Abstract
Imaging spectroscopy in the visible-to-shortwave infrared wavelength range (VSWIR), or nowadays more commonly known as ‘hyperspectral imaging’, for terrestrial Earth Observation remote sensing, dates back to the early 1980s when its development started with mainly airborne demonstrations. From its initial use as a research tool, imaging spectroscopy encompassing the VSWIR spectral range has gradually evolved towards operational and commercial applications. Today, it is one of the fastest growing research areas in remote sensing owing to its diagnostic power by means of discrete spectral bands that are contiguously sampled over the spectral range with which a target is observed. The main principles of imaging spectroscopy rely on the exploitation of light dispersion technologies to split the incoming light through a telescope before being projected onto detector arrays. The light dispersion can be achieved by using prism or diffractive grating optical systems, perpetually aiming for improved performances in terms of efficiency, straylight rejection, and polarization sensitivity. The sensor technique has been first used in airborne imaging spectroscopy since the early 1980s and later in spaceborne hyperspectral missions from the end of the 1990s onwards. Currently, several hyperspectral spaceborne systems are under development and in preparation to be launched within the next few years. Through hyperspectral remote sensing, physical, chemical, and biological components of the observed matter can be separated and resolved thus providing a spectral ‘fingerprint’. The analyses of the spectral absorptions often give rise to quantitative retrievals of components of the observed target. The derived information is vital for the generation of a wide variety of new quantitative products and services in the domain of agriculture, food security, raw materials, soils, biodiversity, environmental degradation and hazards, inland and coastal waters, snow hydrology and forestry. Many of these are relevant to various international policies and conventions. Originally developed as a powerful detection and analysis tool for applications predominantly related to planetary exploration and non-renewable resources, imaging spectroscopy now covers many disciplines in atmospheric, terrestrial vegetation, cryosphere, and marine research and application fields. There is an increasing number of visible/near-infrared (VNIR) imaging spectrometers emerging also as small payloads on small satellites and cubesats, built and launched by small-medium enterprises. These are targeted to address commercial applications mainly in agriculture, resources and environmental management, and hazard observations.
Similar content being viewed by others
References
ACCP (1994) “Accelerated canopy chemistry program final report to NASA-EOS-IWG”. In: Aber J (ed), Washington, DC http://daac.ornl.gov/ACCP/accp.html
Adão T, Hruška J, Pádua L, Bessa J, Peres E, Morais R, Sousa JJ (2017) Hyperspectral imaging: a review on UAV-based sensors, data processing and applications for agriculture and forestry. Remote Sens 9(11):1110
Apan A, Held A, Phinn S, Markley J (2003) Detecting sugarcane ‘orange rust’ disease using EO-1 hyperion hyperspectral imagery. Int J Remote Sens 25(2):489–498. https://doi.org/10.1080/01431160310001618031
Asner GP, Martin RE (2016) Convergent elevation trends in canopy chemical traits of tropical forests. Glob Change Biol 22:2216–2227. https://doi.org/10.1111/gcb.13164
Asner GP, Knapp DE, Kennedy-Bowdoin T, Jones MO, Martin RE, Boardman JW, Field CB (2007) Carnegie airborne observatory: in-flight fusion of hyperspectral imaging and waveform light detection and ranging for three-dimensional studies of ecosystems. J Appl Remote Sens 1(1):013536. https://doi.org/10.1117/1.2794018
Asner GP, Knapp DE, Balaji A, Páez-Acosta G (2009) Automated mapping of tropical deforestation and forest degradation: CLASlite. J Appl Remote Sens 3:033543. https://doi.org/10.1117/1.3223675
Asner GP, Knapp DE, Boardman J, Green RO, Kennedy-Bowdoin T, Eastwood M, Martin RE, Anderson C, Field CB (2012) Carnegie airborne observatory-2: increasing science data dimensionality via high-fidelity multi-sensor fusion. Remote Sens Environ 1(124):454–465. https://doi.org/10.1016/j.rse.2012.06.012
