Some features of the use of emission detectors in on-board hyperspectrometers

1Donets, VV, 2Muravskiy, LI
1Corporation «Research and Production Enterprise «Arsenal», Kyiv, Ukraine
2Karpenko Physico-Mechanical Institute of the National Academy of Science of Ukraine, L’viv, Ukraine
Kosm. nauka tehnol. 2012, 18 ;(3):20–37
Publication Language: Russian
We consider some features of the application of linear and matrix emission detectors in on-board air- and space-based hyperspectrometers (AVIRIS of the first and second generations, APEX, HYDICE, RESURS-P and others) for the spectrometric study of the Earth’s surface, for spectrometric data subsatellite validation and also in compact devices for the exploration of the Moon’s and Mars’ surfaces (M3, CRISM)
Keywords: on-board hyperspectrophotometers, validation
1.  Andrianov V. Yu. English-Russian Dictionary of geoinformatics. Retrieved from [in Russian].
2.  Andronov A. New satellite "Resurs-P" will not bring Russia into the lead, GIS-Association portal.  May 24, 2004, Retrieved from [in Russian].
3.  Arkhipov S. A., Lin'ko V. M., Baklanov A. I. et al. Hyperspectral instruments for the spacecraft "Resurs-P" and the prospects for its modernization,  Mater. All-Russian Sci.-Technical conference «Actual problems of rocket and space technology and its role in sustainable social development of society», Samara, 28 September —3 October 2009, P. 186 (Samara, 2009) [in Russian].
4.  Arkhipov S. A., Lin'ko V. M., Baklanov A. I. et al. Selection circuitry hyperspectral imaging opto-electronic devices for spacecraft "Resurs-P", Retrieved from  http://d33. [in Russian].
5.  Arkhipov S. A., Lin'ko V. M., Lukashevich E. L. Onboard videospektrometr "Sokol-GPC", Sixth All-Russian open annual Conf. "Modern problems of remote sensing of the Earth from space", Moscow, IKI RAN, 10—14 November 2008: Sb. tez. konf.  (Moscow, 2008).  Retrieved from [in Russian].
6. Arhipov S. A., Lin'ko V. M., Lukashevich E. L. Onboard videospektrometr "Sokol-GPC".  Retrieved from [in Russian].
7. Belov A.A., Behr P., Vorontsov D.V. et al. Distributed On-board Computer System Prototype (Moscow, 2004) (Preprint, Inst. Appl. Math., the Russian Academy of Science, Project No.2323)  Retrieved from [in Russian].
8. Bogomolov E. N., Vasilec N. V., Krivenkov B. E. et al. LED opto-electronic measuring size instrument "SENSOR".  Avtometrija,  N 5, 83—91 (1989). Retrieved from 5_Autometria/5_Archives/1989/5/83-91.pdf [in Russian].
9. Production spectrophotometer for field testing of vegetation. Retrieved from[in Ukrainian].
10. Vishnevskij G. I., Kossov V. G., Nesterov V. K. et al. Development and production of digital cameras and FPZS on its basis. Pt. I. Tele Foto Tehnika: Internet-zhurn. 01.11.2008. Retrieved from  [in Russian].
11. Vishnevskij G. I., Kossov V. G., Nesterov V. K. et al. Development and production of digital cameras and FPZS on its basis. Pt. II. Tele Foto Tehnika: Internet-zhurn. 04.06.2009. Retrieved from  [in Russian].
12. Voropaj E. S., Gulis I. M., Kupreev A. G., Kostjukevich A. G. Spectral devices based on the dispersion unit with a micro mirror array. (Minsk).  Retrieved from  [in Russian].
13. Kirilin A.N., Akhmetov R.N., Stratilatov N.P., et al. Resurs-P spacecraft. Geomatics, No.4, 23—26 (2010).  Retrieved from 2010_04/2010_04_004.pdf,  [in Russian].
