Review of optical-based remote sensing for plant trait mapping

[1]  N. Coops,et al.  Intercomparison of fraction of absorbed photosynthetically active radiation products derived from satellite data over Europe , 2014 .

[2]  J. Chun,et al.  Variations in Species and Functional Plant Diversity among Forest Types on the Ridge of the Baekdudaegan Mountains, South Korea , 2013 .

[3]  D. Shrestha,et al.  ASSESSING THE EFFECTS OF LAND USE CHANGE ON RUNOFF IN BEDOG SUB WATERSHED YOGYAKARTA , 2013 .

[4]  M. Schaepman,et al.  Retrieval of spruce leaf chlorophyll content from airborne image data using continuum removal and radiative transfer , 2013 .

[5]  Gregory P. Asner,et al.  Observing Changing Ecological Diversity in the Anthropocene , 2013 .

[6]  Aleixandre Verger,et al.  ntercomparison and quality assessment of MERIS , MODIS and SEVIRI FAPAR roducts over the Iberian Peninsula , 2012 .

[7]  R. Nelson,et al.  Achieving accuracy requirements for forest biomass mapping: A spaceborne data fusion method for estimating forest biomass and LiDAR sampling error , 2013 .

[8]  Marek K. Jakubowski,et al.  Tradeoffs between lidar pulse density and forest measurement accuracy , 2013 .

[9]  Philip Lewis,et al.  Hyperspectral remote sensing of foliar nitrogen content , 2012, Proceedings of the National Academy of Sciences.

[10]  P. Zarco-Tejada,et al.  Carotenoid content estimation in a heterogeneous conifer forest using narrow-band indices and PROSPECT + DART simulations , 2012 .

[11]  Oliver Cartus,et al.  Mapping Canopy Height and Growing Stock Volume Using Airborne Lidar, ALOS PALSAR and Landsat ETM+ , 2012, Remote. Sens..

[12]  Roberta E. Martin,et al.  Carnegie Airborne Observatory-2: Increasing science data dimensionality via high-fidelity multi-sensor fusion , 2012 .

[13]  Christopher Conrad,et al.  Quantifying and mapping ecosystem services supplies and demands: a review of remote sensing applications. , 2012, Environmental science & technology.

[14]  Philip Lewis,et al.  Retrieval and global assessment of terrestrial chlorophyll fluorescence from GOSAT space measurements , 2012 .

[15]  Joanne C. White,et al.  Lidar sampling for large-area forest characterization: A review , 2012 .

[16]  Michael E. Schaepman,et al.  Sentinels for science: potential of Sentinel-1, -2, and -3 missions for scientific observations of ocean, cryosphere, and land , 2012 .

[17]  Jan G. P. W. Clevers,et al.  Using Hyperspectral Remote Sensing Data for Retrieving Canopy Chlorophyll and Nitrogen Content , 2012, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[18]  Juha Hyyppä,et al.  An International Comparison of Individual Tree Detection and Extraction Using Airborne Laser Scanning , 2012, Remote. Sens..

[19]  J. Suomalainen,et al.  Full waveform hyperspectral LiDAR for terrestrial laser scanning. , 2012, Optics express.

[20]  Håkan Olsson,et al.  Estimation of 3D vegetation structure from waveform and discrete return airborne laser scanning data , 2012 .

[21]  S. Bruin,et al.  Trend changes in global greening and browning: contribution of short‐term trends to longer‐term change , 2012 .

[22]  Achieving Accuracy Requirements for Forest Biomass Mapping: A Data Fusion Method for Estimating Forest Biomass and LiDAR Sampling Error with Spaceborne Data , 2012 .

[23]  F. Rocca,et al.  The BIOMASS mission: Mapping global forest biomass to better understand the terrestrial carbon cycle , 2011 .

[24]  Xianjun Hao,et al.  Estimating dry matter content from spectral reflectance for green leaves of different species , 2011 .

[25]  Wout Verhoef,et al.  Inversion of a coupled canopy–atmosphere model using multi-angular top-of-atmosphere radiance data: A forest case study , 2011 .

[26]  Pablo J. Zarco-Tejada,et al.  Assessing structural effects on PRI for stress detection in conifer forests , 2011 .

[27]  S. Higgins,et al.  TRY – a global database of plant traits , 2011, Global Change Biology.

[28]  A. Ramoelo,et al.  Water-removed spectra increase the retrieval accuracy when estimating savanna grass nitrogen and phosphorus concentrations , 2011 .

[29]  Andrew K. Skidmore,et al.  Dry season mapping of savanna forage quality, using the hyperspectral Carnegie Airborne Observatory sensor , 2011 .

[30]  Jonathan Seaquist,et al.  The effect of the temporal resolution of NDVI data on season onset dates and trends across Canadian broadleaf forests , 2011 .

[31]  W. Verhoef,et al.  Estimating forest variables from top-of-atmosphere radiance satellite measurements using coupled radiative transfer models , 2011 .

