## 1 Introduction  
The use of hyperspectral reflectance spectra (\"spectral data\") in the iron ore resources industry is well established and continues to be a valuable tool to aid orebody characterisation, mineral classification, and quantification [1; 2; 3; 4]. The use of spectral data for characterisation purposes is dependent on the wavelength region in which the reflectance spectra were collected. This has led to spectral region-specific metrics that are used to leverage the strength of each spectral region and, in many cases, is deposit specific [1; 5; 6; 7]. In the combined visible (VIS), near-infrared (NIR) and short-wave infrared (SWIR) between 350 and 2500 nm, the 1300-2500 nm spectral region has alteration mineral assemblages associated with hydrothermal base and precious metal deposits which can often be defined by the absorption features present [8; 9; 10; 11; 12; 13], while absorptions in the VIS and NIR between 350 and 1300 nm can be used to infer iron-bearing minerals [2; 14; 15]. At much longer wavelengths in the thermal infrared (TIR) spectral region, absorptions between 6000 and 14,000 nm are used to assist in mineral species differentiation due to overlapping and confounding absorptions, such as carbonates and chlorites, in the SWIR as well as the identification of minerals that do not exhibit any identifiable absorptions in the VIS, NIR and SWIR such as quartz and feldspars [13; 16; 17]. The two major types of iron ore deposits in the Pilbara Province of Western Australia are banded iron formation (BIF)-hosted iron ore deposits and bedded iron deposits BID, respectively, named martite-goethite and martite-microplaty hematite and channel iron deposits (CID), as described in [18]. Ochreous goethite has been defined as yellow in colour and powdery to friable, vitreous goethite is dark red-brown to black in colour, with a relative hardness ranging from medium to hard; brown goethite is light to dark brown in colour, with a medium to hard hardness [19]. In a typical goethite, the Moh hardness scale has a range of 5-5.5 but the yellow ochreous goethite is much lower due to its porosity. The collection of spectral data from exploration samples or laboratory prepared samples is fast and cost-effective and can provide a greater insight into the iron oxide mineral and mineral assemblages of iron ore bodies. The spectral data might be collected from rotary core (RC) chip samples collected via a diamond core scanned with the HyLoggerTM [20; 21; 22] or Corescan HSI [23], or from samples prepared as pulps prior to geochemical assay using laboratory spectrometers. Processing the spectral data with a suite of spectral metrics allows a fast overview to be produced, which can aid further exploration decisions, free up field geologists, and potentially assist in ongoing mining operations, for example, by informing material handling indices [24]. The interpretation of ore and waste mineral assemblages present in each iron ore-specific spectral dataset will, as previously noted, be dependent on the wavelength regions and instrument specifications available. Shale-containing clay minerals can be established via SWIR spectral metrics, chert and high-silica samples can be identified with TIR spectral metrics, while the VNIR can be used to establish the presence of hematite/magnetite and goethite. In the latter case, the crystal field absorption (CFA) \({}^{6}\)A\({}_{1}\)\(\rightarrow\)\({}^{4}\)T\({}_{1}\) at approximately 900 nm (F\({}_{900}\)) [25], shown in Figure 1, has been used to infer proportions of hematite/magnetite and goethite [5], vitreous and ochreous goethite discrimination and Fe content [1; 26]. The F\({}_{900}\) is of particular interest as it is a large and well-resolved absorption feature.