Multitemporal assessment of crop parameters using multisensorial flying platforms

UAV sensors suitable for precision farming (Sony NEX-5n RGB camera; Canon Powershot modified to infrared sensitivity; MCA6 Tetracam; UAV spectrometer) were compared over differently treated grassland. The high resolution infrared and RGB camera allows spatial analysis of vegetation cover while the UAV spectrometer enables detailed analysis of spectral reflectance at single points. The high spatial and six-band spectral resolution of the MCA6 combines the opportunities of spatial and spectral analysis, but requires huge calibration efforts to acquire reliable data. All investigated systems were able to provide useful information in different distinct research areas of interest in the spatial or spectral domain. The UAV spectrometer was further used to assess multiangular reflectance patterns of wheat. By flying the UAV in a hemispherical path and directing the spectrometer towards the center of this hemisphere, the system acts like a large goniometer. Other than ground based goniometers, this novel method allows huge diameters without any need for infrastructures on the ground. Our experimental results shows good agreement with models and other goniometers, proving the approach valid. UAVs are capable of providing airborne data with a high spatial and temporal resolution due to their flexible and easy use. This was demonstrated in a two year survey. A high resolution RGB camera was flown every week over experimental plots of barley. From the RGB imagery a time series of the barley development was created using the color values. From this analysis we could track differences in the growth of multiple seeding densities and identify events of plant development such as ear pushing. These results lead towards promising practical applications that could be used in breeding for the phenotyping of crop varieties or in the scope of precision farming. With the advent of high endurance UAVs such as airships and the development of better light weight sensors, an exciting future for remote sensing from UAV in agriculture is expected

Retrieval of aerosol optical thickness over snow and ice surfaces in the Arctic using Advanced Along Track Scanning Radiometer

Aerosols in the Arctic cause radiative forcing and a variety of climatic feedbacks, which affect climate of both local and global scales. In order to assess the state of the Arctic climate, information on the aerosol type and amount is needed. Harsh conditions and remoteness of the Arctic region result in very few ground based measurements of aerosol optical thickness. Remote sensing has the potential to provide the necessary temporal and spatial coverage. A non-trivial task of aerosol retrieval over a very bright surface is being solved within the thesis; the developed retrieval consists of cloud screening over snow and two types of aerosol retrieval over snow - in the visible and infrared spectral regions. A number of validation and case studies has been performed to assess the quality of the retrieval. The developed algorithm applies to the data of Advanced Along Track Scanning Radiometer and produces maps of aerosol optical thickness over snow and ice