[32]  Jessica J. Mitchell,et al.  Errors in LiDAR-derived shrub height and crown area on sloped terrain , 2011 .

[33]  K. Omasa,et al.  Identification of invasive vegetation using hyperspectral imagery in the shore of the Kinu River, Japan , 2011 .

[34]  Arnon Karnieli,et al.  Exploring remotely sensed technologies for monitoring wheat potassium and phosphorus using field spectroscopy , 2011 .

[35]  Josep Peñuelas,et al.  The photochemical reflectance index (PRI) and the remote sensing of leaf, canopy and ecosystem radiation use efficiencies: A review and meta-analysis , 2011 .

[36]  X. Yao,et al.  Assessing newly developed and published vegetation indices for estimating rice leaf nitrogen concentration with ground- and space-based hyperspectral reflectance , 2011 .

[37]  Sandra Lavorel,et al.  Using plant functional traits to understand the landscape distribution of multiple ecosystem services , 2011 .

[38]  Roberta E. Martin,et al.  Taxonomy and remote sensing of leaf mass per area (LMA) in humid tropical forests. , 2011, Ecological applications : a publication of the Ecological Society of America.

[39]  S. Ollinger.  Sources of variability in canopy reflectance and the convergent properties of plants. , 2011, The New phytologist.

[40]  E. Middleton,et al.  First observations of global and seasonal terrestrial chlorophyll fluorescence from space , 2010 .

[41]  Barbara Koch,et al.  Status and future of laser scanning, synthetic aperture radar and hyperspectral remote sensing data for forest biomass assessment , 2010 .

[42]  Thomas Hilker,et al.  Estimation of Light-use Efficiency of Terrestrial Ecosystems from Space: A Status Report , 2010 .

[43]  D. Haboudane,et al.  New spectral indicator assessing the efficiency of crop nitrogen treatment in corn and wheat , 2010 .

[44]  Mark D. Schwartz,et al.  Intercomparing multiple measures of the onset of spring in eastern North America , 2010 .

[45]  Benjamin L Turner,et al.  Linkages of plant traits to soil properties and the functioning of temperate grassland , 2010 .

[46]  Miina Rautiainen,et al.  Ecological applications of physically based remote sensing methods , 2010 .

[47]  Brian J McGill,et al.  How do traits vary across ecological scales? A case for trait-based ecology. , 2010, Ecology letters.

[48]  Susan L Ustin,et al.  Remote sensing of plant functional types. , 2010, The New phytologist.

[49]  D. Wardle,et al.  Plant traits, leaf palatability and litter decomposability for co‐occurring woody species differing in invasion status and nitrogen fixation ability , 2010 .

[50]  S. Nilsson,et al.  Comparison of four global FAPAR datasets over Northern Eurasia for the year 2000 , 2010 .

[51]  M. Nieuwenhuis,et al.  Retrieval of forest structural parameters using LiDAR remote sensing , 2010, European Journal of Forest Research.

[52]  L. Monika Moskal,et al.  Fusion of LiDAR and imagery for estimating forest canopy fuels , 2010 .

[53]  Wouter Dorigo,et al.  Applying different inversion techniques to retrieve stand variables of summer barley with PROSPECT + SAIL , 2010, Int. J. Appl. Earth Obs. Geoinformation.

[54]  Michael E. Schaepman,et al.  Estimating canopy water content using hyperspectral remote sensing data , 2010, Int. J. Appl. Earth Obs. Geoinformation.

[55]  M. Schaepman,et al.  Effects of woody elements on simulated canopy reflectance: Implications for forest chlorophyll content retrieval , 2010 .

[56]  Clement Atzberger,et al.  Retrieval of chlorophyll and nitrogen in Norway spruce (Picea abies L. Karst.) using imaging spectroscopy , 2010, Int. J. Appl. Earth Obs. Geoinformation.

[57]  M. Fischer,et al.  A meta-analysis of trait differences between invasive and non-invasive plant species. , 2010, Ecology letters.

[58]  Damien Sulla-Menashe,et al.  MODIS Collection 5 global land cover: Algorithm refinements and characterization of new datasets , 2010 .

[59]  Onisimo Mutanga,et al.  Forage quality of savannas - Simultaneously mapping foliar protein and polyphenols for trees and grass using hyperspectral imagery , 2010 .

[60]  J. Moreno,et al.  Remote sensing of sun‐induced fluorescence to improve modeling of diurnal courses of gross primary production (GPP) , 2010 .

[61]  Geoffrey M. Henebry,et al.  Spatio-Temporal Statistical Methods for Modelling Land Surface Phenology , 2010 .

[62]  George Vosselman,et al.  Airborne and terrestrial laser scanning , 2011, Int. J. Digit. Earth.

[63]  I. Woodhouse,et al.  Using satellite radar backscatter to predict above‐ground woody biomass: A consistent relationship across four different African landscapes , 2009 .

