Brown and green LAI mapping through spectral indices

Baret, 2007, LAI, fAPAR and fCover CYCLOPES global products derived from VEGETATION. Part 1: Principles of the algorithm, Remote Sens. Environ., 110, 275, 10.1016/j.rse.2007.02.018 Broge, 2000, Comparing prediction power and stability of broadband and hyperspectral vegetation indices for estimation of green leaf area index and canopy chlorophyll density, Remote Sens. Environ., 76, 156, 10.1016/S0034-4257(00)00197-8 Brown, 2000, A shortwave infrared modification to the simple ratio for LAI retrieval in boreal forests: an image and model analysis, Remote Sens. Environ., 71, 16, 10.1016/S0034-4257(99)00035-8 Bsaibes, 2009, Albedo and LAI estimates from FORMOSAT-2 data for crop monitoring, Remote Sens. Environ., 113, 716, 10.1016/j.rse.2008.11.014 Byambakhuu, 2010, Spectral unmixing model to assess land cover fractions in Mongolian steppe regions, Remote Sens. Environ., 114, 2361, 10.1016/j.rse.2010.05.013 Chen, 2002, Derivation and validation of Canada-wide coarse-resolution leaf area index maps using high-resolution satellite imagery and ground measurements, Remote Sens. Environ., 80, 165, 10.1016/S0034-4257(01)00300-5 Clark, 2003, Imaging spectroscopy: earth and planetary remote sensing with the USGS Tetracorder and expert systems, J. Geophys. Res., 108, 5131 Cocks, 1998, The HYMAP airborne hyperspectral sensor: the system, calibration and performance, 37 Curran, 1989, Remote sensing of foliar chemistry, Remote Sens. Environ., 30, 271, 10.1016/0034-4257(89)90069-2 Darvishzadeh, 2008, Estimation of vegetation LAI from hyperspectral reflectance data: effects of soil type and plant architecture, Int. J. Appl. Earth Observ. Geoinform., 10, 358, 10.1016/j.jag.2008.02.005 Daughtry, 2001, Discriminating crop residues from soil by shortwave infrared reflectance, Agron. J., 93, 125, 10.2134/agronj2001.931125x Daughtry, 2005, Remote sensing the spatial distribution of crop residues, Agron. J., 97, 864, 10.2134/agronj2003.0291 Deng, 2006, Algorithm for global leaf area index retrieval using satellite imagery, IEEE Trans. Geosci. Remote Sens., 44, 2219, 10.1109/TGRS.2006.872100 Delegido, 2011, Evaluation of Sentinel-2 red-edge bands for empirical estimation of Green LAI and chlorophyll content, Sensors, 11, 7063, 10.3390/s110707063 Delegido, 2013, A red-edge spectral index for remote sensing estimation of green LAI over agroecosystems, Eur. J. Agron., 46, 42, 10.1016/j.eja.2012.12.001 Drusch, 2012, Sentinel-2: ESA's optical high-resolution mission for GMES operational services, Remote Sens. Environ., 120, 25, 10.1016/j.rse.2011.11.026 Duveiller, 2012, Remotely sensed green area index for winter wheat crop monitoring: 10-year assessment at regional scale over a fragmented landscape, Agric. Forest Meteorol., 152, 156, 10.1016/j.agrformet.2012.07.014 ESA, 2004 Fensholt, 2003, Derivation of a shortwave infrared water stress index from MODIS near- and shortwave infrared data in a semiarid environment, Remote Sens. Environ., 87, 111, 10.1016/j.rse.2003.07.002 Feret, 2008, PROSPECT-4 und 5: advances in the leaf optical properties model separating photosynthetic pigments, Remote Sens. Environ., 112, 3030, 10.1016/j.rse.2008.02.012 Frampton, 2013, Evaluating the capabilities of Sentinel-2 for quantitative estimation of biophysical variables in vegetation, J. Photogram. Remote Sens., 82, 83, 10.1016/j.isprsjprs.2013.04.007 Gandía, 2004, Retrieval of vegetation biophysical variables from Chris/Proba data in the SPARC campaing Glenn, 2008, Relationship between remotely-sensed vegetation indices, canopy attributes and plant physiological processes: what vegetation indices can and cannot tell us about the landscape, Sensors, 8, 2136, 10.3390/s8042136 Gonsamo, 2011, Normalized sensitivity measures for leaf area index estimation using three-band spectral vegetation indices, Int. J. Remote Sens., 32, 2069, 10.1080/01431161.2010.502153 Gu, 2013, NDVI saturation adjustment: a new approach for improving cropland performance estimates in the Greater Platte River Basin, USA, Ecol. Indic., 30, 1, 10.1016/j.ecolind.2013.01.041 Haboudane, 2004, Hyperspectral vegetation indices and novel algorithms for predicting green LAI of crop canopies: modeling and validation in the context of precision agriculture, Remote Sens. Environ., 90, 337, 10.1016/j.rse.2003.12.013 Heiskanen, 2013, Sensitivity of narrowband vegetation indices to boreal forest LAI, reflectance seasonality and species composition, ISPRS J. Photogr. Remote Sens., 78, 1, 10.1016/j.isprsjprs.2013.01.001 Houborg, 2007, Combining vegetation index and model inversion methods for the extraction of key vegetation biophysical parameters using Terra and Aqua MODIS reflectance data, Remote Sens. Environ., 106, 39, 10.1016/j.rse.2006.07.016 Jacquemoud, 2000, Comparison of four radiative transfer models to simulate plant canopies reflectance – direct and inverse mode, Remote Sens. Environ., 74, 471, 10.1016/S0034-4257(00)00139-5 