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The work evaluates multi- and hyperspectral sensors and their fit-for-purpose performance across VNIR, SWIR, and selected TIR coverage, linking spectral resolution to mineral- and lithology-relevant signals. It outlines spaceborne data processing levels, from radiance and atmospheric correction to geocoding and reflectance products, and describes workflows for pre-processing large tile sets. Mineral abundance indices and active mineral species/groups derived from spectral fitting are discussed, including integration concepts using ML and ab initio methods.",{"@graph":69,"@context":122},[70,84,105],{"@type":71,"itemListElement":72},"BreadcrumbList",[73,77,79,82],{"item":74,"name":75,"@type":76,"position":8},"https://docshare.wps.com","Home","ListItem",{"item":78,"name":9,"@type":76,"position":14},"https://docshare.wps.com/document/",{"item":80,"name":40,"@type":76,"position":81},"https://docshare.wps.com/document/research-report/",3,{"item":83,"name":65,"@type":76,"position":19},"https://docshare.wps.com/document/towards-mapping-the-australian-continent-with-the-next-generation-of-hyperspectral-satellite-imagery-igarss-paper-3436/267450/",{"url":83,"name":65,"@type":85,"image":86,"author":91,"headline":65,"publisher":94,"fileFormat":97,"inLanguage":63,"description":67,"dateModified":98,"datePublished":99,"encodingFormat":97,"isAccessibleForFree":100,"interactionStatistic":101},"DigitalDocument",{"url":87,"@type":88,"width":89,"height":90},"https://docshare.wps.com/thumbnails/towards-mapping-the-australian-continent-with-the-next-generation-of-hyperspectral-satellite-imagery-igarss-paper-3436/267450.png","ImageObject",300,407,{"name":92,"@type":93},"Melati","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-10-23","2026-09-14",true,{"@type":102,"interactionType":103,"userInteractionCount":52},"InteractionCounter",{"@type":104},"ViewAction",{"@type":106,"mainEntity":107},"FAQPage",[108,114,118],{"name":109,"@type":110,"acceptedAnswer":111},"Which hyperspectral satellites and missions are considered for mapping Australia?","Question",{"text":112,"@type":113},"The document lists several hyperspectral/ multispectral sources including DESIS/EMIT, ASTER, PRISMA/EnMap, HyMap, WorldView-3, Landsat 8, and Sentinel-2A, along with their spectral coverage and resolutions.","Answer",{"name":115,"@type":110,"acceptedAnswer":116},"How do the document’s processing levels relate to mineral mapping products?",{"text":117,"@type":113},"It describes mission processing stages such as at-sensor radiance, atmospherically corrected surface reflectance, and geocoded products, which then enable mineralogy estimation through spectral fitting and aggregation into mineral composition with uncertainty and quality flags.",{"name":119,"@type":110,"acceptedAnswer":120},"What role do mineral abundance indices play in the results?",{"text":121,"@type":113},"The document highlights abundance indices such as ferric oxide and silica indices derived from hyperspectral products, used to support continental-scale mineral mapping outcomes.","https://schema.org",{"og:url":83,"og:type":124,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":126,"canonical":83},"index,follow",{"doc_id":128,"site_id":62},267450,1790002798,{"code":4,"msg":5,"data":131},{"doc_id":128,"user_id":132,"nickname":92,"user_avatar":133,"doc_module":4,"category_id":39,"category_name":40,"doc_title":65,"doc_description":67,"doc_content":134,"file_id":135,"file_url":136,"file_type":137,"file_size":138,"view_count":52,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":139,"language":140,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":141,"faqs":142,"seo_title":143,"seo_description":67,"update_tm":144,"read_time":36,"preview_page_count":4},962085570644,"https://ap-avatar.wpscdn.com/davatar_994ba38a5ba835b3df7d355c54d3ed8d","Towards mapping the Australian continent with the next generation of hyperspectral satellite imagery  \nCarsten Laukamp, A. Jo Miles, Morgan Williams, Ian C. Lau, Shane Mule, Heta M. Lampinen, Alex Hunt, Sam Bradley, Anusuriya Devaraju, Cindy Ong, Mike Caccetta  \nCSIRO Mineral Resources  \nAugust 2025  \nAustralia’s National Science Agency  \nInternational Space Station  \nDESIS EMIT  \nASTER  \nPRISMA EnMap  \nEarth Observation Applications for the Mineral Resources Sector  \n• Developing spectral sensing solutions to address mineral resources industry challenges  \n• Case studies and collaborations with industry, academia and government bodies  \nAreas of research:  \n• Evaluating currently available remote