[64]  M. Ball,et al.  Non-destructive measurement of chlorophyll b : a ratios and identification of photosynthetic pathways in grasses by reflectance spectroscopy. , 2009, Functional plant biology : FPB.

[65]  Zbyněk Malenovský,et al.  Near-distance imaging spectroscopy investigating chlorophyll fluorescence and photosynthetic activity of grassland in the daily course. , 2009, Functional plant biology : FPB.

[66]  José M. Paruelo,et al.  Grass species differentiation through canopy hyperspectral reflectance , 2009 .

[67]  Luis Alonso,et al.  Remote sensing of solar-induced chlorophyll fluorescence: Review of methods and applications , 2009 .

[68]  M. Schaepman,et al.  Intercomparison, interpretation, and assessment of spring phenology in North America estimated from remote sensing for 1982–2006 , 2009 .

[69]  Margaret Kalacska,et al.  Differences in leaf traits, leaf internal structure, and spectral reflectance between two communities of lianas and trees: Implications for remote sensing in tropical environments , 2009 .

[70]  R. Kokaly,et al.  Characterizing canopy biochemistry from imaging spectroscopy and its application to ecosystem studies , 2009 .

[71]  W. Verhoef,et al.  PROSPECT+SAIL models: A review of use for vegetation characterization , 2009 .

[72]  Alexander F. H. Goetz,et al.  Three decades of hyperspectral remote sensing of the Earth: a personal view. , 2009 .

[73]  Michael E. Schaepman,et al.  Retrieval of foliar information about plant pigment systems from high resolution spectroscopy , 2009 .

[74]  Andrew D Richardson,et al.  Near-surface remote sensing of spatial and temporal variation in canopy phenology. , 2009, Ecological applications : a publication of the Ecological Society of America.

[75]  Z. Malenovský,et al.  Scientific and technical challenges in remote sensing of plant canopy reflectance and fluorescence. , 2009, Journal of experimental botany.

[76]  Lea Hallik,et al.  Contrasting correlation networks between leaf structure, nitrogen and chlorophyll in herbaceous and woody canopies , 2009 .

[77]  José A. Sobrino,et al.  Global land surface phenology trends from GIMMS database , 2009 .

[78]  Timothy A. Warner,et al.  The SAGE Handbook of Remote Sensing , 2009 .

[79]  John R. Miller,et al.  Imaging chlorophyll fluorescence with an airborne narrow-band multispectral camera for vegetation stress detection , 2009 .

[80]  Benjamin Koetz,et al.  Airborne and terrestrial laser scanning for measuring vegetation canopy structure , 2009 .

[81]  Juli G. Pausas,et al.  Fire-related traits for plant species of the Mediterranean Basin , 2009 .

[82]  Liang Liang,et al.  Landscape phenology: an integrative approach to seasonal vegetation dynamics , 2009, Landscape Ecology.

[83]  Frédéric Bretar,et al.  Full-waveform topographic lidar : State-of-the-art , 2009 .

[84]  S. Frolking,et al.  Canopy nitrogen, carbon assimilation, and albedo in temperate and boreal forests: Functional relations and potential climate feedbacks , 2008, Proceedings of the National Academy of Sciences.

[85]  M. Chopping.  Terrestrial applications of multiangle remote sensing , 2008 .

[86]  Paul E. Gessler,et al.  The influence of conifer forest canopy cover on the accuracy of two individual tree measurement algorithms using lidar data , 2008 .

[87]  Susan L. Ustin,et al.  Identification of invasive vegetation using hyperspectral remote sensing in the California Delta ecosystem , 2008 .

[88]  Martin Hermy,et al.  The LEDA Traitbase: a database of life‐history traits of the Northwest European flora , 2008 .

[89]  Nathan J B Kraft,et al.  Functional Traits and Niche-Based Tree Community Assembly in an Amazonian Forest , 2008, Science.

[90]  T. A. Black,et al.  The use of remote sensing in light use efficiency based models of gross primary production: a review of current status and future requirements. , 2008, The Science of the total environment.

[91]  S. Ollinger,et al.  A generalizable method for remote sensing of canopy nitrogen across a wide range of forest ecosystems , 2008 .

[92]  Lara A. Arroyo,et al.  Fire models and methods to map fuel types: The role of remote sensing , 2008 .

[93]  Michael E. Schaepman,et al.  Using spectral information from the NIR water absorption features for the retrieval of canopy water content , 2008, Int. J. Appl. Earth Obs. Geoinformation.

[94]  K. Itten,et al.  Estimating foliar biochemistry from hyperspectral data in mixed forest canopy , 2008 .

[95]  T. A. Black,et al.  Separating physiologically and directionally induced changes in PRI using BRDF models , 2008 .

[96]  Y. Knyazikhin,et al.  Validation and intercomparison of global Leaf Area Index products derived from remote sensing data , 2008 .

