Supervising Scientist Report 195
Pfitzner K, Bartolo R, Carr G, Esparon A & Bollhöfer A
Department of Sustainability, Environment, Water, Population and Communities, 2011
- SSR195 - Standards for reflectance spectral measurement of temporal vegetation plots (PDF - 4,743 KB) | (Word - 22,487 KB)
- Part 1 - Preliminary pages including Contents, Executive Summary and Introduction (PDF - 567 KB) | (Word - 132 KB)
- Part 2 - Literature review and research context (PDF - 1 MB) | (Word - 4.4 MB)
- Part 3 - Plant species and sites (PDF - 1.7 MB) | (Word - 2.1 MB)
- Part 4 - Factors affecting spectral reflectance measurements (PDF - 1.2 MB) | (Word - 1.7 MB)
- Part 5 - Reflectance spectra and metadata: A database approach (PDF - 568 KB) | (Word - 1 MB)
- References (PDF - 201 KB) | (Word - 55 KB)
- Appendix A - SSD's standards for collecting field reflectance spectra (PDF - 541 KB) | (Word - 385 KB)
- Appendix B - Standards for collecting laboratory measurements (PDF - 2.8 MB) | (Word - 14.6 MB)
The collection of ground-based radiance, irradiance and reflectance spectra is a critical and common exercise for many environmental applications. The resulting measurements need to be accurate and precise representations of the target condition. There are many factors that can affect the spectral response obtained. Some of these factors are dependent on the experimental design. The environmental conditions, as well as the response of the spectrometer and reference panel used, may also influence the spectral measurements.
However, there are no national or international standards for the collection of in situ spectral data. While many field spectral campaigns may be undertaken, the effort expended in ground-based spectral collection is often only applicable to a single point and time. This is because few samples are acquired, accurate metadata are not recorded, the data are not stored in a manner that is easily retrievable, the method of data collection is not described and the data represent targets whose spectral response varies spatially and temporally.
In order to gain quality reference spectra of objects of interest, it is vital that careful consideration be given to the way in which spectral data are obtained. The sample size and times series of spectra must be appropriate. Importantly, metadata describing what was measured, how the measurement was taken and what the conditions were like during spectral measurement must accompany the spectral data. Factors that affect spectral measurements, including environmental factors, must be documented so that any external spectral influences can be accounted for. Photographic records can be a useful record of the type and condition of the target measured, the way in which the target was measured and the environmental conditions at the time of measurement. Whilst spectral data can be acquired quickly in the field, the acquisition and recording of spectral metadata does increase the time required for the field campaign. However, the increase in usefulness of fully described spectral data far outweighs the small additional investment in time required for metadata descriptions of associated spectra.
This report focuses on the standards for reflectance spectral measurement developed by the Supervising Scientist Division (SSD). The standards described here relate specifically to the Spectral Database Project and, in particular, standards for measuring terrestrial vegetative ground covers. The Spectral Database Project aims to provide a database of ‘reference’ spectral signatures over the 400–2500 nm range, pertinent to the study of cover and condition of minesites and surrounding country. Vegetative ground covers, shrubs and trees, soils and minerals, mine related features and built-up features will be incorporated into the database. The ground cover component aims to investigate the use of remotely sensed data to discriminate ground cover plant species using spectral data acquired by in situ spectrometry. To do this, dense and homogenous plots of key ground cover species pertinent to the success of minesite rehabilitation, including native and weedy grasses, herbs, vines and sedges, were established. The spectra of these species were measured over time at fortnightly intervals. The spectral data were accompanied by metadata descriptions and photographic records, using the methods described in this report.