Asner GP, Martin RE, Knapp DE, Tupayachi R, Anderson CB, Sinca F, Vaughn NR, Llactayo W (2017) Airborne laser-guided imaging spectroscopy to map forest trait diversity and guide conservation. Science 355:385–389. https://doi.org/10.1126/science.aaj1987
Ben-Dor E, Chabrillat S, Demattê J, Taylor G, Hill J, Whiting M, Sommer S (2009) Using imaging spectroscopy to study soil properties. Remote Sens Environ 113:S38–S55
Bianchi R, Cavalli RM, Fiumi L, Marino CM, Pignatti S (1996) Airborne imaging spectrometry: a new approach to environmental problems. In: Proceeding of the XVIII ISPRS, pp128–132
Carrere V, Briottet X, Jacquemoud S, Marion R, Bourguignon A, Cham M, Dumont M, Minghelli-Roman A, Weber C, Lefevrefonollosa M-J, Mandea M (2013) “HYPXIM: a second generation high spatial resolution hyperspectral satellite for dual applications,” 2013 5th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS). Gainesville, FL 2013:1–4. https://doi.org/10.1109/WHISPERS.2013.8080685
Chabrillat S, Goetz AF, Krosley L, Olsen HW (2002) Use of hyperspectral images in the identification and mapping of expansive clay soils and the role of spatial resolution. Remote Sens Environ 82(2):431–445. https://doi.org/10.1016/S0034-4257(02)00060-3
Chang SH, Westfield MJ, Lehmann F, Oertel D, Richter R (1993) 79-channel airborne imaging spectrometer. In: Vane G (ed) Imaging spectrometry of the terrestrial environment, vol 1937. International Society for Optics and Photonics, Bellingham, pp 164–173. https://doi.org/10.1117/12.157053
Chang CI (2007) Hyperspectral data exploitation: theory and applications. Wiley, Hoboken
Chapin FS (1991) Integrated responses of plants to stress. Bioscience 41:29–36. https://doi.org/10.2307/1311538
CHIME mission advisory group (MAG) (2018) “Copernicus hyperspectral imaging mission requirements document” ESA-EOPSM-CHIM-MRD-3216, version 1.2
Chudnovsky A, Ben‐Dor E, Kostinski A, Koren I (2009) “Mineral content analysis of atmospheric dust using hyperspectral information from space.” Geophys Res Lett 36(15). https://doi.org/10.1029/2009GL037922
Clark RN, Swayze GA, Livo KE, Kokaly RF, Sutley SJ, Dalton JB, McDougal RR, Gent CA (2003) “Imaging spectroscopy: earth and planetary remote sensing with the USGS tetracorder and expert systems.” J Geophys Res Planets 108(E12). https://doi.org/10.1029/2002JE001847
Clark RN, Swayze GA, Hoefen TM, Green RO, Livo KE, Meeker GP, Sutley SJ, Plumlee GS, Pavri B, Sarture C (2005) Environmental mapping of the world trade center area with imaging spectroscopy after the September 11, 2001 attack. In: Vane G, Green RO, Chrien TG, Enmark HT, Hansen EG, Porter WM (eds) The airborne visible/infrared imaging spectrometer mapping. ACS Publications, Washington. https://doi.org/10.1021/bk-2006-0919.ch004
Cocks T, Jenssen R, Stewart A, Wilson I, Shields T (1998) The hymap airborne hyperspectral sensor: the system, calibration and performance. In: EARSEL workshop on imaging spectroscopy
Colombo R, Meroni M, Marchesi A, Busetto L, Rossini M, Giardino C, Panigada C (2008) Estimation of leaf and canopy water content in poplar plantations by means of hyperspectral indices and inverse modeling. Remote Sens Environ 112(1820–1834):20. https://doi.org/10.1016/j.rse.2007.09.005
Corson MR, DR Korwan, RL Lucke, WA Snyder, CO Davis (2008) The hyperspectral imager for the coastal ocean (HICO) on the international space station. In: Proceedings of international geoscience and remote sensing symposium (IGARSS’08). 4, pp I-101–I-104
Cutter MA (2006) The PROBA-1/CHRIS hyperspectral mission—five years since launch. In: Proceedings of the 4S symposium: small satellite systems and services, Chia Laguna Sardinia, Italy, Sept. 25–29, 2006, ESA SP-618
Dekker A, Pinnel N, Gege P, Briottet X, Peters S, Turpie K, Sterckx S, Costa M, Giardino C, Brando V (2018). Feasibility study of an Aquatic ecosystem earth observing system.” CEOS Report copyright CSIRO, Australia, http://ceos.org/document_management/Publications/CEOS_FS-Aquatic-Ecosystem-EO-System_v2.5_low-res_April2018.pdf
Del Bello U, Bezy JL, Fuchs J, Rast M (2003) System definition of the ESA earth explorer spectra mission. In: Lurie JB, Aten ML, Weber K (eds) Sensors, systems, and next-generation satellites VI, vol 4881. International Society for Optics and Photonics, Bellingham, pp 1–12. https://doi.org/10.1117/12.463003