[97]  J. Martonchik,et al.  Large area mapping of southwestern forest crown cover, canopy height, and biomass using the NASA Multiangle Imaging Spectro-Radiometer , 2008 .

[98]  C. Giardino,et al.  Estimation of leaf and canopy water content in poplar plantations by means of hyperspectral indices and inverse modeling , 2008 .

[99]  K. Soudani,et al.  Calibration and validation of hyperspectral indices for the estimation of broadleaved forest leaf chlorophyll content, leaf mass per area, leaf area index and leaf canopy biomass , 2008 .

[100]  Xia Yao,et al.  Monitoring leaf nitrogen status with hyperspectral reflectance in wheat , 2008 .

[101]  Yichun Xie,et al.  Remote sensing imagery in vegetation mapping: a review , 2008 .

[102]  K. Treseder,et al.  Nitrogen limitation of net primary productivity in terrestrial ecosystems is globally distributed. , 2008, Ecology.

[103]  Sorin C. Popescu,et al.  Mapping surface fuel models using lidar and multispectral data fusion for fire behavior , 2008 .

[104]  Frédéric Achard,et al.  GLOBCOVER : The most detailed portrait of Earth , 2008 .

[105]  F. Baret,et al.  Estimating Canopy Characteristics from Remote Sensing Observations: Review of Methods and Associated Problems , 2008 .

[106]  Hans-Hermann Gerdes,et al.  Functional Traits and Niche-Based Tree Community Assembly in an Amazonian Forest , 2008 .

[107]  Andrew K. Skidmore,et al.  Can nutrient status of four woody plant species be predicted using field spectrometry , 2007 .

[108]  Johan E. S. Fransson,et al.  Effects on estimation accuracy of forest variables using different pulse density of laser data , 2007 .

[109]  Wilfried Thuiller,et al.  Plant-trait-based modeling assessment of ecosystem-service sensitivity to land-use change. , 2007, Ecological applications : a publication of the Ecological Society of America.

[110]  Fabien Quétier,et al.  Assessing functional diversity in the field - methodology matters! , 2007 .

[111]  L. Kumar,et al.  Estimating and mapping grass phosphorus concentration in an African savanna using hyperspectral image data , 2007 .

[112]  O. Hagolle,et al.  LAI, fAPAR and fCover CYCLOPES global products derived from VEGETATION: Part 1: Principles of the algorithm , 2007 .

[113]  J. Eitel,et al.  Using in‐situ measurements to evaluate the new RapidEye™ satellite series for prediction of wheat nitrogen status , 2007 .

[114]  Johan Ehrlén,et al.  Variation in vegetative and flowering phenology in a forest herb caused by environmental heterogeneity. , 2007, American journal of botany.

[115]  Terry Caelli,et al.  Hyperspectral discrimination of tropical dry forest lianas and trees: Comparative data reduction approaches at the leaf and canopy levels , 2007 .

[116]  Rosa Lasaponara,et al.  Remotely sensed characterization of forest fuel types by using satellite ASTER data , 2007, Int. J. Appl. Earth Obs. Geoinformation.

[117]  W. Verhoef,et al.  Coupled soil–leaf-canopy and atmosphere radiative transfer modeling to simulate hyperspectral multi-angular surface reflectance and TOA radiance data , 2007 .

[118]  Lloyd L. Coulter,et al.  Detecting Tamarisk species (Tamarix spp.) in riparian habitats of Southern California using high spatial resolution hyperspectral imagery , 2007 .

[119]  L. Guanter,et al.  Spectral calibration and atmospheric correction of ultra-fine spectral and spatial resolution remote sensing data. Application to CASI-1500 data , 2007 .

[120]  Mathias Disney,et al.  Can we measure terrestrial photosynthesis from space directly, using spectral reflectance and fluorescence? , 2007 .

[121]  Giles M. Foody,et al.  Discriminating and mapping the C3 and C4 composition of grasslands in the northern Great Plains, USA , 2007, Ecol. Informatics.

[122]  Sassan Saatchi,et al.  Estimation of Forest Fuel Load From Radar Remote Sensing , 2007, IEEE Transactions on Geoscience and Remote Sensing.

[123]  C. Buschmann.  Variability and application of the chlorophyll fluorescence emission ratio red/far-red of leaves , 2007, Photosynthesis Research.

[124]  Menno Straatsma,et al.  Extracting structural characteristics of herbaceous floodplain vegetation under leaf‐off conditions using airborne laser scanner data , 2007 .

[125]  A. Skidmore,et al.  Red edge shift and biochemical content in grass canopies , 2007 .

[126]  C. Violle,et al.  Let the concept of trait be functional , 2007 .

[127]  Eric Garnier,et al.  Assessing the effects of land-use change on plant traits, communities and ecosystem functioning in grasslands: a standardized methodology and lessons from an application to 11 European sites. , 2007, Annals of botany.

