Informative spectral bands for remote green LAI estimation in C3 and C4 crops
暂无分享,去创建一个
[1] J. G. Lyon,et al. Hyperspectral Vegetation Indices , 2016 .
[2] Jan G. P. W. Clevers,et al. Optical remote sensing and the retrieval of terrestrial vegetation bio-geophysical properties - A review , 2015 .
[3] T. Jarmer,et al. Comparison of different regression models and validation techniques for the assessment of wheat leaf area index from hyperspectral data , 2015 .
[4] Zhihao Qin,et al. Estimation of Crop LAI using hyperspectral vegetation indices and a hybrid inversion method , 2015 .
[5] James Hansen,et al. Anatomy of a local-scale drought: Application of assimilated remote sensing products, crop model, and statistical methods to an agricultural drought study , 2015 .
[6] Anatoly A. Gitelson,et al. Non-destructive estimation of foliar chlorophyll and carotenoid contents: Focus on informative spectral bands , 2015, Int. J. Appl. Earth Obs. Geoinformation.
[7] Bangqian Chen,et al. Spatio-temporal prediction of leaf area index of rubber plantation using HJ-1A/1B CCD images and recurrent neural network , 2015 .
[8] José F. Moreno,et al. rown and green LAI mapping through spectral indices , 2014 .
[9] Reuben Nilus,et al. The relationship between leaf area index and microclimate in tropical forest and oil palm plantation: Forest disturbance drives changes in microclimate , 2015, Agricultural and forest meteorology.
[10] A. Gitelson,et al. Estimating green LAI in four crops: Potential of determining optimal spectral bands for a universal algorithm , 2014 .
[11] Jing M. Chen,et al. Continuous observation of leaf area index at Fluxnet-Canada sites , 2014 .
[12] A. Gitelson,et al. Near real-time prediction of U.S. corn yields based on time-series MODIS data , 2014 .
[13] Anatoly A. Gitelson,et al. Elements of an Integrated Phenotyping System for Monitoring Crop Status at Canopy Level , 2014 .
[14] Bo-Hui Tang,et al. Inversion of the PROSAIL model to estimate leaf area index of maize, potato, and sunflower fields from unmanned aerial vehicle hyperspectral data , 2014, Int. J. Appl. Earth Obs. Geoinformation.
[15] Jan G. P. W. Clevers,et al. Remote estimation of crop and grass chlorophyll and nitrogen content using red-edge bands on Sentinel-2 and -3 , 2013, Int. J. Appl. Earth Obs. Geoinformation.
[16] Michael J. O. Pocock,et al. The robustness of a network of ecological networks to habitat loss. , 2013, Ecology letters.
[17] L. Alonso,et al. A red-edge spectral index for remote sensing estimation of green LAI over agroecosystems , 2013 .
[18] Sharon Phillips,et al. Compilation and interpretation of photochemical model performance statistics published between 2006 and 2012 , 2012 .
[19] A. Viña,et al. Green leaf area index estimation in maize and soybean: Combining vegetation indices to achieve maximal sensitivity , 2012 .
[20] E. Pattey,et al. Assessment of vegetation indices for regional crop green LAI estimation from Landsat images over multiple growing seasons , 2012 .
[21] A. Gitelson,et al. Remote estimation of crop gross primary production with Landsat data , 2012 .
[22] C. Atzberger,et al. Spatially constrained inversion of radiative transfer models for improved LAI mapping from future Sentinel-2 imagery , 2012 .
[23] 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.
[24] Frédéric Baret,et al. Forcing a wheat crop model with LAI data to access agronomic variables: Evaluation of the impact of model and LAI uncertainties and comparison with an empirical approach , 2012 .
[25] A. Viña,et al. Comparison of different vegetation indices for the remote assessment of green leaf area index of crops , 2011 .
[26] A. Skidmore,et al. Mapping grassland leaf area index with airborne hyperspectral imagery : a comparison study of statistical approaches and inversion of radiative transfer models , 2011 .
