Separating Crop Species in Northeastern Ontario Using Hyperspectral Data
暂无分享,去创建一个
[1] Wen-Shin Lin,et al. Classifying cultivars of rice (Oryza sativa L.) based on corrected canopy reflectance spectra data using the orthogonal projections to latent structures (O-PLS) method , 2012 .
[2] J. Qi,et al. A comparative analysis of broadband and narrowband derived vegetation indices in predicting LAI and CCD of a cotton canopy , 2007 .
[3] Xin Huang,et al. Wavelength selection and spectral discrimination for paddy rice, with laboratory measurements of hyperspectral leaf reflectance , 2011 .
[4] Noel D.G. White,et al. Feasibility of near-infrared hyperspectral imaging to differentiate Canadian wheat classes , 2008 .
[5] N. R. Rao,et al. RETRACTED ARTICLE: Development of a crop‐specific spectral library and discrimination of various agricultural crop varieties using hyperspectral imagery , 2008 .
[6] David Riaño,et al. Assessing the potential of hyperspectral remote sensing for the discrimination of grassweeds in winter cereal crops , 2011 .
[7] N. Broge,et al. Comparing prediction power and stability of broadband and hyperspectral vegetation indices for estimation of green leaf area index and canopy chlorophyll density , 2001 .
[8] D. Haboudane,et al. ESTIMATION OF LEAF AREA INDEX USING GROUND SPECTRAL MEASUREMENTS OVER AGRICULTURE CROPS : PREDICTION CAPABILITY ASSESSMENT OF OPTICAL INDICES , 2004 .
[9] P. Thenkabail,et al. Hyperspectral Vegetation Indices and Their Relationships with Agricultural Crop Characteristics , 2000 .
[10] K. Dean,et al. Mapping recent lava flows at Westdahl Volcano, Alaska, using radar and optical satellite imagery , 2004 .
[11] Eileen Krakar,et al. AN OVERVIEW OF THE CANADIAN AGRICULTURE AND AGRI- FOOD SYSTEM , 2004 .
[12] H. Kage,et al. Analysis of vegetation indices derived from hyperspectral reflection measurements for estimating crop canopy parameters of oilseed rape (Brassica napus L.) , 2008 .
[13] John R. Miller,et al. Integrated narrow-band vegetation indices for prediction of crop chlorophyll content for application to precision agriculture , 2002 .
[14] J. Kovacs,et al. The influence of seasonality in estimating mangrove leaf chlorophyll-a content from hyperspectral data , 2013, Wetlands Ecology and Management.
[15] Yuan Wang,et al. Validation of artificial neural network techniques in the estimation of nitrogen concentration in rape using canopy hyperspectral reflectance data , 2009 .
[16] Yubin Lan,et al. Differentiation of Cotton from Other Crops at Different Growth Stages Using Spectral Properties and Discriminant Analysis , 2012 .
[17] Tsuyoshi Akiyama,et al. Estimating grain yield of maturing rice canopies using high spectral resolution reflectance measurements , 1991 .
[18] K. McGwire,et al. Hyperspectral mixture modeling for quantifying sparse vegetation cover in arid environments. , 2000 .
[19] Rama Rao Nidamanuri,et al. Transferring spectral libraries of canopy reflectance for crop classification using hyperspectral remote sensing data , 2011 .
[20] Francisca López-Granados,et al. Spectral discrimination of Ridolfia segetum and sunflower as affected by phenological stage , 2006 .
[21] N. Broge,et al. Deriving green crop area index and canopy chlorophyll density of winter wheat from spectral reflectance data , 2002 .
[22] J. Six,et al. Object-based crop identification using multiple vegetation indices, textural features and crop phenology , 2011 .
[23] Sushma Panigrahy,et al. Discrimination of Spectrally-Close Crops Using Ground-Based Hyperspectral Data , 2011 .
[24] G. A. Blackburn,et al. Towards the Remote Sensing of Matorral Vegetation Physiology : Relationships between Spectral Reflectance, Pigment, and Biophysical Characteristics of Semiarid Bushland Canopies. , 1999 .
[25] Yubin Lan,et al. Discriminating among Cotton Cultivars with Varying Leaf Characteristics Using Hyperspectral Radiometry , 2012 .
[26] M. Ashton,et al. Accuracy assessments of hyperspectral waveband performance for vegetation analysis applications , 2004 .
[27] Prasad S. Thenkabail,et al. Evaluation of Narrowband and Broadband Vegetation Indices for Determining Optimal Hyperspectral Wavebands for Agricultural Crop Characterization , 2002 .
[28] Zhan-yu Liu,et al. Estimation of vegetation biophysical parameters by remote sensing using radial basis function neural network , 2007 .
[29] Lori M. Bruce,et al. Utility of Hyperspectral Reflectance for Differentiating Soybean (Glycine max) and Six Weed Species , 2009, Weed Technology.
[30] Prasad S. Thenkabail,et al. Biophysical and yield information for precision farming from near-real-time and historical Landsat TM images , 2003 .
[31] Kathleen Kittson,et al. An Overview of the Canadian Agriculture and Agri-Food System , 2008 .
[32] 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 .
[33] J. Qi,et al. Identification of red and NIR spectral regions and vegetative indices for discrimination of cotton nitrogen stress and growth stage , 2005 .
[34] Sakae Shibusawa,et al. Field-derived spectral characteristics to classify conventional and conservation agricultural practices , 2007 .
[35] Jingfeng Huang,et al. Application of neural networks to discriminate fungal infection levels in rice panicles using hyperspectral reflectance and principal components analysis , 2010 .
[36] Clement Atzberger,et al. LAI and chlorophyll estimation for a heterogeneous grassland using hyperspectral measurements , 2008 .
[37] R. Bro,et al. Exploratory study of winter wheat reflectance during vegetative growth using three‐mode component analysis , 2006 .
[38] J. R. Jensen. Remote Sensing of the Environment: An Earth Resource Perspective , 2000 .
[39] Mark P. Wachowiak,et al. Relationship between Hyperspectral Measurements and Mangrove Leaf Nitrogen Concentrations , 2013, Remote. Sens..
[40] Heather McNairn,et al. Estimating and mapping crop residues cover on agricultural lands using hyperspectral and IKONOS data , 2006 .