[128]  Fausto W. Acerbi-Junior,et al.  Scaling dimensions in spectroscopy of soil and vegetation , 2007, Int. J. Appl. Earth Obs. Geoinformation.

[129]  Michael E. Schaepman,et al.  Spectrodirectional remote sensing: From pixels to processes , 2007, Int. J. Appl. Earth Obs. Geoinformation.

[130]  G. A. Blackburn,et al.  Hyperspectral remote sensing of plant pigments. , 2006, Journal of experimental botany.

[131]  S. Ustin,et al.  Estimating Vegetation Water content with Hyperspectral data for different Canopy scenarios: Relationships between AVIRIS and MODIS Indexes , 2006 .

[132]  F. Bello,et al.  Variations in species and functional plant diversity along climatic and grazing gradients , 2006 .

[133]  A. Rango,et al.  Mapping shrub abundance in desert grasslands using geometric-optical modeling and multi-angle remote sensing with CHRIS/Proba , 2006 .

[134]  R. Colombo,et al.  Leaf level detection of solar induced chlorophyll fluorescence by means of a subnanometer resolution spectroradiometer , 2006 .

[135]  A. Kuusk,et al.  Impact of understory vegetation on forest canopy reflectance and remotely sensed LAI estimates , 2006 .

[136]  T. Painter,et al.  Reflectance quantities in optical remote sensing - definitions and case studies , 2006 .

[137]  Nigel P. Fox,et al.  Progress in Field Spectroscopy , 2006, 2006 IEEE International Symposium on Geoscience and Remote Sensing.

[138]  Alan H. Strahler,et al.  Validation of the global land cover 2000 map , 2006, IEEE Transactions on Geoscience and Remote Sensing.

[139]  A. Goetz,et al.  Assessing spatial patterns of forest fuel using AVIRIS data , 2006 .

[140]  J. Greenberg,et al.  Mapping Invasive Aquatic Vegetation in the Sacramento-San Joaquin Delta using Hyperspectral Imagery , 2006, Environmental monitoring and assessment.

[141]  A. Gitelson,et al.  Three‐band model for noninvasive estimation of chlorophyll, carotenoids, and anthocyanin contents in higher plant leaves , 2006 .

[142]  W. Walker,et al.  Mapping forest structure for wildlife habitat analysis using multi-sensor (LiDAR, SAR/InSAR, ETM+, Quickbird) synergy , 2006 .

[143]  M. Cho,et al.  A new technique for extracting the red edge position from hyperspectral data: The linear extrapolation method , 2006 .

[144]  N. Delbart,et al.  Remote sensing of spring phenology in boreal regions: A free of snow-effect method using NOAA-AVHRR and SPOT-VGT data (1982-2004) , 2006 .

[145]  M. Reyniers,et al.  Measuring wheat nitrogen status from space and ground‐based platform , 2006 .

[146]  Philip Lewis,et al.  3D modelling of forest canopy structure for remote sensing simulations in the optical and microwave domains , 2006 .

[147]  K. L. b.  Appendix S1 , 2006 .

[148]  Sandra Díaz,et al.  Specific leaf area and dry matter content estimate thickness in laminar leaves. , 2005, Annals of botany.

[149]  S. Ollinger,et al.  Net Primary Production and Canopy Nitrogen in a Temperate Forest Landscape: An Analysis Using Imaging Spectroscopy, Modeling and Field Data , 2005, Ecosystems.

[150]  Edwin W. Pak,et al.  An extended AVHRR 8‐km NDVI dataset compatible with MODIS and SPOT vegetation NDVI data , 2005 .

[151]  A. Skidmore,et al.  Nitrogen detection with hyperspectral normalized ratio indices across multiple plant species , 2005 .

[152]  Stephen Porder,et al.  Ground-based and remotely sensed nutrient availability across a tropical landscape. , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[153]  M. Williams,et al.  OPTICAL INSTRUMENTS FOR MEASURING LEAF AREA INDEX IN LOW VEGETATION: APPLICATION IN ARCTIC ECOSYSTEMS , 2005 .

[154]  Peter Schröder,et al.  What can we measure? , 2005, SIGGRAPH Courses.

[155]  A. Belward,et al.  GLC2000: a new approach to global land cover mapping from Earth observation data , 2005 .

[156]  Pablo J. Zarco-Tejada,et al.  Estimation of fuel moisture content by inversion of radiative transfer models to simulate equivalent water thickness and dry matter content: analysis at leaf and canopy level , 2005, IEEE Transactions on Geoscience and Remote Sensing.

[157]  T. Dawson,et al.  Synthesis of remote sensing approaches for forest carbon estimation: reporting to the Kyoto Protocol , 2005 .

[158]  M. Schlerf,et al.  Remote sensing of forest biophysical variables using HyMap imaging spectrometer data , 2005 .

