Abstract
Imaging spectroscopy (IS), also commonly known as hyperspectral remote sensing, is a powerful remote sensing technique for the monitoring of the Earth’s surface and atmosphere. Pixels in optical hyperspectral images consist of continuous reflectance spectra formed by hundreds of narrow spectral channels, allowing an accurate representation of the surface composition through spectroscopic techniques. However, technical constraints in the definition of imaging spectrometers make spectral coverage and resolution to be usually traded by spatial resolution and swath width, as opposed to optical multispectral (MS) systems typically designed to maximize spatial and/or temporal resolution. This complementarity suggests that a synergistic exploitation of spaceborne IS and MS data would be an optimal way to fulfill those remote sensing applications requiring not only high spatial and temporal resolution data, but also rich spectral information. On the other hand, IS has been shown to yield a strong synergistic potential with non-optical remote sensing methods, such as thermal infrared (TIR) and light detection and ranging (LiDAR). In this contribution we review theoretical and methodological aspects of potential synergies between optical IS and other remote sensing techniques. The focus is put on the evaluation of synergies between spaceborne optical IS and MS systems because of the expected availability of the two types of data in the next years. Short reviews of potential synergies of IS with TIR and LiDAR measurements are also provided.
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Abdalati W, Zwally HJ, Bindschadler R, Csatho B, Farrell SL, Fricker HA, Harding D, Kwok R, Lefsky M, Markus T, Marshak A, Neumann T, Palm S, Schutz B, Smith B, Spinhirne J, Webb C (2010) The ICESat-2 laser altimetry mission. Proc IEEE 98(5):735–751
Anderson M, Kustas W (2008) Thermal remote sensing of drought and evapotranspiration. EOS Trans Am Geophys Union 89(26):233–234
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 124(Supplement C):454–465
Asner GP, Brodrick PG, Anderson CB, Vaughn N, Knapp DE, Martin RE (2016) Progressive forest canopy water loss during the 2012–2015 California drought. Proc Natl Acad Sci 113(2):E249–E255
Barnsley MJ, Settle JJ, Cutter M, Lobb D, Teston F (2004) The PROBA/CHRIS mission: a low-cost smallsat for hyperspectral, multi-angle, observations of the Earth surface and atmosphere. IEEE Trans Geosci Remote Sens 42:1512–1520
Bishop CA, Liu JG, Mason PJ (2011) Hyperspectral remote sensing for mineral exploration in Pulang, Yunnan Province, China. Int J Remote Sens 32(9):2409–2426
Botha EJ, Brando VE, Anstee JM, Dekker AG, Sagar S (2013) Increased spectral resolution enhances coral detection under varying water conditions. Remote Sens Environ 131(Supplement C):247–261
Brell M, Rogass C, Segl K, Bookhagen B, Guanter L (2016) Improving sensor fusion: a parametric method for the geometric coalignment of airborne hyperspectral and lidar data. IEEE Trans Geosci Remote Sens 54(6):3460–3474
Brell M, Segl K, Guanter L, Bookhagen B (2017) Hyperspectral and lidar intensity data fusion: a framework for the rigorous correction of illumination, anisotropic effects, and cross calibration. IEEE Trans Geosci Remote Sens 55(5):2799–2810
Bresciani M, Stroppiana D, Odermatt D, Morabito G, Giardino C (2011) Assessing remotely sensed chlorophyll-a for the implementation of the water framework directive in European perialpine lakes. Sci Total Environ 409(17):3083–3091
