Monitoring Forest Infestation and Fire Disturbance in the Southern Appalachian Using a Time Series Analysis of Landsat Imagery

Mahsa Khodaee,Scott M Robeson,Jihyun Kim,Conghe Song,Taehee Hwang,Steven P Norman

doi:10.3390/rs12152412

Abstract

The southern Appalachian forests have been threatened by several large-scale disturbances, such as wildfire and infestation, which alter the forest ecosystem structures and functions. Hemlock Woolly Adelgid (Adelges tsugae Annand, HWA) is a non-native pest that causes widespread foliar damage and eventual mortality, resulting in irreversible tree decline in eastern (Tsuga canadensis) and Carolina (T. caroliniana) hemlocks throughout the eastern United States. It is important to monitor the extent and severity of these disturbances over space and time to better understand their implications in the biogeochemical cycles of forest landscapes. Using all available Landsat images, we investigate and compare the performance of Tasseled Cap Transformation (TCT)-based indices, Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), and Disturbance Index (DI) in capturing the spectral-temporal trajectory of both abrupt and gradual forest disturbances (e.g., fire and hemlock decline). For each Landsat pixel, the temporal trajectories of these indices were fitted into a time series model, separating the inter-annual disturbance patterns (low frequency) and seasonal phenology (high frequency) signals. We estimated the temporal dynamics of disturbances based on the residuals between the observed and predicted values of the model, investigated the performance of all the indices in capturing the hemlock decline intensity, and further validated the results with the number of individual dead hemlocks identified from high-resolution aerial images. Our results suggested that the overall performance of NDVI, followed by TCT wetness, was most accurate in detecting both the disturbance timing and hemlock decline intensity, explaining over 90% of the variability in the number of dead hemlocks. Despite the overall good performance of TCT wetness in characterizing the disturbance regime, our analysis showed that this index has some limitations in characterizing disturbances due to its recovery patterns following infestation.

Highlights

Over the last century, due to climate change and human activities the eastern North American forests have been affected by a number of large-scale disturbances, including wildfires, insect infestation, frequent droughts, and human-induced deforestation [1,2,3]
We investigated the performance of eight spectral indices—including three Tasseled Cap Transformation (TCT) indices, two TCT ratio indices, Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI) [74], and Disturbance Index (DI) trajectories (Table 1)—in monitoring the spectral-temporal patterns of forest disturbances
We examined the capability of eight spectral indices to capture the spectral and temporal dynamics of fire and infestation disturbances in the southern Appalachian forest using all available Landsat images

Summary

Introduction

Due to climate change and human activities the eastern North American forests have been affected by a number of large-scale disturbances, including wildfires, insect infestation, frequent droughts, and human-induced deforestation [1,2,3]. Non-native pests and wildfires have been reported as two major forest disturbance agents in the southern Appalachian. Hemlock Woolly Adelgid (Adelges tsugae Annand, HWA) is a non-native insect that causes widespread foliar damage and potentially complete mortality [6,7] in eastern (Tsuga canadensis) hemlock and Carolina hemlock (Tsuga caroliniana) (hereafter, “hemlocks” refers to both species). Due to the lack of natural controls such as predator insects and lethal cold temperature [10,17], complete hemlock mortality usually occurs over 4 to 6 years after the initial infestation in this region [12,18,19]

Objectives

Methods

Findings

Discussion

Conclusion