879 resultados para spectral vegetation indices
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This study analyses the influence of vegetation structure (i.e. leaf area index and canopy cover) and seasonal background changes on moderate-resolution imaging spectrometer (MODIS)-simulated reflectance data in open woodland. Approximately monthly spectral reflectance and transmittance field measurements (May 2011 to October 2013) of cork oak tree leaves (Quercus suber) and of the herbaceous understorey were recorded in the region of Ribatejo, Portugal. The geometric-optical and radiative transfer (GORT) model was used to simulate MODIS response (red, near-infrared) and to calculate vegetation indices, investigating their response to changes in the structure of the overstorey vegetation and to seasonal changes in the understorey using scenarios corresponding to contrasting phenological status (dry season vs. wet season). The performance of normalized difference vegetation index (NDVI), soil-adjusted vegetation index (SAVI), and enhanced vegetation index (EVI) is discussed. Results showed that SAVI and EVI were very sensitive to the emergence of background vegetation in the wet season compared to NDVI and that shading effects lead to an opposing trend in the vegetation indices. The information provided by this research can be useful to improve our understanding of the temporal dynamic of vegetation, monitored by vegetation indices.
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View angle and directional effects significantly affect reflectance and vegetation indices, especially when daily images collected by large field-of-view (FOV) sensors like the Moderate Resolution Imaging Spectroradiometer (MODIS) are used. In this study, the PROSAIL radiative transfer model was chosen to evaluate the impact of the geometry of data acquisition on soybean reflectance and two vegetation indices (Normalized Difference Vegetation Index - NDVI and Enhanced Vegetation Index -EVI) by varying biochemical and biophysical parameters of the crop. Input values for PROSAIL simulation were based on the literature and were adjusted by the comparison between simulated and real satellite soybean spectra acquired by the MODIS/Terra and hyperspectral Hyperion/Earth Observing-One (EO-1). Results showed that the influence of the view angle and view direction on reflectance was stronger with decreasing leaf area index (LAI) and chlorophyll concentration. Because of the greater dependence on the near-infrared reflectance, the EVI was much more sensitive to viewing geometry than NDVI presenting larger values in the backscattering direction. The contrary was observed for NDVI in the forward scattering direction. In relation to the LAI, NDVI was much more isotropic for closed soybean canopies than for incomplete canopies and a contrary behavior was verified for EVI.
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Vegetation-cycles are of general interest for many applications. Be it for harvest-predictions, global monitoring of climate-change or as input to atmospheric models.rnrnCommon Vegetation Indices use the fact that for vegetation the difference between Red and Near Infrared reflection is higher than in any other material on Earths surface. This gives a very high degree of confidence for vegetation-detection.rnrnThe spectrally resolving data from the GOME and SCIAMACHY satellite-instrumentsrnprovide the chance to analyse finer spectral features throughout the Red and Near Infrared spectrum using Differential Optical Absorption Spectroscopy (DOAS). Although originally developed to retrieve information on atmospheric trace gases, we use it to gain information on vegetation. Another advantage is that this method automatically corrects for changes in the atmosphere. This renders the vegetation-information easily comparable over long time-spans.rnThe first results using previously available reference spectra were encouraging, but also indicated substantial limitations of the available reflectance spectra of vegetation. This was the motivation to create new and more suitable vegetation reference spectra within this thesis.rnThe set of reference spectra obtained is unique in its extent and also with respect to its spectral resolution and the quality of the spectral calibration. For the first time, this allowed a comprehensive investigation of the high-frequency spectral structures of vegetation reflectance and of their dependence on the viewing geometry.rnrnThe results indicate that high-frequency reflectance from vegetation is very complex and highly variable. While this is an interesting finding in itself, it also complicates the application of the obtained reference spectra to the spectral analysis of satellite observations.rnrnThe new set of vegetation reference spectra created in this thesis opens new perspectives for research. Besides refined satellite analyses, these spectra might also be used for applications on other platforms such as aircraft. First promising studies have been presented in this thesis, but the full potential for the remote sensing of vegetation from satellite (or aircraft) could bernfurther exploited in future studies.
