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Comparing Methods for Quantitative Estimation of Rangeland Vegetation Cover* Qiming Zhou Department of Geography, Hong Kong Baptist University Kowloon Tong, Kowlong, Hong Kong Phone: (852) 23395048; Fax: (852) 23395990; E-mail:
[email protected] Marc Robson School of Geography, University of New South Wales Sydney, NSW 2052, Australia Phone: (02) 93854394; Fax: (02) 93137878; E-mail:
[email protected] Keywords: Remote sensing, assessment, vegetation cover.
INTRODUCTION Sustainable rangeland management practices require information on vegetation dynamics at the various land scales utilised by the pastoral industry. In general these can be categorised as the piosphere, paddock, property and regional levels, with the emphasis placed on the piosphere and paddock areas. It is at these basic levels that management decisions have the greatest impact on natural rangeland resources, namely soil and vegetation. It is therefore important to have a regular source of information relating to such factors as biomass and vegetation cover. This information, ideally quantitative, is necessary for the manager to maximise productivity while minimising soil erosion (Williamson and Eldridge, 1993). Satellite imagery is ideally suited to assess and monitor the condition of the rangelands at the desired scales, on a continuous and cost effective basis. However, the practical use of remote sensing for rangeland management has been limited by the low accuracy in extracting quantitative measurements, such as biomass and cover (Graetz, 1987). One of the main problems is that the existing models provide inadequate linkages between spectral characteristics recorded by remote sensors and relevant field variables. This is particularly a problem in Australian rangelands, where ‘mixed’ land cover types are common. In these areas, variations in land cover types occur at spatial resolutions below those of the available satellite sensors. Thus, an individual image pixel is a ‘mixel’; that is, its value (reflectance) is essentially an average of the response from the separate landscape components (bare soil, litter, grasses, shrubs, etc.), as well as their interaction (shadow), within the spatial size of the pixel. Accurate field estimation of vegetation cover is important for rangeland vegetation modelling. The reliability of some field techniques for cover estimation is questionable (Wilson et al, 1987). In addition to the sample size issues outlined by Curran and Williamson (1986), it was also argued that some field methods could produce significantly inconsistent results, making the subsequent remote sensing data processing a less-meaningful effort. This paper reports a research that seeks to accurately quantify vegetation cover in the semi-arid shrublands of Australia. Different techniques were tested to determine which were the most suitable. The resulting information, commonly called ground truth, can then be used in determining a model which relates the spectral reflectance recorded by the remote sensor with the amount of vegetation in a scene. This can also be further processed into output such as forage and erosion risk maps which could be used to assist the management.
METHODOLOGY The study was undertaken at Fowlers Gap Arid Zone Research Station located in western New South Wales, Australia. The vegetation is a semi-arid rangeland community dominated by bladder saltbush (Atriplex vesicaria). Four square sample sites with sides of 100m were accurately surveyed. Each site was further sub-divided into four square sub-areas with sides of 50m. Four methods were used to estimate the cover of various landscape components, such as vegetation and bare soil, within the sub-areas. Required sample sizes were determined using the methods outlined in Curran and Williamson (1986). The line intercept method for measuring cover of herbaceous vegetation and shrubs was described by Canfield (1941) for use in rangelands. This method involves using a measuring tape to record the measured proportions of landscape components (vegetation, soil, and rock) which intercept it. In this study, five randomly located, 50m transects for each sub-area. The wheel point technique (Tidmarsh and Havenga, 1955) utilises a multi spoked wheel. The cover type intercepted by a particular spoke(s) is recorded at set intervals. Percent cover is estimated by dividing “hits” for a particular cover type by total points taken. Seven randomly located, 50m transects were
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In People and Rangelands: Building the Future, Eldridge, D. and Freudenberger, D. (eds.), VI International Rangeland Congress, Inc., Aitkenvale, Australia: 750-752.
