urban remote sensing: using nasa goddard's lidar, hyperspectral & thermal imager to map ash...

Rich Halletta, Jen Pontiusba , Bruce Cookc , Ryan P. Hanavand a USFS Northern Research Station, b University of Vermont ,

c NASA Goddard Space Flight Center, d USFS Forest Health Protection

Scanning/Profiling LiDAR

Urban Remote Sensing: Using NASA Goddard's LiDAR, Hyperspectral & Thermal Imager to map Ash and detect the

effects of emerald ash borer (EAB), Agrilus plannipenis, in Bowie, MD

First discovered in SE MI in 2002

Currently in 22 US states and 2 Canadian provinces

Larvae feed on all ash species (don’t discriminate between healthy or sick trees)

Emerald ash borer, Agrilus planipennis

Girdled Trap Trees Woodpecker “blonding”Purple Panel Traps

Current Detection Techniques

Hyperspectral remote sensing has been used to effectively assess ash decline associated with EAB (Hallett et al. 2008, Pontius et al. 2008)

The G-LiHT (PI Bruce Cook) imaging system provides a data fusion opportunity to increase accuracy and early detection of incipient EAB infestations.

First use of the G-LiHT sensor in an urban forest health application (summer 2012)

Introduction

Goddard’s LiDar, Hyperspectral and Thermal Airborne Imaging System

1. Off the shelf instrumentation2. Surface temperature

observations3. Downwelling irradiance

measurements4. Profiling and scanning LiDAR

instruments5. Eye-safe lasers at two

wavelengths (905, 1550 nm)6. Portability (~80lbs)7. Versatility (adaptable to many

platforms, low power8. Low operating costs (~$1/ha –

acquisition & processing)

Data Fusion – What is G-LiHT?

Data Fusion – What is G-LiHT?

Imagery collected for Bowie, MDJuly 2012

Goal: collect data from ~100 trees per AOI

Health Data – Species, DBH, Discoloration, Defoliation Class, % dieback, Vigor, Crown Class, Woodpecker evidence, Epicormic Branching

Chlorophyll Fluorescence – Hansatech PEA

Canopy Transparency – digital images

Spectrometer calibration – Handheld and tarp fly-over

Methods – Field Plots

Vigor – percent dieback on a scale of 1-5 (Millers et al. 1991)

1 = <10% dieback5 = dead tree

Discoloration – measured on a scale of 0-3

0 – no trace of discoloration

3 - >60% discoloration

Methods – Health Plots

Physiologically, a reduction in net photosynthesis is one of the earliest and most subtle signs of plant stress.

Photosynthetic capacity was directly measured as chlorophyll fluorescence (photosynthetic activity)

(Carter and Knapp 2001)

Methods – Photosynthetic Capacity

4 photos taken straight up capturing as much pure canopy as possible

Canopy Thinning – measured with digital photos

Consistent height and location

Processed as jpg’s and assessed with Gap Light Analyzer (GLA)

12 % 63 %

Automated process

Methods – Canopy Transparency

Results – Canopy Transparency

Uninfested - Healthy Infested – EAB confirmed

Putting it all together: Creating a stress index

Tree 36Stress Index -0.783

Tree 71Stress Index -.409

Tree 45Stress Index -0.191

Tree 77Stress Index 0.81

Tree 65Stress Index 1.3

Tree 75Stress Index -0.009

𝑋 (𝑧𝑃𝐼+𝑧𝐹𝑣𝐹𝑚+𝑧𝐷𝑖𝑒𝑏𝑎𝑐𝑘+𝑧𝑇𝑟𝑎𝑛𝑠𝑝𝑎𝑟𝑒𝑛𝑐𝑦+𝑧 𝐷𝑖𝑠𝑐𝑜𝑙𝑜𝑟 )

Tree Stress Index

Variable NotesPI Chlorophyll FluorscenceFvFm Chlorophyll FluorscenceTransparency Digital estimateDiscolor Visual estimateDieback Visual estimate

Early Signs

Later Signs

Pontius, J., & Hallett, R. (2014). Comprehensive methods for earlier detection and monitoring of forest decline. Forest Science, 60(2).

Field Validation Canopies

Ash species

Red MapleOak speciesNorway MapleHoney Locust

Field/Lawn

SycamoreCallery Pear

Silver Maple

Impervious

Results - Where are the ash trees?

Results - Where are the ash trees?

Overall accuracy of the 290 independent validation points resulted in 81% accuracy in distinguishing ash from non-ash polygons.

Sick ash trees don’t look like ash trees anymore!

Results – Identifying trees in decline

Visible Wavelengths

Healthy

Sick

Healthy Sick

Severe decline

Healthy

All Trees

AshTreesSevere decline

Healthy

Severe decline

Healthy

Ash Trees in Bowie

Thank You!Questions?