Earth remote sensing with SMOS, Aquarius and SMAP missions

The first three of a series of new generation satellites operating at L-band microwave frequencies have been launch in the last decade. L-band is particularly sensitive to the presence of water content in the scene under observation, being considered the optimal bandwidth for measuring the Earth's global surface soil moisture (SM) over land and sea surface salinity (SSS) over oceans. Monitoring these two essential climate variables is needed to further improve our understanding of the Earth's water and energy cycles. Additionally, remote sensing at L-band has been proved useful for monitoring the stability in ice sheets and measuring sea ice thickness. The ESA's Soil Moisture and Ocean Salinity (SMOS, 2009-2017) is the first mission specifically launched to monitor SM and SSS. It carries on-board a novel synthetic aperture radiometer with multi-angular and full-polarization capabilities. NASA's Aquarius (2011-2015) was the second mission, devoted to SSS monitoring with a combined real aperture radiometer/scatterometer system that allows correcting for sea surface roughness. NASA's Soil Moisture Active Passive (SMAP, 2015-2018) is the second mission dedicated to measure SM. It carries on-board a real aperture full-polarimetric radiometer and a synthetic aperture radar (SAR) for enhanced spatial resolution and freeze/thaw detection. This Ph.D. Thesis is focused on analyzing the geophysical information that can be obtained from L-band SMOS, Aquarius and SMAP observations. The research activities are structured as follows: -Inter-comparison of radiometer brightness temperatures at selected targets. A novel methodology to measure the consistency between SMOS and Aquarius radiometric data over the entire dynamic range of observations (land, ice and ocean) is proposed. It allows detecting spatial/temporal differences or biases without latitudinal limitations neither cross-overs. This is a necessary step to combine observations from different instruments in a long term dataset for environmental, meteorological, hydrological or climatological studies. -Ice thickness effects on passive remote sensing of Antarctic continental ice. The relationship between Antarctic ice thickness spatial variations and changes detected by SMOS and Aquarius measurements is explored. The emissivity of Antarctica is analyzed to disentangle the role of the geophysical contributions (snow layers at different depths and subglacial lakes) to the observed signal. The stability of the L-band signal in the East Antarctic Plateau, calibration/validation site for microwave satellite missions, is assessed. -Microwave/optical synergy for multi-scale soil moisture sensing. The relationship of SM and land surface temperature (LST) dynamics is evaluated to better understand the fundamental SM-LST link through evapotranspiration and thermal inertia physical processes. A new approach to measure the critical soil moisture from time-series of spaceborne SM and LST is proposed. The synergistic use of SMOS SM and remotely sensed LST for refining SM disaggregation algorithms is also analyzed. -Comparison of passive and active microwave vegetation parameters. Recent research has shown that microwave vegetation opacity, sensitive to biomass and water content, and albedo, related to canopy structure, can be retrieved from passive L-band observations. The relationships between these two parameters and radar-derived vegetation descriptors have been explored using airborne observations from the SMAP Validation Experiment 2012 (SMAPVEX12). The obtained relations could allow for improved SM retrievals in active-passive systems, and also to estimate the vegetation properties at high resolution using SAR observations. The Ph.D. Thesis has been developed within the activities of the Barcelona Expert Centre (BEC). The presented results contribute to the use of L-band remote sensing in different scientific disciplines such as climate, cryosphere, hydrology and ecology.Els primers tres d'una sèrie de satèl·lits de nova generació funcionant a la banda L han sigut llançats a l'última dècada. La banda L es molt sensible a la presència d'aigua a l'escena observada, sent considerada òptima per mesurar la humitat del sòl (SM) i la salinitat del mar (SSS) de manera global a la superfície de la Terra. Monitoritzar aquestes dues variables climàtiques essencials es necessari per millorar el nostre coneixement dels cicles de l'aigua i l'energia. La teledetecció a banda L també ha sigut útil per monitoritzar l'estabilitat de les capes de gel i mesurar el gruix de gel marí. La missió Soil Moisture and Ocean Salinity (SMOS, 2009-2017) de l'ESA és la primera específicament llançada per monitoritzar SM i SSS. Porta un nou radiòmetre d'apertura sintètica amb capacitat multiangular i polarització completa. La missió Aquarius (2011-2015) de la NASA va ser la segona, dedicada a monitoritzar SSS amb un sistema de radiòmetre/escateròmetre d’apertura real que permet corregir la rugositat de la superfície del mar. La missió Soil Moisture Active Passive (SMAP, 2015-2018) de la NASA és la segona dedicada a mesurar SM. Porta un radiòmetre d'apertura real i polarització completa i un radar d'apertura sintètica (SAR) per una millor resolució espaial i detecció de congelació/descongelació. Aquesta tesi està enfocada en analitzar la informació geofísica que pot obtenir-se de les observacions a banda L d'SMOS, Aquarius i SMAP. La seva investigació està estructurada com: -Intercomparació de temperatures de brillantor en zones seleccionades. Es proposa un nou mètode per mesurar la consistència entre les dades radiomètriques d'SMOS i Aquarius sobre el rang dinàmic complet d'observacions (terra, gel, oceà). Això permet detectar diferències espaials/temporals o biaixos sense limitacions latitudinals ni creuaments. Aquest pas es necessari per combinar observacions de diferents instruments en un llarg conjunt de dades per estudis mediambientals, hidrològics o climatològics. -Efecte de gruix de gel en teledetecció de gel continental a l'Antàrtida. S'explora la relació entre les variacions espaials del gruix de gel antàrtic i els canvis detectats a les mesures d'SMOS i Aquarius. L'emissivitat de l'Antàrtida es analitzada per discernir el rol de les contribucions geofísiques (capes de gel a diferents profunditats i llacs subglacials) al senyal observat. S'avalua l'estabilitat del senyal a banda L sobre la zona est de l'altiplà antàrtic, lloc per calibratge/validació de satèl·lits de microones. -Sinèrgia de microones/òptic per teledetecció de SM multiescala. S'avalua la correlació entre la SM i la temperatura de la superfície del sòl (LST) per entendre millor la relació SM-LST a través de processos físics d'evapotranspiració i inèrcia tèrmica. Es proposa un nou mètode per mesurar la humitat crítica utilitzant sèries temporals de SM i LST de satèl·lit. S'analitza l'ús de la SM de SMOS amb la LST de teledetecció per refinar algorismes de desagregació de SM. -Comparació de paràmetres passius i actius de microones relatius a la vegetació. Recent investigació ha mostrat que l'opacitat, sensible a la biomassa i el contingut d'aigua, i l'albedo, relacionat amb l'estructura, poden ser recuperats d'observacions passives a banda L. S'exploren les relacions entre aquests dos paràmetres i estimadors de vegetació derivats de radar utilitzant les observacions d'avió de l'experiment de validació d'SMAP 2012 (SMAPVEX12). Les relacions obtingudes podrien permetre millors recuperacions de SM en sistemes actius/passius i estimar les propietats de la vegetació a alta resolució utilitzant mesures de SAR. La tesi s'ha desenvolupat dins les activitats del Barcelona Expert Centre (BEC). Els resultats presentats contribueixen a l'ús de la banda L a diferents disciplines científiques com la climatologia, la criosfera, la hidrologia i l'ecologia

