Detecting change in vegetation condition using high resolution digital multispectral imagery

Bradley Evans; Tom J. Lyons; Paul A. Barber; Christine Stone; Giles Hardy

Detecting change in vegetation condition using high resolution digital multispectral imagery

Bradley Evans^*, Tom J. Lyons, Paul A. Barber, Christine Stone, Giles Hardy

^*Corresponding author for this work

Department of Biological Sciences

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › peer-review

1 Citation (Scopus)

Abstract

Remote sensing of vegetation condition using high resolution digital multispectral imagery (DMSI) is an option for land managers interested in quantifying the distribution and extent of dieback in native forest. Crown condition is assessed as reference to the physical structure and foliage (i.e. density, transparency, extent and in-crown distribution) of a tree crown. At 20 sites in the Yalgorup National Park, Western Australia, a total of 80 (Eucalyptus gomphecephala) crowns are assessed both in-situ and using 2 acquisitions (2008 and 2010) of airborne DMSI. Each tree was assessed using four crown-condition indices: Crown Density, Foliage transparency, and the Crown Dieback Ratio and Epicormic Index. DMSI data is trained against canopy condition assessment data from 2008, crown condition is predicted using only spectral data. Comparison of DMSI derived Normalized Difference Vegetation Index (NDVI), Soil Adjusted Vegetation Index (SAVI) and a novel Red Edge Extrema Index (REEI) suggests the REEI is more suited to classification applications of this type.

Original language	English
Title of host publication	34th International Symposium on Remote Sensing of Environment - The GEOSS Era: Towards Operational Environmental Monitoring
Pages	1-5
Number of pages	5
Publication status	Published - 2011
Event	34th International Symposium on Remote Sensing of Environment - The GEOSS Era: Towards Operational Environmental Monitoring - Sydney, NSW, Australia Duration: 10 Apr 2011 → 15 Apr 2011

Other

Other	34th International Symposium on Remote Sensing of Environment - The GEOSS Era: Towards Operational Environmental Monitoring
Country	Australia
City	Sydney, NSW
Period	10/04/11 → 15/04/11

Keywords

Classification
Crown condition
Dieback
Eucalyptus gomphecephala

Access to Document

Link to publication in Scopus

Fingerprint Dive into the research topics of 'Detecting change in vegetation condition using high resolution digital multispectral imagery'. Together they form a unique fingerprint.

Cite this

@inproceedings{0358143ecebc425fa028d96c51f6f816,

title = "Detecting change in vegetation condition using high resolution digital multispectral imagery",

abstract = "Remote sensing of vegetation condition using high resolution digital multispectral imagery (DMSI) is an option for land managers interested in quantifying the distribution and extent of dieback in native forest. Crown condition is assessed as reference to the physical structure and foliage (i.e. density, transparency, extent and in-crown distribution) of a tree crown. At 20 sites in the Yalgorup National Park, Western Australia, a total of 80 (Eucalyptus gomphecephala) crowns are assessed both in-situ and using 2 acquisitions (2008 and 2010) of airborne DMSI. Each tree was assessed using four crown-condition indices: Crown Density, Foliage transparency, and the Crown Dieback Ratio and Epicormic Index. DMSI data is trained against canopy condition assessment data from 2008, crown condition is predicted using only spectral data. Comparison of DMSI derived Normalized Difference Vegetation Index (NDVI), Soil Adjusted Vegetation Index (SAVI) and a novel Red Edge Extrema Index (REEI) suggests the REEI is more suited to classification applications of this type.",

keywords = "Classification, Crown condition, Dieback, Eucalyptus gomphecephala",

author = "Bradley Evans and Lyons, {Tom J.} and Barber, {Paul A.} and Christine Stone and Giles Hardy",

year = "2011",

language = "English",

pages = "1--5",

booktitle = "34th International Symposium on Remote Sensing of Environment - The GEOSS Era: Towards Operational Environmental Monitoring",

note = "34th International Symposium on Remote Sensing of Environment - The GEOSS Era: Towards Operational Environmental Monitoring ; Conference date: 10-04-2011 Through 15-04-2011",