Bresciani M, Bolpagni R, Braga F, Oggioni A, Giardino C (2012) Retrospective assessment of macrophytic communities in southern Lake Garda (Italy) from in situ and mivis (multispectral infrared and visible imaging spectrometer) data. J Limnol 71(1):19
Bush A, Sollmann R, Wilting A et al (2017) Connecting Earth observation to high-throughput biodiversity data. Nat Ecol Evol 1:0176
Calvin WMF, Littlefield E, Kratt C (2015) Remote sensing of geothermal-related minerals for resource exploration in Nevada. Geothermics 53:517–526
Candela L, Formaro R, Guarini R, Loizzo R, Longo F, Varacalli G (2016) The PRISMA mission. In: 2016 IEEE international geoscience and remote sensing symposium (IGARSS), pp 253–256
Casal G, Kutser T, Domínguez-Gómez J, Sánchez-Carnero N, Freire J (2011) Mapping benthic macroalgal communities in the coastal zone using CHRIS-PROBA mode 2 images. Estuar Coast Shelf Sci 94(3):281–290
Chan JC-W, Yokoya N (2016) Mapping land covers of Brussels capital region using spatially enhanced hyperspectral images. In: WHISPERS 2016, pp 1–5. IEEE Xplore
Chan JC-W, Paelinckx D (2008) Evaluation of random forest and adaboost tree-based ensemble classification and spectral band selection for ecotope mapping using airborne hyperspectral imagery. Remote Sens Environ 112(6):2999–3011
Chan JCW, Ma J, de Voorde TV, Canters F (2011) Preliminary results of superresolution-enhanced angular hyperspectral (CHRIS/PROBA) images for land-cover classification. IEEE Geosci Remote Sens Lett 8(6):1011–1015
Chavez W Jr (2000) Supergene oxidation of copper deposits: zoning and distribution of copper oxide minerals. SEG Newsl 41:9–21
Chen Z, Pu H, Wang B, Jiang GM (2014) Fusion of hyperspectral and multispectral images: a novel framework based on generalization of pan-sharpening methods. IEEE Geosci Remote Sens Lett 11(8):1418–1422
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):5131
Dabbiru L, Samiappan S, Nobrega RAA, Aanstoos JA, Younan NH, Moorhead RJ (2015) Fusion of synthetic aperture radar and hyperspectral imagery to detect impacts of oil spill in gulf of mexico. In: 2015 IEEE international geoscience and remote sensing symposium (IGARSS), pp 1901–1904
Danson FM, Hetherington D, Morsdorf F, Koetz B, Allgower B (2007) Forest canopy gap fraction from terrestrial laser scanning. IEEE Geosci Remote Sens Lett 4(1):157–160
Dekker AG, Brando VE, Anstee JM (2005) Retrospective seagrass change detection in a shallow coastal tidal Australian lake. Remote Sens Environ 97(4):415–433
Dekker AG, Phinn SR, Anstee J, Bissett P, Brando VE, Casey B, Fearns P, Hedley J, Klonowski W, Lee ZP, Lynch M, Lyons M, Mobley C, Roelfsema C (2011) Intercomparison of shallow water bathymetry, hydro-optics, and benthos mapping techniques in Australian and caribbean coastal environments. Limnol Oceanogr Methods 9(9):396–425
Demarchi L, Chan JC-W, Ma J, Canters F (2012) Mapping impervious surfaces from superresolution enhanced CHRIS/PROBA imagery using multiple endmember unmixing. ISPRS J Photogramm Remote Sens 72(Supplement C):99–112
Dierssen H, Mcmanus G, Chlus A, Qiu D, Gao B-C, Lin S (2015) Space station image captures a red tide ciliate bloom at high spectral and spatial resolution. Proc Natl Acad Sci USA 112:14783–14787
Drusch M, Bello UD, Carlier S, Colin O, Fernandez V, Gascon F, Hoersch B, Isola C, Laberinti P, Martimort P, Meygret A, Spoto F, Sy O, Marchese F, Bargellini P (2012) Sentinel-2: ESA’s optical high-resolution mission for GMES operational services. Remote Sens Environ 120:25–36