This work was undertaken because management of both operating and rehabilitated minesites requires comprehensive information on species distribution and composition. Traditional ground-based surveys for floristic mapping involve time-consuming fieldwork that is often very stressful for workers in the tropical environment. Remote sensing has the potential to greatly reduce the requirement of ground-based surveys for floristic mapping. Broad band remote sensing sensors that have historically been used extensively for mapping of plant communities vii are, however, not sufficiently sensitive to allow discrimination of individual plant species. Relatively recent advances, particularly with respect to hyperspectral and very high spatial resolution sensors, offer the potential for application to the mine environment. The data obtained with the spectral database project will show whether or not there is potential for fine-spectral resolution remote sensing products to map vegetation cover and condition based on spectral signatures at scales appropriate to the mine environment. An evaluation of the most suitable wavelengths for spectral separation of cover species may identify specific spectral features that provide the best separation. These data can be resampled to indicate whether or not current multispectral systems can resolve important features for vegetation land cover mapping and condition monitoring in the mine environment.
The standards described here were developed to provide a consistent and repeatable method for recording spectra that minimises the influence of extraneous factors in spectral reflectance, radiance and irradiance measurements. The standards should be used to routinely obtain accurate and precise spectral measurements. A literature review of the factors affecting in situ spectral measurements was undertaken to define what equipment needed to be calibrated, what features needed to be characterised, how the equipment should be calibrated, how the features should be characterised and how the required measurement accuracy could be obtained. The report identifies the key parameters that determine the accuracy and uncertainty of spectral measurements systems and the resultant measured data from them. The method considers the factors affecting spectral data (outlined in Pfitzner et al 2005) and provides standards to collect time series spectra of vegetation that maximise the spectral response of the end member itself (Pfitzner & Carr 2006, Pfitzner et al 2006). A detailed description of the measurement process developed to collect reference spectra and ancillary metadata is then given.
This report details the scientific and operational requirements needed for the SSD Spectral Database Project. The SSD Spectral Measurement Database has been developed to take into account: spectrometer metadata and performance data of the standard Spectralon® panels (including temporal laboratory Hg/Ar, Mylar panel and Spectralon® spectra and associated metadata); images of the target at nadir, scaled set-up, horizon photographs and hemispherical photographs; subject information (classification, condition, appearance, physical state); subject background (scene background information similar to subject data); measurement information (instrument mode, date, local time, data collector(s), fore optics, number of integrations, reference material, height of measurement from target and ground, viewing and illumination geometry); environmental conditions (general site description, specific site location, geophysical location, sun azimuth and altitude, ambient temperature, relative humidity, wind speed and direction, weather instrument used and sky conditions); and, of course, reflectance spectrum and averaged reflectance data. This information is stored and available for data retrieval through the SSD Spectral Database. The standards are transferable to other researchers and applications. The only difference required may be that of the fore optic height and target field-of-view.
It is envisaged that this report provides not only a reference manual for spectral measurements but will also play a key role in enabling data comparisons by ensuring the quality, consistency and portability of spectral signature measurements. Apart from improved measurement quality (compared with most ad hoc spectral campaigns), the design and implementation of these spectral standards will also limit lost time due to poor measurements, enable the measurements and associated uncertainties to be independent of the technician undertaking the measurements, provide confidence that the operating equipment is performing as expected, and accelerate the training of new staff members.
Importantly, the standards facilitate measurement comparisons and improved measurement accuracy through identification and reduction of primary sources of uncertainty. It is only once this level of rigor is applied to spectral measurements that ground-based spectral feasibility studies will advance the use of spectral remote sensing beyond the short-term project specific research realm and into practical cost effective tools for long-term operational management. The data compiled from this project form a knowledge base of spectral information suitable for data sharing, particularly with respect to remote sensing feasibility studies. The data collected to date will result in a knowledge base far greater than that ever obtained for vegetation spectra with respect to the range of species sampled, the frequency of sampling, duration of sampling, and method and metadata documentation.
Further protocols on the analysis of these data will follow this report and will document any change in spectral pattern for a given species, the regions of the spectrum that provide the richest information for species discrimination, the possibility to discriminate species at a particular point in time and over time in the hyperspectral feature space, any optimum phenological stage to enhance the spectral separability of species and provide the most appropriate processing techniques. Also, further reports will detail other aspects of the project such as soil spectral measurements made in the laboratory.