Delwart S, Bourg L, Huot JP (2004) MERIS 1st year: early calibration results. In: Meynart R, Neeck S, Shimoda H, Habib S (eds) Sensors, systems, and next-generation satellites vii, vol 5234. International Society for Optics and Photonics, Bellingham, pp 379–391. https://doi.org/10.1117/12.508485
Dennison PE (2006) Fire detection in imaging spectrometer data using atmospheric carbon dioxide absorption. Int J Remote Sens 27(14):3049–3055. https://doi.org/10.1080/01431160600660871
Dozier J, Green RO, Nolin AW, Painter TH (2009) Interpretation of snow properties from imaging spectrometry. Remote Sens Environ 113:S25–S37. https://doi.org/10.1016/j.rse.2007.07.029
Drusch M, Del Bello U, Carlier S, Colin O, Fernandez V, Gascon F, Hoersch B, Isola C, Laberinti P, Martimort P, Meygret A (2012) Sentinel-2: ESA’S optical high-resolution mission for GMES operational services. Remote Sens Environ 120:25–36. https://doi.org/10.1016/j.rse.2011.11.026
e-GEOS (2018) Hyperspectral imaging mission concepts, ESA contract for ESA-ESRIN, e-GEOS-HYP-ES-0055, January 2018
Eismann MT (2012) Hyperspectral remote sensing. SPIE Press Book, Bellingham
Feingersh T, Ben-Dor E (2015) SHALOM–A commercial hyperspectral space mission. In: Qian SE (ed) Optical payloads for space missions. Wiley, Hoboken
Feng W, Zhu Y, Yao X, Tian YC, Cao WX (2008) Monitoring leaf nitrogen status with hyperspectral reflectance in wheat. Eur J Agron 28:394–404. https://doi.org/10.1016/j.eja.2007.11.005
Fernández-Renau A, Gómez JA, de Miguel E (2005) The INTA AHS system. In: Meynart R, Neeck S, Shimoda H, Habib S (eds) Sensors, systems, and next-generation satellites IX, vol 5978. International Society for Optics and Photonics, Bellingham. https://doi.org/10.1117/12.629440
Field CB, Chapin FS, Matson PA, Mooney HA (1992) Responses of the terrestrial ecosystems to changing atmosphere. Annu Rev Ecolol Syst 23:201–235
Gamon JA, Peñuelas J, Field CB (1992) A narrow-waveband spectral index that tracks diurnal changes in photosynthetic efficiency. Remote Sens Environ 41:35–44. https://doi.org/10.1016/0034-4257(92)90059-S
Gamon J, Serrano L, Surfus J (1997) The photochemical reflectance index: an optical indicator of photosynthetic radiation use efficiency across species, functional types, and nutrient levels. Oecologia 112:492–501
Gao BC, Goetz AFH (1995) Retrieval of equivalent water thickness and information related to biochemical components of vegetation canopies from AVIRIS data. Remote Sens Environ 52(3):155–162. https://doi.org/10.1016/0034-4257(95)00039-4
Gardner AS, Moholdt G, Cogley JG, Wouters B, Arendt AA, Wahr J, Berthier E, Hock R, Pfeffer WT, Kaser G, Ligtenberg SRM, Bolch T, Sharp MJ, Hagen JO, van den Broeke MR, Paul F (2013) A reconciled estimate of glacier contributions to sea level rise: 2003 to 2009. Science 340:852–857. https://doi.org/10.1126/science.1234532
Gege P, Beran D, Mooshuber W, Schulz J, van der Piepen H (1998) System analysis and performance of the new version of the imaging spectrometer ROSIS, In: Proc 1st EARSEL workshop on imaging spectroscopy, Zurich, pp 29–35
Giardino C, Brando VE, Gege P, Pinnel N, Hochberg E, Knaeps E, Reusen I, Doerffer R, Bresciani M, Braga F, Foerster S, Champollion N, Dekker A (2018) Imaging spectrometry of inland and coastal waters: state-of-the-art, achievements and perspectives. Surv Geophys. https://doi.org/10.1007/s10712-018-9476-0
Goetz AF, Vane G, Solomon JE, Rock BN (1985) Imaging spectrometry for earth remote sensing. Science 228(4704):1147–1153. https://doi.org/10.1126/science.228.4704.1147
Gomez C, Lagacherie P, Coulouma G (2008) Continuum removal versus PLSR method for clay and calcium carbonate content estimation from laboratory and airborne hyperspectral measurements. Geoderma 148(2):141–148. https://doi.org/10.1016/j.geoderma.2008.09.016
Gower JFR, Borstad GA, Anger CD, Edel HR (1992) CCD-based imaging spectroscopy for remote sensing: the FLI and CASI programs. Can J Remote Sens 18(4):199–208. https://doi.org/10.1080/07038992.1992.10855325
Green RO (1996) Estimation of biomass fire temperature and areal extent from calibrated AVIRIS spectra. http://hdl.handle.net/2014/25024
Green RO (2018) The earth surface mineral dust source investigation (EMIT) https://hyspiri.jpl.nasa.gov/downloads/2018_Workshop/day1/13_HyspIRI_EMIT_Overview_20180815b.pdf
