Ground cover monitoring for Australia: Sampling strategy and selection of ground cover control sites

[摘要] High frequency, spatially explicit ground cover information is required to improve wind and water erosion modelling and monitoring, and our understanding of the impact of climate variability and changing management practice on pasture condition, particularly in the rangelands. Ultimately, a national network of sensor independent reference sites is required to improve validation of land cover products derived from remotely sensed data and which are monitored using agreed standardised sampling approaches. •To meet these needs the Australian Government Department of Agriculture, Fisheries and Forestry has funded delivery of a validated remotely sensed time-series of fractional cover for Australia using MODIS satellite data based on the method of Guerschman et al. (2009). The fractional cover product will provide monthly ground cover data to better parameterise the CEMSYS (Shao et al. 2007) wind erosion model and the SedNet (Wilkinson et al. 2004) water erosion model.•The fractional cover dataset is derived from two indices which provide information on vegetation amount and colour. Plotting these indices against each other, the amounts of three cover components—for each satellite pixel—can be estimated, namely:–photosynthetic (green) vegetation cover–non-photosynthetic (brown) vegetation cover, and –bare soil.•Before it can be routinely used the fractional cover product needs to be validated. Validation will establish confidence in the approach and encourage operational use of the data products. The successful operational use of medium resolution data will help build a case to fund work based on sensors operating at higher spatial resolution. To date, only a qualitative analysis of algorithm retrieval and accuracy of the fractional cover product has been undertaken.•Defining the uncertainty of the cover fraction estimates requires quantitative validation of the fractional cover product. Users need to know whether the product (and version) is suitable for their purpose and/or region. Defining uncertainty enables: assessment of its impact as a data input into other models (e.g. CEMSYS and SedNet); informed decisions on the basis of the data itself and; ultimately improvement in the predictions through modifying the fractional cover algorithm by understanding the possible sources of the error.•A limited qualitative evaluation showed that the fractional cover algorithm works well in areas with high greenness, such as the intensive land use zone. This includes land covers such as cropping, woodlands and aquatic vegetation. It performs poorly for some soil types—gibber and to a certain extent red, black and bright soils—and low vegetation covers, particularly those typical of the rangelands. This lack of performance for these surfaces may reflect their absence from the area upon which the end-member dataspace was developed—the Northern Territory savanna. It could also be that differences in soil spectral reflectance may be influencing fractional cover estimation using the algorithm.•An Expert Workshop on Sampling Strategy and Selection of Ground Cover Control Sites was held at CSIRO Land and Water, Canberra on the 17-18 August 2010. The workshop brought together experts from federal and state agencies with the aim to: develop a statistically robust sampling strategy for ground cover validation sites; prioritise target areas for field measurement of fractional cover and; validate the fractional cover product. To implement the sampling strategy a national network of field sites will be established through collaboration with state agencies. This report elaborates on the main recommendations made at the workshop.

[发布日期] 2013-03-06 [发布机构] CSIRO

[学科分类] 地球科学(综合)