Predicting Levels of Crude Protein, Digestibility, Lignin and Cellulose in Temperate Pastures Using Hyperspectral Image Data

Hyperspectral sensors provide the potential for direct estimation of pasture feed quality attributes. However, remote sensing retrieval of digestibility and fibre (lignin and cellulose) content of vegetation has proven to be challenging since tissue optical properties may not be propagated to the canopy level in mixed cover types. In this study, partial least squares regression on spectra from HyMap and Hyperion imagery were used to construct predictive models for estimation of crude protein, digestibility, lignin and cellulose concentration in temperate pastures. HyMap and Hyperion imagery and field spectra were collected over four pasture sites in southern Victoria, Australia. Co-incident field samples were analyzed with wet chemistry methods for crude protein, lignin and cellulose concentration, and digestibility was calculated from fiber determinations. Spectral data were subset based on sites and time of year of collection. Reflectance spectra were extracted from the hyperspectral imagery and collated for analysis. Six different transformations including derivatives and continuum removal were applied to the spectra to enhance absorption features sensitive to the quality attributes. The transformed reflectance spectra were then subjected to partial least squares regression, with full cross-validation “leave-one-out” technique, against the quality attributes to assess effects of the spectral transformations and post-atmospheric smoothing techniques to construct predictive models. Model performance between spectrometers, subsets and attributes were assessed using a coefficient of variation (CV), —the interquantile (IQ) range of the attribute values divided by the root mean square error of prediction (RMSEP) from the models. The predictive models with the highest CVs were obtained for digestibility for all spectra types, with HyMap the highest. However, models with slightly lower CVs were obtained for crude protein, lignin and cellulose. The spectral regions for diagnostic wavelengths fell within the chlorophyll well, red edge, and 2000-2300 nm ligno-cellulose-protein regions, with some wavelengths selected between the 1600 and 1800 nm region sensitive to nitrogen, protein, lignin and cellulose. The digestibility models with the highest CV’s had confidence intervals corresponding to ±5% digestibility, which constitutes approximately 30% of the measured range. The cellulose and lignin models with the highest CV’s also had similar confidence intervals but the slopes of the prediction lines were substantially less than 1:1 indicating reduced sensitivity. The predictive relationships established here could be applied to categorizing pasture quality into range classes and to determine whether pastures are above or below for example threshold values for livestock productivity benchmarks.

Digital Earth 2020:towards the vision for the next decade

This position paper is the outcome of a brainstorming workshop organised by the International Society for Digital Earth(ISDE)in Beijing in March 2011.It argues that the vision of Digital Earth(DE)put forward by Vice-President Al Gore 13 years ago needs to be re-evaluated in the light of the many developments in the fields of information technology,data infrastructures and earth observation that have taken place since.The paper identifies the main policy,scientific and societal drivers for the development of DE and illustrates the multi-faceted nature of a new vision of DE grounding it with a few examples of potential applications.Because no single organisation can on its own develop all the aspects of DE,it is essential to develop a series of collaborations at the global level to turn the vision outlined in this paper into reality.

Advancing Digital Earth:beyond the next generation

The Digital Earth(DE)movement is gaining momentum.Much of it is unstructured.This paper examines a number of recent developments including those in health sensors(Wearable Absence,Q-Sensor,and Guardian Angels)and systems frameworks(Gelernter’s Mirror Worlds,Virtual Australia,and New Zealand).Consideration is given to the implications of DE for citizens and on citizen science,including those of ethics.A suite of principles to guide the development of DE is proposed.

The Australian approach to geospatial capabilities;positioning,earth observation,infrastructure and analytics:issues,trends and perspectives

This paper examines the current state of three of the key areas of geospatial science in Australia:positioning;earth observation(EO);and spatial infrastructures.The paper discusses the limitations and challenges that will shape the development of these three areas of geospatial science over the next decade and then profiles what each may look like in about 2026.Australia’s national positioning infrastructure plan is guiding the development of a nation-wide,sub decimeter,real-time,outdoor positioning capability based on multi-GNSS and in particular the emerging precise point positioning−real-time kinematic(PPP-RTK)capability.Additional positioning systems including the ground-based Locata system,location-based indoor systems,and beacons,among others are also discussed.The importance of the underpinning role of a next generation dynamic datum is considered.The development of Australia’s first EO strategy is described along with the key national needs of the products of remote sensing.The development of massive on-line multi-decadal geospatial imagery data stores and processing engines for co-registered stacks of continuous base-line satellite imagery are explored.Finally,perspectives on the evolution of a future spatial knowledge infrastructure(SKI)emerging from today’s traditional spatial data infrastructures(SDIs)are provided together with discussion of the growing importance of geospatial analytics for transforming whole supply chains.

Spatially enabling Australia-the next decade

A strategy for the development of the Australian spatial information industry called‘Spatially Enabling Australia’has recently been developed by the Cooperative Research Centre for Spatial Information.It comprises three fundamental research programs and an integrated applications program.Research Program 1,‘Positioning,’underpins a full framework of continuous operating reference stations to ultimately enable all of continental Australia to be capable of realtime precise positioning services based on global navigation satellite systems.Research Program 2,‘Automated Spatial Information Generation,’addresses complex processing of multiple remote sensing sources.Research Program 3,‘Spatial Infrastructures,’helps form the foundation for development of an Australian Spatial Marketplace that will make accessible vast amounts of government held data under a new licensing and access regime which supports combination with user-generated content from the mass market.The three core programs are integrated with Program 4,‘Applications,’to support users from the Health,Defense and Security,Energy and Utilities,Urban Development,and Agriculture-Natural Resources-Climate Change sectors.Program 4 drives outputs from the three core research programs in sector-specific deployments for high impact.This will see a rapid acceleration of the use and value adding of information products and services that utilize spatial information.There are considerable research and development challenges that must be met in order to achieve the strategic outcomes.