[159]  P. Vitousek,et al.  Remote analysis of biological invasion and biogeochemical change. , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[160]  E. Næsset,et al.  Laser scanning of forest resources: the nordic experience , 2004 .

[161]  J. Dash,et al.  The MERIS terrestrial chlorophyll index , 2004 .

[162]  D. Diner,et al.  Canopy Structure Parameters Derived from Multi-Angular Remote Sensing Data for Terrestrial Carbon Studies , 2004 .

[163]  R. Stöckli,et al.  European plant phenology and climate as seen in a 20-year AVHRR land-surface parameter dataset , 2004 .

[164]  R. Jongschaap,et al.  Spectral measurements at different spatial scales in potato: relating leaf, plant and canopy nitrogen status , 2004 .

[165]  K. Itten,et al.  Radiative transfer modeling within a heterogeneous canopy for estimation of forest fire fuel properties , 2004 .

[166]  R. Fensholt,et al.  Evaluation of MODIS LAI, fAPAR and the relation between fAPAR and NDVI in a semi-arid environment using in situ measurements , 2004 .

[167]  J. P. Grime,et al.  The plant traits that drive ecosystems: Evidence from three continents , 2004 .

[168]  K. Itten,et al.  Quantitative retrieval of biogeophysical characteristics using imaging spectroscopy - a mountain forest case study , 2004 .

[169]  W. Cohen,et al.  Landsat's Role in Ecological Applications of Remote Sensing , 2004 .

[170]  B. Law,et al.  Forest Attributes from Radar Interferometric Structure and Its Fusion with Optical Remote Sensing , 2004 .

[171]  D. Roberts,et al.  Small-footprint lidar estimation of sub-canopy elevation and tree height in a tropical rain forest landscape , 2004 .

[172]  Craig M. Trotter,et al.  Estimating photosynthetic light-use efficiency using the photochemical reflectance index: variations among species. , 2004, Functional plant biology : FPB.

[173]  Sean C. Thomas,et al.  The worldwide leaf economics spectrum , 2004, Nature.

[174]  C. Hopkinson,et al.  Assessing forest metrics with a ground-based scanning lidar , 2004 .

[175]  E. Davidson,et al.  Satellite-based modeling of gross primary production in an evergreen needleleaf forest , 2004 .

[176]  A. Skidmore,et al.  Predicting in situ pasture quality in the Kruger National Park, South Africa, using continuum-removed absorption features , 2004 .

[177]  Richard Fernandes,et al.  Evaluating image-based estimates of leaf area index in boreal conifer stands over a range of scales using high-resolution CASI imagery , 2004 .

[178]  N. Goel,et al.  Needle chlorophyll content estimation through model inversion using hyperspectral data from boreal conifer forest canopies , 2004 .

[179]  Andres Kuusk,et al.  The effect of crown shape on the reflectance of coniferous stands , 2004 .

[180]  C. François,et al.  Towards universal broad leaf chlorophyll indices using PROSPECT simulated database and hyperspectral reflectance measurements , 2004 .

[181]  N. Oppelt,et al.  Hyperspectral monitoring of physiological parameters of wheat during a vegetation period using AVIS data , 2004 .

[182]  Jean-Philippe Gastellu-Etchegorry,et al.  DART: a 3D model for simulating satellite images and studying surface radiation budget , 2004 .

[183]  P. Reich,et al.  Different photosynthesis-nitrogen relations in deciduous hardwood and evergreen coniferous tree species , 1995, Oecologia.

[184]  J. R. Evans.  Photosynthesis and nitrogen relationships in leaves of C3 plants , 2004, Oecologia.

[185]  I. Moyaa,et al.  A new instrument for passive remote sensing 1 . Measurements of sunlight-induced chlorophyll fluorescence , 2004 .

[186]  S. Liang.  Quantitative Remote Sensing of Land Surfaces , 2003 .

[187]  J. Schjoerring,et al.  Reflectance measurement of canopy biomass and nitrogen status in wheat crops using normalized difference vegetation indices and partial least squares regression , 2003 .

[188]  P. Reich,et al.  A handbook of protocols for standardised and easy measurement of plant functional traits worldwide , 2003 .

[189]  Nicholas C. Coops,et al.  Prediction of eucalypt foliage nitrogen content from satellite-derived hyperspectral data , 2003, IEEE Trans. Geosci. Remote. Sens..

[190]  Marie-Louise Smith,et al.  Analysis of hyperspectral data for estimation of temperate forest canopy nitrogen concentration: comparison between an airborne (AVIRIS) and a spaceborne (Hyperion) sensor , 2003, IEEE Trans. Geosci. Remote. Sens..

[191]  Jane R. Foster,et al.  Application of imaging spectroscopy to mapping canopy nitrogen in the forests of the central Appalachian Mountains using Hyperion and AVIRIS , 2003, IEEE Trans. Geosci. Remote. Sens..

