respiration rates for the evergreen forest sites also corresponded favorably with remote sensing estimates of the seasonal timing of spring thaw and associated growing season length, indicating the importance of these parameters in determining spatial and temporal patterns of NPP and the potential utility of satellite radar remote sensing for regional monitoring of the terrestrial biosphere.