Drusch M, Moreno J, Bello UD, Franco R, Goulas Y, Huth A, Kraft S, Middleton EM, Miglietta F, Mohammed G, Nedbal L, Rascher U, Schüttemeyer D, Verhoef W (2017) The fluorescence explorer mission concept—ESA’s Earth explorer 8. IEEE Trans Geosci Remote Sens 55(3):1273–1284
Ehret G, Bousquet P, Pierangelo C, Alpers M, Millet B, Abshire JB, Bovensmann H, Burrows JP, Chevallier F, Ciais P, Crevoisier C, Fix A, Flamant P, Frankenberg C, Gibert F, Heim B, Heimann M, Houweling S, Hubberten HW, Jöckel P, Law K, Löw A, Marshall J, Agusti-Panareda A, Payan S, Prigent C, Rairoux P, Sachs T, Scholze M, Wirth M (2017) Merlin: a French–German space lidar mission dedicated to atmospheric methane. Remote Sens 9(10):1052
Eisele A, Chabrillat S, Hecker C, Hewson R, Lau IC, Rogass C, Segl K, Cudahy TJ, Udelhoven T, Hostert P, Kaufmann H (2015) Advantages using the thermal infrared (TIR) to detect and quantify semi-arid soil properties. Remote Sens Environ 163(Supplement C):296–311
Eysn L, Pfeifer N, Ressl C, Hollaus M, Grafl A, Morsdorf F (2013) A practical approach for extracting tree models in forest environments based on equirectangular projections of terrestrial laser scans. Remote Sens 5(11):5424–5448
Féret JB, Gitelson AA, Noble SD et al (2017) PROSPECT-D: towards modeling leaf optical properties through a complete lifecycle. Remote Sens Environ 193:204–215
Foody GM (2002) Status of land cover classification accuracy assessment. Remote Sens Environ 80(1):185–201
Garcia RA, Fearns PR, McKinna LI (2014) Detecting trend and seasonal changes in bathymetry derived from hico imagery: a case study of Shark Bay, western Australia. Remote Sens Environ 147(Supplement C):186–205
Giardino C, Brando VE, Dekker AG, Strömbeck N, Candiani G (2007) Assessment of water quality in Lake Garda (Italy) using hyperion. Remote Sens Environ 109(2):183–195
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 AFH, Vane G, Salomon JE, Rock BN (1985) Imaging spectroscopy for Earth remote sensing. Science 228:1147–1153
Gómez-Dans J, Lewis P, Disney M (2016) Efficient emulation of radiative transfer codes using Gaussian processes and application to land surface parameter inferences. Remote Sens 8(2):119
Green RO, Eastwood M, Sarture C, Chrien T, Aronsson M, Chippendale B, Faust J, Pavri B, Chovit C, Solis M, Olah M, Williams O (1998) Imaging spectroscopy and the airborne visible/infrared imaging spectrometer (AVIRIS). Remote Sens Environ 65:227–248
Grohnfeldt C, Zhu XX, Bamler R (2013) Jointly sparse fusion of hyperspectral and multispectral imagery. In: 2013 IEEE international geoscience and remote sensing symposium—IGARSS, pp 4090–4093
Guanter L, Kaufmann H, Segl K, Foerster S, Rogass C, Chabrillat S, Kuester 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
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(3):304–319
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(Supplement C):181–195
Hilker T, Coops NC, Hall FG, Black TA, Wulder MA, Nesic Z, Krishnan P (2008) Separating physiologically and directionally induced changes in PRI using BRDF models. Remote Sens Environ 112(6):2777–2788
Hu J, Mou L, Schmitt A, Zhu XX (2017) Fusionet: a two-stream convolutional neural network for urban scene classification using polsar and hyperspectral data. In: 2017 Joint urban remote sensing event (JURSE), pp 1–4
Hubbard B, Crowley JK (2005) Mineral mapping on the Chilean–Bolivian altiplano using co-orbital ali, aster and hyperion imagery: data dimensionality issues and solutions. Remote Sens Environ 99:173–186