}

Evans, B, Lyons, TJ, Barber, PA, Stone, C & Hardy, G 2011, Detecting change in vegetation condition using high resolution digital multispectral imagery. in 34th International Symposium on Remote Sensing of Environment - The GEOSS Era: Towards Operational Environmental Monitoring. pp. 1-5, 34th International Symposium on Remote Sensing of Environment - The GEOSS Era: Towards Operational Environmental Monitoring, Sydney, NSW, Australia, 10/04/11.

Detecting change in vegetation condition using high resolution digital multispectral imagery. / Evans, Bradley; Lyons, Tom J.; Barber, Paul A.; Stone, Christine; Hardy, Giles.

34th International Symposium on Remote Sensing of Environment - The GEOSS Era: Towards Operational Environmental Monitoring. 2011. p. 1-5.

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › peer-review

TY - GEN

T1 - Detecting change in vegetation condition using high resolution digital multispectral imagery

AU - Evans, Bradley

AU - Lyons, Tom J.

AU - Barber, Paul A.

AU - Stone, Christine

AU - Hardy, Giles

PY - 2011

Y1 - 2011

N2 - Remote sensing of vegetation condition using high resolution digital multispectral imagery (DMSI) is an option for land managers interested in quantifying the distribution and extent of dieback in native forest. Crown condition is assessed as reference to the physical structure and foliage (i.e. density, transparency, extent and in-crown distribution) of a tree crown. At 20 sites in the Yalgorup National Park, Western Australia, a total of 80 (Eucalyptus gomphecephala) crowns are assessed both in-situ and using 2 acquisitions (2008 and 2010) of airborne DMSI. Each tree was assessed using four crown-condition indices: Crown Density, Foliage transparency, and the Crown Dieback Ratio and Epicormic Index. DMSI data is trained against canopy condition assessment data from 2008, crown condition is predicted using only spectral data. Comparison of DMSI derived Normalized Difference Vegetation Index (NDVI), Soil Adjusted Vegetation Index (SAVI) and a novel Red Edge Extrema Index (REEI) suggests the REEI is more suited to classification applications of this type.

AB - Remote sensing of vegetation condition using high resolution digital multispectral imagery (DMSI) is an option for land managers interested in quantifying the distribution and extent of dieback in native forest. Crown condition is assessed as reference to the physical structure and foliage (i.e. density, transparency, extent and in-crown distribution) of a tree crown. At 20 sites in the Yalgorup National Park, Western Australia, a total of 80 (Eucalyptus gomphecephala) crowns are assessed both in-situ and using 2 acquisitions (2008 and 2010) of airborne DMSI. Each tree was assessed using four crown-condition indices: Crown Density, Foliage transparency, and the Crown Dieback Ratio and Epicormic Index. DMSI data is trained against canopy condition assessment data from 2008, crown condition is predicted using only spectral data. Comparison of DMSI derived Normalized Difference Vegetation Index (NDVI), Soil Adjusted Vegetation Index (SAVI) and a novel Red Edge Extrema Index (REEI) suggests the REEI is more suited to classification applications of this type.

KW - Classification

KW - Crown condition

KW - Dieback

KW - Eucalyptus gomphecephala

UR - http://www.scopus.com/inward/record.url?scp=84879752336&partnerID=8YFLogxK

M3 - Conference proceeding contribution

AN - SCOPUS:84879752336

SP - 1

EP - 5

BT - 34th International Symposium on Remote Sensing of Environment - The GEOSS Era: Towards Operational Environmental Monitoring

T2 - 34th International Symposium on Remote Sensing of Environment - The GEOSS Era: Towards Operational Environmental Monitoring

Y2 - 10 April 2011 through 15 April 2011

ER -