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The main objective of this work was to evaluate the linear regression between spectral response and soybean yield in regional scale. In this study were monitored 36 municipalities from the west region of the states of Parana using five images of Landsat 5/TM during 2004/05 season. The spectral response was converted in physical values, apparent and surface reflectances, by radiometric transformation and atmospheric corrections and both used to calculate NDVI and GVI vegetation indices. Those ones were compared by multiple and simple regression with government official yield values (IBGE). Diagnostic processing method to identify influents values or collinearity was applied to the data too. The results showed that the mean surface reflectance value from all images was more correlated with yield than individual dates. Further, the multiple regressions using all dates and both vegetation indices gave better results than simple regression.
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Thesis submitted to the Instituto Superior de Estatstica e Gesto de Informao da Universidade Nova de Lisboa in partial fulfillment of the requirements for the Degree of Doctor of Philosophy in Information Management Geographic Information Systems
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Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.
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The objective of this work was to evaluate the use of multispectral remote sensing for site-specific nitrogen fertilizer management. Satellite imagery from the advanced spaceborne thermal emission and reflection radiometer (Aster) was acquired in a 23 ha corn-planted area in Iran. For the collection of field samples, a total of 53 pixels were selected by systematic randomized sampling. The total nitrogen content in corn leaf tissues in these pixels was evaluated. To predict corn canopy nitrogen content, different vegetation indices, such as normalized difference vegetation index (NDVI), soil-adjusted vegetation index (Savi), optimized soil-adjusted vegetation index (Osavi), modified chlorophyll absorption ratio index 2 (MCARI2), and modified triangle vegetation index 2 (MTVI2), were investigated. The supervised classification technique using the spectral angle mapper classifier (SAM) was performed to generate a nitrogen fertilization map. The MTVI2 presented the highest correlation (R=0.87) and is a good predictor of corn canopy nitrogen content in the V13 stage, at 60 days after cultivating. Aster imagery can be used to predict nitrogen status in corn canopy. Classification results indicate three levels of required nitrogen per pixel: low (0-2.5 kg), medium (2.5-3 kg), and high (3-3.3 kg).
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The aim of this study was to use digital images acquired by cameras attached to a helium balloon to detect variation of the nutritional status in Brachiaria decumbens. The treatments consisted of five doses of nitrogen (0, 50, 100, 150 e 200kg ha-1) with six replications each, evaluated in a completely randomized statistical design. A remote sensing system composed of digital cameras and microcomputers was used for image acquisition, and a helium balloon lifted the cameras to the heights of 15, 20, 25 and 30m. A portable chlorophyll meter and analyses of leaf nitrogen content were used to make comparisons with data obtained by the remote sensing system. Data was acquired in two phases, in different climatic conditions. At the end of each phase, dry matter production was measured. Three vegetation indices were used to evaluate the detection of different nutritional status. The three indices were able to detect the effects of N doses. The indices constructed with the Green spectral band showed to be more efficient.
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RSUM - Les images satellitales multispectrales, notamment celles haute rsolution spatiale (plus fine que 30 m au sol), reprsentent une source dinformation inestimable pour la prise de dcision dans divers domaines lis la gestion des ressources naturelles, la prservation de lenvironnement ou lamnagement et la gestion des centres urbains. Les chelles dtude peuvent aller du local (rsolutions plus fines que 5 m) des chelles rgionales (rsolutions plus grossires que 5 m). Ces images caractrisent la variation de la rflectance des objets dans le spectre qui est linformation cl pour un grand nombre dapplications de ces donnes. Or, les mesures des capteurs satellitaux sont aussi affectes par des facteurs parasites lis aux conditions dclairement et dobservation, latmosphre, la topographie et aux proprits des capteurs. Deux questions nous ont proccup dans cette recherche. Quelle est la meilleure approche pour restituer les rflectances au sol partir des valeurs numriques enregistres par les capteurs tenant compte des ces facteurs parasites ? Cette restitution est-elle la condition sine qua non pour extraire une information fiable des images en fonction des problmatiques propres aux diffrents domaines dapplication des images (cartographie du territoire, monitoring de lenvironnement, suivi des changements du paysage, inventaires des ressources, etc.) ? Les recherches effectues les 30 dernires annes ont abouti une srie de techniques de correction des donnes des effets des facteurs parasites dont certaines permettent de restituer les rflectances au sol. Plusieurs questions sont cependant encore en suspens et dautres ncessitent des approfondissements afin, dune part damliorer la prcision des