Multiangular crop differentiation and LAI estimation using PROSAIL model inversion

xiii, 161 leaves : ill., map ; 29 cmUnderstanding variations in remote sensing data with illumination and sensor angle changes is important in agricultural crop monitoring. This research investigated field bidirectional reflectance factor (BRF) in crop differentiation and PROSAIL leaf area index (LAI) estimation. BRF and LAI data were collected for planophile and erectophile crops at three growth stages. In the solar principal plane, BRF differed optimally at 860 nm 60 days after planting (DAP) for canola and pea, at 860 nm 45 and 60 DAP for wheat and barley, and at 860 nm and 670 nm 45 and 60 DAP for planophiles versus erectophiles. The field BRF data helped better understand PROSAIL LAI estimation. NDVI was preferred for estimating LAI, however the MTVI2 vegetation index showed high sensitivity to view angles, particularly for erectophiles. The hotspot was important for crop differentiation and LAI. Availability of more along-track, off-nadir looking spaceborne sensors was recommended for agricultural crop monitoring

Automated proximal sensing for estimation of the bidirectional reflectance distribution function in a Mediterranean tree-grass ecosystem

Premio Extraordinario de Doctorado de la UAH en el año académico 2015-2016Los sistemas automáticos de proximal sensing permiten adquirir información espectral de las cubiertas terrestres elevada frecuencia temporal, que puede relacionarse con observaciones remotas o de otros tipos de sensores como los sistemas de eddy covariance. Si bien inicialmente los sistemas automáticos empleaban sensores multi-banda, en los últimos años se ha incrementado el uso de sensores hiperespectrales. Si bien estos sensores ofrecen información redundante y de alta resolución espectral, las mediciones están sujetas a múltiples fuentes de incertidumbre; tanto instrumentales (dependencias de la temperatura o el nivel de señal) como direccionales (dependencia de la geometría de observación e iluminación). Las dependencias instrumentales pueden ser minimizadas, por ejemplo, controlando la temperatura del instrumento o el nivel de señal registrado. En otros casos, es necesario parametrizar y emplear modelos para corregir los datos. En la presente tesis doctoral los capítulos 1 al 3 presentan la caracterización completa de un espectrómetro de campo instalado en un sistema automático. Los capítulos 1 y 2 analizan las fuentes de no linealidad en este instrumento, una de las cuales no había sido anteriormente descrita en este tipo de instrumentos. El tercer capítulo muestra el conjunto completo de modelos de corrección de los efectos instrumentales y la cadena de procesado correspondiente. Por otro lado, los sistemas automáticos se enfrentan a efectos direccionales ya que adquieren mediciones continuamente durante el ciclo solar diario y bajo cualquier condición de iluminación. Esto maximiza los rangos de los ángulos de iluminación y también de la fracción difusa de la irradiancia. Esta variabilidad de condiciones de iluminación, combinada con una variación de los ángulos de observación permite obtener la información necesaria para caracterizar las respuestas direccionales de la cubierta observada. Algunos sistemas automáticos multi-angulares ya han sido empleados para realizar esta caracterización mediante la estimación de la Función de Distribución de Reflectividad Bidireccional (BRDF) en ecosistemas homogéneos. Sin embargo, esto no se ha conseguido aún en áreas heterogéneas, como es el caso de los ecosistemas tree-grass o de sabana. Así mismo, los trabajos previos no han considerado los efectos de la radiación difusa en el estudio del BRDF. En el capítulo 4 proponemos una metodología que permite desmezclar y caracterizar simultáneamente la función de distribución de reflectividad hemisférica-direccional de las dos cubiertas de vegetación presentes en el ecosistema, pasto y arbolado. También se analizan los efectos de las diferentes características del método. Finalmente, los resultados se escalan y se comparan con productos globales de satélite como el producto BRDF de MODIS. La conclusión obtenida es que se requieren más esfuerzos en el desarrollo y caracterización de sensores hiperespectrales instalados en sistemas automáticos de campo. Estos sistemas deberían adoptar configuraciones multi-angulares de modo que puedan caracterizarse las respuestas direccionales. Para ello, será necesario considerar los efectos de la radiación difusa; y en algunos casos también la heterogeneidad de la escena

