TITLE:
The Use of Sentinel-2 Data in Detecting Brown Spot Needle Blight in Loblolly Pine
AUTHORS:
Kate S. Montgomery, Michael K. Crosby, Laura L. Sims, Joshua P. Adams
KEYWORDS:
Brown Spot Needle Blight, Image Indices, TGI, NDVI, VARI, Loblolly Pine
JOURNAL NAME:
Open Journal of Forestry,
Vol.15 No.4,
September
22,
2025
ABSTRACT: Over the last several years, pine forests in the southeastern United States have been impacted by needle disease, commonly referred to as Brown Spot Needle Blight (BSNB). This has impacted large areas of pine plantations, and while the short- and long-term impacts are still being studied, it is thought to at least be causing growth reductions, and in several cases, widespread mortality has been reported. The first visual signs are browning needles, which occur at the bottom of the crown first and progress upwards. This study seeks to leverage remotely sensed data and derived image indices to assess the possibility of detecting and tracking foliar changes using a time series of image indices in a pine forest impacted by BSNB. The image indices calculated were used to track growing-season changes, which are found to decrease as the needle disease impacted the forest. This method could be enhanced on monthly or greater time scales to provide forest managers with a means of early detection that would allow them to employ measures to mitigate spread.