Spatial Upscaling of Tree-Ring-Based Forest Response to Drought with Satellite Data

• Main Authors: Peipei Xu, Wei Fang, Tao Zhou, Xiang Zhao, Hui Luo, George Hendrey, Chuixiang Yi
• Format: Article
• Language: English
• Published: MDPI AG 2019-10-01
• Series: Remote Sensing
• Subjects: ndvi; tree ring; upscaling; drought
• Online Access: https://www.mdpi.com/2072-4292/11/20/2344

We have integrated the observational capability of satellite remote sensing with plot-scale tree-ring data to upscale the evaluation of forest responses to drought. Satellite data, such as the normalized difference vegetation index (NDVI), can provide a spatially continuous measure with limited temporal coverage, while tree-ring width index (RWI) provides an accurate assessment with a much longer time series at local scales. Here, we explored the relationship between RWI and NDVI of three dominant species in the Southwestern United States (SWUS) and predicted RWI spatial distribution from 2001 to 2017 based on Moderate Resolution Imaging Spectroradiometer (MODIS) 1-km resolution NDVI data with stringent quality control. We detected the optimum time windows (around June−August) during which the RWI and NDVI were most closely correlated for each species, when the canopy growth had the greatest effect on growth of tree trunks. Then, using our upscaling algorithm of NDVI-based RWI, we were able to detect the significant impact of droughts in 2002 and in 2011−2014, which supported the validity of this algorithm in quantifying forest response to drought on a large scale.