rsultats et dautre part, de rendre ces techniques plus versatiles en les adaptant un plus large ventail de conditions dacquisition des donnes. Nous pouvons en mentionner quelques unes : - Comment prendre en compte des caractristiques atmosphriques (notamment des particules darosol) adaptes des conditions locales et rgionales et ne pas se fier des modles par dfaut qui indiquent des tendances spatiotemporelles long terme mais sajustent mal des observations instantanes et restreintes spatialement ? - Comment tenir compte des effets de contamination du signal provenant de lobjet vis par le capteur par les signaux provenant des objets environnant (effet dadjacence) ? ce phnomne devient trs important pour des images de rsolution plus fine que 5 m; - Quels sont les effets des angles de vise des capteurs hors nadir qui sont de plus en plus prsents puisquils offrent une meilleure rsolution temporelle et la possibilit dobtenir des couples dimages stroscopiques ? - Comment augmenter lefficacit des techniques de traitement et danalyse automatique des images multispectrales des terrains accidents et montagneux tenant compte des effets multiples du relief topographique sur le signal capt distance ? Dautre part, malgr les nombreuses dmonstrations par des chercheurs que linformation extraite des images satellitales peut tre altre cause des tous ces facteurs parasites, force est de constater aujourdhui que les corrections radiomtriques demeurent peu utilises sur une base routinire tel quest le cas pour les corrections gomtriques. Pour ces dernires, les logiciels commerciaux de tldtection possdent des algorithmes versatiles, puissants et la porte des utilisateurs. Les algorithmes des corrections radiomtriques, lorsquils sont proposs, demeurent des botes noires peu flexibles ncessitant la plupart de temps des utilisateurs experts en la matire. Les objectifs que nous nous sommes fixs dans cette recherche sont les suivants : 1) Dvelopper un logiciel de restitution des rflectances au sol tenant compte des questions poses ci-haut. Ce logiciel devait tre suffisamment modulaire pour pouvoir le bonifier, lamliorer et ladapter diverses problmatiques dapplication dimages satellitales; et 2) Appliquer ce logiciel dans diffrents contextes (urbain, agricole, forestier) et analyser les rsultats obtenus afin dvaluer le gain en prcision de linformation extraite par des images satellitales transformes en images des rflectances au sol et par consquent la ncessit doprer ainsi peu importe la problmatique de lapplication. Ainsi, travers cette recherche, nous avons ralis un outil de restitution de la rflectance au sol (la nouvelle version du logiciel REFLECT). Ce logiciel est bas sur la formulation (et les routines) du code 6S (Seconde Simulation du Signal Satellitaire dans le Spectre Solaire) et sur la mthode des cibles obscures pour lestimation de lpaisseur optique des arosols (aerosol optical depth, AOD), qui est le facteur le plus difficile corriger. Des amliorations substantielles ont t apportes aux modles existants. Ces amliorations concernent essentiellement les proprits des arosols (intgration dun modle plus rcent, amlioration de la recherche des cibles obscures pour lestimation de lAOD), la prise en compte de leffet dadjacence laide dun modle de rflexion spculaire, la prise en compte de la majorit des capteurs multispectraux haute rsolution (Landsat TM et ETM+, tous les HR de SPOT 1 5, EO-1 ALI et ASTER) et trs haute rsolution (QuickBird et Ikonos) utiliss actuellement et la correction des effets topographiques laide dun modle qui spare les composantes directe et diffuse du rayonnement solaire et qui sadapte galement la canope forestire. Les travaux de validation ont montr que la restitution de la rflectance au sol par REFLECT se fait avec une prcision de lordre de 0.01 units de rflectance (pour les bandes spectrales du visible, PIR et MIR), mme dans le cas dune surface topographie variable. Ce logiciel a permis de montrer, travers des simulations de rflectances apparentes quel point les facteurs parasites influant les valeurs numriques des images pouvaient modifier le signal utile qui est la rflectance au sol (erreurs de 10 plus de 50%). REFLECT a galement t utilis pour voir limportance de lutilisation des rflectances au sol plutt que les valeurs numriques brutes pour diverses applications courantes de la tldtection dans les domaines des classifications, du suivi des changements, de lagriculture et de la foresterie. Dans la majorit des applications (suivi des changements par images multi-dates, utilisation dindices de vgtation, estimation de paramtres biophysiques, ), la correction des images est une opration cruciale pour obtenir des rsultats fiables. Dun point de vue informatique, le logiciel REFLECT se prsente comme une srie de menus simples dutilisation correspondant aux diffrentes tapes de saisie des intrants de la scne, calcul des transmittances gazeuses, estimation de lAOD par la mthode des cibles obscures et enfin, lapplication des corrections radiomtriques limage, notamment par loption rapide qui permet de traiter une image de 5000 par 5000 pixels en 15 minutes environ. Cette recherche ouvre une srie de pistes pour dautres amliorations des modles et mthodes lis au domaine des corrections radiomtriques, notamment en ce qui concerne lintgration de la FDRB (fonction de distribution de la rflectance bidirectionnelle) dans la formulation, la prise en compte des nuages translucides laide de la modlisation de la diffusion non slective et lautomatisation de la mthode des pentes quivalentes propose pour les corrections topographiques.
