Mapping Multiple Insect Outbreaks across Large Regions Annually Using Landsat Time Series Data

Benjamin C Bright,Joel M Egan,Carl L Jorgensen,Andrew T Hudak,Arjan J.H Meddens

doi:10.3390/rs12101655

Benjamin C Bright, Joel M Egan + Show 3 more

Open Access

https://doi.org/10.3390/rs12101655

Copy DOI

Abstract

Forest insect outbreaks have caused and will continue to cause extensive tree mortality worldwide, affecting ecosystem services provided by forests. Remote sensing is an effective tool for detecting and mapping tree mortality caused by forest insect outbreaks. In this study, we map insect-caused tree mortality across three coniferous forests in the Western United States for the years 1984 to 2018. First, we mapped mortality at the tree level using field observations and high-resolution multispectral imagery collected in 2010, 2011, and 2018. Using these high-resolution maps of tree mortality as reference images, we then classified moderate-resolution Landsat imagery as disturbed or undisturbed and for disturbed pixels, predicted percent tree mortality with random forest (RF) models. The classification approach and RF models were then applied to time series of Landsat imagery generated with Google Earth Engine (GEE) to create annual maps of percent tree mortality. We separated disturbed from undisturbed forest with overall accuracies of 74% to 80%. Cross-validated RF models explained 61% to 68% of the variation in percent tree mortality within disturbed 30-m pixels. Landsat-derived maps of tree mortality were comparable to vector aerial survey data for a variety of insect agents, in terms of spatial patterns of mortality and annual estimates of total mortality area. However, low-level tree mortality was not always detected. We conclude that our methodology has the potential to generate reasonable estimates of annual tree mortality across large extents.

Highlights

Forest insect outbreaks have caused widespread tree mortality worldwide in recent years [1]
The classification approach and random forest (RF) models were applied to time series of Landsat imagery generated with Google Earth Engine (GEE) to create annual maps of percent tree mortality
We demonstrate a methodology for mapping insect-caused tree mortality annually across large extents using Landsat time series analysis

Summary

Introduction

Forest insect outbreaks have caused widespread tree mortality worldwide in recent years [1]. Extensive tree mortality caused by insect outbreaks affects crucial ecosystem services provided by forests such as water supply [6,7], carbon storage [8], wildlife habitat [9], and the availability of forest products [10]. Accurate estimates of the extent and severity of insect-caused tree mortality are important for determining to what degree ecosystem services have been affected [11,12,13]. Surveyors aboard fixed-wing aircraft estimate the spatial extent, insect mortality agent, tree species host, and severity of insect-caused tree damage. IDS data coverage might become less extensive in the future than recent years as costs increase and budgets decrease; the USDA Forest Health Protection program responsible for overseeing IDS is making efforts to incorporate satellite remote sensing in future forest health monitoring [19]

Objectives

Methods

Results

Discussion

Conclusion