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Hyperspectral Close-Range and Remote Sensing of Soils and Related Plant Associations Spectroscopic Applications in the Boreal Environment

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Hyperspectral Close-Range and Remote Sensing of Soils and Related Plant Associations Spectroscopic Applications in the Boreal Environment Hyperspectral close-range and remote sensing of soils and related plant associations Spectroscopic applications in the boreal environment Maarit Middleton mallikuva; kuva-alan koko voi vaihdella Academic Dissertation GEOLOGICAL SURVEY OF FINLAND Espoo 2014 HYPERSPECTRAL CLOSE-RANGE AND REMOTE SENSING OF SOILS AND RELATED PLANT ASSOCIATIONS Spectroscopic applications in the boreal environment by Maarit Middleton Geological Survey of Finland P.O. Box 77 FI-96101 Rovaniemi, Finland ACADEMIC DISSERTATION Doctoral dissertation for the degree of Doctor of Science in Technology to be presented with due permission of the School of Engineering for public examination and debate in Auditorium M1 at the Aalto University School of Engineering (Otakaari 1, Espoo, Finland) on the 26th of September 2014 at 12 noon. Unless otherwise indicated, the figures have been prepared by the author of the publication. Geological Survey of Finland Espoo 2014 Instructor: Doc. Raimo Sutinen Geological Survey of Finland Rovaniemi, Finland Department of Geosciences University of Oulu Oulu, Finland Supervisor: Prof. Henrik Haggrén Department of Real Estate, Planning and Geoinformatics Aalto University Espoo, Finland Reviewers: Dr. Angela Harris School of Environment, Education and Development University of Manchester Manchester, United Kingdom Prof. Alexander McBratney Department of Environmental Sciences University of Sydney Sydney, Australia Opponents: Assoc. Prof. John Carranza School of Earth and Environmental Sciences James Cook University Townsville, Australia Prof. Nicholas Coops Department of Forest Resources Management University of British Columbia Vancouver, Canada Front cover: Peatland site type classification at southern boreal study site in Keminmaa, Finland (pa- per IV). Mapping was based on fuzzy support vector machine classification of airborne HyMap data. Peatland class-specific probabilities are presented with RGB composition. Class ‘bog’ is represented as red, ‘sedge fen’ as green, and ‘eutrophic fen’ as blue. Prob- ability values are scaled with histogrammic equalization to emphasize spatial details. Pure RGB colors depict high probabilities. Normalized differential vegetation index (NDVI) was calculated for background. High NDVI values are illustrated as light shades of grey. Middleton, M. 2014. Hyperspectral close-range and remote sensing of soils and related plant associations. Spectroscopic applications in the boreal en- vironment. Geological Survey of Finland. 68 pages, 8 figures, 5 tables, with original articles (I−IV). Maarit Middleton Geological Survey of Finland, P.O. Box 77, FI-96101 Rovaniemi, Finland E-mail: [email protected] ISBN 978-952-217-281-5 (paperback) ISBN 978-952-217-282-2 (PDF version without articles) Layout: Elvi Turtiainen Oy Printing house: Juvenes Print – Suomen Yliopistopaino Oy – One of the primary resources upon which man directly depends for his existence is soil moisture. [...] This resource, among others, man now seeks to monitor from space, and towards this end he is applying some of the most sophisticated technology and management expertise. – Idso et al. (1975) To Kent, Sofia and Benjamin Aalto University, P.O. BOX 11000, 00076 AALTO www.aalto.fi Abstract Author Maarit Middleton Author Maarit Middleton Name of the doctoral dissertation Hyperspectal close-range and remote sensing of soils and relatedName ofplant the associations. doctoral dissertation Spectroscopic Hyperspectal applications close-range in the boreal and environment remote sensing of soils and Publisherrelated plant Geological associations. Survey Spectroscopic of Finland applications in the boreal environment UnitPublisher Department Geological of Real Survey Estate, of FinlandPlanning and Geoinformatics SUniteries Department Geological of Survey Real Estate, of Finland, Planning Academic and Geoinformatics Dissertation FieldSeries of Geologicalresearch SurveyRemote of sensing Finland, Academic Dissertation ManuscriptField of research submitted Remote 3 December sensing 2013 Date of the defence 26 September 2014 PermissionManuscript to submitted publish granted 3 December 29 January 2013 2014 Date of the defenceLanguage 26 September English 2014 ArticlePermission dissertatio to publishn (summary granted + original 29 January articles) 2014 .. .. Language English.. Article dissertation (summary + original articles) . Abstract AbstractHyperspectral close-range and remote sensing techniques have been available to the research communityHyperspectral since close-range the 1980's and but remote applications sensing techniqueshave focused have on been forestry