and proximal sensors whether they are fit for purpose  \n• Adviser for geoscience-tuned optical sensors  \n• Mineral physiochemistry and spectral reference libraries  \n• Data integration using ML and ab initio methods  \n• Education & training on best practice 2 |  \nContinental ASTER-derived mineral maps  \nFerric oxide abundance index  \nRTI International impact assessment 2025:  \nBCR @ 363  \n(median estimate)  \nFalse colour RGB, ASTER tile centres (red), Hyperion (yellow)  \nCaccetta et al. (2013), Cudahy et al. (2012, 2016)  \n3 |  \nSilica abundance index  \n Active wavelength regions & spectral resolution  \nQuartz-Alunite Epithermal systems, modified after Tosdal et al. (2009)  \nproximal  \noxidised/ advanced argillic  \nadvanced argillic  \nphyllic  \npropylitic  \ndistal  \nNVCL drill core  \nHyMap  \n[http://www.auscope.org.au/auscope-grid/](http://www.auscope.org.au/auscope-grid/)  \n Multi-/hyperspectral satellite sensors ‘25  \nSpectra l resolution [ bands, wv l coverage]  \nEMIT/Tanager: VNIR/SWIR: 286 B @ 60/30 m, TIR: none  \nPRISMA/EnMap: VNIR: 66/89 B @ 30 m, SWIR: 173/155 B @ 30 m, TIR: none  \nHyMap:  \nVNIR/SWIR: 128 B @ 1-30 m, TIR: none  \nVNIR-SWIR-active mineral species, mineral chemistry  \nASTER:  \nVNIR: 3+1 B @ 15 m, SWIR: 6 B @ 30 m, TIR: 5 B @ 90 m  \nWorldview3: VNIR: 8 B @ 1.24 m, SWIR: 8 B @ 7.5 m, TIR: none  \nVNIR-SWIR-(TIR)-active mineral groups  \nLandsat 8: VNIR: 6 B @ 30 m, SWIR: 2 B @ 30 m, TIR: 2 B @ 100 m  \nSentinel 2A:  \nVNIR: 10 B @ 10/30/60 m, SWIR: 2 B @ 20 m, TIR: none  \nsurface patterns  \nNote: atmospheric bands and panchromatic bands not mentioned  \n5 |  \n Spaceborne hyperspectral VNIR-SWIR sensors  \nPRISMA  \n(PRecursore IperSpettrale della Missione Applicativa)  \nItalian Space Agency (ASI)  \n• L1: at-sensor radiance  \n• L2b: at-surface radiance  \n• L2c: atmospherically corrected atsurface reflectance  \n• L2d: geocoded  \n[https://www.asi.it/en/earth](https://www.asi.it/en/earth)science/prisma/  \n6 |  \nEnMAP  \n(Environmental Mapping and Analysis Program)  \nGerman Aerospace Center/ GeoForschungsZentrum (DLR/GFZ)  \n• Level 1B: at-sensor radiance physical values  \n• Level 1C Processor orthorectification  \n• Level 2A: atmospherically corrected reflectance values for land and water areas (incl. several quality masks)  \n[https://www.enmap.org/](https://www.enmap.org/)  \nEMIT  \n(Earth Surface Mineral Dust Source Investigation)  \nNASA/JPL  \nLevel 1b  \nLevel 2a  \nLevel 2b  \nLevel 3  \nLevel 4  \nLevel 1a + geolocation and observation geometry information  \nSurface reflectance + correction for atmospheric effects  \nMineralogy from fitting reflectance spectra, screening for non-mineralogical components Mineral composition aggregated from L2b + uncertainties and quality flags  \nEarth System Model runs to address science objectives  \n[https://earth.jpl.nasa.gov/emit/](https://earth.jpl.nasa.gov/emit/)  \nData processing workflow  \n7 |  \nmineral maps pre-processing  \nEnMap (~12,200 tiles)  \nPRISMA (~7,200 tiles)  \n8 |  \nlow  high  \nlow  high  \nGreen vegetation masked","cbCaieLFOY32C3h8","https://ap.wps.com/l/cbCaieLFOY32C3h8","pdf",4212011,16,"English","# Sensor capabilities and mission products\n## Active wavelength regions, spectral resolution, and mineral relevance\n# Data processing workflows and product levels\n## Radiance, surface reflectance, geocoding, and mineral composition outputs\n# Mapping outputs and mineral indices","[{\"question\":\"Which hyperspectral satellites and missions are considered for mapping Australia?\",\"answer\":\"The document lists several hyperspectral/ multispectral sources including DESIS/EMIT, ASTER, PRISMA/EnMap, HyMap, WorldView-3, Landsat 8, and Sentinel-2A, along with their spectral coverage and resolutions.\"},{\"question\":\"How do the document’s processing levels relate to mineral mapping products?\",\"answer\":\"It describes mission processing stages such as at-sensor radiance, atmospherically corrected surface reflectance, and geocoded products, which then enable mineralogy estimation through spectral fitting and aggregation into mineral composition with uncertainty and quality flags.\"},{\"question\":\"What role do mineral abundance indices play in the results?\",\"answer\":\"The document highlights abundance indices such as ferric oxide and silica indices derived from hyperspectral products, used to support continental-scale mineral mapping outcomes.\"}]","Towards Mapping the Australian Continent with the Next Generation of Hyperspectral Satellite Imagery - IGARSS Paper 3436 | PDF",1789419014]