Satellite-based Phenology and Climate Anomaly Analysis in Evaluating the Response of Puerto Rico and the U.S. Virgin Islands Tropical Forests to the 2015-2016 drought.

Abstract:

Tropical forests include a majority of the world’s biodiversity. There is limited knowledge of how tropical forests will respond to the impacts of climate change and if the unique biodiversity of these forests will allow for a buffer against climate anomalies. By understanding both short- and long-term changes in tropical forest phenology concerning these climate anomalies, we can assess the ability of forests to recover from such events.

This research will utilize Landsat satellite data and ground-based Forest Inventory and Analysis data to investigate Puerto Rico and the U.S. Virgin Island’s tropical forests after the worst drought in the regions recorded history between May 2015 and November 2016. By using these two data sources in unison we can assess how pre-drought forest structure and diversity are related to the impact of the drought, how the climate anomalies caused by the drought affect Puerto Rico and the U.S. Virgin Islands’ tropical forest phenology, and if there is a significant difference in species distribution caused by the drought.

Extensive cloud masking processes on Landsat satellite imagery will take place to produced near cloud free composite images. These will be used to produce annual phenology curse. Forest Inventory and Analysis data will be used to quantify drought-related tree mortality and forest growth patterns. While comparing these to Landsat scale phenometrics through regression and spatial autoregressive models.

We expect to see significant changes in phenometrics and forest growth patterns. We also expect a decrease in overall forest health and substantial drought-related tree mortality.

Results will help develop an understanding of Puerto Rico and the U.S. Virgin Island’s tropical forests susceptibility to drought. Furthermore, this research will convey new techniques in the field of remote sensing and tropical forest ecology that will aid in monitoring global forest health.