[192]  R. Colombo,et al.  Retrieval of leaf area index in different vegetation types using high resolution satellite data , 2003 .

[193]  Wim Klaassen,et al.  The contribution of ocean‐leaving DMS to the global atmospheric burdens of DMS, MSA, SO2, and NSS SO4= , 2003 .

[194]  J. Holmgren,et al.  Estimation of Tree Height and Stem Volume on Plots Using Airborne Laser Scanning , 2003, Forest Science.

[195]  Pablo J. Zarco-Tejada,et al.  Hyperspectral Remote Sensing of Forest Condition: Estimating Chlorophyll Content in Tolerant Hardwoods , 2003, Forest Science.

[196]  Tomas Brandtberg.  Detection and analysis of individual leaf-off tree crowns in small footprint, high sampling density lidar data from the eastern deciduous forest in North America , 2003 .

[197]  R. DeFries,et al.  Global distribution of C3 and C4 vegetation: Carbon cycle implications , 2003 .

[198]  R. Clark,et al.  Mapping vegetation in Yellowstone National Park using spectral feature analysis of AVIRIS data , 2003 .

[199]  S. Dobrowski,et al.  Steady-state chlorophyll a fluorescence detection from canopy derivative reflectance and double-peak red-edge effects , 2003 .

[200]  Yuri Knyazikhin,et al.  Retrieval of canopy biophysical variables from bidirectional reflectance Using prior information to solve the ill-posed inverse problem , 2003 .

[201]  A. Huete,et al.  Overview of the radiometric and biophysical performance of the MODIS vegetation indices , 2002 .

[202]  S. Running,et al.  Global products of vegetation leaf area and fraction absorbed PAR from year one of MODIS data , 2002 .

[203]  S. Ollinger,et al.  DIRECT ESTIMATION OF ABOVEGROUND FOREST PRODUCTIVITY THROUGH HYPERSPECTRAL REMOTE SENSING OF CANOPY NITROGEN , 2002 .

[204]  S. Lavorel,et al.  Predicting changes in community composition and ecosystem functioning from plant traits: revisiting the Holy Grail , 2002 .

[205]  N. Broge,et al.  Airborne multispectral data for quantifying leaf area index, nitrogen concentration, and photosynthetic efficiency in agriculture , 2002 .

[206]  J. Peñuelas,et al.  Remote sensing of nitrogen and lignin in Mediterranean vegetation from AVIRIS data: Decomposing biochemical from structural signals , 2002 .

[207]  D. Sims,et al.  Relationships between leaf pigment content and spectral reflectance across a wide range of species, leaf structures and developmental stages , 2002 .

[208]  John R. Miller,et al.  Integrated narrow-band vegetation indices for prediction of crop chlorophyll content for application to precision agriculture , 2002 .

[209]  S. Leblanc,et al.  Derivation and validation of Canada-wide coarse-resolution leaf area index maps using high-resolution satellite imagery and ground measurements , 2002 .

[210]  A. Gitelson,et al.  Assessing Carotenoid Content in Plant Leaves with Reflectance Spectroscopy¶ , 2002, Photochemistry and photobiology.

[211]  Bill Shipley,et al.  Dry matter content as a measure of dry matter concentration in plants and their parts , 2002 .

[212]  D. Riaño,et al.  Estimation of fuel moisture content from multitemporal analysis of Landsat Thematic Mapper reflectance data: Applications in fire danger assessment , 2002 .

[213]  D. Lobell,et al.  View angle effects on canopy reflectance and spectral mixture analysis of coniferous forests using AVIRIS , 2002 .

[214]  W. Cohen,et al.  Lidar Remote Sensing for Ecosystem Studies , 2002 .

[215]  P. North,et al.  Remote sensing of canopy light use efficiency using the photochemical reflectance index , 2001 .

[216]  E. Garnier,et al.  A standardized protocol for the determination of specific leaf area and leaf dry matter content , 2001 .

[217]  D. Roberts,et al.  Practical limits on hyperspectral vegetation discrimination in arid and semiarid environments , 2001 .

[218]  Raymond F. Kokaly,et al.  Investigating a Physical Basis for Spectroscopic Estimates of Leaf Nitrogen Concentration , 2001 .

[219]  Lalit Kumar,et al.  Imaging Spectrometry and Vegetation Science , 2001 .

[220]  F. Csillag,et al.  The Influence of Vegetation Index and Spatial Resolution on a Two-Date Remote Sensing-Derived Relation to C4 Species Coverage , 2001 .

[221]  S. M. de Jong,et al.  Imaging spectrometry : basic principles and prospective applications , 2001 .

[222]  Nadine Gobron,et al.  Advanced vegetation indices optimized for up-coming sensors: Design, performance, and applications , 2000, IEEE Trans. Geosci. Remote. Sens..

[223]  John R. Krebs,et al.  Improving bird population models using airborne remote sensing , 2000 .