Green RO, Painter TH, Roberts DA, Dozier J (2006) Measuring the three phases of water in a melting snow environment with an imaging spectrometer in the solar reflected spectrum. Water Resour Res
Green RO, Hook SJ, Middleton E, Turner W, Ungar S, Knox R (2013) The HyspIRI decadal survey mission: update on the mission concept and prepatory airborne science campaign. In: Proceedings of the international geoscience and remote sensing symposium (IGARSS’13), Melbourne, Australia, p 4
Guanter L, Richter R, Moreno J (2006) Spectral calibration of hyperspectral imagery using atmospheric absorption features. Appl Opt 45(10):2360–2370. https://doi.org/10.1364/AO.45.002360
Guanter L, Kaufmann H, Segl K, Förster S, Rogaß C, Chabrillat S, Küster T, Hollstein A, Rossner G, Chlebek C, Straif C, Fischer S, Schrader S, Storch T, Heiden U, Mueller A, Bachmann M, Mühle H, Müller R, Habermeyer M, Ohndorf A, Hill J, Buddenbaum H, Hostert P, van der Linden S, Leitão PJ, Rabe A, Doerffer R, Krasemann H, Xi H, Mauser W, Hank T, Locherer M, Rast M, Staenz K, Sang B (2015) The EnMAP spaceborne imaging spectroscopy mission for earth observation. Remote Sens 7(7):8830–8857. https://doi.org/10.3390/rs70708830
Hackwell JA, Warren DW, Bongiovi RP, Hansel SJ, Hayhurst TL, Mabry DJ, Sivjee MG, Skinner JW (1996) LWIR/MWIR imaging hyperspectral sensor for airborne and ground-based remote sensing. In: Lurie JB, Aten ML, Weber K (eds) Imaging spectrometry II, vol 2819. International Society for Optics and Photonics, Bellingham, pp 102–108. https://doi.org/10.1117/12.258057
Hall JL, Boucher RH, Gutierrez DJ, Hansel SJ, Kasper BP, Keim ER, Moreno NM, Polak ML, Sivjee MG, Tratt DM, Warren DW (2011) First flights of a new airborne thermal infrared imaging spectrometer with high area coverage. Infrared technology and applications XXXVII (Vol. 8012, p. 801203). International Society for Optics and Photonics. https://doi.org/10.1117/12.884865
Hedrick AR, Marks D, Havens S, Robertson M, Johnson M, Sandusky M, Marshall HP, Kormos PR, Bormann KJ, Painter TH (2018) Direct insertion of NASA airborne snow observatory-derived snow depth time series into the iSnobal energy balance snow model. Water Resour Res 54(10):8045–63
Heimann M, Reichstein M (2008) Terrestrial ecosystem carbon dynamics and climate feedbacks. Nature 451(7176):289–292. https://doi.org/10.1038/nature06591
Henn B, Painter TH, Bormann KJ, McGurk B, Flint AL, Flint LE, White V, Lundquist JD (2018) High-elevation evapotranspiration estimates during drought: using streamflow and NASA airborne snow observatory SWE observations to close the upper tuolumne river basin water balance. Water Resour Res 54(2):746–66
Hestir EL, Brando VE, Bresciani M, Giardino C, Matta E, Villa P, Dekker AG (2015) Measuring freshwater aquatic ecosystems: the need for a hyperspectral global mapping satellite mission. Remote Sens Environ 167:181–195. https://doi.org/10.1016/j.rse.2015.05.023
Hochberg EJ, Roberts DA, Dennison PE, Hulley GC (2015) Special issue on the hyperspectral infrared imager (HyspIRI): emerging science in terrestrial and aquatic ecology, radiation balance and hazards. Remote Sens Environ 167:1–5. https://doi.org/10.1016/j.rse.2015.06.011
Hook SJ, Johnson WR, Abrams MJ (2013) NASA’s hyperspectral thermal emission spectrometer (HyTES). In: Thermal infrared remote sensing. Springer, Dordrecht. 93–115 https://doi.org/10.1007/978-94-007-6639-6_5
Hunt GR (1980) Electromagnetic radiation: the communication link in remote sensing. Remote Sens Geol: 5–45
IPCC (2013): Summary for Policymakers. In: Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change [Stocker, T.F., D. Qin, G.-K. Plattner, M. Tignor, S. K. Allen, J. Boschung, A. Nauels, Y. Xia, V. Bex and P.M. Midgley (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA
Kampe TU, Johnson BR, Kuester MA, Keller M (2010) NEON: the first continental-scale ecological observatory with airborne remote sensing of vegetation canopy biochemistry and structure. J Appl Remote Sens 4(1):043510. https://doi.org/10.1117/1.3361375
Kieffer HH (1997) Photometric stability of the lunar surface. Icarus 130(2):323–327. https://doi.org/10.1006/icar.1997.5822
