- Agrawal G, Sarup J. 2011. Comparision of QUAC and FLAASH atmospheric correction modules on EO-1 Hyperion data of Sanchi. Int J Adv Eng Sci Technol. 4:178–186.
- Ashoori H, Fahimnejad H, Alimohammadi A, Soofbaf SR. 2008. Evaluation of the usefulness of texture measures for crop type classification by Hyperion data. Proc Int Arch Photogramm Rem Sens Spat Inform Sci. 37:999–1006.
- Bhojaraja BE, Hegde G, Pruthviraj U, Shetty A, Nagaraj MK. 2015. Mapping agewise discrimination of arecanut crop water requirement using hyperspectral remote sensing. International Conference on Water Resources, Coastal and Ocean Engineering ICWRCOE 2015.
- Foody GM, Mathur A. 2004. A relative evaluation of multiclass image classification by support vector machines. IEEE Trans Geosci Remote Sens. 42:1335–1343.
- Galvao LS, Formaggio AR, Tisot DA. 2005. Discrimination of sugarcane varieties in Southeastern Brazil with EO-1 Hyperion data. Remote Sens Environ. 94:523–534.
- Herold M, Roberts DA, Gardner ME, Dennison PE. 2004. Spectrometry for urban area remote sensing – Development and analysis of a spectral library from 350 to 2400 nm. Remote Sens Environ. 91:304–319.
- Joevivek V, Hemalatha T, Soman ST. 2009. Determining an efficient supervised classification method for hyperspectral image. IEEE International Conference on Advances in Recent Technologies in Communication and Computing. 384–386.
- Mahesha A, Abdul Khader KB, Ranganna G. 1990. Consumptive use and irrigation requirement of arecanut palm (Areca Catechu). Indian Journal of Agricultural Sciences. 60:609–611.
- Mountrakis G, Im J, Ogole C. 2011. Support vector machines in remote sensing: a review. ISPRS J Photogramm Remote Sens. 66:247–259.
- Nidamanuri RR, Zbell B. 2012. Existence of characteristic spectral signatures for agricultural crops – potential for automated crop mapping by hyperspectral imaging. Geocarto Int. 27:103–118.
- Petropoulos George P, Vadrevu Krishna Prasad, Kalaitzidis Chariton. 2013. Spectral angle mapper and object-based classification combined with hyperspectral remote sensing imagery for obtaining land use/cover mapping in a Mediterranean region. Geocarto Int. 28:114–129.
- Rao NR, Garg PK, Ghosh SK. 2007. Development of an agricultural crops spectral library and classification of crops at cultivar level using hyperspectral data. Precision Agric. 8:173–185.
- Sahoo RN, Ray SS, Manjunath KR. 2015. Hyperspectral remote sensing of agriculture. Curr Sci. 108:848.
- Somdatta C, Chakrabarti S. 2011. Preprocessing of hyperspectral data: a case study of Henry and Lothian Islands in Sunderban region, West Bengal, India. Int J Geomat Geosci. 2: 2–l
- Song Shalei, Gong Wei, Zhu Bo, Huang Xin. 2011. Wavelength selection and spectral discrimination for paddy rice, with laboratory measurements of hyperspectral leaf reflectance. ISPRS J Photogramm Rem Sens. 66:672–682.
- Thenkabail PS, Lyon JG, Huete A. 2011. Hyperspectral remote sensing of vegetation. CRC Press: Taylor and Francis.
- Younan NH, King RL, Bennett HH Jr. 2004. Classification of hyperspectral data: a comparative study. Precis Agric. 5:41–53.
- Zhang C, Qiu F. 2012. Mapping individual tree species in an urban forest using airborne lidar data and hyperspectral imagery. Photogramm Eng Remote Sens. 78:1079–1087.
- Choose new content alerts to be informed about new research of interest to you
- Easy remote access to your institution's subscriptions on any device, from any location
- Save your searches and schedule alerts to send you new results
- Export your search results into a .csv file to support your research