Hubbard BE, Crowley JK, Zimbelman DR (2003) Comparative alteration mineral mapping using visible to shortwave infrared (0.4–2.4 mu m) hyperion, ali, and aster imagery. IEEE Trans Geosci Remote Sens 41(6):1401–1410
Junttila S, Kaasalainen S, Vastaranta M, Hakala T, Nevalainen O, Holopainen M (2015) Investigating bi-temporal hyperspectral lidar measurements from declined trees-experiences from laboratory test. Remote Sens 7(10):13863–13877
Koetz B, Sun G, Morsdorf F, Ranson K, Kneubühler M, Itten K, Allgöwer B (2007) Fusion of imaging spectrometer and lidar data over combined radiative transfer models for forest canopy characterization. Remote Sens Environ 106(4):449–459
Koetz B, Morsdorf F, van der Linden S, Curt T, Allgöwer B (2008) Multi-source land cover classification for forest fire management based on imaging spectrometry and lidar data. For Ecol Manag 256(3):263–271. Impacts of forest ecosystem management on greenhouse gas budgets
Kutser T (2004) Quantitative detection of chlorophyll in cyanobacterial blooms by satellite remote sensing. Limnol Oceanogr 49(6):2179–2189
Lanaras C, Baltsavias E, Schindler K (2015) Hyperspectral super-resolution by coupled spectral unmixing. In: The IEEE international conference on computer vision (ICCV)
Lee CM, Cable ML, Hook SJ, Green RO, Ustin SL, Mandl DJ, Middleton EM (2015) An introduction to the NASA hyperspectral infrared imager (hyspiri) mission and preparatory activities. Remote Sens Environ 167(Supplement C):6–19
Lewis P, Gómez-Dans J, Kaminski T, Settle J, Quaife T, Gobron N, Styles J, Berger M (2012) An Earth observation land data assimilation system (EO-LDAS). Remote Sens Environ 120:219–235
Lucke RL, Corson M, McGlothlin NR, Butcher SD, Wood DL, Korwan DR, Li RR, Snyder WA, Davis CO, Chen DT (2011) Hyperspectral imager for the coastal ocean: instrument description and first images. Appl Opt 50(11):1501–1516
Matheson DS, Dennison PE (2012) Evaluating the effects of spatial resolution on hyperspectral fire detection and temperature retrieval. Remote Sens Environ 124(Supplement C):780–792
Mielke C, Boesche NK, Rogass C, Kaufmann H, Gauert C, de Wit M (2014a) Spaceborne mine waste mineralogy monitoring in South Africa, applications for modern push-broom missions: hyperion/OLI and EnMAP/Sentinel-2. Remote Sens 6(8):6790–6816
Mielke CK, Boesche N, Rogaß C, Segl K, Gauert C, Kaufmann H (2014b) Potential applications of the Sentinel-2 multispectral sensor and the EnMAP hyperspectral sensor in mineral exploration. In: EARSeL eProceedings, vol 13, p 93
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
Milewski R, Chabrillat S, Behling R (2017) Analyses of recent sediment surface dynamic of a Namibian Kalahari salt pan based on multitemporal landsat and hyperspectral hyperion data. Remote Sens 9(2):170
Mishra D, Ogashawara I, Gitelson A (2017) Bio-optical modeling and remote sensing of inland waters. Elsevier, Amsterdam, p 332
Morsdorf F, Nichol C, Malthus T, Woodhouse IH (2009) Assessing forest structural and physiological information content of multi-spectral lidar waveforms by radiative transfer modelling. Remote Sens Environ 113(10):2152–2163
Mouw CB, Greb S, Aurin D, DiGiacomo PM, Lee Z, Twardowski M, Binding C, Hu C, Ma R, Moore T, Moses W, Craig SE (2015) Aquatic color radiometry remote sensing of coastal and inland waters: challenges and recommendations for future satellite missions. Remote Sens Environ 160(Supplement C):15–30
Olmanson LG, Bauer ME, Brezonik PL (2008) A 20-year landsat water clarity census of minnesota’s 10,000 lakes. Remote Sens Environ 112(11):4086–4097