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De nos jours les cartes dutilisation/occupation du sol (USOS) une chelle rgionale sont habituellement gnres partir dimages satellitales de rsolution modre (entre 10 m et 30 m). Le National Land Cover Database aux tats-Unis et le programme CORINE (Coordination of information on the environment) Land Cover en Europe, tous deux fonds sur les images LANDSAT, en sont des exemples reprsentatifs. Cependant ces cartes deviennent rapidement obsoltes, spcialement en environnement dynamique comme les megacits et les territoires mtropolitains. Pour nombre dapplications, une mise jour de ces cartes sur une base annuelle est requise. Depuis 2007, le USGS donne accs gratuitement des images LANDSAT ortho-rectifies. Des images archives (depuis 1984) et des images acquises rcemment sont disponibles. Sans aucun doute, une telle disponibilit dimages stimulera la recherche sur des mthodes et techniques rapides et efficaces pour un monitoring continue des changements des USOS partir dimages rsolution moyenne. Cette recherche visait valuer le potentiel de telles images satellitales de rsolution moyenne pour obtenir de linformation sur les changements des USOS une chelle rgionale dans le cas de la Communaut Mtropolitaine de Montral (CMM), une mtropole nord-amricaine typique. Les tudes prcdentes ont dmontr que les rsultats de dtection automatique des changements dpendent de plusieurs facteurs tels : 1) les caractristiques des images (rsolution spatiale, bandes spectrales, etc.); 2) la mthode mme utilise pour la dtection automatique des changements; et 3) la complexit du milieu tudi. Dans le cas du milieu tudi, lexception du centre-ville et des artres commerciales, les utilisations du sol (industriel, commercial, rsidentiel, etc.) sont bien dlimites. Ainsi cette tude sest concentre aux autres facteurs pouvant affecter les rsultats, nommment, les caractristiques des images et les mthodes de dtection des changements. Nous avons utilis des images TM/ETM+ de LANDSAT 30 m de rsolution spatiale et avec six bandes spectrales ainsi que des images VNIR-ASTER 15 m de rsolution spatiale et avec trois bandes spectrales afin dvaluer limpact des caractristiques des images sur les rsultats de dtection des changements. En ce qui a trait la mthode de dtection des changements, nous avons dcid de comparer deux types de techniques automatiques : (1) techniques fournissant des informations principalement sur la localisation des changements et (2)techniques fournissant des informations la fois sur la localisation des changements et sur les types de changement (classes de- ). Les principales conclusions de cette recherche sont les suivantes : Les techniques de dtection de changement telles les diffrences dimage ou lanalyse des vecteurs de changements appliqus aux images multi-temporelles LANDSAT fournissent une image exacte des lieux o un changement est survenu dune faon rapide et efficace. Elles peuvent donc tre intgres dans un systme de monitoring continu des fins dvaluation rapide du volume des changements. Les cartes des changements peuvent aussi servir de guide pour lacquisition dimages de haute rsolution spatiale si lidentification dtaille du type de changement est ncessaire. Les techniques de dtection de changement telles lanalyse en composantes principales et la comparaison post-classification appliques aux images multi-temporelles LANDSAT fournissent une image relativement exacte de classes de- mais un niveau thmatique trs gnral (par exemple, bti espace vert et vice-versa, boiss sol nu et vice-versa, etc.). Les images ASTER-VNIR avec une meilleure rsolution spatiale mais avec moins de bandes spectrales que LANDSAT noffrent pas un niveau thmatique plus dtaill (par exemple, boiss espace commercial ou industriel). Les rsultats indiquent que la recherche future sur la dtection des changements en milieu urbain devrait se concentrer aux changements du couvert vgtal puisque les images rsolution moyenne sont trs sensibles aux changements de ce type de couvert. Les cartes indiquant la localisation et le type des changements du couvert vgtal sont en soi trs utiles pour des applications comme le monitoring environnemental ou lhydrologie urbaine. Elles peuvent aussi servir comme des indicateurs des changements de lutilisation du sol. De techniques telles lanalyse des vecteurs de changement ou les indices de vgtation son employes cette fin.