[27] Michael E. Schaepman,et al. Retrieval of foliar information about plant pigment systems from high resolution spectroscopy , 2009 .
[28] A. Gitelson,et al. Application of Spectral Remote Sensing for Agronomic Decisions , 2008 .
[29] 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 .
[30] W. Cai,et al. A variable selection method based on uninformative variable elimination for multivariate calibration of near-infrared spectra , 2008 .
[31] Andrew E. Suyker,et al. Annual carbon dioxide exchange in irrigated and rainfed maize-based agroecosystems , 2005 .
[32] Anatoly A. Gitelson,et al. Collecting Spectral Data over Cropland Vegetation Using Machine-Positioning versus Hand-Positioning of the Sensor , 2004 .
[33] Richard G. Brereton,et al. Chemometrics: Data Analysis for the Laboratory and Chemical Plant , 2003 .
[34] A. Viña,et al. Remote estimation of leaf area index and green leaf biomass in maize canopies , 2003 .
[35] Simon Haykin,et al. Neural Networks: A Comprehensive Foundation , 1998 .
[36] A. Huete,et al. A comparison of vegetation indices over a global set of TM images for EOS-MODIS , 1997 .
[37] D. Massart,et al. Elimination of uninformative variables for multivariate calibration. , 1996, Analytical chemistry.
[38] Anatoly A. Gitelson,et al. Why and What for the Leaves Are Yellow in Autumn? On the Interpretation of Optical Spectra of Senescing Leaves (Acerplatanoides L.)* , 1995 .
[39] A. Gitelson,et al. Spectral reflectance changes associated with autumn senescence of Aesculus hippocastanum L. and Acer platanoides L. leaves. Spectral features and relation to chlorophyll estimation , 1994 .
[40] D. M. Moss,et al. Red edge spectral measurements from sugar maple leaves , 1993 .
[41] Claus Buschmann,et al. In vivo spectroscopy and internal optics of leaves as basis for remote sensing of vegetation , 1993 .
[42] H. Mohr,et al. ABSORPTION SPECTRA OF LEAVES CORRECTED FOR SCATTERING and DISTRIBUTIONAL ERROR: A RADIATIVE TRANSFER and ABSORPTION STATISTICS TREATMENT , 1993 .
[43] C. Daughtry,et al. Spectral estimates of absorbed radiation and phytomass production in corn and soybean canopies , 1992 .
[44] J. Dungan,et al. Exploring the relationship between reflectance red edge and chlorophyll content in slash pine. , 1990, Tree physiology.
[45] G. Asrar,et al. Estimating Absorbed Photosynthetic Radiation and Leaf Area Index from Spectral Reflectance in Wheat1 , 1984 .
[46] D. Horler,et al. The red edge of plant leaf reflectance , 1983 .
[47] C. Tucker. Red and photographic infrared linear combinations for monitoring vegetation , 1979 .
[48] C. Tucker. Asymptotic nature of grass canopy spectral reflectance. , 1977, Applied optics.
[49] C. Jordan. Derivation of leaf-area index from quality of light on the forest floor , 1969 .
[50] J. Ayars,et al. Long-rotation sugarcane in Hawaii sustains high carbon accumulation and radiation use efficiency in 2nd year of growth , 2015 .
[51] F. M. Danson,et al. RED-EDGE RESPONSE TO FOREST LEAF-AREA INDEX (VOL 16, PG 183, 1995) , 1995 .
[52] J. Dungan,et al. The effect of a red leaf pigment on the relationship between red edge and chlorophyll concentration , 1991 .
[53] J. A. Schell,et al. Monitoring vegetation systems in the great plains with ERTS , 1973 .
[54] D. Watson. Comparative Physiological Studies on the Growth of Field Crops: I. Variation in Net Assimilation Rate and Leaf Area between Species and Varieties, and within and between Years , 1947 .