Palmer SC, Kutser T, Hunter PD (2015) Remote sensing of inland waters: challenges, progress and future directions. Remote Sens Environ 157(Supplement C):1–8
Palsson F, Sveinsson JR, Ulfarsson MO, Benediktsson JA (2016) Quantitative quality evaluation of pansharpened imagery: consistency versus synthesis. IEEE Trans Geosci Remote Sens 54(3):1247–1259
Phinn S, Roelfsema C, Dekker A, Brando V, Anstee J (2008) Mapping seagrass species, cover and biomass in shallow waters: an assessment of satellite multi-spectral and airborne hyper-spectral imaging systems in moreton bay (Australia). Remote Sens Environ 112(8):3413–3425
Rainforth T, Wood F (2015) Canonical correlation forests. ArXiv e-prints
Ribeiro da Luz B, Crowley JK (2007) Spectral reflectance and emissivity features of broad leaf plants: prospects for remote sensing in the thermal infrared (8.0–14.0 μm). Remote Sens Environ 109(4):393–405
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 117(Supplement C):83–101
Rodriguez JJ, Kuncheva LI, Alonso CJ (2006) Rotation forest: a new classifier ensemble method. IEEE Trans Pattern Anal Mach Intell 28(10):1619–1630
Roy D, Wulder M, Loveland T, Woodcock CE, Allen R, Anderson M, Helder D, Irons J, Johnson D, Kennedy R, Scambos T, Schaaf C, Schott J, Sheng Y, Vermote E, Belward A, Bindschadler R, Cohen W, Gao F, Hipple J, Hostert P, Huntington J, Justice C, Kilic A, Kovalskyy V, Lee Z, Lymburner L, Masek J, McCorkel J, Shuai Y, Trezza R, Vogelmann J, Wynne R, Zhu Z (2014) Landsat-8: science and product vision for terrestrial global change research. Remote Sens Environ 145:154–172
Schmid T, Koch M, Gumuzzio J (2005) Multisensor approach to determine changes of wetland characteristics in semiarid environments (central Spain). IEEE Trans Geosci Remote Sens 43(11):2516–2525
Schneider FD, Morsdorf F, Schmid B, Petchey OL, Hueni A, Schimel DS, Schaepman ME (2017) Mapping functional diversity from remotely sensed morphological and physiological forest traits. Nat Commun 8:1441
Segl K, Guanter L, Rogass C, Kuester T, Roessner S, Kaufmann H, Sang B, Mogulsky V, Hofer S (2012) Eetes—the enmap end-to-end simulation tool. IEEE J Sel Top Appl Earth Obs Remote Sens 5(2):522–530
Segl K, Guanter L, Gascon F, Kuester T, Rogass C, Mielke C (2015) S2etes: an end-to-end modeling tool for the simulation of Sentinel-2 image products. IEEE Trans Geosci Remote Sens 53(10):5560–5571
Selva M, Aiazzi B, Butera F, Chiarantini L, Baronti S (2015) Hyper-sharpening: a first approach on SIM-GA data. IEEE J Sel Top Appl Earth Obs Remote Sens 8(6):3008–3024
Stavros EN, Schimel D, Pavlick R, Serbin S, Swann A, Duncanson L, Fisher JB, Fassnacht F, Ustin S, Dubayah R, Schweiger A, Wennberg P (2017) ISS observations offer insights into plant function. Nat Ecol Evol 1:0194
Strong AE (1974) Remote sensing of algal blooms by aircraft and satellite in Lake Erie and Utah Lake. Remote Sens Environ 3(2):99–107
Taylor R (2011) Gossans and leached cappings—field assessment. Springer, Berlin, p 146
Thompson DR, Boardman JW, Eastwood ML, Green RO (2017) A large airborne survey of earth’s visible-infrared spectral dimensionality. Opt Express 25(8):9186–9195
Torabzadeh H, Morsdorf F, Leiterer R, Schaepman M (2014a) Fusing imaging spectrometry and airborne laser scanning data for tree species discrimination. In: Geoscience and remote sensing symposium (IGARSS), 2014 IEEE international, pp 1253–1256
