Evaluation of photo imaging methods for vegetation condition assessment

Apan, Armando ORCID: https://orcid.org/0000-0002-5412-8881 and Baral, Govinda and Dunwoody, Ernest and Richardson, Lucy and McDougall, Kevin ORCID: https://orcid.org/0000-0001-6088-1004 (2011) Evaluation of photo imaging methods for vegetation condition assessment. In: 2011 Surveying and Spatial Sciences Conference: Innovation in Action: Working Smarter (SSSC 2011), 21-25 Nov 2011, Wellington, New Zealand.

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Official URL: http://www.sssc2011.org/


The aim of this project was to assess the feasibility of a photo imaging approach in the assessment of vegetation condition attributes in comparison with the Queensland Department of Environment and Resource Management (QDERM) Vegetation Condition Assessment approach. The project applied both the QDERM BioCondition monitoring method and an alternative photo imaging analysis approach to the assessment of vegetation condition attributes on different regional ecosystems. The study focused on the comparability of results and the cost-effectiveness of the photo imaging approach in comparison to the standard BioCondition assessment method.

Six regional ecosystems (RE) sites, of varying structural complexity, were selected for this study. They contained a diverse range of different vegetation attributes. Each site was assessed using both approaches. A low-cost Canon PowerShot SX10 IS camera was used to collect the photographs. It is equipped with a 20x Optical Zoom lens with a focal length of 5.0-100mm that allows shooting a scene from wide-angle to telephoto. For the ground cover data collection, two vertical-down photographs were taken of each quadrat. To capture canopy cover, vertical-up photographs were taken at 5m intervals along the transect midline. A two pole photographic method was developed to estimate tree canopy height.

This study found that the use of photo imaging methods to measure most attributes of vegetation for the BioCondition approach is technically possible. However, their application for operational use in ecosystems with closed vegetation canopies is not feasible. The estimation of the vegetation condition variables is constrained, in various degrees, by several factors. The estimation of shrub species richness in grassland and open canopy forests are the only attributes that have potential for operational use. Canopy cover estimates from vertical-up photographs produced comparable Tree Cover Rank results compared to the manually based crown cover estimate method. The photographic technique also has good potential for estimating major classes of ground cover in quadrats. Canopy height can be estimated more easily by using a laser range finder than a photo imaging method. In the future, when the cost of data acquisition becomes less expensive, the suitability of a LiDAR system could be considered to quantify the desired vegetation attributes.

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Item Type: Conference or Workshop Item (Commonwealth Reporting Category E) (Paper)
Refereed: Yes
Item Status: Live Archive
Additional Information: This publication is copyright. It may be reproduced in whole or in part for the purposes of study, research, or review, but is subject to the inclusion of an acknowledgment of the source.
Faculty/School / Institute/Centre: Historic - Faculty of Engineering and Surveying - Department of Surveying and Land Information (Up to 30 Jun 2013)
Faculty/School / Institute/Centre: Historic - Faculty of Engineering and Surveying - Department of Surveying and Land Information (Up to 30 Jun 2013)
Date Deposited: 12 Apr 2012 00:08
Last Modified: 03 Dec 2014 04:03
Uncontrolled Keywords: photo imaging; BioCondition; vegetation assessment; low-cost camera
Fields of Research (2008): 07 Agricultural and Veterinary Sciences > 0701 Agriculture, Land and Farm Management > 070104 Agricultural Spatial Analysis and Modelling
09 Engineering > 0909 Geomatic Engineering > 090905 Photogrammetry and Remote Sensing
05 Environmental Sciences > 0502 Environmental Science and Management > 050206 Environmental Monitoring
Fields of Research (2020): 30 AGRICULTURAL, VETERINARY AND FOOD SCIENCES > 3002 Agriculture, land and farm management > 300206 Agricultural spatial analysis and modelling
40 ENGINEERING > 4013 Geomatic engineering > 401304 Photogrammetry and remote sensing
41 ENVIRONMENTAL SCIENCES > 4104 Environmental management > 410404 Environmental management
Socio-Economic Objectives (2008): D Environment > 96 Environment > 9605 Ecosystem Assessment and Management > 960501 Ecosystem Assessment and Management at Regional or Larger Scales
D Environment > 96 Environment > 9606 Environmental and Natural Resource Evaluation > 960602 Eco-Verification (excl. Environmental Lifecycle Assessment)
URI: http://eprints.usq.edu.au/id/eprint/21053

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