available and landto the use. research The objective commu- ofnity the since study the was 1980’s to explore but applications relevant haveapplications focused ofon visible forestry and and short land wavelength use. The objective infrared of spectro the studys- copywas to (350 explore−2500 relevant nm) for applications detection ofof physicalvisible and and short chemical wavelength properties infrared of glacial spectroscopy till soils (350−2500and plant speciesnm) for communitiesdetection of physical related andto the chemical soil properties properties in ofthe glacial boreal till environment soils and plant of northernspecies communities Finland. relatedEmpirical to the single soil properties and multivariate in the boreal regression environment techniques of northern (MVR) Finland.were applied for predicting glacial tillEmpirical soil dielectric single permittivity and multivariate (Ɛ, i.e. regression soil moisture) techniques and till(MVR) element wereal applied concentrations for predicting from glacialclose- rangetill soil spectrometry. dielectric permittivity Predictive (ε, kerneli.e. soil andmoisture) neural and network till elemental based fuzzyconcentrations classification from approachesclose-range TM werespectrometry. applied forPredictive classification kernel andof data neural acquired network with based AISA fuzzy and classification HyMap airborne approaches imaging were appliedspec- trometers. Ordination techniques were used for revealing plant community structures and optimiz- for classification of data acquired with AISA and HyMapTM airborne imaging spectrometers. Ordina- ing the thematic class hierarchal level. tion techniques were used for revealing plant community structures and optimizing the thematic class The till soil Ɛ could be well predicted from VSWIR spectra with the exponential single-spectral variatehierarchal but level. also with MVR techniques. The most accurate results were gained with relevance vector machines.The till soilPrediction ε was well of predictedtill soil chemical from VSWIR element spectra concentrations with the exponential of Al, Ba, single-spectral Co, Cr, Cu, Fe, variate Mg, Mn, but Ni,also V, with and MVR Zn was techniques. also statistically The most valid. accurate Soil results moisture were based gained site with suitability relevance for vector Scots machines.pine (Pinus Pre- sylvestrisdiction of )till from soil imagingchemical spectroscopicelement concentrations data was ofmoderately Al, Ba, Co, successfulCr, Cu, Fe, asMg, the Mn, highest Ni, V, areaand Znunder was thealso receiver statistically operating valid. Soil characteristics moisture based curve site (AUC) suitability value for was Scots 0.741. pine Site (Pinus type sylvestrismapping) offrom aapa imaging peat- landsspectroscopic with support data was vector moderately machines successful was highly as the succe highestssful area with under AUC the values receiver 0.946 operating−0.999 character for bog,- sedgeistics curve fen, and (AUC) eutrophic value wasfen. 0.741. Site type mapping of aapa peatlands with support vector machines wasUnderstanding highly successful the withƐ-reflectance AUC values relationship 0.946−0.999 would for bog, be sedgeevident fen, when and eutrophic artificial fen. regeneration to ScotsUnderstanding pine, intolerant the ε-reflectance of wet soils, wasrelationship considered would on clearbe evident-cuts withwhen high artificial soil moisture regeneration variability. to Scots Thepine, site intolerant suitability of wet on soils, site isprepared considered forest on clear-cuts compartments with high could soil be moisture predicted variability. using exposedThe site soilsuit- pixels in high spatial resolution imagery but also with indirect imaging of soil moisture through ability on site prepared forest compartments could be predicted using exposed soil pixels in high spatial understory species patterns. The high success of the peatland site type mapping was attributed to optimizationresolution imagery of class but hierarchalalso with indirect levels withimaging a constrained of soil moisture ordination through based understory approach species which patterns. was usedThe tohigh test success the spectral of the andpeatland ecological site type class mappingseparabilit wasy priorattributed to classification. to optimization These of novelclass hierarchalapplica- tionslevels ofwith imaging a constrained spectroscopic ordination data based can readilyapproach be which applied was in used practice to test once the spectralcost-effective and ecological satellite basedclass separability data is available. prior to Furtherclassification. research These is required novel applications to make the of imagingclose-range spectroscopic spectroscopy data canoper reada-- tionalily be appliedfor quantification in practice onceof element cost-effective concentrations satellite tobased serve data forest is available. soil research Further and research
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