Automated hyperspectral vegetation index retrieval from multiple correlation matrices with hypercor
暂无分享,去创建一个
Helge Aasen | Yuxin Miao | G. Bareth | Martin L. Gnyp | Y. Miao | G. Bareth | M. Gnyp | H. Aasen
[1] Prasad S. Thenkabail,et al. Nondestructive Estimation of Foliar Pigment (Chlorophylls, Carotenoids, and Anthocyanins) Contents: Evaluating a Semianalytical Three-Band Model , 2016 .
[2] Elizabeth M. Middleton,et al. 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 , 2013, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.
[3] C. Milesi,et al. Assessing future risks to agricultural productivity, water resources and food security: How can remote sensing help? , 2012 .
[4] N. Fageria,et al. LOWLAND RICE GROWTH AND DEVELOPMENT AND NUTRIENT UPTAKE DURING GROWTH CYCLE , 2013 .
[5] John R. Miller,et al. Hyperspectral vegetation indices and novel algorithms for predicting green LAI of crop canopies: Modeling and validation in the context of precision agriculture , 2004 .
[6] P. Thenkabail,et al. Hyperspectral Vegetation Indices and Their Relationships with Agricultural Crop Characteristics , 2000 .
[7] Tim R. McVicar,et al. Current and potential uses of optical remote sensing in rice-based irrigation systems: a review , 2004 .
[8] C. Justice,et al. Development of vegetation and soil indices for MODIS-EOS , 1994 .
[9] Fumin Wang,et al. Relationship between Narrow Band Normalized Deference Vegetation Index and Rice Agronomic Variables , 2004 .
[10] Timothy J. Malthus,et al. The Fields of View and Directional Response Functions of Two Field Spectroradiometers , 2012, IEEE Transactions on Geoscience and Remote Sensing.
[11] L. Plümer,et al. Development of spectral indices for detecting and identifying plant diseases , 2013 .
[12] C. Tucker. Red and photographic infrared linear combinations for monitoring vegetation , 1979 .
[13] John R. Miller,et al. Integrated narrow-band vegetation indices for prediction of crop chlorophyll content for application to precision agriculture , 2002 .
[14] C. Jordan. Derivation of leaf-area index from quality of light on the forest floor , 1969 .
[15] A. Huete,et al. Hyperspectral versus multispectral crop-productivity modeling and type discrimination for the HyspIRI mission , 2013 .
[16] Christoph Hütt,et al. Rice monitoring with multi-temporal and dual-polarimetric TerraSAR-X data , 2013, Int. J. Appl. Earth Obs. Geoinformation.
[17] Alfredo Huete,et al. Advances in hyperspectral remote sensing of vegetation and agricultural croplands: Chapter 1 , 2011 .
[18] J. Muller,et al. Terrestrial remote sensing science and algorithms planned for EOS/MODIS , 1994 .
[19] Yuxin Miao,et al. Combining chlorophyll meter readings and high spatial resolution remote sensing images for in-season site-specific nitrogen management of corn , 2008, Precision Agriculture.
[20] M. S. Moran,et al. Opportunities and limitations for image-based remote sensing in precision crop management , 1997 .
[21] Georg Bareth,et al. Analysis of crop reflectance for estimating biomass in rice canopies at different phenological stages , 2013 .
[22] Nigel P. Fox,et al. Progress in Field Spectroscopy , 2006 .
[23] Andrea Ciampalini,et al. Two GUIs-based analysis tool for spectroradiometer data pre-processing , 2013, Earth Science Informatics.
[24] S. Ghosh,et al. Development of an agricultural crops spectral library and classification of crops at cultivar level using hyperspectral data , 2007, Precision Agriculture.
[25] M. Ashton,et al. Accuracy assessments of hyperspectral waveband performance for vegetation analysis applications , 2004 .
[26] H. J. Chauhan,et al. Development of Agricultural Crops Spectral Library and Classification of Crops Using Hyperion Hyperspectral Data , 2013 .
[27] M. Boschetti,et al. Plant nitrogen concentration in paddy rice from field canopy hyperspectral radiometry , 2009 .
[28] M. Ashton,et al. Hyperion, IKONOS, ALI, and ETM+ sensors in the study of African rainforests , 2004 .
[29] Georg Bareth,et al. Remotely detecting canopy nitrogen concentration and uptake of paddy rice in the Northeast China Plain , 2013 .
[30] Shanyu Huang,et al. Non-destructive estimation of rice plant nitrogen status with Crop Circle multispectral active canopy sensor , 2013 .
[31] S. Ustin,et al. Hyperspectral canopy sensing of paddy rice aboveground biomass at different growth stages , 2014 .
[32] Georg Bareth,et al. Evaluating hyperspectral vegetation indices for estimating nitrogen concentration of winter wheat at different growth stages , 2010, Precision Agriculture.
[33] 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 .
[34] A. Gitelson,et al. Signature Analysis of Leaf Reflectance Spectra: Algorithm Development for Remote Sensing of Chlorophyll , 1996 .
[35] D. Mulla. Twenty five years of remote sensing in precision agriculture: Key advances and remaining knowledge gaps , 2013 .
[36] A. Skidmore,et al. Narrow band vegetation indices overcome the saturation problem in biomass estimation , 2004 .
[37] Y. Miao,et al. Evaluating Multispectral and Hyperspectral Satellite Remote Sensing Data for Estimating Winter Wheat Growth Parameters at Regional Scale in the North China Plain , 2010 .
[38] J. G. Lyon,et al. Hyperspectral Vegetation Indices , 2016 .
[39] Yoshiki Yamagata,et al. Spectral Observations for Estimating the Growth and Yield of Rice , 1989 .
[40] A. Skidmore,et al. Predicting in situ pasture quality in the Kruger National Park, South Africa, using continuum-removed absorption features , 2004 .
[41] John H. Prueger,et al. Value of Using Different Vegetative Indices to Quantify Agricultural Crop Characteristics at Different Growth Stages under Varying Management Practices , 2010, Remote. Sens..
[42] J. G. Lyon,et al. Hyperspectral Remote Sensing of Vegetation and Agricultural Crops: Knowledge Gain and Knowledge Gap After 40 Years of Research , 2011 .
[43] M. Shibayama,et al. Seasonal visible, near-infrared and mid-infrared spectra of rice canopies in relation to LAI and above-ground dry phytomass , 1989 .