Kieffer HH, Jarecke PJ, Pearlman J (2002) Initial lunar calibration observations by the EO-1 hyperion imaging spectrometer. In: Imaging spectrometry VII 2002 Jan 17 (Vol. 4480, pp. 247-259). International Society for Optics and Photonics. https://doi.org/10.1117/12.453347
King TVV, Berger BR, Johnson MR (2014) Characterization of potential mineralization in Afghanistan: four permissive areas identified using imaging spectroscopy data, USGS Open-File Report 2014-1071, https://doi.org/10.3133/ofr20141071. https://doi.org/10.3133/ofr20141071
Kokaly RF, Rockwell BW, Haire SL, King TV (2007) Characterization of post-fire surface cover, soils, and burn severity at the Cerro Grande Fire, New Mexico, using hyperspectral and multispectral remote sensing. Remote Sens Environ 106(3):305–325. https://doi.org/10.1016/j.rse.2006.08.006
Kokaly RF, Asner GP, Ollinger SV, Martin ME, Wessman CA (2009) Characterizing canopy biochemistry from imaging spectroscopy and its application to ecosystem studies. Remote Sensing of Environment. 113:S78–S91. https://doi.org/10.1016/j.rse.2008.10.018
Kokaly RF, Couvillion BR, Holloway JM, Roberts DA, Ustin SL, Peterson SH, Khanna S, Piazza SC (2013) Spectroscopic remote sensing of the distribution and persistence of oil from the deepwater horizon spill in Barataria Bay marshes. Remote Sens Environ 129:210–230. https://doi.org/10.1016/j.rse.2012.10.028
Kraft S, Del Bello U, Harnisch B, Bouvet M, Drusch M, Bézy, JL (2017) Fluorescence imaging spectrometer concepts for the earth explorer mission candidate FLEX. In: International conference on space optics—ICSO 2012 International Society for Optics and Photonics. 10564, p 105641 https://doi.org/10.1117/12.2309086
Kunkel B, Harms J, Kummer U, Schmidt E, Del Bello U, Harnisch B, Meynart R (2000) Hyperspectral imager survey and developments for scientific and operational land processes monitoring applications. In: Observing land from space: science, customers and technology. Springer, Dordrecht. pp 303–327 https://doi.org/10.1007/0-306-48124-3_30
Lagacherie P, Baret F, Feret J-B, Netto JM, Robbez-Masson JM (2008) Estimation of soil clay and calcium carbonate using laboratory, field and airborne hyperspectral measurements. Remote Sens Environ 112(3):825–835. https://doi.org/10.1016/j.rse.2007.06.014
Lee KS, Cohen WB, Kennedy RE, Maiersperger TK, Gower ST (2004) Hyperspectral versus multispectral data for estimating leaf area index in four different biomes. Remote Sens Environ 91:508–520. https://doi.org/10.1016/j.rse.2004.04.010
Makisara K, Meinander M, Rantasuo M, Okkonen J, Aikio M, Sipola K (1993) Airborne imaging spectrometer for applications (AISA). In: Geoscience and Remote Sensing Symposium, IGARSS’93. Better understanding of earth environment, International (pp 479–481). IEEE. https://doi.org/10.1109/igarss.1993.322291
Martin ME, Aber JD (1997) “High spectral resolution remote sensing of forest canopy lignin, nitrogen, and ecosystem processes.” Ecology applications 7(2):431–443. https://doi.org/10.1890/1051-0761(1997)007%5b0431:HSRRSO%5d2.0.CO;2
Matsunaga T, Iwasaki A, Tsuchida S, Iwao K, Tanii J, Kashimura O, Nakamura R, Yamamoto H, Kato S, Obata K, Mouri K (2017) Current status of hyperspectral imager suite (HISUI) onboard international space station (ISS). In: Geoscience and remote sensing symposium (IGARSS), pp 443–446 https://doi.org/10.1109/igarss.2017.8126989
Middleton EM, Ungar SG, Mandl DJ, Ong L, Frye SW, Campbell PE, Landis DR, Young JP, Pollack NH (2013) The earth observing one (EO-1) satellite mission: over a decade in space. IEEE J Sel Top ApplEarth Obs Remote Sens 6(2):243–256. https://doi.org/10.1109/JSTARS.2013.2249496
Mielke C, Rogass C, Boesche N, Segl K, Altenberger U (2016) EnGeoMAP 2.0—automated hyperspectral mineral identification for the german EnMAP space mission. Remote Sens 8(2):127. https://doi.org/10.3390/rs8020127
Miglani SS, Pandey RR, Parihar JS (2008) Evaluation of EO-1 hyperion data for agricultural application. J Indian Soc Remote Sens 36:255–266. https://doi.org/10.1007/s12524-008-0026-y
Misra T (2017) Indian remote sensing sensor system: current and future perspective. In: Proceedings of the national academy of sciences, India section A: physical sciences, 87(4): pp 473–486. https://doi.org/10.1007/s40010-017-0429-7