Torabzadeh H, Morsdorf F, Schaepman ME (2014b) Fusion of imaging spectroscopy and airborne laser scanning data for characterization of forest ecosystems—a review. ISPRS J Photogramm Remote Sens 97(Supplement C):25–35
Treuhaft RN, Asner GP, Law BE, Van Tuyl S (2002) Forest leaf area density profiles from the quantitative fusion of radar and hyperspectral data. J Geophys Res Atmos 107(D21):ACL 7-1–ACL 7-13
Tyler AN, Hunter PD, Spyrakos E, Groom S, Constantinescu AM, Kitchen J (2016) Developments in earth observation for the assessment and monitoring of inland, transitional, coastal and shelf-sea waters. Sci Total Environ 572(Supplement C):1307–1321
Ungar SG, Pearlman JS, Mendenhall JA, Reuter D (2003) Overview of the Earth Observing One (EO-1) mission. IEEE Trans Geosci Remote Sens 41:1149–1159
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
van der Meer FD, van der Werff HM, van Ruitenbeek FJ, Hecker CA, Bakker WH, Noomen MF, van der Meijde M, Carranza EJM, de Smeth JB, Woldai T (2012) Multi- and hyperspectral geologic remote sensing: a review. Int J Appl Earth Obs Geoinf 14(1):112–128
Veraverbeke S, Hook S, Harris S (2012) Synergy of vswir (0.4–2.5 μm) and MTIR (3.5–12.5 μm) data for post-fire assessments. Remote Sens Environ 124(Supplement C):771–779
Verhoef W (1984) Light scattering by leaf layers with application to canopy reflectance modeling: the SAIL model. Remote Sens Environ 16(2):125–141
Vermote EF, Tanre D, Deuze J-L, Herman M, Morcette J-J (1997) Second simulation of the satellite signal in the solar spectrum, 6S: an overview. IEEE Trans Geosci Remote Sens Publ IEEE Geosci Remote Sens Soc 35(3):675–686
Wei Q, Dobigeon N, Tourneret JY (2015) Bayesian fusion of multi-band images. IEEE J Sel Top Signal Process 9(6):1117–1127
Woodhouse IH, Nichol C, Sinclair P, Jack J, Morsdorf F, Malthus TJ, Patenaude G (2011) A multispectral canopy lidar demonstrator project. IEEE Geosci Remote Sens Lett 8(5):839–843
Xu B, Gong P (2007) Land-use/land-cover classification with multispectral and hyperspectral EO-1 data. Photogramm Eng Remote Sens 73:955–965
Yokoya N, Yairi T, Iwasaki A (2012) Coupled nonnegative matrix factorization unmixing for hyperspectral and multispectral data fusion. IEEE Trans Geosci Remote Sens 50(2):528–537
Yokoya N, Chan JC-W, Segl K (2016) Potential of resolution-enhanced hyperspectral data for mineral mapping using simulated enmap and Sentinel-2 images. Remote Sens 8(3):172
Yokoya N, Grohnfeldt C, Chanussot J (2017) Hyperspectral and multispectral data fusion: a comparative review of the recent literature. IEEE Geosci Remote Sens Mag 5(2):29–56
Zilioli E, Brivio P, Gomarasca M (1994) A correlation between optical properties from satellite data and some indicators of eutrophication in Lake Garda (Italy). Sci Total Environ 158(Supplement C):127–133
Zwally H, Schutz B, Abdalati W, Abshire J, Bentley C, Brenner A, Bufton J, Dezio J, Hancock D, Harding D, Herring T, Minster B, Quinn K, Palm S, Spinhirne J, Thomas R (2002) Icesat’s laser measurements of polar ice, atmosphere, ocean, and land. J Geodyn 34(3):405–445
Acknowledgements
This 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. LG, KS, MB and CM were partly funded by the EnMAP scientific preparation program (FKZ: 50EE1617).
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Guanter, L., Brell, M., Chan, J.CW. et al. Synergies of Spaceborne Imaging Spectroscopy with Other Remote Sensing Approaches. Surv Geophys 40, 657–687 (2019). https://doi.org/10.1007/s10712-018-9485-z
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DOI: https://doi.org/10.1007/s10712-018-9485-z