Automated proximal sensing for estimation of the bidirectional reflectance distribution function in a Mediterranean tree-grass ecosystem

Premio Extraordinario de Doctorado de la UAH en el año académico 2015-2016Los sistemas automáticos de proximal sensing permiten adquirir información espectral de las cubiertas terrestres elevada frecuencia temporal, que puede relacionarse con observaciones remotas o de otros tipos de sensores como los sistemas de eddy covariance. Si bien inicialmente los sistemas automáticos empleaban sensores multi-banda, en los últimos años se ha incrementado el uso de sensores hiperespectrales. Si bien estos sensores ofrecen información redundante y de alta resolución espectral, las mediciones están sujetas a múltiples fuentes de incertidumbre; tanto instrumentales (dependencias de la temperatura o el nivel de señal) como direccionales (dependencia de la geometría de observación e iluminación). Las dependencias instrumentales pueden ser minimizadas, por ejemplo, controlando la temperatura del instrumento o el nivel de señal registrado. En otros casos, es necesario parametrizar y emplear modelos para corregir los datos. En la presente tesis doctoral los capítulos 1 al 3 presentan la caracterización completa de un espectrómetro de campo instalado en un sistema automático. Los capítulos 1 y 2 analizan las fuentes de no linealidad en este instrumento, una de las cuales no había sido anteriormente descrita en este tipo de instrumentos. El tercer capítulo muestra el conjunto completo de modelos de corrección de los efectos instrumentales y la cadena de procesado correspondiente. Por otro lado, los sistemas automáticos se enfrentan a efectos direccionales ya que adquieren mediciones continuamente durante el ciclo solar diario y bajo cualquier condición de iluminación. Esto maximiza los rangos de los ángulos de iluminación y también de la fracción difusa de la irradiancia. Esta variabilidad de condiciones de iluminación, combinada con una variación de los ángulos de observación permite obtener la información necesaria para caracterizar las respuestas direccionales de la cubierta observada. Algunos sistemas automáticos multi-angulares ya han sido empleados para realizar esta caracterización mediante la estimación de la Función de Distribución de Reflectividad Bidireccional (BRDF) en ecosistemas homogéneos. Sin embargo, esto no se ha conseguido aún en áreas heterogéneas, como es el caso de los ecosistemas tree-grass o de sabana. Así mismo, los trabajos previos no han considerado los efectos de la radiación difusa en el estudio del BRDF. En el capítulo 4 proponemos una metodología que permite desmezclar y caracterizar simultáneamente la función de distribución de reflectividad hemisférica-direccional de las dos cubiertas de vegetación presentes en el ecosistema, pasto y arbolado. También se analizan los efectos de las diferentes características del método. Finalmente, los resultados se escalan y se comparan con productos globales de satélite como el producto BRDF de MODIS. La conclusión obtenida es que se requieren más esfuerzos en el desarrollo y caracterización de sensores hiperespectrales instalados en sistemas automáticos de campo. Estos sistemas deberían adoptar configuraciones multi-angulares de modo que puedan caracterizarse las respuestas direccionales. Para ello, será necesario considerar los efectos de la radiación difusa; y en algunos casos también la heterogeneidad de la escena