Mouroulis P, Van Gorp B, Green RO, Dierssen H, Wilson DW, Eastwood M, Boardman J, Gao B-C, Cohen D, Franklin B, Loya F, Lundeen S, Mazer A, McCubbin I, Randall D, Richardson B, Rodriguez JI, Sarture C, Urquiza E, Vargas R, White V, Yee K (2014) The Portable Remote Imaging Spectrometer (PRISM) coastal ocean sensor: design, characteristics and first flight results, Appl. Opt. 53(7) 1363–1380 http://dx.doi/org/10.1364/AO.99.099999
Müller R, Avbelj J, Carmona E, Gerasch B, Graham L, Günther B, Heiden U, Kerr G, Knodt U, Krutz D, Krawczyk H (2016) The new hyperspectral sensor DESIS on the multi-payload platform MUSES installed on the ISS. The international archives of the photogrammetry. Remote Sens Spatial Inf Sci, 41, 461–467. https://doi.org/10.5194/isprsarchives-xli-b1-461-2016
Munné-Bosch S, Alegre L (2004) Die and let live: leaf senescence contributes to plant survival under drought stress. Funct Plant Biol 31(3):203–216. https://doi.org/10.1071/FP03236
Naegeli K, Damm A, Huss M, Schaepman M, Hoelzle M (2015) Imaging spectroscopy to assess the composition of ice surface materials and their impact on glacier mass balance. Remote Sens Environ 168:388–402
National Academies of Sciences, and Medicine (2018) “Thriving on our changing planet: a decadal strategy for earth observation from space,” Washington, DC
Ong CC, Cudahy TJ, Caccetta MS, Piggott MS (2003) Deriving quantitative dust measurements related to iron ore handling from airborne hyperspectral data. Mining Technol 112(3):158–163. https://doi.org/10.1179/037178403225003555
Painter TH, Duval B, Thomas WH, Mendez M, Heintzelman S, Dozier J (2001) Detection and quantification of snow algae with an airborne imaging spectrometer. Appl Environ Microbiol 67(11):5267–5272. https://doi.org/10.1128/AEM.67.11.5267-5272.2001
Painter TH, Dozier J, Roberts DA, Davis RE, Green RO (2003) Retrieval of subpixel snow-covered area and grain size from imaging spectrometer data. Remote Sens Environ 85(1):64–77. https://doi.org/10.1016/S0034-4257(02)00187-6
Painter TH, Seidel F, Bryant AC, Skiles SM, Rittger K (2013) Imaging spectroscopy of albedo and radiative forcing by light absorbing impurities in mountain snow. J Geophys Res Atmos 118(17):9511–9523. https://doi.org/10.1002/jgrd.50520
Painter TH, Berisford DF, Boardman JW, Bormann KJ, Deems JS, Gehrke F, Hedrick A, Joyce M, Laidlaw R, Marks D, Mattmann C (2016) The airborne snow observatory: fusion of scanning lidar, imaging spectrometer, and physically-based modeling for mapping snow water equivalent and snow albedo. Remote Sens Environ 31(184):139–152. https://doi.org/10.1016/j.rse.2016.06.018
Paz-Kagan T, Zaady E, Salbach C, Schmidt A, Lausch A, Zacharias S, Notesco G, Ben-Dor E, Karnieli A (2015) Mapping the spectral soil quality index (SSQI) using airborne imaging spectroscopy. Remote Sens Environ 7(11):15748–15781. https://doi.org/10.3390/rs71115748
Pearlman J, Barry PS, Segal C, Shepanski J, Beiso D, Carman SL (2003) Hyperion, a space-based imaging spectrometer. IEEE Trans Geosci Remote Sens 41(6):1160–1173. https://doi.org/10.1109/TGRS.2003.815018
Pereira HM, Ferrier S, Walters M, Geller GN, Jongman R, Scholes RJ, Bruford MW, Brummitt N, Butchart S, Cardoso A (2013) Essential biodiversity variables. Science 339(6117):277–278. https://doi.org/10.1126/science.1229931
Pignatti S, Acito N, Amato U, Casa R, de Bonis R, Diani M, Laneve G, Matteoli S, Palombo A, Pascucci S, Romano F, Santini F, Simoniello T, Ananasso C, Corsini G, Cuomo V (2013) “The PRISMA Hyperspectral Mission: Science Activities and Opportunities for Agriculture and Land Monitoring,” Proceedings of the International Geoscience and Remote Sensing Symposium (IGARSS’13), Melbourne, Australia, 4 pages https://doi.org/10.1109/igarss.2013.6723850
Rast M (1991) Imaging spectroscopy: fundamentals and considerations for the application of spaceborne systems. ESA SP 1144:144p
Rast M, Bézy JL, Bruzzi S (1999) The ESA medium resolution imaging spectrometer MERIS- review of the instrument and it’s mission. Int J Remote Sens 20(9):1681–1702. https://doi.org/10.1080/014311699212416
Rast M, Baret F, Hurk B, Knorr W, Mauser W, Menenti M, Miller J, Moreno J, Schaepman ME, Verstraete M (2004) SPECTRA-surface processes and ecosystem changes through response analysis ( http://esamultimedia.esa.int/docs/SP_1279_2_SPECTRA.pdf )