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Summary: Productivity, botanical composition and forage quality of legume-grass swards are important factors for successful arable farming in both organic and conventional farming systems. As these attributes can vary considerably within a field, a non-destructive method of detection while doing other tasks would facilitate a more targeted management of crops, forage and nutrients in the soil-plant-animal system. This study was undertaken to explore the potential of field spectral measurements for a non destructive prediction of dry matter (DM) yield, legume proportion in the sward, metabolizable energy (ME), ash content, crude protein (CP) and acid detergent fiber (ADF) of legume-grass mixtures. Two experiments were conducted in a greenhouse under controlled conditions which allowed collecting spectral measurements which were free from interferences such as wind, passing clouds and changing angles of solar irradiation. In a second step this initial investigation was evaluated in the field by a two year experiment with the same legume-grass swards. Several techniques for analysis of the hyperspectral data set were examined in this study: four vegetation indices (VIs): simple ratio (SR), normalized difference vegetation index (NDVI), enhanced vegetation index (EVI) and red edge position (REP), two-waveband reflectance ratios, modified partial least squares (MPLS) regression and stepwise multiple linear regression (SMLR). The results showed the potential of field spectroscopy and proved its usefulness for the prediction of DM yield, ash content and CP across a wide range of legume proportion and growth stage. In all investigations prediction accuracy of DM yield, ash content and CP could be improved by legume-specific calibrations which included mixtures and pure swards of perennial ryegrass and of the respective legume species. The comparison between the greenhouse and the field experiments showed that the interaction between spectral reflectance and weather conditions as well as incidence angle of light interfered with an accurate determination of DM yield. Further research is hence needed to improve the validity of spectral measurements in the field. Furthermore, the developed models should be tested on varying sites and vegetation periods to enhance the robustness and portability of the models to other environmental conditions.
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The purpose of this work was to study fragmentation of forest formations (mesophytic forest, riparian woodland and savannah vegetation (cerrado)) in a 15,774-ha study area located in the Municipal District of Botucatu in Southeastern Brazil (So Paulo State). A land use and land cover map was made from a color composition of a Landsat-5 thematic mapper (TM) image. The edge effect caused by habitat fragmentation was assessed by overlaying, on a geographic information system (GIS), the land use and land cover data with the spectral ratio. The degree of habitat fragmentation was analyzed by deriving: 1. mean patch area and perimeter; 2. patch number and density; 3. perimeter-area ratio, fractal dimension (D), and shape diversity index (SI); and 4. distance between patches and dispersion index (R). In addition, the following relationships were modeled: 1. distribution of natural vegetation patch sizes; 2. perimeter-area relationship and the number and area of natural vegetation patches; 3. edge effect caused by habitat fragmentation, the values of R indicated that savannah patches (R = 0.86) were aggregated while patches of natural vegetation as a whole (R = 1.02) were randomly dispersed in the landscape. There was a high frequency of small patches in the landscape whereas large patches were rare. In the perimeter-area relationship, there was no sign of scale distinction in the patch shapes, In the patch number-landscape area relationship, D, though apparently scale-dependent, tends to be constant as area increases. This phenomenon was correlated with the tendency to reach a constant density as the working scale was increased, on the edge effect analysis, the edge-center distance was properly estimated by a model in which the edge-center distance was considered a function of the to;al patch area and the SI. (C) 1997 Elsevier B.V. B.V.
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Recently high spectral resolution sensors have been developed, which allow new and more advanced applications in agriculture. Motivated by the increasing importance of hyperspectral remote sensing data, the need for research is important to define optimal wavebands to estimate biophysical parameters of crop. The use of narrow band vegetation indices (VI) derived from hyperspectral measurements acquired by a field spectrometer was evaluated to estimate bean (Phaseolus vulgaris L.) grain yield, plant height and leaf area index (LAI). Field canopy reflectance measurements were acquired at six bean growth stages over 48 plots with four water levels (179.5; 256.5; 357.5 and 406.2 mm) and tree nitrogen rates (0; 80 and 160 kg ha-1) and four replicates. The following VI was analyzed: OSNBR (optimum simple narrow-band reflectivity); NB_NDVI (narrow-band normalized difference vegetation index) and NDVI (normalized difference index). The vegetation indices investigated (OSNBR, NB_NDVI and NDVI) were efficient to estimate LAI, plant height and grain yield. During all crop development, the best correlations between biophysical variables and spectral variables were observed on V4 (the third trifoliolate leaves were unfolded in 50 % of plants) and R6 (plants developed first flowers in 50 % of plants) stages, according to the variable analyzed.