14. Donets V.V. Substantiation of the Structure of hardware-software for remote sensing of vegetation in the field: Extended abstract of candidate’s thesis. 19 p. (Kyiv, 2010) [in Ukrainian].
15. Kondratin T. V., Kozoderov V. V., Topchiev A. G. et al. condition assessment technology objects natural and industrial environment according to the aerospace monitoring. (MPhTI, MSU, Institute Comput. Mathematics RAS, NPO «Lepton», Moscow, 2007) Retrieved from  http://d33.  [in Russian].
16. Kulev M. O., Baryshnikova E. V., Pavlov A. N. et al. Estimation of influence of heterogeneity of the CCD cell sensitivity to the source of fire origin sensor error. Polzunovsky vestnik, No. 3, 56 —58 (2007) Retrieved from  [in Russian].
17. Lapchuk V. P., Ivchenko V. N. Static visible range of the Fourier spectrometer for microsatellites. Second All-Russian open annual conference “Modern problems of remote sensing of the Earth from space”: Abstarcts.  (ISR RAS, Moscow, 2004).  Retrieved from  [in Russian].
18. The new Russian satellite distanced sensing "Resurs-P" will operate in orbit for at least five years. Novosti kosmonavtiki: Arhiv novostej. Is. 790 (2009)
19. Ovchinnikov A. M., Platonov A. K. Hyperspectral System of Mobile Robots. Photogr. Eng. and Remote Sens., 63 (7) (1997).  Retrieved from ppt/platonov.ppt [in Russian].
20. Orlov A. G. Development and research of aviation hyperspectrometer visible and near-infrared ranges: Extended abstract of candidate’s thesis, 26 p. (IKI RAN, Moscow, 2008)  Retrieved from [in Russian].
21. Popov M. A., Stankevich S. A., Koval'chuk S. P. et al. Features satellite hyperspectrometer in solving topical problems of natural resources, environment and disaster monitoring. Modern information technology management ecological safety, environmental, emergency measures: Proc. 8th International scientific-practical Conference, Kyiv, Kharkiv, AR Crimea, September 7—11, 2009. Retrieved from [in Russian].
22. Stempkovsky A., Shilin V. CMOS Photodiode LSI as an Advanced Base for a Single Chip Receiver and Processor System. Retrieved from [in Russian].
23.  The CCD array is different from the CMOS sensor? Retrieved from [in Russian].
24. Schowengerdt R.A. Remote Sensing. Models and Methods for Image Processing, 560 p. (Tehnosfera, Moscow, 2010) [in Russian].
25. Aikoi Mauri. Hyperspectral prism-grating-prism imaging spectrograph. (Finland ESPOO 2001). Retrieved from
27. Aksakal S. KOCAMAN sensor modeling and validation for linear array aerial and satellite imagery DISS. N 18120.  (Middle East Technical University, Turkey, 2008).  Retrieved from
28. ARTEMIS (Advanced Responsive Tactically Effective Military Imaging Spectrometer). Retrieved from sen ta tions/9911/14941.html#footback12%29
29. AVIRIS (Airborne Visible/Infrared Imaging Spectrometer) — eoPortal.  Retrieved from
30. Bai Yibin, Bajaj J., Beletic J. W., et al. Teledyne imaging sensors: Silicon CMOS imaging technologies for x-ray, UV, visible and near infrared. Retrieved from 20Paper%20_7021-01_.pdf
31. Bannari A., Chevrier M., Staenz K., McNairn H. Potential of hyperspectral indices for estimating crop residue cover. Rev. Télédétection, 7 (1-2-3-4), 447—463 (2007).  www.teledetection. net. Retrieved from  http://www.teledetection. net/upload/TELEDETECTION/pdf/20080527120832.pdf
32.  Bianco A. D., Serafino G., Spock G. An introduction to spectral imaging. Retrieved from