Riaño D, Chuvieco E, Ustin S, Zomer R, Dennison P, Roberts D, Salas J (2002) Assessment of vegetation regeneration after fire through multitemporal analysis of AVIRIS images in the Santa Monica Mountains. Remote Sens Environ 79(1):60–71. https://doi.org/10.1016/S0034-4257(01)00239-5
Rickard LJ, Basedow RW, Zalewski EF, Silverglate PR, Landers M (1993) HYDICE: An airborne system for hyperspectral imaging. In: Imaging Spectrometry of the Terrestrial Environment (Vol. 1937, pp. 173-180). International Society for Optics and Photonics. https://doi.org/10.1117/12.157055
Roberts DA, Gardner M, Church R, Ustin S, Scheer G, Green RO (1998) Mapping chaparral in the Santa Monica Mountains using multiple endmember spectral mixture models. Remote Sens Environ 65:267–279. https://doi.org/10.1016/S0034-4257(98)00037-6
Roberts DA, Dennison PE, Gardner ME, Hetzel Y, Ustin SL, Lee CT (2003) Evaluation of the potential of Hyperion for fire danger assessment by comparison to the Airborne Visible/Infrared Imaging Spectrometer. IEEE Trans Geosci Remote Sens 41(6):1297–1310. https://doi.org/10.1109/TGRS.2003.812904
Roberts DA, Quattrochi DA, Hulley GC, Hook SJ, Green RO (2012) Synergies between VSWIR and TIR data for the urban environment: an evaluation of the potential for the hyperspectral infrared imager (hyspiri) decadal survey mission. Remote Sens Environ 15(117):83–101. https://doi.org/10.1016/j.rse.2011.07.021
Rossel RV, Behrens T, Ben-Dor E, Brown D, Demattê J, Shepherd K, Shi Z, Stenberg B, Stevens A, Adamchuk V (2016) A global spectral library to characterize the world’s soil. Earth Sci Rev 155:198–230. https://doi.org/10.1016/j.earscirev.2016.01.012
Sankaran S, Mishra A, Ehsani R, Davis C (2010) A review of advanced techniques for detecting plant diseases. Comput Electron Agric 72(1):1–13. https://doi.org/10.1016/j.compag.2010.02.007
Schaepman ME (2009) Imaging spectrometers. SAGE Handb Remote Sens 18:166
Schaepman ME, Jehle M, Hueni A, D’Odorico P, Damm A, Weyermann J, Schneider FD, Laurent V, Popp C, Seidel FC, Lenhard K (2015) Advanced radiometry measurements and Earth science applications with the airborne prism experiment (APEX). Remote Sens Environ 158:207–219. https://doi.org/10.1016/j.rse.2014.11.014
Schepers S, Blackmer TM, Wilhelm WW, Resende M (1996) Transmittance and reflectance measurements of corn leaves from plants with different nitrogen and water supply. J Plant Physiol 148:523–529. https://doi.org/10.1016/S0176-1617(96)80071-X
Schlerf M, Atzberger C, Hill J, Buddenbaum H, Werner W, Schüler G (2010) Retrieval of chlorophyll and nitrogen in Norway spruce (Picea abies L. Karst.) using imaging spectroscopy. Int J Appl Earth Obs Geoinf 12(1):17–26
Schmidt KS, Skidmore AK (2010) Exploring spectral discrimination of grass species in African rangelands. Int J Remote Sens 22(17):3421–3434. https://doi.org/10.1080/01431160152609245
Schweiger AK, Schütz M, Risch AC, Kneubühler M, Haller R, Schaepman ME (2016) How to predict plant functional types using imaging spectroscopy: linking vegetation community traits, plant functional types and spectral response. Methods Ecol Evolut https://doi.org/10.1111/2041-210X.12642
Serrano L, Ustin SL, Roberts DA, Gamon JA, Peñuelas J (2000) Deriving water content of chaparral vegetation from AVIRIS data. Remote Sens Environ 74(3):570–581. https://doi.org/10.1016/S0034-4257(00)00147-4
Shafri HZM, Hamdan N (2009) Hyperspectral imagery for mapping disease infection in oil palm plantation using vegetation indices and red edge techniques. Am J Appl Sci 6(6):1031–1035
Staenz K, Mueller A, Heiden U (2013) Overview of terrestrial imaging spectroscopy missions. IEEE Int Geosci Remote Sens Symp—IGARSS 2013:3502–3505. https://doi.org/10.1109/IGARSS.2013.6723584
Suárez L, Zarco-Tejada PJ, Berni JA, González-Dugo V, Fereres E (2009) Modelling PRI for water stress detection using radiative transfer models. Remote Sens Environ 113:730–744. https://doi.org/10.1016/j.rse.2008.12.001
Sun J, Xiong X (2011) Solar and lunar observation planning for Earth-observing sensor, Proc SPIE, 8176 https://doi.org/10.1117/12.897751
Swayze GA, Smith K, Clark R, Sutley S, Pearson R, Rust G, Vance J, Hageman P, Briggs P, Meier A, Singleton M, Roth S (2000) Using imaging spectroscopy to map acidic mine waste. Environ Sci Technol 34(1):47–54. https://doi.org/10.1021/es990046w