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The integration of remote monitoring techniques at different scales is of crucial importance for monitoring of volcanoes and assessment of the associated hazard. In this optic, technological advancement and collaboration between research groups also play a key role. Vhub is a community cyberinfrastructure platform designed for collaboration in volcanology research. Within the Vhub framework, this dissertation focuses on two research themes, both representing novel applications of remotely sensed data in volcanology: advancement in the acquisition of topographic data via active techniques and application of passive multi-spectral satellite data to monitoring of vegetated volcanoes. Measuring surface deformation is a critical issue in analogue modelling of Earth science phenomena. I present a novel application of the Microsoft Kinect sensor to measurement of vertical and horizontal displacements in analogue models. Specifically, I quantified vertical displacement in a scaled analogue model of Nisyros volcano, Greece, simulating magmatic deflation and inflation and related surface deformation, and included the horizontal component to reconstruct 3D models of pit crater formation. The detection of active faults around volcanoes is of importance for seismic and volcanic hazard assessment, but not a simple task to be achieved using analogue models. I present new evidence of neotectonic deformation along a north-south trending fault from the Mt Shasta debris avalanche deposit (DAD), northern California. The fault was identified on an airborne LiDAR campaign of part of the region interested by the DAD and then confirmed in the field. High resolution LiDAR can be utilized also for geomorphological assessment of DADs, and I describe a size-distance analysis to document geomorphological aspects of hummock in the Shasta DAD. Relating the remote observations of volcanic passive degassing to conditions and impacts on the ground provides an increased understanding of volcanic degassing and how satellite-based monitoring can be used to inform hazard management strategies in nearreal time. Combining a variety of satellite-based spectral time series I aim to perform the first space-based assessment of the impacts of sulfur dioxide emissions from Turrialba volcano, Costa Rica, on vegetation in the surrounding environment, and establish whether vegetation indices could be used more broadly to detect volcanic unrest.
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Due to highly erodible volcanic soils and a harsh climate, livestock grazing in Iceland has led to serious soil erosion on about 40% of the country's surface. Over the last 100 years, various revegetation and restoration measures were taken on large areas distributed all over Iceland in an attempt to counteract this problem. The present research aimed to develop models for estimating percent vegetation cover (VC) and aboveground biomass (AGB) based on satellite data, as this would make it possible to assess and monitor the effectiveness of restoration measures over large areas at a fairly low cost. Models were developed based on 203 vegetation cover samples and 114 aboveground biomass samples distributed over five SPOT satellite datasets. All satellite datasets were atmospherically corrected, and digital numbers were converted into ground reflectance. Then a selection of vegetation indices (VIs) was calculated, followed by simple and multiple linear regression analysis of the relations between the field data and the calculated VIs. Best results were achieved using multiple linear regression models for both %VC and AGB. The model calibration and validation results showed that R2 and RMSE values for most VIs do not vary very much. For percent VC, R2 values range between 0.789 and 0.822, leading to RMSEs ranging between 15.89% and 16.72%. For AGB, R2 values for low-biomass areas (AGB < 800 g/m2) range between 0.607 and 0.650, leading to RMSEs ranging between 126.08 g/m2 and 136.38 g/m2. The AGB model developed for all areas, including those with high biomass coverage (AGB > 800 g/m2), achieved R2 values between 0.487 and 0.510, resulting in RMSEs ranging from 234 g/m2 to 259.20 g/m2. The models predicting percent VC generally overestimate observed low percent VC and slightly underestimate observed high percent VC. The estimation models for AGB behave in a similar way, but over- and underestimation are much more pronounced. These results show that it is possible to estimate percent VC with high accuracy based on various VIs derived from SPOT satellite data. AGB of restoration areas with low-biomass values of up to 800 g/m2 can likewise be estimated with high accuracy based on various VIs derived from SPOT satellite data, whereas in the case of high biomass coverage, estimation accuracy decreases with increasing biomass values. Accordingly, percent VC can be estimated with high accuracy anywhere in Iceland, whereas AGB is much more difficult to estimate, particularly for areas with high-AGB variability.