Jonckheere, 2004, Review of methods for in situ leaf area index determination. Part I. Theories, sensors and hemispherical photography, Agric. For. Meteorol., 121, 19, 10.1016/j.agrformet.2003.08.027 Koltunov, 2009, Selective logging changes forest phenology in the Brazilian Amazon: evidence from MODIS image time series analysis, Remote Sens. Environ., 113, 2431, 10.1016/j.rse.2009.07.005 Kokaly, 2009, Characterizing canopy biochemistry from imaging spectrometer data for studying ecosystem processes, Remote Sens. Environ., 113, S78, 10.1016/j.rse.2008.10.018 Li, 2013, Developing and validating novel hyperspectral indices for leaf area index estimation: effect of canopy vertical heterogeneity, Ecol. Indic., 32, 123, 10.1016/j.ecolind.2013.03.025 Mishra, 2014, Estimating fractional land cover in semi-arid central Kalahari: the impact of mapping method (spectral unmixing vs. object-based image analysis) and vegetation morphology, Geocarto Int., 10.1080/10106049.2013.868041 Myneni, 2002, Global products of vegetation leaf area and fraction absorbed PAR from year one of MODIS data, Remote Sens. Environ., 83, 214, 10.1016/S0034-4257(02)00074-3 Nagler, 2000, Plant litter and soil reflectance, Remote Sens. Environ., 71, 207, 10.1016/S0034-4257(99)00082-6 Othman, 2014, Remote sensing used to detect moisture status of pecan orchards grown in a desert environment, Int. J. Remote Sens., 35, 949, 10.1080/01431161.2013.873834 Richter, 2001, Atmospheric correction methodology for imaging spectrometer data Rivera, 2013, Multiple cost functions and regularization options for improved retrieval of leaf chlorophyll content and LAI through inversion of the PROSAIL model, Remote Sens., 5, 3280, 10.3390/rs5073280 Romero, 2012, Estimation of dry matter content in leaves using normalized indexes and PROSPECT model inversion, Int. J. Remote Sens., 33, 396, 10.1080/01431161.2010.532819 Rouse, 1973, Monitoring vegetation systems in the Great Plains with ERTS, 309 Stagakis, 2010, Monitoring canopy biophysical and biochemical parameters in ecosystem scale using satellite hyperspectral imagery: an application on a Phlomis fruticosa Mediterranean ecosystem using multiangular CHRIS/PROBA observations, Remote Sens. Environ., 114, 977, 10.1016/j.rse.2009.12.006 Serrano, 2000, Deriving water content of chaparral vegetation from AVIRIS data, Remote Sens. Environ., 74, 570, 10.1016/S0034-4257(00)00147-4 Thenkabail, 2013, Selection of hyperspectral narrowbands (HNBs) and composition of hyperspectral twoband vegetation indices (HVIs) for biophysical characterization and discrimination of crop types using field reflectance and hyperion/EO-1 data, IEEE J. Sel. Topics Appl. Earth Observ. Remote Sens., 6, 427, 10.1109/JSTARS.2013.2252601 Ustin, 2009, Retrieval of foliar information about plant pigment systems from high resolution spectroscopy, Remote Sens. Environ., 113, S67, 10.1016/j.rse.2008.10.019 Verhoef, 2007, Coupled soil–leaf-canopy and atmosphere radiative transfer modeling to simulate hyperspectral multi-angular surface reflectance and TOA radiance data, Remote Sens. Environ., 109, 166, 10.1016/j.rse.2006.12.013 Verrelst, 2013, Gaussian process retrieval of chlorophyll content from imaging spectroscopy data, IEEE J. Select. Top. Appl. Earth Obs. Remote Sens., 6 Verrelst, 2012, Machine learning regression algorithms for biophysical parameter retrieval: opportunities for Sentinel-2 and -3, Remote Sens. Environ., 118, 127, 10.1016/j.rse.2011.11.002 Verrelst, 2008, Angular sensitivity analysis of vegetation indices derived from CHRIS/PROBA data, Remote Sens. Environ., 112, 2341, 10.1016/j.rse.2007.11.001 Verrelst, 2010, Effects of woody elements on simulated canopy reflectance: implications for forest chlorophyll content retrieval, Remote Sens. Environ., 114, 647, 10.1016/j.rse.2009.11.004 Vuichard, 2007, Estimating the greenhouse gas fluxes of European grasslands with a process-based model: 1. Model evaluation from in situ measurements, Global Biogeochem. Cycles, 21 Wang, 2013, Remote sensing of fuel moisture content from ratios of narrow-band vegetation water and dry-matter indices, Remote Sens. Environ., 1129, 103, 10.1016/j.rse.2012.10.027 Welles, 1991, Instrument for indirect measurement of canopy architecture, Agron. J., 83, 818, 10.2134/agronj1991.00021962008300050009x Yang, 2006, MODIS leaf area index products: from validation to algorithm improvement, IEEE Trans. Geosci. Remote Sens., 44, 1885, 10.1109/TGRS.2006.871215 Zheng, 2013, Multitemporal remote sensing of crop residue cover and tillage practices: a validation of the minNDTI strategy in the United States, J. Soil Water Conserv., 68, 120, 10.2489/jswc.68.2.120 Zheng, 2014, Remote sensing of crop residue and tillage practices: present capabilities and future prospects, Soil Tillage Res., 138, 26, 10.1016/j.still.2013.12.009 Zheng, 2009, Retrieving leaf area index (LAI) using remote sensing: theories, methods and sensors, Sensors, 9, 2719, 10.3390/s90402719