The acquisition of Hyperspectral Digital Surface Models of crops from UAV snapshot cameras

This thesis develops a new approach to capture information about agricultural crops by utilizing advances in the field of robotics, sensor technology, computer vision and photogrammetry: Hyperspectral digital surface models (HS DSMs) generated with UAV snapshot cameras are a representation of a surface in 3D space linked with hyperspectral information emitted and reflected by the objects covered by that surface. The overall research aim of this thesis is to evaluate if HS DSMs are suited for supporting a site-specific crop management. Based on six research studies, three research objectives are discussed for this evaluation. Firstly the influences of environmental effects, the sensing system and data processing of the spectral data within HS DSMs are discussed. Secondly, the comparability of HS DSMs to data from other remote sensing methods is investigated and thirdly their potential to support site-specific crop management is evaluated. Most data within this thesis was acquired at a plant experimental-plot experiment in Klein-Altendorf, Germany, with six different barley varieties and two different fertilizer treatments in the growing seasons of 2013 and 2014. In total, 22 measurement campaigns were carried out in the context of this thesis. HS DSMs acquired with the hyperspectral snapshot cameras Cubert UHD 185-Firefly show great potential for practical applications. The combination of UAVs and the UHD allowed data to be captured at a high spatial, spectral and temporal resolution. The spatial resolution allowed detection of small-scale heterogeneities within the plant population. Additionally, with the spectral and 3D information contained in HS DSMs, plant parameters such as chlorophyll, biomass and plant height could be estimated within individual, and across different growing stages. The techniques developed in this thesis therefore offer a significant contribution towards increasing cropping efficiency through the support of site-specific management

New algorithms for atmospheric correction and retrieval of biophysical parameters in earth observation : application to ENVISAT/MERIS data

An algorithm for the derivation of atmospheric and surface biophysical products from the MEdium Resolution Imaging Spectrometer Instrument (MERIS) on board ENVIronmental SATellite (ENVISAT/MERIS) Level 1b data over land has been developed. Georectified aerosol optical thickness (AOT), columnar water vapor (CWV), spectral surface reflectance and chlorophyll fluorescence (CF) maps are generated. Emphasis has been put on implementing a robust software able to provide those products on an operational manner, making no use of ancillary parameters apart from those attached to MERIS images. For this reason, it has been named Self-Contained Atmospheric Parameters Estimation from MERIS data (SCAPE-M). The fundamentals of the algorithm and the validation of the derived products are presented in this thesis. Errors of ±0.03, ±4% and ±8% have been estimated for AOT, CWV and surface reflectance retrievals, respectively, by means of a sensitivity analysis. More than 200 MERIS images have been processed in order to assess the method performance under a range of atmospheric and geographical conditions. A good comparison is found between SCAPE-M AOT retrievals and ground-based measurements taken during the SPectra bARrax Campaigns (SPARC) 2003 and 2004, except for a date when an episode of Saharan dust intrusion was detected. Comparison of SCAPE-M retrievals with data from AErosol RObotic NETwork (AERONET) stations showed a square Pearson's correlation coefficient R2 of about 0.7-0.8. Those values grow up to more than 0.9 in the case of CWV after comparison with the same stations. A good correlation is also found with the ESA Level 2 official CWV product, although slight different performances with varying surface elevation are detected. Retrieved surface reflectance maps have been intercompared with reflectance data derived from MERIS images by the Bremen AErosol Retrieval (BAER) method in the first place

The development of a temporal-BRDF model-based approach to change detection, an application to the identification and delineation of fire affected areas.