33. Bridges N. T. et al. Simulating CRISM and HIRESE data using airborn hyperspectral imagery. Lessons learned from ground truth, 41st Lunar and Planetary Science Conference. (2010). Retrieved from
34. CASI-2 sensor, Overview of Configuration & Specification. Retrieved from
35. CHAPTER 1 The Nature of Remote Sensing (Remote Sensing Models and Mechods for Imaging Processing by Robert Schowengerdt, (USA, 2007). Retrieved from 9780123694072/9780123694072.pdf
36. CRISM (Compact Reconnaissance Imaging Spectrometer for Mars. Retrieved from
37. Cristina Antonella Maria, Nathues Andreas, Eng Pascal, et. al. VIS-IR imaging spectrometer for MARCO POLO. Marco Polo Symposium (18—20 May 2009). Retrieved from cfm?fobjectid=45193
38. Cocks T., Jenssen R., Stewart A., et al. The HyMAPTM airborne hyperspectral sensor: the system, calibration and performance T.  Presented at 1st EARSEL Workshop on Imaging Spectroscopy, (October 1998, Zurich). Retrieved from
39. Cutter M. A. Compact high resolution imaging spectrometer (CHRIS).  Retrieved from
40. EnMAP hyperspectral imager (HSI). Retrieved from
41. Folientitel Kein EnMAP. Retrieved from workshops/4th_chris_proba/CHRIS_WS4_ KAUFMANN.pdf
42. FPGA-based CMOS Matrix Controller for Digital Camera. Retrieved from digital-camera-cmos-fpga.html
43. Gat N. Imaging Spectroscopy Using Tunable Filters: A Review. Proc. SPIE, 4056, 50—64 (2000).  Retrieved from
44. Green R., et al. Imaging spectroscopy and the airborne visible/infrared imaging spectrometer AVIRIS.  Remote Sens. Environ., 65, 227—248 (1998). Retrieved from ES6973/AVIRIS.pdf
45. Green R. O., et al. HysplRI Decadal Survey Mission Development Status. Decadal Survey Symposium (2009). decadal.gsfc.  Retrieved from  http://decadal.gsfc.
46. Hamlin L., Green R. O., Mouroulis P., et al. Imaging Spectrometer Science Measurements for Terrestrial Ecology: AVIRIS and the Next Generation AVIRIS Characteristics and Development Status. Jet Propulsion Laboratory, California Institute of Technology Pasadena, CA, 91109 22 June 2010.  NASA Earth Science Technology Forum. Retrieved from
47. HyMap DAIS Airborne Hyperspectral Scanner. www.op.dlr. Retrieved from  http://
48. Indium Antimonide Detectors. Teledyne Judson Technologies. LLC. USA. (2003)  Retrieved from
49. Infrared Focal Plane Arrays. Opt. and Photonics News, 19 (6), (June 2008). Retrieved from
50. Itres Research of Canada.  Retrieved from products/imagers/casi1500
51. Kempeneers P. Information Extraction from Hyperspectral Images. Antwerpen. (2007). Retrieved from
52. Kaufmann H., Segl K., Chabrillat S., et al. ENMAP — An advanced optical payload for Earth observation. Retrieved from 0382afb3-531e-42dc-9cca-368224d86478/ EnMAP—An-Advanced-Optical-Payload-for-Earth-Observation.pdf.aspx
53. Kaufmann H., Segl K., Chabrillat S., et al. ENMAP — An advanced hyperspectral mission.  Retrieved from 03_Kaufmann_31_34.pdf
54.  Kodak Digital Science KAC — 1310. Retrieved from
55. LUPA-1300-C-1. 3 M pixel high speed CMOS image sensor. Cypress Semiconductor.  Retrieved from
56. LUPA-4000: 4M Pixel CMOS image sensor. Cypress Semiconductor. Retrieved from  http://pdf1. LUPA-4000.html
57. Mouroulis P., Sellar R. G., Wilson D. W., et al. Optical design of a compact imaging spectrometer for planetary mineralogy. Opt. Eng., 46 (6) (2007). Retrieved from dspace/bitstream/2014/40926/1/06-1912.pdf.