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used for the study. These two techniques are the most frequently cited in the literature for cover type estimation in rangeland environments. Two techniques utilising remotely sensed imagery were also applied. The first, similar to that proposed by Wimbush et al (1967), utilises a quadrat-based method to estimate cover components within the sub-areas. A digital camera was mounted atop a 5.2m pole with image acquisition controlled remotely by a single observer. Each image is of an area approximately 4m by 3m (Figure 1). The recorded image is then classified into land cover components. For each sub area 12 images were acquired. The second technique utilises a 35mm camera mounted in a remote control aircraft. Camera operation is also remotely controlled, with colour photographs acquired of each sub-area (Figure 2) and also the entire site. The negatives are scanned into digital format and classified. Sample size is not an issue for this technique as whole areas are recorded. For this reason, the processed imagery may be used to derive the accuracy of the other methods.
DISCUSSION Although this study has, at the time of writing, not been completed, there have been some encouraging results. In a preliminary studies using the line intercept, wheel point, low level digital imagery and a number of other techniques, it was discovered that all methods returned significantly different results (Zhou et al., 1998a; Zhou et al., 1998b). All methods were highly correlated, suggesting that any technique can be safely used in qualitative studies. The most consistent results were returned by the classification of digital imagery. However, in the absence of ‘truth’ no conclusions could be made concerning accuracy. It is hoped the imagery recorded by the RC plane camera will provide a baseline to determine accuracy. Other important issues in any ground truthing method are those of time and cost. The standard techniques take a great deal of time and effort, when compared to the classification of digital imagery. Digital images can be acquired and processed quickly at minimum cost. Problems remain however, to define a method to accurately classify the images into cover components. Encouraging results have been obtained using automated classifiers based on image context (Zhou and Sun, 1996).
CONCLUSION The link between satellite acquired data and ground data is vital for accurate interpretation of imagery. It is necessary to develop a cover estimation technique that is both precise and accurate so that models developed using remotely sensed imagery will not provide misleading results. In an environment characterised by a low projected foliage cover even small errors in the ground truth will result in ambiguous model output. Preliminary results have shown that the current popular ground truthing techniques (line intercept and wheel point) can produce significantly different results though they are highly correlated. This suggests the techniques are only suitable for qualitative studies. It is hoped the imagery acquired using the new techniques (e.g. the RC plane camera) will yield more reliable quantitative results relating to land cover components.
REFERENCES Canfield, R.H. (1941). Application of the line interception method in sampling range vegetation. J. For. 39:388394. Curran, P.J. and Williamson, H.D., 1986, Sample size for ground and remotely sensed data. Remote Sensing of Environment, 20, 31-41. Graetz, R.D. (1987). Satellite remote sensing of Australian rangelands. Remote Sens. Environ. 23:313-331. Tidmarsh, C.E.M. and Havenga, C.M. (1955). The wheel point method of survey and measurement of semi-arid grasslands and Karoo vegetation in South Africa. Bot. Survey of South Africa, Memoir No. 29. Williamson, H.D. and Eldridge, D.J. (1993). Pasture status in a semi-arid grassland. International Journal ofR emote Sensing, 14(13):2535-2546. Wilson, A.D., Abraham, N.A., Barratt, R., Choate, J., Green, D.R., Harland, R.J., Oxley, R.E. and Stanley, R.J., 1987, Evaluation of methods of assessing vegetation change in the semi-arid rangelands of southern Australia. Australian Rangeland Journal, 9, 5-13. Wimbush, D.J., Barrow, M.D. and Costin, A.B. (1967). Colour stereophotography for the measurement of vegetation. Ecology. 48:150-152. Zhou, Q., Robson. M. and Pilesjo (1998a). On the estimation of vegetation cover in Australian rangelands. Int. J. Remote Sensing, 19(9): 1815-1820 Zhou, Q., Robson, M. and Horn, G. (1998b). Comparison between the results from different ground vegetation cover estimation methods in a rangeland environment. Procs. 9th Australasian Photogrammetry and Remote Sensing Conf. 20-24 July, Sydney, Vol 1, Paper # 71.
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Zhou, Q and Sun, H (1996). Digital image classification using label relaxation for improved ground vegetation cover investigation. Procs. 8th Australasian Photogrammetry and Remote Sensing Conf. 25-29 March, Canberra, Vol 1. P122-131
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Figure 1. Image recorded by low altitude digital camera.
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Figure 2. Image acquired by camera on RC plane.
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