Although large quantities of southern Africa burn every year, minimal information is available relating to the fire regimes of this area. This study develops a new, generic approach to change detection, applicable to the identification of land cover change from high temporal and moderate spatial resolution satellite data. Traditional change detection techniques have several key limitations which are identified and addressed in this work. In particular these approaches fail to account for directional effects in the remote sensing signal introduced by variations in the solar and sensing geometry, and are sensitive to underlying phenological changes in the surface as well as noise in the data due to cloud or atmospheric contamination. This research develops a bi-directional, model-based change detection algorithm. An empirical temporal component is incorporated into a semi-empirical linear BRDF model. This may be fitted to a long time series of reflectance with less sensitivity to the presence of underlying phenological change. Outliers are identified based on an estimation of noise in the data and the calculation of uncertainty in the model parameters and are removed from the sequence. A "step function kernel" is incorporated into the formulation in order to detect explicitly sudden step-like changes in the surface reflectance induced by burning. The change detection model is applied to the problem of locating and mapping fire affected areas from daily moderate spatial resolution satellite data, and an indicator of burn severity is introduced. Monthly burned area datasets for a 2400km by 1200km area of southern Africa detailing the day and severity of burning are created for a five year period (2000-2004). These data are analysed and the fire regimes of southern African ecosystems during this time are characterised. The results highlight the extent of the burning which is taking place within southern Africa, with between 27-32% of the study area burning during each of the five years of observation. Higher fire frequencies are exhibited by savanna and grassland ecosystems, while more dense vegetation types such as shrublands and deciduous broadleaf forests burn less frequently. In addition the areas which burn more frequently do so with a greater severity, with a positive relationship identified between the frequency and the severity of burning