58. Müller A. The new frontiers of hyperspectral imaging sensors. Retrieved from
59. Murchie S., Arvidson R., Bedini P. Compact reconnaissance imaging spectrometer for Mars (CRISM) on Mars reconnaissance orbiter (MRO). J. Geophys. Res., 112 (2007)  Retrieved from
60. Neural  network architectures for information extraction from hyper... Retrieved from hyper-spectral-images.pdf
61. Next Generation Airborne Visible/Infrared Imaging Spectrometer (AVIRISng). — Retrieved from
62. Nieke Jens, Kaiser J. W., Schläpfer D., et al. Calibration methodology for the Airborne Dispersive Pushbroom Imaging Spectrometer (APEX). Proc. SPIE, 5570 (2004).  Retrieved from
63. Nischan M. L., Kerekes J. P., Baum J. E., et. al. Analysis of HYDICE noise characteristics and their impact on subpixel object detection.  Proc. SPIE, 3753, 112—123 (1999). Retrieved from 3210/JKerekesConfProc07-19-1999.pdf
64. Ocean Optics, LVF-series Linear Variable Filters. Retrieved from lvfslinearvariablefilters.asp
65. Parameters of selectable CCD area array.  Retrieved from
66. Pearlman J. S., Barry P. S., Segal C. C., et al. Hyperion, a space-based imaging spectrometer. IEEE Trans. Geosci. Remote Sens., 41, 1160—1173 (2003).
67. Richardson B. S., Eastwood M. L., Bruce C. F., et al. Mercury-cadmium-telluride focal plane array performance under non-standard operating conditions. Aerospace Conf., P. 1—6 (March 2011).  Retrieved from  http://journals2.scholarsportal. info/details.xqy?uri=/1095323x/v2011inone/ 1_mfpapunoc.xml
68. Roden N. C., et al. Mineral Mapping and Applications of Imaging Spectroscopy. IG-
ARSS, (August 1, 2006). Retrieved from internet/grs/Workshops/Environmental_ Applications_Imaging_Spectroscopy/9_Clark_Mineral/Clark_Mineral.pdf
69.  Schaepman M., Alberti  E., Dell’Endice F., D’Odorico P. APEX Airborne Prism Experiment. Retrieved from
70. Schläpfer D., Kaiser J. W., Nieke J., et al. Modeling and correcting spatial non-uniformity of the APEX pushbroom imaging spectrometer. Retrieved from
71. SPECIM ImSpectors. Retrieved from media/pdf/imspector-data  sheets/vis-vnir-imspectors-ver1-2009.pdf
72. Semeniv O., Yatsenko V., Khandriga P., Shatokhina Yu. A hyperspectrometer for remote sensing of biochemical components in the vegetation.  37th COSPAR Scientific Assembly. 13—20 July 2008, in Montréal, Canada, P. 2806.  Retrieved from abs/2008cosp...37.2806S
73. Tong Q., Zhang B., Zheng L. Hyperspectral remote sensing technology and applications in China. Proc. of the 2nd CHRIS/Proba Workshop, ESA/ESRIN, Frascati, Italy 28—30 April 2004.  Retrieved from
74. The Airborne Imaging Spectrometer ROSIS. Retrieved from pdf/rosis-description.pdf
75. The AHS2005 Flight Campaign APEX.  Retrieved from
76. The DAIS 7915 System Specifications.  Retrieved from
77.  Turner W. Status of HyspIRI Mission. HyspIRI Sci. Symp., 2011, May 17—18.  Retrieved from 2011_Symposium/Summary_2011_HyspIRI_Symposium_2. pdf
78. Weatherup Cliff CCD and CMOS imaging Where are we? (12th May 2010).  Retrieved from uploads/2010/05/Cliff-Weatherup-Web-version.pdf
79. Wilson I. J., Cocks T. D. Development of the airborne reflective emissive spectrometer (ARES) A Progress Report.  Retrieved from workshops/imaging-spectroscopy-2003/papers/sensors_and_missions/wilson.pdf