Swayze GA, Clark RN, Goetz AF, Livo K, Breit G, Sutley S, Kruse F, Snee L, Lowers H, Post J, Stoffregen R, Ashley R (2014) Mapping advanced argillic alteration at Cuprite, Nevada using imaging spectroscopy. Econ Geol 109(5):1179–1221. https://doi.org/10.2113/econgeo.109.5.1179
Thenkabail PS, Smith RB, De Pauw E (2000) Hyperspectral vegetation indices and their relationship with agricultural crop characteristics. Remote Sens Environ 71:158–182. https://doi.org/10.1016/S0034-4257(99)00067-X
Thenkabail PS, Enclona EA, Ashton MS, Van Der Meer B (2004) Accuracy assessments of hyperspectral waveband performance for vegetation analysis applications. Remote Sens Environ 91:354–376. https://doi.org/10.1016/j.rse.2004.03.013
Thome KJ (2001) Absolute radiometric calibration of Landsat 7 ETM + using the reflectance-based method. Remote Sens Environ 78(1–2):27–38. https://doi.org/10.1016/S0034-4257(01)00247-4
Thompson D, Thorpe A, Frankenberg C, Green R, Duren R, Guanter L, Hollstein A, Middleton E, Ong L, Ungar S (2016) Space-based remote imaging spectroscopy of the Aliso Canyon CH4 superemitter. Geophys Res Lett 43(12):6571–6578
Ustin SL, Roberts DA, Jacquemoud S, Pinzón J, Gardner M, Scheer G et al (1998) Estimating canopy water content of chaparral shrubs using optical methods. Remote Sens Environ 65(3):280–291. https://doi.org/10.1016/S0034-4257(98)00038-8
Ustin SL, Roberts DA, Gamon JA, Asner GP, Green RO (2004). “Using imaging spectroscopy to study ecosystem processes and properties.” BioScience 54(6): 523–534. https://doi.org/10.1641/0006-3568(2004)054%5b0523:UISTSE%5d2.0.CO;2
Van der Meer FD, De Jong SM (eds) (2011) Imaging spectrometry: basic principles and prospective applications (Vol. 4). Springer Science & Business Media
Vane G, Goetz AFH (1985) Introduction to the proceedings of the airborne imaging spectrometer (AIS) data analysis workshop, JPL Publication 85–41, Vane G. & Goetz A.F.H. eds. pp 1–21
Vane G, Goetz AF (1988) Terrestrial imaging spectroscopy. Remote Sens Environ 24(1):1–29. https://doi.org/10.1016/0034-4257(88)90003-X
Vane G, Goetz AFH, Wellman JB (1984) Airborne imaging spectrometer: a new tool for remote sensing. IEEE Trans Geosci Remote Sens 6:546–549. https://doi.org/10.1109/TGRS.1984.6499168
Veraverbeke S, Dennison P, Gitas I, Hulley G, Kalashnikova O, Katagis T, Kuai L, Meng R, Roberts D, Stavros N (2018) Hyperspectral remote sensing of fire: state-of-the-art and future perspectives. Remote Sens Environ 216:105–121. https://doi.org/10.1016/j.rse.2018.06.020
West JS, Bravo C, Oberti R, Lemaire D, Moshou D, McCartney HA (2003) The potential of optical canopy measurement for targeted control of field crop diseases. Annu Rev Phytopathol 41:593–614. https://doi.org/10.1146/annurev.phyto.41.121702.103726
Xiong X, Sun J, Fulbright J, Wang Z, Butler JJ (2016) Lunar calibration and performance for S-NPP VIIRS reflective solar bands. IEEE Trans Geosci Remote Sens 54(2):1052–1061. https://doi.org/10.1109/TGRS.2015.2473665
Zarco-Tejada PJ, Miller JR, Mohammed GH, Noland TL, Sampson PH (2001) Vegetation stress detection through chlorophyll a + b estimation and fluorescence effects on hyperspectral imagery. J Environ Qual 31(5):1433–1441. https://doi.org/10.2134/jeq2002.1433
Zimmermann G, Neumann A (2000) The imaging spectrometer experiment mos on ipr-p3-three years of experience. J Spacecr Technol 10(1):1–9
Acknowledgements
The paper is an outcome of a Workshop on Requirements, capabilities, and directions in Spaceborne Imaging Spectroscopy held at the International Space Science Institute (ISSI) in Bern, Switzerland, in November 2016. Part of this work was performed at the Jet Propulsion Laboratory, California Institute of Technology, under contract with NASA. The authors acknowledge the support of J. Adams (ESA-ESRIN), U. del Bello (ESA-ESTEC), C. Giardino (IREA-CNR), R.O. Green (JPL), L. Guanter (GFZ), S. Förster (GFZ), and C. Mielke (GFZ).
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Rast, M., Painter, T.H. Earth Observation Imaging Spectroscopy for Terrestrial Systems: An Overview of Its History, Techniques, and Applications of Its Missions. Surv Geophys 40, 303–331 (2019). https://doi.org/10.1007/s10712-019-09517-z
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10712-019-09517-z