Puiden runkojen monikulmamittaus kannettavalla hyperspektrikameralla

Laboratory measurement settings that can acquire spectral and multi-angular information on canopy elements (e.g. leaves and woody tree structures) provide invaluable data for the interpretation and development of forest reflectance models and other optical remote sensing techniques. Previous studies have pointed out that the spectral properties of woody tree structures of boreal tree species have been studied little in comparison to leaves, and that there is a need to fill this gap in knowledge. This thesis presents a custom-built multi-angular measurement system with imaging capabilities that was used to acquire a hyperspectral dataset of boreal woody tree structures of the three most common tree species found in Finland. A total of six trees, two trees per species of Norway spruce (Picea abies (L.) Karst), Scots pine (Pinus sylvestris L.) and silver birch (Betula pendula Roth) stems were sampled at different heights (at every meter of height between 1–10 m) and sides (northward and southward facing sides of the stem), and the stem surface (bark) was measured with a novel mobile hyperspectral camera called Specim IQ. The camera operates in the wavelength range of 400–1000 nm. The acquired dataset contains hyperspectral images of 120 stem samples, each imaged from six different view angles. A designed pixel-by-pixel data processing chain is described. It can calculate and extract accurate pixel specific reflectance information that is invariant to uneven spatial distribution of incident irradiance from the lamp. Finally, the processed data was analyzed to reveal within- and between-species, angular, and spatial variations in stem bark reflectance for the three species. In concordance to previous studies, this thesis found that the species varied highly in their mean spectra and were distinguishable from one another. In addition, the within-species variation and standard deviation between mean spectra of samples was surprisingly low with very similar spectral signatures between samples of the same species. Investigating angular variation revealed that both pine and birch present strong specular reflections in the forward-scattering angles, in comparison to spruce, which presented a hot spot effect in the backward-scattering angles when measured near the lamp. Birch and spruce showed weak trends when looking at the spatial variations occurring in reflectance due to sampling height or side of the stem. However, pine displayed a clear increase in reflectance from 1 m to 4 m height at 663.81 nm (red band) and from 1 m to 5 m height at 865.5 nm (near-infrared band). The data obtained in this study show potential for future tasks such as tree species classification and the further development of forest reflectance models. The methods and materials presented in this study can give ideas for developing imaging goniometer systems that can acquire even more information on various vegetation canopy elements than what were presented in this thesis.Laboratorio-olosuhteissa käytettävät mittausjärjestelmät, jotka pystyvät keräämään spektriaineistoa eri mittauskulmista, tuottavat arvokasta tietoa metsien heijastusmallien ja muiden kaukokartoitustekniikoiden tulkintaa ja kehittämistä varten. Aikaisemmat tutkimukset ovat osoittaneet, että boreaalisen vyöhykkeen puulajien puumaisten osien spektriominaisuuksia ei ole tutkittu yhtä paljon kuin lehtien, ja tämän takia kyseiselle tiedolle on selkeä tarve. Tässä diplomityössä rakennettiin monikulmainen kuvantava mittausasetelma, jolla mitattiin hyperspektriaineisto kolmesta Suomen yleisimmästä puulajista: kuusesta (Picea abies (L.) Karst), männystä (Pinus sylvestris L.) ja rauduskoivusta (Betula pendula Roth). Mitattavat näytteet kerättiin yhteensä kuudesta puusta, kahdesta puusta per puulaji. Näytteitä otettiin rungon eri korkeuksilta (metrin välein kymmeneen metriin asti) ja ilmansuunnista (pohjoinen ja eteläinen puoli runkoa). Rungon pintaosan (kuoren) heijastusspektri mitattiin uudella kannettavalla Specim IQ -hyperspetrikameralla, joka pystyy keräämään tietoa 400–1000 nanometrin aallonpituuksilta. Kerätty spektriaineisto koostuu Specim IQ:lla mitatuista hyperspektrikuvista, joita otettiin 120 näytteestä. Jokainen näyte kuvattiin kuudesta eri kulmasta. Mittausasetelman lisäksi tässä diplomityössä kehitettiin pikselikohtainen prosessointimenetelmä, jonka avulla voi laskea näytteen heijastusspektrin siten, että siihen ei vaikuta lampusta epätasaisesti jakautuva valo. Prosessoitujen hyperspektrikuvien avulla tutkittiin, kuinka heijastusspektri vaihtelee puulajien välillä sekä sisäisesti puulajin näytteiden välillä. Lopuksi tutkittiin, kuinka eri mittauskulmat ja näytteenottokorkeus vaikuttavat kuusen, männyn ja koivun heijastusspektreihin. Yhtenevästi aikaisempien tutkimusten kanssa tämän diplomityön tulokset osoittavat, että puulajien väliset erot heijastusspektreissä olivat suuria ja puulajit toisistaan erotettavissa. Toisaalta puulajin sisäinen vaihtelu oli yllättävän pientä ja saman puulajin näytteiden spektrit olivat samanlaisia toisiinsa nähden. Mittauskulman vaikutuksen selvittäminen osoitti, että männyllä ja rauduskoivulla heijastus suuntautuu voimakkaasti eteenpäin. Toisaalta kuusi osoitti voimakkaampaa taaksepäin valonlähdettä kohti suuntautuvaa heijastusta. Kuusella ja rauduskoivulla oli havaittavissa vähäistä heijastuksen spatiaalista vaihtelua näytteenottokorkeuksien ja ilmansuuntien välillä. Toisin kuin kuusi ja rauduskoivu, mänty osoitti selkeää nousevaa heijastusta 663.81 nm aallonpituudella (punainen kanava) 1 m korkeudelta 4 m korkeuteen. Lähi-infrapunakanavalla (865.5 nm) vastaava kasvu havaittiin välillä 1–5 m. Tässä diplomityössä kerättyä tietoa on mahdollista käyttää puulajien tunnistusmenetelmien sekä metsien heijastusmallien kehittämisessä. Tämän lisäksi esitetyt koetekniikat ja tutkimusmenetelmät voivat auttaa kehittämään kuvantavia goniometrijärjestelmiä, joilla voisi kerätä vieläkin laajempaa tietoa kasvillisuudesta ja sen eri heijastusominaisuuksista