Dr Karin Reinke is a part-time Research Fellow in the School of Mathematical and Geospatial Sciences at RMIT University (GPO Box 2476V, Melbourne, Vic. 3001, Australia. Tel. +61 39925 9726. Fax +61 39663 2517. Email: email@example.com). Dr Simon Jones is an Associate Professor in the School of Mathematical and Geospatial Sciences at RMIT University (GPO Box 2476V, Melbourne, Vic. 3001, Australia. Email: firstname.lastname@example.org). This paper arises from an Australian Research Council funded project ‘Remote Sensing and Spatial Analysis of Native Vegetation Condition’ (LP0455316). It was also supported in part by the NSW Government's Environmental Trust.
Integrating vegetation field surveys with remotely sensed data
Article first published online: 11 MAY 2006
Ecological Management & Restoration
Volume 7, Issue Supplement s1, pages S18–S23, June 2006
How to Cite
Reinke, K. and Jones, S. (2006), Integrating vegetation field surveys with remotely sensed data. Ecological Management & Restoration, 7: S18–S23. doi: 10.1111/j.1442-8903.2006.00287.x
- Issue published online: 11 MAY 2006
- Article first published online: 11 MAY 2006
- data integration;
- data quality;
- field data;
- multiscale data;
- remote sensing
Summary This paper explores data compatibility issues arising from the assessment of remnant native vegetation condition using satellite remote sensing and field-based data. Space-borne passive remote sensing is increasingly used as a way of providing a total sample and synoptic overview of the spectral and spatial characteristics of native vegetation canopies at a regional scale. However, integrating field-collected data often not designed for integration with remotely sensed data can lead to data compatibility issues. Subsequent problems associated with the integration of unsuited datasets can contribute to data uncertainty and result in inconclusive findings. It is these types of problems (and potential solutions) that form the basis of this paper. In other words, how can field surveys be designed to support and improve compatibility with remotely sensed total surveys? Key criteria were identified for consideration when designing field-based surveys of native vegetation condition (and other similar applications) with the intent to incorporate remotely sensed data. The criteria include recommendations for the siting of plots, the need for reference location plots, the number of sample sites and plot size and distribution, within a study area. The difficulties associated with successfully integrating these data are illustrated using real examples taken from a study of the vegetation in the Little River Catchment, New South Wales, Australia.