[224]  L. Lymburner,et al.  Estimation of Canopy-Average Surface-Specific Leaf Area Using Landsat TM Data , 2000 .

[225]  C. V. M. Bartona,et al.  Remote sensing of canopy light use efficiency using the photochemical reflectance index Model and sensitivity analysis , 2000 .

[226]  Karin S. Fassnacht,et al.  Relationships between leaf area index and Landsat TM spectral vegetation indices across three temperate zone sites , 1999 .

[227]  R. Clark,et al.  Spectroscopic Determination of Leaf Biochemistry Using Band-Depth Analysis of Absorption Features and Stepwise Multiple Linear Regression , 1999 .

[228]  Peter R. J. North,et al.  The Propagation of Foliar Biochemical Absorption Features in Forest Canopy Reflectance , 1999 .

[229]  J. P. Grime,et al.  Benefits of plant diversity to ecosystems: immediate, filter and founder effects , 1998 .

[230]  B. Datt.  Remote Sensing of Chlorophyll a, Chlorophyll b, Chlorophyll a+b, and Total Carotenoid Content in Eucalyptus Leaves , 1998 .

[231]  Mary E. Martin,et al.  Determining Forest Species Composition Using High Spectral Resolution Remote Sensing Data , 1998 .

[232]  Frédéric Baret,et al.  On spectral estimates of fresh leaf biochemistry , 1998 .

[233]  J. Ehleringer,et al.  C4 photosynthesis, atmospheric CO2, and climate , 1997, Oecologia.

[234]  S. Díaz,et al.  Plant functional types and ecosystem function in relation to global change , 1997 .

[235]  Frédéric Baret,et al.  Estimation of leaf water content and specific leaf weight from reflectance and transmittance measurements , 1997 .

[236]  Mary E. Martin,et al.  HIGH SPECTRAL RESOLUTION REMOTE SENSING OF FOREST CANOPY LIGNIN, NITROGEN, AND ECOSYSTEM PROCESSES , 1997 .

[237]  L. Johnson,et al.  Spectrometric Estimation of Total Nitrogen Concentration in Douglas-Fir Foliage , 1996 .

[238]  Bernard Pinty,et al.  Designing optimal spectral indexes for remote sensing applications , 1996, IEEE Trans. Geosci. Remote. Sens..

[239]  S. Ustin,et al.  Estimating leaf biochemistry using the PROSPECT leaf optical properties model , 1996 .

[240]  S. Ustin,et al.  Critique of stepwise multiple linear regression for the extraction of leaf biochemistry information from leaf reflectance data , 1996 .

[241]  Mary E. Martin,et al.  Determination of carbon fraction and nitrogen concentration in tree foliage by near infrared reflectance : a comparison of statistical methods , 1996 .

[242]  Jean-Philippe Gastellu-Etchegorry,et al.  Forest canopy chemistry with high spectral resolution remote sensing , 1996 .

[243]  J. Peñuelas,et al.  Assessment of photosynthetic radiation‐use efficiency with spectral reflectance , 1995 .

[244]  B. Yoder,et al.  Predicting nitrogen and chlorophyll content and concentrations from reflectance spectra (400–2500 nm) at leaf and canopy scales , 1995 .

[245]  J. Randerson,et al.  Global net primary production: Combining ecology and remote sensing , 1995 .

[246]  Jesslyn F. Brown,et al.  Measuring phenological variability from satellite imagery , 1994 .

[247]  R. Myneni,et al.  On the relationship between FAPAR and NDVI , 1994 .

[248]  David L. Peterson,et al.  Multivariate analysis of AVIRIS data for canopy biochemical estimation along the oregon transect , 1994 .

[249]  A. Wellburn,et al.  The spectral determination of chlorophyll a and chlorophyll b, as well as total carotenoids, using various solvents with spectrophotometers of different resolution. , 1994 .

[250]  C. Field,et al.  A narrow-waveband spectral index that tracks diurnal changes in photosynthetic efficiency , 1992 .

[251]  The effect of crown shape on sprinkler irrigation in a container nursery , 1992 .

[252]  P. Curran.  Remote sensing of foliar chemistry , 1989 .

[253]  R. J. Porra,et al.  Determination of accurate extinction coefficients and simultaneous equations for assaying chlorophylls a and b extracted with four different solvents: verification of the concentration of chlorophyll standards by atomic absorption spectroscopy , 1989 .

[254]  M. D. Hatch,et al.  C4 photosynthesis: a unique elend of modified biochemistry, anatomy and ultrastructure , 1987 .

[255]  J. Ross.  The radiation regime and architecture of plant stands , 1981, Tasks for vegetation sciences 3.

[256]  J. Monteith.  SOLAR RADIATION AND PRODUCTIVITY IN TROPICAL ECOSYSTEMS , 1972 .

[257]  A. Apinis.  Mapping Vegetation , 1959, Nature.